bluuebunny/crossref_metadata_2025 huggingface dataset:
A 21. századi szakképzés oktatóinak kompetenciái: egy pilot kutatás előkészítése
Authors: Kolacsek Sándor
Published: November 2024

Az előadásban ismertetett kutatás témája a szakképzésben dolgozó oktatók pedagógiai és digitális kompetenciáinak feltérképezése, valamint annak vizsgálata, hogy ezek a kompetenciák milyen mértékben jelennek meg az oktatói gyakorlatban. A témát egy jövőbeli kutatás alapozza meg, amely arra keresi a választ, hogy milyen oktatói/tanári/szakmai kompetenciákra van szükség a 21. századi szakképzésben és hogy ezek a kompetenciák milyen mértékben haladják meg a szakmai ismereteket. Az oktatásban a pedagógusnak, a társadalmi elvárásokhoz igazodva, a meglévő tudása, kompetenciái mellé folyamatosan új jártasságokra is szert kell tennie, hogy a megjelenő igényekhez igazított tanulási környezetet tudjon megteremteni a tanulók számára. Ezt figyelembe véve, kell vizsgálni, hogy az IKT eszközök használatát, a digitális pedagógia adta lehetőségeket mennyire alkalmazzák hatékonyan az oktatók. A tervezett kutatás továbbá arra is kitér, hogy milyen különbségek mutathatók ki a különböző szak-képző intézményekben dolgozó oktatók között, illetve, hogy a különböző régiókban és azonos profilú oktatási intézményekben dolgozó oktatók kompetenciái között milyen eltérések figyelhetők meg.
A hatékony tanulás aktuális kérdéskörei - digitális kompetenciafejlesztés és digitális idegenvezetés kihívásai és lehetőségei napjainkban
Authors: Molnár György , Nagy Enikő
Published: November 2024

Napjainkban a digitális technológiák térnyerése nemcsak az üzleti és szórakoztató szektorban, hanem az oktatásban és turisztikai iparban is számos kihívást és lehetőséget teremt a digitális kompetenciafejlesztés és digitális idegenvezetés területén. A digitális kompetenciafejlesztés kihívásai közé tartozik a technológia gyors változása és a folyamatos fejlesztések, amelyek következtében új ismereteket és készségeket kell megszerezni. Ezen kívül, a digitális technológiák nagymértékű használata miatt a digitális szakadék is egyre nagyobb problémát jelenthet, hiszen nem mindenki rendelkezik az szükséges eszközökkel és ismeretekkel a digitális világban való megfelelő tájékozódásban. A cikk a digitális kompetencia és technológia tanítási-tanulás folyamatba való integrációs lehetőségeire fókuszál. Ennek keretében vizsgálja digitális kompetenciafejlesztés lehetőségét napjainkban kiemelve az ehhez kapcsolódó hazai és nemzetközi stratégiákat.
Dróntechnológia az osztályteremben: drónok használata a STEM oktatásban
Authors: Tomolya Róbert
Published: November 2024

Az oktatásban alkalmazott drónok fejlesztik a diákok technikai, programozási és problémamegoldó készségeit. A tanulmány megpróbálja összefoglalni, ismertetni, hogy miként integrálhatók ezek a drónok a különböző tantárgyakba, például a programozásba, a fizikába és a matematikába. A drónok használata révén interaktív és élményalapú tanulási környezet hozható létre, amely elősegíti a diákok aktív részvételét és elköteleződését. A drónok az utóbbi években egyre nagyobb népszerűségnek örvendenek mind a hobbi, mind az ipari alkalmazások területén. A DJI TelloEdu és a Robomaster TT egy kisméretű, könnyen kezelhető drón, amely ideális eszköz a programozás és a robotika alapjainak elsajátításához.
Hibrid oktatási technikák az angol mint idegen nyelv oktatásában
Authors: Katona Nikolas
Published: November 2024

A kombinált oktatáshoz (Blended Learning) sorolt hibrid oktatás magába foglalja a hagyományos értelemben vett osztálytermi tanítást, valamint az IKT-eszközökkel támogatott online tanulást. A COVID-járványnak köszönhetően mind az általános és középiskolai, mind pedig a felsőoktatásban kiemelkedő szerepet kapott, és a pandémia lecsengése után is előszeretettel alkalmazzák az oktatásban. A tanulmány igyekszik rámutatni a két oktatási forma által kínált előnyökre és hátrányokra az angol mint idegen nyelv oktatásának kontextusában. Célja megvilágítani a hibrid oktatás sajátos jellemzőit, bemutatni annak egyes taxonómiai szerepeit. Az elméleti háttér a szerző saját oktatási tapasztalatán alapuló jó gyakorlatokkal kerül kiegészítésre a középiskolai, valamint a felnőttoktatás példáján.
Olvasás a digitális kor előtt és után
Authors: Molnár Csilla
Published: November 2024

