bluuebunny/crossref_metadata_2025 huggingface dataset:
Menopausal Hormone Therapy and the Breast: A Review of Clinical Studies
Authors: Sourouni Marina , Kiesel Ludwig
Published: March 2023

Background: Women in the peri- or postmenopause can experience symptoms related to the gradual degradation of ovarian function. Hormone replacement therapy (HRT) is the most effective therapy to treat common menopausal symptoms such as hot flashes and vaginal discomfort. However, safety concerns have been raised revolving, among others also, around the risk of breast cancer. Methods: This article is based on a selective literature search for relevant studies regarding HRT use and the risk of breast cancer in the general population or BRCA carriers, the risk of breast cancer recurrence, or the risk of breast cancer in situ. Summary: HRT can lead to little or no increase in breast cancer risk. The risk depends on the duration and composition of the HRT and decreases after stopping the treatment. Data assessing the oncological safety of HRT after breast cancer are inconsistent. According to current knowledge, HRT is fundamentally contraindicated after breast cancer but can be individually considered after a risk-benefit assessment and when nonhormonal therapies have failed. The same applies to HRT after DCIS, which should not be routinely offered but nonetheless can be considered in individual cases. HRT can be offered up to the age of natural menopause for BRCA mutation carriers who are undergoing risk-reducing bilateral salpingo-oophorectomy and do not have a personal history of breast cancer, but is contraindicated in BRCA mutation carriers who have already had breast cancer.
Distributed formation control for groups of mobile robots using consensus algorithm
Authors: Afdila Ryandika , Fahmi Fahmi , Sani Arman
Published: March 2023

The increasing implementation of autonomous robots in industries and daily life demands the development of a robust control algorithm that enables robots to perform their tasks successfully. Critical tasks such as rescue missions and area exploration require robots to work cooperatively in a formation to accomplish the tasks quickly. Moreover, the existence of obstacles in the environment requires all the robots' to rapidly process environmental changes to maintain the formation pattern. Thus, this paper introduces a distributed robot formation control system using the consensus algorithm that enables a group of robots to establish and maintain formations using only the local information of the robots. Furthermore, an obstacle avoidance algorithm based on the distance and angle between robots and obstacles is introduced to ensure safe navigation for the group of robots. The algorithm's effectiveness is demonstrated by a multi-robot system with randomly generated starting positions and velocities, where it is shown that the robots can agree on the control variables and establish the required formation while also avoiding obstacles in the environment.
A novel octagonal slot circular compact ultrawideband antenna with detailed frequency and time-domain analysis
Authors: Kannale Satish Kumar , Biradar Nagashettappa
Published: March 2023

With time, the device's reliance on wireless communication and its users grows tremendously. The ultrawideband (UWB) technology offers a 7.5 GHz uncontrolled bandwidth. Because it allows for larger data rates over a short distance, UWB technology is the current and future requirement of new generation mobile networks. As a result, a novel octagonal slot circular compact UWB antenna with detailed frequency and time-domain analysis is proposed in this research. Throughout the UWB range, the hexagonal-shaped circular radiator aids in reaching better S11 parameters (S11-10 dB). The modified trapezoidal like partial ground plane allows for a wide bandwidth. The proposed UWB antenna operates at frequencies ranging from 3.2 to 13.1 GHz, allowing for a bandwidth of 9.9 GHz and a fractional bandwidth of 121.4%. Voltage standing wave ratio (VSWR) is seen to be in the range of 1 to 2 throughout this UWB range. Throughout the operational bandwidth, the antenna's gain ranges from 2.8 to 4.1 dB. The suggested UWB antenna has the advantages of being small, having superior impedance matching, a simple design, and having a high gain, all of which can be used to deploy the antenna for the aforementioned purposes.
Breast cancer detection: an effective comparison of different machine learning algorithms on the Wisconsin dataset
Authors: Hossin Md. Murad , Javed Mehedi Shamrat F. M. , Bhuiyan Md Rifat , Akter Hira Rabea , Khan Tamim , Molla Shourav
Published: March 2023

According to the American cancer society, breast cancer is one of the leading causes of women's mortality worldwide. Early identification and treatment are the most effective approaches to halt the spread of this cancer. The objective of this article is to give a comparison of eight machine learning algorithms, including logistic regression (LR), random forest (RF), K-nearest neighbors (KNN), decision tree (DT), ada boost (AB), support vector machine (SVM), gradient boosting (GB), and Gaussian Naive Bayes (GNB) for breast cancer detection. The breast cancer Wisconsin (diagnostic) dataset is being utilized to validate the findings of this study. The comparison was made using the following performance metrics: accuracy, sensitivity, false omission rate, specificity, false discovery rate and area under curve. The LR method achieved a maximum accuracy of 99.12% among all eight algorithms and was compared to other comparable studies in the literature. The five features chosen are used to calculate the model's fidelity-to-interpretability ratio (FIR), which indicates how much interpretability was sacrificed for performance. The uniqueness of this work is the explainability approach taken in the model's performance, which aims to make the model's outputs more understandable and interpretable to healthcare experts.
Secure two-factor mutual authentication scheme using shared image in medical healthcare environment
Authors: Abdulmalek Husam A. , Yassin Ali A.
Published: March 2023

