Weather In Malaysia Research Articles

The Crime Prediction of Criminal Activity Based on Weather Changes Towards Quality of Life

Crime is a significant problem in society, and crime prevention is crucial. Factors such as politics, economics, culture, education, demographics, and employment have been identified as contributing to crime. Recent studies have also explored the relationship between weather and crime. Therefore, this research aims to identify the best-performing machine learning algorithm based on weather in Malaysia, using crime data from the Royal Malaysia Police and Meteorological Department from 2011 to 2020. Five machine learning algorithms were utilized, and the results showed that all algorithms had good prediction accuracy, with Gradient Boosted Trees performing the best, with an error rate of less than 23%. Location was found to be the most important feature in all the models. This study provides a valuable fundamental framework for environmental crime and social impact research scholars to conduct a more in-depth analysis of the prediction models. This study establishes a fundamental framework for scholars in environmental crime and social impact research to conduct in-depth analysis using prediction models, thereby contributing to a better understanding of the complex relationship between weather and crime, and aiding in the development of effective crime prevention strategies.

Design and Fabrication of Automatic Temperature Control for Chicken Shade

Design and Fabrication of Automatic Temperature Control for Chicken Shade

Green IoT Based on Tropical Weather: The Impact of Energy Harvesting in Wireless Sensor Network

Wireless Sensor Networks (WSNs) are a key component of Green IoT, as they play a critical role in many applications. However, a major challenge faced by WSNs is their limited energy capacity, which can impede their effectiveness. To address this issue, energy harvesting techniques are used to harness ambient energy and power the nodes, eliminating the need for frequent battery replacements or recharging. This study proposes a solar energy harvesting technique to prolong the lifespan of each wireless sensor node in a network. The aim of the research is to assess the impact of energy harvesting on wireless sensor networks with a focus on solar ambient light energy, as it is a critical component of achieving a Green Internet of Things (IoT). The study is adapted to the tropical weather of Malaysia and its forecasted conditions. Through the use of NetSim simulations, the energy efficiency and reliability of the network are evaluated using solar energy harvesting. The recharge rate for energy harvesting in a wireless sensor network is calculated to be 2.34W per day using a 55x70mm solar photovoltaic panel based on Malaysia weather forecasts and sun hours. This proposed method is successfully executed using NetSim, which utilizes real device parameters for a WSN in a simulated agriculture environment. The results show an overall improvement of 22.4 percent in performance parameters in all areas, including energy consumption, network layer, routing performance, and IEEE 802.15.4 metrics, representing a significant improvement. With the implementation of solar energy harvesting, traditional energy of WSNs can benefit from developing smart agricultural monitoring systems. This efficient method and calculation for solar energy harvesting can help to sustain the infinite lifetime of WSN by optimizing the operational time to 18% of the duty cycle. Results demonstrate that the proposed method can effectively increase the energy efficiency and reliability of the network, making it a promising solution for WSNs operating in tropical regions. This research contributes to the development of sustainable and energy-efficient WSNs, promoting the Green IoT concept.

Cultivation of Arthrospira platensis and harvesting using edible fungi isolated from mould soybean cake

In this study, the cultivation and harvesting of Arthrospira platensis biomass were proposed via simple, safe, and efficient techniques for direct consumption. Cultivation of microalgae in a covered macrobubble column under outdoor conditions resulted in significant differences (p < 0.05) with a maximum dry cell weight (Xm) of 0.959 ± 0.046 g/L. Notably, outdoor cultures resulted in approximately twofold biomass compared to indoor cultures. This outcome shows that the developed outdoor setup integrated with solar panels while utilising Malaysia's weather and atmospheric air as carbon sources is viable. Meanwhile, for harvesting, the screening showed that the fungus isolated from mould soybean cake (tempeh) starter indicated the highest harvesting efficiency, which was then further identified as Rhizopus microsporus, microscopically and molecularly. Overall, the economical and portable setup of outdoor cultivation coupled with safe harvesting via locally isolated fungus from tempeh as a bioflocculant would provide sustainability to produce A. platensis biomass.

