bluuebunny/crossref_metadata_2025 huggingface dataset:
The calculation of point quantity for lighting based on android OS using ionic framework and rule based expert system
Authors: Mufadhol Mufadhol , Hartono Budi , Sulartopo Sulartopo , Dewi Maya Utami , Danang Danang , Aryotejo Guruh
Published: December 2021

At this time, the Covid-19 pandemic has not been finished so all activities and expenditure of funds must be economical. On the each building will be required electricity resources as a means for lighting the room. Reduced activities carried out outside the room make people carry out activities indoors, this results in a significant increase in electricity consumption for lighting. PT. PLN as the provider in Indonesia of electricity services for the community experiences a shortage of electricity resources and most of the electricity resources are used for lighting purposes. Indonesia as a developing country has a very large of population growth, so it requires many buildings as a place to live or a place of business and other activities. This paper will be discussion how a smartphone with an Android operating system can be used to determining the lighting requirements using the Ionic Framework and Rule Based Expert Systems. Using this application system, so electricity to lighting can be optimal and not too wasteful, which in turn can save on the use of electrical energy resources and can save of the cost.
Customized moodle-based learning management system for socially disadvantaged schools
Authors: Utami Ika Qutsiati , Fakhruzzaman Muhammad Noor , Fahmiyah Indah , Masduki Annaura Nabilla , Kamil Ilham Ahmad
Published: December 2021

This study aims to develop Moodle-based LMS with customized learning content and modified user interface to facilitate pedagogical processes during covid-19 pandemic and investigate how teachers of socially disadvantaged schools perceived usability and technology acceptance. Co-design process was conducted with two activities: 1) need assessment phase using an online survey and interview session with the teachers and 2) the development phase of the LMS. The system was evaluated by 30 teachers from socially disadvantaged schools for relevance to their distance learning activities. We employed computer software usability questionnaire (CSUQ) to measure perceived usability and the technology acceptance model (TAM) with insertion of 3 original variables (i.e., perceived usefulness, perceived ease of use, and intention to use) and 5 external variables (i.e., attitude toward the system, perceived interaction, self-efficacy, user interface design, and course design). The average CSUQ rating exceeded 5.0 of 7 point-scale, indicated that teachers agreed that the information quality, interaction quality, and user interface quality were clear and easy to understand. TAM results concluded that the LMS design was judged to be usable, interactive, and well-developed. Teachers reported an effective user interface that allows effective teaching operations and lead to the system adoption in immediate time.
Design of a dual-band antenna for energy harvesting application
Authors: Said Maizatul Alice Meor , Jaya Syed Mohd Iqwan Naqiuddin Syed , Zakaria Zahriladha , Misran Mohamad Harris , Ismail Mohd Muzafar
Published: December 2021

This report presents an investigation on how to improve the current dual-band antenna to enhance the better result of the antenna parameters for energy harvesting application. Besides that, to develop a new design and validate the antenna frequencies that will operate at 2.4 GHz and 5.4 GHz. At 5.4 GHz, more data can be transmitted compare to 2.4 GHz. However, 2.4 GHz has long distance of radiation, so it can be used when far away from the antenna module compare to 5 GHz that has short distance in radiation. The development of this project includes the scope of designing and testing of antenna using computer simulation technology (CST) 2018 software and vector network analyzer (VNA) equipment. In the process of designing, fundamental parameters of antenna are being measured and validated, in purpose to identify the better antenna performance.
Using particle swarm optimization to solve test functions problems
Authors: Ahmed Abed Issa , Mohammed Ali May , Abood Abdul Kadhim Afrah
Published: December 2021

In this paper the benchmarking functions are used to evaluate and check the particle swarm optimization (PSO) algorithm. However, the functions utilized have two dimension but they selected with different difficulty and with different models. In order to prove capability of PSO, it is compared with genetic algorithm (GA). Hence, the two algorithms are compared in terms of objective functions and the standard deviation. Different runs have been taken to get convincing results and the parameters are chosen properly where the Matlab software is used. Where the suggested algorithm can solve different engineering problems with different dimension and outperform the others in term of accuracy and speed of convergence.
Wireless HART stack using multiprocessor technique with laxity algorithm
Authors: Manjunathan A. , Kanmani Ruby E. D. , Santhkumar W. Edwin , Vanathi A. , Jenopaul P. , Kannadhasan S.
Published: December 2021

The use of a real-time operating system is required for the demarcation of industrial wireless sensor network (IWSN) stacks (RTOS). In the industrial world, a vast number of sensors are utilised to gather various types of data. The data gathered by the sensors cannot be prioritised ahead of time. Because all of the information is equally essential. As a result, a protocol stack is employed to guarantee that data is acquired and processed fairly. In IWSN, the protocol stack is implemented using RTOS. The data collected from IWSN sensor nodes is processed using non-preemptive scheduling and the protocol stack, and then sent in parallel to the IWSN's central controller. The real-time operating system (RTOS) is a process that occurs between hardware and software. Packets must be sent at a certain time. It's possible that some packets may collide during transmission. We're going to undertake this project to get around this collision. As a prototype, this project is divided into two parts. The first uses RTOS and the LPC2148 as a master node, while the second serves as a standard data collection node to which sensors are attached. Any controller may be used in the second part, depending on the situation. Wireless HART allows two nodes to communicate with each other.
Hyper-parameter optimization of convolutional neural network based on particle swarm optimization algorithm
Authors: Fouad Zainab , Alfonse Marco , Roushdy Mohamed , Salem Abdel-Badeeh M.
Published: December 2021

