Search

The new electrical motor used as the automotive engines seen to be very efficient which use only clean energy generated as one of the efforts to minimize the carbon emissions. The high usage of electric vehicle around the world for responding to the demands of taking care the ecological system has establish many Electric Vehicles (EV) charging station to accommodate the user. However, high charging loads of fast charging stations result in increased peak load demand, reduced reserve margins and voltage instability. Thus, the optimal distribution network reconfiguration with interconnection of charging station is this solution for this issue. The finding of the optimal reconfiguration in this study are used to improve the voltage profile and minimize the power loss of the distribution system. The best reconfiguration is searched by using Cuckoo Search Algorithm (CSA). The result of the finding then will be verified by comparing to other research papers for its efficiency of the method used.

Overpopulation has adverse effects on increasing energy consumption. This energy demand is so much that the traditional grid is unable to sustain energy supply. To meet this demand, battery energy storage and distributed generation sources are important in maintaining a constant energy supply. This paper minimizes the residential customer's energy cost with PV, battery storage system, and home to grid energy exchange. The results show how much home to grid energy exchange is important in reducing cost. A complete home energy management (HEM) system is explored, incorporating PV, battery storage system, and home to grid energy exchange. The cuckoo search (CS) optimization algorithm uses a residential home's data and develops optimal running of appliances. The results obtained from the algorithm depicts that the approach is beneficial and useful for the residential consumer to initiate different DR actions. The cost associated is reduced, and energy utilization is very efficient in the proposed scheme.

The stochastic yield of renewable energy renders their integration in the energy grids very confined. In this study, a hybrid energy system (HES) was investigated that comprises an energy storage system (ESS), a wind turbine (WT), and a diesel generator (DG). This research aims to generate a sustainable energy supply using an efficient energy management system (EMS). Thus, the designed control system considers the constraints of the various components of the HES in question. To develop and examine the efficacy of the purposed HES and the supervision algorithm, the MATLAB (Simulink) software tool was used.

With the massive rise in population as well as economic growth, the energy consumption of residential end-users has increased considerably. To confront this issue distributed generations (DGs) and electrical energy storage (EES) are very crucial for meeting energy demand. In this paper, the electricity cost for residential end-users has been investigated due to integration of distributed photovoltaic (PV) and EES for IoT-enabled smart homes. Also, the benefits of energy management because of bidirectional flow of energy (H2G) have also been explored. Formulation of home energy management (HEM) problem is performed by taking PV, EES end-users comfort constraints into consideration. The Q-value based reinforcement learning (RL) strategy considering end-users priority is exploited for optimal home appliances scheduling (HAS). Simulation results shows that proposed schedule for home appliances is effective and demand response (DR) actions are accomplished. Furthermore, the reduction in both electricity consumption cost and system uncertainty has also been observed.

Temperature measurement is a vital process that is used in almost every industry. To control the temperature at a required fixed value, different types of controllers are used. The problem addressed in this research is to control and measure the temperature of the calorimeter's heating element for the desired target temperature. In this paper, a PD controller-based temperature control and measurement system have been designed to solve this problem. A PD controller is integrated with the Arduino mega 2560 and LabVIEW software to monitor and control the real-time temperature of the heating element of the calorimeter. Resistance Temperature Detector (RTD) sensor is used for temperature sensing in the calorimeter. A sensor consistently delivers the temperature of the heating element to the Arduino microcontroller in the form of voltage through an analog to digital converter (24-bit ADC) module. PD algorithm is used to tune the pulse width modulation (PWM) signal timely according to the error signal. PC based LabVIEW software is used to design Graphical User Interface (GUI) for the control system to compare and store the data of actual temperature coming from the microcontroller with target temperature and also used to tune the PD controller according to the current error signal. Form the results; it is revealed that PD is an efficient controller for controlling and tracking the temperature of the heating element of calorimeter towards the randomly selected different target temperature (52°C, 65°C, 75°C, 85°C). This temperature control approach has a simple structure, fast reaction speed, excellent stability, and high precision.