Automated clothesline retrieval system using LDR and raindrop sensors

Doing laundry is a simple chore that every household will perform on a daily basis. Clothesline is widely used by Malaysian because it is an efficient and budgeted method but it needs to be operated manually. The disadvantages of manual clothesline are due to the unpredictable weather in Malaysia. Rain will come in a blink of an eye and cause the freshly washed clothes to get wet. People who are away from home will unable to collect their clothes once the rain comes. Therefore, an Automated Cloth Hanging System was invented to solve these problems by using Light Dependant Resistor (LDR) sensor and raindrop sensor to detect the weather and activate the motor movement. In this research, user will receive notification of clothesline using Blynk application via Wi-Fi. From the result obtained, the system can detect the sunlight and rain to determine the clothes should be hand inside or outside. Thus, clothesline able to retrieve in and out by the sensors where user can hang their clothes outside the house without worrying about the weather by using concept of Internet of Things (IoT).

Deployment of multiservice code in FSO-based hybrid subcarrier system

Abstract This research aims to investigate and improve multi-user free space optic systems (FSO) based on a hybrid subcarrier multiplexing spectral amplitude coding-optical code division multiple access (SCM-SAC-OCDMA) technique using MS code with a direct decoding technique. The performance is observed under different weather conditions including clear, rain, and haze conditions. The investigation includes analyzing the proposed system mathematically using MATLAB and OptiSystem software. The simulation is carried out using a laser diode. Furthermore, the performances of the MS code in terms of angles of bit rate, beam divergence and noise are evaluated based on bit error rate (BER), received power, and transmission distance. The performance of the MS code-based system was subsequently compared with Khazani Syed code (KS), multi-diagonal (MD), and modified quadratic congruence code (MQC) codes under different weather conditions at a bit rate of 1 Gb/s and BER threshold of 10−9. Heavy rain indicates the worst performance in terms of transmission distance of 0.9 km. Nevertheless, the system designed using the MS code outperformed the KS, MD and MQC systems as it is capable of supporting up to 6.3, 0.8, 0.9, and 1.5 km, respectively, under clear weather. In conclusion, this study provides a means of improving FSO communications that suits tropical and Malaysia weather conditions.

Modelling wind direction data of Langkawi Island during Southwest monsoon in 2019 to 2020 using bivariate linear functional relationship model with von Mises distribution

The weather in Malaysia is characterised by two monsoons, namely, the southwest monsoon from May to September, and the northeast monsoon from November to March. Wind direction is essential in observing the weather patterns and global climate. In this study, our interest is on investigating the relationship of the wind direction data of Langkawi Island in Malaysia during the southwest monsoon from year 2019 to 2020. It is essential to highlight that wind direction data that is circular and this requires different statistical techniques from the techniques that are used to analyse linear data. In this paper, we model the relationship of wind direction data by using the bivariate functional relationship model with von Mises distribution. The magnificence of this model is that the existence of error terms in all variables is considered. When modelling the data, outliers of the wind direction data are identified by using the covratio method that considers row deletion. The covariance matrix of the parameter estimates of the data is obtained by using the Fisher information matrix. Also, the result is supported by the Q-Q plots of the von Mises that indicate the goodness-of-fit of the wind direction data to the von Mises distribution. Then, maximum likelihood estimation is used in obtaining the parameter estimates of the data and hence, the model of the wind direction data is attained. The implications of this study provides an improved comprehension of the behaviour of wind direction and may be used for the prediction of wind energy in future.

Study on Water Distribution of Spraying Drone by different Speed and Altitude

The application of unmanned aerial vehicles (UAV) in Malaysia, or best known as a drone, is changing from time to time. Today, drones are used not only in the military, but also in agriculture. The use of drones became common in agriculture due to a reduction in cultivated land, labour shortages and obsolete methods. The spraying of pesticides and herbicides may also be carried out using drones. Furthermore, the time-consumed using drone is faster compared to the conventional method. On the market, there are different kinds and types of drone sprayers. Although the manufacturer has set the Standard Operating Procedure (SOP) for drone usage, the efficacy of spraying should first be examined because of Malaysia's weather and environmental factors which vary from other countries. The purpose of this paper is to investigate the effects of altitude and speed of the drone onto the coverage area during spraying application. In this study, a plot consisting of 0.5 Hectares situated at MARDI Seberang Perai was used. Three different speeds of 2 m/s, 3 m/s, and 4 m/s and three altitudes measured in heights of 1.5 m, 2.0 m, and 2.5 m from the top of the crop were tested. Wind speed and direction were recorded using an anemometer during the study. Water-sensitive paper was used during the experiment to examine the effect on spraying. In order to calculate the coverage area percentage, the spraying effect on water sensitive paper was analysed using ImageJ software. The results are expected to show which speed and altitude may contribute to the largest area of coverage percentage. The appropriate altitude and speed for the spraying operation on the basis of crop requirements can be concluded from the result which is 2 m from above crop at speed of 2.5 m/s.

