Discrete Dynamic Modeling for Complex Systems Based on Big DataView this Special Issue
Construction of Graduate Behavior Dynamic Model Based on Dynamic Decision Tree Algorithm
With the research of machine learning technology and big data intelligent processing technology in engineering application becoming more and more mature, people gradually combine machine learning technology and big data intelligent processing technology. Aiming at the problem of innovative employment in colleges and universities, this paper proposes a dynamic decision tree algorithm based on these two technologies and constructs a dynamic model of graduates’ behavior. Through the analysis of dynamic decision tree algorithm, a big data analysis system is formed. Finally, simulation experiments verify whether the dynamic model can correctly reflect the behavior of college graduates. The results show that the big data integration system based on big data and dynamic decision tree algorithm has high adaptability. Incremental adaptive optimization of the traditional decision tree model can significantly improve the prediction effect and prediction time of dynamic data and provide theoretical support for the industrialization and social significance of big data technology. The dynamic decision tree algorithm of college employment proposed in this paper has good predictability and provides a certain theoretical reference for college graduates’ entrepreneurship.
Big data usually refers to the data with huge volume of information in the three dimensions of “data volume,” “data speed,” and “data category.” People call it big data technology to get some quantitative statistical results through big data analysis, which mainly relies on the internal logic of various specific rules. Among them, machine learning is an effective method to realize this analysis method . Every year, the graduation of college students injects a lot of productivity into the society. Their behavior after graduation is the focus of all sectors of society. At present, most of the graduate behavior analysis still adopts the questionnaire method . Although the statistical results of the questionnaire survey method are easy to quantify, the statistics, processing, and analysis of the survey results can be completed more quickly and economically . However, due to the subjective changes and differences in the intention, thinking, and motivation of the respondents in the questionnaire survey for employment and entrepreneurship, the quality of the survey results is often not guaranteed, and its recovery rate is difficult to be guaranteed, resulting in a great reduction in the accuracy of the data analysis results . This makes the dynamic model of graduates’ whereabouts constructed by questionnaire has some limitations. As the data set of graduates’ graduation behavior is changing day by day and its internal inaccessible nodes are increasing, the predictability of the traditional model to each node is not high, which often leads to the quantitative change of the prediction distortion of each node, resulting in the qualitative change of the overall prediction result error. Therefore, it is necessary to study the dynamic model of graduates’ employment and entrepreneurship data . Based on this, this study proposes a dynamic model construction method based on big data and machine learning decision tree.
Decision tree is a tree structure similar to flow chart, in which each internal node represents a test on an attribute, each branch represents an attribute output, and each leaf node represents a class or class distribution. The top layer of the tree is the root node. The amount of information is directly related to its uncertainty. To understand a very, very uncertain thing or something we know nothing about, we need to know a lot of information, and the measurement of the amount of information is equal to the amount of uncertainty. Decision tree machine learning method is an effective method to simulate human learning behavior. Its core problem is how to construct the tree topology based on the known training sample data. Since machine learning is a problem closely related to the problem domain, different application goals will lead to more specific and in-depth topics that cannot be solved or well solved by the existing theoretical framework.
Aiming at the problem that colleges and universities cannot carry out dynamic analysis on graduates’ employment and entrepreneurship destination statistics, a big data integrated analysis system based on dynamic decision tree machine learning algorithm is proposed to solve the problem of dynamic analysis and statistics of graduates’ destination data. This study is mainly carried out in four chapters. Section 1 gives a framework overview of the research background and research direction of this study; Section 2 introduces the application status of big data analysis technology and its application scope not covered at present. Section 3 introduces the big data technology, machine learning algorithm, the establishment of dynamic decision tree model, and the construction of big data integration system. Section 4 uses the established decision tree model based on machine learning algorithm to practice a large amount of sample data through public data sets and designs confirmatory experiments to verify whether the optimized decision tree model can accurately predict the postgraduation behavior of college graduates.
The innovation of this study is to solve the problem of statistics and analysis of employment and entrepreneurship dynamics of college graduates through big data analysis technology. This study combines the big data of graduates’ behavior after graduation with machine learning algorithm. Aiming at the problem that graduates’ behavior data changes year by year, a dynamic decision tree model is proposed based on machine learning algorithm. Even if the data sample changes, it can still get a high prediction accuracy without rebuilding the new model, which solves the problem of low energy efficiency when the traditional model analyzes dynamic data. The effective application of the algorithm can greatly improve the model structure of each branch of the decision tree and then improve the efficiency of retrieving dynamic data.
2. Related Work
Although researchers have studied the complex system strategy based on big data for many years, there are still some deficiencies in the construction scenario of big data dynamic model . Elsayad et al. proposed to use whale optimization algorithm under the background of big data of college graduates and carry out algorithm loading through machine learning H2O framework to find the best feature subset, so as to maximize the prediction accuracy of employment of college graduates . Through experiments, Dommaraju et al. have proved that using the multilayer perceptron deep neural network learning technology based on expectation condition maximization clustering and Ruzicka regression to analyze the big data of cellular network can provide theoretical support for the intelligent suggestions on employment and entrepreneurship of college graduates . Yahia et al. proposed to transform the common feature data in big data technology into the deep feature data filtered by the feature selector and, combined with the hybrid machine learning algorithm, analyzed the incentive elements of the whereabouts of college graduates. This method shows that business trip practice is the main incentive to determine the behavior of graduates and achieves an accuracy rate of more than 95% . With the help of random forest algorithm, Gui et al. overcome the shortcomings of overfitting algorithm by using the weather conditions, flight time, airport location, and other employment registration information of college graduates, so as to improve the accuracy of prediction and analysis of college graduates in employment to more than 90% . Latif et al. analyzed the big data according to 70 attributes that may affect the delayed graduation of college graduates and obtained the prediction accuracy of delayed graduation events greater than 98% based on convolutional neural network (CNN) algorithm. Based on this result, it has good social significance for college graduates to change their strategies according to the current learning situation and improve their school efficiency . Dijk et al. proposed to establish the largest information database for college graduates, which aims to use big data technology to predict the whereabouts of college graduates, so as to improve the statistical efficiency of the whereabouts of graduates . Xiao et al. analyzed the data of the ship automatic identification system by using adaptive learning, motion modeling, and particle filter technology through big data acquisition and aiming at the direction of intelligent maritime traffic and carried out the collision risk assessment of ship navigation dynamic trajectory. They found that big data analysis technology has a good effect in processing dynamic data analysis . Liu et al. verified the effectiveness of the cooperative spectrum sensing network based on the two terminal machine learning models for the intelligent spectrum sensing method by detecting the probability simulation method. It realized the diversified statistics of employment and entrepreneurship of college graduates, but could not achieve dynamic real-time analysis . Through the particle swarm optimization algorithm, Nogueira et al. generate a large data set of dynamic feasible solutions and obtain the optimal solution based on big data, so as to establish a probability confidence region, find the optimal conditions for analyzing graduates’ employment and entrepreneurship choices, and realize the dynamic analysis of equipment status based on big data technology . Fnyes et al. put forward the theory of using machine learning linear parameter change control to analyze big data, obtained a highly robust vehicle selection function for college graduates to check in and take a ride, and verified its effectiveness through simulation. This method can intelligently analyze the choice of graduates’ whereabouts, but can not carry out high accuracy analysis and statistics on dynamic data .
To sum up, it can be seen that, in the process of dynamic statistics and analysis of employment and entrepreneurship of college graduates, there are some problems, such as inability to effectively obtain real-time data of graduates, large error of analysis model, small database of graduates’ statistical information, and poor coupling of analysis model [17, 18]. In terms of the research on the dynamic model of employment and ntrepreneurship of college graduates, the current research results are mostly implemented based on statistics, but rarely combined with big data technology and artificial intelligence algorithms for diversified and convenient analysis [19–21]. On the other hand, big data analysis technology is mostly coupled with traditional engineering and less combined with science education. In terms of algorithm structure, most machine learning algorithms only perform fini calculation for static data, and few dynamic algorithm models are designed for complex dynamic discrete data . Therefore, under the background of big data in today’s era, it is of great significance to carry out the research on the dynamic model of employment and entrepreneurship of college graduates.
3. Dynamic Model Construction Method Based on Big Data and Dynamic Decision Tree Algorithm
3.1. Application of Machine Learning Algorithm in Digital Model Construction
Machine learning algorithm is a subject that can optimize computer algorithm by improving the previous data. The three main elements of machine learning are “algorithm,” “strategy,” and “model,” in which “algorithm” fits the training data set through “strategy,” so as to create a new “model,” which makes the algorithm very important in machine learning . Common machine learning algorithms are usually trained only for fixed data sets. Once the data sets change, the algorithm will rescan all the data sets, which makes the algorithm inefficient in solving dynamic big data . In fact, in solving practical engineering problems, big data with dynamic attributes are often used as training data sets . In recent years, with the deepening of the special work of Higher Vocational enrollment expansion by the Ministry of Education, the Ministry of Human Resources and Social Security, and other departments, the number of college graduates in China has increased from 2.8 million per year in 2004 to an estimated 9 million in 2021. According to the regularity and uncertainty of social development every year, the data of employment and entrepreneurship of college graduates also show dynamic changes.
Based on this, in order to solve the lag analysis problem in graduates’ employment and entrepreneurship data, this study improves the traditional decision tree algorithm for static data and proposes a big data integration system based on dynamic decision tree algorithm, so as to build a new dynamic model in the complex discrete data of graduates’ employment and entrepreneurship changing year by year.
