bluuebunny/crossref_metadata_2025 huggingface dataset:
Self Balancing Robot
Authors: Verma Sonu , Rajankar Omprakash
Published: December 2024

Abstract: Self-regulation robot is among the demainding topic and the working principle behind it is widely used in the
humanoids, transportation and robotic hands in industries for improvemising the capaibility and features. In this project, we are
working on the layout, control mechanisum, and draft of self-propelled robot. The robot is equipped with stepper motor, PID
controller, accelerometer and gyroscope that are used to measure the robot motions and along the x and y axis.
In addition, we have focused on the mathematical modeling and simulation of robot. This robot is designed to use analog data to
control vehicle speed efficiently. This data is used to feed variation in the pulse width of the motor to reset the robot angle to
zero
A Study on Performance of Al-Si alloy Bearing with SAE20W40 as Lubricants in Constant Load and Varying Speed Condition
Authors: P Sreenivasa Murthy B , P Prasad , B Thimmegowda M
Published: December 2024

Abstract: Bearing is used to carry radial loads of transmitting members in motion is called as journal bearing. Journal bearings
are considered as essential components of all the rotating machinery. Various researchers carried out analysis particularly on
copper based alloys published information related to Aluminium-Silicon alloy as a bearing material and relevant information
are not available. So in the present work it has been selected to carry out the study on performance of the Aluminium-Silicon
alloy bearing by considering the SAE20W40 grade lubricating oils as lubricating mediums and study has been carried out to find
out the maximum pressure distribution by using a journal bearing test rig. The Al-Si alloy as test bearing and test lubricating
oils SAE20W40 is run at different loads and speeds either by constant load and varying speed conditions (Example; 150N,
300rpm). It is made to run for 1hour to take maximum pressure value at angular rotation of 180̊. Sensor mounted on the bellow
of the housing which gives the pressure readings and the data are transferred to the WINDOWS DUCOM 2010 software, extract
condition of the bearings and gives the pressure distribution graphs as shown outcomes. In the results found by the graphs at all
operating conditions of constant load and varying speed. The maximum pressure distribution of SAE20W40 grade oil is
1744kPa at 500 rpm. It can be conclude that the load carrying capacity and frictional force which acts on the journal and
bearing material is safer, where frictional force decrease when speed increases.
Aluminium-SiC-B4C Hybrid Composites- An Overview on the Mechanical Properties
Authors: H Kashinath S V , N YogavardhanSwamy G , Venkatesh
Published: December 2024

Abstract: Modern growth necessitates the use of modern engineering materials for a variety of engineering applications, and
demand for these materials is continually rising. Metal matrix composite is a dependable supply of the material that has been
shown to be advantageous in every part of advancement for meeting such demands.With composites, materials are blended in a
way that allows us to maximize the benefits of their parent material while somewhat reducing the consequences of any
shortcomings. The word "Composites" simply refers to materials that have been combined to increase their qualities.Due to their
low density and good mechanical properties, improved corrosion resistance and wear, and low thermal coefficient of expansion
when compared to conventional metals and alloys, aluminium composites, among the available composite materials, are in
higher demand and are therefore frequently used in the aerospace and automotive industries. However, the properties of the
materials can he further enhanced with addition of the reinforcement materials like SiC, Al2O3 and B4C. Hence in the present
investigation an attempt is made to process a composite material with a combination of SiC and B4C as reinforcement materials
followed by the evaluation of the mechanical properties. The results of the study indicate a progressive strength in the processed
materials.
The Influence of Reinforcement Size and Shape on the Mechanical Properties of Composites
Authors: V Lavanya K , Venkatesh  , N YogavardhanSwamy G
Published: December 2024

