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Distance Measurement and Energy Conservation Using Arduino Nano and Ultrasonic Sensor
Adekunle Adebola Olayinka,
Adekunle Adewale Oluwadamilare,
Ayo Femi Emmanuel
Issue:
Volume 5, Issue 2, December 2021
Pages:
40-44
Received:
23 November 2020
Accepted:
5 July 2021
Published:
13 July 2021
Abstract: This research work is designed as the distance measurement with energy conservation system using Ultrasonic sensor and Arduino NANO. Ultrasonic sensor emits high frequency sound waves, which reflects from target surfaces. This work utilized these sound waves through Ultrasonic sensor HC-SR04 to determine the change in distance and to apply it to detect the presence of an obstacle (person in this case), which in turns triggers a light bulb ON. Sonar waves are projected back to the receiving end of the sensor after which electrical pulses emitted from the sensor are sent into the Arduino NANO board, electrical signals are then sent to the LEDs and lighting system (bulbs). This work shows the importance of distance measurement to an automatic, hands-free environment control, efficient use of energy sources, and conservation of energy. The experimental results have shown minimal errors (< 3cm) for distances between 10cm and 100cm as the research deployment is most suitable within these distances. The results also describe the corresponding responses of the control system to the different physical conditions likely to be present. The above processes focus on electrical energy conservation as the light bulb comes ON when a person approaches the sensing system and goes OFF when the person leaves.
Abstract: This research work is designed as the distance measurement with energy conservation system using Ultrasonic sensor and Arduino NANO. Ultrasonic sensor emits high frequency sound waves, which reflects from target surfaces. This work utilized these sound waves through Ultrasonic sensor HC-SR04 to determine the change in distance and to apply it to de...
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Reliability Analysis and Improvement of Debre Berhan Power Distribution Network by Using Fuzzy Logic Optimization Technique
Issue:
Volume 5, Issue 2, December 2021
Pages:
45-55
Received:
1 June 2021
Accepted:
20 July 2021
Published:
2 August 2021
Abstract: This paper presents determination and allocation optimal number of sectionalizer switches using fuzzy based approach to improve the reliability of Berhan power distribution network. My intention to present in this study on the reliability assessment and method of improving reliability is that Debre Berhan power distribution network has frequent instructions. To improve customer reliability of power distribution system different methods can be used. Thus to complete this study MATLAB Simulink models of distribution network initial and optimal number of sectionalizer switch allocation are developed. Sheno 15kV feeder of the distribution network is selected for simulation studies to test the efficiency of the proposed approach. Simulation studies using ETAP software are carried out reliability indies of distribution network with and without optimal number of switch allocation. The simulation results show optimal allocation of sectionalizer switches improve the reliabity indices such as SAIFI, SAIDI and expected energy not supplied (EENS) and evaluates the reliability of Debre Berhan power distribution network using analytical techniques, software simulation and level of optimization achievable through the application optimal placement of switches. At the result of optimal placement of sectionalizers switches for sheno 15kV feeder SAIFI is improved by 12.76% and SAIDI are 41.61%. From the test result the proposed technique presents better interruption cost in comparison that of existing system 64,806.06$/yr. to 57,346.57$/yr. (which is 11.5% reduction) along with improvement in reliability indices and expected energy not supplied (EENS) was improved from 17828.014MWh/yr. to1533.75MWh/yr. (91.04%).
Abstract: This paper presents determination and allocation optimal number of sectionalizer switches using fuzzy based approach to improve the reliability of Berhan power distribution network. My intention to present in this study on the reliability assessment and method of improving reliability is that Debre Berhan power distribution network has frequent ins...
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Evaluation of Technical and Commercial Losses on Power Distribution Networks in Nigeria Using Statistical Analytical Method
Magnus Iheukwumere Uchechukwu,
Okafor N. C. Ephraim
Issue:
Volume 5, Issue 2, December 2021
Pages:
56-71
Received:
16 May 2021
Accepted:
21 July 2021
Published:
31 August 2021
Abstract: Losses are always present in every power distribution system from the source of supply to the point of utilization. The Nigerian electricity industry experiences so many challenges which contribute to the poor electric power supply to the citizens and many losses to the industry. The purpose of this dissertation work is to evaluate technical and commercial losses on power distribution networks in Nigeria using Statistical Analytical Method with Microsoft excel. The procedures followed in order to achieve the purpose of this work centered on the history of power sectors (Generation, Transmission and Distribution) in Nigeria, the theoretical review and the review of previous work done on the topic and different methods used to achieve the results. This work also centered on the data collected from a power distribution industry and its presentation, distribution loss equations and percentage distribution losses, calculations made on the 11kV distribution feeders and its billing efficiency. Monthly technical and commercial revenue losses and its net revenue losses for a period of one year were achieved. The percentage distribution losses and a chart of distribution losses against the supplied energy on the feeder were also achieved in this work with the challenges encountered. At the end of the work, summary of findings and conclusions were drawn with better contributions and recommendations to improve power industries in Nigeria.
Abstract: Losses are always present in every power distribution system from the source of supply to the point of utilization. The Nigerian electricity industry experiences so many challenges which contribute to the poor electric power supply to the citizens and many losses to the industry. The purpose of this dissertation work is to evaluate technical and co...