anulmányomban igyekszem rövid áttekintést adni arról a folyamatról, amely megváltoztatta az olvasás 20. század közepére betöltött társadalmi szerepét. Ebben a felvázolni kívánt kontextusban az olvasásnak arra a státuszváltására utalok vissza, amelynek kezdetén a könyv az 1970-es évek végégig töretlen népszerűséget látszott kivívni a társadalom szélesebb köreiben is. Az akkori könyvek, magazinok manapság hihetetlen példányszámban fogytak. Ehhez képest az ezredforduló körüli évektől tömegek fordultak az új, attraktívabb médiákhoz, jelentős mértékben felhagyva a könyvek vásárlásával. Kérdés, hogy a digitális média térhódítása az 1990-es évek közepétől ténylegesen csökkentette-e az olvasási kedvet. Ezen belül szándékom rámutatni arra az összefüggésre, hogy az olvasás egykor legendás népszerűsége majd „térvesztése” nem pusztán a digitális világ térnyerésével hozható összefüggésbe. Véleményem szerint ugyanis az olvasás állítólagos aranykora a szélesebb társadalmi rétegekben inkább afféle médiapótléknak tekinthető, amely a könnyebben hozzáférhető eszközök és tartalmak megjelenése után természetszerűleg vesztette el szerepét. Ezt igazolja az a mások által már többször vizsgált összefüggés is, hogy az olvasás jelentősége nem változott azokban a társadalmi körökben, ahol az írott szövegekben való tájékozottság, a szövegértés a mai napig is fontos elvárás és társadalmi megkülönböztető jegy. Olvasásszociológiai jellegűnek tűnő írásomban kitérek többek között Pierre Bourdieu, illetve Ivan Ilich gondolataira, igyekszem rámutatni a téma feldolgozásakor alkalmazott émikus kutatási módszerrel annak pedagógiai öszszefüggéseire is.
A köznevelés digitális transzformációjának egri aspektusai: a 2009-2017-ig zajló iskolakísérletek médiadidaktikai elemzése
Authors: Racsko Réka
Published: November 2024

Az ezredfordulót követő technológiai forradalom erős hatást gyakorolt a társadalmi alrendszerekre, különös tekintettel az iskola világára. Megindultak az új típusú oktatási környezetek fejlesztésével kapcsolatos kutatások, amelyben nagy szerepet kaptak a magas innovációs potenciállal rendelkező digitális hardvereszközök (pl. hordozható számítógépek, interaktív táblák, táblagépek), a kapcsolódó új módszertani megoldások (BYODmodell), az interaktív mediális elemek (multimédiás tartalmak), valamint a hozzájuk kapcsolódó curriculumfejlesztések. Fókuszuk pedig a magas szintű digitális kompetenciafejlesztés és az iskolai digitális transzformáció rendszerszintű megvalósítása volt. Az Eszterházy Károly Főiskola Médiainformatika Intézete ennek szellemében 2009-ben indította el azt a hazai és nemzetközi téren is úttörőnek számító iskolakísérlet-sorozatát, amely a fentebb vázolt kihívásokra kereste a választ a korszerű és hazánkban egyedülálló mentorált innováció (Dorner–Kárpáti, 2008) módszere révén. Az alkalmazott módszertani megoldások erős párhuzamot mutatnak a digitális technológia integrációjához köthető elfogadás modellekkel, amelyek megjelenésre egybeesik a személyi számítógépek elterjedésével. Az első ismert modell Davis (1986) nevéhez fűződik, aki megalkotta a Technology Acceptance Model (TAM) koncepcióját, amely később alapját képezte számos médiadidaktikai (Kis-Tóth et. al, 2001) modellnek (PIC-RAT, TIP, TIM, LoTI, SAMR, kiterjesztett BLOOM-taxonómia), amelyek az egyes eszközök tanulási-tanítási folyamatba történő integrációját foglalják rendszerbe. Előadásomban az egri iskolakísérletek főbb állomásait és sajátosságait tekintem át a szisztematikus szakirodalmi áttekintés PRISMA-protokollját alkalmazva, valamint a technológiaintegrációs modellek elemeivel történő összehasonlító kvalitatív elemzésének eredményeit ismertetem, a tartalomelemzés módszerét alkalmazva.
Crowdsourcing, digitalizáció és mikrotörténet. Az interaktív közgyűjtemény. A felhasználók szerepe a digitális tartalomgyűjtésben
Authors: Szűts-Novák Rita , Szűts Zoltán
Published: November 2024

Az információs kor kihívásai és a technológiai fejlődés új perspektívát teremtett a közgyűjtemények számára a tartalomgyűjtés és tárolás terén. A hagyományos múzeumi és könyvtári gyakorlat szemlélete fokozatosan változik az új digitális kor elvárásainak megfelelően. Írásunk elemzi az elmozdulást a közgyűjteményi gyakorlatban, és rámutat, hogy a szemlélet-váltásnak kiemelkedő fontossága van a felhasználók bevonásában. A közgyűjtemények hagyományosan az információk megőrzésének és átadásának szentelt intézmények voltak. Azonban a digitális technológiák térnyerése és az internet elterjedése megnyitotta az utat az interaktivitás és a közösségi együttműködés előtt. Az új szemléletben a közgyűjtemények már nem csupán a tárolás és a kutatás helyszínei, hanem aktív szereplői a tudásmegosztásnak és a közösségi kreativitásnak. A digitális eszközök segítségével a látogatók, kutatók és érdeklődők aktívan részt vesznek a gyűjtemények gazdagításában, rendezésében és a művek címkézésében. A crowdsourcing és a kollektív intelligencia elveinek alkalmazása lehetővé teszi a közgyűjtemények számára, hogy a felhasználók sokféleségéből merítve építsék fel gyűjteményeiket és töltsék meg tartalmukat értékes információkkal. A szemléletváltás nemcsak a közgyűjtemények tartalmának sokszínűségét növeli, hanem a felhasználók bevonásának élményét is fokozza. Az interaktív közgyűjtemények nem csak statikus információt kínálnak, hanem lehetőséget teremtenek az aktív párbeszédre és az együttműködésre a közönség és az intézmények között. Az így létrejövő közgyűjteményi tartalmak sokkal relevánsabbak és hitelesebbek a felhasználók számára, hiszen a közösség tagjai maguk is részeseivé válnak a tudás és a kultúra megőrzésének. Emellett az ilyen módon felépített közgyűjtemények megfelelnek a modern digitális kor igényeinek, és új lehetőségeket kínálnak az oktatás, kutatás és kreativitás terén. Tanulmányunkban többek között a Fortepan példáján keresztül mutatunk rá, hogy a szemléletváltás a közgyűjteményi gyakorlatban kiemelkedő jelentőségű, hiszen az interaktív közgyűjtemények révén a felhasználók aktív szereplőkké válnak a tartalomgyűjtésben és a tartalom létrehozásában. Ezáltal a közgyűjtemények sokkal élénkebb és gazdagabb tudásközpontokká válnak, amelyek képesek megfelelni a modern digitális kor elvárásainak és a közösség igényeinek.
A new approach for smart attendance system based on improved video facial recognition technology for smart university
Authors: El-Mashad Yehia , Ali Hesham A.
Published: November 2024