Deep neural networks have accomplished enormous progress in tackling many problems. More specifically, convolutional neural network (CNN) is a category of deep networks that have been a dominant technique in computer vision tasks. Despite that these deep neural networks are highly effective; the ideal structure is still an issue that needs a lot of investigation. Deep Convolutional Neural Network model is usually designed manually by trials and repeated tests which enormously constrain its application. Many hyper-parameters of the CNN can affect the model performance. These parameters are depth of the network, numbers of convolutional layers, and numbers of kernels with their sizes. Therefore, it may be a huge challenge to design an appropriate CNN model that uses optimized hyper-parameters and reduces the reliance on manual involvement and domain expertise. In this paper, a design architecture method for CNNs is proposed by utilization of particle swarm optimization (PSO) algorithm to learn the optimal CNN hyper-parameters values. In the experiment, we used Modified National Institute of Standards and Technology (MNIST) database of handwritten digit recognition. The experiments showed that our proposed approach can find an architecture that is competitive to the state-of-the-art models with a testing error of 0.87%.
Non-linear creep of polypropylene utilizing multiple integral
Authors: Idan Mahmoud Fadhel
Published: December 2021

Multiple integral representation (MIR) has been used to represent studying the effect of temperature on the amount of nonlinear creep on the semi- crystalline polypropylene (PP) under the influence of axial elastic stress. To complete this research, the Kernel functions were selected, for the purpose of performing an analogy, and for arranging the conditions for the occurrence of the first, second and third expansion in a temperature range between 20 °C-60 °C, i.e., between the glass transition and softening temperatures, within the framework of the energy law. It was observed that the independent strain time increased non-linearly with increasing stress, and non-linearly decreased with increase in temperature, although the time parameter increased non-linearly with stress and temperature directly. In general, a very satisfactory agreement between theoretical and practical results on the MIR material was observed.
Techno economic environmental assessment of hybrid renewable energy system in India
Authors: K M Venkatachalam , Saravanan V
Published: December 2021

The co-ordination of non-conventional energy technologies such as solar, wind, geothermal, biomass and ocean are gaining significance in India due to more energy requirements and high greenhouse gas emission. In this assessment, the sustainability of emerging the gird isolated hybrid solar photovoltaic (PV)/wind turbine (WT)/diesel generator (DG)/battery system for Arunai Engineering College (India) building is evaluated. The techno- economic and environmental research was inspected by HOMER Pro software by choosing the optimal combination depends on size of the components, renewable fraction, net present cost (NPC), cost of energy (COE) and greenhouse gas (GHG) emission of the hybrid system. From the acquired outcomes and sensitivity investigation, the optimal PV-WT-DG- Battery combination has a NPC of $28.944.800 and COE $0.1266/kWh, with an operating cost of $256.761/year. The grid isolated hybrid system is environmentally pleasant with a greenhouse gas emission of 2.692 kg/year with renewable fraction of 99.9%.
Optimization of wind solar and battery hybrid renewable system using backtrack search algorithm
Authors: Meitei Ingudam Chitrasen , Pudur Rajen
Published: December 2021

Penetration of renewable sources to the grid is always a problem for electrical engineers, apart from reliability and efficiency, cost optimization is also a big concern among them. Wind, solar and battery hybrid combinations (WSB-HPS) are also very common among hybrid systems, but this WSBHPS combines wind and solar energy power generation reduces the charge and discharge time of the battery. Therefore, this system improves the reliability of the power supply by fully utilizing the wind and solar power generation and improves the charging and discharging state of the battery and hence reduces the whole cost as the investment in battery is reduced. backtrack search algorithm (BSA) is the highly efficient and powerful algorithm to solve combinatorial optimization problems. In this paper an attempt is made to optimize the hybrid combination using BSA in the matrix laboratory (MATLAB) environment and comparable study is made using HOMER. A complete optimised data is generated for a particular area in Manipur and reduced cost is suggested.
Comprehensive analysis of current research trends in energy storage technologies
Authors: Salkuti Surender Reddy , Pagidipala Sravanthi , Kim Seong-Cheol
Published: December 2021

