bluuebunny/crossref_metadata_2025 huggingface dataset:
Design and implementation of school bus information and tracking system application
Authors: Sarosa Moechammad , Ningrum Mentari Tika Putri , Mas’udia Putri Elfa
Published: February 2023

The school bus is a means of transportation that is very attractive to students because it is free. This study aims to develope an application that can track school bus trips and provide information about bus passengers. Bus location information sent to the user application can help students estimate the arrival time of the school bus at the pick-up point. In addition, information on the identity of school bus passengers can be used by parents to monitor the whereabouts of their children going to or from school on the bus. This application uses the global positioning system (GPS) of the smartphone on the school bus to find out the location of the bus and send it along with passenger identification information to the user application. To read passenger identities, near field communication (NFC) cards are used as passenger identity cards by tapping them on a smartphone on a school bus. Tests have been carried out on all functions of the application features and testing the accuracy of location reading and tracking of school bus trips, obtained latitude and longitude tolerance values of about 3.2 meters.
An innovativefractal architecture model for implementing MapReduce in an open multiprocessing parallel environment
Authors: Khudhair Muslim Mohsin , AL-Rammahi Adil , Rabee Furkan
Published: February 2023

One of the infrastructure applications that cloud computing offers as a service is parallel data processing. MapReduce is a type of parallel processing used more and more by data-intensive applications in cloud computing environments. MapReduce is based on a strategy called "divide and conquer," which uses regular computers, also called "nodes," to do processing in parallel. This paper looks at how open multiprocessing (OpenMP), the best shared-memory parallel programming model for high-performance computing, can be used with the proposed fractal network model in the MapReduce application. A well-known model, the cube, is used to compare the fractal network model and its work. Where experiments demonstrated that the fractal model is preferable to the cube model. The fractal model achieved an average speedup of 2.7 and an efficiency rate of 67.7%. In contrast, the cube model could only reach an average speedup of 2.5 and an efficiency rate of 60.4%.
Blackhole attacks in internet of things networks: a review
Authors: Kamis Noor Hisham , Yassin Warusia , Abdollah Mohd Faizal , Razak Siti Fatimah Abdul , Yogarayan Sumendra
Published: February 2023

The internet of things (IoT) is one of data revolution area and is the following extraordinary mechanical jump after the internet. In terms of IoT, it is expected that electronic gadgets that are used on a regular basis would be connected to the current of the internet. IPv6 over low-power wireless personal area networks (6LoWPAN) is a one of IPv6 header pressure technology, and accordingly, it is vulnerable to attack. The IoT is a combination of devices with restricted resource assets like memory, battery power, and computational capability. To solve this, RPL or routing protocol for low power Lossy network is deploy by utilizing a distance vector scheme. One of denial of service (Dos) attack to RPL network is blackhole attack in which the assailant endeavors to become a parent by drawing in a critical volume of traffic to it and drop all packets. In this paper, we discuss research on numerous attacks and current protection methods, focusing on the blackhole attack. There is also discussion of challenge, open research issues and future perspectives in RPL security. Furthermore, research on blackhole attacks and specific detection technique proposed in the literature is also been presented.
A hybrid approach to enhanced genetic algorithm for route optimization problems
Authors: Chattoraj Mrinmoyee , Vinayakamurthy Udaya Rani
Published: February 2023

Shortest path problem has emerged to be one of the significant areas of research and there are various algorithms involved in it. One of the successful optimization techniques is genetic algorithm (GA). This paper proposes an efficient hybrid genetic algorithm where initially we use a map reduction technique to the graph and then find the shortest path using the conventional genetic algorithm with an improved crossover operator. On comparing this hybrid algorithm with other algorithms, it has been detected that the performance of the modified genetic algorithm is better as comparison to the other methods in terms of various metrics used for the evaluation.
Machine learning to improve the performance of anomaly-based network intrusion detection in big data
Authors: Chimphlee Siriporn , Chimphlee Witcha
Published: February 2023

With the rapid growth of digital technology communications are overwhelmed by network data traffic. The demand for the internet is growing every day in today's cyber world, raising concerns about network security. Big Data are a term that describes a vast volume of complicated data that is critical for evaluating network patterns and determining what has occurred in the network. Therefore, detecting attacks in a large network is challenging. Intrusion detection system (IDS) is a promising cybersecurity research field. In this paper, we proposed an efficient classification scheme for IDS, which is divided into two procedures, on the CSE-CIC-IDS-2018 dataset, data pre-processing techniques including under-sampling, feature selection, and classifier algorithms were used to assess and decide the best performing model to classify invaders. We have implemented and compared seven classifier machine learning algorithms with various criteria. This work explored the application of the random forest (RF) for feature selection in conjunction with machine learning (ML) techniques including linear regression (LR), k-Nearest Neighbor (k-NN), classification and regression trees (CART), Bayes, RF, multi layer perceptron (MLP), and XGBoost in order to implement IDSS. The experimental results show that the MLP algorithm in the most successful with best performance with evaluation matrix.
Supply chain strategy during the COVID-19 terms: sentiment analysis and knowledge discovery through text mining
Authors: Zuhanda Muhammad Khahfi , Anisa Yuan , Desniarti Desniarti , Hafiz Muhammad , Syofra Anil Hakim , Caraka Rezzy Eko , Noh Maengseok
Published: February 2023

