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29,939 Article Results

Performance evaluation of 50MWp solar plant under different climatic conditions

10.11591/ijpeds.v13.i1.pp561-575
Mohamed Saleck Heyine , Ahmed Mohamed Yahya , Daha Hassan Daher , Léon Gaillard , Christophe Menezo , Abdel Kader Mahmoud
The aim of this study was to evaluate a performance analysis of a 50 MWp solar plant connected to the medium voltage electrical grid installed in the Saharan environment of Nouakchott, Mauritania. This study is done in two seasons characterizing the climate of Nouakchott, then in three typical days based on the measurement data that are obtained from the site of the installation. The measurements were collected daily, to improve the performance evaluation, real-time measurements with a step of 10 seconds for solar irradiation, ambient temperature, module temperature, wind speed, and electrical parameters. The performance evaluation was done based on the IEC 61724 standard to study the comportment of the power plant during different weather conditions. The total energy produced by the plant in May 2020 dry season is 10.559 GWh. However, the total energy produced in November 2019 wet season was 8.132 GWh. Besides, the energy injected by the plant into the grid was for a clear day 263.87 MWh, while for a cloudy day was 118.41 MWh, while it was 39.81 MWh for a sandstorm day. The results showed that temperature and irradiation play an important role in the performance of the system.
Volume: 13
Issue: 1
Page: 561-575
Publish at: 2022-03-01

Analysis of active islanding detection techniques for grid-connected inverters systems

10.11591/ijeecs.v25.i3.pp1287-1296
Naima Ikken , Nour-Eddine Tariba , Abdelhadi Bouknadel , Ahmed Haddou , Hafsa El Omari , Hamid El Omari
An island is a section of the electrical grid that contains producing assets and loads that are separated from the main grid and powered by these generators, such as solar systems, with voltage and frequency maintained at nominal levels. It's worth noting that the concept of islanding is linked to time. When the inverter detects an isolated grid activity for a particular period of time, the inverter is compelled to decouple from the general grid, according to the criteria that dictate the working principle of a photovoltaic (PV) systemThis paper presents research and comparisons of the main islanding detection techniques for single-phase systems based on various structures, as well as a comparison of the improvement of the traditional islanding detection method using three different methods (active frequency drift (AFD), slip mode phase shift (SMS) and Sandia frequency shift (SFS)). Under normal and abnormal operating conditions, a comparison of these three examined improvements was made. Additionally, physical security information management (PSIM) software simulation results are generated to test the performance and effectiveness of the effective technique plan.
Volume: 25
Issue: 3
Page: 1287-1296
Publish at: 2022-03-01

Artificial speech detection using image-based features and random forest classifier

10.11591/ijai.v11.i1.pp161-172
Choon Beng Tan , Mohd Hanafi Ahmad Hijazi , Frazier Kok , Mohd Saberi Mohamad , Puteri Nor Ellyza Nohuddin
The ASVspoof 2015 Challenge was one of the efforts of the research community in the field of speech processing to foster the development of generalized countermeasures against spoofing attacks. However, most countermeasures submitted to the ASVspoof 2015 Challenge failed to detect the S10 attack effectively, the only attack that was generated using the waveform concatenation approach. Hence, more informative features are needed to detect previously unseen spoofing attacks. This paper presents an approach that uses data transformation techniques to engineer image-based features together with random forest classifier to detect artificial speech. The objectives are two-fold: (i) to extract image-based features from the melfrequency cepstral coefficients representation of the speech signal and (ii) to compare the performance of using the extracted features and Random Forest to determine the authenticity of voices with the existing approaches. An audio-to-image transformation technique was used to engineer new features in classifying genuine and spoof voices. An experiment was conducted to find the appropriate combination of the engineered features and classifier. Experimental results showed that the proposed approach was able to detect speech synthesis and voice conversion attacks effectively, with an equal error rate of 0.10% and accuracy of 99.93%.
Volume: 11
Issue: 1
Page: 161-172
Publish at: 2022-03-01