The cloud healthcare system has become the essential online service during the COVID-19 pandemic. In this type of system, the authorized user may login to a distant server to acquire the service and resources they demand, we need full security procedures that cover criteria such as authentication, privacy, integrity, and availability. The journey of security for any healthcare system starts with the authentication of users based on their privileges. Traditional user authentication mechanisms, such as password and personal identification number (PIN) typing, are vulnerable to malicious attacks like on/offline, insider, replay, guessing, and shoulder surfing. To address these issues, we proposed a secure authentication scheme that uses the authenticated delegating mechanism based on two factors: a one-time password and generating a secure variable vector from a legible user's digital image to enable the permission of a user through the back-end database of a cloud server. The proposed mutual authentication can protect the information against well-known attacks, ensure the user's privacy, and key management. Moreover, comparisons with existing schemes show that the proposed scheme supplies more privacy, security metrics, and resistance to attacks than the others while being more efficient in computation and communication costs.
Impulsive noise mitigation based adaptive filtering and Reed Solomon coding for power line communication
Authors: Mohammed Asaad Jasim , Mahmoud Al-Azawi Maher Khudair
Published: March 2023

In the realm of power line communication (PLC), impulsive noise is often regarded as the most difficult challenge to face in PLC. The impulsive noise effects are reduced by employing a combined adaptive least mean square (LMS) filtering and Reed Solomon (RS) coding. As a result, the bit error rate (BER) and throughput performance over this channel are enhanced. The results of a MATLAB computer simulation indicated that a significant improvement is achieved by utilizing the LMS adaptive filter in conjunction with the RS code. This is in contrast to a system that utilizes RS code alone or a system that utilizes the conventional time domain clipping approach.
Design of CRC circuit for 5G system using VHDL
Authors: Saleh Adham Hadi , AL-Qaysi Hayder Khaleel , Humood Khalid Awaad , Mahmood Tahreer
Published: March 2023

In this document, we focus on how to design cyclic redundancy check (CRC) circuits with different 5G polynomial divisor using very high-speed integrated circuit (VHSIC) hardware description language (VHDL) to integrate in field-programmable gate array (FPGA) suitable kit using a suitable design code. The different between designed circuits came from the different of data size according to polynomials requirements conditions since there are huge data size in 5G system that required divide it with suitable method and then implemented the required circuit. CRC code as a polar code and short low density parity check (LDPC) is proposed in 5G new radio (NR) systems, CRC properties to divided data and CRC cod make it particularly very useful for codes with higher data rate and longer lengths, and for codes with low data rates and small length as an error detection method. The CRC encoder circuit (transmitter side) and CRC decoder circuit (receiver side) with different polynomial and data size have been designed using VHDL. Xilinx ISE 14.3 simulator, where the test bench simulation results give the expected simulator results of proposed decoding circuit scheme so to integrated using ZYNQ FPGA kit.
Bandwidth enhancement of millimeter-wave microstrip patch antenna array for 5G mobile communication networks
Authors: Musa Umar , Babani Suleiman , Babale Suleiman Aliyu , Ali Abubakar Sani , Yunusa Zainab , Lawan Sani Halliru
Published: March 2023

This paper proposed enhancing the bandwidth of a millimeter wave microstrip patch antenna (MPA) and its array for a 5G mobile communication network. The proposed antenna is designed and fabricated on a Rogers RT Duroid 5,880 substrate with a standard thickness of 0.5 mm, a relative dielectric constant of 2.2, and a tangent loss of 0.0009. With a center frequency of 28 GHz, a measured return loss of -21.37 dB, a bandwidth of 1.14 GHz, and a gain of 6.27 dBi, the proposed single element operates in the local multipoint distribution service band. The proposed antenna is designed and manufactured as an array of 1×2 and 1×4 elements. The 2-element MPA array has a measured bandwidth of 1.207 GHz and a gain of 7.76 dBi, higher than that of a single element. The 4-element MPA array achieved a measured bandwidth of 2.685 GHz and a gain of 9.87 dBi, which is higher than the 2-element and single-element arrays at 28 GHz. This demonstrates that the array of antennas improves gain and bandwidth significantly. Hence, the proposed antenna and array are suitable for 5G mobile communication networks due to their small size.
Wind power forecasting model based on linguistic fuzzy rules
Authors: Moujabbir Mohammed , Bahani Khalid , Ramdani Mohammed , Ali-Ou-Salah Hamza
Published: March 2023

