bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative Study of Suspended Sediment Load Prediction Models Based on Artificial Intelligence Methods
Authors: Boye Cynthia Borkai , Boye Paul , Ziggah Yao Yevenyo
Published: June 2023

Quantification of suspended load sediment is crucial for maintaining the ecosystem and quality of water/river bodies that serve as the habitat for many living organisms. Because the influencing factors are nonlinearly related to the suspended load sediment, it is a challenge to apply linear statistical models to predict accurately. To address such a problem, this study appliedartificial intelligence methods to simulate and predict suspended load sediment. The artificial intelligence methods are robust andcan handle adequately issues related to nonlinearity in modeling. In the present study, four artificial intelligence methods were developed to predict suspended sediment load distribution. The methods include a backpropagation neural network, group method of data handling, least squares support vector machine, and generalised regression neural network. In developing the respective models, drainage areas, river slopes, and length of rivers served as predictor variables while suspended sediment load was the response variable. The models were evaluated using the metrics of root mean square error, percentage root mean square error, uncertainty at 95%, root mean square error observations standard deviation ratio, and Legates and McCabe index. According to the results, the generalised regression neural network model achieved higher prediction accuracy than the other competing methods. The performance of the generalised regression neural network model can be attributed to its ability to calibrate and generalise appropriately to the training and testing data set. Hence, in practice, the generalised regression neural network model is proposed for suspended sediment load prediction for the study area which can be useful to policymakers and managers of water resources.
 
Received: 6 March 2023 | Revised: 11 May 2023 | Accepted: 26 May 2023
 
Conflicts of Interest
The authors declare that they have no conflicts of interest to this work.
 
Data Availability Statement
Data available on request from the corresponding author upon reasonable request.
Covid-19 associated coagulopathy (CAC): Global research output, 2020-2022
Authors: Gupta B.M. , Kappi Mallikarjun M. , Walke Rajpal , Bansal Madhu , Mandal Aurum
Published: June 2023

Objective. This study examined the Covid-19 associated coagulopathy (CAC) publication and citation trends, focusing on the top authors, countries, organizations, journals, collaboration, subject areas, keywords, and high-cited articles. Design/Methodology/Approach. Publications data on Covid-19 associated coagulopathy (CAC) were identified and extracted from the Scopus database. Data analysis has been performed using VOS viewer software, Biblioshiny, and MS Excel Software. Results/Discussion. The study identified 1740 articles on Covid-19 associated coagulopathy from the Scopus database, which received 47,502 citations, averaging 27.3 citations per paper. In all, 905 authors from 601 organizations originating in 96 countries participated in research and published in 776 journals. United States, Italy, and China contributed the most publications (498, 258, and 164 papers). While China (73.43 and 2.69), France (57.60 and 2.11,) and Germany (50.13 and 1.84) registered the highest citation impact by CPP and RCI. Harvard Medical School, USA, Huazhong University of S&T, China, and Tongji Medical College, China, lead with most of the publications (4,4, 41, and 39 papers). In contrast, Tongji Medical College, China (198.31 and 7.26), Huazhong University of S&T, China (198.15 and 7.26), and University College Hospital NHS Foundation Trust, U.K (129.23 and 4.73) lead in citation impact. J.H. Levy, T. Iba and M. Levy contributed to most of the publications (27, 25, and 20), while N. Tag (804.75 and 29.48), A. Tripodi (157.83 and 5.78), and J. Thachil (154.17 and 5.65) registered the highest citation impact by CPP and RCI. Journal of Thrombosis and Haemostasis, Journal of Thrombosis and Thrombolysis, and Thrombosis Research were the most productive ones (with 55, 51, and 46 publications). At the same time, Medical Hypotheses (1222), Blood (355.71) and Thrombosis Journal (233.86) were the most impactful journals. The top 9 keywords were Covid-19 (1681 occurrences), Blood Clotting (952), D Dimer (652), C (628), Coagulopathy (628), Thrombosis (584), blood (506), Anticoagulants (499), Blood Coagulation (426) and Fibrinogen (376). Conclusions. Global research on Covid-19 associated coagulopathy since the pandemic was considered for scientometric assessment for the first time, combining the productivity and citation measures to present an overall picture of the literature in this area. Such an analysis will provide scholars and policy-makers with a meaningful reference for further exploration of topical issues and research trends in the field.
Penguatan Koperasi Siswa SMKS Kharisma Tangerang Dalam Rangka Optimalisasi Kemandirian Ekonomi
Authors: Effendi Bahtiar
Published: June 2023