Since entering the information age, there have been considerable developments in the methods of managing the various learning processes, so there is no need to rely on a large amount of human resources to collect and analyze data. Many technologies have emerged that are capable of analyzing different types of data and providing interdependence and movement to data effectively. So, it can be said that digital transformation has played a decisive role in developing management systems in smart universities. Attendance systems through facial recognition may be considered the most important operation in the smart university. The main objective of this paper is to introduce the attendance system through a new methodology for detecting and identifying faces through video cameras based on artificial intelligence techniques to predict the face and match it with what is in the database. By developing a robust attendance system using video facial recognition technology, the proposed methodology in this paper aims to improve the accuracy, efficiency, and safety of attendance tracking in smart universities. To achieve the proposed goal, this paper will focus on developing a facial recognition algorithm that can accurately identify individuals under varying lighting conditions and facial expressions. The proposed system can provide real-time attendance information, allowing for timely interventions and support for students who may need it. Moreover, the use of video facial recognition technology can help reduce the workload for teachers and administrators. The proposed algorithm is tested, and the experimental results prove that, due to minimal error, better classification accuracy and high confidence value are achieved.
Machine learning approaches for predicting cardiovascular disease: a systematic review and meta-analysis
Authors: El-Attar Noha E. , El-Mashad Yehia. A.
Published: November 2024

Heart failure and heart attack are serious cardiovascular diseases that are responsible for a significant number of deaths worldwide. Early detection and accurate prediction of these diseases can be challenging, but machine learning models offer a promising approach to improve diagnosis and treatment. There has been growing interest in using machine learning models to predict heart failure and heart attack disease. These models use various types of data, such as patient demographics, medical history, vital signs, and laboratory tests, to identify patterns and predict the risk of disease in recent years. Some of the commonly used machine learning algorithms for this task includes logistic regression, decision trees, random forests, support vector machines, and neural networks. The use of machine learning models for this purpose has the potential to improve patient outcomes by enabling earlier diagnosis and targeted treatment, leading to better management of cardiovascular diseases and ultimately reducing the burden of these diseases on healthcare systems.
Refractory porous filler based on ash and slag mixture, metallurgical slag and liquid glass composition
Authors: Nikitina N. V. , Abdrakhimov D. V.
Published: November 2024

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An Emotionally Intelligent System for Multimodal Sentiment Classification
Authors:   Department of Computer Science with Cyber Security, Dr. SNS Rajalakshmi College of Arts and Science, Coimbatore, 641049, Tamil Nadu, India, Suganya R , Narmatha M , Kumar S Vengatesh
Published: November 2024

Objectives: To develop a multimodal sentiment classification model by analyzing the impact of biological signals and examining the concatenation of various modalities in a marketing scenario. Methods: This paper proposes a new emotionally intelligent system for multimodal sentiment classification. Initially, a multimodal database is prepared by collecting text, speech, facial expression, posture, and biological signals for each individual in the user-machine interaction scenario. This database is preprocessed to remove unwanted noise or missing values. After preprocessing, the dataset is split into training and testing sets. The training set is then fed into the feature extraction phase which involves different methods to extract various types of features like texture, color, acoustic, linguistic, and biological signals. These features are independently trained by the Multi-Modal Deep Belief Network (MMDBN) model to generate the trained classifier. The trained classifier is later used to classify the test sets as different sentiment classes like positive, negative, or neutral. The effectiveness of the proposed MMDBN model is evaluated in MATLAB 2019b using Interactive Emotional Dyadic Motion Capture Database (IEMOCAP) and Wearable Stress and Affect Detection (WESAD) datasets. Each dataset is divided into 70% for training and 30% for testing. A comparative study is conducted by applying existing sentiment classification models on the datasets to evaluate MMDBN prediction efficiency using metrics like accuracy, precision, recall, and F-Score. Findings: The MMDBN model achieves 80.28% and 81.17% accuracy on IEMOCAP and WESAD databases compared to the existing sentiment classification models like Deep Multi-View Attentive Network (DMVAN), Multi-Channel Multimodal Joint Learning Method (MCMJLM) and Multi-Level Textual-Visual Alignment and Fusion Network (MTVAF) and Attention-Based Multimodal Sentiment Analysis and Emotion Recognition (AMSAER). Novelty: This study introduces a novel emotional intelligence system for multimodal sentiment classification, integrating biological signals and other modalities to enhance accuracy in marketing by combining linguistic, acoustic, visual, and biological data.