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Low Voltage Time-Resolved Emission (TRE) Measurements of VLSI Circuit
Shang Chih Lin,
Frank Yong
Issue:
Volume 5, Issue 2, December 2021
Pages:
72-76
Received:
2 May 2021
Accepted:
20 May 2021
Published:
4 September 2021
Abstract: Advanced technology nodes with small feature sizes and increased design complexity make it increasingly time-consuming to determine the root cause of yield loss. Several of the defects also occur inside a circuit making physical failure analysis (PFA) and electrical failure analysis (EFA) much more challenging. EFA has been instrumental in driving product yield and reliability for consumer products such as mobile phones and computer chips. It involves the use of state-of-the-art tools and techniques. One of the main changes EFA analyses is an enhancement of dynamic EFA in circuit failed in functional test. We propose a technique for advanced Electrical Failure Analysis (EFA) tool with a Superconducting Nanowire Single Photon Detector (SnSPD) system and its application to low voltage Time-Resolved Emission (TRE) measurements (also known as Picosecond Imaging Circuit Analysis, PICA) of scaled VLSI circuits with enhanced sensitivity for discussing Time Resolved Emission (TRE). In order to understand the figures of advantage that a single-photon detector should have to enable the acquisition of time resolved emission waveforms for low voltage applications. We will provide that measurements down to a low 1 V supply voltage were made possible by a careful optimization of the detector front-end electronics. We also characterized the emission from devices with different threshold voltages in order to understand how the emission contributions depend on this parameter and how this affects the resulting waveform. we hope to be able to show soon even better results that should allow continued application of the non-invasive TRE and PICA technology towards future scaled nodes with smaller gates and lower supply voltages.
Abstract: Advanced technology nodes with small feature sizes and increased design complexity make it increasingly time-consuming to determine the root cause of yield loss. Several of the defects also occur inside a circuit making physical failure analysis (PFA) and electrical failure analysis (EFA) much more challenging. EFA has been instrumental in driving ...
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EffCNet: An Efficient CondenseNet for Image Classification on NXP BlueBox
Priyank Kalgaonkar,
Mohamed El-Sharkawy
Issue:
Volume 5, Issue 2, December 2021
Pages:
77-87
Received:
17 August 2021
Accepted:
8 September 2021
Published:
12 October 2021
Abstract: Intelligent edge devices with built-in processors vary widely in terms of capability and physical form to perform advanced Computer Vision (CV) tasks such as image classification and object detection, for example. With constant advances in the field of autonomous cars and UAVs, embedded systems and mobile devices, there has been an ever-growing demand for extremely efficient Artificial Neural Networks (ANN) for real-time inference on these smart edge devices with constrained computational resources. With unreliable network connections in remote regions and an added complexity of data transmission, it is of an utmost importance to capture and process data locally instead of sending the data to cloud servers for remote processing. Edge devices on the other hand, offer limited processing power due to their inexpensive hardware, and limited cooling and computational resources. In this paper, we propose a novel deep convolutional neural network architecture called EffCNet which is an improved and an efficient version of CondenseNet Convolutional Neural Network (CNN) for edge devices utilizing self-querying data augmentation and depthwise separable convolutional strategies to improve real-time inference performance as well as reduce the final trained model size, trainable parameters, and Floating-Point Operations (FLOPs) of EffCNet CNN. Furthermore, extensive supervised image classification analyses are conducted on two benchmarking datasets: CIFAR-10 and CIFAR-100, to verify real-time inference performance of our proposed CNN. Finally, we deploy these trained weights on NXP BlueBox which is an intelligent edge development platform designed for self-driving vehicles and UAVs, and conclusions will be extrapolated accordingly.
Abstract: Intelligent edge devices with built-in processors vary widely in terms of capability and physical form to perform advanced Computer Vision (CV) tasks such as image classification and object detection, for example. With constant advances in the field of autonomous cars and UAVs, embedded systems and mobile devices, there has been an ever-growing dem...
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Tracking Automotive Electronics Related Sensory and Their Traceability by Boundary Scan Technology
Wang Shun Shen Peter,
Wang Yin Tien,
Chao Chong Lii,
Yang Wei Bin,
Lee Tzung Hang
Issue:
Volume 5, Issue 2, December 2021
Pages:
88-97
Received:
8 November 2021
Accepted:
22 November 2021
Published:
24 November 2021
Abstract: This paper proposes several Python-based test methods to study a series of MCU-associated sensors. In light of today's automotive electronics, many electric systems are involved in modularized bare dies such as power management ICs along with embedded programming. As to the application of autonomous driving like the ADAS system, having many Multiple-Chips Modules (MCM) which are popular in SoC related functional boards. It is necessary to have these electrical systems follow stringent safety standards and regulations by the International Electrotechnical Commission (IEC). That is to ensure the electronic systems to be designed, implemented, operated within safety range. That is traceable according to the prerequisite Safety Integrity Level (SIL) besides the Automotive Safety Integrity Level (ASIL) towards five classes. These classes further evolved into higher requirements such as IEC-61508 and more recently the ISO-26262. All of these, have driven many companies to research and develop a suite of methods and strategies to solve some of the “reliability” associated issues, especially in the area of autonomous driving. This paper proposes the boundary scan based test methodology to cop with government’s regulations by tracking some of the major sensors in responses to motion, temperature and dynamic forces based on a JTAG’s sensor board in case study A. Thereafter, using an NXP’s automotive board to trace on board electronics, mainly the CPU and MCU via the MODBUS is made possible to log and record test results through VB.XML.NET. These languages speak uniformly to the relational data base in one “DataSet” by in-memory cache of the data retrieved from a database, in case study B. Both are realized by the JTAG’s Functional Test (JFT) system, to log the “pass or fail” results in a sequential execution. This paper illustrates how-to reach this goal through the process in use of the public-domain based open frame-ware, and to demonstrate them on a JTAG’s Provision platform throughout the development stages.
Abstract: This paper proposes several Python-based test methods to study a series of MCU-associated sensors. In light of today's automotive electronics, many electric systems are involved in modularized bare dies such as power management ICs along with embedded programming. As to the application of autonomous driving like the ADAS system, having many Multipl...
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