Tinjauan terhadap pengetahuan, kemahiran dan minat dalam bidang keusahawanan di kalangan peserta kursus jangka pendek anjuran Jabatan Pendidikan Teknik dan Vokasional

The purpose of this research is to determine the knowledge, skill and enthusiasm among participants short term course organized by Jabatan Pendidikan Teknik dan Vokasional (JPTV). Fifty-four participants from three short term courses, Kursus Usahawan Berasas Kimpalan, Kursus Penyelenggaraan dan Pemasangan Komputer dan Kursus Chargeman AO are selected as respondents to gather feedbacks based on the questionnaire distributed. Collected data is analyzed by using Statistical Package For Social Science (SPSS), 11.0 version, which were represented using mean scores, percentage and Correlations Pearson. The result of this research shows that majority of the participants are enthusiasm towards entrepreneurship but they are lack of knowledge and skill in entrepreneurship basic. "Garis Panduan Asas Keusahawanan " had been created to give knowledge and skill entrepreneurship basic for participants short term course organized by JPTV

Analog Defect Injection and Fault Simulation Techniques: A Systematic Literature Review

Since the last century, the exponential growth of the semiconductor industry has led to the creation of tiny and complex integrated circuits, e.g., sensors, actuators, and smart power. Innovative techniques are needed to ensure the correct functionality of analog devices that are ubiquitous in every smart system. The ISO 26262 standard for functional safety in the automotive context specifies that fault injection is necessary to validate all electronic devices. For decades, standardization of defect modeling and injection mainly focused on digital circuits and, in a minor part, on analog ones. An initial attempt is being made with the IEEE P2427 draft standard that started to give a structured and formal organization to the analog testing field. Various methods have been proposed in the literature to speed up the fault simulation of the defect universe for an analog circuit. A more limited number of papers seek to reduce the overall simulation time by reducing the number of defects to be simulated. This literature survey describes the state-of-the-art of analog defect injection and fault simulation methods. The survey is based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodological flow, allowing for a systematic and complete literature survey. Each selected paper has been categorized and presented to provide an overview of all the available approaches. In addition, the limitations of the various approaches are discussed by showing possible future directions

Hybrid Verification for Analog and Mixed-signal Circuits

With increasing design complexity and reliability requirements, analog and mixedsignal (AMS) verification manifests itself as a key bottleneck. While formal methods and machine learning have been proposed for AMS verification, these two types of techniques suffer from their own limitations, with the former being specifically limited by scalability and the latter by inherent errors in learning-based models. We present a new direction in AMS verification by proposing a hybrid formal/machinelearning- based verification technique (HFMV) to combine the best of the two worlds. HFMV builds formalism on the top of a machine learning model to verify AMS circuits efficiently while meeting a user-specified confidence level. Guided by formal checks, HFMV intelligently explores the high-dimensional parameter space of a given design by iteratively improving the machine learning model. As a result, it leads to accurate failure prediction in the case of a failing circuit or a reliable pass decision in the case of a good circuit. Our experimental results demonstrate that the proposed HFMV approach is capable of identifying hard-to-find failures which are completely missed by a huge number of random simulation samples while significantly cutting down training sample size and verification cycle time

An Implementation of POPBL for Analog Electronics (BEL10203) Course at the Faculty Of Electrical and Electronic Engineering, Uthm

A Project Oriented Problem Based Learning (POPBL) has been introduced to the first year students in the Analog Electronics (BEL10203) course at the Faculty of Electrical and Electronic Engineering, UTHM. The aim is to design an electronic circuit using transistors and diodes that can function as electronic appliances with low cost, low power consumption, and has the features of smart and portable. The total of 143 students were divided into groups and assigned to setup an electronic based company that will be manufacturing the electronic product. Each group had to conduct their regular meetings and develop different kind of products with their creativity. The overall evaluation is divided for both lecturer and peer assessment which carried 20% of their course work. The assessment covered 60% of evaluation for the group management, attitude, progress presentation, report writing while another 40% for the functionality and features of their product. As a result, the POPBL session has increased the student’s ability to analyze and design an analog circuit using various kinds of transistors and diodes. They also gained practical understanding on transistor and diode operation. The POPBL not only expanded their experience in using software tools for circuit design and simulation, but also developed greater awareness to conduct professional presentation and technical report. They also learned to work as professional, keen to ethical responsibilities and committed to the group. The analysis conducted has shown that 95% of the students agreed that the problem given helped them understands better the course syllabus and developed a good problem solving skills