Keywords: Sentiment classification, Biological signals, Multimodal database, Deep Learning, Deep belief network
Customer Retention Modeling over the OTT Platform using Machine Learning
Authors:   Department of Electronics and Communication Engineering, Maharaja Surajmal Institute of Technology, 110058, Delhi, India, Singh Upma , Singh Sandeep , Rathee Tripti , Vaish Manav
Published: November 2024

Objectives: Customer retention, a multifaceted issue that plagues the digital entertainment industry, particularly within the realm of Over-the-Top (OTT) platforms, poses a significant challenge, impacting revenue and sustainability. With the discontinuation of subscriptions or usage, retention not only impacts immediate revenue streams but also threatens the long-term sustainability of these platforms. Recognizing this challenge, this paper undertakes a comprehensive examination of predictive modeling methods tailored explicitly for forecasting customer retention within OTT platforms. Method: To construct predictive models, a diverse array of datasets is harnessed, encompassing a wide spectrum of customer-related variables. These datasets include demographic information, viewing history, subscription patterns, and various engagement metrics. Leveraging these datasets, advanced machine learning algorithms are deployed to develop robust models capable of predicting customer retention. Findings: The scrupulous study evaluates the implementation of a range of machine learning algorithms, including logistic regression, random forests, AdaBoost classifier, Decision Tree, and K nearest neighbor (KNN) classifier. Assessment metrics such as F1-score, recall, precision, and accuracy are employed to show the effectiveness of the employed models for customer retention modeling within OTT platforms. The results reveal that the highest accuracy of 80.40% is obtained using the AdaBoost classifier. Novelty: The research uses attribute significance analysis as a means of identifying the fundamental factors that impact client retention. OTT providers can receive important insights into the elements causing subscriber attrition by identifying these main drivers, which will help them develop tailored retention strategies.

Keywords: Neural networks, Logistic regression, Random forests, Decision trees, KNN, AdaBoost classifier, Retention prediction
Generalized Fuzzy Technique and its Consistent Assessment in Multicriteria Decision Making of Medical Decisions
Authors:   Professor, Mathematics Department, Chaudhary Charan Singh University, Meerut, Uttar Pradesh, India, Kumar Kamesh , Sharma M K
Published: November 2024

Objectives: The purpose of this study is to develop a decision-making expert system to assist the diagnostic decisions effectively. Generalized fuzzy sets (Vague sets) are used to model the uncertainty that exists in the process. Method: Initially, concepts of centroid and signed distance are generalized for Trapezoidal Vague Numbers (TVNs). This model introduces some desirable properties for the proposed distance measure. A multicriteria decision-making (MCDM) is introduced using trapezoidal vague numbers (TVNs) and other intuitions in medical diagnostics. In this MCDM, firstly, each symptom is classified into some criteria. Patients’ states and weights for the existing symptoms are assumed as vague point entries. As a mathematical tool, the present model used vague relations for illustrating different associations like symptom criteria and diseases and the state of the patients. The present model also discusses confidence interval-based statistical analysis for the construction of TVNs, which are the prominent component of the study. Findings: A numerical computation is illustrated with the whole procedure of the decision-making. To show the capability and distinctness of the proposed methodology, a comparative discussion for outcomes is given. The present method coincides with the existing fuzzy-based method for the initial diagnosis, while possibility degrees of diagnoses differences for patient P1 and patient P2 differ. It ranges from 1% to 16.3% in the method based on the existing traditionally fuzzy approach, and in the present approach, these differences range from 2.15% to 7.46%. Novelty: This research contributes to presenting a novel decision expert system that is more capable of making diagnosis efficient. This study provides a practical and visual tool to assess potential outcomes of the proposed technique through a numerical example.

Keywords: Vague set, Lower and upper membership function, Vague point, Trapezoidal vague number, Medical diagnosis
Mechanical Properties and Microstructure of 7075T6 Aluminum Alloy – DC01 Low Carbon Steel Rod Joints by Magnetic Pulse Welding
Authors:   Research Scholar, Department of Manufacturing Engineering, Faculty of Engineering and Technology, Annamalai University, Annamalai Nagar, 608 002, Tamil Nadu, India, Gnanamurugan K , Varahamoorthi R , Sundarraj C
Published: November 2024

Objectives: The production of solidification flaws such as porosity, alloy segregation, hot cracking, etc. makes the fusion welding process extremely challenging when joining aluminum alloys with low-carbon steel (DC01). Explosive welding and magnetic pulse welding are two solid-state welding methods that can be utilized to solve these issues. With magnetic pulse welding (MPW), welding can be done more quickly and affordably while creating overlapped joints. Methods: In this study, the MPW method was used to join the dissimilar AL 7075T6 aluminum alloy tube and DC01 steel rod. The mechanical characteristics and microstructure of MPW joints were evaluated and observed. The results demonstrate that the metallurgical joints may be formed in the lapping region at a discharge energy of 23 kJ, a stand-off distance of 2 mm, and an working length of 8.5 mm. Findings: The joint is made up of a transition zone with varying widths, two matrix metals, and two interfaces between the zone and the two metals. The interface has a characteristic wavy pattern, and mutual diffusion of Fe and Al elements occurs in the zone. The micro hardness of the interface is much higher than that of the matrix metals. The metallurgical joint consists of two interfaces, one transition zone and two basic metals. The mutual diffusion of Fe and Al elements occurs across the interface and in the transition zone. The multi-direction micro-cracks and the micro-apertures present in the transition zone. Novelty: Aluminium alloys with low carbon steel joints were developed using MPW for cars and ships applications without fusion welding defects. The microstructural features of Aluminium alloys with low carbon steel tube joints were correlated to the TSFL and Hardness of the joints.