The coronavirus pandemic has affected not only health but also the economy. The use of big data in finding information can be used to gain profits that logistics companies can utilize to survive during the pandemic. This study conducted text-mining research on service consultant sites in the logistics sector. This study aims to present frequency diagrams, analyze sentiment using the National Research Council (NRC) lexicon, present bigrams, and seek knowledge about strategies to minimize shipping costs and maintain inventories of manufactured goods. The words "supply", "chain", and "COVID-19" are words that are used frequently throughout the article. The results of this study showed that the words that often appear from word excavation are the words "supply", "chain", "logistics", "kpis," and "inventory". Then emotion trust becomes an emotional word that often appears in articles. The words "Supply" and "pandemic" are the words that seem the most positive and negative words, respectively. The words "COVID-19", "safety stock", and "inventory management" are words that often appear together. The result of discovery knowledge is that logistics consultants offer emotions of trust and provide many insights on minimizing shipping costs and maintaining inventory during a pandemic.
Measuring geospatial information system success on individual performance impact
Authors: Kurniawan Edie , Tjhin Viany Utami
Published: February 2023

This research will analyze the influence of the quality of sales IndiHome information system (SIIS) on individual performance. In this research, the SIIS dashboard quality aims to accommodate them using a model that meets the updated Delone and McLean model. Individual productivity is measured through the Net Individual Benefit variable. It measures the impacts obtained after using the SIIS dashboard on work success. Indihome is Telkom Indonesia broadband retail brand. In this business, the service must be installed for each house. The challenges are to provide the best service to customers, manage the chain of resources in a series of infrastructures for providing broadband services, and maintain business performance to be sustainable. Telkom Indonesia has developed a geospatial-based Sales Information System by utilizing geospatial and spatial analytics, so the data can be viewed comprehensively in one map. The interpretation of the SIIS dashboard shows that the success rate is at a high level for the six variables (system quality, user quality, information quality, information use, user satisfaction, and net individual benefit). There is also a significant effect in increasing the work productivity of SIIS dashboard users as indicated by the correlation measure between SIIS dashboard success and net individual benefits.
Google trends and online media data for supply and demand information in waste management evaluation in Jakarta
Authors: Kurniawan Robert , Purwanto Agung , Monika Anugerah Karta , Wahyuni Krismanti Tri , Hendrawan Muhammad Yunus , Andrian Isnaeni Mohamad
Published: February 2023

Demand and supply of information in online media, particularly regarding waste management, remain hampered by a number of obstacles. Consequently, the objective of this study is to determine the public's interest in waste management knowledge based on demand data obtained from Google trends and to determine the most recent events in waste management by analyzing online news content. As a result, vector autoregressive (VAR) with impulse response function (IRF) and latent dirichlet allocation (LDA) are utilized as the analysis method. An important finding of this study is that it takes at least four weeks for individuals to absorb waste management information. Therefore, it is necessary for the government and the pentahelix component to sit together in order to reduce the community's information acquisition delay. Waste management, which is the subject of the shared information, should guide the selection of keywords by information providers.
A novel decision-making approach based on a decision tree for micro-grid energy management
Authors: Mansoury Ibtissame , El Bourakadi Dounia , Yahyaouy Ali , Boumhidi Jaouad
Published: February 2023

Environmental challenges such as climate change have accelerated humanity's need for renewable alternative energy sources. For this reason, we propose in this paper a decision-making strategy that allows controlling the flows of energy into a micro-grid (MG) compound of solar energy, batteries, and diesel generator (DG), and connected to the distributed network (DN). Therefore, the power supply to the loads is obtained either from the energy produced by solar sources, from the batteries, from the DN, or from the DG when renewable energy (RE) and batteries are depleted. To make the final decision, we consider four parameters at the same time: the energy produced by solar energy, the requested load, the state of charge of batteries (SoC), and the purchase or sale price. Decision tree (DT) is used to build the energy management strategy to ensure the availability of power on demand by making logical decisions about charging batteries, discharging batteries, buying necessary energy from DN, selling excess energy to DN, and recovering necessary energy from DG. The suggested DT approach is applied to a real MG to minimize the cost-benefit balance, and the comparison analysis demonstrates good results when compared to related works.
Using support vector machine regression to reduce cloud security risks in developing countries
Authors: Dhahi Sanaa Hammad , Dhahi Estqlal Hammad , Khadhim Ban Jawad , Taha Ahmed Shaymaa
Published: February 2023