Implementation of multicarrier PWM based 7-level Z-source cascaded H-bridge inverter

10.11591/ijpeds.v13.i1.pp322-329
Palanisamy Ramasamy , Vidyasagar Sugavanam , Kalyanasundaram Vakesan , Subbulakshmy Ramamurthi , Selvakumar Kuppusamy , Usha Sengamalai , Thamizh Thentral
This paper elucidates the realization of multicarrier pulse width modulation (MC-PWM) based 7-level Z-source cascaded H-bridge inverter. MC-PWM technique is developed to generate switching pulses for Z-source inverter; it leads to boost the inverter output voltage with help of shoot through mode of operation. The output of Z-source inverter is connected to 7-level cascaded H-bridge inverter. Cascaded H-bridge inverter system much suitable for AC load drive, high voltage and high power and industrial applications. This proposed system provides reduced total harmonic distortion, improved stepped output voltage and current, nearly sinusoidal output voltage and reduced voltage stress across the switching devices. The inductors and capacitors values are selected based on the boosting level of Z-source inverter. The simulation results of proposed 7-level Z-source cascaded H-bridge inverter with MC-PWM technique is verified using MATLAB/Simulink.
Volume: 13
Issue: 1
Page: 322-329
Publish at: 2022-03-01

Smart monitoring system of composite plates for structural health monitoring using electromechanical impedance approach

10.11591/ijeecs.v25.i3.pp1375-1382
Jayachitra Tanabalou , Rashmi Priyadarshini
The damage detection in structural health monitoring was performed in glass fiber composite plates and carbon nanotude composite plates. Electromechanical Impedance technique was used for identification of damage using lead zirconate titanate patches. Impact on composite structure was created artificially by drilling a hole in composite structures. Bolt stiffnesss were detected by loosening of bolts and nuts in the composite structures. Corrosion occurs due to the aging and change of environmental conditions. The novelty in this paper is the use of corroded bolts in composite structures and identified the effects of corrosion and compared the output signatures with potentiostat. In this paper common deformation detection in composite plates, measurement of bolt stiffness and effects of corrosion has been performed. Measurement of Impedance at different frequencies were normalized with the undamaged composite structures and considered as the reference signatures. These results have been analyzed and verified with the output from potentiostat.
Volume: 25
Issue: 3
Page: 1375-1382
Publish at: 2022-03-01

The trend of sharenting among Malaysian parents: a qualitative study on their content and motivation

10.11591/ijphs.v11i1.21193
Lee Jia Wen , Crendy Tan , Saroja Dhanapal
With social media having penetrated people’s daily life, sharenting has become a common phenomenon among the current generation. The term “sharenting” is derived from the combination of the words “share” and "parenting” which refers to parents who often post or share their children’s photos/videos on social media such as Facebook, Instagram, Snapchat, YouTube, Blog, and so on. Sharenting has resulted in a lot of consequences due to the sharing of children’s information. To understand the consequences of sharenting, the current research analysed the contents of children’s information that are shared by parents in Malaysia. The research also investigated the reasons that motivated parents to be involved in the trend of sharenting. A qualitative research adopting one-to-one interview was conducted to obtain in-depth information and knowledge from the respondents selected through a non-probability snowball sampling method. The responses from the interviews were analysed using a thematic analysis where it was noted that in terms of the content shared, two key themes emerged specifically funny and interesting photos as well as children’s educational progress. On the other hand, in terms of reasons for sharenting, the respondents listed several reasons including to keep in touch with friends/family members, to keep as memories, and gain support from others.
Volume: 11
Issue: 1
Page: 310-319
Publish at: 2022-03-01

Sliding mode control strategy based lead screw control design in electromechanical tracking drive system

