University of Technology Malaysia
Universiti Teknologi Malaysia Institutional RepositoryNot a member yet
70456 research outputs found
Sort by
Sales contract of commodity murabahah via tawarruq arrangement in supporting maqasid of shariah in economy
No full textCommodity Murabahah contract via Tawarruq arrangement is a replacement of debatable contract of Bay al ‘Inah where the later involving only to two parties, to which involving the third party in order to obtain cash. Commodity Murabahah via Tawarruq arrangement also play important role in supporting the financial and economic activities in Malaysia for depository purposes such as Term Deposit-i thus it generate economic activities and promoting the growth of related commodity. On the other hand, the financing product such as Term Financing-i from Islamic financial institutions is example of fund application or utilization from the Islamic Bank. This product offered to retail customers for their personal need and usage. The cash facility will support the business expansion of Small Medium Enterprise (SME) or small business owner, and grow their business which later will contributing to increase of Zakat’s collection. By offering the Islamic Finance Product, not only it obliges in obeying Allah’s instruction in avoiding riba’ (usury), the applicant also may use for the purpose of better standard of living, improving financial status and avoiding illegal loan shark. Thus, this practice also accordance to the objective of Maqasid Shariah in protecting the life, as well as protecting the wealth
Lightweight IoT based indoor positioning for Guard Touring System
No full textAn Indoor Positioning System (IPS) with Internet of Things (IoT) platform for a Guard Touring System (GTS) application is developed to track in real-time the guards’ whereabouts in an indoor setting when they perform their patrolling duties. The developed system comprises of Bluetooth Low Energy (BLE) beacons, mobile application and Node-RED IoT platform. BLE beacons are used to collect position data. The position information from the beacons captured by the developed mobile phone application is then transmitted using MQTT broker service to reach the Node-RED cloud platform for analysis of the information and generating a real-time end-user display dashboard. The real-time position data is also stored in MongoDB database platform for future reference. Two methods are used to estimate the indoor positioning of the guards which are machine learning using Linear Regression model and BLE Media Access Control (MAC) Identifier. The findings show the BLE MAC Identifier method provides a high accuracy of 98% and the least delay in decision time, which can be as fast as 0.5 s. The method is also more cost-effective as it uses lesser number of devices to achieve high accuracy indoor positioning estimation
Effect of directional spreading angles on the wave hydrodynamic coefficients for vertical cylinder
No full textIn the prediction of accurate wave force, the consideration of short-crested wave is important in representing the actual ocean condition. Owing that, nonlinear wave characteristics are expected to change the flow properties when the wave passes the structures, which showing these characteristics are crucial to be accounted. However, literature reported that the overestimation on the design of marine structures has shown a lower reliability in the wave force prediction considering long-crested wave. Further in detail, the effect of wave directionality and directional spreading angle from the actual sea conditions, i.e. the short-crested waves, have been neglected in a way. To prove the validity of this statement, an experimental investigation was conducted to quantify the effects of wave directionality on the wave forces and to propose the hydrodynamic coefficients incorporated the effect of directional spreading angles. The wave directionality in term of directional spreading angles were considered, ranging from 5 to 45°. Then, the measured wave surface elevation and wave forces were processed using least square method to compute the hydrodynamic coefficients and to evaluate the wave forces. To quantify the effect, force ratio factor was adopted. Based on the finding, short-crested waves led to 20 % force reduction as compared to the long-crested. On top of that, a reduction of 1.12 % of wave force has also been observed for every one-degree incremental of the directional spreading angle. As conclusion, the wave directionality was found contributing to the reduction of wave force which may provide new improvement on the accuracy of wave force formulation for the design of lean marine structures
A machine learning-based classification model to identify the effectiveness of vibration for µEDM