The design and operationalization of a wind energy system is mainly based on wind speed and wind direction, theses parameters depend on several geographic, temporal, and climatic factors. Fluctuating factors such as climate cause irregularities in wind energy production. Therefore, wind power forecasting is necessary before using wind power systems. Furthermore, in order to make informed decisions, it is necessary to explain the system's predictions to stakeholders. The explainable artificial intelligence (XAI) provides an interactive interface for intelligent systems to interact with machines, validate their results, and trust their behavior. In this paper, we provide an interpretable system for predicting wind energy using weather data. This system is based on a two-step method for fuzzy rules learning clustering (FRLC). The first step uses subtractive clustering and a linguistic approximation to extract linguistic rules. The second step uses linguistic hedges to refine linguistic rules. FRLC is compared to with artificial neural network (ANN), random forest (RF), k-nearest neighbors (K-NN), and support vector regression (SVR) models. The experimental results show that the accuracy of FRLC is acceptable regarding the comparison models and outperform them in terms of the interpretability. In parallel with prediction, FRLC model provides a set of linguistic fuzzy rules that explain the obtained results to the stakeholders.
Bengali Slang detection using state-of-the-art supervised models from a given text
Authors: Hamid Md. Abdul , Tumpa Eteka Sultana , Polin Johora Akter , Nahian Jabir Al , Rahman Atiqur , Mim Nurjahan Akther
Published: March 2023

Almost all Bengalis who own smartphones also have social media accounts. People from different regions occasionally employ regional Slang that is unfamiliar to outsiders and confuses the meaning of the sentence. Nearly all languages can now be translated thanks to modern technology, but only in very basic ways, which is a concern. Bengali Slang terms are difficult to translate due to a dearth of rich corpora and frequently occurring new Slang terms developed by people, making it impossible for speakers of other languages to understand the context of a sentence in which Slang is used. We developed a solution to this issue. To create models that can detect Bengali Slang terms from social media, we gather various Slang phrases from various regions and develop a modest corpus. Our suggested method nearly always succeeds in extracting Bengali Slang terms from fresh material. We create a total of 7 supervised models and assess which is the most effective for our study. One of them has a 70% accuracy and 86% recall rate for successful identification. Our models may be linked to the social media platform's backend to restrict the use of Bengali Slang in posts, blogs, comments, and other areas.
A 2.45 GHz microstrip patch antenna design, simulation, and anlaysis for wireless applications
Authors: Rana Md. Sohel , Sen Bijoy Kumer , Tanjil-Al Mamun Md. , Mahmud Md. Shahriar , Rahman Md. Mostafizur
Published: March 2023

This paper designs, simulates, and analyzes the S-band microstrip patch antenna (MPA) for wireless applications. FR-4 (lossy) and Rogger RT/duroid, whose dielectric permittivity is 4.3 and 2.2, respectively, have been used as substrate materials. Simulation is done by computer simulation technology (CST) suite studio 2019 software. Simulations with FR-4 material showed that the return loss was -20.405 dB, the gain was 2.592 dB, the directivity was 7.47 dBi, the voltage standing wave ratio (VSWR) was 1.221, the bandwidth (BW) was 0.0746 GHz, and the efficiency was 34.69%. Also, Rogers RT/duroid material gives results of a return loss of -12.542 dB, a bandwidth (BW) of 0.0349 GHz, a gain of 8.092 dB, a directivity of 8.587 dBi, and an efficiency of 94.24%. The main goal of this antenna is to have a low return loss while getting as close as possible to a VSWR of 1. This will improve the antenna's gain, directivity, and efficiency compared to other antennas. Copper was used to make the patch and the ground, which were 0.35 mm and 0.0077 mm thick, respectively. The results obtained from the proposed antenna were better than those previously published in various in modern scientific journal and conference papers.
Statistical analysis of the predictors of annual electric vehicle mileage
Authors: Du Sizhuo , Paliivets Maxim , Petunina Irina
Published: March 2023

This study evaluates the impact of technical and economic factors related to electric vehicles and the impact of socio-demographic factors related to electric vehicle owners on annual electric vehicle mileage from a statistical perspective. The data set was analyzed using regression and correlation analyses using Ms Excel and several Python libraries. The influence of the socio-demographic characteristics of the respondents was estimated as minimal and requiring reassessment. It was shown that among the socio-demographic factors considered, only the age of vehicle owners correlates with the annual mileage of electric vehicles. It is shown that technical and economic parameters are much more closely related to the annual mileage of electric cars than socio-demographic parameters. Significant factors among the technical and economic ones were battery capacity, power consumption of the electric car, and the size of the respondent's locality.
Modeling and simulation of a pipeline leak detection using smart inspection ball
Authors: Abed Marwa H. , Wali Wasan A. , Alaziz Musaab
Published: March 2023

