EMITTER - International Journal of Engineering Technology
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Low Power, Area Efficient Architecture for Successive Cancellation Decoder
Full text linkPolar codes have recently emerged as an error-correcting code and have become popular owing to their capacity-achieving nature. Polar code based communication system primarily consists of two parts, including Polar Encoder and Decoder. Successive Cancellation Decoder is one of the methods used in the decoding process. The Successive Cancellation Decoder is a recursive structure built with the building block called Processing Element. This article proposes a low power, area-efficient architecture for the Successive Cancellation Decoder for polar codes. Successive Cancellation Decoder with code length 1024 and code rate 0.5 was designed in Verilog HDL and implemented using 45-nm CMOS technology. The proposed work focuses on developing an area-efficient Successive Cancellation Decoder architecture by presenting a new Processing Element architecture. The proposed architecture has produced about 35% lesser area with a 12% reduced gate count. Moreover, power is also reduced by 50%. A substantial reduction in the latency and improvement in the Technology Scaled Normalized Throughput value was observed
Text Mining for Employee Candidates Automatic Profiling Based on Application Documents
Full text linkOpening job vacancies using the Internet will receive many applications quickly. Manually filtering resumes takes a lot of time and incurs huge costs. In addition, this manual screening process tends to be inaccurate due to fatigue conditions and fails in obtaining the right candidate for the job. This paper proposed a solution to automatically generate the most suitable candidate from the application document. In this study, 126 application documents from a private company were used for the experiment. The documents consist of 41 documents for Human Resource and Development (HRD) staff, 42 documents for IT (Data Developer), and 43 documents for the Marketing position. Text Processing is implemented to extract relevant information such as skills, education, experiences from the unstructured resumes and summarize each application. A specific dictionary for each vacancy is generated based on terms used in each profession. Two methods are implemented and compared to match and score the application document, namely Document Vector and N-gram analysis. The highest the score obtained by one document, the highest the possibility of application to be accepted. The two methods’ results are then validated by the real selection process by the company. The highest accuracy was achieved by the N-Gram method in IT vacancy with 87,5%, while the Document Vector showed 75% accuracy. For Marketing staff vacancy, both methods achieved the same accuracy as 78%. In HRD staff vacancy, the N-Gram method showed 68%, while Document Vector showed 74%. In conclusion, overall the N-gram method showed slightly better accuracy compared to the Document Vector method. 
Numerical Study of a Wind Turbine Blade Modification Using 30° Angle Winglet on Clark Y Foil
Full text linkThe depletion of fossil fuels and the worsening environment motivate engineers and researchers to explore renewable energy resources. One of the promising renewable energy is wind energy. The wind turbine extracts wind energy to generate electricity. This study aims to modify a wind turbine blade using Clark Y foil to improve the lift force. The modification is employed by forming a winglet profile with a 30° angle on the foils tip. The result shows that the 30° winglet enlarges the lift coefficient to 1.3253 from 1.2795 of the original blade lift coefficient. 
Classification of Ischemic Stroke with Convolutional Neural Network (CNN) approach on b-1000 Diffusion-Weighted (DW) MRI
Full text linkWhen the blood flow to the arteries in brain is blocked, its known as Ischemic stroke or blockage stroke. Ischemic stroke can occur due to the formation of blood clots in other parts of the body. Plaque buildup in arteries, on the other hand, can cause blockages because if it ruptures, it can form blood clots. The b-1000 Diffusion Weighted (DW) Magnetic Resonance Imaging (MRI) image was used in a general examination to obtain an image of the part of the brain that had a stroke. In this study, classifications used several variations of layer convolution to obtain high accuracy and high computational consumption using b-1000 Diffusion Weighted (DW) MR in ischemic stroke types: acute, sub-acute and chronic. Ischemic stroke was classified using five variants of the Convolutional Neural Network (CNN) architectural design, i.e., CNN1–CNN5. The test results show that the CNN5 architectural design provides the best ischemic stroke classification compared to other architectural designs tested, with an accuracy of 99.861%, precision 99.862%, recall 99.861, and F1-score 99.861%
Experimental Study of Hydroformed Al6061T4 Elliptical Tube Samples under Different Internal Pressures
Full text linkIn order to achieve crack free elliptical shape under controlled conditions, an experimental set-up was designed and fabricated. This setup consists of three hydraulic cylinders, an intensifier, a hydraulic power pack, storage tanks, forming die, and all parts are controlled by a Programmable Logic Controller (PLC) system. The elliptical samples can be achieved through proper control of internal pressure and axial force with proper sealing. Experimental work has been carried out with different magnitudes of internal pressure and constrained conditions of axial force. Initially die of elliptical shape has been designed and modeled in Abaqus to successfully achieve the particular shape of the Al6061T4 tube under different internal pressure. The fabricated tube hydroforming machine set-up is highly effective for forming 0.5 mm-2 mm thick Al6061T4 alloy tube samples. The Experimental test has been carried out at 12.7 mm outer diameter, 175 mm length and 0.5 mm thick Al6061T4 samples. Bulge height parameters measured at different points of regular distance gap on the axial direction of the tube length and corner radius found at different pressures range of the samples are plotted under different internal pressures. Samples having an 18.7 mm major elliptical bulge were achieved during the experiment. The experimental data was validated by simulation results