Abstract: In the present work the effects of size and shape of reinforcements on the mechanical properties of composite material
is discussed in detail Since reinforcements have a dominant control on mechanical properties such as, tensile strength, stiffness,
toughness and fracture resistance. This work comprehensively assesses how the size and the shape of reinforcements, which can
be nano, micro and macroscopic, and can be fibers, particles, or platelets, affect the behaviour of the resulting composites. Both
numerical and experimental approaches were used to investigate the interface adhesion, stress profile and fracture
characteristics as influenced by the kind of reinforcements. Specific outcomes suggest that the use of nano-sized reinforcements
results in enhanced values of toughness and thermal stability, when compared with the use of micro- and macro-sized
reinforcements of glass fibers in epoxy composites, which in turn results in improved tensile strength and bulk mechanical
stability. Reinforcement shape was also identified as playing a significant part; continuous fibers provided the best load-carrying
capability, spherical particles uniform stress distribution, while platelet strengthened impact strength of the composite. In
addition, the study on the hybrid reinforcement systems revealed the interaction and cooperation of different reinforcement types
to design composite properties for certain industries. The findings of the current study offer corollary guidelines on the
development high-performance composites with enhanced mechanical features and fathom the innovative research solutions for
the existing flaws such as testing methodologies and bio- spheres reinforcements.
SUHU KERUT DAN KETAHANAN RETAK KULIT KELINCI (Oryctolagus cuniculus) SAMAK PADA BERBAGAI KONSENTRASI MIMOSA
Authors: Muhammad Bangun Prayogo , Pancapalaga Wehandaka
Published: December 2024

Potensi kulit kelinci di Indonesia sangat melimpah. Itu membuat peningkatan limbah kulit. Oleh karena itu, perlu dilakukan penyamakan agar kulit kelinci dapat bertahan lebih lama. Penelitian ini bertujuan untuk mengetahui mimosa pengaruh konsentrasi terhadap suhu kerut dan ketahanan retak untuk mengetahui tingkat konsentrasi mimosa terbaik. Metode penelitian yang digunakan adalah rancangan acak lengkap (RAL), dengan perlakuan konsentrasi mimosa : 5%, 10%, 15%, 20%. Variabel yang diukur adalah suhu kerut dan ketahanan retak. Hasil yang diperoleh dari pengaruh konsentrasi mimosa terhadap nilai suhu kerut tertinggi 20% sebesar 84,33 oC dan terendah pada 5% adalah 70,33 oC. Diperoleh hasil konsentrasi terhadap ketahanan retak nilai terendah 5% adalah 4,75 dan nilai tertinggi 20% adalah 5,32. Kesimpulan dari hasil penelitian, semakin tinggi tingkat mimosanya diberikan, hal ini akan meningkatkan suhu kerutan pada kulit kelinci tetapi tidak berpengaruh menuju tahan retak. Kadar konsentrasi mimosa terbaik adalah sebesar 20%
The Political View of Muhammadiyah; Does It Closer to The Welfare State?
Authors: Maulana Angga Fajar
Published: December 2024

This article discusses Muhammadiyah's political views in the context of the organization's relationship with the concept of the welfare state. As one of the largest Islamic organizations in Indonesia, Muhammadiyah has a significant role in political and social dynamics in this country. This study explores whether the values ​​and policies promoted by Muhammadiyah are closer to the principles of a welfare state, which emphasizes social equality, economic justice, and public services. Using a qualitative approach, this research analyzes various Muhammadiyah documents, policies, and official statements, as well as their historical and political context. The findings show that Muhammadiyah consistently encourages strengthening the role of the state in ensuring the welfare of society, while still maintaining Islamic principles and political independence. This study offers a new perspective on Muhammadiyah's contribution to realizing a just and civilized social order in Indonesia.
The Theological Value of Al-Ma’un in Free Lunch Policy: An Islamic Ethical Perspective on Social Empowerment
Authors: Zuhdi Andifa Nurasyam
Published: December 2024