This paper addresses the comprehensive analysis of various energy storage technologies, i.e., electrochemical and non-electrochemical storage systems by considering their storage methods, environmental impact, operations, costs, and their importance and applications. These storage technologies will help to reduce the energy shortage. There has been a significant deployment of storage systems in power grids throughout the world. The characteristics of storage systems such as the ability to act both as generation and load, fast response time, and high ramp rate. Make them promising options for the system operators to reduce the peak demand, and facilitate renewable energy integration. Various new trends in energy depict the ways this generated energy could be stored and harnessed. With the recent integration of renewable energy, it is important to store the energy and it is combined to help the green energy demand. The integration of renewable energy into the power grid has increased reliability, efficiency, and stability. Adding the energy component will further enhance the capabilities of the grid. This paper also recommends an optimal storage technique from various available storage technologies.
Differential equations of motion of a material point in the perpendicular plane to the plane of the gravitating disk
Authors: Rakhmetullina Zhenisgul , Uvaliyeva Indira , Amenova Farida
Published: December 2021

This paper presents an analytical solution of the differential equations of motion of a material point in the plane perpendicular to the plane of the gravitating disk. The differential equations of the problem under study and the applied Gilden's method are described in the works of A. Poincaré. Differential equations refer to nonlinear equations. The analysis of methods for solving nonlinear differential equations was carried out. The methodology of applying the Gilden method to the solution of the differential equations under consideration can be applied in studies of the problem of the motion of celestial bodies in the “disk-material point” system in perpendicular planes. To identify the various properties of the gravitating disk, an analytical review of the state of the problem of the motion of a material point in the field of a gravitating disk is carried out. Summing up the presented review on the problem under study, a conclusion is made. The substantive formulation of the problem is described, which is formulated as follows: the study of the influence of disk-shaped bodies on the motion of a material point and methods for their solution.
Power quality mitigation and transient analysis in AC/DC hybrid microgrid for electric vehicle charging
Authors: Rao Sumana Sreenivasa , Rangaswamy Dhanalakshmi
Published: December 2021

The usage of electric vehicles (EV) increased in recent years as the vehicles design and performances are nearly similar to petrol vehicles. The main source of energy for EV is taken from the grid for charging. So, the penetration of EVs in alternating current (AC) grid creates more power quality issues like voltage sag, swell and harmonics in the current. This energy can also be produced from the renewable energy resources like photovoltaic (PV) power generation. This PV energy can also be used as direct current (DC) grid. The electric vehicle chargers which come with intelligent grid operation is considered as load in this paper. This paper is an attempt to discuss the penetration of EVs in AC/DC hybrid micro grid which causes the power quality problems, and the power quality problem is mitigated by using the unified power quality conditioner (UPQC). The results are analyzed for three cases and four scenarios which is based on the function of UPQC and the action of smart charger in grid connected as well as autonomous mode operation of the AC/DC micro grid when the load is considered as dynamic load. The simulation is carried out in MATLAB2017b environment
Power optimization of binary division based on FPGA
Authors: Nasser Fadi T. , Hashim Ivan A.
Published: December 2021

In modern very large scale integrated (VLSI) digital systems, power consumption has become a critical concern of VLSI designers. As size shrinks and density increases in chips, it will be a challenge to design high performance and low-power digital systems. Therefore, VLSI designers are trying to reduce power dissipation in these systems by using power optimization techniques. Different mathematical operations can be found in the architectures of most digital systems. The focus of this paper is division. In comparison to other basic computational operations, division requires more iterations, takes a long time, covers a large area, and consumes more power from the digital system. As a result, the system's design requires high speed and a low-power divider in order to improve its overall performance. This paper focuses on dynamic power dissipation. In order to determine which design consumes the lowest dynamic power, different system designs of digit-recurrence division algorithms, such as restoring division and non-restoring division are suggested. An innovative power-optimization technique, the very hardware descriptions language (VHDL) technique, is utilized to the suggested system designs. The VHDL technique achieved the higher optimization in dynamic power, at 93.66% for non-restoring division with internal-loop iteration, than traditional approaches.
Proof of concept for lightweight PUF-based authentication protocol using NodeMCU ESP8266
Authors: Mispan Mohd Syafiq , Jidin Aiman Zakwan , Kamaruddin Muhammad Raihaan , Nasir Haslinah Mohd
Published: December 2021

Wireless sensor node is the foundation for building the next generation of ubiquitous networks or the so-called internet of things (IoT). Each node is equipped with sensing, computing devices, and a radio transceiver. Each node is connected to other nodes via a wireless sensor network (WSN). Examples of WSN applications include health care monitoring, and industrial monitoring. These applications process sensitive data, which if disclosed, may lead to unwanted implications. Therefore, it is crucial to provide fundamental security services such as identification and authentication in WSN. Nevertheless, providing this security on WSN imposes a significant challenge as each node in WSN has a limited area and energy consumption. Therefore, in this study, we provide a proof of concept of a lightweight authentication protocol by using physical unclonable function (PUF) technology for resource-constrained wireless sensor nodes. The authentication protocol has been implemented on NodeMCU ESP8266 devices. A server-client protocol configuration has been used to verify the functionality of the authentication protocol. Our findings indicate that the protocol used approximately 7% of flash memory and 48% of static random-access memory (SRAM) in the sensor node during the authentication process. Hence, the proposed scheme is suitable to be used for resource-constrained IoT devices such as WSN.
Distant temperature and humidity monitoring: prediction and measurement
Authors: Hafeez Farrukh , Sheikh Usman Ullah , Khidrani Attaullah , Bhayo Muhammad Akram , Altbawi Saleh Masoud Abdallah , Jumani Touqeer Ahmed
Published: December 2021