3.2. Data Analysis Process of Machine Learning Dynamic Decision Tree Algorithm in Dynamic Model
The traditional decision tree algorithm selects the optimal subnode by calculating the information gain of different attributes. For the uncertainty of college graduates’ employment and entrepreneurship, this study extends a decision tree algorithm with dynamic incremental solution based on the traditional decision tree algorithm, reprocesses the discrete data at all levels in the dynamic model structure, and extracts the rules of each node. The process of dynamic decision tree data analysis is shown in Figure 1.
As can be seen from Figure 1, the relationship between the decision tree analysis data is based on information entropy. Under the influence of dynamic data, when the change of a child node of the decision tree reaches the threshold, the child node becomes invalid, so it is automatically replaced with another child node. When the dynamic data does not touch the threshold, it means that the subnodes of the decision tree are probabilistic classified based on the node attributes.
Make a subnode of the decision tree algorithm model have two attributes to be selected: A and B. If is found after calculating the information gain of a and B, that is, in terms of subnodes of the decision tree, the decision of attribute a is better than attribute B. When the data is dynamically incremented, if the current decision tree branch node subpoint has and only has two attributes a and B, then and are used to represent the entropy of attributes a and B, respectively, and then there will bewhere represents the number of positive examples with a certain attribute value record set, represents the number of counterexamples with the same attribute value record set, and their number count is expressed in , represents the amount of information estimated based on the overall data source, and and are the possibility of positive examples and the possibility of counterexamples, respectively. At this time, the method of calculating information entropy is as follows:where
In the formula, and represent the values of the branch subnodes of a decision tree. The value includes the number of values of the node attribute, and the bottom of is 2. When the dynamic incremental data is introduced into the decision tree, the information gain of attributes A and B will change accordingly. This change may lead to the final change of the node classification attribute under some columns of complex discrete calculations. When the dynamic incremental data with attribute appears in a value segment and the value segment is between A and B, the method for calculating information entropy is as follows:where
After transforming the deformation formula,
After calculation, when the dynamic incremental information is added to the training data set, the change of information entropy before and after is
In order to evaluate the impact of dynamic incremental information on attributes A and B, it is necessary to calculate the maximum and minimum values of information entropy before and after the emergence of dynamic incremental information. According to the characteristics of functions and , when , takes the minimum value:
When , takes the maximum value:
3.3. Analysis Process of Machine Learning Dynamic Decision Tree Algorithm in Dynamic Model
When the new dynamic data increment is added to the data set, instead of rescanning all the data and building a new model, adaptive correction is carried out on the basis of the model obtained from the previous training data by the decision tree algorithm, so as to improve the classification accuracy of the new decision tree. If samples are dynamically added to a branch subnode of a decision tree of the previously constructed data model, the newly added samples will meet the following inequalities according to the previous classification attributes:
If the number of newly added samples is less than the number of samples data on the attribute value segment, (10) can be scaled as
To sum up, the value of determines the number of new samples :
Taking (13) as a guide, the refitting method of dynamic decision tree can be obtained. If the dynamically added data samples meet , after the data is dynamically added and updated, the entropy of the classification attribute is still less than that of the substitute attribute. In other words, the information gain calculated based on the classification attribute will still be greater than that calculated based on the substitute attribute. Therefore, the subnode classification attributes of the decision tree model remain unchanged compared with the previous classification attributes. If the number of samples x meets , the corresponding entropy of the classification attribute will become greater than that of the substitute attribute after the dynamic new data appears. At this time, the dynamic decision tree algorithm will replace the original classification attribute of the branch subnode of the decision tree with the substitute attribute, so as to update the dynamic decision tree.
3.4. Prototype Construction of Machine Learning Dynamic Decision Tree Algorithm Fusion Big Data Integration System
The machine learning dynamic decision tree algorithm fusion big data integration system needs to run in real time to complete the analysis task. Users can quantify the performance of big data according to the output behavior of discrete data dynamic fusion in the system process. The big data system designed in this research mainly includes three modules: import module, management module, and analysis module. The analysis process of graduate employment data by big data system is shown in Figure 2.
After data loading, the big data system imports the extracted data into the database of the management module to meet the data analysis of graduates’ employment and entrepreneurship. The data is listed according to the data name, data type, and data length compiled by the database type, and the management module has the functions of adding, deleting, and modifying the imported data. The analysis module mainly integrates the algorithm of dynamic decision tree, which belongs to an enhanced decision tree algorithm. The underlying logic of the algorithm has been described above. In this stage, the employment simulation analysis results of senior, junior, and senior graduates are shown in Figure 3.
As can be seen from Figure 3, under the dynamic decision tree algorithm, with the increase of analysis times and data samples, the proportion of dynamic employment choice of senior, junior, and senior graduates is also increasing. The growth rate of senior is the slowest, and the growth rate of junior and senior graduates is similar, which is also in line with the actual law of employment choice. And in the data operation process of dynamic decision tree algorithm, this research uses Python software which is brilliant in the field of data processing as the development language of this part, develops the IDE, and uses the Tensorflow framework which is more open for machine learning to complete the real-time simulation analysis of the dynamic discrete data of graduates’ behavior, so the simulation results are closer to the real situation. Tensorflow is an open source software library using data flow graphs for numerical calculation. Nodes represent mathematical operations in the graph, and edges in the graph represent multidimensional data arrays, namely, tensors, which are interrelated between nodes.
According to the characteristics of big data system integration, this research designs the SSM big data system framework based on MVC traditional design pattern. Its structure mainly includes DAO layer, service layer, Controller layer, and View layer. The big data system framework is used to simulate and analyze the entrepreneurship of senior, junior, and senior graduates, and the results are shown in Figure 4.
As can be seen from Figure 4, under the dynamic decision tree algorithm, with the increase of analysis times and data samples, the proportion of dynamic entrepreneurial choice of senior, junior, and senior graduates is also increasing. The growth rate of senior graduates is the slowest, and the growth rate of junior and senior graduates is similar. This is because the dynamic decision tree model uses real graduate data for in-depth learning, and senior graduates have less entrepreneurial skills (such as business skills, financial skills, business thinking skills, and management skills), while doctoral and master’s students have relatively certain technical ability and business thinking.
For complex discrete dynamic data, a big data processing system based on dynamic decision tree is designed. The designed big data system structure is simulated through trial data. The simulation uses the employment and entrepreneurship of graduates in 2021 disclosed by a municipal government in China as training data and test data. The prediction analysis results are shown in Figure 5.
It can be seen from Figure 5, under the dynamic decision tree algorithm, with the increase of analysis times, the change rules of the training data group and the test data group are different. The result jump percentage of the training data group is almost unchanged and changes slightly around 20%, but the result jump percentage of the test data group decreases gradually with the increase of analysis times (the maximum is 88.1%). It is close to 90%, the minimum is 2.1% (close to 0%), because with the increase of analysis times, the stability of test data in dynamic analysis stage becomes stronger due to random variation factors, while the training sample is because the data will not change randomly with the increase of analysis times. Therefore, the big data model proposed in this study has good accuracy and stability in the process of dynamic analysis under static data.
4. Result Analysis and Discussion
4.1. Confirmatory Experiment and Data Analysis
In the specific experimental process, the dynamic model algorithm and big data system proposed in Section 3 of this paper are used to start the experimental process. Before the experiment, it is necessary to explain various characteristic parameters in the algorithm in advance. For convenience, this study analyzes the dynamic data of graduates’ employment and entrepreneurship from 2012 to 2019 published by a municipal government in China.
According to the algorithm ideas described in Section 3 of this study, this study selected more than 50 attributes of college graduates, such as education, gender, major, age, household registration category, and failure rate during school and graduation years, as the characteristic categories of the decision tree and predicted the whereabouts of college graduates in 2013 based on the employment and entrepreneurship of graduates in 2012. The study also compared with the actual situation of the whereabouts of college graduates in 2013 and the teacher data to verify the accuracy of the algorithm and then fused the dynamic data in 2013 with the base data to predict the whereabouts of college graduates in 2014 and calculate its accuracy and so on. In this study, the data generated are analyzed many times, and the results are recorded. In order to verify that the dynamic decision tree algorithm proposed in this study effectively generates new characteristic attribute branches among the subnodes of the data structure, based on the above experimental methods, this study establishes a retrieval line model system based on Tensorflow framework through the analysis module in Section 4 of this study. For the dynamic decision tree algorithm, ID3 decision tree, and C4.5 decision tree (ID3 decision tree and C4.5 decision tree are two mainstream decision algorithm models in the latest research results), three different decision tree machine learning algorithms are experimentally studied. The preliminary experimental analysis results are shown in Figure 6.
As can be seen from Figure 6, the accuracy of three different machine learning decision tree algorithms in predicting the dynamic employment and entrepreneurship of college graduates from 2013 to 2019 is different in terms of the reliability of the experimental data results. When the number of people is less than 1000, the prediction result accuracy of ID3 decision tree algorithm is the highest. When the number of people is greater than 1000, the data result reliability of dynamic decision tree algorithm is the highest and has been maintained at a high level. The data result reliability of ID3 decision tree algorithm is the lowest, and the prediction accuracy tends to decline gradually. When the number of people is greater than 2000, the prediction accuracy of the three groups of results has decreased to varying degrees, because the dynamic decision tree algorithm has continuously generated new subbranches during the experiment. The maximum bearing capacity of the experimental data has been attenuated since 1800 (that is, the data has been cleared and dynamically analyzed again), and the data collection samples have good coupling with the base data samples. It can be understood that the dynamic decision tree algorithm will test, judge, and classify the new dynamic samples under the “guidance” of the category training samples. The experimental time for all three decision trees is shown in Figure 7.
