Nor Hisham Hamid

Performance analysis of FPGA based Sobel edge detection operator

Edge detection operation is an essential part in the field of image processing. There are few ways to improve the performance of edge detection. This paper proposes a FPGA-based approach Sobel edge detection. An image is captured by a CMOS camera and converted into RGB color space and the image is converted into grayscale to obtain image intensity for edge detection. The proposed Sobel edge detection operator is model using of Finite State Machine (FSM) which executes a matrix area gradient operation to determine the level of variance through different of pixels and display the result on a monitor. The whole process is performed in the hardware level that utilizes the resources of FPGA board. The result shows good performance of edge detection with 27 MHz clock operation.

Time-Domain Modeling of Low-Frequency Noise in Deep-Submicrometer MOSFET

1/f noise and random telegraph signal (RTS) noise are increasingly dominant sources of low-frequency noise as the MOSFET enters the nanoscale regime. In this study, 1/f noise and RTS noise in the n-channel MOSFET are modelled in the time domain for efficient implementation in transient circuit simulation. A technique based on sum-of-sinusoids models 1/f noise while a Monte Carlo based technique is used to generate RTS noise. Low-frequency noise generated using these models exhibits the correct form of noise characteristics as predicted by theory, with noise parameters from standard 0.35-mum and 35-nm CMOS technology. Implementation of the time-domain model in SPICE shows the utility of the noisy MOSFET model in simulating the effect of low-frequency noise on the operation of deep-submicrometer analog integrated circuits.

Electricity forecasting for small scale power system using fuzzy logic

Electricity supply to Universiti Teknologi PETRONAS (UTP) comes from gas district cooling (GDC) plant as a primary source of energy and utility company Tenaga Nasional Berhad (TNB) as a backup. With a maximum capacity of 8.4 MW which comes from 2 nos of gas turbine generators rated at 4.2 MW each, this work aims to forecast short term electricity demand of the plant. As a sole customer of the plant, UTP 2008 electricity demand data is being used as a basis to design a forecast model using Fuzzy Logic. With the forecast model, it will help GDC for pre-planned scheduling and maintenance of the plant and also as guidance for the daily operation of the plant. The proposed fuzzy logic model is applied to obtain one week forecast load demand data for GDC. The forecast accuracy is obtained and it is represented in mean absolute percentage error (MAPE).

Electricity forecasting for small scale power system using artificial neural network

Short term load forecasting (STLF) method is the basis of efficient operation for power system. It has an important role in planning and operation of power system. In this paper, a practical STLF using artificial neural network method (ANN) for Gas District Cooling (GDC) power plant of Universiti Teknologi PETRONAS (UTP) is presented. As a sole customer of GDC power plant, the load data from 2006 till 2009 are gathered and utilized for model developments. The developed models forecast electricity load for one week ahead. The paper proposes a method of a multilayer perceptron neural network and it is trained and simulated by using MATLAB. The models have been tested with the actual load data and perform relatively good results.

A performance comparison study on multiplier designs

This study investigates the relative performances of Array, Wallace, Dadda and Reduced Area multipliers for several synthesis optimization modes. All multiplier designs were modeled in Verilog HDL and synthesized based on the TSMC 0.35-micron ASIC Design Kit standard cell library. Performance data was extracted after logic synthesis in LeonardoSpectrum for Area, Speed and Auto optimization modes. Findings indicate that the Dadda multiplier may not always have a speed advantage over Wallaces design, but depends greatly on the optimization effects in gate-level synthesized design. Results for comparison of 32×32-bit variants indicate that the Wallace scheme is well suited for high-speed applications, independent of area constraints, while the Dadda and Reduced Area designs deliver best speed when synthesized to minimize area or logic usage.