The use of the cloud by governments throughout the world is being aggressively investigated to increase efficiency and reduce costs. The majority of cloud computing risk management programs prioritize addressing cloud security issues that government organizations may face when they choose to adopt cloud computing systems, but these programs lack evidence of security risks, and problems with using cloud computing in developing nations are uncommon, so they called for more research in this area. The objective of this paper is to use quantitative models namely Spearman's Rank correlation coefficient, simple regression, and support vector machine regression (SVMR) for estimating cloud security issues based on cloud control factors for improving the mitigation of cloud computing security issues based on control factors using intelligent models in a government organization. Identify the proper cloud control factors for every cloud security issue from estimation errors using a standard for performance measurement like mean square error (MSE) and root mean square error (RMSE), performance measurement to evaluate and validate proposed models. SVMR is an approach to enhance practices for cloud security platforms to mitigate risks and infrastructure for cloud adoption in developing countries in this paper.
A survey on automatic engagement recognition methods: online and traditional classroom
Authors: Sukumaran Ajitha , Manoharan Arun
Published: February 2023

Student engagement in a learning environment is directly related to students’ perception and involvement of the educational activities in the class, along with their physical and mental health. This paper presents an extensive survey of the various automatic engagement detection approaches and algorithms based on computer vision, physiological and neurological signals analysis-based methods. The computer vision-based techniques depend on the traits captured by image sensors such as facial expressions, gesture and posture analysis, and gaze direction. The physiological and neurological signal based approach depends on the sensor data, like heart rate (HR), electroencephalogram (EEG), blood pressure (BP), and galvanic skin response (GSR). A brief analysis of the available datasets for Engagement Recognition and its features are also summarized. This study highlights a few commercially available wearables which provides the physiological signals that helps in student’s attentivity recognition. Our study reveal that the accuracy of engagement recognition system will increase if we increase the number of modalities used. In this survey, we intend to support the upcoming researchers as well as tutors of smart education set up by providing an overview of existing or proposed approaches of automatic engagement detection techniques in different scenarios.
Flexible and secure continues data transmission among multiple users in cloud environment
Authors: Elumalai Ezhilarasan , Muruganandam Dinakaran
Published: February 2023

Cloud computing is an internet based computing where the sharable information, software and resources are provided based on demand devices. Where, the rapid development and pervasive growth of unavoidable sending of message advances, there are expanding requests of adaptable cryptographic natives to protected group data transactions and computing platforms in cloud. Group key agreement (GKA) protocol enables a group to share a standard encryption key across an open network so that only members of the group may decode the ciphertexts encoded using the secret encryption key that has been released. However, a sender cannot deny any specific member from decryptions the ciphertexts in cloud. However, before sending a message to a group, a user must join the group and follow the GKA protocol to provide the intended members access to a secret key. To find a better solution for the above-mentioned issues, flexible and secure continues data transmission (FSCDT) algorithm is proposed to offer dynamic and secure data transfer broadcasting without full trust of key authority in unreliable cloud environment. It provides compete security proof, outlines the requirements of the aggregatability of the secret attribute based FSCDT building block. Based on experimental evaluations, FSCDT algorithm minimizes encryption time, decryption time and communication cost.
Mapping and predicting research trends in international journal publications using graph and topic modeling
Authors: Suyanto Asep Herman , Djatna Taufik , Wijaya Sony Hartono
Published: February 2023

Researchers and journal managers need summary information, such as research maps and trends. Topic and words-based document content analysis alternative to science mapping and trend prediction based on bibliographic analysis. The data are a collection of journal articles/proceeding documents and metadata for 2011-2020 published by the International Journal of Electrical and Computer Engineering (IJECE). A combination of several techniques and methods is used, such as text mining, topic modeling, cosine similarity, network analysis, graph theory, and seasonal autoregressive integrated moving average (SARIMA). This research has produced research topics, mapping, trend prediction, and visualization according to its objectives. The results of the topic coherence test obtained the optimal number of topics, as many as 6. The results of the topics were evaluated by experts to be given labels and areas of focus. On the research map for each topic, information is found on trending research, the most popular research, research that is central to the research group, and critical research on the development of the group path. It also identifies the type of breakthrough, incremental, and research gap. Predictions of research trends obtained are based on topics and words that describe the development of research. Visualization is descriptive and predictive.
Rainfall prediction model in Semarang City using machine learning
Authors: Usman Carissa Devina , Widodo Aris Puji , Adi Kusworo , Gernowo Rahmat
Published: February 2023