Figure 7 shows the time required to process different amounts of data during the experiment of three machine learning decision tree algorithms in the big data system. It can be seen from Figure 7, the time required by the dynamic decision tree algorithm is significantly lower than that of the other two mainstream big data analysis decision tree algorithms. This is because the training data of the dynamic decision tree is constructed based on the addition of base data. After each data dynamic increases, the algorithm does not need to rescan all the data, but modifies the previously obtained tree branch structure, which greatly saves the high cost and low efficiency of the decision tree that the algorithm needs to rescan all the data every time the data is changed, and provides efficiency support for the large data system to analyze the characteristics of graduates’ employment and entrepreneurship.
4.2. Result Analysis
The experimental results show that, on the premise of meeting the hierarchical optimization model of conceptual dynamic model, the existing decision tree algorithm is improved by incremental optimization, and the structural analysis of graduates’ employment destination is completed combined with big data system. In order to explore the employment and entrepreneurship of college graduates, this study visualized the details of the employment and entrepreneurship of graduates in a city in China from 2018 to 2020, and the calculation results are shown in Figure 8. Based on the employment and entrepreneurship data of college students from 2018 to 2020, this study calculates the whereabouts of graduates in a city in China in 2021 through the dynamic decision tree algorithm of big data system. The comparison between the predicted results and the real results is shown in Figure 9.
According to the data analysis of the experimental results in Figures 8 and 9, with the continuous growth of China’s economic strength, the continuous opening of China’s College Students’ Entrepreneurship Policy, and the continuous improvement of China’s social system, the proportion of graduates in a city in China who choose to start their own business and enter a higher school after graduation has been increasing since 2018∼2020, and the proportion of unemployed graduates after graduation has shown an overall downward trend. The overall employment choice of graduates tends to be stable and upward, which is also consistent with the actual situation of the city in 2018–2020. On the other hand, the prediction errors of graduates’ employment rate, entrepreneurship rate, and other choice rate in a city in 2021 predicted by the algorithm are 2.8%, 2.6%, and 2.3%, respectively, which is very similar to the whereabouts of graduates in the first half of 2021. Therefore, the dynamic analysis model of college graduates’ employment and entrepreneurship proposed in this study has high accuracy and practical application value.
How to industrialize big data technology with low cost and high efficiency has always been the industry hotspot of big data technology research. Based on this, aiming at the employment and entrepreneurship of college graduates, this study establishes a multilayer dynamic model system based on big data and machine learning dynamic decision tree. Firstly, the development status of various types of big data application technologies and the shortcomings of research progress are introduced, and a dynamic model establishment method based on big data and machine learning dynamic decision tree algorithm is proposed. Secondly, the establishment of big data technology, machine learning technology, and dynamic decision tree algorithm model is introduced, respectively. With the help of these technologies, complex discrete dynamic data can be analyzed and predicted quickly and accurately. Finally, combined with the public data set, the proposed dynamic model is analyzed. Experiments show that the big data integration system based on big data and dynamic decision tree algorithm has high result adaptability. If incremental adaptation optimization is carried out on the traditional decision tree model, the prediction effect and prediction time of dynamic data can be significantly improved, which puts forward theoretical support for the industrialization and social significance of big data technology. This method expands the attributes in the form of dichotomy and only pays attention to the construction of logical attributes in each subbranch of the dynamic model. Therefore, the dynamic model established by this method may lead to too deep decision tree, which needs to be further studied.
The experimental data used to support the findings of this study are available from the corresponding author upon request.
Conflicts of Interest
The author declares no conflicts of interest regarding this work.
The study was funded by the study on the Influence of the Employment and Entrepreneurship of Graduates under the Epidemic Situation of Pneumonia in COVID-19 (JYB2020302).
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OLED is a new display technology, used to create thin, power efficient and bright displays. Today OLEDs are used in mobile phones, tablets, digital cameras and even TV sets - as OLEDs are considered the best display technology ever.
Apple's OLED iPhone
Apple's 10th anniversary iPhone X was the company's first OLED Phone - with a 5.8" 1125x2436 (458 PPI) flexible Super AMOLED display. Since then Apple has been adding more OLED iPhones, and as of 2021, the company's entire smartphone lineup adopts AMOLED displays.
The OLED Apple Watch
In April 2015 Apple launched its first wearable device, the Apple Watch which used a flexible AMOLED display (made by LG Display). All Apple Watch products to date continue to use flexible AMOLED displays. OLED displays are especially suitable for wearable devices - as the displays are thinner and lighter than LCD displays, and are more power efficient (especially if you tweak the UI to suit the special OLED properties). According to reports, Apple is developing next-generation MicroLED display technologies for future wearable devices.
Apple OLED MacBook Pro
Apple's MacBook Pro range of high-end laptops started adopting an OLED Touch Bar instead of the traditional function keys in 2016. The display itself is either a 13" or a 15" LCD.
The OLED strip is supported by most of Apple's applications and can show commonly used emojis in messaging applications, bookmarks while you browse and other context-activated options. It also includes a Touch ID sensor that is activated for example when you wish to pay online (on supported web stores). Apple released an API to developers can support the Touch Bar in third-party applications.
The latest Apple OLED news:
DSCC sees a $63 billion OLED market in 2026, driven by high demand for laptop, monitor and tablet displays
DSCC has released its latest OLED market forecast, and the company forecasts a 8% CAGR revenue growth, with the market reaching $64 billion in revenue in 2026. The growth will be fueled by high demand for laptop, monitor and tablet displays. The smartphone and OLED TV market will also continue to grow.
DSCC sees a 31% CAGR shipment growth for laptop displays, to reach around $2.4 billion in 2026, and a 95% CAGR unit growth for monitor OLED displays, which will reach $1.3 billion in 2026 (up from $200 million in 2022). This is fast growth for monitor OLED displays, but slower than DSCC previously estimated, due to competition for miniLEDs, rigid OLED capacity that will be used for laptops and tablets and lower demand to mirroring display monitors.
Towards the end of 2021 we reported that Apple plans to launch its first AR headset in Q4 2022, powered by dual 4K OLED microdisplays, produced by Sony
According to Ross Young from DSSC, Apple first headset will actually be a VR headset, that uses a foveated display system. The headset will feature three displays - two 4K microLEDs (indeed produced by Sony) and one larger AMOLED display.
Apple analyst Ming-chi Kuo says that Apple plans to launch its first AR headset in Q4 2022, powered by dual 4K OLED microdisplays, produced by Sony. The headset will feature Mac-level computer power and will not require a tethered smartphone to operate.
Apple has been working on AR technologies for many years. Last year it was indeed reported in Japan that Apple is working with Sony on its microdisplays. Earlier this year it was reported that Apple has teamed up with TSMC for microdisplay production - but it could be that TSMC will be the manufacturing partner, while Sony will provide the OLED technology and knowhow.
DSCC posted an interesting article, comparing the production costs of OLED vs mini-LED panels for IT. DSCC estimates that for tablets and notebooks, a tandem structure will be used, and the panels will be based on rigid substrates.
In the chart above you see a production cost comparison, between 2021 and 2025, for 12.9" panels. DSCC looks at two OLED production options: a tandem OLED panel with an LTPO backplane produced in a 6-Gen fab, and a similar panel that uses an Oxide-TFT backplane and produced in a larger 8.5-Gen fab. As you can see, OLED panels are more cost effective, and will remain so throughout the forecast period.
According to a report from China, BOE will produce around 15 million AMOLED panels for Apple in 2021, or about 10% of Apple's total OLED panel orders.
BOE is supplying displays for refurbished iPhone 12 devices, and Apple is now looking into adopting BOE's panels in the iPhone 13. It is likely that the 15 million shipments estimate relies on Apple's approval of BOE's iPhone 13 panels, and even so it might be a bit optimistic that BOE will supply so many panels by year's end.
UBI Research estimates that Samsung Display shipped 124.76 million smartphone AMOLED panels in Q3 2021, an increase of 24.6% from the previous quarter, enjoying high demand from Apple for its iPhone 13 series.
SDC produced and shipped 62.63 million rigid panels (or about 50% of its total shipments), for low-end and mid-tier smartphones. Flexible OLED shipments were 58.2 million units (out of which 39.31 million went to Apple), and foldable OLEDs shipments reached 3.93 million units.
A few days ago we posted that Apple has reportedly decided to delay its iPad OLED launch to 2023, and the company canceled its current joint development project with Samsung Display, as SDC could not develop what Apple wanted - a tandem stack structure, which would have improved the lifetime and performance of the AMOLED display.
According to a new report from Korea, LG Display is also developing a tablet display for Apple - a 12.9" AMOLED panel. LG's iPad display will be ready for mass production by 2023-2024, and it will use a tandem (2 stacks) architecture on an LTPO backplane. As SDC's project is canceled, it is likely that LG's 12.9" will be the first OLED adopted by Apple's tablets.
Reports from Korea suggest that Apple has decided to delay its iPad OLED launch to 2023, and the company canceled its current joint development project with Samsung Display.
SDC aimed to develop a 10.86 AMOLED display for Apple's iPad. According to earlier reports, Apple wanted SDC to developed a tandem stack structure to improve the OLED device lifetime and brightness - and also to reduce burn-in problems. Apparently SDC is not ready to start tandem OLED production next year, and Apple will not accept a single-stack OLED for tablet applications.
Our friends at DisplayMate posted an in-depth technical review of the iPhone 13 Pro Max display. The 6.7-inch 1284x2778 10Hz-120Hz 1200 nits LTPO AMOLED receives DisplayMate's highest display performance grade of A+.
DisplayMate says that the new display outperforms the display adopted by Apple in last year's iPhone 12 Pro Max. The iPhone 13 Pro display's new adaptive 120Hz refresh rate which results in a 25% boost to power efficiency. The new display is also brighter by 27% and enjoys a higher absolute color accuracy. The size of the notch was also reduced by 20%.
According to reports from Korea, Apple has given BOE a "conditional approval" for iPhone panel supply. BOE hasn't been able to meet 100% of Apple's requirements, but it is now given time to fix these issues, and may be able to become a supplier to Apple if all goes well.
Even if BOE manage to satisfy Apple, it will take some time and so it is likely that it won't receive large orders for the iPhone 13 series. Apple currently buys all of its iPhone AMOLED panels from Samsung Display and LG Display. BOE aims to supply the panels for the standard iPhone 13 (not the Pro series).