With the proliferation of decentralised power generation technologies and smart grid infrastructures, residential renewable energy generation (REG) has burgeoned to become intrinsic to modern power grids and is expected to play a fundamental role for the realization of netzero energy buildings to cater to the ever-escalating energy demand. The integration of domestic REG into the utility grid necessitates a medium of intelligent devices to perform net metering operations. Henceforth, we propose one such cost effective smart net-metering device for household REG systems with in-built wireless bi-directional communication based on Internet of Things (IoT) technology. Net metering operations are implemented using a microcontroller to synchronously collect, analyze and transmit data from sensors installed at the utility to consumer and REG to utility sides to both an offline display and an online server via a WiFi module interfaced to the microcontroller. We successfully implemented a prototype device for real-time energy monitoring over a sustained period of time, yielding accurate power generation and energy transfer statistics with remote-control operations. These results demonstrate the considerable potential for the prototype to be a stimulant in catalysing our eventual shift to decentralised power generation.

Electricity shortages are severe for developing countries like Pakistan as a result of massive population growth. To solve this problem Renewable energy resources (RER’s) and energy storage systems (ESS) can play a considerable role. In this paper, we have analyzed the effects on the operational cost of residential electricity consumers by installing the rooftop photovoltaic (PV) and ESS on their smart homes. Additionally, the home to grid (H2G) energy exchange framework is also included to explore its benefits on energy management. Home Energy Management (HEM) problem is formulated with the integration of PV and ESS by considering user preferences and other system boundaries. A Grey wolf optimization (GWO) algorithm is used to find out optimal scheduling of appliances. The findings of the simulations indicate that the proposed solution can improve the performance of the home electricity scheduling, reduced the effect of uncertainty on the system and decrease the overall energy consumption cost.

This paper demonstrates a compact Multiple-Input Multiple-Output (MIMO) antenna supporting millimeter-wave (mm-wave) 5G communication applications. The antenna structure proposed in this work is a two-port MIMO antenna system, where each MIMO element consists of 1×2 linear array fed with parallel feed network. The prototype is designed on Rogers R043S0B substrate with the board dimensions of 25×35×0.762 mm3. Defected Ground Structure (DGS) is incorporated to optimize the performance of the demonstrated structure. The resonant frequency band covered by the MIMO antenna array ranges from 38.8- 42.9 GHz, thus covering 4.1 GHz wide bandwidth. Whereas, the peak gain attained for the resonant band is 9.86 dB. Moreover, significant isolation is obtained between the MIMO elements. In addition, diversity performance of the demonstrated antenna structure is analyzed through Envelope Correlation Coefficient (ECC), Total Active Reflection Coefficient (TARC), Mean Effective Gain (MEG), and Channel Capacity Loss (CCL). The simple structure, planar configuration, and radiation characteristics validates the presented MIMO antenna array as a suitable candidate for the forthcoming mm-wave 5G applications.

Static Random Access Memories (SRAM) based configuration bits is used to store data in Look Up Tables (LUTs) and routing through switch matrix is accomplished using the SRAM contents. Date write operation takes place only when the FPGA needs to be configured or reconfigured and hence a major source of power consumption comes from the SRAM cell leakage current during idle phase. Low power SRAM cell design forms an important requirement in today’s FPGAs because it is one of the critical components in FPGAs and consumes a large fraction of the total power. Hence a novel SRAM 6T structure is proposed where cell power supply is raised to higher V DD only during read or write operation and supply line is pulled down to lower voltage during idle phase.

Permanent magnet generators are the majority source of commercial electrical energy. With the recent reduction in the price of high performance magnet, it is made possible to construct a high efficiency compact generator. The problem with the compact generator is the temperature management. Too high magnet temperature could lead to irreversible demagnetization of the permanent magnet material. This paper proposes a method to formulate an empirical model based on the simulation data. Ansys Fluent software is used to simulate the heating and the cooling effects inside the generator. Design of Experiment is used to plan the experimental run so that the results are sufficient enough to formulate a linear or a nonlinear model. The formulated empirical model shows a good prediction of the winding coil temperature with the percentage of difference of less than 5 % for the natural convection cooling.

