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Development of Framework for ACI-Powered Human Resource Recruitment Assistant

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Management Studies 2024年第3期12卷 182-187页

作者： md Jawadur rahman Gabriele M.Murry Stephanie Schmitt-Rüth OTH Amberg-Weiden AmbergGermany

The landscape of human resource management within large enterprises necessitates efficient and unbiased recruitment practices to ensure organisational effectiveness and foster diversity(Ayoko&Fujimoto,2023).Traditional hiring processes often create biases,which cause additional challenges in achieving proper objectives(Bogen,2021).According to Workable(***),the average time to fill a job requisition is 41 days(Howden,2023).This paper proposes a framework for the development and implementation of an Artificially Capable Intelligent(ACI)-powered Human Resource(HR)Assistant for large enterprises(possibly more than 300 employees)to eliminate these unnecessary challenges caused by biases in hiring practices,therefore directly addressing fair and just participation in society and the world of *** framework integrates ACI technologies,particularly candidate identification,to revolutionise HR *** leveraging ACI algorithms,the proposed hyper-realistic assistant aims to revolutionise the recruitment *** will significantly reduce the average time to fill job ***,the ACI-powered system is designed to mitigate biases inherent in traditional hiring practices,thus fostering a fair and inclusive environment for all candidates in the shortest possible time *** paper includes the key components and working processes of the ACI-powered HR Assistant *** a comprehensive theoretical analysis,the paper investigates the system’s working process and how the framework aligns with the goal of promoting a fair and participatory environment in the world of ***,the proposed framework represents a main step towards enhancing organisational effectiveness,fostering diversity,and advancing equitable recruitment practices in the futuristic workplace.

关键词： artificial capable intelligence human resource

Mechanical and Electrical Properties of Some Sn-Zn Based Lead-Free Quinary Alloys

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Materials Sciences and Applications 2024年第7期15卷 213-227页

作者： Shihab Uddin md. Abdul Gafur Suraya Sabrin Soshi Mohammad Obaidur rahman Department of Physics Jahangirnagar University Savar Dhaka Bangladesh Pilot Plant and Process Development Centre Dhaka Bangladesh Department of Mechanical Engineering Ahsanullah University of Science and Technology Tejgaon Dhaka Bangladesh

Although there are many lead-free soldering alloys on the market, none of them have ideal qualities. The researchers are combining binary alloys with a variety of additional materials to create the soldering alloys’ features. The eutectic Sn-9Zn alloy is among them. This paper investigated the mechanical and electrical properties of Sn-9Zn-x (Ag, Cu, Sb);{x = 0.2, 0.4, and 0.6} lead-free solder alloys. The mechanical properties such as elastic modulus, ultimate tensile strength (UTS), yield strength (YS), and ductility were examined at the strain rates in a range from 4.17 10−3 s−1 to 208.5 10−3 s−1 at room temperature. It is found that increasing the content of the alloying elements and strain rate increases the elastic modulus, ultimate tensile strength, and yield strength while the ductility decreases. The electrical conductivity of the alloys is found to be a little smaller than that of the Sn-9Zn eutectic alloy.

关键词： Lead-Free Solder Strain Rate Ultimate Tensile Strength Ductility Electrical Conductivity

Credit Card Fraud Detection Using Machine Learning Techniques

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Journal of Computer and Communications 2024年第6期12卷 1-11页

作者： Ananya Sarker Must. Asma Yasmin md. Atikur rahman md. Harun Or Rashid Bristi Rani Roy Department of Computer Science and Engineering Bangladesh Army University of Engineering & Technology (BAUET) Natore Bangladesh

Credit card companies must be able to identify fraudulent credit card transactions so that clients are not charged for items they did not purchase. Previously, many machine learning approaches and classifiers were used to detect fraudulent transactions. However, because fraud patterns are always changing, it is becoming increasingly vital to investigate new frauds and develop the model based on the new patterns. The purpose of this research is to create a machine learning classifier that not only detects fraud but also detects legitimate transactions. As a result, the model should have excellent accuracy, precision, recall, and f1-score. As a result, we began with a large dataset in this study and used four machine learning classifiers: Support Vector Machine (SVM), Decision Tree, Naïve Bayes, and Random Forest. The random forest classifier scored 99.96% overall accuracy with the best precision, recall, f1-score, and Matthews correlation coefficient in the experiments.