I noticed there is a new Patch ‘B’ available and I would
like to upgrade my machine, the problem is that I am
using a network card not yet supported by QNX so I
can’t access the web while running it. This means I can’t
access the QNX repository and I am somewhat reluctant
to donwload the whole CD again so I could upgrade from
Is there a way to download the patch from MS-Windows
and then access it directly using a dual-boot?


Anritsu has introduced an LTE-V2X PSCCH TX measurement MX887068A-001 software option to enhance the cellular vehicle to everything (C-V2X) measurement function of universal wireless test set MT8870A / MT8872A. The software supports the physical sidelink shared channel (PSSCH) for LTE-V2X (PC5) and supports RF measurement of the physical sidelink control channel (PSCCH). It also supports […]
The post Anritsu’s software option enhances C-V2X measurement appeared first on Softei.com – Global Electronics Industry News.
Softei.com – Global Electronics Industry News


The REDSCAN RLS-3060 is an award-winning laser scanner detector series. It can detect a moving object's size, speed and distance from the detector and process that information with a unique built in algorithm, which results in high reliability detection with minimal false alarms. The detector can also be mounted vertically or horizontally according to the application and site conditions.
The REDSCAN RLS-3060SH is a high resolution, long range 2D LiDAR detector. It has both intelligent detection analysis functions and adjustable detection algorithm parameters that increase its range of applications. Our RLS-3060SH model provides a flexible solution that streamlines video surveillance and a wide range of security applications.
The REDSCAN RLS-3060-SH can be installed directly on an IP security network and integrates with all major Video Management Software (VMS) platforms.
The RLS-3060SH firmware version 8 and REDSCAN Manager (configuration software) version 8.0 together extend the detection range to 50m and add some new setting options.
|Extended Detection Range||Changeable Dry- contact Alarm Output type|
|The increased detection range function can be set to 50m (165ft) radius. The extended area from 30-50m is ideal as a pre-warning zone. In horizontal mode, at 50m, the laser scanner will be able to detect large moving objects such as vehicles: in vertical mode the RLS-3060Sh could detect a walking or squatting person over 100m.||The new version 8 update offers more flexibility in managing dry contacts with the option to switch from normally open (N.O) to normally closed (N.C). The flexibility in being able to manage multiple outputs means that the sensor suits a number of security applications.|
- Roof / Ceiling
- Vertical and horizontal mounting
- Unique detection algorithm
- Scene selection (outdoor, indoor, indoor etc.)
- Anti-masking function
|Detection Method||Infrared Laser Scan|
|Laser Protection Class||Class 1|
|Vertical Area Coverage||Max. 60 m (Approx. 200 ft.) at 10% reflectivity|
|Horizontal Area Coverage||Radius: 50 m (Approx. 165 ft.), Arc:190° at 10% reflectivity|
|Communication Port||Ethernet ,RJ-45 ,10BASE-T/100BASE-TX|
|Protocol||UDP, TCP/IP *Redwall Event Code|
|Power Imput||24 VDC , 24 VAC|
|Current Draw||400 mA max. (24 VDC) 600 mA max. (24 VAC)|
|Vertical Mounting Height||15 m (50ft.) (recommendation)|
|Horizontal Mounting Height||0.7 m (28in.) (recommendation)|
|Target Object Selector||S / M / L|
|Sensitivity selector||H / M / L|
|Camera control output||N.O. 28 VDC, 0.2 A x 4 outputs|
|Master alarm output||Form C, 28 VDC, 0.2 A max.|
|Trouble output||Form C, 28 VDC, 0.2 A max.|
|Tamper output||N.C. 28 VDC, 0.1 A max.|
|Environmental disqualification circuit||Form C, 28 VDC, 0.2 A max.|
|Alarm period||Approx. 2 sec., Off delay timer|
|Operating temperature||-20 to 60 °C (-4 to 140° F)|
|Dimensions (H x W x D)||334 x 144 x 155 mm (13.2 x 5.7 x 6.1 in.)|
|Weight||2.4 kg (85 oz)|


The Divison of Marketing and Communications provides access to the most up-to-date information released by Memorial University of Newfoundland. Archives of previous news releases are also available.
To access news releases from Grenfell Campus please click here.
REF NO.: 34
SUBJECT: Electrical and computer engineering conference marks 25th anniversary
DATE: Nov. 8
The 2016 Newfoundland Electrical and Computer Engineering Conference will take place on Thursday, Nov. 10, at the Holiday Inn in St. John’s.
This year marks the 25th anniversary of the conference.
This year’s conference brings together a diverse technical program and will explore a wide range of technologies, including power systems, sensing, biomedical, networks and instrumentation.
Conference speakers include Emad Rizkalla, founder and CEO, Bluedrop Performance Learning, who will talk about entrepreneurship and leadership, and Stan Marshall, president and CEO, Nalcor Energy, who will speak about the Muskrat Falls megaproject.
Members of the media are invited to attend either of the above sessions, which will take place at 9 a.m. and 7 p.m., respectively.
The annual conference, which is organized by the Newfoundland and Labrador section of the Institute of Electrical and Electronics Engineers and in co-operation with Memorial University, brings together presenters from industry and academia to highlight the impressive work that is being done in Newfoundland and Labrador in the areas of electrical and computer engineering.
More information about the conference is available here.
- 30 -
For more information, please contact Jackey Locke, communications co-ordinator, Faculty of Engineering and Applied Science, at (709) 864-8287 or email@example.com.


