Green technology design approach for liveable park of Tasik Biru Kundang, Malaysia / Rijal Saffuan, Junaidah Ariffin and Zamreen Amin

Green Technology design approach is a new solution that must be applicable to preserve a nature and reduce the pollution. There are so much innovation could be used to in the development of the park to reduce the electricity use, eco-friendly and livable for the community. This paper aims to exemplify an effort by a group of students, through multi-professional inputs, in designing for a city facility that can add more towards a livable city. The results of the approach are multidisciplinary design that includes the idea from multiprofessional in making a livable park for community surroundings Tasik Biru Kundang, Kuang, Selangor, Malaysia

Evacuation routing optimizer (EROP) / Azlinah Mohamed … [et_al.]

This report presents the solution to the two of the most critical processes in planning for flash Hood evacuation: the evacuation vehicle assignment problem (EVAP) and the evacuation vehicle routing problem (EVRP). With these solutions, the evacuation routing optimizer (EROP) is constructed. The EVAP is firstly solved, followed by the EVRP. For EVAP, discrete particle position is proposed to support the implementation of discrete particle swarm optimization called myDPSOVAP-A. Particle positions are initially calculated based on the average passenger capacity of each evacuation vehicle. We experiment with different numbers of the potential flooded areas (PFA) using two types of sequences for vehicle capacity; random and sort ascending order. Both of these sequences are tested with different inertia weights, constriction coefficients (CF), and acceleration coefficients. We analyse the performance of each vehicle allocation in four experiment categories: myDPSOVAP-A using inertia weight with random vehicle capacity, myDPSOVAP-A using inertia weight with sort ascending order of vehicle capacity; myDPSOVAP-A using CF with random vehicle capacity, and myDPSOVAP-A using CF with sort ascending of vehicle capacity. Flash flood evacuation datasets from Malaysia are used in the experiment. myDPSOVAP-A using inertia weight with random capacity was found to give the best results for both random and sort ascending order of vehicle capacity. Solutions reached by analyses with CF random and inertia weight sorted in ascending order were shown to be competitive with those obtained using inertia weight with random capacity. Overall, myDPSOVAP-A outperformed both a genetic algorithm with random vehicle capacity and a genetic algorithm with sort ascending order of vehicle capacity in solving the EVAP. Consequently EVRP, myDPSOVRPl is modified and named as myDPSO_VRP_2, adopts a new solution mapping which incorporates a graph decomposition and random selection of priority value. The purpose of this mapping is to reduce the searching space of the particles, leading to a better solution. Computational experiments involve EVRP dataset from road network for flash flood evacuation in Johor State, Malaysia. The myDPSOVRPl and myDPSO_VRP_2 are respectively compared with a genetic algorithm (GA) using solution mapping for EVRP. The results indicate that the proposed myDPSO_VRP_2 are highly competitive and show good performance in both fitness value and processing time. Overall, DPSOVRP2 and myDPSOVAP-A which are the main component in the EROP gave good performance in maximizing the number of people to vehicles and minimizing the total travelling time from vehicle location to PFA. EROP was embedded with the DPSOVRP2 and retrieved the generated capacitated vehicles from the myDPSOVAP-A. EROP is also accommodated with the routing of vehicles from PFA to relief centres to support the whole processes of the evacuation route planning

Robustness analysis of model parameters for sediment transport equation development

Robustness analysis of model parameters for sediment transport equation development is carried out using 256 hydraulics and sediment data from twelve Malaysian rivers. The model parameters used in the analyses include parameters in equations by Ackers-White, Brownlie, EngelundHansen, Graf, Molinas-Wu, Karim-Kennedy, Yang, Ariffin and Sinnakaudan. Seven parameters in five parameter classes were initially tested. Robustness of the model parameters was measured on the statistical relations through Evolutionary Polynomial Regression (EPR) technique and further examined using the discrepancy ratio of the predicted versus the measured values. Results from analyses sugges

Development of Rainfall Model using Meteorological Data for Hydrological Use

Abstract At present, research on forecasting unpredictable weather such as heavy rainfall is one of the most important challenges for equipped meteorological center. In addition, the incidence of significant weather events is estimated to rise in the near future due to climate change, and this situation inspires more studies to be done. This study introduces a rainfall model that has been developed using selected rainfall parameters with the aim to recognize rainfall depth in a catchment area. This study proposes a rainfall model that utilizes the amount of rainfall, temperature, humidity and pressure records taken from selected stations in Peninsular Malaysia and they are analyzed using SPSS multiple regression model. Seven meteorological stations are selected for data collection from 1997 until 2007 in Peninsular Malaysia which are Senai, Kuantan, Melaka, Subang, Ipoh, Bayan Lepas, and Chuping. Multiple Regression analysis in Statistical Package for Social Science (SPSS) software has been used to analyze a set of eleven years (1997 – 2007) meteorological data. Senai rainfall model gives an accurate result compared to observation rainfall data and this model were validating with data from Kota Tinggi station. The analysis shows that the selected meteorological parameters influence the rainfall development. As a result, the rainfall model developed for Senai proves that it can be used in Kota Tinggi catchment area within the limit boundaries, as the two stations are close from one another. Then, the amounts of rainfall at the Senai and Kota Tinggi stations are compared and the calibration analysis shows that the proposed rainfall model can be used in both areas.&nbsp

Accounting pick and paste / Wan Noor Asmuni Wan Fauzi ...[et al.]