Sensing environmental measuring parameters has a pivotal role in our everyday lives. Most of our daily life activities depend upon environmental conditions. Accurate information about these parameters also helps in several industrial applications like ventilation rate calculation, energy prediction, stock maintenance in warehouses, and saving from harmful conditions. The emergence of machine learning can make it easy to predict such time series problems. This paper describes the design of a remotely controlled robotic car for measuring and predicting humidity and temperature. A customized app for accessing the robotic car is designed to indicate predicted and realtime measured values of humidity and temperature. A sensor installed builtin helps in the measurement. The recurrent neural network (RNN) model is used to predict humidity and temperature. For this purpose, experiments are carried out in both outdoor and indoor settings. Accuracy of 85% and 90% is achieved in an outdoor environment and indoor settings.
Audio classification for music information retrieval of Hindustani vocal music
Authors: Rege Amit , Sindal Ravi
Published: December 2021

An important task in music information retrieval of Indian art music is the recognition of the larger musicological frameworks, called ragas, on which the performances are based. Ragas are characterized by prominent musical notes, motifs, general sequences of notes used and embellishments improvised by the performers. In this work we propose a convolutional neural network-based model to work on the mel-spectrograms for classication of steady note regions and note transition regions in vocal melodies which can be used for finding prominent musical notes. It is demonstrated that, good classification accuracy is obtained using the proposed model.
Integrated NIR-HE based SPOT-5 image enhancement method for features preservation and edge detection
Authors: Zulkifle Farizuwana Akma , Hassan Rohayanti , Ahmad Mohammad Nazir , Kasim Shahreen , Sutikno Tole , Halim Shahliza Abd
Published: December 2021

Recently, many researchers have directed their attention to methods of predicting shorelines by the use of multispectral images. Thus, a simple and optimised method using image enhancements is proposed to improve the low contrast of the Satellite pour l'Observation de la Terre-5 (SPOT-5) images in the detection of shorelines. The near-infrared (NIR) channel is important in this study to ensure the contrast of the vegetated area and sea classification, due to the high reflectance of leaves in the near infrared wavelength region. This study used five scenes of interest to show the different results in shoreline detection. The results demonstrated that the proposed method performed in an enhanced manner as compared to current methods when dealing with the low contrast ratio of SPOT-5 images. As a result, by utilising the near-infrared histogram equalization (NIR-HE), the contrast of all datasets was efficiently restored, producing a higher efficiency in edge detection, and achieving higher overall accuracy. The improved filtering method showed significantly better shoreline detection results than the other filter methods. It was concluded that this method would be useful for detecting and monitoring the shoreline edge in Tanjung Piai.
New scaled algorithm for non-linear conjugate gradients in unconstrained optimization
Authors: Al-Naemi Ghada M. , Sheekoo Ahmed H.
Published: December 2021

A new scaled conjugate gradient (SCG) method is proposed throughout this paper, the SCG technique may be a special important generalization conjugate gradient (CG) method, and it is an efficient numerical method for solving nonlinear large scale unconstrained optimization. As a result, we proposed the new SCG method with a strong Wolfe condition (SWC) line search is proposed. The proposed technique's descent property, as well as its global convergence property, are satisfied without the use of any line searches under some suitable assumptions. The proposed technique's efficiency and feasibility are backed up by numerical experiments comparing them to traditional CG techniques.
Parallel extreme gradient boosting classifier for lung cancer detection
Authors: Abdualjabar Rana Dhia’a , Awad Osama A.
Published: December 2021

Most lung cancers do not cause symptoms until the disease is in its later stage. That led the lung cancer having a high fatality rate compared to other cancer types. Many scientists try to use artificial intelligence algorithms to produce accurate lung cancer detection. This paper used extreme gradient boosting (XGBoost) models as a base model for its effectiveness. It enhanced lung cancer detection performance by suggesting three stages model; feature stage, XGBooste parallel stage and selection stage. This study used two types of gene expression datasets; RNA-sequence and microarray profiles. The results presented the effectiveness of the proposed model, especially in dealing with imbalanced datasets, by having 100% each of sensitivity, specificity, precision, F1_score, area under curve (AUC), and accuracy metrics when it applied on all of the datasets used in this study.
Analysis the digital images by using morphology operators
Authors: Saeed Hadeel Amjed , Hamad Sumaya , Hussain Azmi Tawfik
Published: December 2021