A Behavioral Model of a Built-in Current Sensor for IDDQ Testing

IDDQ testing is one of the most effective methods for detecting defects in integrated circuits. Higher leakage currents in more advanced semiconductor technologies have reduced the resolution of IDDQ test. One solution is to use built-in current sensors. Several sensor techniques for measuring the current based on the magnetic field or voltage drop across the supply line have been proposed. In this work, we develop a behavioral model for a built-in current sensor measuring voltage drop and use this model to better understand sensor operation, identify the effect of different parameters on sensor resolution, and suggest design modifications to improve future sensor performance

Circuit Design

Circuit Design = Science + Art! Designers need a skilled "gut feeling" about circuits and related analytical techniques, plus creativity, to solve all problems and to adhere to the specifications, the written and the unwritten ones. You must anticipate a large number of influences, like temperature effects, supply voltages changes, offset voltages, layout parasitics, and numerous kinds of technology variations to end up with a circuit that works. This is challenging for analog, custom-digital, mixed-signal or RF circuits, and often researching new design methods in relevant journals, conference proceedings and design tools unfortunately gives the impression that just a "wild bunch" of "advanced techniques" exist. On the other hand, state-of-the-art tools nowadays indeed offer a good cockpit to steer the design flow, which include clever statistical methods and optimization techniques.Actually, this almost presents a second breakthrough, like the introduction of circuit simulators 40 years ago! Users can now conveniently analyse all the problems (discover, quantify, verify), and even exploit them, for example for optimization purposes. Most designers are caught up on everyday problems, so we fit that "wild bunch" into a systematic approach for variation-aware design, a designer's field guide and more. That is where this book can help! Circuit Design: Anticipate, Analyze, Exploit Variations starts with best-practise manual methods and links them tightly to up-to-date automation algorithms. We provide many tractable examples and explain key techniques you have to know. We then enable you to select and setup suitable methods for each design task - knowing their prerequisites, advantages and, as too often overlooked, their limitations as well. The good thing with computers is that you yourself can often verify amazing things with little effort, and you can use software not only to your direct advantage in solving a specific problem, but also for becoming a better skilled, more experienced engineer. Unfortunately, EDA design environments are not good at all to learn about advanced numerics. So with this book we also provide two apps for learning about statistic and optimization directly with circuit-related examples, and in real-time so without the long simulation times. This helps to develop a healthy statistical gut feeling for circuit design. The book is written for engineers, students in engineering and CAD / methodology experts. Readers should have some background in standard design techniques like entering a design in a schematic capture and simulating it, and also know about major technology aspects

An Analog VLSI Deep Machine Learning Implementation

Machine learning systems provide automated data processing and see a wide range of applications. Direct processing of raw high-dimensional data such as images and video by machine learning systems is impractical both due to prohibitive power consumption and the “curse of dimensionality,” which makes learning tasks exponentially more difficult as dimension increases. Deep machine learning (DML) mimics the hierarchical presentation of information in the human brain to achieve robust automated feature extraction, reducing the dimension of such data. However, the computational complexity of DML systems limits large-scale implementations in standard digital computers. Custom analog signal processing (ASP) can yield much higher energy efficiency than digital signal processing (DSP), presenting means of overcoming these limitations. The purpose of this work is to develop an analog implementation of DML system. First, an analog memory is proposed as an essential component of the learning systems. It uses the charge trapped on the floating gate to store analog value in a non-volatile way. The memory is compatible with standard digital CMOS process and allows random-accessible bi-directional updates without the need for on-chip charge pump or high voltage switch. Second, architecture and circuits are developed to realize an online k-means clustering algorithm in analog signal processing. It achieves automatic recognition of underlying data pattern and online extraction of data statistical parameters. This unsupervised learning system constitutes the computation node in the deep machine learning hierarchy. Third, a 3-layer, 7-node analog deep machine learning engine is designed featuring online unsupervised trainability and non-volatile floating-gate analog storage. It utilizes massively parallel reconfigurable current-mode analog architecture to realize efficient computation. And algorithm-level feedback is leveraged to provide robustness to circuit imperfections in analog signal processing. At a processing speed of 8300 input vectors per second, it achieves 1×1012 operation per second per Watt of peak energy efficiency. In addition, an ultra-low-power tunable bump circuit is presented to provide similarity measures in analog signal processing. It incorporates a novel wide-input-range tunable pseudo-differential transconductor. The circuit demonstrates tunability of bump center, width and height with a power consumption significantly lower than previous works