Fuzzy C-means clustering for rainfall signature detection and towards understanding weather patterns

This study investigates the use of fuzzy C-means (FCM) clustering algorithm to cluster Malaysia weather data for rainfall signature detection. Rainfall signature detection of several stations is vital to gain insight into the behaviour of the specific stations. Understanding rainfall behaviour has many advantages, such as preparing mitigation initiatives and developing early warning systems in specific areas to avoid abrupt changes that may affect the security and economy of the area. Three stations in the state of Selangor, Malaysia situated in Sepang, Subang, and Petaling Jaya collected rainfall data from 2009 to 2011. A comparison of the FCM with another fuzzy clustering algorithm, namely the Gustafson-Kessel (GK) proves that in terms of the number of iterations, the FCM consumes less processing time and gives the optimal number of clusters. Through verification tests using three different validity indices, the performance of the FCM could compete with that of the GK to produce a better validity index. Statistical analysis using the analysis of variance (ANOVA) test showed different parameters representing different stations, indicating the contributing factor in the formation of the cluster. This study gives new insight into analysing different signatures among the rainfall stations.

Fuzzy C-means clustering for rainfall signature detection and towards understanding weather patterns

This study investigates the use of fuzzy C-means (FCM) clustering algorithm to cluster Malaysia weather data for rainfall signature detection. Rainfall signature detection of several stations is vital to gain insight into the behaviour of the specific stations. Understanding rainfall behaviour has many advantages, such as preparing mitigation initiatives and developing early warning systems in specific areas to avoid abrupt changes that may affect the security and economy of the area. Three stations in the state of Selangor, Malaysia situated in Sepang, Subang, and Petaling Jaya collected rainfall data from 2009 to 2011. A comparison of the FCM with another fuzzy clustering algorithm, namely the Gustafson-Kessel (GK) proves that in terms of the number of iterations, the FCM consumes less processing time and gives the optimal number of clusters. Through verification tests using three different validity indices, the performance of the FCM could compete with that of the GK to produce a better validity index. Statistical analysis using the analysis of variance (ANOVA) test showed different parameters representing different stations, indicating the contributing factor in the formation of the cluster. This study gives new insight into analysing different signatures among the rainfall stations.

Innovation of Sustainable and Greener Raised Median or Road Divider on Expressway

This study purposes a new innovation design for the construction of road divider that more sustainable and greener which is eco-friendly. It was conducted to modify the material used on the road divider, so that the suitability of the material can reduce the impact of the vehicle during road accident. Objective of this study is to test and design greener sustainable materials as a road median component. Besides, the study is to determine the suitability and characteristics of materials for road median. Materials used in this study are gunny sacks filled with sand, laterite soil, soft turfing (cow and pearl grass) and used tire as a cushion effect. Based on experiment testing, sieve analysis result showed that river sand is a good grade sand and suitable for road median. While, direct shear test showed sand and soil used for this study are suitable because there have a high shear strength. For grass observation, cow grass is suitable compare pearl grass in term of growth rate, maintenance cost, durability on sunlight exposure and weather in Malaysia. The load applied for conducting impact test on the sand sack were 14.08N 25.6N 44.8N. The initial damage occurred when a force reaches at 44.8N. However, the condition of the arrangement of sand sack is still stable. In conclusion, this new innovation of green and sustainable road divider has high potential in absorbing the impact of accidents.

Parametric Study of Photovoltaic Thermal Solar Collector Using An Improved Parallel Flow

Photovoltaic Thermal Solar Collector (PVT) is a hybrid technology used to produce electricity and heat simultaneously. Current enhancements in PVT are to increase the electrical and thermal efficiencies. Many PVT factors such as type of absorber, thermal conductivity, type of PV module and operating conditions are important parameters that can control the PVT performance. In this paper, an analytical model, using energy balance equations, is studied for PVT with an improved parallel flow absorber. The performance is calculated for a typical sunny weather in Malaysia. It was found that the maximum electrical and thermal efficiencies are 12.9 % and 62.6 %, respectively. The maximum outlet water temperature is 59 oC.

