Fast, area-efficient 32-bit LNS for computer arithmetic operations

PhD ThesisThe logarithmic number system has been proposed as an alternative to floating-point. Multiplication, division and square-root operations are accomplished with fixedpoint arithmetic, but addition and subtraction are considerably more challenging. Recent work has demonstrated that these operations too can be done with similar speed and accuracy to their floating-point equivalents, but the necessary circuitry is complex. In particular, it is dominated by the need for large lookup tables for the storage of a non-linear function. This thesis describes the architectures required to implement a newly design approach for producing fast and area-efficient 32-bit LNS arithmetic unit. The designs are structured based on two different algorithms. At first, a new cotransformation procedure is introduced in the singularity region whilst performing subtractions in which the technique capable to generate less total storage than the cotransformation method in the previous LNS architecture. Secondly, improvement to an existing interpolation process is proposed, that also reduce the total tables to an extent that allows their easy synthesis in logic. Consequently, the total delays in the system can be significantly reduced. According to the comparison analysis with previous best LNS design and floating-point units, it is shown that the new LNS architecture capable to offer significantly better in speed while sustaining its accuracy within floating-point limit. In addition, its implementation is more economical than previous best LNS system and almost equivalent with existing floating-point arithmetic unit.University Malaysia Perlis: Ministry of Higher Education, Malaysia

The Effectiveness of Virtual Reality Technologies to Enhance Learning and Training Experience: During the Covid-19 Pandemic and Beyond

During the global pandemic, we now live and work differently, forcing government decision-makers to find innovative, new ways to learn and train that will still be feasible during the pandemic. As we move slowly away from the Covid-19 shadow, upskilling and reskilling students are crucial for learning and professional development. Consequently, the pandemic has highlighted the necessity for transforming distance learning and opened new opportunities for immersive virtual exchanges. Nowadays, virtual reality (VR) has a significant role in fighting the Covid-19 pandemic. This paper proposes the potential of integrating VR technology in learning and training perspectives as an effective strategy or approach used to complete students' experiences. The purpose of this study is to develop and design a virtual environment (VE) that guides students through the educational process at high levels of performance. The focus of this study was to evaluate the effectiveness of a VR simulation for students. In this study, we have designed a VR simulation using Unity 3D software connected with the Hp reverb G2 headset. We collected data by a survey which indicates 50 samples attending a soft skills training course. The results revealed that virtual learning (V-learning) in VR is much more interactive and effective than traditional learning methods like E-learning and classrooms. This study contributes a significant role that the adoption of VR technology can be extremely beneficial to educators in helping students enhance their skills and continue the educational process in universities

High Performance Systolic Array Core Architecture Design for DNA Sequencer

This paper presents a high performance systolic array (SA) core architecture design for Deoxyribonucleic Acid (DNA) sequencer. The core implements the affine gap penalty score Smith-Waterman (SW) algorithm. This time-consuming local alignment algorithm guarantees optimal alignment between DNA sequences, but it requires quadratic computation time when performed on standard desktop computers. The use of linear SA decreases the time complexity from quadratic to linear. In addition, with the exponential growth of DNA databases, the SA architecture is used to overcome the timing issue. In this work, the SW algorithm has been captured using Verilog Hardware Description Language (HDL) and simulated using Xilinx ISIM simulator. The proposed design has been implemented in Xilinx Virtex -6 Field Programmable Gate Array (FPGA) and improved in the core area by 90% reduction

High Performance Systolic Array Core Architecture Design for DNA Sequencer

This paper presents a high performance systolic array (SA) core architecture design for Deoxyribonucleic Acid (DNA) sequencer. The core implements the affine gap penalty score Smith-Waterman (SW) algorithm. This time-consuming local alignment algorithm guarantees optimal alignment between DNA sequences, but it requires quadratic computation time when performed on standard desktop computers. The use of linear SA decreases the time complexity from quadratic to linear. In addition, with the exponential growth of DNA databases, the SA architecture is used to overcome the timing issue. In this work, the SW algorithm has been captured using Verilog Hardware Description Language (HDL) and simulated using Xilinx ISIM simulator. The proposed design has been implemented in Xilinx Virtex -6 Field Programmable Gate Array (FPGA) and improved in the core area by 90% reduction

Comparison of edge detection techniques for M7 subtype Leukemic cell in terms of noise filters and threshold value

This paper will focus on the study and identifying various threshold values for two commonly used edge detection techniques, which are Sobel and Canny Edge detection. The idea is to determine which values are apt in giving accurate results in identifying a particular leukemic cell. In addition, evaluating suitability of edge detectors are also essential as feature extraction of the cell depends greatly on image segmentation (edge detection). Firstly, an image of M7 subtype of Acute Myelocytic Leukemia (AML) is chosen due to its diagnosing which were found lacking. Next, for an enhancement in image quality, noise filters are applied. Hence, by comparing images with no filter, median and average filter, useful information can be acquired. Each threshold value is fixed with value 0, 0.25 and 0.5. From the investigation found, without any filter, Canny with a threshold value of 0.5 yields the best result

Comparison of edge detection techniques for M7 subtype Leukemic cell in terms of noise filters and threshold value

This paper will focus on the study and identifying various threshold values for two commonly used edge detection techniques, which are Sobel and Canny Edge detection. The idea is to determine which values are apt in giving accurate results in identifying a particular leukemic cell. In addition, evaluating suitability of edge detectors are also essential as feature extraction of the cell depends greatly on image segmentation (edge detection). Firstly, an image of M7 subtype of Acute Myelocytic Leukemia (AML) is chosen due to its diagnosing which were found lacking. Next, for an enhancement in image quality, noise filters are applied. Hence, by comparing images with no filter, median and average filter, useful information can be acquired. Each threshold value is fixed with value 0, 0.25 and 0.5. From the investigation found, without any filter, Canny with a threshold value of 0.5 yields the best result