Providing free lunches is one of the innovations to prepare Indonesia's golden generation. This policy focuses on improving the nutrition of children and pregnant women. By providing free lunches, it is hoped that it will have a domino effect on the community. Of course, this policy must also be based on the ethics that apply in Indonesia. The free lunch policy has also gone through a series of in-depth scientific studies. Of course, this research will have a significant positive impact on society, considering that there is still a lot of inequality and poverty in Indonesia. Programs that are classified as social policies in economics are usually called "Robin Hood" policies. Considering this big policy, it is hoped that there will be even and special support for people who need it. The government also needs to develop a powerful formula so that this policy can be realized and evenly distributed, especially in remote and underdeveloped areas in Indonesia. Of course, the main goal of a free lunch policy is to effectively reduce inequality and promote a fair allocation of economic resources.
Study of iron-based composite materials using modelling and simulation
Authors: Adamko Justin , Provazkova Livia , Oleksakova Denisa
Published: December 2024

Composite materials are materials composed of two or more components that have different physical and chemical properties. These properties complement each other to create a material with unique properties that cannot be achieved by using the individual components alone. Modelling the effect of preparation processes on the properties of composite materials is an important tool to predict the properties of a material prior to its manufacture. This can help in optimizing the preparation technology and obtaining the desired material properties. In the present work the topicality of the problem of iron-based composite materials and the possibilities of modelling and simulation of selected models are presented.
Design of an affordable dynamic arm support for motorized wheelchairs
Authors: Campeau-Lecours Alexandre , Larouche Charles , Doyon Charles , Latour Simon , Laliberte Thierry , Roy Jean-Sebastien , Flamand Veronique
Published: December 2024

Upper limb impairments, resulting from various neurological and neuromuscular conditions, significantly impact daily activities and limit social participation. Assistive technologies, particularly dynamic arm supports, offer promising solutions to enhance independence for individuals facing these challenges. This paper presents the development of an affordable dynamic arm support, designed with a focus on static balancing. The support utilizes a four-bar linkage mechanism to allow smooth vertical movement while maintaining the orientation of the armrest. Furthermore, the integration of rotational and prismatic joints enhances the device's adaptability, enabling horizontal movements. Through comprehensive mathematical modeling and prototype testing, we introduce a cost-effective arm support that effectively counterbalances the arm's weight, ensuring ease of movement and stability across various spatial orientations.
Intellectual capital valuation in digital economy: a review of corporate and national perspectives
Authors: Dancakova Darya , Safar Leos
Published: December 2024

Intellectual capital (IC) has emerged as a critical driver of organizational value and competitive advantage in the knowledge-based economy. Unlike tangible assets, IC encompasses intangible assets such as human capital, structural capital, and relational capital, which collectively contribute to the innovative capacity and strategic positioning of firms and economies. Despite its significance, measuring intellectual capital poses substantial challenges due to its intangible nature and the lack of standardized valuation methods. This paper aims to provide a brief overview of the components and methods used in the measurement of intellectual capital at both corporate and national levels.
The importance of logistics in the circular economy of agricultural enterprises
Authors: Kacprzak Martyna , Kozaryn Maciej , Kurowski Mateusz
Published: December 2024

The article is intended to show the role of logistics in the circular economy. This is because it encompasses the actual flow of products from their source of production to the final consumer, taking into account all the tasks and activities involved, ensuring efficient, sustainable and economic processes. Circular economy aims to maximise product value through eco-design, increased sustainability, improved quality, eco-efficiency and the widespread use of renewable materials. This approach promotes waste reuse, recycling and recovery, as well as treating waste as a valuable resource. The agricultural industry deserves special attention in the context of the circular economy, so improvements have been proposed to change the agricultural enterprise to a greener and more practical one that applies the principles of the circular economy. Thus, biogas production, the transportation of slurry via pipeline system and the creation of an on-site photovoltaic panel farm were suggested. The application of these improvements could make the company independent and use only its resources. Furthermore, by using renewable energy sources, the company could increase its competitiveness in the market, become an independent entity and reduce its operating costs, all while increasing its efficiency.
Factors shaping Indonesian preservice math teachers’ digital media adoption in online mathematics teaching practice: An instrument development and validation study
Authors: Ishartono Naufal , Halili Siti Hajar binti , Razak Rafiza binti Abdul , Jufriansah Adi
Published: December 2024