Pengabdian Kepada Masyarakat ini dilakukan melalui Kerjasama dengan Tentara Manunggal Membangun Desa (TMMD) dalam kegiatan nasional untuk mempercepat pembangunan desa dengan kegiatan fisik dan non fisik, yang melibatkan TNI, Polri, Kementerian, Lembaga Non Kementerian, Pemerintah Daerah dan seluruh lapisan masyarakat. Sesuai dengan konsep RBTL (Research Based Teaching and Learning) perkuliahan akuntansi keuangan melalui penerapan pelatihan Koperasi di beberapa Sekolah Menengah Atas diantaranya SMK Kesehatan Kharisma, Panongan. Materi yang disampaikan dalam pelatihan ini disesuaikan dengan perkembangan kondisi sekolah yang bersangkutan. Tujuannya adalah untuk meningkatkan pemahaman siswa/i terkait praktik pencatatan pembukuan Koperasi serta untuk menumbuhkan kesiapan dan motivasi siswa/i menerapkan Koperasi di kegiatan unit sekolah. Melalui post test yang dilakukan, ditemukan hasil sebanyak 87% siswa/i mampu dan mengerti menyelesaikan soal latihan terkait konsep dasar Koperasi secara “baik” dan 13% siswa/i mampu dan mengerti menyelesaikan soal latihan terkait konsep dasar Koperasi secara “cukup”. Selain itu, terdapat peningkatan kepercayaan diri siswa/i untuk mengembangkan Koperasi dalam kegiatan ekstrakurikuler sekolah. Informasi ini didapatkan dari hasil monitoring pasca pelatihan yang telah dilakukan.
PKM Penerapan Spesifikasi Kebutuhan Perangkat Lunak (SKPL) untuk Sistem Informasi Laboratorium
Authors: Syaefudin Achmad , Hendriyati Penny , Yusti Annasya Bela
Published: June 2023

Dokumen SKPL ini dibagi menjadi tiga bagian utama. Bagian utama berisi penjelasan tentang dokumen SKPL yang mencakup tujuan pembuatan dokumen ini, lingkup masalah yang diselesaikan oleh perangkat lunak yang dikembangkan, definisi, referensi, dan deskripsi umum. Bagian kedua berisi penjelasan secara umum mengenai perangkat lunak yang akan dikembangkan meliputi fungsi dari perangkat lunak, karakteristik pengguna, batasan, dan asumsi yang diambil dalam pengembangan perangkat lunak. Bagian ketiga berisi uraian kebutuhan perangkat lunak secara lebih rinci.
An Analytical Study of Applications of Artificial Intelligence on Banking Practices
Authors: M. Jomon Jose , Aithal P. S.
Published: June 2023

Purpose: Artificial intelligence (AI) has the potential to enhance the creativity, adaptability, and flexibility of enterprises beyond their current capabilities. Many businesses are already leveraging AI to increase productivity and competitiveness, as well as drive digital transformation in various industries. In India, AI is assisting banks in upgrading their operations across the board, from traditional to digital banking practices. This study is based on the application of AI on various virtual assistants provided by public sector banks in Kerala as well as the recent advancements and emergence of virtual banking and modern banking trends.
Design: In this study, both descriptive and analytical research designs were employed. A standardized questionnaire was administered to 150 Bank employees to collect primary data and demographic information. To ensure the validity and reliability of the study, a pilot survey and Cronbach's Alpha test were conducted to assess the variables of measures. The collected data were analyzed using correlation analysis, multiple regression analysis, and Multicollinearity.
Findings/Results: The current research findings support the notion that artificial intelligence has a significant impact on various practices within public-sector banking. The study's results demonstrate that the independent variables, including Chatbot, Robo Advice, Predictive Analytics, Cyber security, and Credit Scoring, collectively serve as significant predictors (64%) of banking practices.
Paper Type: Descriptive and Analytical Research
Synthesis of Graphene Oxide-Coated Mesoporous Silica with Cetyltrimethylammonium Bromide (CTAB) Template for Methylene Blue Adsorption
Authors: Aisyah Amma , Azmiyawati Choiril , Darmawan Adi
Published: June 2023

The synthesis of graphene oxide-coated mesoporous silica (MS_GO) with the template surfactant (Cetyltrimethylammonium Bromide) CTAB has been carried out. The effect of combining mesoporous silica and graphene oxide was studied by knowing the bonds, functional groups and crystalline structures. Functional groups C=O and C=C were formed at wave numbers 1,722, 1,617 and 1,647 cm−1, respectively, as a characteristic of GO compounds. XRD data showed that MS_GO has a more amorphous structure than graphite and GO due to the incorporation of silica onto the graphene oxide surface. The MS_GO synthesis was also applied as an adsorbent for methylene blue dye in water. The adsorption results showed that MS_GO was more effective than pure GO. The percent adorption efficiency (R %) of MS_GO against 10 ppm methylene blue was 93.1 % while that of pure GO was 91.5 %. The addition of mesoporous silica to graphene oxide makes MS_GO adsorbent more effective in adsorption dyes than pure GO, this is supported by the larger total surface area of BET MS_GO was 161.066 m2·g−1, while that of pure GO was 103.818 m2·g−1.
HIGHLIGHTS

Preparation of graphene oxide from graphite by the modified hummer method
Mesoporous silica is synthesized with Graphene Oxide (GO) and occupies between GO layers in the GO interlayer space
CTAB is used as a template and forms pores in the synthesis of layered Mesoporous Silica-Graphene Oxide (MS_GO)
Graphene Oxide-Coated Mesoporous Silica will be applied for adsorption of methylene blue dye in water.
The adsorption efficiency (% R) of GO against methylene blue is lower than % R of MS_GO against methylene blue

GRAPHICAL ABSTRACT
Ecology of soil animals (Diplopoda class, Myriapoda group)
Authors: Kicaj Hajdar
Published: June 2023