Keywords: Magnetic pulse joining, Dissimilar metals, Metallurgical joint, Aluminum, Alloy, Mechanical properties
Developing an Agent-based Model for Evaluating the Effectiveness of Malaria Interventions in Nanyumbu and Masasi Districts, Tanzania
Authors:   School of Computational and Communication Sciences and Engineering, Nelson Mandela African Institution of Science and Technology, P.O Box 447, Arusha, Tanzania, Mfala Celina Theophil , Nyambo Devotha Godfrey , Mwaiswelo Richard Owden , Mmbando Bruno , Clemen Thomas
Published: November 2024

Objective : Agent-based models and simulation (ABMS) can be utilized to understand the dynamism of transmission and the effect of interventions. We evaluated using ABMS, the efficacy of insecticide-treated bednets (ITNs) at different coverage levels and quality of houses for control of malaria in Masasi and Nanyumbu districts, Tanzania. Methods: The model was developed and simulated in Anylogic software with mosquitoes, humans, and the environment along with their attributes as agents. Using field data, buildings of different qualities were created to be human environment, and ITN use was assigned to respective human agents. Shapefiles were imported into the built-in global imaging system map in Anylogic for better placement of buildings using their coordinates, and coordinates of streams extracted from the study area map were used to allocate the aquatic environment of the mosquito agents. ITNs coverage scenarios of 16%, 40%, 64%, and 80% were simulated. The model was simulated for 90-day period and a model time-step was set to a day. The primary outcome was the prevalence of human agents with malaria infection at the end of the 90-day simulation period. Results: At the end of the 90-day simulation period and initial ITNs coverage of 16% (257/1607), the prevalence of malaria infection was 15.4% (248/1607). When the coverage was increased to 40%, 64%, and 80% malaria prevalence declined to 15.1% (242/1607), 14.1% (227/1607), and 13.9% (223/1607), respectively. ABMS clearly indicated that an increase in ITNs coverage was associated with a decline in the prevalence of infected humans and mosquito population in consistency with the field data. Novelty: This work is unique in a sense that it incorporated the data on house quality which has direct impact in malaria transmission.

Keywords: Agent based model, Anylogic, ITN coverage, Malaria control, Public health
𝔑 𝑆 𝔇𝔏𝔑ℓ and 𝔑𝐐𝐒𝔇𝔏𝔑ℓ- Spaces in 𝔇𝔏-Nano Topological Space
Authors:   Assistant Professor, Department of Mathematics, Shrimati Indira Gandhi College, Affiliated to Bharathidasan University, Tiruchirappalli, Tamil Nadu, India, Maheswari R , Rekha K
Published: November 2024

Objectives: The purpose of this study is to propose a new kind of Nano Ideal topological space called 𝔇𝔏-Nano topological space, explores several novel forms of open and closed sets in the context of 𝔇𝔏-Nano topological space, and generate 𝔑 𝑆 𝔇𝔏𝔑ℓ and 𝔑𝐐𝐒𝔇𝔏𝔑ℓ-spaces in 𝔇𝔏-Nano topological space. Methods: The 𝔇𝔏-lower, 𝔇𝔏-upper and 𝔇𝔏-boundary regions have been established for any subset of the specified universal set and any binary relation defined on it. The associated 𝔇𝔏-Nano topological space can be determined by these regions in addition with universal set and the empty set. Findings: The relationship between 𝔇𝔏-Nano open sets and other sets in 𝔇𝔏- Nano topological spaces are found. Additionally, we figure out the forms of 𝔑 𝑆 𝔇𝔏𝔑ℓ and 𝔑𝐐𝐒𝔇𝔏𝔑ℓ-spaces. Novelty: Nano-open sets were used in the formation of normal spaces in Nano topological spaces, whereas in the current researchwork𝔑𝔇𝔏 and𝔑𝑆̄𝔇𝔏-open sets have been used to generate 𝔑 𝑆 𝔇𝔏𝔑ℓ and 𝔑𝐐𝐒𝔇𝔏𝔑ℓ -spaces.

Keywords: 𝔇𝔏-Nano topological space; 𝔇𝔏-lower, 𝔇𝔏-upper; 𝔇𝔏-boundary region, 𝔑 𝑆 𝔇𝔏𝔑ℓ -space, 𝔑𝐐𝐒𝔇𝔏𝔑ℓ-space
Self-Anticipation and Current Difference Effect in Lattice Model under Lane-Changing Behavior
Authors:   Department of Mathematics, MD University, Rohtak, 124001, Haryana, India, Mehta Shubham , Siwach Vikash , Redhu Poonam
Published: November 2024

Objectives: To develop a two-lane “lattice hydrodynamic model” incorporating “optimal current difference” and “self-anticipation” to improve traffic flow stability and reduce congestion. Methods: A two-lane lattice model is introduced, incorporating both “optimal current difference and self-anticipation effect”. Linear stability analysis alongside the reductive perturbation technique for deriving mKdV equations and nonlinear calculations are utilized to evaluate the model's impact on traffic stability and congestion, with theoretical results further validated through numerical simulations under periodic boundary conditions. Findings: The linear stability analysis reveals that the “self-anticipation” term significantly expands the stable region in the phase diagram compared to Peng's lattice model. The derived modified Korteweg-de Vries (mKdV) equation highlights heavy traffic near the critical point, indicating areas where congestion is most severe. Nonlinear calculations further demonstrate that incorporating both anticipation time and lane-changing behavior coefficient effectively reduces congestion. This combined approach smooths out traffic flow, especially in areas near the critical point of congestion. The findings suggest that drivers' self-anticipation has a differential effect that directly mitigates vehicular congestion, as drivers are better able to adjust behavior based on traffic conditions. Additionally, numerical simulations conducted with periodic boundary conditions confirm the effectiveness of these theoretical solutions in practice, reinforcing the model's applicability to real-world traffic conditions. Novelty: The model integrates “self-anticipation and optimal current difference”, expanding vehicles' stability and mitigating congestion more effectively than existing models.