10.11591/ijpeds.v13.i1.pp150-158
Tran Duc Chuyen , Van Hai Nguyen , Phuong Nam Dao , Nguyen Anh Tuan , Nguyen Van Toan
This article presents the research synthesis method of electromechanical tracking system for lead screw control using alternating current (AC) servo motors applied in machine tools, based on the framework of sliding mode control method and the state observer. Control algorithms are capable of compensating for perturbation components, with a state observation to be established to evaluate and compensate for uncertain nonlinear components. The chattering reduction techniques of sliding mode surface are proposed to improve the control effectiveness. The research results are verified by simulation on MATLAB-Simulink, showing that the proportional integral derivative (PID) controller has not met the control quality, but requires the sliding mode control law and state observation as proposed. Then this tracking drive system will work with better quality and can be developed for lead screw system of machine tool. The research results in the paper are also the completed development for calculating, designing, and manufacturing intelligent electrical drive systems in industrial applications.
Volume: 13
Issue: 1
Page: 150-158
Publish at: 2022-03-01

Implementation of reactive compensator for voltage balancing using AI based models and novel performance index

10.11591/ijpeds.v13.i1.pp594-605
Dana Ragab , Jasim Ghaeb
Voltage-unbalance is one of the power quality deficiencies that degrades electrical power systems performance. In this work, voltage unbalance problem is tackled through two stages; evaluation using a novel performance index and mitigation using a thyristor-controlled reactor (TCR) compensator with artificial intelligent (AI) based models. Unlike standard performance indices that rely on voltages' root mean square (RMS) values, the proposed index depends on the space vector (SV) signal amplitude for voltage unbalance evaluation. This signal depends on the instantaneous values of the three-phase voltages and has twice the system frequency. Therefore, the proposed index entitled as space vector unbalance factor (SVUF) reflects the amount of voltage unbalance and reduces the time necessary for evaluation by half. Subsequently, advanced models based on several algorithms are proposed to generate the required firing angles for TCR compensator to restore voltage balance, including radial basis functions networks (RBFNs), hybrid-RBFNs (H-RBFNs), polynomials (PNs), and simplified neural networks (NNs). Models' structure, prediction capability, and response time are analyzed. Results show that the time required for voltage unbalance mitigation is reduced. Moreover, the models used to generate the firing angles are simplified significantly while maintaining high accuracy.
Volume: 13
Issue: 1
Page: 594-605
Publish at: 2022-03-01

A single-phase bidirectional AC-AC converter with H-bridge energy buffer for wireless power transfer applications

10.11591/ijpeds.v13.i1.pp191-199
Nazmul Hasan , Tarak Saha
This paper introduces a single-phase bidirectional AC-AC Matrix type converter for wireless power transfer (WPT) applications. The proposed converter converts mains 50 Hz alternating current (AC) directly to high frequency 85 kHz AC without an intermediate direct current (DC) conversion stage. A minimum cost realization of only two bidirectional AC switches comprised each of two semiconductor device and one gate drive signal is employed. The converter operation modes are quantum energy injection and circulating self-oscillation. Elimination of the DC link introduces a sag in the power transfer during the zero crossing of input AC mains, which is well documented in literature. A novel H-bridge buffer structure is introduced which eliminates the power sag by storing energy during mains peak and delivering energy during the zero-crossing period. The converter operates with inherent zero current switching, thus achieving a low switching loss and electro-magnetic interference. The control feature ensures that the converter can be used for both static and dynamic wireless charging applications. The bidirectional power transfer capability ensures that the system can operate in both grid to vehicle (G2V) and vehicle to grid (V2G) power transfer modes. The proposed converter design is analyzed analytically and verified through thorough simulation study.
Volume: 13
Issue: 1
Page: 191-199
Publish at: 2022-03-01