In this paper, we deal with morphology images that try to improve the use of images. On the one hand, the process is used to obtain the histogram of the image then converted it into a non-color image (gray scale). The next step is to perform the erosion, dilation, open and close operations on the images, how these methods have important effects, and how can be used on a variable number of images, and found the differences between them. These operations were applied on four different images, check images, four basic operations (dilation, erosion, open and close) for each image were performed. Then, retrieving process to the original state of the image (the colored copy) was applied. The results found that retrieving the original images is difficult, and there is the occurrence of some noises on the image when it was retrieved. Finally, conclusions of the work are presented.
Classifying clinically actionable genetic mutations using KNN and SVM
Authors: Chivukula Rohit , Lakshmi T. Jaya , Uday Sanku Satya , Pavani Satti Thanuja
Published: December 2021

Cancer is one of the major causes of death in humans. Early diagnosis of genetic mutations that cause cancer tumor growth leads to personalized medicine to the decease and can save the life of majority of patients. With this aim, Kaggle has conducted a competition to classify clinically actionable gene mutations based on clinical evidence and some other features related to gene mutations. The dataset contains 3321 training data points that can be classified into 9 classes. In this work, an attempt is made to classify these data points using K-nearest neighbors (KNN) and linear support vector machines (SVM) in a multi class environment. As the features are categorical, one hot encoding as well as response coding are applied to make them suitable to the classifiers. The prediction performance is evaluated using log loss and KNN has performed better with a log loss value of 1.10 compared to that of SVM 1.24.
Sentiment analysis of Twitter posts related to the COVID-19 vaccines
Authors: Alabid Noralhuda N. , Katheeth Zainab Dalaf
Published: December 2021

A real threat to the people of the world has appeared as a result of the spread of the Coronavirus disease of 2019 (COVID-19) disease. A lot of scientific and financial support has been made to devote vaccines capable of ending this epidemic. However, these vaccines have become a subject of debate between individuals, as some people tend to support taking vaccines and others rejecting them. This paper aims to create a framework model to classify the sentiment and opinions of individuals that published in Twitter regarding the COVID-19 vaccines. Identify those opinions can help public health institutions to know public opinions and direct their efforts towards promoting taking vaccinations. Two of the machines learning classification models which are the support vector machine (SVM) and naive Bayes (NB) classifier are applied here. Other pre-processing methods were applied as well to filter unstructured tweets.
Series FACTS controllers in industrial low voltage electrical distribution networks for reducing fault current levels
Authors: Thippana Vishnu Charan , Parimi Alivelu Manga , Karri Chandram
Published: December 2021

In this paper, series FACTS devices like Thyristor control series capacitor(TCSC)and Static synchronous series compensator (SSSC) with designed control logic used to reduce the fault current located in LV distribution network at the LV busbar. The electrical distribution network in small and medium scale industries such as steel plants, process and power plants is through low voltage switchgear (LVS) fed from motor control centre (MCC) switchgear through step down transformer of 11kV or 33kV /415V. The designed switchgear in the LV side for these utilities usually is at 50kA. However, the process loads are continuously increasing and sustained with additional feeders with the existing switchgear. Consequently, the fault current at the busbar of the switchgear increases which may require the replacement of entire switchgear to the new design fault current. However, upgrading the existing switchgear is not an economical solution to the industries. Alternatively reducing the fault current at the busbar is feasible. Controller design implemented for reducing the short circuit current with series FACTS devices. A study carried on 800 MW Thermal power plant Ash handling LVS in ETAP and Matlab. It is observed that the results are encouraging to use series FACTS devices effectively in the LVS.
Performances analysis of interior permanent magnet motors having different rotor iron pole shapes
Authors: Shuraiji Ahlam Luaibi , Awad Buraq Abdulhadi
Published: December 2021

Interior permanent magnet motors (IPMMs) have been increasing in popularity, since the emergence of permanent magnet material with high energy products, i.e. rare earth permanent magnet material. This paper analyses the performances of IPMMs having different rotor iron pole shapes including eccentric, sinusoidal and sinusoidal with 3th order harmonic injected rotor pole arc shapes IPMMs. Cogging torque, static torque, torque ripple, torque-speed and power-speed curves of the mentioned motors have been compared. It must be noted that the mentioned motors have been designed with the same stator, PM shape and the same dimensions, in order to highlight the effect of the rotor pole arc shape on the performance of the such motors. Two-dimensional (2D) finite element analysis (FEA) has been utilized to design and analyze the mentioned machines. It has been found that rotor iron pole shape of the IPM has notably influence on the machine performance, practically on output electromagnetic torque and its ripple. The highest value of average electromagnetic torque as well as torque capability in the constant torque reign is delivered by 3th order harmonic injected rotor pole arc shapes machine, while the lowest torque ripple is obtained by the sinusoidal rotor pole arc machine.
DTC with fuzzy logic for multi-machine systems: traction applications
Authors: Max Ndoumbé Matéké , Maurice Nyobe Yomé Jean , Samuel Eke , Jordan Mouné Cédric , Biboum Alain , Laurent Bitjoka
Published: December 2021