Recently, pipelines have replaced more carbon-intensive transportation methods making them more environmentally friendly for transporting energy and water supplies. However, pipelines can pollute the air, water, soil, and climate when they leak, causing economic, and environmental damage. Pipeline online monitoring provides data analysis and suitable controlling strategies to contain the risk. This paper proposes a three-dimensional numerical model simulation taking advantage of the fluids moving through pipelines at specific speeds. The transport speeds depend on many conditions, such as pipe diameter, the pressure through which the fluid is being transported, and other factors, such as terrain's topography and viscosity of the fluid. Under these conditions, the inspection approach uses a self-charging movable ball. The sensors inside the ball capture data as it travels through the pipe. The simulation focuses on spherical flow and pipe noise with and without leakage based on the COMSOL software platform. The paper shows the effect of several parameters, including leak location, sensor placement, ball diameter, sound pressure level propagation along a pipe and around the sphere, velocity, and temperature distribution that give the background for future smart ball design in a promising practical pipeline test project.
Experimental and simulation investigation for rotor bar fault diagnosis in closed-loop induction motors drives
Authors: Tabet Seddik , Ghoggal Adel , Razik Hubert , Amrani Ishaq , Zouzou Salah Eddine
Published: March 2023

This research presents a comparative analysis of two broken rotor bar (BRB) fault identification techniques for closed-loop induction motors (IMs). Both motor current signal analysis and Hilbert transform (HT) rely on spectrum analysis by means of fast fourier transform (FFT). Both approaches have shown their ability to identify BRBs under varying loads. In contrast, the HT is deemed more efficient than the motor current signature analysis (MCSA) approach when the motor is working without load. To maintain a high-performance speed control and to compensate for BRBs effect on the mechanical speed, the approach of control used is direct torque control (DTC). Utilizing a real-time implementation in MATLAB/Simulink with the real-time interface (RTI) based on the dSPACE 1104 board, the efficacy of the two techniques was evaluated.
Performance analysis of wireless power transfer using series-to-series topology
Authors: Abdul Shukor Fairul Azhar , Ahmed Alhattami Ahmed Mohammed Salem , Mohd Nasir Nur Ashikin , Vaithilingam Chockalingam Aravind
Published: March 2023

Wireless power transfer (WPT) is a technology used to transmit power using air as it medium of transfer. The function of the WPT is similar to a transformer. The power provided on the primary side will be transferred through air to the secondary side. The performance of the WPT is crucially depends on the air gap length, 𝛿 that separates primary and secondary side. In this paper discusses the performance of WPT using series-to-series topology. The performance of the WPT was estimated using finite element analysis (FEA). During the study, focus was given to effect of turn ratio, a, air gap length, 𝛿 and capacitor value at primary Cp, and secondary, Cs winding to voltage ratio of the WPT. The air gap length, 𝛿 was set to 1 and 2 mm while the capacitors were set depend on the ratio of primary to secondary winding capacitor, Cp/Cs. The WPT performance also being tested under no-load and loaded operation to observed it effect. As a result, the WPT with turn ratio, a at 0.37, air gap length, 𝛿 at 1 mm and ratio of primary to secondary winding capacitor, Cp/Cs at 0.5 produce the best voltage ratio compared to other settings.
Beampattern optimization techniques using metaheuristic algorithm for collaborative beamforming: a review
Authors: Ab Majid Najla Ilyana , Nik Abd Malik Nik Noordini , Zakaria Nor Aini
Published: March 2023

The fast improvements in wireless technology and embedded systems have sparked a renewed interest in collaborative beamforming (CB) approach used in wireless sensor networks (WSNs). Despite the fact that studies on distributed and CB have been conducted for more than 10 years, CB was previously deemed unworkable because of its extreme complexity and difficult-to-attain criteria. It just got well-known in the last several years when cheaply accessible compact wireless communication electronic sensors with high processing capability emerged. These factors contributed as the motivation for this paper's research overview CB in WSNs. We provide the classifications of the static and mobile WSN which is based on the sensor node optimization technique. This paper reviews the metaheuristic algorithms proposed by previous study for beampattern and energy consumption optimization. Finally, this paper also presents a summary analysis of the previous studies in terms of beampattern characteristic and properties, energy consumption and stability.
Effect on signal magnitude thresholding on detecting student engagement through EEG in various screen size environment
Authors: Udayana I Putu Agus Eka Darma , Sudarma Made , Putra I Ketut Gede Darma , Sukarsa I Made
Published: March 2023

In this study, a new method was developed to detect student involvement in the online learning process. This method is based on convolutional neural network (CNN) as a classifier with an emphasis on the preprocessing process combined with a new feature in the form of signal magnitude area (SMA) thresholding. In this study, the data used as training data is a public dataset that emphasizes the decomposition of electroencephalography (EEG) signals into individual signal processing. Twenty subjects were taken to be used as test data, with each subject watching online learning lectures in the field of computer science on three different devices, either with a flat screen, a curved screen or a smartphone screen that is smaller than two standard computer monitors. Based on the study's results, it is known that the change in screen size is inversely proportional to the level of student attention, the smaller the screen, the lower the student's attention. For classification results, the model equipped with SMA thresholding outperformed the standard classifier by 8.33% with a test set of 20 people.
K-nearest neighbor algorithm analysis for path determination in network simulation using software defined network
Authors: Ritzkal Ritzkal , Suhadi Suhadi , Amalia Rizky , Afrianto Yuggo , Triawan Anggra , Syafrial Syafrial , Fatimah Fety
Published: March 2023