Microfluidic Platform for Cell Isolation and Manipulation Based on Cell Properties

In molecular and cellular biological research, cell isolation and sorting are required for accurate investigation of a specific cell types. By employing unique cell properties to distinguish between cell types, rapid and accurate sorting with high efficiency is possible. Though conventional methods can provide high efficiency sorting using the specific properties of cell, microfluidics systems pave the way to utilize multiple cell properties in a single pass. This improves the selectivity of target cells from multiple cell types with increased purity and recovery rate while maintaining higher throughput comparable to conventional systems. This review covers the breadth of microfluidic platforms for isolation of cellular subtypes based on their intrinsic (e.g., electrical, magnetic, and compressibility) and extrinsic properties (e.g., size, shape, morphology and surface markers). The review concludes by highlighting the advantages and limitations of the reviewed techniques which then suggests future research directions. Addressing these challenges will lead to improved purity, throughput, viability and recovery of cells and be an enabler for novel downstream analysis of cells.

An FPGA Implementation of Gradient Based Edge Detection Algorithm Design

Edge detection operation is a method to detect the presence of object image that commonly used in the field of image processing. The most well known technique for edge detection is gradient-based. There are number of methods that have been used to make an implementation of a gradient-based edge detection algorithm design. This paper proposes a design and implementation of gradient based edge detection algorithm using of Sobel operator. An image is captured by a CMOS camera and converted into grayscale to obtain image intensity for edge detection. The Sobel edge detection operator is controlled by Finite State Machine (FSM) which executes a matrix area gradient operation to determine the level of variance through different of pixels and display the result on a monitor. The whole process is performed in the hardware level and implemented on an Altera field programmable gate array platform. The result shows good performance of edge detection with 27MHz clock operation which is able to detect just within 2ms.

A Cross-Layer Opportunistic MAC/Routing protocol to improve reliability in WBAN

Wireless Body Area Network (WBAN) is a modern technology having a wide-range of applications. Reliability is a key performance index for WBANs, especially for medical applications. An unreliable WBAN may severely affect the patient under observation. Main causes of unreliability are inefficient routing, low transmission range, body shadowing and environmental interference. We propose a Cross-Layer Opportunistic MAC/Routing (COMR) protocol that can improve the reliability by using a timer based approach for the relay selection mechanism. The value of this timer depends on Received Signal Strength Indicator (RSSI) and residual energy. The selected relay node will have the highest residual energy and will be closest to the sink as compared to other possible relay nodes. We evaluate the performance of the proposed mechanism in terms of network lifetime, Packet Delivery Ratio (PDR), End-To-End (ETE) delay, and energy used per bit. Results depict that COMR protocol shows improvement in terms of reliability, energy efficiency, ETE delay and network lifetime in a WBAN as compared to Simple Opportunistic Routing (SOR).

Design and modeling of MEMS resonator for magnetic field sensing using hybrid actuation technique

A novel design of 0.751MHz MEMS resonant magnetic field sensor of mass 0.775pg based on hybrid actuation technique (Lorentz force and Electrostatic force) is presented and simulated using Coventor Ware and CADENCE simulators. The sensor consists of Aluminum paddle resonator, two supporting beams, driving electrodes, sensing electrode and silicon substrate with a capacitive CMOS readout amplifier. Working in a resonant condition, the sensors vibration amplitude is converted into the sensing capacitance change, which reflects the outside magnetic flux-density. Based on the simulation, the key structure parameters are optimized and the resonant frequency is estimated. The results of the device are in accordance with the theoretical results of the designed model. The resolution of the sensor is 1 nT. The results indicate its sensitivity more than 0.01 nV/nT, when operating at a normal atmosphere. The sensitivity and resolution can be enhanced through vacuum packaging.

Investigation on high neutral earthing resistor temperature when islanded generator connected to utility grid

Electricity supply to Universiti Teknologi PETRONAS (UTP) is provided by two generating units at gas district cooling (GDC) plant located in the campus. Under normal operation, UTP power system is operating in island mode and during emergency, it will be connected to utility grid of Tenaga Nasional Berhad (TNB). Each generating unit is grounded through neutral earthing resistor (NER). It has been observed that NER temperature become high when generator operating in parallel with the grid. Investigation reveals that triplen harmonics currents continuously flow through NER during island and parallel operation. Higher triplen harmonics currents are noticed during parallel operation as compared to island mode of operation. High NER temperature is caused by increase in triplen harmonics currents that flow through it. The above phenomena are described in this paper together with some proposed measures to overcome the problem.