Class Шplays an important role in natural ecosystems, because it supports biodiversity and soil stability, and a change in the number or distribution of centipede species can indicate changes in the environment, such as pollution, soil degradation, climate change, etc. The purpose of the study is to identify the existing species of soil animals of the Diplopoda class, as well as to determine environmental factors that can affect their distribution. Species’ diversity was assessed by collecting individuals and classifying them into order, family, genus, and species. Climatic factors, namely temperature and precipitation, are also determined. As a result of the study, ecological aspects of centipede development were evaluated and their distribution and dependence on environmental factors, such as climatic, edaphic, and trophic factors, were analysed. In the southern region of Albania, 22 species of the Diplopoda class of the Myriapoda group were identified, among which mainly decomposers of organic remains and phytophages. The regions of Llogara and Šhašhica were noted as the regions with the highest diversity of millipedes. In addition, it was established that the variation of species is influenced by the environment, the presence of organic substances, and climatic factors. Temperature and humidity are determining factors influencing the distribution of the Diplopoda class in different biotopes. Species that have a large regional distribution and are most widespread in time throughout the year: Pachyiulus cattarensis, found in the period June-November, Glomeris pulchra – May-July, SeptemberOctober, Pachyiulus varius – May-October. A less active period was noted for the following species: Polydesmus complanatus, Glomeris latermarginata, Typhloiulus albanichus, Pachyiulus hungaricus, Glomeris pustullata. The research, which was carried out, is of practical importance for nature conservation, as the Diplopoda class plays an important role in maintaining ecosystems and biodiversity and can be an indicator of the state of the environment
Photosynthetic productivity of sorghum (Sorghum bicolor L. (Moenh) in the conditions of the Right-Bank Forest-Steppe of Ukraine
Authors: Pravdyva Liudmyla , Zatserkovna Nataliia , Vakhniy Sergіy , Khakhula Valerii , Hornovska Svitlana
Published: June 2023

Sorghum (Sorghum bicolor L. (Moenh) is a technical, food, and fodder crop and can be used for various purposes, given its value, the acreage should be substantially expanded in Ukraine, and the elements of cultivation technology should be thoroughly examined. The purpose of the study was to determine the effect of the growth regulator on the photosynthetic productivity of sorghum in the conditions of the Right-Bank Forest-Steppe of Ukraine. The following methods were used in the study: field, measuring and weighing, mathematical, and statistical. The study was conducted in conditions of unstable moisture in the Right-Bank Forest-Steppe of Ukraine in 2016-2019. Based on the results of the study, it was determined that the use of a plant growth regulator affected photosynthetic productivity, namely, the leaf surface area, photosynthetic potential and net photosynthesis productivity. The indicators for the content of chlorophylls changed. Thus, the assimilation area of leaves reached a maximum with seed treatment and spraying of crops and amounted to 8.56 thousand m2 /ha during the tillering period, during the period of stem elongation – 29.6 thousand m2 /ha, during flowering and full ripeness – 40.32 and 4.97 thousand m2 /ha. Net photosynthetic productivity in the control was the lowest – 4.67 g/m2 , the use of a growth regulator on seeds and crops contributed to its increase by 0.27 and 0.79 g/m2 . With the treatment of seeds and crops, the net photosynthetic productivity was the highest and amounted to 6.12 g/m2 . The sum of chlorophylls a+b had the highest rates during the tasselling period and, depending on the experiment options, ranged from 4.36 to 5.35. The yield of grain and biomass also varied depending on the use of the preparation, and was the highest in the version with seed treatment and spraying of crops (7.1 and 35.9 t/ha). The close relationship between photosynthetic productivity and the yield of sorghum is also determined. The study can contribute to the widespread use of growth regulators in sorghum crops, ensure the full development of plants, and increase grain yields and biomass
Synergism of a mixture of phosphine and carbon dioxide in fumigation against bean weevils
Authors: Romanko Volodymyr , Dudynska Andreia
Published: June 2023

The study is devoted to searching for alternatives to methyl bromide – a universal fumigant restricted in use at the request of the Montreal Protocol. Purpose: to determine the synergy of a mixture of phosphine and carbon dioxide in their various concentrations and exposures during the fumigation of leguminous products against pests at high temperatures. Methods: analytical review on the subject of research, the current regulatory framework in the field of disinfection; analysis of biological features of insect pests of leguminous products; experimental – a variation of different concentrations of phosphine, duration of exposure and temperature to establish a synergy of fumigant with carbon dioxide in laboratory conditions with appropriate equipment; mathematical and statistical – using computer mathematical functions built into the Microsoft Excel program 2003. When fumigating gas mixtures against pests at the imago stage, the optimal concentration of carbon dioxide is in the range of 110-130 g/m3 (or 5.5-6.5% of the total air volume), regardless of the temperature indicator. While the optimal concentration of phosphine at low temperatures (21-22°C) is in the range of 0.57-0.82 g/m3 , at high temperatures – (31-32°C) – in the range of 0.21-0.36 g/m3 . With an increase in the duration of fumigation, not only the effectiveness of phosphine (standart) against the imago pests but also gas mixtures. In addition, the dependence of gas synergy on the duration of fumigation was established. Thus, at a temperature of 30°C, an increase in gas synergy in the mixture was observed by 4.4±0.66, 7.7±1.61, and 10.3±1.08% compared to the standard for exposure of 2, 4 and 6 hours, respectively. Temperature was the most determining factor influencing the value of the gas synergy index in the mixture of phosphine and carbon dioxide. Thus, an increase in temperature from 30°C to 32°C contributed to an increase in the gas synergy index by 9%, that is, by 2.17 times. Further establishment of lethal standards and fumigation regimes against pests, including quarantine ones, can prevent economic damage from these pests in Ukraine and will contribute to the implementation of the decisions of the Montreal Protocol aimed at protecting the environment and preventing the destruction of the ozone layer
Wastewater Assessment and Biochemical Oxygen Demand Value Prediction from Mining Operations: A Case Study
Authors: Zenati Fella , Djellali Adel , Sarker Debojit
Published: June 2023