Keywords: Two-lane lattice model, Traffic flow, Anticipation, Current difference, Simulation
Hotspots of Land Use Land Cover Change: World’s Largest Riverine Island Scenario
Authors:   Research Scholar, Department of Geography,, Gauhati University, Assam, India, Sharma Namita , Bora Rimlee , Bordoloi Jyotishma
Published: November 2024

Objectives: The study gives priority to the Land Use Land Cover (LULC) changes and changing hotspot locations of Majuli, which is the largest riverine island in Assam. Methods: Satellite imageries for the years 2002, 2011, and 2022 have been utilized to observe spatiotemporal dynamics using the iso cluster unsupervised classification technique. The Iso cluster unsupervised classification method can identify clusters of an image automatically and classify it based on its clusters. The analysis of change has been taken into account by assigning six land use classes, viz. cropland, forest, waterbody, built-up, grassland, and sandbar. Hotspot identification has been done using Getis-OrdGi* statistical methods. This statistical method can distinguish between areas with strong and low spatial associations and detect a tendency for favorable spatial clustering. Findings: The results showed that waterbody, forest, built-up, and grassland have significantly increased by 9.58%, 1.01%, 6.22%, and 9.88% respectively. In contrast, the cropland and sandbars decreased by 25.22% and 1.46% respectively. The kappa accuracy for 2002 is 90.85%, 87.88% for 2011 and 90.22% for 2022. In hotspot analysis, a total of 5 high-range hotspot patches and 11 moderate hotspot patches are identified for the district. The main factors responsible for changing LULC in the study area are the occurrence of floods every year, the combined effects of river erosion, and human interventions. Novelty: Novelty lies in the implications of geospatial techniques in changing LULC in a spatio-temporal context. Thus far, no previous research has been conducted on the identification of LULC hotspots within the study area. This study is significant for managing and conserving land resources and preventing recurring shifts in land cover. It will also offer a fresh perspective on extensively examining the underlying reasons for such frequent changes. Furthermore, identifying the hotspots of changes in the area over twenty years indicates that the district exhibits a volatile landscape. The results will certainly guide stakeholders in the region's sustainable resource management.

Keywords: Change detection, LULC, Hotspots, Isocluster, Majuli
A New Parametrically Extended Exponential Information Measure on Fuzzy Set Framework
Authors:   Department of Mathematics, Govt. V. Y.T.P.G. Autonomous College, Durg, Chhattisgarh, India, Maheshwari Maheshwari , Mishra Vikas Kumar , Thakur Sapna , Siddiqui M A , Dewangan R N
Published: November 2024

Objective: To generalize an existing fuzzy information measure and verify its fundamental characteristics. Methods: Both objective and descriptive methodologies, as well as problem-posing and problem-solving techniques, have been employed. New fuzzy information measures are established using a set of attributes proposed by De Luca and Termini as a standard. Findings: The fuzzy information measure is widely used for characterizing and quantifying fuzzy unpredictability and vagueness. A novel parametrically extended exponential information measure on a fuzzy set framework has been presented to address this. Once the validity of the proposed information measure is established, several features are also provided. Novelty: A new parametrically extended exponential information measure on fuzzy set framework has been introduced. The unique quality of the suggested fuzzy information measure is found in its parameters. The proposed measure of information is substantial and justifiable; it reduces to the present information measure if the parameters are substituted with a suitable value. Furthermore, certain notable and interesting properties of this information measure have been studied. Consequently, from an application standpoint, the stated information measure is more adaptable. Mathematics Subject Classification 2020: 94 D05

Keywords: Fuzzy set, Information measure, Fuzzy entropy, Parametric exponential measure, Uncertainty
Advanced Detection of Acute Lymphoblastic Leukemia Using Integrated Deep Features and Metaheuristic Algorithms
Authors:   Assistant Professor, Department of Electronics and Communication Engineering, Sri Sai Ram Engineering College, Chennai, Tamil Nadu, India, Alagu S , Kavitha G , Bagan K Bhoopathy
Published: November 2024

Objectives: Acute lymphoblastic leukemia is one form of blood cancer. This research work suggests the impact of meta-heuristic feature optimization techniques on leukemia diagnosis. Methods: ALL-IDB2 image database is utilized for this purpose which is publicly available. Techniques for pre-processing images include scaling, SMOTE, and augmentation. Segmentation of the nucleus plays a vital role in detecting leukemia. As a novelty, two distinct deep networks, SegNet and ResUNet are deployed for this purpose in place of conventional segmentation techniques. ResUNet performs better than SegNet with a 0.98 accuracy rate. From the segmented images, about 6144 deep features are extracted using the Xception, Inception-v3, and ResNet50 models. The robust features are selected using mRmR and LASSO methods. The features from the LASSO method are taken for further processing based on the ANOVA test results. Utilizing the whale and moth flame optimization techniques, these features are optimized. SVM and Twin-SVM are used as classifiers in the proposed work. The distinctiveness of the work lies in its combination of metaheuristic algorithms and deep feature integration, which improves detection accuracy. Findings: It is found that the optimized features obtained from whale optimization give an accuracy of 0.9828 whereas the obtained accuracy is only about 0.9478 without using the optimization algorithm. Novelty: The integration of metaheuristic optimization and deep features is introduced in the proposed work to enhance leukemia detection accuracy. The suggested work will definitely help clinicians to make more accurate decisions on acute lymphoblastic leukemia diagnosis.

