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Now showing 1 - 20 of 4271

1700 nm and 1800 nm band tunable thulium doped mode-locked fiber lasers
(Nature Publishing Group, 2017)
Emami S.D.
;
Dashtabi M.M.
;
Lee H.J.
;
Arabanian A.S.
;
Rashid H.A.A.
;
20433709400
;
35368173000
;
57190622221
;
36025017300
;
56055976300
This paper presents short wavelength operation of tunable thulium-doped mode-locked lasers with sweep ranges of 1702 to 1764 nm and 1788 to 1831 nm. This operation is realized by a combination of the partial amplified spontaneous emission suppression method, the bidirectional pumping mechanism and the nonlinear polarization rotation (NPR) technique. Lasing at emission bands lower than the 1800 nm wavelength in thulium-doped fiber lasers is achieved using mode confinement loss in a specially designed photonic crystal fiber (PCF). The enlargement of the first outer ring air holes around the core region of the PCF attenuates emissions above the cut-off wavelength and dominates the active region. This amplified spontaneous emission (ASE) suppression using our presented PCF is applied to a mode-locked laser cavity and is demonstrated to be a simple and compact solution to widely tunable all-fiber lasers. � 2017 The Author(s).
10
3D elastic deformable object model for robot manipulation purposes
(Fuji Technology Press, 2014)
Sahari K.S.M.
;
Hou Y.C.
;
57218170038
;
37067465000
This paper presents a mass-spring model applied to the manipulation of an elastic deformable object for home service robot application. A system is also proposed that is used to fold a piece of rectangular cloth from a specific initial condition using a robot. The cloth is modeled as a three-dimensional object in a two-dimensional quadrangular mesh based on a massspring system, and its state is estimated using an explicit integration scheme that computes the particle position as a function of the internal and external forces acting on the elastic deformable object. The current state of the elastic deformable object under robot manipulation is tracked based on the trajectory of the mass points in the mass-spring system model in a self-developed simulator, which integrates a massspring model and a five-degree-of-freedom articulated robotic arm. To test the reliability of the model, the simulator is used to predict the best possible paths for using the robotic arm to fold a rectangular cloth into two. In the test, the state of the object is derived from the model and then compared with the results of a practical experiment. Based on the test, the error is found to be generally acceptable. Thus, this model can be used as an estimator for the vision-based tracking of the state of an elastic deformable object for manipulation by home service robots.
2
3D printing of high solid loading zirconia feedstock via screw-based material extrusion
(Elsevier Ltd, 2023)
Lim I.Y.
;
Ting C.H.
;
Ng C.K.
;
Tey J.Y.
;
Yeo W.H.
;
S R.
;
Lee K.Y.S.
;
Chuah Y.D.
;
Teng W.D.
;
58203510000
;
57193357476
;
57190445131
;
56042122900
;
26024539700
;
57195516031
;
57221177925
;
36561357900
;
36855788900
Zirconia ceramic (3Y-TZP) feedstocks with solid loadings from 50 vol% to 68 vol%, in a 60:40 paraffin wax to LDPE ratio binder system, were prepared and printed using a screw-based material extrusion printer. A two-step debinding process involving solvent debinding (cyclohexane + ethanol) and thermal debinding (140 �C�600 �C at 0.2 �C/min) followed by sintering at 1500 �C for 2 h was employed. Tests performed include TGA, density test, Vickers hardness and fracture toughness, XRD, and SEM. The TGA result showed two significant drops in weight starting at 180 �C and 380 �C, which corresponds to the decomposition of paraffin wax and LDPE, respectively. A minimum of 40 wt% of soluble binder was removed from the green sample after solvent immersion for 3 h at 40 �C for solid loadings ?55 vol%. High solid loading feedstocks produced samples with comparable density, Vickers hardness and fracture toughness, which are 97.5%, ?12.3 GPa, and ?5.5 MPa m1/2, respectively
9
5E analysis of a novel designed hot water storage header integrated vacuum tube solar water heater
(Elsevier Ltd, 2023)
Chopra K.
;
Tyagi V.V.
;
Pathak S.K.
;
Sharma R.K.
;
Mansor M.
;
Goel V.
;
Sari A.