Wastewater is a byproduct of industrial or household waste processes, and its contamination level must be determined before treatment. Discharges of liquid effluents generated by mining operations, one of the most prevalent forms of industrial waste water, pose a risk to human health and the environment. This study evaluates the physicochemical quality of industrial liquid effluent discharges from the Boukhadra mine (Algeria). Samples were collected from the washing water to identify the level of contamination of these liquid discharges and to measure physicochemical parameters such as temperature (T), hydrogen potential (pH), Electrical Conductivity (EC), Suspended Solids (SS), Chemical Oxygen Demand (COD), Biological Oxygen Demand for 5 days (BOD5), Oils and Greases (O&G), iron (Fe+2) and Kjeldahl Nitrogen (NTK). It was found that the concentration values of those effluents exceeded the maximum contamination limits specified by international industrial waste standards. A simple and reliable prediction model was developed to estimate DBO5, based on MES, COD, and O&G, by using classical regression analysis and fitting Design of Experiments (DOE) methodology. When comparing the analytical results, it was found that the quadratic model provided a better estimation, with a high correlation coefficient (R2) of 0.9976. The parameters determined in this study will enable engineers to quickly estimate the degree of wastewater contamination and choose adequate treatment strategies.
Robust Nonlinear Predictive Control Applied to Induction Motors
Authors: Bektache Abdeldjebar , Achouri Houssem , Belkhir K. Salim
Published: June 2023

In this paper, a nonlinear predictive controller is proposed for a variable-speed induction motor. The research work is directed towards improving the trajectory tracking capability, stability guarantee, robustness to parameter variations, and disturbance rejection. The Generalized Predictive Control (GPC) without constraint and output-constrained controller to induction motor drive is illustrated. The variables to be controlled are rotor speed and flux trajectory. The load torque is considered an unknown disturbance. Finally, the tuning parameter of GPC is automatically determined. The simulation results show a good performance for the nonlinear dynamic system.
A Student Learning Style Auto-Detection Model in a Learning Management System
Authors: Rashid Amirah Binti , Raja Ikram Raja Rina , Thamilarasan Yarshini , Salahuddin Lizawati , Yusof Noor Fazilla Abd , Rashid Zakiah Binti
Published: June 2023

Learning style plays an important role in enabling students to have an efficient learning process. This paper proposes an auto-detection model of student learning styles in learning management systems based on student learning activities. A literature review was conducted to investigate the components of online learning activities. The search terms used were "online learning activities", "learning management systems", and "Felder-Silverman Learning Style Model (FSLSM)." A combination of the search terms above was also executed to enhance the search process. Based on the results of the review, eleven classes of online learning activities were identified, namely forum, chat, mail, reading materials, exam delivery time, exercises, access to examples, answer changes, learning materials, exam results, and information access. The online learning activities identified were then mapped to the Felder-Silverman model based on four model dimensions: processing, perception, input, and understanding. The proposed model shows the attributes of the online learning activities based on the dimensions in the FSLSM. The proposed model can assist educators to improve learning content according to the suitability of students and recommend appropriate learning materials to students based on their characteristics and preferences. Future studies include the use of machine learning algorithms such as decision trees to auto-detect student learning styles in learning management systems.
The Effect of Polypropylene Fibers on the Fracture Characteristics of Lightweight Aggregate Crumb Rubber Concrete Composites
Authors: Badawi Moataz , Ahmed Ayman G. , Eldamaty Tarek A. , Helal Medhat M.
Published: June 2023

The increasing use of rubber tires and their low recycling ratio have made them a serious environmental problem. This work aims to develop and investigate enhanced lightweight aggregate crumb rubber concrete (PFLWACRC) composites regarding the fracture properties of concrete. Polypropylene (PP) fibers are commonly familiar with increased crack growth endurance of concrete. On the other hand, the reuse of waste rubber in concrete plays a major role in the mitigation of the effects of climate change. Various concrete mixtures were designed with conventional Portland cement and common lightweight coarse aggregates. The variables considered in this study are PP fibers in different percentages (0.2%, 0.4%, and 0.6% volume fraction), and crumb rubber with various substitution proportions (0%, 5%, 10%, 15%, 20%, and 25% of fine aggregates). Cement with 450kg/m3 density with 10% silica fume was used. The fracture characteristics, which involve fracture toughness (KIC) and fracture energy generation (GF), of all concrete mixtures were evaluated by testing two types of samples, i.e. 54 notched concrete beams with dimensions of 10×10×52cm and 54 cylinders with diameter×height equal to 15×30cm. The results showed that the fracture toughness generation addresses the energy scattering limit of concrete mixtures. The findings showed that the existence of PP fibers increased the fracture energy and critical Crack Mouth Opening Displacement (CMOD)c. The PP fibers had a limited effect on the compressive strength and may even reduce it, but a remarkable enhancement of the energy absorption was observed.
Analyzing the Effects of MBPSS on the Transit Stability and High-Level Integration of Wind Farms during Fault Conditions
Authors: Dhouib Bilel , Zdiri Mohamed Ali , Alaas Zuhair , Hadj Abdallah Hsan
Published: June 2023