Software defined network (SDN) is a new approach concept for planning, developing, and operating computer networks. Routing is the process of selecting paths on a network system to send or forward packets to the destination network. This study aims to obtain the results of the calculation analysis using the k-nearest neighbor (k-NN) method as the implementation of the recommendations. The results of the analysis use a mesh topology design approach with predicted values of throughput, jitter, delay, and packet loss. This value is used as a recommendation to the network manager to determine the best path. The best path selection from the analysis results is i) path-1 (very good) which includes switch 1, switch 2, and switch 4; ii) path-2 (good) to switch 1, switch 3 and switch 4 switch 4; iii) channel-3 (moderate) through switch 1, switch 2, switch 3 and switch 4; and iv) channel-4 (bad) through switch 1, switch 3, switch 2, and switch 4. While the calculation using the confusion matrix is accuracy=72.31%, precision=96.08% and recall=87.84%.
Interleaved boost converter voltage regulation using hybrid ANFIS-PID controller for off-grid microgrid
Authors: Aloo Linus Alwal , Kihato Peter Kamita , Kamau Stanley Irungu , Orenge Roy Sam
Published: March 2023

The utilization of a microgrid with a photovoltaic (PV) and wind generation system presents a challenge due to their voltage and power output variations. This problem is majorly addressed within the converter section of the microgrid using maximum power point tracking (MPPT) algorithms and voltage regulation strategies. This paper presents an interleaved boost converter (IBC) modeling and voltage control using a hybrid adaptive neuro-fuzzy inference system-proportional plus integral plus derivative (ANFIS-PID) controller for an off-grid microgrid. The modeling used the interleaving technique to obtain the microgrid’s transfer function (TF) and case study simulation models within MATLAB and Simulink environments. The performance of the ANFIS-PID controller, which regulates voltage in the microgrid, was compared to that of the traditional proportional integral (PI) controller. Results indicated that the hybrid ANFIS-PID controller performed better than the PI controller in terms of reduced settling time, overshoot, rise time, and the ability to address the nonlinear dynamics of the microgrid.
Medication correlation analysis for outbreak prediction
Authors: Mohibullah Md , Jahan Meskat , Muzammel Chowdhury Shahriar , Shahriar Fahim , Khan Raihan
Published: March 2023

Outbreak prediction is a way to predict the epidemic potentials of diseases using the pattern of medication sales values. Successful prediction might result in being cautious of the outbreak of diseases and taking necessary measures to prevent the predicted outcome. As medication sales values are too random, the analysis of medication correlation is one of the most interesting and challenging parts for the researchers. The major objective of this proposed research method is to analyze medication drug sales values for a certain period of a pharmaceutical company using statistical methods. It is also the intent of this research to make a comparative analysis of the output generated by the deep learning model with the real sales values of a month. Our method successfully predicts the outbreak potential of diseases with competent accuracy, so that we will have enough time to take precautions and prevent future pandemics through precautionary measures.
Reconfigurable graphene-based multi-input multi-output antenna design for THz applications
Authors: Abd Reem Hikmat , Abdulnabi Hussein A.
Published: March 2023

This paper presents a compact graphene-based multi-input multi-output (MIMO) antenna for wireless communications operating in frequency band (0.1-10) THz. This work has been performed with four ports microstrip antennas based on 37×88 μm² a silicon dioxide (Sio₂) substrate and copper on the ground layer, with high isolation by a series of unit cells of graphene selected between adjacent patches to reduce the transmission coefficient and antenna size. Graphene's chemical potential will change by changing the connected DC voltage, leading to bandwidth and resonant frequency variation. The simulation has a reflection coefficient is less than -10 dB at (4.5-10) THz of the frequency scale, mutual coupling (-15 dB), and the gain from (4.7-9) THz is (1.6-6.7254) dB. This paper aims to provide wideband, efficient and reconfigurable with simple graphene-based MIMO antenna for THz applications.
Handwritten signature identification based on MobileNets model and support vector machine classifier
Authors: Mohammed Israa Bashir , Mahdi Bashar Saadoon , Kadhm Mustafa Salam
Published: March 2023

Biometrics is a field that uses behavioral and biological traits to identify/verify a person. Characteristics include handwrittien signature, iris, gait, and fingerprint. Signature-based biometric systems are common due to their simple collection and non-intrusive. Identify the humans using their handwritten signatures has received an important attention in several modern crucial applications such as in automatic bank check, law-enforcements, and historical documents processing. Therefore, in this paper an accurate handwritten signatures system is proposed. The system uses a proposed preprocessing stage for the input handwritten signatures images. Besides, a new deep learning model called MobileNets, which used for classification process. Support vector machine (SVM) used as a classifier with the MobileNets inorder to get a better identifaction results. Experimental results conducted on standard CEDAR, ICDER, sigcomp handwritten signature datasets report 99.8%, 98.2%, 99.5%, identification accuracy, respectively.
New efficient fractal models for MapReduce in OpenMP parallel environment
Authors: Khudhair Muslim Mohsin , Rabee Furkan , AL_Rammahi Adil
Published: March 2023