No full textMicro electro-discharge machining (µEDM) uses electro-thermal energy from repetitive sparks generated between the tool and workpiece to remove material from the latter. However, one of the bottlenecks of µEDM is the phenomenon of short circuits due to the physical contact between the tool and debris (formed during the erosion of the workpiece). Adequate flushing of the debris can be achieved by applying low amplitude high-frequency vibration to the workpiece. This study, however, shows that the application of vibration does not yield beneficial results for the µEDM for all the parametric conditions. This research used an off-the-shelf piezo vibrator as the high-frequency, low amplitude vibration source to the workpiece during the µEDM process. The experiments were conducted with and without vibration with the variation of applied discharge energy and µEDM speed. The samples were characterized using scanning electron microscopes to gather various data related to µEDM outputs. The results of this study revealed that vibration-assisted µEDM becomes less effective as the discharge energy is increased (primarily by increasing the capacitor value of the RC pulse generator). Similarly, the reduction of the occurrence of the short circuit was profound when the low discharge energy level with low voltage and low capacitor setting of the RC Pulse generator was used. The overall scale of the overcut with various discharge energy and µEDM speed varied from 15.5 µm to 42 µm for the conventional µEDM process. However, the scale above slightly reduced to 14.5 µm to 39 µm using an ultrasonic vibration device. Also, the taperness of the machined hole was slightly reduced by applying the vibration device during the µEDM operation (overall average of ~7%)
Time series forecasting model of future spectrum demands for mobile broadband networks in Malaysia, Turkey, and Oman
No full textMobile broadband (MBB) services are rapidly growing, causing a massive increase in mobile data traffic growth. This surge in data traffic is due to several factors (such as the massive increase of subscribers, mobile applications, etc.) which have led to the need for more bandwidth. Mobile service providers are constantly improving their network efficiency by upgrading current networks and investing in newer mobile network generations. However, these improvements will not be enough to accommodate the future spectrum demands. This paper proposes a time series forecasting model to analyze future spectrum demands based on the spectrum efficiency growth of MBB networks. This model depends on two key input data: the average spectrum efficiency per site and the number of sites per technology. The model is used to predict the spectrum efficiency growth of three countries (Turkey, Malaysia, and Oman) from 2015 to 2025. The proposed model is compared with various traditional statistical models such as the Moving Average (MA), Auto-Regression (AR), Autoregressive–Moving-Average (ARMA), and Autoregressive Integrated Moving Average (ARIMA). The forecasted results indicate that the average spectrum efficiency and growth will continue to rise multiple times by 2025 compared to 2015. The data from this prediction model can be used as input data to forecast the required spectrum needed in future for any specific country. This study further contributes to the network planning of future mobile networks for Fifth Generation (5G) and Sixth Generation (6G) technology. The proposed model obtains higher accuracy (by 90%) compared to other models. The proposed model is also applicable to any country, especially when new wireless communication technologies emerge in future. It is customizable and scalable since spectrum regulators can add additional metrics that positively contribute towards accurately estimating future spectrum efficiency growth
Major l1 interference issues with the productive and receptive skills for Saudi EFL learners
No full textThere are tremendous efforts presently to make the English language as the lingua franca in many Arabic speaking countries especially in the Gulf (Zughoul, 2003). However, the acquisition of the TL (Target Language) is not easy for Arab students, due to the huge differences between the L1 and L2 (Noor, 1996; Al-Bouq, 1988). The role of the mother tongue has an integral part in the SLA (Second Language Acquisition) (Stern, 1992). This study focuses on both; the productive and the receptive skills (Speaking, Writing, Reading, and Listening) to show how L1 interference enters the Saudi L2 learners’ classroom and the effects it has on L2 acquisition. As L1 interference or language transfer (Gass & Selinker, 1983) is a significant topic in applied linguistics and TESOL and has played a major role in SLA (Stern, 1992 and Ellis, 1985). From the result of the interview, all the participants had agreed that L1 interference is affecting the acquisition of the TL
PET-based instant inkjet-printed 4×4 butler matrix beamforming network
No full textIn this paper, a novel planar Butler matrix (BM) utilizing only 3 dB hybrid couplers and a crossover are implemented using a low-cost silver-nano inkjet printing technique. Unlike in the conventional design of BM where a phase shifter is required, this novel design does not need a phase shifter to be implemented. However, the use of delicate substrates like polyethylene terephthalate (PET) in the design makes it unique. This is not possible with the conventional thermal curing process, as PET substrate cannot be subjected to an excessively feverish temperature. The results obtained show good return loss and transmission coefficients better than 26.10 and 23.54 dB, respectively, at the center frequency. Similarly, an amplitude imbalance of less than 2.4 dB with phase mismatch within +/- 0.25 degrees is achieved at the center frequency. The BM has a -10 dB bandwidth of 24.79% with a beam pattern produced at +13 degrees , -40 degrees, +40 degrees, and -13 degrees when ports 1-4 of the BM are energized