FUNDAMENTALS OF CREEP, TESTING METHODS AND DEVELOPMENT OF TEST RIG FOR THE FULL-SCALE CROSSARM: A REVIEW

Most of transmission line (TL) towers are designed and fabricated in the form of lattice using galvanized steel. The crossarm of the TL is made of Neobalanocarpus or Chengal wood. Recently, it has been reported by an electrical corporation situated in Malaysia that mechanical performance of the wooden crossarm declined below their service life of 40 years due to the extreme tropical weather in Malaysia. At present, composite crossarm made of glass fibre reinforced polymer composite were introduced as substitute in the 132 kV TL tower. However, the research findings lack of information on creep life estimation for the full-scale crossarm. Hence, a new test rig has to be developed to cater the testing operation using the uniaxial tension creep test. The primary objective of this review is to provide an overview of the creep theory and the existing creep testing methodology.

Numerical modelling of the power pack system for remote islands electrification

Electricity is one of the indispensable elements in the daily life. From domestic to commercial sector, electricity has been used to provide a wide range of applications. However, access to electricity is only limited to the urban area while rural area electrification is always a challenge due to the geographical location and high cost of the electrification infrastructure. Therefore, electrification using solar energy is projected to be one of the feasible solutions in the rural area. A typical power pack system used for the rural area electrification consists of solar panels, voltage converters and battery pack. Although lead acid battery provides an economic solution for the energy storage system, they are also associated with other disadvantages such as low depth of discharge, bulky and low energy density. Li-ion battery is a new generation of battery technology with high energy density, light weight and high depth of discharge which offer a promising solution for an off grid power systems. In this study, an off grid power pack consists of Li-ion batteries, voltage converters and photovoltaic modules are modelled to evaluate the electrical performances of the system under Malaysia weather conditions. Then, the numerical modelling results are compared with experiments. It is found out that the numerical model correlated well with the experimental data with a relative error less than 5%.

Water quality variation during a strong El Niño event in 2016: a case study in Kampar River, Malaysia

El Niño and Southern Oscillation (ENSO) is a natural forcing that affects global climate patterns, thereon influencing freshwater quality and security. In the advent of a strong El Niño warming event in 2016 which induced an extreme dry weather in Malaysia, water quality variation was investigated in Kampar River which supplies potable water to a population of 92,850. Sampling points were stratified into four ecohydrological units and 144 water samples were examined from October 2015 to March 2017. The Malaysian Water Quality Index (WQI) and some supplementary parameters were analysed in the context of reduced precipitation. Data shows that prolonged dry weather, episodic and sporadic pollution incidents have caused some anomalies in dissolved oxygen (DO), total suspended solids (TSS), turbidity and ammoniacal nitrogen (AN) values recorded and the possible factors are discussed. The month of March and August 2016 recorded the lowest precipitation, but the overall resultant WQI remained acceptable. Since the occurrence of a strong El Niño event is infrequent and far between in decadal time scale, this paper gives some rare insights that may be central to monitoring and managing freshwater resource that has a crucial impact to the mass population in the region of Southeast Asia.

THE EFFECTS OF WEATHER ON CRIME RATES IN MALAYSIA

This study estimates the effects of temperature and rainfall on the prevalence of criminal activity in Malaysia. The analysis is based on annual data for the period 1973-2009, on temperature, rainfall and crime rates – total crime, violent and property crime. By using the generalized one-step error-correction model, we examine the short-run and long-run dynamics between crime rates with varying temperatures and rainfall in Malaysia. Our results suggest that there is long-run relationship between total crime and property crimes with weather in Malaysia. The long-run coefficients indicate a positive impact of temperature (hot weather) on criminal activity. Our results imply that the law enforcement would have a better understanding of how the weather affects crime and a chance for the authorities to better prepare their departments during weather conditions that influence certain criminal activities.Keywords: Crime; Temperature; Rainfall; Generalized error-correction model; Malaysia.