Parallel data processing is one of the specific infrastructure applications categorized as a service provided by cloud computing. In cloud computing environments, data-intensive applications increasingly use the parallel processing paradigm known as MapReduce. MapReduce is based on a strategy called "divide and conquer," which uses ordinary 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 in the MapReduce application using proposed fractal network models. Two fractal network models are offered, and their work is compared with a well-known network model, the hypercube. The first fractal network model achieved an average speedup of 3.239 times while an efficiency ranged from 73-95%. In the second model of the network, the speedup got to 3.236 times while keeping an efficiency of 70-92%. Furthermore, the path-finding algorithm employed in the recommended fractal network models remarkably identified all paths and calculated the shortest and longest routes.
Hash algorithm comparison through a PIC32 microcontroller
Authors: Zniti Asmae , El Ouazzani Nabih
Published: March 2023

This paper presents a comparative study involving SHA-3 final round candidates along with recent versions of hash algorithms. The proposed comparison between hash functions is performed with respect to cycles per byte and memory space. Tests are also carried out on a PIC32-based application taking into account several input cases, thus resulting in a set of ranked algorithms in terms of their specified metrics. The outcome of this work represents a considerable contribution in data protection and information security in relation to various communication and transmission systems, serving as a handy reference for developers to select an appropriate hash algorithm for their particular use condition.
License plate recognition in slow motion vehicles
Authors: Mb Aljelawy Qudes , M. Salman Tariq
Published: March 2023

The recognition of license plate numbers represents one of the most efficient techniques to identify any individual vehicle. The principle of the system is that the detection of the license plate will be done with two techniques first you only look once (YOLO) and cascade classifier. Then after achive correct detection, the system will send the result (the image of the license plate) to Easy optical character recognition (OCR) library to read it and transform the image into text. In this paper, an analytical study of the surveillance system which affects by parallax due to camera movement has been done, by merging the OCR technique with the attached camera using python aided Raspberry Pi. The hardware system has been designed and implemented.
Ultra-wide band antipodal Vivaldi antenna design using target detection algorithm for detection application
Authors: Ahmed Sajjad , Joret Ariffuddin , Katiran Norshidah , Abdullah Muhammad Faiz Liew , Zakaria Zahriladha , Sulong Muhammad Suhaimi
Published: March 2023

This work presents a technique for detecting targets between two walls using ultra-wide band (UWB) modified antipodal Vivaldi antenna (MAVA). The detection system works on principle of time domain reflectrometry (TDR) using through wall imaging (TWI). This technique utilized a vector network analyzer (VNA) to produced short and small pluses to irradiate through an antenna array system onto the wall under study. The purposed detection system operated in UWB frequency spectrum (3.1 GHz to 10.6 GHz). Furthermore, an algorithm for hidden target detection has been developed. The results of the simulation of the designed antenna revealed a significant level of penetration, demonstrating a smart advancement in detecting and imaging system, to locate hidden metallic targets with good accuracy. A signal processing technique have been employed to improve the resolution of the target image. Using computer simulation technology (CST) software, the development and optimization process of an antenna is carried out, and the parametric performance of return loss, directivity and radiation pattern is evaluated.
Enhanced and authenticated cipher block chaining mode
Authors: Alslman Yasmeen Shaher , Ahmad Ashraf , AbuHour Yousef
Published: March 2023

Due to the increased attacks on different applications, data security has become crucial. Many modes can be used to operate the advanced encryption standard (AES), some of which provide integrity, and some outperform other modes in security and simplicity. In this paper, the chain block cipher (CBC) mode has been modified to provide more security to the encrypted data by making it robust against the bit-flipping attack and adding an integrity approach using the keyedhash function. In addition, using the keyd-hash function increases the number of keys needed in CBC-AES to two keys, and this can make the proposed model more secure against bruteforce attacks and Grover’s quantum search algorithm.
Design and manufacture control system for water quality based on IoT technology for aquaculture in the Vietnam
Authors: Chuyen Tran Duc , Nguyen Dien Duc , Cuong Nguyen Cao , Thong Vu Viet
Published: March 2023

In this paper, presents solutions to apply internet of things (IoT) technology in the field of high-tech agriculture and aquaculture in coastal areas of Vietnam, which is currently a new problem. The system includes an application on a smartphone; access parameters via the web, a computer and an IoT control circuit capable of automatically drawing electricity from the solar panel to the energy storage to serve as a source of power for devices (monitoring cabinets). The product has the function of monitoring: water environmental indicators in shrimp ponds (temperature, pH, dissolved oxygen (DO), salinity, redox index at the bottom of oxygen reduction potential (ORP)), on the website 24/24h, and controllable. Automatic control of pump system and DO generator with Inverter technology. The research results in this paper have brought high economic benefits with an automatic water quality control system to improve the productivity and quality of shrimp farming in practice for people in the aquaculture area in Bach Long commune, Giao Thuy district, Nam Dinh province, Vietnam.
SiulMalaya: an annotated bird audio dataset of Malaysia lowland forest birds for passive acoustic monitoring
Authors: Jamil Nursuriati , Norali Ahmad Nazem , Ramli Muhammad Izzad , Mohd Kharip Shah Ahmad Khusaini , Mamat Ismail
Published: March 2023