As the demand for renewable energy continues to increase, wind power has emerged as a prominent source of clean energy. However, incorporating wind energy into the power generation system at a high level can significantly impact the dynamic performance of the power system, resulting in increased uncertainties during operation. This study investigated the effectiveness of the Multi-Band Power System Stabilizer (MBPSS), a new power system stabilizer, in suppressing dynamic oscillations in a multi-machine power system connected to a wind farm. This research focused on analyzing the transient stability of a nine-bus network, commonly known as the Western System Coordinating Council (WSCC), integrated with a Doubly Fed Induction Generator (DFIG) using MATLAB/Simulink. The study evaluated the dynamic performance of the proposed system under fault conditions, including Line-to-Line-to-Line-to-Ground (LLLG) faults. Simulation results showed that MBPSS effectively dampened oscillations and improved the stability of the power system, even in the presence of severe faults and high-level integration of wind farms.
Sentiment Classification based on Machine Learning Approaches in Amazon Product Reviews
Authors: Kausar Mohammad Abu , Fageeri Sallam Osman , Soosaimanickam Arockiasamy
Published: June 2023

Online retailers and merchants increasingly request feedback from their clients on the products they purchase. This has led to a significant increase in the number of product reviews posted online, as more people are making purchases online. The opinions expressed in these customer reviews have a significant impact on other customers' purchase decisions, as they are influenced by other customers' recommendations or complaints. This study used Amazon, a well-known and widely used e-commerce platform, to examine sentiment categorization using several machine learning techniques while analyzing an Amazon Reviews dataset. At first, the reviews were transformed into vector representations using the Bag-of-Words approach. Word cloud was used to illustrate the text data in terms of the frequency they appear in the review. Subsequently, the machine learning methods decision trees and logistic regression were used. The two models used in this study achieved high levels of accuracy in analyzing the dataset. Specifically, the Decision Tree model outperformed the Logistic Regression one, achieving an impressive accuracy of 99% compared to the 94% of the latter.
An Experimental and Numerical Analysis of the Flexural Performance of Lightweight Concrete Beams reinforced with GFRP Bars
Authors: El Zareef Mohamed A.
Published: June 2023

Occasionally it is more crucial to lower the mass of a building component than to improve its rigidity, specifically in massive buildings like long-span structures where the self-weight of the floors is one of the significant challenges that engineers confront. Therefore, the main objective of this work is to explore the flexural performance of Lightweight Concrete Beams (LWCBs) reinforced with Glass Fiber Reinforced Polymer (GFRP) bars in terms of curvature, cracks and failure modes, deflection, material stress-strain relationship, and joint end rotation. The flexural performance of LWCBs reinforced with varied GFRP bars and Steel Reinforcement (SR) ratios is assessed and compared to that of Normal Concrete Beams (NCBs) reinforced with SR. Numerical analytical models for the tested beams were created utilizing the iDiana software. Both analytical and experimental test results were compared. The study revealed a high correlation between the findings of Finite Element Models (FEMs) and those acquired from beam testing. The performance of LWCBs that utilized SR was equivalent to that of NCBs. The GFRP-reinforced LWCBs performed mostly as elastic deformed elements, with just little deflection post-load release. The study emphasized the significant potential for employing LWC and GFRP bars in the construction field's growth.
Heart Sound Classification using the Nonlinear Dynamic Feature Approach along with Conventional Classifiers
Authors: Alromema Waseem , Alduweib Eman , Abduh Zaid
Published: June 2023

Heart sounds show chaotic and complex behavior when murmurs are present, containing nonlinear and non-Gaussian information. This paper studies ways to extract features from nonlinear dynamic models. The features frequently used to describe the underlying dynamics of the heart are derived from nonlinear dynamical modeling of heart sound signals. This study incorporates nonlinear dynamic features alongside conventional classifiers in the analysis of phonocardiograms (PCGs), achieving a significant improvement in the classification performance with 0.90 sensitivity and 0.92 specificity.
Hydrogeochemical Assessment of Groundwater Quality and Suitability for Drinking and Agricultural Use. The Case Study of Fars Province, Iran
Authors: Aghaei Yasamin , Nazari-Sharabian Mohammad , Afzalimehr Hossein , Karakouzian Moses
Published: June 2023

This study aims to evaluate the hydrogeochemistry of aquifers in Fars province, Iran, from 2007 to 2017 and assess the groundwater’s suitability for drinking and agricultural uses. A total of 35,000 samples were collected from wells and qanats across the province. Piper, Gibbs, and Durov diagrams were used to assess the hydrochemical facies and processes. Cross plots of different ions were investigated to assess ion exchange and determine the effects of anthropogenic activities, as well as the weathering and dissolution of different rocks and minerals in the aquifers. Groundwater quality and suitability for agricultural and drinking purposes were also assessed using physicochemical parameters including pH, Electrical Conductivity (EC), Total Dissolved Solids (TDS), Total Hardness (TH), and calcium, magnesium, sodium, potassium, bicarbonate, sulfate, and chloride concentrations. Suitability for domestic purposes was assessed by comparing these values with the WHO standards. Sodium and alkalinity hazards, including Sodium Adsorption Ratio (SAR), sodium percentage (Na%), Permeability Index (PI), Magnesium Hazard (MH), and Residual Sodium Carbonate (RSC) were used to assess irrigation suitability, along with plotting Wilcox and USSL diagrams.
Workability and Flexural Strength of Recycled Aggregate Concrete with Steel Fibers
Authors: Chachar Kashif Hassan , Oad Mahboob , Memon Bashir Ahmed , Siyal Zameer Ahmed , Siyal Kiran Fatima
Published: June 2023