What does Zener mean?
This diode was invented by Clarence Malvin Zener in 1915 and was named after him.
The term "Zener" has been taken from an electrical element called "Zener Diode". This kind of diode passes the electrical current in one direction and allows the current to switch to opposite direction when voltage surpasses the maximum limit.
Zener engineering company was founded by five graduates from Tehran university in 1981. During Iran-Iraq war with increase of frequent interruption of electricity, our company designed and manufactured surge protectors for appliances such as refrigerator, television and others. In 1983 Zener designed and manufactured a new product to protect devices with 3-phase motors.
Manufacturing first Iranian offline UPS with Zener brand and co-founder of UPS Manufacturer’s Association of IRAN
Zener continued manufacturing various types of surge protectors and industrial panels until the 80’s which the usage of computers in government organizations, banks, etc. was on the rise. Interruption for such systems was a major issue and in 1989 Zener engineering company designed and manufactured the first offline UPS in Iran named Zener UPS and expanded the range of production up to 5kVA.
The after sales service department started to grow rapidly due to considerable growth in the market. The commercial department imported necessary electronic components for UPS production primarily and expanded its activity through importing high power industrial UPS, sealed lead-acid batteries and diesel generators.
In 1994 UPS Manufacturer’s Association of IRAN was established with Zener’s participation.
Membership in associations and organizations and acquiring iSO9001: 2008 certificate
From 2000 to 2009, Zener successfully obtained exclusive business partners from famous international brands to provide UPS, battery and generator sets.
Zener established department of renewable energy systems in 2009 and accomplished several research studies. Zener is now officially certified by reputable brands to provide solar panels, inverters, solar chargers and related products.
In 2011 Zener became an active member of Iran Solar Industry Association, Iran Electrical Syndicate and Iran-Italy Chamber of Commerce.
Now with more than 35 years of experience in the field of electronics and more than 60 qualified personnel, we make high efforts to meet and satisfy our clients’ requirements by continuous improvement through various trainings, optimizing procedures and documenting activities. Our ultimate step in achieving this goal was obtaining iSO9001:2008 certificate of quality management system in 2013.
Quality management system standard certification iSO9001:2008 by SGS Switzerland
Membership in Iran’s Electrical Industry Syndicate
Completed construction of 800m2 warehouse for future productions
Membership in the Iran-Italy chamber of commerce
Membership in Solar Industry Institute of Iran
Became official representative of Riello UPS (Italy) after integration of Riello and AROS
The new department of renewable energy systems was created
Became exclusive representative of Global and Rocket batteries from Sebang company (South Korea)
Became exclusive representative of Ablerex Electronics UPS (Taiwan)
Became exclusive representative of AROS UPS (Italy)
Became exclusive representative of Starway battery from Leoch company (China)
Became official representative of AROS UPS (Italy)
Became exclusive representative of Newmax battery from NB corporation (South Korea)
Became official representative of UIS Abler Electronics UPS (Taiwan)
Became official representative of Liebert Hiross UPS (Italy)
Became exclusive representative of PowerCo diesel generators (UK)
Became official representative of Newmax battery from NB corporation (South Korea)
UPS Manufacturer’s Association was established with participation of Zener
Designed and manufactured the first offline UPS in Iran up to 5 kVA named Zener UPS
Change company location to the current location in PHILIPS building and increased office space
Designed and manufactured a surge protection device for 3-phase motors
ZENER Engineering Co was founded on September 16th
Designed and manufactured surge protection devices for appliances such as refrigerator, television and stereos
Zener Engineering Co. with more than 30 years of experience in the electrical and electronics industry is the official and exclusive representative for products of the following companies in Iran:
clusive representative for UPS, frequency converter, power systems manufactured by Ablerex:Ex
Ablerex, with its’own core technologies, has developed power conversion products that promote improved power stability, power quality and green energy for global markets. Ablerex is an organization that invests a high portion of its resources to technical research and development. This strategy results in more than 100 advanced, proprietary patented techniques. In addition, a leading market researcher has presented Ablerex with its Global Leader Award.
representative for UPS, frequency converter, power systems manufactured by Riello:Official
Riello UPS offers a vast range of products, organized into 22 ranges of uninterruptible power supplies (UPS ), based on several different state-of-the-art technological architectures. Thanks to its two research centers, world-class examples of excellence for the design, development and testing of uninterruptible power supplies, Riello UPS can constantly innovate its product portfolio, keeping it at the top in terms of performance, reliability and competitiveness.
clusive representative for Diesel generator and Power systems manufactured by PowerCo:Ex
PowerCo Systems Ltd are an independent British manufacturer of a comprehensive range of diesel generating sets with outputs from 5kVA to 3000kVA, 50 and 60Hz. Based in the United Kingdom, PowerCo have now been manufacturing generators since 1995, however we have decades of experience gained from our main staff working in the Power Industry for well of 20 years.
clusive representative for Starway Sealed-lead acid batteries:Ex
Proprietary battery brand registered under Zener Engineering Co. Zener provides maintenance free sealed lead acid batteries ranging from 7 to 100AH with best quality and high life expectancy used for UPS, telecommunication equipment, lighting applications, security and medical systems.
representative for Rocket/Global Sealed-lead acid batteries manufactured by Sebang:Official
SEBANG GLOBAL BATTERY Co.,Ltd has led the battery industry in Korea with the brand of "Rocket" for over half century since the establishment in 1952. SEBANG Global Battery has put forth its strength to the continuous management innovation corresponding to the rapid changing market environment, and has concentrated ceaseless efforts to the technology development in order to produce the best product.
representative for the Newmax Sealed-lead acid batteries manufactured by Daejin:Official
Daejin Battery Co., Ltd., has over 20 years experience and endless R&D investment in the lead-acid battery industry. Daejin make use of state-of-the-art testing facility to constantly build on experience to provide the most advanced products on the market today. Daejin is passionate about helping customers succeed.


The Burl Audio BAD8 ADC Card is designed for use with the Burl Audio B80 and Burl Audio B16 Mothership; it is the result of over 20 years of R&D A/D design experience.
Following on the overwhelming success of the B2 Bomber ADC and the BAD4, the BAD8 employs a next generation analog circuit path and the latest in analog to digital conversion. This is a no compromise design utilizing all class-A, discrete transistor circuitry and the legendary BX1 transformer coupled input. The BAD8 benefits from the new form factor of the BX1 transformer, allowing for more channel density. The BAD8 also boasts the latest analog-to-digital conversion technology giving it great tone with even greater detail and amazing low latency.
Burl Audio BAD8 ADC Card Features
- 44.1k Hz to 192k Hz, 24 bit, 8 channel ADC
- Proprietary, high definition, BURL AUDIO BX1 transformer input
- Next generation, all class-A, discrete transistor signal path with zero feedback, zero circuit path capacitors
- Next generation AD conversion
- Low latency
- 8-channel DSUB connectivity
2 Reviews Hide Reviews Show Reviews
Of all the a/d Converters that I use these are my favorite musical, conversion you get a sound that is very reminiscent of analog tape deck I use this with the mothership B16 into ProTools HDX system, and I couldn’t be happier
I love these converters. Big! Bold! Clean but with good character. Best AD I've ever had to opportunity to hear. Got 1 and had to immediately get another. Now I track everything using the Burls and it sounds light years better than any other converter that I have ever used on all sources!


Looks like Extron is getting closer and closer to the high-end control market as it just launched the IPCP Pro 555, a high-end IP Link Pro control processor with a dedicated AV LAN port. It features advanced security standards and dual Gigabit Ethernet ports, which are designed to ensure compatibility with multiple TouchLink Pro touchpanels using a standard network infrastructure. Of the two Ethernet ports, the AV LAN is designated to control local AV devices, and is secure from outside interference or intrusion. The IPCP Pro 555 can be used with Extron LinkLicense, which further enhances the capabilities of Extron Pro Series control systems. The IPCP Pro 555 is an ideal choice for controlling multiple devices and signal types within AV systems requiring an isolated AV network.
The IPCP Pro 555 features a DHCP server for the AV LAN that streamlines system setup and management. It automatically distributes IP addresses and network configuration parameters for the AV devices connected to the local AV LAN. In addition, the AV LAN port permits communications from the Ethernet port for remote management and firmware updates for Extron devices, and restricts other Ethernet traffic. The IPCP Pro 555 can be configured and customized using Extron Global Configurator Plus or Global Configurator Professional. It is also compatible with GlobalViewer Enterprise software.