The laborious point count method of conducting bird surveys is still a common practice in Malaysia. An alternative method known as passive acoustic monitoring (PAM) is deployed in many countries by placing sound recorders at surveying sites to collect bird sounds. Studies revealed that the number of bird densities counted by human observers was agreeable with those obtained using PAM. However, one of the most essential gaps in conducting PAM is the lack of expert-verified bird-call databases. Therefore, the aim of this study is to construct the first annotated Malaysia lowland forest bird sounds called SiulMalaya to be used as ground-truth datasets for PAM-related activities. The raw bird sounds dataset was downloaded from Macaulay Library using the eBird platform. Data pre-processing was done to produce annotated audio tracks that can be used as training datasets for bird classification. SiulMalaya dataset was further validated by two bird experts from the Department of Wildlife and National Parks, Malaysia. A bird identification experiment was carried out to assess and validate SiulMalaya dataset using a convolutional neural network (CNN) learning model. Even though the accuracy of bird identification is slightly above 50%, the annotated dataset is shown to be viable for PAM-related operations.
Aspects in Formulating Mathematical Model of Wind Turbine
Authors: Ahmed Waleed Khalil
Published: March 2023

The present paper explores the mathematical molding of the wind turbine and its influence on the subsequent stages. Specifically, the paper investigate the modeling of gear train of the wind turbine and distinguishes the difference in the approaches usually used to establish the mathematical model which is later has a significant impact on the design, characteristic and performance of the modeled system. Mainly two commonly used approached for the gear train systems are analyzed and discussed. The main well know mechanisms are investigated in term of the most proposed assumptions to deal with the damping, shaft stiffness and inertia effect of the gear. This paper elucidates these concerns.
Load Frequency Control in Four Area Power Systems Using Fuzzy Logic PI Controller
Authors: Narasimha Raja Ch. Varaha
Published: March 2023

This paper presents a load frequency control in fourarea power systems using fuzzy gain scheduling of PI controlleris realized. The system simulation is realized by using Matlab/Simulink software. System dynamic performance is observed forconventional PI, fuzzy PI and fuzzy logic controllers.
Semantic Constraints Satisfaction Based Improved Quality of Ontology Alignment
Authors: Fakhar Fatemeh
Published: March 2023

Development of informative and telecommunication technologies have caused to create much dissimilar information. As well with growing different information resources in ontology designs, the importance of management these dissimilar resources has increased. In spite of most matchers use diverse measures for discovery the mappings, some semantic inconsistencies in final alignment are unavoidable. So it is essential to enhance a post-processing phase to training error patterns in the final alignment. The impartial of this research was refining the ontology semantic constraints over defining semantic constraints by a different measure for suitable weighting to the constraints. The outcomes indicated that the standard evaluation measures better in the suggestive method and comparing with other top ranked matchers the used method can create enhanced outcomes.
Off-Grid Energy Technologies used in Rural Areas of India
Authors: Arora Krishan , Singh Virdi Amardeep
Published: March 2023

Energy scenario in India is changing with a greater pace. Growth rate of villages has increased, likewise their energy demand. With the awareness of the decreasing natural resources, non conventional energy resources are gaining lots of interest in sparsely separated areas. The rural areas of India are having the huge scarcity of energy because of limited energy resources and Grid connectivity is not feasible due to economic factors and geographical situations. So we require to establish the off grid system for the benefit of the mass. Off-grid System’s commissioning and operation done as indigenous unit, and free from grid related problems like frequency and voltage regulations and they provides flexible operation because their emphasis is on extraction of energy and conversion into useful work. This paper discusses the potential use of off-grid energy technologies as an alternative for grid extension. Off-grid Energy systems provide the solutions to the basic energy needs in the rural areas of India. These indigenously build plants are not connected to any electrical utility and can be connected with the micro grid for the better reliable operation. Due to small size their demand and load management would be easy. Off-grid system utilizes the solar thermal radiation, wind energy, geothermal energy, tidal wave, Biomass etc. There is numerous numbers of applications where we can use this energy and decrease the dependence on conventional grid.
Design and Development of an Automated Multi Axis Solar Tracker Using PLC
Authors: Venkata Santhosh Krishna , Rajshekar J S
Published: March 2023

Design of a two dimensional automated solar tracking system is discussed in this paper. The objectives of the proposed work are to design an automated tracking technique using Light Dependent Resistance (LDR), and solar panel power output to position the solar panel to absorb maximum energy. For positioning the solar panel two stepper motors are used, each for positioning in a plane. These stepper motors were driven by a Programmable Logic Controller (PLC).  The controller is designed using wonderware software considering the inputs from LDR Sensor and solar panel output to drive the stepper motor connected to solar panels. Then the whole program is implemented with the help of PLC. The system was tested on a real time and results showed the proposed technique had improved the efficiency of solar panel by an amount of 25%.
Numerical Study of CNT Micro Fin Array for Cooling Application
Authors: Nabizadeh Sajjad , Sheikholeslami T. Fanaei , Behzadmehr Amin
Published: March 2023