Keywords: Inception, Xception, LASSO, Feature concatenation, Whale Optimization, Twin-SVM
Comprehensive Characterization of the Siddha Herbo-mineral Formulation Vaalai Rasa Mezhugu using X-ray Diffraction and Fourier Transform Infrared Spectroscopy Techniques
Authors:   PG Scholar, Department of Gunapadam (Siddha Pharmacology), National Institute of Siddha, (Affiliated with the Tamil Nadu Dr.M.G. R Medical University) Ministry of Ayush, Chennai, Tamil Nadu, India, Balasubramani Abarna , Tamilselvan Senthan , Pazhani Shanmugapriyan , Periyasamy Manivannan , antonyraj Kiruba Annammal Paul abraham , Annamalai Siva
Published: November 2024

Background: “Vaalai Rasa Mezhugu” is a herbo-mineral formulation widely used in Siddha medicine prepared according to the process found in Siddha marunthu sei perumuraigal. Traditionally the chosen formulation has been prescribed for the management of Soolai (Throbbing pain), Mudakku vaatham (Arthritis), Kandamaalai (Cervical lymphadenitis), Pauttiram (Fistula), Araiyappu (Lymphnode related neoplasia). Objective: The aim of the research work was to characterize the chemical composition of the drug using XRD and FTIR. Method: The formulation was prepared as per the literature and then subjected to quantitative analysis with XRD and FTIR. Findings: The XRD analysis showed the presence of sylvine and zinc sulfide and the FTIR analysis showed the presence of hydroxyl, carboxylic acids, amines, aromatic compounds, hydrocarbons, and carbonyl groups. Novelty: This study provides a novel chemical characterization of the Siddha formulation "Vaalai Rasa Mezhugu" using XRD and FTIR, revealing its potential antioxidant, antimicrobial, and anti-inflammatory properties. It bridges traditional knowledge with modern scientific validation, encouraging further pharmacological research.

Keywords: Vaalai Rasa Mezhugu, XRD, FTIR, Siddha medicine, Internal medicine
Formulasi dan Validasi Instrumen Kesediaan Penggunaan IoT dalam Pengesanan Kebakaran Rumah Kediaman
Authors:   Department of Architecture, Faculty of Engineering & Built Environment, Universiti Kebangsaan Malaysia, Md Zin Rabeah , Che Ani Adi Irfan ,   Department of Architecture, Faculty of Engineering & Built Environment, Universiti Kebangsaan Malaysia, Mhd Noh Nur ‘Amirah ,   School of Building Surveying, College of Built Environment, Universiti Teknologi Mara, Hassin Mohd Asrul ,   School of Building Surveying, College of Built Environment, Universiti Teknologi Mara, Chohan Afaq Hyder ,   Department of Architecture, Ajman University, UAE
Published: November 2024

This study focuses on developing and validating an instrument to measure the readiness for Internet of Things (IoT) integration in fire detection systems for residential housing types. The main objective is to develop a valid and reliable survey instrument to assess users’ readiness to accept and use IoT technology in the context of home fire safety. The research methodology involves a combination of the Technology Readiness Index (TRI) Theory and the Technology Acceptance Model (TAM) as the theoretical basis for the development of instrument items. This process was followed by content validation involving six expert panel members appointed in the field of fire safety. Survey questions were distributed to experts via email. These experts assessed the proposed items’ appropriateness, clarity, and relevance. The initial instrument consisted of 45 items covering the main dimensions of TRI (optimism, innovation, discomfort, insecurity), TAM constructs (perceived usefulness, perceived ease of use, and behavioral intention), and Readiness to use IoT for fire detection at home. The findings were analyzed using the Content Validity Ratio (CVR) and Content Validity Index (CVI) methods. Through the content validation process, 7 items were revised or filtered to produce a final instrument with 38 items. Findings show that the developed instrument has good content validity, with a satisfactory Content Validity Ratio (CVR) and Content Validity Index (CVI). Reliability analysis indicates high internal consistency across all dimensions of the instrument. This study contributes to the literature by providing a validated instrument to measure IoT integration readiness in residential fire detection systems. This instrument can be used by researchers, policymakers, and industry professionals to assess and predict IoT technology readiness in the context of home fire safety.
Effect of Nano Composite Boron Carbide on the Mechanical and Corrosion Behaviour of Aluminium Matrix Composite
Authors:   aMaterial Science Program, Department of Applied Physics, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia, Samsu Zaifol ,   Material Technology Group, Industrial Technology Division,  Malaysian Nuclear Agency, Bangi, 43000 Kajang, Selangor, Malaysia, Othman Norinsan Kamil ,   aMaterial Science Program, Department of Applied Physics, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia, Md Jamil Mohd Suzeren ,   Department of Science Chemistry, Faculty of Science and Technology,  Universiti Kebangsaan Malaysia, 43600 Bangi , Selangor, Malaysia, Yazid Hafizal ,   Material Technology Group, Industrial Technology Division,  Malaysian Nuclear Agency, Bangi, 43000 Kajang, Selangor, Malaysia, Alias Mohd Sofian ,   Material Science Program, Department of Applied Physics, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia
Published: November 2024