If international car companies want to promote self-driving cars in China, then high-precision positioning services will almost always use Beidou, and high-precision maps will all rely on Chinese related map dealers. For example, BMW established cooperation with NavInfo, which will provide high-precision map services required by BMW for self-driving cars.
Recently, Toyota has also reached strategic cooperation with Chinese self-driving startup Momenta, which will provide high-resolution maps and update services based on camera vision technology. The two parties will jointly promote the commercial implementation of Toyota’s Automated Mapping Platform (AMP) in China to better serve Chinese users.
Momenta is positioned to create the “brain” of autonomous driving, and its core technologies are environment learning based on deep learning, high-precision maps and driving decision algorithms. At the same time, Momenta also has Class A qualification for electronic navigation maps, which can carry out data collection and production of high-precision maps.
In addition to establishing cooperation with Momenta, Toyota itself is also developing high-definition maps. Just a few days ago, Toyota Advanced Research Institute (TRI-AD), a Toyota autonomous driving software research and development company, showed a high-precision map with a relative accuracy of less than 50cm. It has no obvious advantage in terms of accuracy alone. It is reported that TRI-AD has been building high-precision maps since last year, and has now created maps of 23 Tokyo districts and 6 cities around the world.
In terms of autonomous driving research and development, Toyota has been using Lexus LS 500h-based modified cars for related tests. According to Toyota’s plan, Lexus cars with autonomous driving will be launched later in 2020. In addition, Toyota also introduced the e-Palette, a fully electric fully-autonomous driving concept car, which has obvious advantages such as modularity and scalability, and is an ideal solution for mobile travel services.


Pasternack, a leading provider of RF, microwave and millimeter wave products, has signed an agreement with Planar Monolithics Industries, Inc. (PMI) to private-label a selection of PMI manufactured products under the Pasternack brand name. These new products will be available off-the-shelf for immediate shipping.
Through this private-label agreement, Pasternack will expand the visibility of its already extensive portfolio of RF, microwave and millimeter wave coaxial component solutions to a larger number of customers. This new partnership provides customers with urgent RF product needs access to an extensive inventory of industry-leading components through Pasternack, which include Pasternack’s 24/7 sales and technical support, online purchasing and same-day shipping.
“Partnering with PMI is an exciting development for Pasternack, further aligning us with our goal of being the RF engineer’s single source for urgently needed RF products globally. With this agreement, we are able to expand our existing, broad selection of in-stock RF and microwave products and quickly deliver them to engineers when they need them,” said Tim Galla, Senior Product Manager, RF Components at Pasternack.
“Planar Monolithics Industries, Inc. (PMI) has, for a long period of time, been seeking an opportunity to provide customers with off-the-shelf solutions in situations where time and schedules do not allow for our state-of-the-art advanced RF/Microwave components to be built-to-order. Partnering with the remarkable distribution and marketing platform offered by Pasternack Enterprises will now make this possible,” said Sebastian Palacio, VP at Planar Monolithics Industries, Inc.
For more information, visit pmi-rf.com/stock-items.


Elon Musk-owned electric car company Tesla has introduced the new AMD Ryzen chip and 12v Li-ion battery in 2022 Model 3 Model Y vehicles.
Tesla has released an annual holiday software update that turn its electric cars into megaphones by using external speakers that have been installed in recent vehicles.
The company said that the new update brings improved object detection network architecture for non-VRUs (e.g. cars, trucks, buses), seven per cent higher recall, 16 per cent lower depth error and 21 per cent lower velocity error for crossing vehicles.
Elon Musk-owned electric car maker Tesla has withdrawn an application for over $1 billion in subsidies for battery production at Gigafactory Berlin.
Tesla has updated the warning that comes with downloading a new version of the FSD Beta. It includes all the warnings that were part of previous releases, but the automaker added important new language.
The company had earlier said R1S would begin production at the Normal, Illinois plant in December, with the first deliveries expected in January.
Elon Musk-owned electric vehicle company Tesla's app server went down this week, leading to a worldwide app outage that left owners unable to connect to their cars.
Musk was responding to a Tesla owner's tweet, who said that he was experiencing a "500 server error" to connect his Model 3 through the iOS app in Seoul, South Korea.
Elon Musk-owned electric vehicle company Tesla has reportedly removed the dates about Cybertruck production from its website.
Elon Musk-owned electric vehicle company Tesla is using its "Tesla Engage" platform to ask its fanbase to support a new push to convince the New York governor and legislature to allow direct sales of its electric vehicles in the state.


Ce kit de raccordement spécial pour...
The kits "sewable el wire tuning moto" are complete and ready to be used. This el wire has the specificity to have a plastic collar allowing you to stick, staple or sew your el wire easily. The el wire is connected, via its inverter, directly on the electric harness of your motorcycle. Its very low consumption will not penalize your battery.


Electrical engineering degrees are available at both undergraduate and graduate levels. These programs often feature specializations in areas like nanotechnology, microelectronics and circuit design. Undergraduate students must have their high school diploma to pursue an associate's (2 years) or bachelor's (4 years) degree in the field, with some schools requiring SAT or ACT scores. An undergraduate degree in electrical engineering is required for master's and Ph.D programs, as well as GRE scores. Master's programs typically take 2 to 6 years to complete, with thesis projects often being required.
Associate of Applied Science in Electrical Engineering Technology
An associate's degree program in electrical engineering technology prepares grads for employment as engineering technicians. Students in associate's programs learn about electronic devices and components. Hands-on training in assembling and dissembling electronics is often included.
After basic courses in math and physics, students receive training in electronic circuits, machines that utilize electricity and computer applications. Some possible courses include:
- Algebra and calculus
- Logic controllers
- Analog electronics
- DC and AC circuits
Bachelor of Science in Electrical Engineering (BSEE)
A Bachelor of Science in Electrical Engineering provides a foundation in electrical engineering and introduces students to the theory and design of electrical circuits, electronics and systems and signals. Some programs include an optional fifth year in which the student completes a senior design project. This is strongly encouraged for those students who are interested in continuing their study in electrical engineering at the graduate level.
The first and second year of enrollment is primarily devoted to math and science courses. During the final years, a student will complete core courses in electrical engineering and a senior project. Some possible courses include:
- Physics and chemistry
- Calculus including differential equations
- Circuits and digital logic
Master of Science in Electrical Engineering
A master's degree program in electrical engineering introduces students to more advanced concepts within the field. Students may pursue a thesis or non-thesis option; the thesis option is strongly recommendation for students who plan to apply for research-based electrical engineering positions.
The first year is devoted to core courses in a student's area of interest. Course topics typically include:
- Solid state instruments
- Computer engineering and architecture
- Electromagnetic theory
- Analysis of linear systems
- Complex variables
Doctor of Philosophy in Electrical Engineering
A Doctor of Philosophy in Electrical Engineering degree program includes training on the basics of electronic systems and design. Some current electrical engineering emphasis areas include semiconductors, solid state microelectronics, signal processing, wireless networks and electromagnetics.
A majority of the time enrolled in a Ph.D. degree program in electrical engineering is spent on conducting research and the writing of a dissertation. A research topic is chosen and the student works closely with an adviser to develop a course of study that compliments the student's area of interest.
Elective courses should support a student's area of interest within the discipline. Some courses might include:
- Electrical power systems
- Analysis of linear systems
- Processing of digital signals
- Integrated circuits
- Electromagnetics and computational methods
Job Outlook and Salary Information
According to the U.S. Bureau of Labor Statistics (www.bls.gov), the employment of electrical and electronic technicians is expected to decline by 2% for the years 2014-2024. The BLS also reports that the 2015 annual median salary of an electrical and electronics engineering technician was $61,130.
The BLS reported that the employment of electrical engineers is not expected to change for the 2014-2024 period. The median annual salary of an electrical engineer in 2014 was $93,010.
Possible Career Options
Many opportunities exist for electrical engineering at all levels from associate to doctoral degrees.
- Electronics technician
- Electrical engineer or research electrical engineer
- Test engineer
- Research engineer
Continuing Education Information
State licensure is required for engineers who offer their services to the general public. Licensure requires passing a state examination, accumulating four years of work experience as an engineer and graduation from a program accredited by the Accreditation Board for Engineering and Technology (ABET). Certification is also offered by many different professional organizations.
Aspiring electrical professionals can pursue associate's, bachelor's, master's, and doctoral degrees that provide training in various areas of electrical engineering and technology. Those who attain licensure after school can seek careers as engineers.


Haldane charge conjecture in one-dimensional multicomponent fermionic cold atoms
Physical Review B
A Haldane conjecture is revealed for spin-singlet charge modes in 2N-component fermionic cold atoms loaded into a one-dimensional optical lattice. By means of a low-energy approach and DMRG calculations, we show the emergence of gapless and gapped phases depending on the parity of N for attractive interactions at half-filling. The analogue of the Haldane phase of the spin-1 Heisenberg chain is stabilized for N=2 with non-local string charge correlation, and pseudo-spin 1/2 edge states. At the
... art of this even-odd behavior is the existence of a spin-singlet pseudo-spin N/2 operator which governs the low-energy properties of the model for attractive interactions and gives rise to the Haldane physics.