One of the complicated issue in compliance control for rehabilitation and assistive robots is to predict right human's motion intention. In this paper, we have proposed an algorithm to estimate Desired Motion Intention (DMI) so that better compliance could be provided by the rehabilitation and assitive robots. Proposed algorithms is based on Extreme Learning Machine (ELM) and takes inputs from different sensors. These sensors provide information about current angular position, speed and the force applied by the human on robot. Proposed algorithm is free from the issues which appear in traditional Radial Basis Function Neural Network (RBFNN) such as local minima, selection of suitable parameters, slow convergence of adaptation law and over-fitting. These issues cause many problems for such algorithm in tuning for each different individual and makes it impractical for our application. Developed algorithm is experimentally evaluated for two kinds of trajectories which are employed for the Activities of Daily Living (ADL) for rehabilitation purposes. These trajectories include motion in line, circle and mixture of both (line and circular). Experimental results describe the successfully implementation of proposed algorithm in prediction/estimation of the Desired Motion Intention (DMI).

A process of characterizing an unknown system based on the inputs and outputs is called System Identification (SI). Characteristics of a structural system include its stiffness, mass and damping matrices, eigenvalues and eigenvectors and strain energies etc. Eigensystem Realization Algorithm (ERA) is a very useful system identification technique which employs theory and concept of simple linear algebra and Hankel matrix. The aim of this paper is to implement the Eigensystem Realization Algorithm (ERA) on metal-composite spar under impulse loading. Full finite element model of a metal-composite spar in cantilever position is used for the modal and transient response analysis in MSC. Nastran. Modal analysis is used to get the frequencies and mode shapes while transient response analysis is done under impulse loading to get the displacement response at three nodes by exciting each of the three nodes one by one. These nine displacement response vectors are then fed into the ERA code in Matlab to get the displacement responses, mass and stiffness matrices and eigenvalues of the beam by black box identification technique. These structural identification parameters are then compared with the FEM and good correlation is found. The proposed system identification method perform very well and indicate its great potential within the domain of damage detection and Test-FEM correlation.

Need to develop human body's posture supervised robots, gave the push to researchers to think over dexterous design of exoskeleton robots. It requires to develop quantitative techniques to assess motor function and generate the command for the robots to act accordingly with complex human structure. In this paper, we present a new technique for the upper limb power exoskeleton robot in which load is gripped by the human subject and not by the robot while the robot assists. Main challenge is to find non-biological signal based human desired motion intention to assist as needed. For this purpose, we used newly developed Muscle Circumference Sensor (MCS) instead of electromyogram (EMG) sensors. MCS together with the force sensors is used to estimate the human interactive force from which desired human motion is extracted using adaptive Radial Basis Function Neural Network (RBFNN). Developed Upper limb power exoskeleton has seven degrees of freedom (DOF) in which five DOF are passive while two are active. Active joints include shoulder and elbow in Sagittal plane while abduction and adduction motion in shoulder joint is provided by the passive joints. To ensure high quality performance model reference based adaptive impedance controller is employed. Exoskeleton performance is evaluated experimentally by a neurologically intact subject which validates the effectiveness.

This paper investigate the potential of Unmanned aerial imagery capturing system(UAiCs) to mapping a quarry area and carried out area measurement and spataial analysis. This study used fixed wing UAiCs as a platform and a sensor compact camera Canon PowerShot SX230 HS. A workflow from flight planning, data acqusistion and data processing was demonstrates in this research. Two result was produced which is digital orthophoto and digital elelvation model(DEM). Based on the result, contour was generated. Besides the volume, area and perimeter for total area, current excavation and balanced area are discussed.

This paper has discuss the image processing of aerial photograph acquired from unmanned aerial imagery capturing system (UAiCs) in generating a digital orthophoto and digital elevation model of a small catchment. The purpose of the study is to produce a recent digital elevation model of the study area which comprise of terrain and water bodies particularly in depicting river water level during rainy season. The process of handling the UAiCs including the preparation stage for flight planning and the actual flight mission were also discussed. The end result shows the digital orthophoto product as well as digital elevation model of the catchment area that ready to be used for further analysis.

Need to develop human body's posture supervised robots, gave the push to researchers to think over dexterous design of exoskeleton robots. It requires to develop quantitative techniques to assess motor function and generate the command for the robots to act accordingly with complex human structure. In this paper, we focus on developing new technique for the upper limb power exoskeleton in which load is handled by the human subject and not by the robot. Main challenge along with the design complexity is to find the desired human motion intention and to develop an algorithm to assist as needed accordingly. For this purpose, we used newly developed Muscle Circumference Sensor (MCS) instead of electromyogram (EMG) sensors. MCS together with the load cells is used to estimate the desired human intention by which desired trajectory is generated. The desired trajectory is then tracked by passivity based adaptive control technique. Developed Upper limb power exoskeleton has seven degrees of freedom (DOF) in which five are passive and two are active. Active joints include shoulder and elbow, powered by electric motors and move in Sagittal plane while abduction and adduction motion in shoulder joint is provided by the passive joint. Performance of the exoskeleton is evaluated experimentally by a neurologically intact subject. The results show that after adjusting the motion intention recognition algorithm for the subject, the robot assisted effectively and the subject only felt nominal load regardless of the weight in hand.