The erratic distribution of rainfall greatly affects people's daily activities, especially in Semarang City, so it is necessary to predict rainfall. Correct prediction of rainfall can improve community preparedness in dealing with natural disasters. Algorithms for machine learning and data mining have been extensively utilized in research involving rainfall data from various regions. The primary objectives of this study are to find the best regression algorithm and use machine learning algorithms to predict rainfall in Semarang. The dataset used is daily rainfall data for the City of Semarang from the meteorological, climatological, and geophysical agency (BMKG). Machine learning algorithms such as multiple linear regression, random forest regression, and replicated neural networks will be used to conduct regression analysis on this dataset. The mean absolute error and Root mean squared error techniques are utilized to evaluate the performance of machine learning algorithms. With an error rate of 13.055 for root mean squared error (RMSE) and 6.621 for mean absolute error (MAE), the results of the research indicate that the performance of the neural network algorithm is superior to that of other algorithms.
A survey of intelligent energy management based on learning heuristic
Authors: Hamed Musa Abdullah , Hussein Esam Taha Yassin , Abd Wesam Mohammed Jasim
Published: February 2023

Human activities are dependent on energy and lifestyles that important provide services on a daily basis. Currently, polluting and energy consumption worldwide is dominated by sources non-renewable, for instance fossil fuels. Due to their environmental impact, research and investment have increased in alternative and renewable energy sources, such as photovoltaic and wind energy. Buildings use energy management systems to monitor real-time consumption and plan the operation of appliances so that the energy bill is minimized or based on other factors. The purpose of energy management systems in buildings is mainly to monitor real-time energy consumption and adjust the device's operation to minimize energy bills or achieve another specific goal. The purpose of this work is review the latest literature on energy management systems based on heuristic learning of buildings in the smart home. In addition, the literature has been updated a list of techniques that managed appliances and the planning goals and how use these techniques to in the energy scheduling.
Model of intention and actual use mobile learning in higher education institutions in Iraq
Authors: Izkair Ayad Shihan , Lakulu Muhammad Modi
Published: February 2023

Mobile learning (ML) is now involved in the creation of teaching and learning methods for higher education. However, this involvement is varied among countries. The objective of this research was to examine the factors that impact students' intentions to use ML in Iraqi higher education institutions (HEIs). Building on unified theory of acceptance and use of technology (UTAUT) and information system success model (ISSM), a conceptual model was developed. The population of this study are users in Iraqi univeristies. Using a stratified random sampling, a total of 323 responses were collected to examine the proposed hypotheses. The findings showed that variables of UTAUT such as effort expectancy (EE), social influence (SI), performance expectancy (PE), facilitating conditions (FC) as well as variables of ISSM such as satisfaction along with perceived enjoyment and self efficacy affected positively the intention to use ML (ITUML) which in turn affected actual use (AU). Gender and experience moderated the effect of PE, EE, and SI on ITUML. A model of ITUML among users in Iraqi HEI was developed. Decision makers are advised to focus on certain variables to enhance the usage of ML in HEI.
An intelligent mitigation of disturbances in electrical power system using distribution static synchronous compensator
Authors: Alhattab Ahmed Samir , Alsammak Ahmed Nasser B. , Mohammed Hasan Adnan
Published: February 2023

The power quality of an electrical system is critical for industrial, commercial, and housing applications, and with the increasing use of sensitive loads, customers and utilities are beginning to pay more attention to it. A distribution static synchronous compensator (D-STATCOM) represents one of the best custom power devices (CPDs) for improving the power quality of a distribution system. The performance of this device relies upon the algorithm and strategy used for its control. Artificial intelligence was utilized to overcome these shortcomings, while a response optimizer tool was used for the tuning process. An adaptive controller design was also proposed, based on the integration of fuzzy logic with traditional proportional-integral (PI) controller. The fuzzy logic controller system was designed using the adaptive neuro fuzzy interference system (ANFIS) editor. In this work, a D-STATCOM controller was used to mitigate sag and swell problems, while the ANFIS together with the optimization method was used to improve the system response. This study was carried out using MATLAB/Simulink, and the results showed a superior and adaptive performance in mitigating voltage sag and swell problems at different loading conditions compared to the traditional PI.
Effects of parameter adjustment on the electromagnetic field of an overhead power transmission line model
Authors: Ghani Sharin Ab , Khiar Mohd Shahril Ahmad , Chairul Imran Sutan , Rahim Nor Hidayah , Hashim Syahrun Nizam Md Arshad@
Published: February 2023

Studies have shown that high-voltage power transmission lines emit electromagnetic radiation, which has adverse effects on human health. This paper presents the effects of parameter adjustment on the electric and magnetic fields of an overhead power transmission line model at human height. A finite element software, COMSOL multiphysics, was used to simulate the electric and magnetic fields. The electric and magnetic fields generated by the 1200-kV and 220-kV overhead power transmission line models were first computed and the models were validated by comparing the simulation results with those of previous studies. Numbers of parameter were adjusted in order to investigate their effects on the electric and magnetic field distributions. Based on the results, the electric field intensity increases with an increase in the voltage of the conductors. The magnetic field density increases with an increase in the current carried by the conductors. A voltage of 700 kV results in an electricity field intensity that exceeds the residential safety limit (50 kV/m) set by the International Commission on Non-Ionizing Radiation Protection. Hence, a proper right-of-way is needed to ensure that residential areas are at a safe distance away from transmission towers.
The impact of using phase-shift transformers on transmission lines
Authors: Al-Rawashdeh Ayman Y. , Alzyoud Abdallah R. , Alzyoud Khalaf Y. , Alkasassbeh Jawdat S. , Samara Ashraf
Published: February 2023