This item may be available in a different size, colour, scent, version or platform. Click below to be directed to product options:
Compatible Models: Samsung Galaxy Note 3 Package Include : 2 x 3500mAh Li-ion Rechargeable Replacement Battery + 1 x Desktop Dock Charger Cradle + 1 x USB-Cable
Batteries (3.7v, 3500 mAh) AnoKe batteries use high quality cells£¬batteries have an integrated microchip to prevent overcharging and overheating that helps lengthen the life of your battery.
Charger Cradle Function: Data synchronization + Phone charger + Phone holder + Charging Spare Battery both the phone and battery can charger at the same time. Batteries have an integrated microchip to prevent overcharging and losing power that helps lengthen the life of your battery.Stable phone holder allows to watch movies without hand holding all the time.small portable designed that convenient to carry on traveing
Notes:1. The dock is equivalent of a connector. If adapter output voltage is not enough, maybe cannot charge phone and battery at the same time. Only work either. If the special adapter over 18w (quick charger 2.0, quick charger 3.0 )have enough output voltage, both battery and phone are charging.
batteries 24-Month Warranty:If you have any problem with this product , please feel free to contact us, we will reply you within 24 hours.
Notes: 1. The dock is equivalent of a connector. If adapter output voltage is not enough, maybe cannot charge phone and battery at the same time.Just work either. If the special adapter over 18w (quick charger 2.0, quick charger 3.0 )have enough output voltage, both battery and phone are charging. 2. The dock works with TPU slim case. Package Include : 1 x Galaxy Note 3 Charger,2 x Galaxy Note 3 Battery, + 1 x USB-Cabl Batteries (3.7v, 3500 mAh) were made with Lithium-ion technology , allows to charged battery quickly With The Desktop Dock Charger Cradle , You Can Charge Spare Battery And Phone At The Same Time The Dock Charger Cradle Can Makes You Watch Videos And listen To Music more convenient When charging
Package Contents: Perfectly designed for Samsung Galaxy note 3
Samsung Galaxy Note 3 BATTERY*2
Most Helpful Customer Reviews
The battery's work fine, I feel like they give me about the same amount of charge as the battery that came with my note 3. The charger works decently as well. It takes a little longer to charge than the USB 3.0 charger that came with my phone, and even slower when I have both the spare and the phone charging at the same time. I feel good knowing that I am never without a spare battery. The charger holds my phone nicely, especially for video chatting.
I LOVED the product and it helped us with 2 batteries that I can charge quickly. This saved having to replace the phone so it was a win-win deal!!
This charger has worked very well for me I never run out of battery power.
The authorised South African distributor of this product is under no obligation to honour the manufacture's guarantees/warranties or to provide after-sales service.
Please note that this item is imported from the USA, and is designed to be used in the USA. In addition, if the unit is powered it will come with a US plug and an adapter/transformer may be required. Please click here for more information on power requirements, or check with us if you are unsure or need any assistance!
Please also note that certain items cannot be imported, these include Alcohol, Animals, Batteries, Flammable Materials, Currency, Food, Furs, Chemicals, Explosives, Medications, Plants, Seeds, Supplements, Pressurized Cans, Tactical Equipment, Vitamins, Weaponry and Weaponry Accessories. In these cases, the item and information is displayed for reference purposes only. If you are not sure if we are permitted to bring an item, please send us an e-mail with a link to the item to confirm.
Please also ensure that you are ordering the correct item for your particular application as returns to the USA are costly. Product reviews are also provided for most of our items, which can give you a good idea for possible things to look out for and the quality of the item. By clicking Add to Cart, you are confirming that the item is correct and you accept the conditions listed here.


Design Feasibility of a Vortex Induced Vibration Based Hydro-Kinetic Energy Harvesting System
The vortex induced vibration (VIV) based power generating system discussed in this paper is a new concept in power generation from fluid flows in oceans, rivers and streams. The possibility of harnessing energy from the vibrations incurred in a bluff body due to the phenomenon known as VIV, in which motion is induced on a body facing an external flow due to the periodic irregularities in the flow caused by boundary layer separation is explored. The VIV system is based on the idea of maximizing rather than spoiling vortex shedding and exploiting rather than suppressing VIV. The vibrating bodies are in turn used to harness energy using an efficient power-take-off system. The study of fluid dynamics, along with maintaining vortex shedding over the synchronization range, plays an important role in the design of such a system. Apart from this, the main challenge in the design of a VIV generator is introducing optimal damping and low mass ratios for high energy conversion and an efficient power take- off mechanism. This work presents a scoping study of such a device. In contrast to previous work on forced vibrations, the present study focuses on free vibrations that arise due to the shedding of vortices from a cylinder. The working and design considerations of the energy converter is outlined starting with a set of basic definitions pertaining to this technology. © 2011 IEEE.
V. Lobo et al., "Design Feasibility of a Vortex Induced Vibration Based Hydro-Kinetic Energy Harvesting System," 2011 IEEE Green Technologies Conference, Green 2011, Institute of Electrical and Electronics Engineers (IEEE), Jan 2011.
The definitive version is available at http://dx.doi.org/10.1109/GREEN.2011.5754879
2011 IEEE Green Technologies Conference, Green 2011 (2011, Baton Rouge, LA)
Mechanical and Aerospace Engineering
Article - Conference proceedings
© 2011 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.


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Global market for battery recycling services will register a steady 10.9% CAGR from 2016 to 2024, with the opportunity in this market rising from US$7.1 bn to be worth US$19.9 bn by the end of the forecast period.
[USPRwire, Mon Apr 15 2019] In order to study the various trends and patterns prevailing in the concerned market, Market Research Reports Search Engine (MRRSE) has included a new report titled “Global Battery Recycling Market” to its wide online database. This research assessment offers a clear insight about the influential factors that are expected to transform the global market in the near future.
Get Sample Report @ https://www.mrrse.com/sample/1855
Battery recycling involves the recycling of used batteries from various sources such as household batteries; car batteries; and batteries from laptops, mobile phones, power tools, etc.. This activity prevents batteries from ending up in municipal waste and landfills and prevents hazardous materials such as lead, cadmium, mercury, and nickel from entering the environment. These materials are highly toxic and can leach into the soil from landfills. They not only contaminate soil but also underground and surface water sources. Therefore, battery recycling not only protects the environment from potential hazards but also prevents possible health ailments due to these hazardous materials.
This report analyzes and forecasts the market for battery recycling at the global and regional level. The market has been forecast based on revenue (US$ Mn) from 2018 to 2026, considering 2017 as the base year. The study includes drivers and restraints of the global battery recycling market. It also covers the impact of these drivers and restraints on demand for battery recycling during the forecast period. The report also highlights opportunities in the battery recycling market at the global and regional level.
The report includes a detailed value chain analysis, which provides a comprehensive view of the global battery recycling market. Porter’s Five Forces model for the battery recycling market has also been included to help understand the competitive landscape in the market. The study encompasses market attractiveness analysis, in which battery chemistry, spent battery source, and end-use are benchmarked based on their market size, growth rate, and general attractiveness.
The study provides a decisive view of the global battery recycling market by segmenting it in terms of battery chemistry, spent battery source, and end-use. In terms of battery chemistry, the battery recycling market has been classified into lithium-ion, lead-acid, nickel-cadmium, and others. Based on spent battery source, the battery recycling market has been categorized into automotive, electronic appliances, and others. In terms of end-use, the battery recycling market has been segmented into extraction of material; repackaging, reuse, & second life; and disposal. These segments have been analyzed based on present and future trends. Regional segmentation includes current and forecast demand for battery recycling in North America, Europe, Asia Pacific, Latin America, and Middle East & Africa.
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The report provides the actual size of the battery recycling market for 2017 and estimated market size for 2018 with forecast for the next eight years. The global market for battery recycling has been provided in terms of revenue. Market revenue has been defined in US$ Mn. Market numbers have been estimated based on battery chemistry, spent battery source, and end-use of battery recycling. Market size has been provided in terms of global, regional, and country level markets.
The report comprises profiles of major companies operating in the global battery recycling market. Key players in the battery recycling market are Battery Solutions LLC, Call2Recycle, Inc., Exide Technologies, Retriev Technologies, Inc., East Penn Manufacturing Company, EnerSys, G & P Batteries, Gravita India Ltd., Johnson Controls, Inc., and Umicore N.V. Market players have been profiled in terms of attributes such as company overview, financial overview, business strategies, regional presence, and recent developments.
The global battery recycling market has been segmented as follows:
Battery Recycling Market, by Battery Chemistry


Researchers at the
) have developed a digital memory device by incorporating platinum nanoparticles into the tobacco mosaic virus. They claim that the result could be used to develop biocompatible electronic equipment.
In recent years researchers have exploited the unique selectivity of biomaterials by nanostructuring biological molecules with inorganic materials for applications such as biosensing. The UCLA researchers have taken this idea one-step further with a hybrid biological system that can store digital information.
‘We have developed an electronic device, fabricated from the tobacco mosaic virus conjugated with nanoparticles, which exhibits a unique memory effect,’ said Yang Yang, the group’s lead researcher. ‘This device can be operated as an electrically bi-stable memory device whose conductance states can be controlled by a bias voltage. The states are non-volatile and can be digitally recognised.’
The TMV is a 300nm tube consisting of a protein shell and RNA core. According to the researchers, the TMV’s thin, wire-like structure makes it suitable for attaching nanoparticles, in this case, around sixteen positive platinum ions per virion. The device works by transferring charge, under a high electric field, from the RNA to the platinum nanoparticles with the TMV’s surface proteins acting as an energy barrier, stabilising the trapped charges.
‘The TMV’s surface makes it an ideal template for organising the nanoparticles, which can bind to the specific carboxyl or hydroxyl sites on the surface,’ said Yang. ‘The RNA core in TMV is likely to serve as the charge donor to the nanoparticles with the coat proteins acting as the barrier to the charge transferring process.’
The TMV hybrid, says the team, has an access time in the order of microseconds. This is comparable to current flash memory. In addition, the device is non-volatile, which means that data is retained once the computer’s power is turned off.
The researchers say the device still needs to be scaled-down to a smaller size to increase storage density and to include more circuitry. ‘There will be issues involving retention time, power consumption, and integration of drivers required to write and read each bit, which we need to consider in order to optimise the system,’ said Yang.
Such devices could one day be integrated in biological tissues for applications in therapeutics or biocompatible electronics.