关键词： Support Vector Machine Decision Tree Nave Bayes Random Forest Matthews Correlation

Assessment of Physico-Chemical and Microbial Quality of Sugarcane Juice Sold by Street Vendors in Three Regions of Bangladesh

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Food and Nutrition Sciences 2024年第4期15卷 263-276页

作者： Nargis Akter Khan md. Murtaja Reza Linkon Munni Akter md. Alamgir Hossain md. Mahbubur rahman Tayeba Khan md. Abdul Alim md. Esrafil Department of Food Technology and Nutritional Science Mawlana Bhashani Science and Technology University Tangail Bangladesh Department of Biotechnology and Genetic Engineering Mawlana Bhashani Science and Technology University Tangail Bangladesh

Sugar cane juice is a popular refreshing drink in most part of Bangladesh. It has great taste and health benefits;also it is available most of the public places at reasonable prices which consumed by road side customers including general public, shopping personals, tourists, students. In our country, street vendors crushing sugarcane between roller crusher and sold without any heat treatment or preservative, also served with or without added ice and lemon juice. The study aimed to identify and compare the physico-chemical and microbial quality of sugarcane juice. The chemical qualities of juices including moisture, PH, ash, total soluble solid, total sugar, reducing sugar and titrable acidity were found slightly different in Mymensingh, Gazipur and Narayangonj areas. The highest and lowest value of moisture, ash, PH, total soluble solids, total sugar, reducing sugar and titrable acidity were found in 84.33% - 79.26% (Gazipur-Mymensingh), 0.57% - 0.04% (Mymensingh-Gazipur), 5.9 - 2.9 (Gazipur-Narayangonj), 17.48% - 4.98% (Mymensingh-Narayangonj), 21.9% - 6.56% (Mymensingh-Gazipur), 3.7 - 2.1 (Gazipur-Mymensingh) and 0.523% - 0.007% (Narayangonj-Gazipur) respectively. For microbiological analysis, the total viable count of sugar cane juice in Mymensingh, Gazipur and Narayangonj were ranged from 0.6 × 105 - 43.6 × 105 cfu/ml, 4.6 × 105 - 21.6 × 105 cfu/ml and 3.6 × 105 - 36.6 × 105 cfu/ml respectively, where the permitted value is 1.0 × 104 cfu/ml, whereas the total coliform count was ranged from 0.4 × 105 - 6.4 × 105 cfu/ml, 0.6 × 105 - 8.4 × 105 cfu/ml and 0.00 - 8.4 × 105 cfu/ml, where the permitted value is 100 cfu/ml and total fungal count was ranged from 5.5 × 105 - 56.5 × 105 cfu/ml, 21.5 × 105 - 54.5 × 105 cfu/ml and 32.5 × 105 - 68.5 × 105 cfu/

关键词： Sugarcane Street Vendors Microbial Quality Reducing Sugar

Predicting the Stitch Density of Finished Fabrics Using Weft Blended Grey Knit Fabrics

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Journal of Textile Science and Technology 2024年第3期10卷 51-63页

作者： Kazi md. Elias Mohammad Obaidur rahman H. M. Zakir Hossain Department of Physics Jahangirnagar University Savar Bangladesh Jute Textile Wing Bangladesh Jute Research Institute Dhaka Bangladesh

Stitch density is one of the critical quality parameters of knit fabrics. This parameter is closely related to other physical quality parameters like fabric weight, fabric tightness factor, fiber types, blend ratio, yarn diameter and linear density, and fabric structure. Selecting stitch density (wales per inch, course per inch) is essential to getting the appropriate fabric weight and desired quality. Usually, no rules or assumptions exist to get the desired stitch density in the finished fabric stage. Fifteen types of blended knit fabrics were prepared to conduct the study. The varying percentages of cotton, polyester, and elastane are incorporated in the blends. Regression analysis and regression ANOVA tests were done to predict the stitch density of finished fabrics. A suitable regression equation is established to get the desired results. The study also found that the stitch density value in the finished stage fabric decreases by approximately 15% compared to the stitch density in the grey fabric stage. This study will help the fabric manufacturers get the finished fabric stitch density in advance by utilizing the grey fabric stitch density data set. The author expects this research to benefit the knitting and dyeing industry, new researchers, and advanced researchers.