Phase shift transformers (PST) are a special type of transformers used to regulate active and reactive power on 3-phase transmission networks by adjusting the difference of voltage phase angle between system nodes. Problems related to power flow and stability, particularly voltage stability issues, are important at the extra high voltage (EHV) and ultra high voltage (UHV) levels due to their extreme sensitivity to active and reactive power changes. Several studies investigated these problems using three-phase systems. Accordingly, this research aims to demonstrate the impact of using PST with single and double transmission lines and to compare its performance under various operational modes.
Electromagnetic force distribution computations due to switching surge in disc-type winding
Authors: Md Yasid Nurul Farahwahida , Azis Norhafiz , Yousof Mohd Fairouz Mohd , Jasni Jasronita , Talib Mohd Aizam , Murthy Avinash Srikanta
Published: February 2023

This manuscript discusses the computation of electromagnetic forces on a disc-type winding due to a standard switching impulse (SSI). First, the resistances, inductances and capacitances (RLC) of a 30 MVA, 33/11 kV disc-type distribution transformer were estimated to obtain the winding equivalent circuit. The transient voltage waveforms for each of the disc layers and corresponding resonances of the windings under the SSI were then obtained in time domains. Next, the axial and radial force distributions in the disc winding due to the SSI were computed. The forces on each disc layer and along the disc windings due to the SSI were computed based on the analytical and numerical methods via the finite element method (FEM) respectively. The non-uniform switching impulse voltage distribution results in non-uniform force distribution along the disc winding. The magnitude of the axially directed force on the disc winding is found to be higher as compared to the radially directed force.
Neural network based novel controller for hybrid energy storage system for electric vehicles
Authors: Sharma Sagar , Boora Shakuntla
Published: February 2023

This manuscript deals with the various control strategies of storage system for an electrical vehicle. High demands in the electrical systems in the field of transportations leads to various challenges and more precise control and regulations techniques. Apart from the conventional grid system now a days the integration of renewable energy systems like solar, wind and fuel cell system leads to more complex system but these system shares the load from conventional generating system. This paper deals with the study and control aspects of the electrical vehicles associated with hybrid energy storage (HES) systems. In general, when systems are integrated with the main grid there are more distortions and ripples in the system. To reduce these distortions various control techniques are used. This paper proposes a neural network-based PI (NNPI) controller for HES system for electric vehicles for better distortion less outputs.
Low-cost portable throttle curve manipulator for smooth initial movement of an electric vehicle
Authors: Adiputra Dimas , Widodo Pangestu , Widodo Aldo Juan , Bayuaji Yosefan Alfeus , Putri Nadia Dinda Pratama
Published: February 2023

This research aims to develop a low-cost portable throttle curve manipulator for a smooth initial movement of an electric vehicle. The hardware is mostly made up of an Arduino and a pulse width modulation (PWM)-to- direct current (DC) converter, which can be easily installed in electric vehicle. The manipulator produces a throttle output curve based on the current throttle input. The suitable throttle output curve is investigated in two stages. First, the four throttle curve types are compared based on motor vibration change and total energy usage during initial movement. They are none, linear, exponential, and polynomial curve types with a delay of 1 s. Then, in the second stage, the delay is varied from 0.5 to 2.5 s. The result shows that the linear throttle curve output with a delay of 1 s produces is appropriate to refine the initial movement of an electric vehicle compared to the polynomial and exponential curve types. The brushless DC electric (BLDC) motor vibration change decreases from 148.75 Hz to 107.45 Hz and total energy usage decreases from 90.64 joules to 87.23 joules. Therefore, the research concludes that the low-cost portable throttle curve manipulator can be developed using a linear throttle output curve with a delay of 1 s.
Design of sample display system on electronic nose for synthetic flavor classification
Authors: Barokah Barokah , Radi Radi , Zamzami Luthfi Fadillah , Setiawan Andi , Putro Joko Purwo Leksono Yuroto
Published: February 2023