The teaching and learning process has evolved over time. Nowadays, educators have to continuously search and develop tools to successfully engage their students in learning process, especially if the students are mature learners or very young children. Accounting Pick and Paste (APP) is an interactive learning product developed with the objective to facilitate learners who want to learn basic accounting concepts in a very simplified and fun manner. This product can help educators overcome students‟ inattentiveness problem by making lessons more enjoyable, personally interesting and motivating. Instead of merely memorising, learners would also be able to apply what they have learned during class in a more realistic wa

Study on Characteristic of Bed Material and Bed Load Discharge in Sungai Jemberau, Tasik Chini

Tasik Chini is located in the state of Pahang about 100 km from Kuantan, the capital of the state of Pahang. Most of the lowland within the study area has been converted into agricultural and including rubber and oil palm plantations and mixed crops. This logging and mining activities gave impact to sediment characteristics and discharge. The purpose of this study was to identify the bed material characteristics and to determine the bed load discharge in Sungai Jemberau at Tasik Chini. Bed material sample was collect at Sungai Jemberau in 24 November 2016, 1 December 2016 and 5 March 2017. Bedload discharge also measured between these date. The bed load discharges also estimate by using Duboys and Schoklitschequation to identify the suitable predicted method for this area. From the analysis of the results, DuboysEquation was more suitable to predict and estimate the bed load discharges for Sungai Jemberau at Tasik Chini because the predicted value closer to measured value

New promotion criteria for academics: a case of University Teknologi Mara / Fauziah Noordin … [et al.]

A university is said to be defined by its system of promotion. Designing a promotion system and participating in its decisions are two of the most important ways in which each academic shapes the university. The promotion system reflects two overlapping but distinct sets of values, namely, those of the various disciplines and those of the institution. In June 2010, the Deputy Vice Chancellor of Academic and International appointed a university task force on new promotion criteria to revise and develop promotion criteria with the purpose of maintaining high academic standard that are consistent to current changes and needs of UiTM

Improving Total Sediment Load Prediction using the GE Technique (Case Study: Malaysia)

Predicted total sediment load is usually used to identify the intensity of a sedimentation process. Currently, the existing available models to predict total load are mostly developed based on data collected from flumes, channels and rivers located in western countries. These models may not be valid to predict sediment transport of rivers in the Tropics due to significant differences in the hydrological and sediment characteristics conditions. A new model using genetic programming (GE) technique is used to improve the prediction of sediment load for rivers in tropical Malaysia. Methods/StatisticalAnalysis: The model predictions are compared with those obtained from five available sediment transport models, including Engelund & Hansen (1967), Graf (1971), Ariffin (2004), Chan et al. (2005) and Sinnakaudan et al. (2006). Findings: The performance of the model in relation to the test set shows less scattering around the line of equality, between the measured and predicted total sediment loads. Statistical analyses of 68 data sets give the coefficient of correlation, r and the discrepancy ratio of 0.82 and 0.53 respectively. Application/Improvements: Hence, the GE Technique used in the prediction of Total Sediment Load is found to give better accuracy compared to other methods

Streambank Erosion Prediction for Natural Channel using Artificial Neural Network Autoregressive Exogenous (ANNARX) Model

This study aims to develop a streambank erosion prediction model using Artificial Neural Network Autoregressive Exogenous (ANNARX) for natural channels. ANNARX is one type of ANN models and it is a supervised network that trains spasmodic data sets. Field data of 494 data extracted from two (2) rivers in Selangor, namely Sg. Bernam and Sg. Lui were used in the training and testing phases. Total of eleven (11) independent variables are used as input variables in the input layer and the ratio between erosion rates, ? to the near-bank velocity, Ub as the output variable. The functional relationships were derived using Buckingham Pi Theorem in the dimensional analysis. A supervised learning technique was employed and the target output is streambank erosion rates, ?b. The established models were validated to assess their performances in predicting the rates of streambank erosion using 176 data. Validation of the newly developed streambank erosion rates equation has been conducted using data obtained from this study. The performance of the derived model was tested using discrepancy ratio and graphical analysis. Discrepancy ratio (DR) is the ratio of predicted values to the measured values and these values are deemed accurate if the data lie between 0.5 to 2.0 limit. Total of 8 models have been developed in the predictive model. Analysis confirmed that models developed using ANNARX are capable to achieve coefficient correlations (r-squared) values above 0.9 and successfully predict the measured data at accuracy above 90%