This study examined the use of stir casting to create an aluminum-nanoscale boron carbide composite. Following the sample’s solidification, mechanical and physical tests are carried out to determine the density and hardness. Tafel polarization in a 3.5% NaCl solution was utilized to determine the composite’s corrosion behavior, and tensile strength and hardness characterization techniques were employed to determine its mechanical characteristics. After the stir casting process, the surface morphology of the metal and the dispersion of boron carbide particles on the matrix were examined using a field emission scanning electron microscope (SEM). The obtained powders and matrix samples were examined using X-ray diffraction (XRD) analysis to determine the phase and if reinforcement particles (B4C) were present in the composite samples. The mechanical, microstructural, and corrosion investigations were used to evaluate the performance of the composites. The homogeneous distribution of the reinforcing particle was observed by the inspection of micrographs. The results showed that the corrosion rate of the aluminium matrix composite was lower than that of the base alloy in a 3.5% NaCl solution. Simultaneously, the composite’s corrosion rates escalated as the B4C concentration in the aluminum matrix grew. Hardness investigation has demonstrated that an increase of B4C content in the aluminium matrix enhanced the hardness rating. In the tensile test, the composite containing 0.8 weight percent B4C achieved a maximum strength of 149.95 MPa, which was roughly 48.64 MPa (32%) greater than the basic alloy.
Physico-Mechanical Properties of GGBS based Geopolymer Mortar for Semi-Rigid Binder: Impact of Crumb Rubber Replacement
Authors:   School of Civil Engineering, College of Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia, Helmi Abu Bakar Mohd Najmudin , Ahmad Zailani Warid Wazien ,   School of Civil Engineering, College of Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia, Apandi Nazirah Mohd ,   School of Civil Engineering, College of Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia, Abdul Mutalif Muhammad Syamim ,   School of Civil Engineering, College of Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia, Abdul Majid Anis Mawaddah ,   School of Civil Engineering, College of Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia, Sinarta I Nengah ,   Faculty of Engineering and Planning, Warmadewa University, Denpasar, 80239 Bali, Indonesia, Ayu Agustini Ni Komang ,   Faculty of Engineering and Planning, Warmadewa University, Denpasar, 80239 Bali, Indonesia
Published: November 2024

Geopolymer mortar presents a promising alternative to traditional cementitious materials, with the potential to significantly reduce CO2 emissions and support the development of sustainable construction materials. This study investigates the use of waste rubber tyres as a partial sand replacement in rubberised geopolymer mortar, addressing the environmental issue of tyre disposal. Annually, approximately one billion tyres reach the end of their life cycle, with only about 50% being recycled and the rest ending up in landfills. The research evaluates the effects of substituting sand with crumb rubber (CR) at 20%, 40%, 60%, and 80% proportions in geopolymer mortar, focusing on compressive strength, tensile strength, and workability. Results from workability tests revealed that increasing CR content reduced the slump flow by up to 30%. Furthermore, compressive and split tensile strength tests showed a decline in strength with higher CR content. The optimal replacement level of CR was found to be 20%, achieving a compressive strength of 33.35 MPa and a split tensile strength of 3.4 MPa using a GGBS-WCT mix. These findings underscore the potential of utilizing recycled waste materials as aggregate replacements, with significant implications for improving the sustainability and mechanical performance of construction materials.
SHEVCHENKO MEASURED AS A NATIONAL SYMBOL
Authors:   Taras Shevchenko National University of Kyiv, Kyiv, Ukraine, Radchuk Vitalii
Published: November 2024

The study highlights the actualization of Taras Shevchenko's creative heritage as a whole. This is done historically, in the context of war in Ukraine and in the aspect of international perception of the Ukrainian genius as a poet, artist, ambassador and symbol of the nation. Sharing his impressions of a bookworm, the author notes the contribution of the diaspora to the popularization of the artist, critically analyzes a number of recent editions of Shevchenko's works in Ukraine, ponders upon the reasons for Shevchenko's absence in the name lists of well-known Western poetry and art book series, probes the potential of global symbolization of Shevchenko's artistic world (primarily as a code), ultimately emphasizes that the scale and power of influence of the artistic genius, the interest in him depend on the achievements with which his people convince the planet. The author holds a view that Shevchenko's poetry and paintings are inseperable as a unique all-in-one system of imagery, with a potential to be actualized, revalued and symbolized internationally on a wider scale because Ukraine is destined to play a key role in the world's history nowadays. The essay traces some tendencies in the translations of Shebchenko's poetry into English. Modernist vers libre versions of interpretation along with analytical prose are contrasted to those done in verse and frowned upon as inadequate in style. A demand of a congenial translator for Shevchenko's "Kobzar" is emphasized.
IDEALOGICAL SENSES OF TARAS SHEVCHENK'S POEM "DREAM"
Authors:   Taras Shevchenko National University of Kyiv, Kyiv, Ukraine, Slipushko Oksana , Shchelkunova Olha ,   Taras Shevchenko National University of Kyiv, Kyiv, Ukraine
Published: November 2024

In this article the social and political ideas of Taras Shevshenko that declared in the poem "Son" are investigated. The specific of democracy and nationality in the outlook of the author is analyzed. The phenomenon "shevchenkizm" is underlined. The poem "Son" is a special idea manifest of artistic heritage of Taras Shevchenko. In this text we observe the author artistic interpretation of that historical situation. The historical role of Ukraine, its mission in European context are represented. Thinking about political and philosophical problems poet represent its as artistic categories. He interpret the social life in the artistic space. The nationalism of Taras Shevchenko is nationalism of a special type. It is based on the respect to every nation, on the recognition of its right to have own independent state. In this way Shevchenko think according to European democracy of that time. The idea of natural right for every nation to have own state was very popular and general in that political and social process. In general historical poems of Taras Shevchenko motivated national feeling of Ukrainian people, activated Ukrainian patriotic outlook. Taras Shevchenko understood the sense of Ukrainian history. Through history he determined political and social aim for Ukrainian nation.
EXPLORANDO EL CINE CARIBEÑO (EXPLORING CARIBBEAN CINEMA; EDS. LUIS ALBERTO NOTARIO AND BRUCE PADDINGTON)
Authors: Van Haesendonck Kristian
Published: November 2024

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