In this work, a direct torque control (DTC) method for multi-machine systems is applied to electric vehicles (EVs). Initially, the DTC control method associated with the model reference adaptive system (MRAS) is used for speed control, and management of the magnetic quantities is ensured by the variable master-slave control (VMSC). In order to increase the technical performance of the studied system, a DTC method has been associated with a fuzzy logic approach. These two control methods are applied to the traction chain of an electric vehicle to highlight its speed, precision, stability, and robustness metric during particular stress tests imposed on the wheel motor. The results obtained in MATLAB/Simulink software made feasible a comparison of two proposed methods based on their technical performances. It should be noted that the direct fuzzy logic torque control (DFTC) has better performance than the DTC associated with the MRAS system as a rise time reduction of 1.4%, an oscillation of torque, and flux amplitude of less than 9%, static steady-state error near zero. The DTFC control method responds favorably to electric vehicle traction chain systems by the nature of the comfort and safety provided.
Harnessing wind and solar PV system to build hybrid power system
Authors: Saswat S. S. , Patra Suman , Mishra Debani Prasad , Salkuti Surender Reddy , Senapati Rudra Narayan
Published: December 2021

Electricity is the most important consideration for individual needs. Natural crossover power architecture using photovoltaic and wind is presented in this study, together with a Cuk direct current-direct current (DC-DC) converter, third phase inverter, and an inductors capacitors (LC) filter. Due to its natural disposal and availability in India, wind power and photovoltaics are ideal for the hybrid system. Hybrid power structures, on the other hand, reduce the risk of damage to equipment in sustainable stock storage since they have a higher electrical output. MATLAB Simulink was used to demonstrate this hybrid application. Before connecting the entire DC voltage frame with the main lattice of the power frame, blocks such as the wind model, PV model, Cuk converter, inverter, and LC channel are built individually. Information limitations for participating in varying levels of irradiance and variations in wind speed. The results show that the hybrid system has a considerably more reliable standard in terms of energy efficiency than an independent framework. Furthermore, the hybrid system's Cuk DC-DC converter, three-phase standard-based inverter, and LC channel can minimise power switching power.
Prospect of low-cost energy conservation in residential energy consumption
Authors: Tyagi Ruchi , Vishwakarma Suresh
Published: December 2021

The energy sector of trinidad and tobago (T&T), with its nationally determined contributions (NDCs), is still struggling for its place in mainstream academic literature. The review paper aims to identify the prospects of low-cost energy conservation measures in the residential sector of T&T. The review follows a four-step review methodology to serve as a basis for creating policy and practice guidelines. First, review articles are checked for their quality on a 5-point scale on the mixed methods appraisal tool (MMAT) to check the quality of review articles. Second, Microsoft Excel, R (RQDA) package, and Voyant tools have been used to index code, analyse, and visualise data. The research trends on small islands developing states (SIDS) energy aspect in general and T&T specifically highlight the critical role of energy challenges related to economic and social development, emphasising technology, infrastructure development, and funds availability. Awareness of low-cost energy conservation measures has a high prospect in reducing residential consumption and balancing demand-side management. This paper contributes to facilitating policy direction on energy efficiency and energy conservation for T&T and other SIDS.
A comparative study of meta-heuristic and conventional optimization techniques of grid connected photovoltaic system
Authors: Traore Mamadou , Ndiaye Alphousseyni , Mbodji Senghane
Published: December 2021

This paper presents the meta-heuristic and conventional optimizations techniques for the grid connected photovoltaic solar system. The perturb and observe (P&O) and particle swarm optimization (PSO) algorithms are proposed to track the maximum power point (MPP) of the photovoltaic solar system (PVSS). The regularization of the current supplied into the grid is ensured by the proportional integral (PI) corrector whose parameters are generated by the genetic algorithm (GA). The results of these two MPPT methods are compared and showed that the PSO is more efficient than the P&O. The use of GA algorithm to determine PI parameters allowed to obtain 0.89% of total distortion harmonic (THD).
Improved filtering H∞ finite frequency of Takagi-Sugeno fuzzy systems
Authors: Alaoui Rim Mrani , El-Amrani Abderrahim
Published: December 2021

The work treats the filter H∞ finite frequency (FF) in Takagi-Sugeno (T-S) two dimensional (2-D) systems described by Fornasini-Marchesini local state-space (FM LSS)models. The goal of this work is to find an FF H∞ T-S fuzzy filter model design in such a way that the error system is stable and has a reduced FF H∞ performance over FF area swith noise is established as aprerequisite. Via the use of the generalized Kalman Yakubovich Popov (gKYP) lemma, Lyapunov functions approach, Finsler’s lemma, and parameterize slack matrices, new design conditions guaranteeing the FF H∞ T-S fuzzy filter method of FM LSS models are developed by solving linear matrix inequalities (LMIs). At last, the simulation results are provided to show the effectiveness and the validity of the proposed FF T-S fuzzy of FM LSS models strategy by a practical application has been made.
Energy management system and supervision in a micro-grid using artificial neural network technique
Authors: Jarmouni Ezzitouni , Mouhsen Ahmed , Lamhammedi Mohammed , Ouldzira Hicham
Published: December 2021