This study aimed to design a controlled sample display system on an electronic nose and test its performance for classifying synthetic flavors. There are four primary components to the electronic nose design. They are a controlled sample display system, detector, signal conditioning and preprocessing, and pattern recognition software. The sample display system consists of six vials. The sample room temperature setpoint is set to 40 ℃. The controlled sample display system has one heater and two fans to even the room temperature. The one-time data collection process consists of flushing (120 s), collecting (180 s), and purging (180 s). The samples for the performance test were synthetic flavors with four different aromas; durian, mocca, orange, and strawberry. Data analysis of gas sensor response was done through two stages; pre-treatment data processing and principal component analysis (PCA). The four samples were clearly different from others, according to the PCA results. The scores of the PC-1, PC-2, and PC-3 cumulative variance were 98.28%.
Fingerprint biometric voting machine using internet of things
Authors: Yusoff Zakiah Mohd , Yusnoor Yusradini , Markom Arni Munira , Nordin Siti Aminah , Ismail Nurlaila
Published: February 2023

Free elections are one of democracy's principles. Elections will be used to choose the representatives of the people. It is underlined on how important it is to organize free, fair, and secret elections. Traditionally, voting used to be conducted by stamping on paper, then placing it in a ballot box with the chosen candidate. Each vote in every ballot box must be counted separately, and the votes for each contender must then be added up to determine which candidate had the most votes. Everything was done manually, it will take longer to announce the winner. Numerous errors are being made, but they will not change the outcome. In this study, a significant system that stops electoral malpractices and expedites the voting process will propose. The controller utilized in this project is the Arduino Uno. The user is authenticated using a fingerprint. Everybody's fingerprints differ from one another. The device is programmed using the Arduino IDE, and the ballot card is displayed, and the results are stored in the cloud. Only a registered voter may cast a vote, and the system alerts users to any fraud. This project protects citizens' freedom to vote and ensures an impartial election.
Effects of (Ba,Ca)ScO2F:Bi3+,K+ phosphor particle size on color uniformity white light-emitting diodes
Authors: Tung Ha Thanh , Dang Huu Phuc
Published: February 2023

Phosphors that offer considerable performance as well as heat consistency has been a high priority of recent studies concerning light-emitting diodes (LED) devices. This study employs the perovskite phosphors BCSOF (short for Ba1-xCaxScO2F:0.001Bi3+,0.001K+ with x value from 0 to 0.12 and one chip at 415 nm generating thin green illumination via cation-replacement method. The study examines the aftermath when Ca2+ replaces Ba2+ within the crystal formations of BCSOF as well as the luminescent features of the phosphors, detecting a formation of cube-like perovskite within the space group of Pm3m in the employed phosphors. In addition, the study also assesses the development concerning the magnitude of cells as well as the binding extent of Ba/Ca/K/Bi-O. When the inner quantum performance reaches 77.4% in BCSOF, a potent green discharge is manifested, reaching 510 nm when excited by a chip at 415 nm. Greater luminescent performance as well as heat consistency correlating with changes in inner formation were reported. Via the method of replacing cations, it is possible to control spectrum by manipulating the latticework’s surroundings, leading to desirable performance in LED products.
The impacts from SrS:Cu+,Na and LaOF:Eu3+ phosphors on color and luminous performances at 5600 K–8000 K WLEDs
Authors: Tung Ha Thanh , Dang Huu Phuc
Published: February 2023

In terms of lumen performance, the remote phosphor structure can yield better results than the conformal phosphor and in-cup phosphor packages. The application of such a package in LEDs might make the manipulation of the device’s chromatic performance challenging. Two remote phosphor packages are available for raising chromatic performance: one-layer and triple-layer phosphor adjustments. Using software simulation and phosphors created through specific procedures, our study was carried out to select the best adjustment that provides the best results in white LEDs (WLEDs) implemented with many chips: color rendering index (CRI), color quality scale (CQS), lumen output (LO), along with chromatic uniformity. We utilized the WLEDs at five temperatures of color between 5,600 K and 8,500 K. From the outcome, we can consider the three-layer phosphor package to have greater CRI, CQS, and lumen efficiency (LE). Notably, CQS and LE receive a roughly 30% boost compared to singular-layer package. The package can also reduce the chromatic deviation by roughly 30% to 50%, and therefore, grants a boost in chromatic homogeneity. To authenticate these outcomes, the dispersion attribute underwent examination in the layers of phosphor based on Mie-dispersion hypothesis. The outcome may prove useful for creating WLED devices with greater standards.
Watch winder based on the internet of things
Authors: Kamajaya Leonardo , Fitri Fitri , Azzmi Santoso Mocharief
Published: February 2023

Watches are wearable devices that support human activities as timepieces. There are two types of watches based on their source driving energy: the quartz type, which uses a battery, and the automatic mechanical type, which uses a mechanical mechanism to convert the kinetic energy obtained when the clock is used as the energy to drive the hands. Automatic mechanical type watches have a time limit of 48 hours or two days until the energy turns off and the time stop. Therefore, a watch winder is needed to make movements to keep the automatic watch running while not in use. So, users can use their watch again without the need to adjust the time, date and other functions. The watch winder produced in this study employs a stepper motor that is controlled by an ESP32 microcontroller via a ULN2003 motor driver integrated circuit (IC). This type of stepper motor is used because it has a high rotor rotation precision to prevent the clock from over-winding problems. This watch winder device also has a watch condition monitoring feature through application-based temperature and humidity parameters. Users can monitor the condition of their watch and control the dial of the watch winder’s modules through the integrated application.
Transmission line characterization and modeling for electronic circuits and systems design
Authors: Famoriji Oluwole John , Shongwe Thokozani
Published: February 2023