关键词： Wales per Inch Course per Inch Stitch Density Blended Knit Fabric

Effect of Exchange-Correlation Functional on the Structural, Mechanical, and Optoelectronic Properties of Orthorhombic RbSrBr3 Perovskite

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Materials Sciences and Applications 2024年第6期15卷 137-154页

作者： Fatema Najrin Rabeya Bakar Sarna md. Alamin Sarker Budrun Neher md. Mahbubur rahman Bhuiyan Farid Ahmed Department of Physics Jahangirnagar University Dhaka Bangladesh Department of Electrical and Electronics Engineering Green University of Bangladesh Purbachal American City Kanchan Rupganj Narayanganj-1461 Dhaka Bangladesh

In the present study, the effect of the exchange-correlation functional on the structural, mechanical, and optoelectronic properties of orthorhombic RbSrBr3 perovskite has been investigated using various functionals in Density Functional Theory (DFT) with the CASTEP code. The optimized lattice parameters are quite similar for all the functionals. The electronic properties have shown that RbSrBr3 perovskite is a wide direct band gap compound with a band gap energy ranging from 4.296 eV to 4.494 eV for all the functionals. The mechanical parameters like elastic constants, Young’s modulus, Shear modulus, Poisson’s ratio, Pugh’s ratio, and an anisotropic factor reveal that the RbSrBr3 perovskite has ductile behavior and an anisotropic nature which signifies the mechanical stability of the compound. The Debye temperature might withstand lattice vibration heat. High absorption coefficient (>104 cm−1), high optical conductivity, and very low reflectivity have been found in the RbSrBr3 perovskite for all functions. The computed findings on the RbSrBr3 perovskite suggested that the presented studied material is potentially applicable for photodetector and optoelectronic devices.

关键词： Density Functional Theory Mechanical Properties Photodetector Ductility Anisotropic Factor

Phytochemical Screening and Evaluation of Pharmacological Potential of Baliospermum solanifolium Leaf Extract

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Clinical Complementary Medicine and Pharmacology 2024年第1期4卷 69-75页

作者： Amit Mazumder Rabindra Nath Acharyya Milton Kumar Kundu Pritam Kundu md.Amirul Islam md.Mustafizur rahman Pharmacy Discipline Khulna UniversityKhulna-9208Bangladesh

Background:Baliospermum solanifolium is a traditional medicinal plant,locally known as“dantigaacha”from Eu-phorbiaceae family,and has been used in different diseases treatments likes helminthiasis,skin diseases,diabetes,snake-bite,and ***:Depending on the traditional uses of *** and the lack of scientific works,we aimed to conduct some pharmacological tests on its ***:Active constituents of *** were assessed by qualitative ***(2,2-diphenyl-1-picrylhydrazyl)was used for free radical scavenging *** change and mortality rate were used as indicators to assess the toxicity of *** antidiabetic potential was evaluated by oral glucose toler-ance test(OGTT)and alpha-glucosidase enzyme inhibitory *** antidiarrheal activity,castor oil-induced mice were *** test was carried out by disk diffusion assay and MIC ***,analgesic activity was done by acetic acid-induced writhing ***:*** contains alkaloids,carbohydrates,glycosides,flavonoids,tannis,phenolics *** toxicity test ensured the safety of the *** DPPH,the extract showed antioxidant activity with an IC50(con-centration needed to scavenge 50%DPPH)value of 61.65μg/*** phenolic,flavonoid and tannin contents were determined as 124 mg GAE/g,440 mg QE/g and 344 mg GAE/g dried extract,*** OGTT,the ex-tract reduced the blood glucose level *** the alpha-glucosidase inhibitory activity,the plant showed a concentration-dependent reduction of the enzyme at IC50 of 8.53 mg/*** the antidiarrheal test,*** inhibit defecation 30.69%and 53.41%at dose 250 mg/kg and 500 mg/kg,*** extract also showed antibacterial activity against four bacterial strains in the disk diffusion method and minimum inhibitory concen-tration(MIC)values were 62.5μg/mL,62.5μg/mL,125μg/mL and 62.5μg/mL against four bacterial strains,*** an

关键词： Baliospermum solanifolium Antioxidant Antidiabetic Antidiarrheal Antibacterial Analgesic

Impact of non-alcoholic fatty liver disease on coronavirus disease 2019: A systematic review

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World Journal of Hepatology 2024年第8期16卷 1185-1198页