Is yaber a good projector?
The Yaber V7 Pro is a budget projector that delivers more features and better image quality than you might expect for the price. It’s quieter than the firm’s V10 model, smaller and comes with more features but, despite a slightly higher price, it’s just as much of a bargain, if not more so.
How do I setup my yaber V6 projector?
Does yaber projector have Bluetooth?
V6 movie projector built-in the latest Bluetooth 5.0 chip which can connect your Bluetooth speaker wirelessly any time freely. Built-in 6w dual HiFi Stereo speakers with SRS sound system provides a great auditory sense experience without external speakers.
How do I connect my soundbar to my yaber projector?
Connecting a DVD: Use the supplied AV cable to connect the DVD player to the projector and turn on the projector and DVD player. ⑤. Connect the soundbar: Use the supplied AV cable to connect the soundbar to the projector and turn on the projector and the sound bar.


The MySpot 200 restricts unauthorized access to parking spaces, driveways, and access ramps. Drivers of authorized vehicles use a remote-control key fob to lower the steel barrier that protects their exclusive parking spots. The self-powered, self-contained system captures energy from the vehicle's weight and uses the stored energy to raise and lower the barrier, thus obviating the need to connect the device to an electrical power source.
Designated Parking Corp.
Input No. 204 at BDCnetwork.com/BDCinfo


Eppendorf which is a leading life science company recently launched BioFlo 120, their latest bench scale fermentor/bioreactor system for research and development. BioFlo 120 can ferment microbial as well mammalian cell culture application with a single platform. The newly developed Auto Culture modes for push button control of microbial and cell culture applications drastically reduce the learning curve associated with new equipment.
Ease of use and flexibility ensure the new bioreactor/fermentor serves the needs of scientists today and in the years to come - be it in academic, governmental, or industrial research settings.
Kevin Voll, product manager Eppendorf bioprocess said, "We know that in research and development time is critical. Our priority was to develop a bioprocess system that is straightforward to set up and easy to use. By reducing the time required in learning to use new equipment, we free up scientists to spend more time on what is important, their research"
Hamed Tehrani after using the new control station for few weeks said, "A very user-friendly system, which is self-explanatory"
The new BioFlo 120 bioprocess control station will be presented at the BioProcess International Europe in Amsterdam, the BioProcess International West in San Francisco, the BioPharm Asia in Singapore, and other industry events.


Realme narzo 30 Pro 5G with 6.5-inch 120Hz display, Dimensity 800U launched starting at Rs. 16999
Along with Realme Narzo 30A, Realme also launched a low-cost 5G phone Realme narzo 30 Pro 5G in India. This phone starts at just Rs. 16999.
Realme narzo 30 Pro 5G features a 6.5-inch Full HD+ LCD display with hole-punch for the selfie camera. The display also has 120Hz refresh rate and 180Hz touch sampling rate.
It packs an Octa-Core MediaTek Dimensity 800U processor that supports dual 5G. There are two RAM Storage models: 6+64GB and 8+128GB. Storage is also expandable. The phone runs on realme UI based on Android 10 and is also upgradable to realme UI 2.0 based on Android 11.
The Narzo 30 Pro 5G has a triple camera setup that includes 48-megapixel primary camera, 8 megapixels ultra-wide camera, and a 2 megapixels macro camera. It also has 16 megapixels selfie camera.
The fingerprint sensor is on the side. The narzo 30 Pro 5G also features Hi-Res audio and Dolby Atmos.
Also see: 5G Phones in India
Connectivity options include 5G SA/ NSA, Dual 4G VoLTE, Wi-Fi 802.11 ac (2.4GHz + 5GHz), Bluetooth 5, GPS/GLONASS/Beidou, and USB Type-C. It packs a 5000mAh battery with 30W Dart Charge fast charging.
Realme narzo 30 Pro 5G price in India
- 6GB RAM + 64GB Storage: Rs. 16,999
- 8GB RAM + 128GB Storage: Rs. 19,999
realme narzo 30 Pro 5G specifications
- 6.5-inch (2400 × 1080 pixels) Full HD+ LCD screen with 120Hz refresh rate
- Octa Core MediaTek Dimensity 800U (MT6873V) 7nm processor
- 6GB RAM with 64GB storage / 8GB RAM with 128GB storage,
- Android 10 with realme UI
- 48MP rear camera, 8MP 119° ultra-wide angle camera, 2MP 4cm macro camera
- 16MP front camera
- Side-mounted fingerprint sensor
- Dolby Atmos, Hi-Res audio
- 5G SA/ NSA, Dual 4G VoLTE, Wi-Fi 802.11 ac (2.4GHz + 5GHz), Bluetooth 5, GPS/GLONASS/Beidou, USB Type-C
- 5000mAh battery with 30W Dart Charge fast charging
- Dimensions: 162.2×75.1×9.1mm
- Weight: 194g


Shut everything down, including the Cable Modem. Leave the modem off for a couple of minutes.
Connect an ethernet cable between the modem and the router's "WAN" port and between the PC and one of the router's "LAN" ports. Power on the modem and wait for it to be fully booted and online. Then power on the router, wait for it to boot fully and finally boot the PC. You should now be able to access the router's setup pages by entering its IP address into a web browser.
The default setting will probably have let you get online with the PC that is connected with the cable. You need to configure its "wireless" settings so that the laptop can get online wirelessly then you can remove the cable to the PC.
<<< do I have to leave the desktop connected permanently? >>>
<<< would I have to install any drivers onto my laptop?. >>>
You only need to install the software for the Wireless Network Adapter. There is no software to install for the router to which you connect over the LAN, with either a wired or a wireless connection.


Payment & Shipping Terms:
|Voltage:||AC220V, AC110V, DC24V||Scaning Beams:||154 Beams|
|Catagory:||Elevator Spare Parts, Light Curtain||Feature:||NV-917G|
|Opening Mode:||Central Opening, Side Opening||Transportation:||Air, Sea|
safety light guard,
elevator door safety edge
917G Elevator Light Curtain AC220 / DC24 Power Supply Control Photocell
Adopting infrared light reflecting principle, when elevator doors are interrupted by obstructions, a signal will be sent out from door detectors, door operators will receive this signal and control the door opening. With advanced production management and strict quality inspection, WECO door detector has become the first brand in the world, providing reliable guarantee of passengers’ safety.
WECO-957G elevator door photocell is same as 917/ 957E, 917/ 957F door detector, all belong to 2- IN- 1 elevator door photocell. Which can better replace the safety edge to work on lift to be more effective to protect passenagers from being hurt.
Multi series production design.
Various outputs to match with different door operator’s demand.
Door detector height can be customized.
Replacement solution can be proved.
|Number of infra red diodes||32diodes||32diodes|
|Response time||relay output||61ms||61ms|
|Led Interpretation||The yellow LED and red LED in receiver is on when blocked or in malfunction|
|The yellow LED in receiver is on and red LED in receiver off without blocking.|
Dimension and Mounting holes
Every piece packed in tube,five tubes in a bundle;
Each tube includes
Power supply control unit (1pieces)
Durable flexible cable (2cables)
User Manual (1copy)
Mounting accessories (1 set)
1. More than20years experience in elevator light curtain production and designing.
2. Our products have been exported to more than 40 countries, like Germany, Greece, Italy, Spain, UK, France, Russia, USA, Brazil, Mexico, Australia, Korea, Thailand, Indonesia, India and many other countries.
3. Flexible and Untraceable payment terms.
4. Good after-sale service.
5. We offer high quality products at competitive price in quick delivery.
Contact Person: Ailsa