Dielectric Ceramics (DRs) have revolutionized the microwave wireless communication industry globally. The three key properties of ceramic dielectrics that determine their functionality at microwave and millimetrewave frequencies include relative permittivity (er), unloaded quality factor Qu - the inverse of the dielectric loss (tanδ) and temperature coefficient of resonant frequency (τf). These microwave dielectric properties are affected by a number of factors. These includes tolerance factor, onset of structural phase transitions, dark core formation, processing conditions, raw materials and impurities, order/disorder behavior, compositional ordering, porosity, humidity, grain size, orientation of the crystallites, and grain boundaries. The data related to these factors is scattered. The main purpose of this review is to bring these together and present the effects of these factors on the microwave dielectric properties. Control of these factors is important for improvement in the microwave properties. This review would be very helpful to the novice researchers and technologists in the field.

Energy is a fundamental and critical component in modern global economy of a country. Industries, education, commercial facilities and people use the energy to enjoy a comfortable standard of living. Thus, energy supply and consumption are an important issue in national economies and quality of life. The inefficient electricity consumption management leads to incur the highest possible cost. Big consumer is billed by the utility not only on the total energy consumed, but also on maximum demand, power factor and time off use. Therefore, to respond to the challenges of increasing energy cost, this study is conducted using spatial or geographic information system (GIS) technology in assisting the Electrical and Telecommunication Unit of UiTM Shah Alam to manage the building energy cost. The GIS establishment and database management can practice 3-Dimensional mapping of energy consumption and demand location from the utilities record, and analyze the energy consumption according to UiTM Academic session. A prototype system is also generated for calculating a total of energy use for a month by using a graph and estimate building electrical bill in achieving energy efficiency. GIS is a powerful tool that could analyze energy use for a better cost-effective decision making.

Trust is a directional relationship between two parties; the trustor and trustee. To manage trust, a procedure for trust management is needed. Trust in Mobile Ad-Hoc Network (MANET) during emergency case involves probability since it is not absolutely certain how much the nodes can be trusted, because there is not enough information collected by the time the decision needs to be made, hence creates uncertain environment. This paper focuses on the use of subjective logic in creating a trust model for evaluating nodes' trustworthiness at the emergency site. Nodes need to share information during emergency cases, hence before access is granted, nodes must be proven authentic. A trust model that consists of two important components which are trust formation and trust calculation is then proposed and verified.

This paper presents an application of static and dynamic sliding mode control of ball and beam system. Conventional PID controllers use incomplete simplified models and are mostly designed for linear systems. Although, some PID controllers are designed for nonlinear system but they are using simplified incomplete model which do not cater for matched disturbances. Our proposed control laws using static & dynamic sliding mode control use complete nonlinear system without model approximation. Moreover, static sliding mode control (SSMC) caters for matched disturbance rejection as well. There is an inherent issue of chattering with static sliding mode control (SSMC). However, dynamics sliding mode control (DSMC) counter it well. DSMC is not only equally effective when it comes to matched disturbance rejection but also removes chattering as well. In the end detailed comparative analysis is presented and experimental results confirm the superiority of DSMC.

The purpose of this paper is to evaluate and measure the role of Lembaga Zakat Selangor in ensuring business success for its zakat recipients.

Renewable energy is a crucial factor if sustainable development on the continent of Africa is to be given the priority it deserves. The technologies for achieving this however mainly exist outside its geographical boundaries. This makes the issue of technology transfer quite pertinent.