;
57200420308
;
15078199200
;
57221807296
;
56424398200
;
6701749037
;
57892187100
;
7006342950
In this study, 5-E analysis of a heat pipe equipped vacuum tube collector system for residential warm water application has been carried out. The issue of overheating in heat pipes and low thermal efficiency is the major key issues associated with heat pipe vacuum tube collector. This design completely removes the problem of overheating. In addition to this copper fins mounting with condensers of heat pipe enhance the heat transmission rate between the condenser & water stored in a manifold. The results of an experimental investigation reveal that thermal and exergy outputs of the proposed system were obtained almost 63�74% and 4�10% respectively. The average energy gain at the end of the days selected for Run-A, B, and C was calculated to be 7505, 6912, and 6619 kJ respectively, whereas the average exergy gain for corresponding runs was found to be 928, 700, and 401 kJ respectively. In addition to this, the proposed system can provide hot water of approximately 125 L, 76 L, and 52 L in temperatures 50 �C, 55 �C, and 60 �C respectively. Concerning to techno-economic investigation, the per liter cost of warm water generation for the proposed & electric geyser was observed to be 0.15 INR/L & 0.47 INR/L respectively. The levelized energy cost, net present worth, and payback time were found to be 5.48 INR/kWh, 55,819 INR, and 4.12 years respectively. The amount of CO2 mitigation by the developed system was found to be 18.76, 17.28, and 16.54 tCO2/lifetime for Run-A, B & C respectively. � 2023
4
5G New Radio: Dynamic Time Division Duplex Radio Resource Management Approaches
(Institute of Electrical and Electronics Engineers Inc., 2021)
Samidi F.S.
;
Radzi N.A.M.
;
Ahmad W.S.H.M.W.
;
Abdullah F.
;
Jamaludin M.Z.
;
Ismail A.
;
57215054855
;
57218936786
;
25928314500
;
56613644500
;
57216839721
;
36023817800
The Internet of Everything is currently in demand and has burdened the network tremendously. Accommodating this exponential increase in demand will require improved Radio Resource Management technology. This problem can be curbed with higher spectrum bands, reevaluation of Time Division Duplex, deployment of Software Defined Network, and Network Function Virtualization into 5G New Radio (NR) network. Therefore, this work aims to provide an in-depth survey on the recent resource management schemes that can be proposed for 5G NR enhancement by exploiting both rule-based algorithms and machine learning methods. Radio resource management consists of managing user allocation, the antenna transmission power, bandwidth, and modulation scheme. Therefore, in this paper, three categories of radio resource management technologies are introduced: resource allocation, energy efficiency, and interference management. The discussion revolves around their potentials and contributions as well as challenges faced to produce efficient 5G resource management schemes. � 2013 IEEE.
43
5G Technology: ML Hyperparameter Tuning Analysis for Subcarrier Spacing Prediction Model
(MDPI, 2022)
Samidi F.S.
;
Mohamed Radzi N.A.
;
Mohd Azmi K.H.
;
Mohd Aripin N.
;
Azhar N.A.
;
57215054855
;
57218936786
;
57982272200
;
57858108600
;
57219033091
Resource optimisation is critical because 5G is intended to be a major enabler and a leading infrastructure provider in the information and communication technology sector by supporting a wide range of upcoming services with varying requirements. Therefore, system improvisation techniques, such as machine learning (ML) and deep learning, must be applied to make the model customisable. Moreover, improvisation allows the prediction system to generate the most accurate outcomes and valuable insights from data whilst enabling effective decisions. In this study, we first provide a literature study on the applications of ML and a summary of the hyperparameters influencing the prediction capabilities of the ML models for the communication system. We demonstrate the behaviour of four ML models: k nearest neighbour, classification and regression trees, random forest and support vector machine. Then, we observe and elaborate on the suitable hyperparameter values for each model based on the accuracy in prediction performance. Based on our observation, the optimal hyperparameter setting for ML models is essential because it directly impacts the model�s performance. Therefore, understanding how the ML models are expected to respond to the system utilised is critical. � 2022 by the authors.
4
5G Technology: Towards Dynamic Spectrum Sharing Using Cognitive Radio Networks
(Institute of Electrical and Electronics Engineers Inc., 2020)
Ahmad W.S.H.M.W.
;
Radzi N.A.M.
;
Samidi F.S.
;
Ismail A.
;
Abdullah F.
;
Jamaludin M.Z.
;
Zakaria M.N.