This study examined how concrete workability and flexural strength are affected by steel fibers and recycled aggregates. Steel fibers were used in doses between 1-5%, with an increment of 0.5%, and 50% of the natural coarse aggregates were replaced by recycled. Two mixes of conventional and recycled aggregate concrete without steel fibers were used as control mixes. Concrete mixes were prepared using 1:2:4 and 0.45 water-to-cement ratios. Workability was determined using the slump cone. Three prism specimens sized 500×100×100mm were prepared for each batch and cured for 28 days in potable water. After curing, the specimens were air-dried in the laboratory and tested to evaluate their flexural strength under two-point loading. The load and deflection were monitored at regular intervals until failure. A comparison of results with control mixes showed that as the percentage of steel fiber increased, flexural strength increased by 69% and deflection decreased by 66%. The use of steel fibers improved the flexural strength of the recycled aggregate concrete by 59%.
Randomly-based Stepwise Multi-Level Distributed Medical Image Steganography
Authors: Munshi Asmaa
Published: June 2023

Steganography deals with concealing sensitive information that can either be communicated across a network or stored in a secured location. The concealment of information is accomplished through the carrier, making data access by an unauthorized person more difficult. There are many stenographic techniques that have been used. Unfortunately, the hybrid-multi-level approach was ignored. For this reason, the current research utilized image steganography on a hybrid-multi level involving encryption, data compression, and two-stage high data concealment. The proposed technique can be used to conceal information in medical images without any distortion, allowing flexible and secure transfer capability. After using the Trible DES algorithm to encrypt the secret text at the beginning of the process, the next step involves embedding the secret encrypted cipher message into the host image while keeping the image intact. The findings indicate that the value of PSNR and NCC are satisfactory when compared to the sensitivity of the human eye. As a direct impact, the confidential message is hidden from the adversary. It can be seen that the PSNR value is quite high. Therefore, this indicates that the image after the stenographic process is relatively similar to the original image.
Buckling Analysis of Porous Functionally Graded Plates
Authors: Gupta Anil Kumar , Kumar Ajay
Published: June 2023

This study investigated the buckling behavior of Porous Functionally Graded Material (PFGM) plates. The present model assumes unevenly distributed porosity along the plate thickness and the use of the novel hyperbolic shear deformation functions and hyperbolic tangent and secant thickness stretching functions. In the present work, a porous Functionally Graded (FG) plate was analyzed by the principle of virtual work in order to understand the buckling behavior under uniaxial and biaxial compressive loading. The Rayleigh quotient method was applied to find the critical buckling load. The mesh convergence was investigated on a Finite Element (FE) model, and the accuracy of the results was compared with the prior research. The results of the proposed model match reasonably well with the ones of the published literature. Thorough parametric studies were performed to investigate the effect of porosity on the critical buckling load of the PFGM plate.
Optimization of Technological Parameters when Plasma Nitriding the Gear Working Surface
Authors: Danh Bui Thanh , Ky Le Hong
Published: June 2023

This paper presents the results of optimizing the technological parameters when plasma nitriding the gear working surface. 27 experiments were carried out on an H4580 Eltrolab instrument to obtain a working surface hardness database table, and the Minitab statistical software was used to process the experimental results. A regression equation was identified to analyze the influence of temperature, time, and gas permeation concentration on the hardness of the working surface. An analysis of variance (ANOVA) showed that all these nitriding parameters influence the regression equation. The results showed that the permeation temperature TL has the greatest influence on the hardness, while the permeation time h and the first gas permeation concentration G1 had less influence. An optimal set of technological parameters was established, where the permeation temperature was TL=550°C, permeation time was h=8h, and the first gas permeation concentration was G1=4l/h. Experiments were carried out using this set of optimal parameters to evaluate the microstructure and the depth of the hardening layer of the part surface. Finally, this study presented the whole process for the permeation and plasma nitriding of 18XГT steel.
Fraud Prediction in Movie Theater Credit Card Transactions using Machine Learning
Authors: Alshutayri Areej
Published: June 2023

This paper highlights how the proliferation of online transactions, especially those involving the use of credit cards, has resulted in the emergence of new security flaws that pose threats to customers and enterprises worldwide. E-commerce and other forms of online monetary transactions have become essential in the manufacturing and service sectors, propelling the global economy. The widespread and dependent connectivity of mobile payment systems using credit card transactions presents chances for fraud, risk, and security breaches. In light of the importance of accurately predicting fraud incidents through payment procedures, this study investigated the credit card payment methods used for movie tickets, using the machine learning logistic regression method to analyze and predict such incidents. This study used a dataset from cinema ticket credit card transactions made in two days of September 2013 by European cardholders, including 284,807 transactions out of which 492 were fraudulent purchases. The results of the proposed method showed a prediction accuracy of 99%, proving its high prediction performance.
Α New Agent-based Solution for Bridge Lifespan Extension
Authors: Ben Hassine Ahlem
Published: June 2023

