Universiti Teknikal Malaysia Melaka: UTeM Open Journal System
Not a member yet
2735 research outputs found
Sort by
Measurement of Carbon Dioxide Using Low-Cost & Compact Spectroscopy Based Gas Sensor
Get PDFA compact and low-cost gas sensor using absorption spectroscopy for Carbon Dioxide (CO2) measurement is presented. The sensing principle is based on open-path direct absorption spectroscopy in the mid-infrared range. The improved reflective structure of optical gas sensor consists of low cost and compact components, such as filament emitter, multispectral pyroelectric detector, Calcium Fluoride (CaF2) window and aluminium curve reflective surface. In the previous investigation, the optimized gas cell structure was simulated using ZEMAX®12 software prior to fabrication for measuring CO2 gas concentration. The developed gas sensing system using the optimized gas cell structure has shown the capability of accurately detecting CO2 concentration. The sensor utilizes a CaF2 narrow bandpass (NBP) filter for detection of CO2 gas with no cross-sensitivity with other gases present in the gas cell. The repeatability of sensor’s response of detecting CO2 was tested with response times were calculated as being less than 1 second
Low-Rank Representation for Internet Traffic Reconstruction Using Compressive Sampling
Get PDFWe study compressive sampling for internet traffic reconstruction. Compressive Sampling (CS) requires that the traffic satisfies the low-rank feature. Low-rank states that traffic matrix can be represented in the right domain which the entire necessary information is concentrated in a low number of coefficients. In this paper, we compared three low-rank representation, which are Principal Component Analysis (PCA), Singular Value Decomposition (SVD), and Singular Value Decomposition Mean (SVDM). This low-rank representation is applied to four CS reconstruction algorithms, namely: Sparsity Regularized Singular Value Decomposition (SRSVD), Singular Value Decomposition L1 (SVDL1), Iteratively Reweighted Least Square (IRLS), Orthogonal Matching Pursuit (OMP), and Interpolation. The SVD outperforms the others low-rank representation techniques when used together with SRSVD, SVDL1, IRLS, and Interpolation. The SVDM gives the best NMAE when applied to the OMP. The computational times is linear with the number of the rank matrix. For all reconstruction algorithms, SVDM takes the least computational times
Classification of EEG Signal for Body Earthing Application
Get PDFStress is the way our body reacts to the threat and any kind of demand. Stress happens when your nervous system releases the stress hormones including adrenaline and cortisol that lead to an emergency response of the body. Body earthing technique is used to resolve this problem. Body earthing is a method that is used to neutralize positive and negative charge in the human body by connecting to the earth. EEG signals can be used to verify the positive effect of body earthing. This project focuses on the classification of EEG signals for body earthing application. First, EEG signals from human brainwaves were recorded by using Emotive EPOC Headset, before and after body earthing for the 30 subjects. The alpha band and the Beta band were filtered by using Band-pass filter ‘Butterworth’. After filtering, the threshold of signal amplitude was set in the range of -100 μV to 100 μV in order to remove the noise or artifact. For feature extraction, Short-time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT) were used. Lastly, the Artificial Neural Network (ANN) model is employed to classify EEG signal taken from samples, before and after the body earthing. A number of neurons chosen for this project are 55 with the mean square error 0.0023738. The result showed that Alpha band signals before body earthing are low compared to after body earthing. Whereas, for the Beta band signals, the result before body earthing is high compared to after body earthing. The increased signals of the Alpha band show that subjects are in relax state, while the decreased of Beta band signals shows the sample in stress state. These results imply for both features of STFT and CWT. Based on the confusion matrix, the result for the ANN classification yields 86.7% accuracy
Semiconductor Nanowires Biosensors for Highly Selective and Multiplexed Detection of Biomolecules
Get PDFThe surface modification of Nano-structure has allowed specific and selective detection to be made on nano structures devices. Current study, a nanowire was surface engineered with the potential of silicon nanowires biosensors (SiO2) which enhance the biosensor activity especially identifying single-stranded bio-molecular such as E.coli DNA. The device's capabilities were studied based on it response n electrochemical activities of the terminal group of the surface modification agent. NH2 -terminated APTES) to provide rigid chemistry between the DNA organic and Si inorganic link of a biomolecule single_stranded ssDNA probe and SiO2_APTES link nanostructure. Thus, the study demonstrates that silicon nanowire sensing capability to discriminate molecular probe to that of molecule target of supra-genome 21 mers salmonella due to sensitive surface chemistries that made distinguishing the two species. The device captured the molecule precisely; the approach took the advantages of strong binding chemistry created between APTES and biomolecule. The results indicated how modifications of the nanowires provide sensing capability with strong surface chemistries that can lead to specific and selective target detection
Adoption of E-hailing Applications: A Comparative Study between Female and Male Users in Thailand