;
25928314500
;
57218936786
;
57215054855
;
36023817800
;
56613644500
;
57216839721
;
57213826693
The explosive popularity of small-cell and Internet of Everything devices has tremendously increased traffic loads. This increase has revolutionised the current network into 5G technology, which demands increased capacity, high data rate and ultra-low latency. Two of the research focus areas for meeting these demands are exploring the spectrum resource and maximising the utilisation of its bands. However, the scarcity of the spectrum resource creates a serious challenge in achieving an efficient management scheme. This work aims to conduct an in-depth survey on recent spectrum sharing (SS) technologies towards 5G development and recent 5G-enabling technologies. SS techniques are classified, and SS surveys and related studies on SS techniques relevant to 5G networks are reviewed. The surveys and studies are categorised into one of the main SS techniques on the basis of network architecture, spectrum allocation behaviour and spectrum access method. Moreover, a detailed survey on cognitive radio (CR) technology in SS related to 5G implementation is performed. For a complete survey, discussions are conducted on the issues and challenges in the current implementation of SS and CR, and the means to support efficient 5G advancement are provided. � 2013 IEEE.
1
A 9- and 13-Level Switched-Capacitor-Based Multilevel Inverter With Enhanced Self-Balanced Capacitor Voltage Capability
(Institute of Electrical and Electronics Engineers Inc., 2022)
Islam S.
;
Siddique M.D.
;
Iqbal A.
;
Mekhilef S.
;
55432805800
;
57200143813
;
7005402806
;
57928298500
Boost action is required for enhancing the output voltage of the sources such as photovoltaic (PV) sources, fuel cells, and battery storage devices, which eliminates the need for additional units. For this purpose, switched-capacitor (SC)-based multilevel inverters (SC-MLIs) are widely used. The proposed SC-based single-phase MLI is able to produce 13-level output ac voltage and furnishes voltage gains of 3 and 6. The same topology is also able to produce a single-phase nine-level ac output with a voltage gain of 4. The abovementioned voltage levels and voltage gains are achieved using the proposed topology just by modifying the switching strategy used for firing the switches and do not require any modification in the proposed SC-MLI structure. The proposed configuration of single-phase MLI requires less switch count to produce 9- and 13-level ac output voltages with the abovementioned voltage gains. The switches connected in the proposed configuration undergo less voltage stress compared to the MLIs suggested in the literature. The comparison of the proposed converter topology with the existing MLIs reported in the literature is included. The validation of the performance of the proposed inverter is carried out using experimental results captured on a low-power laboratory prototype. � 2021 IEEE.
9
Ab initio insight into the physical properties of MgXH3 (X = Co, Cu, Ni) lead-free perovskite for hydrogen storage application
(Springer, 2023)
Rehman Z.
;
Rehman M.A.
;
Rehman B.
;
Sikiru S.
;
Qureshi S.
;
Ali E.M.
;
Awais M.
;
Amjad M.
;
Iqbal I.
;
Rafique A.
;
Bibi S.
;
57225362130
;
57204391658
;
57355281700
;
57211063469
;
56247296300
;
57004451100
;
57940545000
;
57976351200
;
58832018200
;
57219255410
;
56400623400
Renewable energy systems are vital for a sustainable future, where solid-state hydrogen storage can play a crucial role. Perovskite hydride materials have attracted the scientific community for hydrogen storage applications. The current work focuses on the theoretical study using density functional theory (DFT) to evaluate the characteristics of MgXH3 (X = Co, Cu, Ni) hydrides. The structural, vibrational, electronic, mechanical, thermodynamic, and hydrogen storage properties of these hydrides were investigated. The equilibrium lattice parameters were calculated using the Birch-Murnaghan equation of state-to-energy volume curves. The elastic constants (Cij) and relevant parameters, such as Born criteria, were calculated to confirm the mechanical stability of the hydrides. The Cauchy pressure (C p) revealed brittle or ductile behavior. The outcomes of the Pugh ratio, Poisson ratio, and anisotropy were also calculated and discussed. The absence of negative lattice vibrational frequencies in phonon dispersion confirmed the lattice�s dynamic stability. The heat capacity curves of thermodynamic properties revealed that hydrides can conduct thermal energy. The metallic character and ample interatomic distances of hydrides were confirmed by the band structure and population analysis, which confirmed that hydrides can conduct electrical energy and adsorb hydrogen. The density of state (DOS) and partial DOS unveiled the role of specific atoms in the DOS of the crystal. The calculated gravimetric hydrogen storage capacity of MgCoH3, MgCuH3, and MgNiH3 hydrides was 3.64, 3.32, and 3.49wt%, respectively. Our results provide a deeper understanding of its potential for hydrogen storage applications through a detailed analysis of MgXH3 (X = Co, Cu, Ni) perovskite hydride material. � 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
7
Abnormal event detection in indoor environment based on acoustic signal processing
(Little Lion Scientific, 2021)
Abdrakhmanov R.