This work presents the development of a new systematic technique to target fresh water consumption and wastewater generation for systems involving multiple contaminants when all options of water minimization including source elimination, reduction, reuse/recycle, outsourcing and regeneration are considered simultaneously. This problem is formulated as mixed integer linear programming (MILP) and implemented in Generalized Algebraic Modeling System (GAMS). The consideration of process changes will lead to optimal design of minimum water utilization network. The MILP model proposed in this work can be used to simultaneously generate the minimum water targets and design the minimum water network for global water-using operations for buildings and industry. The approach is illustrated by using an industrial involving a chlor-alkali plant. Significant water savings for the industrial case study is achieved, illustrating the effectiveness of the proposed approach.

In recent years, the initiative to reduce water and energy simultaneously has received increased attention. Two approaches; conceptual design such as graphical approach and mathematical modeling are widely used to perform this reductions. Mathematical modeling is preferred mostly by academicians because it could lead to global optimal solutions. Graphical methods on the other hands can provide wide insights through its visualization nature and are idler for engineers. In this paper, the targeting and design graphical approach for simultaneous water and energy reduction proposed by Wan Alwi et al. [1] are extended for non-mass transfer based water system. The graphical approach which has been presented in this paper is the simplest technique and easy to understand. It is divided to two steps (1) water targeting and design, (2) energy targeting and design. The method has been tested on a case study and has significant water and energy utility reductions.

Computer aided techniques form an efficient approach to solve chemical product design problems such as the design of blended liquid products (chemical blending). In chemical blending, one tries to find the best candidate, which satisfies the product targets defined in terms of desired product attributes (properties). The systematic computer-aided technique first establishes the search space, and then narrows it down in subsequent steps until a small number of feasible and promising candidates remain. At this point, experimental work may be conducted to verify if any or all the candidates satisfy the desired product attributes. Alternatively, rigorous modeling could also be used in this final step. In other words, the candidates are quickly generated and screened until a small number is left for final selection and evaluation by experiments and/or rigorous modeling. This paper presents a design methodology for blended liquid products that identifies a set of feasible chemical blends. The blend design problem is formulated as a Mixed Integer Nonlinear Programming (MINLP) model where the objective is to find the optimal blended gasoline or diesel product subject to types of chemicals and their compositions and a set of desired target properties of the blended product as design constraints. This blend design problem is solved using a decomposition approach, which eliminates infeasible and/or redundant candidates gradually through a hierarchy of (property) model based constraints. This decomposition method reduces the search space in a systematic manner and the general blend design problem is decomposed into two stages. The first stage investigates the mixture stability where all unstable mixtures are eliminated and the stable blend candidates are retained for further testing (note that all blends must be stable liquid mixture). In the second stage, the blend candidates have to satisfy a set of target properties that are ranked according to a specified priority. Finally, a short list of candidates, ordered in terms of specified performance criteria, is produced for final testing and selection. The application of this systematic and computer-aided approach is illustrated through a case study involving the design of blends of gasoline with oxygenated compounds resulting from degradation and fermentation of biomass for use in internal combustion engines. Emphasis is given here on the concepts used and on the validation of the property models, mainly, the Reid vapor pressure model and the liquid phase stability tests.

Trust play important roles in Mobile ad hoc networks since nodes may randomly joined and leave the network at their own pace. In catastrophe like massive accident or earthquake, groups of rescue personnel form a temporary network structure at the rescue site using their portable devices for coordinating the rescue relief. These groups of user from different agency need to use the temporary network for communication and also for sharing the information. Trust plays important roles in these groups since sharing of information must be among trusted and authorized nodes only. In this paper we form trust model adopting the PGP web-of-trust concept with subjective logic. The PGP web-of-trust is suitable method to adopt in mobile ad hoc networks since nodes are communicating based on peer to peer, hence peer recommendation can be use to create trust between peers. The use of subjective logic operators for calculating trust in the proposed trust model is appropriate since there is an element such as uncertainty as part of calculation. Uncertainty is important in this dynamic network since we do not have full information when decision is make. The trust value later is mapped with the access control policy to determine user access privileges.