Recognizing facial emotions for educational learning settings

10.11591/ijra.v11i1.pp21-32
Akputu Oryina Kingsley , Udoinyang G. Inyang , Ortil Msugh , Fiza T. Mughal , Abel Usoro
Educational learning settings exploit cognitive factors as ultimate feedback to enhance personalization in teaching and learning. But besides cognition, the emotions of the learner which reflect the affective learning dimension also play an important role in the learning process. The emotions can be recognized by tracking explicit behaviors of the learner like facial or vocal expressions. Despite reasonable efforts to recognize emotions, the research community is currently constraints by two issues, namely: i) the lack of efficient feature descriptors to accurately represent and prospectively recognize (detecting) the emotions of the learner; ii) lack of contextual datasets to benchmark performances of emotion recognizers in the learning-specific scenarios, resulting in poor generalizations. This paper presents a facial emotion recognition technique (FERT). The FERT is realized through results of preliminary analysis across various facial feature descriptors. Emotions are classified using the multiple kernel learning (MKL) method which reportedly possesses good merits. A contextually relevant simulated learning emotion (SLE) dataset is introduced to validate the FERT scheme. Recognition performance of the FERT scheme generalizes to 90.3% on the SLE dataset. On more popular but noncontextually datasets, the scheme achieved 90.0% and 82.8% respectively extended Cohn Kanade (CK+) and acted facial expressions in the wild (AFEW) datasets. A test for the null hypothesis that there is no significant difference in the performances accuracies of the descriptors rather proved otherwise (χ2=14.619,df=5,p=0.01212) for a model considered at a 95% confidence interval.
Volume: 11
Issue: 1
Page: 21-32
Publish at: 2022-03-01

Indonesian EFL students’ verbal episodes in proficiency pairings

10.11591/ijere.v11i1.22025
Ani Susanti , Utami Widiati , Bambang Yudi Cahyono , Tengku Intan Suzila Tengku Sharif
The quality of collaborative writing process to some extent depends on the verbal episodes occurring during the collaboration. This study aimed to describe English as a foreign language (EFL) students’ verbal episodes in proficiency pairings. A case study design was used in this study. It involved 40 EFL students of the English department in an Indonesian university. They were divided into two groups based on the types of proficiency pairings: heterogeneous (20 students) and homogenous (20 students). Therefore, this study was also intended to identify which of the two types of proficiency pairings produces more verbal episodes than the other. The verbal processes were audio recorded and then transcribed. The audio transcriptions were analyzed for common themes related to episode categorization. To ensure the reliability of the episode analysis, inter-coder, and intra-coder checks were employed. The results showed that Indonesian EFL students used three major types of verbal episodes: language-related episodes (LREs), text-related episodes (TREs), and scaffolding episodes (SEs). The study also revealed that proficiency levels determined the categories of LREs and SEs most frequently produced by the heterogeneous and homogeneous pairs. Both the heterogeneous and homogeneous pairs were likely to produce almost the same frequencies of categories of TREs more particularly in terms of organization and content. Further research might explore the link between the number of episodes and the learning gains.
Volume: 11
Issue: 1
Page: 431-440
Publish at: 2022-03-01

An efficient resource utilization technique for scheduling scientific workload in cloud computing environment

10.11591/ijai.v11.i1.pp367-378
Nagendra Prasad Sodinapalli , Subhash Kulkarni , Nawaz Ahmed Sharief , Prasanth Venkatareddy
Recently, number of data intensive workflow have been generated with growth of internet of things (IoT’s) technologies. Heterogeneous cloud framework has been emphasized by existing methodologies for executing these data-intensive workflows. Efficient resource scheduling plays a very important role provisioning workload execution on Heterogeneous cloud framework. Building tradeoff model in meeting energy constraint and workload task deadline requirement is challenging. Recently, number of multi-objective-based workload scheduling aimed at minimizing power budget and meeting task deadline constraint. However, these models induce significant overhead when demand and number of processing core increases. For addressing research problem here, the workload is modelled by considering each sub-task require dynamic memory, cache, accessible slots, execution time, and I/O access requirement. Thus, for utilizing resource more efficiently better cache resource management is needed. Here efficient resource utilization (ERU) model is presented. The ERU model is designed to utilize cache resource more efficiently and reduce last level cache failure and meeting workload task deadline prerequisite. The ERU model is very efficient when compared with standard resource management methodology in terms of reducing execution time, power consumption, and energy consumption for execution scientific workloads on heterogeneous cloud platform.
Volume: 11
Issue: 1
Page: 367-378
Publish at: 2022-03-01