Bridges are one of the most important and useful components of the transportation infrastructure, as they are crucial to many aspects of daily life, particularly in terms of economic development. However, bridges are vulnerable to several damages, malfunctions, and collapses that may considerably reduce their lifespan. The main causes of bridge fatigue are congested areas, excessive traffic, overloads, and additional vibration brought on by vehicles crossing them over. These elements reduce a bridge's longevity and raise maintenance costs. For a bridge to last as long as possible, it must not be crossed by an excessive number of cars and big trucks at once, and traffic should be kept under control. This study proposes an intelligent and autonomous multiagent-based system that incorporates a deep learning model to improve the monitoring of a bridge's crossing traffic. The idea was to propose a novel system for monitoring autonomously crossing vehicles in real-time to prevent the hastening of a bridge's infrastructure decline. The proposed system aimed to (i) increase the safety of drivers; (ii) lower maintenance costs; (iii) lessen the likelihood of bridge collapse, and (iv) lengthen bridge lifespans. Using a sample dataset, a straightforward deep learning model (CNN) was tested to improve bridge traffic monitoring. The performance of the proposed model was compared with the VGG-19 model. The results showed that the proposed model was effective in determining traffic congestion status with a 95% accuracy. As a result, the proposed system can be deployed on any bridge and can reduce crossing traffic overloads, extending its lifespan.
DEVELOPING THE READING COMPREHENSION SKILLS OF A STUDENT WITH A SPECIFIC LEARNING DISABILITY THROUGH THE PREDICT-ORGANIZE-SEARCH-SUMMARIZE- EVALUATE (POSSE) READING COMPREHENSION STRATEGY
Authors: KAŞDEMİR Beyhan , OZDEMIR Olcay
Published: June 2023

This study aims to investigate the effectiveness of the Predict-Organize-Search-Summarize-Evaluate (POSSE) reading comprehension strategy in developing the reading comprehension skills of a fourth grader diagnosed with learning diffculty. It was conducted with a student who had learning and reading comprehension difficulties in a primary school in the Western Black Sea region. The data for the study were collected in action research design. They were collected from narrative texts used in primary school grade 1, 2, 3 and 4 Turkish course textbooks, materials and activities designed in accordance with the Prediction-Examination-Summation Organization-Evaluation (POSSE) strategy, using schematic organizers and audio-video recordings. The reading level of the student was determined with a pretest using narrative texts in the 1st grade Turkish textbook. Following the 36-hour pilot trial in which 12 narrative texts were used, 59 main implementations extending over 165 hours were carried out with 40 narrative texts from grade 2, 3 and 4 Turkish textbooks. In the final stage, a posttest was carried out using the narrative texts in grade 2, 3 and 4 Turkish textbooks. The data collected in the study were analyzed with the help of the wrong analysis inventory by Haris and Sipay (1990), Ekwall and Shanker (1988) and May (1986), which had been adapted to Turkish by Akyol (2016). The results suggested that the student’s reading and reading comprehension levels increased from the level of frustrating to the level of independent reading, showing that the Prediction-Examination-Summary Organizing-Evaluation (POSSE) reading comprehension strategy was effective in improving the reading comprehension skills of the student with learning difficulty.
Relationship between pancreatic cancer and Maresin 1
Authors: Varol Hakan , Gül Özlem , Ergül Bilal , Kısa Üçler , Tekin Ercan , Oğuz Dilek
Published: June 2023

Aims: Pancreatic cancer is the 4th most common cause of death from cancer. In addition, pancreatic cancer is the most
common primary malignant tumor of the pancreas. There are many risk factors for pancreatic cancer, including age, certain
genetic syndromes, smoking, diabetes, alcohol abuse and obesity. In our study, we aimed to evaluate the role of Maresin 1
(MaR1), which is responsible for the resolution of inflammation, in the pathogenesis of pancreatic cancer and its differential
power between chronic pancreatitis and pancreatic cancer.
Methods: The study included 47 patients diagnosed with pancreatic cancer, 32 patients diagnosed with chronic pancreatitis,
and 30 volunteers without any additional disease who applied to the internal medicine polyclinic for routine control, who
applied to our clinic since October 2021 and accepted to participate in the study. MaR1 levels were measured using the ELISA technique from blood samples obtained from these volunteers.
Results: In our study, MaR1 level was 374.42 (97.27-74.129) pg/ml in the pancreatic cancer group, 491.39 (252.66-949.28) pg/ml in the chronic pancreatitis group and 558.53 (286.94) in the healthy control group. -886,68) pg/ml was measured. There was a significant difference between the pancreatic cancer patients group and the chronic pancreatitis patients and healthy control group. In the pancreatic cancer patient group, MaR1 level was found to be lower than the chronic pancreatitis group (p=0.01). In our ROC analysis, the discriminative performance of MaR1 (AUC=0.651; [95%CI: 0.535-0.754]; p=0.0169 values) was found to be high in predicting patients with pancreatic cancer according to the patient group with chronic pancreatitis. For MaR1 ?315.52 cut-off point sensitivity was 36.17% and selectivity was 90.62%.
Conclusion: Proinflammatory cytokines, which have a role in the pathogenesis of pancreatic cancer, increase as a result
of the decrease in lipid mediators involved in resolution pathways. Reduction of MaR1 may trigger chronic inflammation
and pancreatic carcinogenesis. MaR1 may make an important diagnostic contribution in clinical practice in predicting the
progression of patients with chronic pancreatitis to pancreatic cancer.
The efficacy of Erector Spinae Plane Block (ESPB) applied under ultrasonography guidance in percutaneous nephrolithotomy operations
Authors: Şahin Ahmet Tuğrul , Aydın Gülçin , Akçaboy Zeynep Nur , Aydın Oktay , Gençay Işın , Peker Kevser , Alparslan Murat , Yılmaz Erdal
Published: June 2023