Numerous studies have examined the development of instruments to identify factors influencing preservice teachers' integration of technology in teaching practices. However, limited research has been dedicated to designing instruments specifically tailored to assess mathematics preservice teachers' integration of Digital Mathematics Learning Media (DMLM) during online teaching practice. This gap is particularly pertinent in the Indonesian context, where assessing future teachers' competencies is crucial. Addressing this gap, the present study endeavors to develop and validate an instrument to identify the factors influencing Indonesian Preservice Mathematics Teachers' (PSMTs) integration of DMLM in online teaching practice. The instrument's theoretical foundation is derived from the Technological Pedagogical Content Knowledge (TPACK) framework, with an emphasis on the Math-TPACK domain, and the Theory of Planned Behavior, focusing on beliefs related to DMLM and online learning. The research employed the ADDIE model for instrument development, combined with Exploratory Factor Analysis (EFA), involving a sample of 303 Indonesian preservice mathematics teachers. The study resulted in the development of a questionnaire comprising 59 indicators across four domains: Math-TPACK, Beliefs on Online Learning, Beliefs on DMLM, and the Use of DMLM. This instrument provides a robust tool for policymakers and educators to identify critical factors affecting PSMTs' effectiveness in online mathematics teaching. Additionally, it offers insights for designing targeted interventions to enhance the quality of online teaching practices.
Horizontal and vertical mathematization processes of 10th grade students: The case of Law of Sines
Authors: Nguyen Quoc Ai , Nguyen Ngoc-Giang
Published: December 2024

Realistic Mathematics Education (RME) has gained significant attention in Vietnam over the past decade due to its potential for enhancing mathematics instruction. This study investigates the process of mathematicization undertaken by students as they transition from solving a real-world contextual problem to discovering and applying the Law of Sines. The primary problem involves determining the angle formed by the crossbar and the hanging rope of a disco ball. Guided by the principles of RME, the mathematicization process encourages students to model this scenario as a triangle with two given side lengths and a specified angle between one side and the base. With teacher facilitation, students construct a general mathematical model and subsequently reinvent the Law of Sines. They apply this law to solve the initial problem and further extend their understanding by tackling a similar contextual scenario. The study involved 40 students, who engaged with worksheets designed to present relevant problems. Their problem-solving processes were documented and analyzed using qualitative methods. The findings contribute to the development of a teaching approach for introducing the Law of Sines within the framework of RME, specifically tailored to the Vietnamese educational context. This approach underscores the progression of students' understanding through the integration of contextual problem-solving and theoretical reinvention.
Statistical literacy in primary education: An analysis of Indonesian fifth-graders' data interpretation and analysis skills
Authors: Hasanah Uswatun , Putrawangsa Susilahudin , Setiawati Farida Agus , Purwanta Edi
Published: December 2024

Statistical literacy is an essential competency in today’s data-driven society. However, research in this field often overlooks primary-level students, focusing predominantly on those in higher education. To address this gap, the present study evaluated the statistical literacy of 50 fifth-grade students in Indonesia, with a focus on their abilities in data analysis and interpretation. Utilizing a descriptive cross-sectional design, the study employed a written test grounded in real-world data scenarios, adapted from established theoretical frameworks. The assessment included various data representations—pictograms, bar charts, tables, and line charts—designed to evaluate students’ skills in comprehension, comparison, and interpretation. The results indicate that the majority of students operated at an Idiosyncratic level, demonstrating limited capacity for data interpretation, while a smaller proportion reached the Transitional level; notably, no students attained Quantitative or Analytical proficiency. These findings underscore the urgent need for curriculum reforms to enhance both computational and analytical skills at an early stage, thereby equipping students with the foundational competencies required for advanced data reasoning. Future research should investigate pedagogical strategies that can bridge early-stage statistical literacy with the demands of higher-level statistical reasoning, ensuring students are better prepared for a data-intensive world.
Revealing the dominant metacognitive activities of high school students in solving central tendency and dispersion problems based on gender
Authors: Henra Kiki , Budayasa I Ketut , Ismail
Published: December 2024