Teaching Programmable Microcontrollers to Novice Users in a College of Agriculture: Effects on Attitude, Self-Efficacy, and Knowledge

This thesis consists of two articles that examined an instructional treatment based on the use of Arduino UNO R3 programmable microcontrollers in a fundamentals of agriculture systems technology course at the University of Arkansas. The first article examined students’ breadboarding and programming self-efficacy and knowledge of Arduino. The treatment consisted of a three-class-period instructional treatment, starting with a pretest before instruction to measure students’ baseline interest, knowledge, and self-efficacy of breadboarding and programming Arduino. This was followed with a short 30-minute instructional video explaining basic Arduino programming and breadboarding. Next a hands-on laboratory activity requiring students to breadboard and program an LED circuit was conducted. The activity was graded and rubrics were returned to the students before they took the posttest. Students’ mean scores for breadboarding and programming self-efficacy and Arduino knowledge were higher after the instructional treatment, while the observed mean for interest slightly declined. The second article examined the rubric scores from the hands-on laboratory activity and evaluated where students most commonly made errors breadboarding and programming. Rubric scores on Arduino breadboarding were 58.5% and programming 23.5%, leading us to conclude that students needed more instruction on Arduino programming and in breadboarding simple electronic circuits. The single most common error made when programming was the lack of writing simple comments at the end of each line of the program sketch to describe what the command is doing. The second most common error in programming was not writing the command to correctly identify a digital pin as an output. For breadboarding, the two most common errors were that students were unable to correctly “forward-bias” an LED and wire a single 240ohm resistor in series in the circuit. Both articles produced findings worth implementing into a future redesigned study where novice agriculture students are introduced to basic electronics circuitry followed by Arduino programming. Readers should design instruction that provides students with the opportunity for mastery experiences like breadboarding and programming success during instruction prior to an individual hands-on task. The instructional treatment should be extended in time to allow students more opportunity to process new knowledge. The hands-on activity should be simplified to include only one LED circuit, and the reference sheet should show more complete examples of programming. Students should be encouraged to work together on the hands-on activity rather than being left to work individually

Summer Institute in Biomedical Engineering, 1973

Bioengineering of medical equipment is detailed. Equipment described includes: an environmental control system for a surgical suite; surface potential mapping for an electrode system; the use of speech-modulated-white-noise to differentiate hearers and feelers among the profoundly deaf; the design of an automatic weight scale for an isolette; and an internal tibial torsion correction study. Graphs and charts are included with design specifications of this equipment

Circuit Design

Circuit Design = Science + Art! Designers need a skilled "gut feeling" about circuits and related analytical techniques, plus creativity, to solve all problems and to adhere to the specifications, the written and the unwritten ones. You must anticipate a large number of influences, like temperature effects, supply voltages changes, offset voltages, layout parasitics, and numerous kinds of technology variations to end up with a circuit that works. This is challenging for analog, custom-digital, mixed-signal or RF circuits, and often researching new design methods in relevant journals, conference proceedings and design tools unfortunately gives the impression that just a "wild bunch" of "advanced techniques" exist. On the other hand, state-of-the-art tools nowadays indeed offer a good cockpit to steer the design flow, which include clever statistical methods and optimization techniques.Actually, this almost presents a second breakthrough, like the introduction of circuit simulators 40 years ago! Users can now conveniently analyse all the problems (discover, quantify, verify), and even exploit them, for example for optimization purposes. Most designers are caught up on everyday problems, so we fit that "wild bunch" into a systematic approach for variation-aware design, a designer's field guide and more. That is where this book can help! Circuit Design: Anticipate, Analyze, Exploit Variations starts with best-practise manual methods and links them tightly to up-to-date automation algorithms. We provide many tractable examples and explain key techniques you have to know. We then enable you to select and setup suitable methods for each design task - knowing their prerequisites, advantages and, as too often overlooked, their limitations as well. The good thing with computers is that you yourself can often verify amazing things with little effort, and you can use software not only to your direct advantage in solving a specific problem, but also for becoming a better skilled, more experienced engineer. Unfortunately, EDA design environments are not good at all to learn about advanced numerics. So with this book we also provide two apps for learning about statistic and optimization directly with circuit-related examples, and in real-time so without the long simulation times. This helps to develop a healthy statistical gut feeling for circuit design. The book is written for engineers, students in engineering and CAD / methodology experts. Readers should have some background in standard design techniques like entering a design in a schematic capture and simulating it, and also know about major technology aspects