Transfer learning based performance comparison of the pre-trained deep neural networks
No full textDeep learning has grown tremendously in recent years, having a substantial impact on practically every discipline. Transfer learning allows us to transfer the knowledge of a model that has been formerly trained for a particular task to a new model that is attempting to solve a related but not identical problem. Specific layers of a pre-trained model must be retrained while the others must remain unmodified to adapt it to a new task effectively. There are typical issues in selecting the layers to be enabled for training and layers to be frozen, setting hyperparameter values, and all these concerns have a substantial effect on training capabilities as well as classification performance. The principal aim of this study is to compare the network performance of the selected pre-trained models based on transfer learning to help the selection of a suitable model for image classification. To accomplish the goal, we examined the performance of five pre-trained networks, such as SqueezeNet, GoogleNet, ShuffleNet, Darknet-53, and Inception-V3 with different Epochs, Learning Rates, and Mini-Batch Sizes to compare and evaluate the network’s performance using confusion matrix. Based on the experimental findings, Inception-V3 has achieved the highest accuracy of 96.98%, as well as other evaluation metrics, including precision, sensitivity, specificity, and f1-score of 92.63%, 92.46%, 98.12%, and 92.49%, respectively
Rainfall forecasting using the group method of data handling model: A case study of Sarawak, Malaysia
No full textTime series forecasting has led to the emergence of various forecasting models applied to arrays of time series problems, such as rainfall forecasting, dengue forecasting, tourism forecasting, and others. The Artificial Neural Network (ANN) is a popular Artificial Intelligence (AI) model extensively employed in much research for time series forecasting due to its nonlinear modeling ability. The group method of data handling (GMDH) is an AI model with the characteristics of heuristic self-organizing capability. This model has shown successful results in many areas. Nowadays, rainfall forecasting remains a vital interest and is still actively researched, where researchers use different soft computing techniques. The ANN has been popularly studied for rainfall forecasting because of its ability to efficiently train a large amount of data and completely detect complex connections between nonlinear dependent and independent variables. However, research on rainfall forecasting using the GMDH model is limited. Hence, this paper designates the GMDH model and its application to rainfall forecasting. The conventional GMDH model uses the polynomial transfer function. The sigmoid transfer function is proven to solve the multicollinearity issue caused by the quadratic polynomial of the GMDH model. Hence, this research tackled the multicollinearity issue of using different transfer functions in GMDH modeling and forecasting. The study compares the results of using polynomial and sigmoid transfer functions for the GMDH model development. This research uses the Malaysia rainfall dataset of the Sarawak regions from 2010 until 2019 as a case study to evaluate the effectiveness of the GMDH models in this research. The results exhibit that the polynomial transfer function is dominant in achieving the smallest RMSE and MSE values in all regions
Extending the occupational Safety and Health Management System as a Knowledge Management System through the mixed-reality remote audit
No full textAuditing is one of the most important stages in evaluating the effectiveness of an Occupational Safety and Health Management System (OSHMS), which is also recognized as a Knowledge Management System (KMS). According to the International Labor Organization (ILO), the audit process is part of the evaluation element, where the auditor must evaluate the OSH performance. The traditional audit might not be able to be conducted due to the Covid-19 pandemic and the Movement Control Order (MCO) scenario, therefore the remote audit is being viewed as a viable solution to ensuring the audit process continues. The solution could also be utilized beyond the pandemic period as it may become one of the effective method for the audit process. The paper describes how the OSHMS can be remotely audited utilizing Mixed Reality (MR) applications in a design thinking manner. To test the approach, preliminary data was collected in an OSH office. The findings of this paper will aid stakeholders in the relevant context in making investment decisions for digitising their OSH audit process in order to create a future-ready ecosystem