;
Tolep A.
;
Kozhamkulova Z.
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Narbekov N.
;
Dossanov N.
;
Yeskarayeva B.
;
57222085447
;
57133046300
;
57224359860
;
57224366230
;
57224352870
;
57133026800
Alert the public about emergencies is to bring to public alerts and emergency information on dangers arising from the threat or occurrence of emergency situations of natural and technogenic character, as well as the conduct of hostilities or owing to these actions, the rules of behavior of the population and the need for protection activities. The aim of the work is to develop a method for detecting the sounds of critical situations in the sound stream. In this paper, the term "critical situation" is understood as an event, the characteristic sound signs of which can speak of acoustic artifacts (a shot, a scream, a glass strike, an explosion, a siren, etc.). The developed method allows you to classify events into two groups: Normal (for example, street noise) and critical situations (for example, an explosion, a scream, a shot). To determine events, machine learning is used, namely the Support Vector Machine method, which solves classification and regression problems by constructing a nonlinear plane separating the solutions. SVM has a fairly wide application in data classification and shows good results in event detection problems. As part of the work, the minimum set of features for the machine learning model was determined, small training and test samples were formed, and a method was developed that classifies normal and abnormal events. � 2021 Little Lion Scientific. All rights reserved.
10
AC Susceptibility and Electrical Properties of BiFeO3 Nanoparticles Added Bi1.6Pb0.4Sr2Ca2Cu3O10 Superconductor
(Springer, 2023)
Suib N.R.M.
;
Ilhamsyah A.B.P.
;
Mujaini M.
;
Mahat A.M.
;
Abd-Shukor R.
;
24072061100
;
57209134726
;
54982692300
;
55443318400
;
7004750914
The effect of bismuth ferrite (BiFeO3) nanoparticles (~ 20�nm) on Bi1.6Pb0.4Sr2Ca2Cu3O10 (Bi-2223) superconductor was studied. Bi-2223 powders with starting formula Bi1.6Pb0.4Sr2Ca2Cu3O10(BiFeO3)x for x = 0�0.20 wt.% were prepared using the co-precipitation method. The temperature dependent electrical resistance measurements showed the highest superconducting transition temperature for the x = 0.10 wt. % sample (Tc-onset = 118�K, Tc-zero = 106�K). The highest transport critical current density, Jct at 40�K was shown by the x = 0.02 wt. % sample (21.93 A cm?2). The peak temperature of imaginary part of susceptibility, Tp was much higher compared with the non-added sample, indicating BiFeO3 nanoparticles enhanced the flux pinning energy and intergranular coupling. The addition of a small amount of BiFeO3 nanoparticles (0.02�0.04% wt.%) increased the transport critical current density while further additions (0.06�0.20 wt.%) improved the superconducting transition temperatures. BiFeO3 nanoparticles slightly suppressed the formation of the Bi-2223 phase, but it increased the transport critical current density by more than eleven times demonstrating BFO could act as effective pinning centres and enhanced connectivity between grains. This work showed that BiFeO3 was better than other nanoparticles such as Ni0.5Zn0.5Fe2O4, Cr2O3, NiFe2O4, MgO, ZnO and Co3O4 in improving the transition temperatures and critical current density of the Bi-2223 phase superconductor. � 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
8
Academics' profile and perceived institutional leadership practices in public and private universities
(Edelweiss Publications Inc, 2023)
Abdullah N.S.
;
Azman N.M.
;
Ghani E.
;
Muhammad K.
;
Ilias A.
;
Jais I.R.M.