Nowadays, the combination of conventional and renewable energy sources such as solar energy is one of the most widespread solutions to surmount the challenge of the climate and energy crisis. In the presence of random behavior of photovoltaic systems and variable power demand by consumers, energy management is a real challenge. In this paper, we propose a new energy management technique based on artificial neural networks in a smart grid. This will ensure the continuous supply of electricity to the consumer in the presence of random operation in energy consumption and generation. The global system is modeled and simulated under the MATLAB/Simulink tool.
Internet of robotic things: Design and develop the quality of service framework for the healthcare sector using CoAP
Authors: Kumar Arun , Sharma Sharad
Published: December 2021

The number of robotics used globally is gradually growing, according to a variety of research. They are becoming more and more popular in different workplaces, like manufacturing, distribution, medical conditions, military, inaccessible areas, etc. The internet of things (IoT) and robotics groups have until now been guided by a set of, but somewhat compatible, goals, which are mainly to help knowledge systems in the field of general sensing, tracking, and monitoring. Therefore, the development of an internet of robotic things (IoRT), which incorporates the outcome from both cultures, is progressively said to have a significant added benefit. Internet of robotic things, the intersection of the Internet of Things and robotics, is where self-sufficient machines will assemble information from various sensors and speak with one another to perform errands including basic reasoning. As the name suggests, IoRT is the combination of two front-line innovations, the internet of things and robotics. People can manage any electronic device in homes with IoT and can also be used in contactless applications in healthcare. The constrained application protocol (CoAP), for the management and control of a community of homogeneous sensor modules, has recently endorsed multicast communications in IoRT. It will boost connectivity performance, less power consumption due to data aggregation, and enhanced security features with DTLS security features for various applications for the internet of things. This paper presents an implementation of the CoAP framework on IoRT sky motes using the Contiki Cooja Simulator that will be a useful healthcare sector that will confirm their potential and therefore, new research directions are outlined
Adaptive Language Processing Unit for Malaysian Sign Language Synthesizer
Authors: MAARIF HARIS AL QODRI
Published: December 2021

Language Processing Unit (LPU) is a system built to process text-based data to comply with the rules of sign language grammar. This system was developed as an important part of the sign language synthesizer system. Sign language (SL) uses different grammatical rules from the spoken/verbal language, which only involves the important words that Hearing/Impaired Speech people can understand. Therefore, it needs word classification by LPU to determine grammatically processed sentences for the sign language synthesizer. However, the existing language processing unit in SL synthesizers suffers time lagging and complexity problems, resulting in high processing time. The two features, i.e., the computational time and success rate, become trade-offs which means the processing time becomes longer to achieve a higher success rate. This paper proposes an adaptive Language Processing Unit (LPU) that allows processing the words from spoken words to Malaysian SL grammatical rule that results in relatively fast processing time and a good success rate. It involves n-grams, NLP, and Hidden Markov Models (HMM)/Bayesian Networks as the classifier to process the text-based input. As a result, the proposed LPU system has successfully provided an efficient (fast) processing time and a good success rate compared to LPU with other edit distances (Mahalanobis, Levensthein, and Soundex). The system has been tested on 130 text-input sentences with several words ranging from 3 to 10 words. Results showed that the proposed LPU could achieve around 1.497ms processing time with an average success rate of 84.23% for a maximum of ten-word sentences.
Low-cost SARS-CoV-2 vaccine homogenization system for Pfizer-BioNTech covid-19 vials
Authors: Lima Jose , Rocha Luísa , Rocha Cláudia , Costa Paulo
Published: December 2021

The current SARS-CoV-2 pandemic has been affecting all sectors worldwide, and efforts have been targeting the enhancement of people’s health and labour conditions of collaborators belonging to healthcare institutions. The recent vaccines emerging against covid-19 are seen as a solution to address the problem that has already killed up to two million people. The preparation of the Pfizer-BioNTech covid-19 vaccine requires a specific manipulation before its administration. A correct homogenization with saline solution is needed and, therefore, a manual process with a predefined protocol should be accomplished. This action can endanger the operators’ ergonomics due to the repetitive movement of the process. This paper proposes a low-cost prototype incorporating an arduino based embedded system actuating a servomotor to perform an autonomous vials’ homogenization allowing to redirect these healthcare workers to other tasks. Moreover, a contactless start order process was implemented to avoid contact with the operator and, consequently, the contamination. The prototype was successfully tested and recognised, and is being applied during the preparation of the covid-19 vaccines at the hospital pharmacy of Centro Hospitalar de Vila Nova de Gaia/Espinho, E.P.E., Portugal. It can be easily replicated since the source files to assemble it are provided by the authors.
Efficient Commercial Classification of Agricultural Products using Convolutional Neural Networks
Authors: Jebelli Ali , Ahmad Rafiq
Published: December 2021