Heat removing from a microelectronic chip packaging has grand effect on performance and durability of the chip. Today’s microchips with high power densities would require efficient methods of cooling. Recently, vertical alignment CNTs, due to their superior thermal, electrical and mechanical properties, was suggested as an effective micro cooler on the level of modern electronics demands. In this paper, the cooling performance of the CNT fin structures is studied numerically. Flow of air was considered as the working fluid flow. CFD simulations have been carried out for a series of CNT micro-fin cooling architectures based on one and two dimensional fin array models. The modeling results indicate that fluid speed is the key factor in heat transfer capacity of the device. Also, the results of 2D carbon nanotube fin array model show more precise and greater thermal performance than that of 1D model. Finally, the examination of pressure drop between inlet and outlet of the cooling device is presented as an important factor which could limit the fluid speed and fin height effect on heat sink performance also investigated.
Using HBMO Algorithm to Optimal Sizing & Sitting of Distributed Generation in Power System
Authors: Ghadimi Noradin
Published: March 2023

This paper analyzes of HBMO placement method efficiency in comparison with PSO and GA in order to sizing and sitting of distributed generation in distribution power system. These algorithms for optimization in this paper is tested on IEEE 33 bus reconfigured test system. The proposed objective function considers active power losses and the voltage profile in nominal load of system. In order to use of optimization algorithms, at first, placement problem is written as an optimization problem which includes the objective function and constraints, and then to achieve the most desirable results, Optimization methods is applied to solve the problem. High performance of the proposed algorithm in mention system is verified by simulations in MATLAB software and in order to illustrate of feasibility of proposed method will accomplish.
Sliding Mode Control of Buck Converter
Authors: Kiran Nagulapati
Published: March 2023

DC-DC converters are used to convert DC voltage from one level to other. These converters are drastically used in industry as well as in research. One of the main limitations of these converters is unregulated supply of voltage and current. To overcome these problems there are various control techniques. This paper presents two such methods. This paper compares dynamic performance of buck Converter using PID controller and Sliding mode controller. Simulation of PI and Sliding mode control of Buck Converter is carried out in MATLAB SIMULINK.
Diferenças no consumo alimentar da população brasileira por raça/cor da pele em 2017–2018
Authors: Costa Janaína Calu , Jesus Amanda Cristina da Silva de , Jesus Juliana Giaj Levra de , Madruga Mariana Ferreira , Souza Thays Nascimento , Louzada Maria Laura da Costa
Published: March 2023

OBJETIVO: Avaliar o consumo alimentar no Brasil por raça/cor da pele da população. MÉTODOS: Foram analisados dados de consumo alimentar da Pesquisa de Orçamentos Familiares 2017–2018. Alimentos e preparações culinárias foram agrupados em 31 itens, compondo três grupos principais, definidos por características do processamento industrial: 1 – in natura/minimamente processados, 2 – processados e 3 – ultraprocessados. O percentual de calorias de cada grupo foi estimado por categorias de raça/cor da pele – branca, preta, parda, indígena e amarela –, utilizando-se regressão linear bruta e ajustada para sexo, idade, escolaridade, renda, macrorregião e área. RESULTADOS: Nas análises brutas, o consumo de alimentos in natura/minimamente processados foi menor para amarelos [66,0% (Intervalo de Confiança 95% 62,4–69,6)] e brancos [66,6% (IC95% 66,1–67,1)] que para pretos [69,8% (IC95% 68,9–70,8)] e pardos [70,2% (IC95% 69,7–70,7)]. Amarelos consumiram menos alimentos processados, com 9,2% das calorias (IC95% 7,2–11,1) enquanto os demais consumiram aproximadamente 13%. Ultraprocessados foram menos consumidos por pretos [16,6% (IC95% 15,6–17,6)] e pardos [16,6% (IC95% 16,2–17,1)], e o maior consumo ocorreu entre brancos [20,1% (IC95% 19,6–20,6)] e amarelos [24,5% (IC95% 20,0–29,1)]. O ajuste dos modelos reduziu a magnitude das diferenças entre as categorias de raça/cor da pele. A diferença entre pretos e pardos em relação aos brancos diminuiu, de três pontos percentuais (pp), para 1,2 pp no consumo de alimentos in natura/minimamente processados e as maiores diferenças remanescentes foram no consumo de arroz e feijão, com maior percentual na alimentação de pretos e pardos. A participação de alimentos processados permaneceu aproximadamente 4 pp menor para amarelos. O consumo de ultraprocessados diminuiu aproximadamente 2 pp para brancos e amarelos; por outro lado, aumentou 1 pp no consumo de pretos, pardos e indígenas. CONCLUSÃO: Diferenças no consumo alimentar segundo raça/cor da pele foram encontradas e são influenciadas por condições socioeconômicas e demográficas.