Channel bandwidth-limited high-speed links or interfaces make circuit solutions not efficient. Both recent and subsequent links (SerDes-Serializer/Deserializer) design demand efficient and effective coupling between future circuit design, communication, and optimization. The challenges vary and new solutions are needed. In this article, an analytical wireline model is presented to predict electronic path loss towards adequate designs of electronic circuits and systems. An open loop system analysis is adapted in this paper. Our model was tested against different channels: a legacy channel with via stub discontinuity and FR4 dielectric, and a more recent microwave-engineered channel without stub and NELCO 6,000 dielectric, a very good matching attained. Good agreement was observed between our model and electromagnetic full-wave simulation data, as a result showed high level of applicability to thin-film microstrip line for adequate circuit design. The model is recommended for electronic engineers for adequate and faster interfaces and high-speed links designs.
Simulation model of ANN and PID controller for TCP/AQM wireless networks by using MATLAB/Simulink
Authors: Jaber Manal Hadi , Oudah Manal Kadhim , Shneen Salam Waley
Published: February 2023

The wireless network transmission control protocol/active queue management (TCP/AQM) is a network that was chosen as a topic for research a basis is laid to simulate the proposed network and to conduct the simulation under certain conditions. To manage the queue control protocol (TCP/AQM) was chosen. The solution for many modern systems depends on placing additional units called controllers, which work to improve the performance of the work of the systems. The current simulation system can be described according to the test cases that were conducted, where four test cases were identified with sequential steps. In this work there are two control methods by simulation and mathematical model of wireless network TCP/AQM with proportional, integral and derivative (PID) controller and neural network. Simulation is conducted for cases in order to determine the performance of each case through comparison according to appropriate criteria to determine the best. The first case is a wireless communication network system with with a traditional controller PID type. The second is a wireless communication network system, a large neural network controller. Simulations were conducted to choose the best methods among those suggested for nonlinear systems and to enhance and achieve the possibility of adopting MATLAB to perform the required simulation.
Control of gas pipeline leakage detection based on hybrid inline fiber interferometer
Authors: Noori Nada F. , Mansour Tahreer S.
Published: February 2023

Hybrid inline fiber interferometers gained attention recently especially in the building control and detection fields due to their hybrid multi-path interferences, multi-parameter measurements, high sensitivity, and high precision. This work used etched multimode fiber (MMF) to introduce a novel medical gas pipeline leakage detector based on hybrid Fabry-Perot/Mach-Zehnder inline fiber interferometer (FP-MZI). The hybrid FP-MZI of this work consisted of two cascaded identical fiber Bragg gratings (FBGs) spliced to coreless fiber sandwiching the MMF. Four samples of different MMF lengths and sizes were used as sensing heads in the detection measurements. Self-imaging and phase-equations of the proposed interferometer were solved analytically to select the required length; then COMSOL software was used to ensure the occurrence of the required interference along the proposed interferometer at the designed wavelength. Two medical gas sources; air compressor and high-pressure gas cylinder, attached to two pipelines of size 15×0.7, and 12×0.6 mm was used to provide the required pressure. Gas leak was introduced to the pipes manually through controlled valves and measured using the proposed hybrid FP-MZI. Both constant and variable gas flowrates was investigated with variable gas pressures. The obtained sensitivity was ranged from 0.17-20.9 pm/bar for all of the investigated cases.
A new motion structure for a six-legged insect robot with Bluetooth remote-control
Authors: Alawan Mazin Abdulelah , Abdulabbas Ali Kadhim , Al-Furaiji Oday Jasim Mohammed
Published: February 2023

This paper focuses on motion which is considered an important issue for insect robots, which consumes significant energy sources in general. We inspired the robot design structure from the challenges that crawling insects face in nature, especially a cockroach. The proposed robot configuration enhanced error scale such as energy modulation, computation, and mass. This paper presents the design and construction of six-legged robot with minimum number of trigger motors and the movement mechanisms used for the leg movements. The insect robot resembles a cockroach in shape and size (1.6 cm × 4 cm) and can move at rates of up to 3.5 cm per second. The robot can operate for up to 260 minutes. Additionally, it has a camera that can rotate more than 60 degrees in response to commands from a smartphone. The 160×120 pixels monochrome "first person" camera transmits video to a Bluetooth radio at a distance of up to 120 meters away at a frame rate of 1 to 5 per second.
Smart system for controlling and monitoring electronic facilities in budget hotel rooms
Authors: Hutabarat Daniel Patricko , Saleh Robby , Sebastian Lukas , Jonathan Jonathan , Arosha Senanayake Mudiyanselage Namal
Published: February 2023