;
59097405800
;
58788345200
;
35098434100
;
56926348400
;
30967552600
;
57220604410
This study analyses the profiles of academics and their perceived institutional leadership practices at their universities. A questionnaire survey was conducted among 1771 academics from Malaysian public and private universities. The results of the survey show that women make up the majority of academics in universities, and most of them hold at least a master's degree. The academics at the universities have an average of more than six years of professional experience, and most of them are senior lecturers and associate professors. Many of the professors are or have been in senior positions. The study also shows that the majority of academics believe that the selection of senior staff at their universities is well controlled and that procedures are followed. Their universities also offer a talent pool system for institutional leaders. Academics are selected as institutional leaders on a rotational basis, and their appointment is duly publicized. However, the results of this study show that many universities continue to appoint and nominate future leaders under the old system rather than the new system. The study also shows that academics, whether from public or private universities, have similar views on the procedures of institutional leadership in their respective universities. The academics are generally in favor of the institutional governance approaches at their universities. The results of the study may be valuable in planning talent management for younger members of the academic community, as succession planning requires early intervention rather than identifying key leaders without a focus on talent management. � 2023 by the authors.
7
Accelerated thermal cycle and chemical stability testing of polyethylene glycol (PEG) 6000 for solar thermal energy storage
(Elsevier B.V., 2016)
Sharma R.K.
;
Ganesan P.
;
Tyagi V.V.
;
Mahlia T.M.I.
;
56424398200
;
55329358900
;
15078199200
;
56997615100
Accelerated thermal cycle test of polyethylene glycol (PEG) of molecular weight 6000, an organic phase change material (O-PCM), has been carried out for 1500 melt/freeze cycles. The latent heat of fusion and melting temperature is measured using differential scanning calorimeter between 0th and 1500th melt-freeze cycles to study the changes in its thermal properties. Also, the changes in the compositional/functional groups of the material during the cycle test are also measured using FT-IR spectroscopy technique. The melting temperature is found to be stable in the quoted range of 55-60 �C with a maximum deviation of 6.5% when compared to that of at 0th cycle. However, a gradual drop in the latent heat of fusion with the increasing number of thermal cycles is measured. The FT-IR spectra do not show any noticeable changes in the peaks which confirm its compositional stability even after the higher number of thermal cycles. Thermal and chemical reliability tests of PEG 6000 along with the techno-economic analysis have shown that this PCM has a significant potential to be used as a thermal energy storage system. � 2015 Elsevier B.V. All rights reserved.
7
Accelerated thermal cycling test of microencapsulated paraffin wax/polyaniline made by simple preparation method for solar thermal energy storage
(2013)
Silakhori M.
;
Naghavi M.S.
;
Metselaar H.S.C.
;
Mahlia T.M.I.
;
Fauzi H.
;
Mehrali M.
;
55551495400
;
42062005000
;
57218580099
;
56997615100
;
55802575800
;
55639087200
Microencapsulated paraffin wax/polyaniline was prepared using a simple in situ polymerization technique, and its performance characteristics were investigated. Weight losses of samples were determined by Thermal Gravimetry Analysis (TGA). The microencapsulated samples with 23% and 49% paraffin showed less decomposition after 330 �C than with higher percentage of paraffin. These samples were then subjected to a thermal cycling test. Thermal properties of microencapsulated paraffin wax were evaluated by Differential Scanning Calorimeter (DSC). Structure stability and compatibility of core and coating materials were also tested by Fourier transform infrared spectrophotometer (FTIR), and the surface morphology of the samples are shown by Field Emission Scanning Electron Microscopy (FESEM). It has been found that the microencapsulated paraffin waxes show little change in the latent heat of fusion and melting temperature after one thousand thermal recycles. Besides, the chemical characteristics and structural profile remained constant after one thousand thermal cycling tests. Therefore, microencapsulated paraffin wax/polyaniline is a stable material that can be used for thermal energy storage systems. � 2013 by the authors; licensee MDPI, Basel, Switzerland.
2
Accelerating charge transfer via nonconjugated polyelectrolyte interlayers toward efficient versatile photoredox catalysis
(Nature Research, 2021)
Li T.
;
Feng C.
;
Yap B.K.
;
Zhu X.
;
Xiong B.
;
He Z.
;
Wong W.-Y.