Omnidirectional Stereo Vision Study from Vertical and Horizontal Stereo Configuration
Full text linkIn stereo vision, an omnidirectional camera has high distortion compared to a standard camera, so the camera calibration is very decisive in its stereo matching. In this study, we will perform stereo matching for an omnidirectional camera with vertical and horizontal configuration so that the result of the image's depth has a 360-degree field of view by transforming the image using a calibration-based method. The result is that by using a vertical camera configuration, the image can be stereo matched directly, but by configuring a horizontal image, it is necessary to carry out a different stereo-matching process in each direction. Stereo matching with the semi-global matching method has better image results than block matching with more image objects detectable by the semi-global block matching method with a maximum disparity value of 32 pixels and with a window size of 21 pixels
Design Analysis of Array of Dipole Transmitters for Wireless Power Transfer
Full text linkConsidered in this work are the radiation aspects of a radio-frequency wireless power transfer system. Using the halfwave dipole as a candidate of choice, the current distribution on the antenna is first evaluated and presented using the versatile electromagnetic numerical Method of Moment technique (MoM). Using the current distribution obtained from the kernel of integration, the radiation fields for the single dipole element was obtained. Also, the analysis is extended to uniformly space linear antenna arrays using broadside and ordinary endfire arrays as candidates of interest. The simulation results for the broadside and endfire arrays were presented for 5, 6, 7, 10, 20 and 30 array elements at 0.3, 0.4 and 0.5 inter-element spacing. The peak directivity of broadside array occurs at 30 elements, 0.5λ spacing, and exceeds endfire array peak directivity by 11.27%. In addition to the advantage of an improved directivity achieved by the 7-element broadside array, an improved peak sidelobe level (PSLL) with the lowest PSLL for 7, 20, and 30 elements broadside array occurring at -12.0534 dB, -12.4298 dB, -12.6642 dB, -13.2246 dB, and -13.2747 dB respectively
Dynamically Energy-Efficient Resource Allocation in 5G CRAN Using Intelligence Algorithm
Full text link5G network is the next generation for cellular networks to overcome the challenges and limitations of the 4G network. Cloud Radio Access Network(C-RAN) is providing solutions for cost-efficient and power-efficient solutions for the 5G network. The aim of this paper proposed an energy-efficient C-RAN to minimize the cost of the network by dynamically allocating BBU resources to RRHs as per facing traffic, and also minimize the energy consumption of centralized BBU resources that affect dynamically allocate of RRHs. Particle Swarm Optimization (PSO) algorithm is a Swarm Intelligence algorithm for optimization of mapping between BBU-RRH for resource allocation in C-RAN. The main objective of the paper is as per resource usage in C-RAN the BBU is put in the active or in-active mode to minimize energy consumption in C-RAN of 5G technology. As per our proposed C-RANapplication, the proposed PSO algorithm 90% minimizes energy consumption and maximizes energy efficiency compared with existing work
3D Visualization for Lung Surface Images of Covid-19 Patients based on U-Net CNN Segmentation
Full text linkThe Covid-19 infection challenges medical staff to make rapid diagnoses of patients. In just a few days, the Covid-19 virus infection could affect the performance of the lungs. On the other hand, semantic segmentation using the Convolutional Neural Network (CNN) on Lung CT-scan images had attracted the attention of researchers for several years, even before the Covid-19 pandemic. Ground Glass Opacity (GGO), in the form of white patches caused by Covid-19 infection, is detected inside the patient’s lung area and occasionally at the edge of the lung, but no research has specifically paid attention to the edges of the lungs. This study proposes to display a 3D visualization of the lung surface of Covid-19 patients based on CT-scan image segmentation using U-Net architecture with a training dataset from typical lung images. Then the resulting CNN model is used to segment the lungs of Covid-19 patients. The segmentation results are selected as some slices to be reconstructed into a 3D lung shape and displayed in 3D animation. Visualizing the results of this segmentation can help medical staff diagnose the lungs of Covid-19 patients, especially on the surface of the lungs of patients with GGO at the edges. From the lung segmentation experiment results on ten patients in the Zenodo dataset, we have a Mean-IoU score = of 76.86%, while the visualization results show that 7 out of 10 patients (70%) have eroded lung surfaces. It can be seen clearly through 3D visualization
Technical Analysis Based Automatic Trading Prediction System for Stock Exchange using Support Vector Machine
Full text linkStock exchange trading has been utilized to gain profit by constantly buying and selling best-performing stocks in a short term. Deep knowledge, time dedication, and experience are essential for optimizing profit if stock price fluctuations are analyzed manually. This research proposes a new trading prediction system that has the ability to automatically predict the accurate time for buying and selling stock using a combination of technical analysis and support vector machine (SVM). Technical analysis is used to analyze stock price fluctuation based on historical data by utilizing technical indicators such as moving average, Bollinger bands, relative strength index, stochastic oscillator, and Aroon oscillator. SVM maps inputs into higher dimensional spaces using non-linear kernel functions, making it suitable for various technical indicators implementation as inputs in stock trading prediction. Experimentation on five Indonesian stocks reveals that the combination of technical analysis and support vector machine is best suited for continuously fluctuated stocks, with the highest accuracy of 77.8%