作者： Abdul Moeed Muhammad Omar Larik Muhammad Ahmed Ali Fahim Hafsah Alim Ur rahman Lubna Najmi Mah I Kan Changez Muhammad Moiz Javed md Al Hasibuzzaman Department of Internal Medicine Dow University of Health SciencesKarachi 74200SindhPakistan Department of Internal Medicine Dow International Medical CollegeKarachi 74200SindhPakistan Department of Internal Medicine Ziauddin UniversityKarachi 75000SindhPakistan Department of Research Yale UniversityNew Haven 06520CTUnited States Department of Internal Medicine King Edward Medical UniversityLahore 54000PunjabPakistan Institute of Nutrition and Food Science University of DhakaDhaka 1000Bangladesh Department of Medicine The Affiliated Hospital of Medical School of Ningbo UniversityNingbo 315211Zhejiang ProvinceChina

BACKGROUND Many studies have revealed a link between non-alcoholic fatty liver disease(NA-FLD)and coronavirus disease 2019(COVID-19),making understanding the relationship between these two conditions an absolute *** To provide a qualitative synthesis on the currently present data evaluating COVID-19 and *** This systematic review was conducted in accordance with the guidelines pro-vided by preferred reporting items for systematic reviews and meta-analyses and the questionnaire utilized the population,intervention,comparison,and outcome *** search strategy was run on three separate databases,PubMed/MEDLINE,Scopus,and Cochrane Central,which were systematically searched from inception until March 2024 to select all relevant *** addition,***,***,and Google Scholar were searched to identify grey *** After retrieval of 11 studies,a total of 39282 patients data were *** was found in 11.5%and 9.4%of people in NAFLD and non-NAFLD *** all,23.2%of NAFLD patients and 22%of non-NAFLD admissions diagnosed with COVID-19 were admitted to the intensive care unit,with days of stay *** support ranged from 5%to 40.5%in the NAFLD cohort and from 3.1%to 20%in the non-NAFLD *** incidence of acute liver injury showed *** improvement on days 7 and 14 between the two classifications was *** stay ranged from 9.6 days to 18.8 days and 7.3 days to 16.4 days in the aforementioned cohorts respectively,with 73.3%and 76.3%of patients being *** rates *** Clinical outcomes except mortality consistently showed a worsening trend in patients with NAFLD and concomitant *** research in conducting prospective longitudinal studies is essential for a more powerful conclusion.

关键词： Non-alcoholic fatty liver disease Coronavirus disease 2019 Mechanical ventilation Intensive care unit Acute liver injury

Lexicon and Deep Learning-Based Approaches in Sentiment Analysis on Short Texts

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Journal of Computer and Communications 2024年第1期12卷 11-34页

作者： Taminul Islam md. Alif Sheakh md. Rezwane Sadik Mst. Sazia Tahosin md. Musfiqur rahman Foysal Jannatul Ferdush Mahbuba Begum Department of Computer Science and Engineering Daffodil International University Dhaka Bangladesh Department of Computer Science Southern Illinois University Carbondale IL USA Department of Economics & Decision Sciences University of South Dakota Vermillion SD USA Department of Computer Science and Engineering Jashore University of Science and Technology Jashore Bangladesh Department of Computer Science and Engineering Mawlana Bhashani Science and Technology University Tangail Bangladesh

Social media is an essential component of our personal and professional lives. We use it extensively to share various things, including our opinions on daily topics and feelings about different subjects. This sharing of posts provides insights into someone’s current emotions. In artificial intelligence (AI) and deep learning (DL), researchers emphasize opinion mining and analysis of sentiment, particularly on social media platforms such as Twitter (currently known as X), which has a global user base. This research work revolves explicitly around a comparison between two popular approaches: Lexicon-based and Deep learning-based Approaches. To conduct this study, this study has used a Twitter dataset called sentiment140, which contains over 1.5 million data points. The primary focus was the Long Short-Term Memory (LSTM) deep learning sequence model. In the beginning, we used particular techniques to preprocess the data. The dataset is divided into training and test data. We evaluated the performance of our model using the test data. Simultaneously, we have applied the lexicon-based approach to the same test data and recorded the outputs. Finally, we compared the two approaches by creating confusion matrices based on their respective outputs. This allows us to assess their precision, recall, and F1-Score, enabling us to determine which approach yields better accuracy. This research achieved 98% model accuracy for deep learning algorithms and 95% model accuracy for the lexicon-based approach.

关键词： Opinion Mining Lexicon Analysis Twitter Data LSTM Machine Learning