;
57113889100
;
57221980511
;
26649255900
;
14029419400
;
55570895400
;
35364405700
;
7403972153
One of the challenges for high-efficiency single-component-based photoredox catalysts is the low charge transfer and extraction due to the high recombination rate. Here, we demonstrate a strategy to precisely control the charge separation and transport efficiency of the catalytic host by introducing electron or hole extraction interlayers to improve the catalytic efficiency. We use simple and easily available non-conjugated polyelectrolytes (NCPs) (i.e., polyethyleneimine, PEI; poly(allylamine hydrochloride), PAH) to form interlayers, wherein such NCPs consist of the nonconjugated backbone with charge transporting functional groups. Taking CdS as examples, it is shown that although PEI and PAH are insulators and therefore do not have the ability to conduct electricity, they can form good electron or hole transport extraction layers due to the higher charge-transfer kinetics of pendant groups along the backbones, thereby greatly improving the charge transfer capability of CdS. Consequently, the resultant PEI-/PAH-functionalized nanocomposites exhibit significantly enhanced and versatile photoredox catalysis. � 2021, The Author(s).
3
Accelerator-based human activity recognition using voting technique with NBTree and MLP classifiers
(Insight Society, 2017)
Azmi M.S.M.
;
Sulaiman M.N.
;
36994351200
;
22434244300
In evolution and ubiquitous computing systems, accelerometer-based human activity recognition has huge potential in a large number of application domains. Accelerometer-based human activity recognition aims to identify physical activities performed by human using accelerometer; a sensor device attached to the body and returns an actual valued estimate of acceleration along the x, y- and z-axes from which the sensor location can be estimated. In this study, an accelerator-based activity recognition model using voting technique was proposed. Two machine learning classifiers, Naive Bayes Tree (NBTree) and Multilayer Perceptron (MLP), were used as ensemble classifiers in the voting technique. To evaluate the proposed voting technique, the performance of selected individual classifiers and existing voting technique was first examined, followed by the experiment to determine the performance of the proposed model. All of the experiments were performed using a standard dataset called Wireless Sensor Data Mining involving six physical human activities; jogging, walking, walking towards upstairs, walking towards downstairs, sitting and stand still. Results showed that the proposed voting technique with NBTree and MLP ensemble classifiers outperformed other individual classifiers and another previously suggested voting technique for accelerometer-based human activity recognition.
4
Acceptance of dance training system based on augmented reality and technology acceptance model (TAM)
(Springer Science and Business Media Deutschland GmbH, 2022)
Iqbal J.
;
Sidhu M.S.
;
57200394167
;
56259597000
The advancement in Computer Vision (CV) has evolved drastically from image processing to object recognition, tracking video, restoration of images, three-dimensional (3D) pose recognition, and emotion analysis. These advancements have eventually led to the birth of Augmented Reality (AR) technology, which means embedding virtual objects into the real-world environment. The primary focus of this research was to solve the long-term learning retention and poor learning efficiency for mastering a dance skill through the AR technology based on constructivism learning theory, Dreyfus model and Technology Acceptance Model (TAM). The problem analysis carried out in this research had major research findings, in which the retention and learning efficiency of a dance training system were predominantly determined through the type of learning theory adopted, learning environment, training tools, skill acquisition technology and type of AR technique. Therefore, the influential factors for the user acceptance of AR-based dance training system (ARDTS) were based on quantitative analysis. These influential factors were determined to address the problem of knowledge gap on acceptance of AR-based systems for dance education through self-learning. The evaluation and testing were conducted to validate the developed and implemented ARDTS system. The Technology Acceptance Model (TAM) as the evaluation model and quantitative analysis was done with a research instrument that encompassed external and internal variables. TAM consisted of 37 items, in which six factors were used to assess the new developed ARDTS by the authors and its acceptability among 86 subjects. The current study had investigated the potential use of AR-based dance training system to promote a particular dance skill among a sample population with various backgrounds and interests. The obtained results support a general acceptance towards ARDTS among the users who are interested in exploring the cutting-edge technology of AR for gaining expertise in a dance skill. � 2021, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.
8
Accretion of Indonesia�s energy sector through renewable energy
(Taylor's University, 2019)
Khattak M.A.
;
Borhana Omran A.A.
;
Andjani H.N.
;
Ainun Mardhiah N.
;
Kazi S.