Aims: This study aimed to evaluate the effect of erector spinae block (ESPB) applied preoperatively under ultrasonography guidance in percutaneous nephrolithotomy (PNL) operations in terms of the intraoperative need for opioids, postoperative analgesia, and patient satisfaction.
Methods: Of 60 patients who were 18 to 65-year-old and evaluated as American Society of Anesthesiologists (ASA) risk I-II-III were planned to undergo elective PNL. The patients were randomly separated into two groups as the Block group-administered ESPB under sedation in the preoperative period and the Control group-administered no ESPB. All the operations were performed under general anesthesia. The study data were analyzed using Mann-Whitney U-test and the Independent Samples t-test.
Results: Demographic data of the patients were not different between the groups (p>0.05). Neither intraoperative opioids nor analgesics were required for any of the patients in the ESPB group whereas intraoperative opioids and analgesic drugs had to be administered to all of the patients in the control group (p<0.001). The postoperative patient satisfaction scores in the ESPB group were found statistically higher than that of the control group (p<0.001).
Conclusion: The results demonstrated that ESPB applied preoperatively under USG guidance reduced the need for intraoperative opioids and postoperative analgesia in PNL operations. This, in turn, increased patient satisfaction by maintaining patient comfort after surgery.
CHUYỂN ĐỔI SỐ TRONG HOẠT ĐỘNG QUẢN LÝ VÀ ĐÀO TẠO TẠI TRƯỜNG ĐẠI HỌC HÙNG VƯƠNG
Authors: Tại Thiều , Nguyễn Quyết , Nguyễn Hiền
Published: June 2023

Trong cuộc cách mạng 4.0, việc thực hiện chuyển đổi số trong hoạt động quản lý và đào tạo tại các trường đại học là một việc làm cấp thiết. Việc ứng dụng công nghệ thông tin vào hoạt động quản lý và đào tạo không chỉ giúp các trường đại học nâng cao hiệu quả quản lý, đào tạo mà còn làm thay đổi tư duy, năng lực và phương pháp của cả đội ngũ từ chuyên viên, giảng viên cho đến lãnh đạo để có thể xây dựng và vận hành hệ thống giáo dục trên nền tảng số. Trường Đại học Hùng Vương trong những năm gần đây cũng đã tiếp cận và thực hiện số hóa một số qui trình quản lý, học liệu điện tử, học tập trực tuyến trên hệ thống E-learning. Chuyển đổi số giúp nhà trường khai thác tối đa nguồn lực để đáp ứng yêu cầu ngày càng cao trong đào tạo nhân lực cả về số lượng và chất lượng cho phát triển kinh tế - xã hội
TƯ CÁCH CHIẾN SĨ LẤN ÁT TƯ CÁCH NGHỆ SĨ CỦA CHỦ THỂ DIỄN NGÔN TRUYỆN NGẮN KHU VỰC TRUNG TÂM GIAI ĐOẠN 1945 - 1975
Authors: Hoang Giang
Published: June 2023

Bất kì nền văn hoá, văn học nào, ở mọi yếu tố, cấp độ cũng có phần trung tâm và ngoại biên. Với văn học nói chung, truyện ngắn nói riêng giai đoạn 1945 – 1975 cũng vậy. Trong truyện ngắn khu vực trung tâm (tập hợp những tác phẩm viết theo chủ trương đường lối của Đảng: cổ vũ, tuyên truyền cho cách mạng, thể hiện tinh thần yêu nước, bảo vệ chủ nghĩa xã hội) ở phương diện chủ thể diễn ngôn, có thể thấy tính quan phương chính thống bộc lộ rõ nét ngay từ tiếng nói của chủ thể diễn ngôn. Trong tiếng nói ấy, tư cách chiến sĩ lấn át tư cách nghệ sĩ là một nét đặc thù.
Systematic Literatur Rivew Systematic Literatur Review: Efektivitas E-Learning sebagai Media Pendukung dalam Pembelajaran Matematika
Authors: Farah Syafira Ibtisa , Kusno Kusno
Published: June 2023

Pembelajaran matematika seringkali masih dianggap sulit oleh sebagian besar peserta didik. Hal tersebut disebabkan oleh beberapa faktor, seperti kesulitan dalam memahami konsep, dan metode yang digunakan oleh pendidik kurang bisa dipahami. Selain itu, peserta didik seringkali merasa bosan karena kurangya interaksi dan penggunaan teknologi yang masih minim. Oleh karena itu, diperlukan media pendukung untuk mengatasi masalah tersebut salah satunya yaitu dengan menggunakan e-learning.  Dengan melakukan kajian literatur terhadap penelitian yang telah dilakukan, diharapkan hasil penelitian ini memberikan pemahaman yang lebih baik tentang efektivitas e-learning sebagai alat pendukung dalam pembelajaran matematika. Hasil dari penelitian menunjukkan bahwa penggunaan e-learning dalam pembelajaran matematika dapat meningkatkan kemampuan pemahaman konsep matematika, meningkatkan kemandirian belajar, dan meningkatkan hasil belajar peserta didik. Penggunaan e-learning sebagai media pendukung efektif, jika kemampuan matematis dan hasil belajar peserta didik meningkat. Oleh karena itu dengan meningkatnya minat dan motivasi belajar, maka akan berpengaruh positif terhadap kemampuan matematis dan hasil belajar peserta didik juga akan meningkat.