The fundamental attribute of a budget hotel is the provision of essential services at a low cost due to reduced services and facilities. Several services at budget hotels that affect customer choice are related to limitation of accommodation and entertainment services which include the use of television, air conditioning, and other electrical devices. The purpose of this research is to develop a smart system that is used to control and monitor electronic facilities in budget hotel rooms. This system provides budget hotels with the ability to select the electronic facilities that guests want to use in their rooms according to their needs and budget. This system also provides a feature to monitor the use of electronic devices in each room via a web application. The system was developed by using microcontrollers, sensors, radio frequency identification (RFID) devices, a database server, and a web application. The developed system can perfectly provide the room electronic facilities requested by the guest. The system can also monitor the service hour and power consumed by the devices with an accuracy of 99.1% for the service hour and 99.4% for the power consumed.
New blender-based augmentation method with quantitative evaluation of CNNs for hand gesture recognition
Authors: Doan Huong-Giang , Nguyen Ngoc-Trung
Published: February 2023

In this study, we extensively analyze and evaluate the performance of recent deep neural networks (DNNs) for hand gesture recognition and static gestures in particular. To this end, we captured an unconstrained hand dataset with complex appearances, shapes, scales, backgrounds, and viewpoints. We then deployed some new trending convolution neuron networks (CNNs) for gesture classification. We arrived at three major conclusions: i) DenseNet121 architecture is the best recognition rate through almost evaluated red, green, blue (RGB) and augmentation datasets. Its performance is outstanding in most original works; ii) blender-based augmentation help to significantly increase 9% of accuracy, compared to the use of a RGB cues; iii) most CNNs can achieve impressive results at 97% accuracy when the training and testing datasets come from the same lab-based or constrained environment. Their performance is drastically reduced when dealing with gestures collected in unconstrained environments. In particular, we validated the best CNN on a new unconstrained dataset. We observed a significant reduction with an accuracy of only 74.55%. This performance can be improved up to 80.59% by strategies such as blender-based and/or GAN-based data augmentations to obtain an acceptable result of 83.17%. These findings contribute crucial factors and make fruitful recommendations for the development of a robust hand-based interface in practice
Evaluating the Bantu parametric grammar in grammatical framework using Swahili grammar
Authors: Kituku Benson , Muchemi Lawrence
Published: February 2023

Monologue grammar development for under-resourced languages is very slow and laborious (involves creating rules to generate the computational grammar to enable analysis and synthesis of the language(s) in question). However, the need for computational grammar continues to soar in this technology-driven economy for information synthesis and analysis. This paper aims to set up an experiment in the grammatical framework (GF), to evaluate the efficiency and effectiveness of the Bantu parameterized grammar to bootstrap a new grammar for Swahili. The goal is to investigate how this approach of bootstrapping grammar in a multilingual environment is effective and efficient in reducing the development effort. The bootstrapping approach uses the GF morphology-driven approach to develop portable and unique segments of Swahili grammar. The bootstrapped Swahili grammar resulted in a shareability of 100%, 71.11%, 68.75%, and 91.41% at category linearization, paradigms, parameters and syntax rules respectively. The portability was at 15.55%, 18.57%, and 8.59% at paradigms, parameters and syntax rules, respectively. Finally, this paper contributes in: first, provides an approach that leads to an effective and efficient method for developing and bootstrapping computational grammar for the under-resourced Bantu languages. Secondly, the research provided a Swahili grammar.
Analysis of SSVEP component acquisition from EEG signals for efficient target identification
Authors: Swetha Kalenahally R. , Krishnegowda Ravikumar G. , Venkataramu Shashikala S.
Published: February 2023

The application of the brain-computer interface (BCI) is massively helpful and advantageous for disabled people. Moreover, BCI is an arrangement of software and hardware interface that provides a direct interaction between the human brain and computer devices. Therefore, in this article, A steady state visual evoked potential (SSVEP)-based BCI system is presented to identify SSVEP components from multi-channel electroencephalogram (EEG) data by minimizing background noise using an adaptive spatial filtering method. Here, the proposed adaptive spatial filtering-based SSVEP component extraction (ASFSCE) model improves reproducibility among multiple trails and identifies targets efficiently by optimizing the Eigenvalue problem. Along with that, the proposed ASFSCE model minimizes computational complexity from O(G2) to to get high target identification accuracy with faster execution. Performance results are measured using the SSVEP dataset. In this dataset, 11 subjects are used to perform experiments and 256-channel EEG data is taken. The efficiency of the proposed ASFSCE model is measured in terms of mean target detection accuracy and mean information transfer rate (ITR) in bits per minute. The average detection accuracy and ITR are evaluated by considering 23 trials for each subject. The obtained detection accuracy is 93.47% and ITR is 308.23 bpm.