;
55909928700
;
55212152300
;
57212444640
;
57212875680
;
25824975100
As the global demand towards conventional fossil fuels is persistently increasing over the decades, exploring the potential of other sources of alternative energy is a crucial measure to have more diversified supply of energy and to anticipate unexpected scenarios where the availability of fossil fuels becomes uncertain as it cannot be equally distributed in order to satisfy the customers� energy needs. This paper scrutinizes the contribution of renewable energy to the future global energy mix and the encountered challenges in energy development. When implementing renewable energy in our country, it has its own challenges due to the technological barriers among the other countries. However, it also gives benefits to the country itself when CO2 emission can be reduced and become more environmentally friendly, especially to society and ecology. The study was conducted based on Indonesia�s scenario, incorporating two specific examples of renewables namely, biofuel and geothermal energy. This paper further assesses the existing challenges associated with renewable energy development and the latest proposed solution to secure Indonesia�s energy supply. � School of Engineering, Taylor�s University.
1
Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy
(MDPI AG, 2019)
Ehteram M.
;
Ahmed A.N.
;
Fai C.M.
;
Afan H.A.
;
El-Shafie A.
;
57113510800
;
57214837520
;
57214146115
;
56436626600
;
16068189400
The estimation of solar radiation for planning current and future periods in different fields, such as renewable energy generation, is very important for decision makers. The current study presents a hybrid model structure based on a multi-objective shark algorithm and fuzzy method for forecasting and generating a zone map for solar radiation as an alternative solution for future renewable energy production. The multi-objective shark algorithm attempts to select the best input combination for solar radiation (SR) estimation and the optimal value of the adaptive neuro-fuzzy inference system (ANFIS) parameter, and the power parameter of the inverse distance weight (IDW) is computed. Three provinces in Iran with different climates and air quality index conditions have been considered as case studies for this research. In addition, comparative analysis has been carried out with other models, including multi-objective genetic algorithm-ANFIS and multi-objective particle swarm optimization-ANFIS. The Taguchi model is used to obtain the best value of random parameters for multi-objective algorithms. The comparison of the results shows that the relative deviation index (RDI) of the distributed solutions in the Pareto front based multi-objective shark algorithm has the lowest value in the spread index, spacing metric index, favorable distribution, and good diversity. The generated Pareto solutions based on the multi-objective shark algorithm are compared to those based on the genetic algorithm and particle swarm algorithm and found to be the optimal and near ideal solutions. In addition, the determination of the best solution based on a multi-criteria decision model enables the best input to the model to be selected based on different effective parameters. Three different performance indices have been used in this study, including the root mean square error, Nash�Sutcliffe efficiency, and mean absolute error. The generated zone map based on the multi-objective shark algorithm-ANFIS highly matches with the observed data in all zones in all case studies. Additionally, the analysis shows that the air quality index (AQI) should be considered as effective input for SR estimation. Finally, the measurement and analysis of the uncertainty based on the multi-objective shark algorithm-ANFIS were carried out. As a result, the proposed new hybrid model is highly suitable for the generation of accurate zone mapping for different renewable energy generation fields. In addition, the proposed hybrid model showed outstanding performance for the development of a forecasting model for the solar radiation value, which is essential for the decision-makers to draw a future plan for generating renewable energy based solar radiation. � 2019 by the authors.
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An accurate medium-term load forecasting based on hybrid technique
(Institute of Advanced Engineering and Science, 2018)
Yasin Z.M.
;
Aziz N.F.A.
;
Salim N.A.
;
Wahab N.A.
;
Rahmat N.A.
;
57211410254
;
57221906825
;
36806685300
;
35790572400
;
55647163881
An accurate medium term load forecasting is significant for power generation scheduling, economic and reliable operation in power system. Most of classical approach for medium term load forecasting only consider total daily load demand. This approach may not provide accurate results since the load demand is fluctuated in a day. In this paper, a hybrid Ant-Lion Optimizer Least-square Support Vector Machine (ALO-LSSVM) is proposed to forecast 24-hour load demand for the next year. Ant-Lion Optimizer (ALO) is utilized to optimize the RBF Kernel parameters in Least-Square Support Vector Machine (LS-SVM). The objective of the optimization is to minimize the Mean Absolute Percentage Error (MAPE). The performance of ALO-LSSVM technique was compared with those obtained from LS-SVM technique through a 10-fold cross-validation procedure. The historical hourly load data are analyzed and appropriate features are selected for the model. There are 24 inputs and 24 outputs vectors for this model which represents 24-hour load demand for whole year. The results revealed that the high accuracy of prediction could be achieved using ALO-LSSVM. � 2018 Institute of Advanced Engineering and Science All rights reserved.
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