Membrane Based Enthalpy Heat Exchanger Performance in HVAC System

The performance of a membrane based heat exchanger utilizing porous paper as the heat and moisture transfer media used in ventilation energy recovery systems is presented. A mathematical model was developed and validated against the experimental results. This model can be used for design aide to predict the effectiveness of the heat exchanger. Furthermore, system analysis of an air conditioner shows an increase in the coefficient of performance and cooling capacity when paper heat exchanger is used, especially in a climate similar to the weather in Malaysia and Darwin.

Heat Lump in Different Pavement Layer Using Ethylene Glycol as A Solar Heat Collector

Due to the hot weather in Malaysia, several studies being carried out regarding solar energy harvesting and use as a noble renewable energy. Therefore, researchers start developing various methods to utilize sun's heat as a renewable source of energy. Solar energy has been always concern researchers to develop most effective, durable and cheap methods and materials to be used as solar energy collectors in road pavements. Therefore, this study was conducted to determine the maximum heat area using ethylene glycol. The study was involved the field monitoring of the six samples of asphalt slab with stainless steel pipe with ethylene glycol and empty pipe act as the controlled sample. The pipe was arranged in three different depths of 50mm, 100mm and 150mm and keeping controlled the pipe diameter and the size of slab of 20mm and 300mm x 300mm respectively. These results show that the maximum heat extraction by the ethylene glycol was at a depth 150mm which was 51.2°C. The average percentage increments of the pipe with ethylene glycol for three days for pipe depth 50mm was 71%, while for pipe at depth 100mm and 150mm were 78% and 62% respectively. The ethylene glycol effect was more noticeable compare to the pipe without ethylene glycol and can store more heat. For the strength of pipe, the highest maximum load bearing capacity that can be supported by the stainless steel pipe was at depth 50mm and the second highest was at a depth 100mm while the third highest was at depth 150mm. So, the suitable depth to install the pipe with the consideration of both cases which was maximum heat gain and the maximum load that can be supported was at depth 50mm.

Three-Phase Supply for Solar Application with MPPT Controller

This paper presents the implementation of three-phase sinusoidal inverter powered from a solar PV, 12V Lead-acid battery, and MPPT controller. Considering the Malaysia weather, it is in general the weather change very fast from the sunny clear sky up to the very thick cloud. Hence, the perturb and observe (P&amp;O) control scheme is designed to crop solar energy in the most efficient manner and store the energy to the battery. To convert the output from solar or battery into high quality three-phase sinusoidal alternating current (AC) voltage, low resistive MOSFETs switches inverter is used by adopting Sinusoidal Pulse Width Modulation Technique (SPWM). The frequency of the AC voltage can be adjusted from 30 up to 65 Hz with constant voltage over frequency (V/F) ratio. It is expected that the device can be used as stand-alone electrical supply for dedicated devices such as agricultural water pumping, drug-cold-storage in remote village, cold storage for fisherman, self-powered and unmanned water pump, forest security and surveillance device, etc. Furthermore, the device is also equipped with status display, over current and excessive charging protection, and low power warnings.

Solar Assisted Desiccant Air Conditioning System for Hot and Humid Areas

Solar assisted desiccant cooling system is an attractive and cost effective application for air conditioningsystem. To find effect of dehumidification capacity on the performance of cooling system, fourconfigurations of desiccant cooling system have been investigated. These models were simulated for8,760 hr of operation under hot and humid weather in Malaysia. Important parameters ( coefficient ofperformance or COP, room temperature and humidity ratio) were evaluated by detecting the temperatureand humidity ratio of different points of each configuration by TRNSYS simulation. The simulationmodels have been validated by means of by data measurement of a one-stage solar desiccant coolingsystem, which was installed in technology park of UKM in Malaysia. The capacity of cooling load andalso the sensible heat ratio of the zone were 1ton, and 0.25respectively. It was achieved that by increasingthe dehumidification capacity of desiccant cooling system the COP of system will be increased.Therefore, due to high dehumidification capacity, the two-stage ventilation mode with 1.06 of COP wasconsidered as the best model amongst the other configurations. The two-stage ventilation produced supplyair at 17.6 °C and 0.0096 kg/kg to remove the sensible load of the room, whereas the supply airtemperatures of the other configurations were higher. Keywords: dehumidification capacity, desiccant cooling, hot and humid, COP