Agricultural products, as essential commodities, are among the most sought-for items in superstores. Barcode is usually utilized to classify and regulate the price of products such as ornamental flowers in such stores. However, the use of barcodes on some fragile agricultural products such as ornamental flowers can be damaged and lessen their life length. Moreover, it is time-consuming and costly and may lead to the production of massive waste and damage to the environment and the admittance of chemical materials into food products that can affect human health. Consequently, we aimed to design a classifier robot to recognize ornamental flowers based on the related product image at different times and surrounding conditions. Besides, it can increase the speed and accuracy of distinguishing and classifying the products, lower the pricing time, and increase the lifetime due to the absence of the need for movement and changing the position of the products. According to the datasheets provided by the robot that is stored in its database, we provide the possibility of identifying and introducing the product in different colors and shapes. Also, due to the preparation of a standard and small database tailored to the needs of the robot, the robot will be trained in a short time (less than five minutes) without the need for an Internet connection or a large hard drive for storage the data. On the other hand, by dividing each input photo into ten different sections, the system can, without the need for a detection system, simultaneously in several different images, decorative flowers in different conditions, angles and environments, even with other objects such as vases, detects very fast with a high accuracy of 97%.
«Somos estudiantes del campo»: identificaciones de jóvenes rurales en Entre Ríos (Argentina)
Authors: Schmuck Emilia
Published: December 2021

(analítico)La extensión de la escolaridad en Argentina y la creación de escuelas secundarias en el campo ha significado transformaciones en el espacio rural y las juventudes rurales. A partir de una investigación realizada desde el enfoque histórico-etnográfico en el norte de la provincia de Entre Ríos, advertimos que la escuela secundaria es el espacio privilegiado de sociabilidad de las y los jóvenes y nos centramos en la Fiesta del Estudiante Rural para comprender los procesos de identificación de estas juventudes. La condición de juventud y la condición de estudiante están estrechamente implicadas en el espacio rural y las y los jóvenes construyen identificaciones por oposición a sus pares urbanos y en relación con el campo, entendido en tanto paisaje natural escindido de las actividades productivas y laborales de la ruralidad.
Palabras clave:  Joven rural; estudiante de secundaria; educación rural; Argentina.
Use of Extracorporeal Membrane Oxygenation as Bridge to Replacement Therapies in Cardiogenic Shock: Insights From the Extracorporeal Life Support Organization
Authors: Mastoris Ioannis , Tonna Joseph E. , Hu Jinxiang , Sauer Andrew J. , Haglund Nicholas A. , Rycus Peter , Wang Yu , Wallisch William J. , Abicht Travis O. , Danter Matthew R. , Tedford Ryan J. , Fang James C. , Shah Zubair
Published: December 2021

Background:

There has been increasing use of extracorporeal membrane oxygenation (ECMO) as bridge to heart transplant (orthotopic heart transplant [OHT]) or left ventricular assist device (LVAD) over the last decade. We aimed to provide insights on the population, outcomes, and predictors for the selection of each therapy.

Methods:

Using the Extracorporeal Life Support Organization Registry between 2010 and 2019, we compared in-hospital mortality and length of stay, predictors of OHT versus LVAD, and predictors of in-hospital mortality for patients with cardiogenic shock that were bridged with ECMO to OHT or LVAD. One hundred sixty-seven patients underwent LVAD versus 234 patients who underwent OHT.

Results:

The overall use of ECMO has increased from 1.7% in 2010 to 22.2% in 2019. Mortality was similar between groups (LVAD: 28.7% versus OHT: 29.1%) while length of stay was longer for OHT (LVAD: 49.6 versus OHT: 59.5 days,
P
=0.05). Factors associated with OHT included prior transplant (odds ratio [OR]=31.26 [CI, 3.84–780.5]), use of a temporary pacemaker (OR=6.5 [CI, 1.39–50.15]), and increased use of inotropes on ECMO (OR=3.77 [CI, 1.39–11.07]), whereas LVAD use was associated with weight (OR=0.98 [CI, 0.97–0.99]), cardiogenic shock presentation (OR=0.40 [CI, 0.21–0.78]), previous LVAD (OR=0.01 [CI, 0.0001–0.22]), respiratory failure (OR=0.28 [CI, 0.11–0.70]), and milrinone infusion (OR=0.32 [CI, 0.15–0.67]). Older age (OR=1.07 [CI, 1.02–1.12]), cannulation bleeding (OR=26.1 [CI, 4.32–221.3]), and surgical bleeding (OR=6.7 [CI, 1.26–39.9]) in patients receiving LVAD and respiratory failure (OR=5 [CI, 1.17–23.1]) and continuous renal replacement therapy (OR=3.82 [CI, 1.28–11.9]) in patients receiving OHT were associated with increased mortality.

Conclusions:

ECMO use as a bridge to advanced therapies has increased over time, with more patients undergoing LVAD than OHT. Mortality was equal between the 2 groups while length of stay was longer for OHT.