Optimal economic dispatch using particle swarm optimization in Sulselrabar system

10.11591/ijai.v11.i1.pp221-228
Marhatang Marhatang , Muhammad Ruswandi Djalal
In this study, a particle swarm optimization (PSO) is proposed to optimize the cost of generating thermal plants in the South Sulawesi system. The study was con ducted by analyzing several methods using the lagrange and ant colony optimization (ACO). PSO algorithm converges on the 11th iteration algorithm with the lowest generation cost obtained, which is Rp129687962.17/hour. While the ACO algorithm converges on the 34th iteration with a generation cost of Rp131,473,269.39/hour. The results of optimization using PSO produce a total thermal power of 400.75 MW and losses of 26.15 MW. The PSO method is able to reduce the cost of generating the South Sulawesi system by Rp11,118,312.07/hour or 7.9%. While using the ACO method generates a generation cost of Rp131,473,269.39/hour to generate power of 400,812 MW with losses of 26,219 MW. The ACO method is able to reduce the cost of generating the South Sulawesi system by Rp9,333,004.9/hour or 6.62%. PSO algorithm provides the lowest cost calculation of generator compared with conventional methods and ACO smart methods. This is also shown in the calculation process, the PSO method completes calculations faster than the ACO method.
Volume: 11
Issue: 1
Page: 221-228
Publish at: 2022-03-01

A smart door prototype with a face recognition capability

10.11591/ijra.v11i1.pp1-9
Ivan Surya Hutomo , Handy Wicaksono
This research aimed to integrate a face recognition capability in a smart door prototype. By using a camera-based face recognition, the house owner does not need to make physical contact to open the door. Avoid physical contact is important due to the coronavirus disease 2019 (COVID19) pandemic. Raspberry Pi 3B was used as the main controller, while a servo motor was utilized as a locking door actuator. The program was developed using Node-RED, Blynk, and message queue telemetry transport (MQTT) platforms which are very powerful for developing internet of things (IoT) devices. All of the programs were coded using Python. Haar cascade and local binary pattern histogram methods were implemented on the face recognition stage. Google Assistant integration was done by using Dialogflow and Firebase as Google Cloud services. Integration of face recognition and the smart door was successful. The smart door was unlocked if faces were recognized (average threshold=60%). If a face was not recognized, an email notification containing a face image is sent to the house owner. The Google Assistant could handle user requests successfully with a success rate of 92.8% from 147 trials.
Volume: 11
Issue: 1
Page: 1-9
Publish at: 2022-03-01

Active object search using a pyramid approach to determine the next-best-view

10.11591/ijra.v11i1.pp70-88
Karen-Lizbeth Flores-Rodriguez , Felipe Trujillo-Romero , Jose-Joel Gonzalez-Barbosa
The development of service robotics continues to arouse interest in the scientific community due to the complexity of the activities performed like interaction in human environments, identifying and manipulating objects, and even learning by themselves. This paper proposed to improve the perception of the environment by searching for objects in service robotics tasks. We present the development and implementation of an active object search method based on three main phases: Firstly, image pyramid segmentation to examine in detail the im- age features. Second step, object detection at each level of the pyramid through a local feature descriptor and a mutual information calculation. Finally, the next camera position selection through analyzing the object detections accumulation in the pyramid. To evaluate the implementation of the proposed method, we use a NAO robot in a familiar place for humans, such as an office or a home. Ordinary objects are part of our database with the premise that a robot must know them before looking for an object. The results in the experiments showed an acceptable performance in simulation and with a real platform.
Volume: 11
Issue: 1
Page: 70-88
Publish at: 2022-03-01
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