Get PDFE-hailing, a process of ordering a taxi via mobile devices, has become popular in Thailand recently. This study focuses on applying Diffusion of Innovations Theory and Technology Acceptance Model in examining the factors affecting adoption of e-hailing applications in Thailand. The objective of this comparative study is to find significant factors influencing female and male users to adopt E-hailing applications. The hypotheses are constructed to test the influence of five factors on consumers’ attitude. This study uses a survey to collect data from 200 female and 200 male users who have experienced using e-hailing applications. The results indicate that the relative advantages and ease of use have an influence towards the adoption of e-hailing applications in both genders. Interestingly, social influence and physical security influence the adoption of e-hailing applications for among male users only
A Study Effect of Specific Absorption Rate in Human Head Model due to Electromagnetic Exposure
Get PDFThis study presents a numerical analysis of the specific absorption rate in the human head model due to electromagnetic exposure. A set of dipole antennas operating at 1800MHz and 2600MHz were located at the ear of human head model to investigate the effect of frequency on human head model. The maximum average of 1gram and 10gram of tissue have been presented to show the effect of the electromagnetic field in the human head model. A comparison of the mass averaged SAR in the head shows the 1g of SAR is quintuple at both 1800MHz and 2600MHz respectively
Requirements Defects Techniques in Requirements Analysis: A Review
Get PDFDefects existing in the systems due to poorly identified requirements defects are viewed as the major factors leading to system failure, especially if the requirements defects are not identified or addressed until at the later stage of software development life cycle. In response to this, several attempts have been made to identify defects during the requirements analysis process. This paper presents a review of the various techniques to handle requirements defects in the requirements analysis activity. These techniques are categorised into four categories, namely reading, inspection, analysis and automated tool. It was found that these techniques have different focus and lack of emphasis on the needs of the industry. This study provides the basis for future research aiming at developing an approach to automate the process of requirements defects handling
Image-Based Vehicle Verification Using Steerable Gaussian Filter
Get PDFThis paper presents a new feature descriptor for a vehicle verification system. The Steerable Gaussian Filter (SGF) is utilized to generate an image feature descriptor. The descriptor is constructed by concatenating the statistical parameters of the SGF filtered output. The Maximum Likelihood Estimation (MLE) estimates the statistical estimator using a heavy-tailed and bell-shaped distribution assumption such as Gaussian, Laplace, or Generalized Gaussian Distribution (GGD). A classifier assigns a class label of the vehicle hypothesis based on an image descriptor. As documented in the experimental results, the proposed feature descriptor achieves a promising result, and it outperforms the state-of-theart vehicle verification systems, making it a very competitive candidate in the practical applications
Coverage Probability Optimization Utilizing Flexible Hybrid mmWave Spectrum Slicing-Sharing Access Strategy for 5G Cellular Systems
Get PDFSpectrum and infrastructure sharing among multiple mobile network operators is a vital solution to substantially and sustainably improves cost and network efficiency. However, such approach may face several challenges, such as the imposed restrictions on the independence of operators, the complexity of spectrum management policies and the mutual interference issues among operators. Therefore, in this study, we propose a flexible hybrid spectrum access strategy, namely, hybrid millimetre wave (mmWave) spectrum slicing–sharing access (HMSSSA), to optimise the coverage probability via distributing the spectrum in a hybrid manner. Accordingly, the interference problem can be addressed, and the coverage probability can be improved. In the proposed strategy, the spectrum splits into three different classes: (i) exclusive right assigned to all of the operators, (ii) semi-pooled among all the operators and (iii) fully pooled (shared) as open access among all the operators with the ultra-flexibility feature. Adaptive hybrid multi-state mmWave cell selection (AHMMC-S) scheme is adopted to optimally associate a typical user to the mmWave base station (mBS) that offers high signal-to-interference plus noise ratio. Numerical results demonstrate that our proposed strategy reduces the outage probability significantly, provides a degree of freedom to the subscribers to optimally select mBS with high signal quality and maintains an acceptable level of mBS densification
Design and Development of Deep Learning Convolutional Neural Network on an Field Programmable Gate Array
Get PDFThis paper presents the design and development of Convolutional Neural Network on Field Programmable Gate Array. In the recent work of deep learning Convolutional Neural Network, CNN is a challenging research area in both software and hardware implementation. Software implementations tend to be prohibitively slow considering that most of the neural networks run on sequentially operation architecture. Thus, the objective of this work is to design and develop deep learning CNN on FPGA based on the premise that hardware implementations that perform parallel computation of each neuron in the layers can be made faster. This work focuses on handwriting recognition where the machine has the ability to receive and interpret intelligible handwritten input from the sources. The speed of the CNN implemented on an FPGA was analyzed. Digits and numbers were successfully recognized by the developed system