Microarray expression data is one of the most widely used to find patterns in genetic expressions. The DNA Microarray Technique participates as one of the leading methods in Cancer Research. Due to the presence of immense noise, fewer numbers of samples and huge amount of genes, the useful genomic knowledge extraction from this technique is an important question in today's Biological Research. Scientists and Researchers are exploring efficient mathematical procedure to find realistic gene expressed knowledge. In this study K-Means Clustering technique is used on an efficient 3rd order polynomial based technique to normalize the genomic data of Acute Myeloid Leukemia (AML) and Acute Lymphocyte Leukemia (ALL). AML was used as a model to generate the coefficients of the polynomial by considering non trending, decorellation and offset based techniques. The K nearest Neighbor technique is used to estimate the missing values of microarray data and avoid the impact of missing data on clustering algorithm. The data can be regenerated easily using 3rd order polynomial normalization based on model generated by AML. Top ranked genes in each cluster have been presented in this paper which helps in finding functionally coregulated genes in ALL and AML.

A microcontroller based advanced technique of generating sine wave with minimized harmonics is implemented in this paper. The proposed technique “impulse-sine product” aims to design and implement a voltage regulated inverter with ripple free and glitch free output sine wave that can operate electronic devices efficiently. The output voltage of the inverter is regulated by a feedback loop using analog to digital protocol of PIC16f877 microcontroller. The design is essentially focused upon low power electronic appliances such as personal computers, chargers, television sets. The inverter output is regulated from 16-volt rms to 220-volt rms for a variation of load between 1-Ω to 180-Ω loads. The designed inverter provides a range of operation from 25 Watts to 250 Watts. The design is mathematically modeled which is simulated in Matlab, Proteus and finally the results are practically verified.

The use of Gaussian Mixture Models (GMM) are most common in speaker identification due to it can be performed in a completely text independent situation. However, it sounds efficient to speaker identification application, but it results long time processing in practice. In this paper, we propose a decision function by using vector quantization (VQ) techniques to decrease the training model for GMM in order to reduce the processing time. In our proposed modeling, we take the superiority of VQ, which is simplicity computation to distinguish between male and female speaker. Then, in second phase of classification, decision tree rule are applied to separate out the similar speaker in same gender into two difference group. While in phase 3, GMM is applied into the subgroup of speaker to get the accuracy rates. Experimental result shows that our hybrid VQ/GMM method always yielded better improvements in accuracy and bring almost 20% reduce in time processing.

Mobile ad-hoc network which is constructed via mobile nodes without the pre-registration of nodes have created problem in resource sharing. As nodes can join/leave the network randomly therefore nodes may not aware to which nodes is it connected with and this make resources been shared among anonymous nodes which can be trusted/not trusted. This has created unfavorable situation for private transaction. Hence a mechanism to formalize trustworthiness among these anonymous nodes is needed to make sure resources are shared among trusted nodes only. In this paper, we proposed a schema that can compute trust value among anonymous nodes. The schema is formed via direct and indirect approach. Parameters such as recommendation, reputation, knowledge, observation and context were used to evaluate the trust value. The result obtained from the calculation is then mapped with the access privileges to determine the action required.

Network congestion control is a critical issue, especially in the growing size, demand, and speed (bandwidth) of the increasingly integrated services networks. Designing effective congestion control strategies for these networks is a challenge because of the complexity of the structure of the networks, nature of the services supported, and the variety of the dynamic parameters involved. Congestion is not a resource shortage problem but a dynamic allocation problem. This paper present congestion avoidance using network based schemes solution.

This paper presents an application of mobile agent technology in distributed speech recognition over the internet. Mobile agent is one of a new paradigms for distributed application. With some advantages of using mobile agent for distributed application, we believe that mobile agent is a good idea to support distributed speech recognition over the internet. Speech is captured by clients, and after some local processing, the information is then sends to the server. The server recognized the speech according to an application framework and sends the result or action back to the client. In this paper, we develop the system by using JADE. JADE is one of the agents programming language and fully implemented in JAVA language.

An architecture design of the intelligent agent for speech recognition and translation is presented in this paper. The design involves the agent architecture and the method of the agent is used. The architecture design shows the relationship between the intelligent agent and speech recognition also translation. The intelligent agent for speech recognition is called S-AGENT and T-AGENT for translation. The purpose of the S-AGENT is to facilitate for transmitting the speech data via Internet or network. The S-AGENT is acting as a data transmit control to ensure the transmitted speech data is securely delivered. The task of the T-AGENT is different from the S-AGENT. The T-AGENT is acting as information retrieval. It processes the output from the speech recognition and translates the output based on its information memory database. If the information cannot be found on its memory, it searches the information required from the database dictionary provided. At the same time, it learns the information and saves the information to its memory for the future purpose.