Research on the relationship between gender and metacognition in mathematical problem-solving has yielded inconsistent findings. Some studies suggest that gender influences metacognitive activities, while others report no significant differences. This study seeks to explore metacognitive activities during each stage of statistical problem-solving among two 12th-grade students with contrasting gender expressions: a feminine-expressing female and a masculine-expressing male. The instruments utilized in this research include the Bem Sex Role Inventory (BSRI) gender questionnaire, a mathematical ability test, a statistical problem-solving task, and an interview guide. Data collection was conducted in two phases: the BSRI questionnaire and mathematical ability test were used to classify participants, followed by problem-solving tasks and semi-structured interviews to capture their metacognitive processes. Employing a descriptive exploratory design with a qualitative approach, the study applied thematic analysis to organize and interpret data from task performance and interview transcripts. These findings were further synthesized into hierarchical diagrams to illustrate the dominance of metacognitive components at different problem-solving stages. Results indicate that the feminine-expressing female predominantly utilized metacognitive knowledge, specifically declarative knowledge, during the problem-understanding phase. In contrast, the masculine-expressing male demonstrated more reliance on metacognitive regulation, particularly in planning and monitoring, during the problem-implementation stage. These findings underscore the importance of developing inclusive curricula and differentiated teaching strategies to enhance metacognitive skills across diverse student populations.
Predictive analysis of independent learning bearing on students’ mathematics performance in Davao de Oro, Philippines
Authors: Cabilan Judiel B. , Peteros Emerson D.
Published: December 2024

The abrupt transition from face-to-face to remote learning due to the COVID-19 pandemic has made independent learning the dominant pedagogical framework globally. As students return to in-person education, there is an increasing expectation for them to demonstrate autonomy in their learning and its impact on academic outcomes. This study aims to evaluate students' level of independent learning across cognitive, metacognitive, and motivational strategies, assess their mathematics performance, and identify which learning strategies predict their performance in mathematics. A descriptive correlational research design was employed to examine the independent learning levels and mathematics performance of secondary school students in Davao de Oro, Philippines. The findings revealed that the students exhibited high levels of independence in their mathematics learning, particularly in cognitive, metacognitive, and motivational strategies, with metacognitive strategies receiving the highest ratings. Additionally, students achieved very satisfactory results in their mathematics courses. A multiple linear regression analysis identified that only cognitive and motivational strategies significantly predicted mathematics performance, with motivational strategies emerging as the strongest predictors. In contrast, metacognitive strategies were found to be non-significant predictors, which contradicts existing literature. These findings provide valuable insights for educational stakeholders to enhance students' independent learning, specifically focusing on cognitive and motivational strategies, to further improve mathematics performance.
FOREIGN ECONOMIC COOPERATION OF KYRGYZSTAN IN THE EAEU: PRIORITIES AND EXPECTATIONS
Authors:   American University of Central Asia, MATEEVA K.M. , MAZUR L.V. ,   Synergy University
Published: December 2024

The purpose is to analyze the processes of foreign economic cooperation of the Kyrgyz Republic after joining the Eurasian Economic Union (EAEU) and to identify the main areas of regulation of foreign economic activity within the EAEU from the point of view of coordinated policy. The institutional framework for the development of foreign economic cooperation of the Kyrgyz Republic within the EAEU is presented through the study of current regulations that form the possibilities of harmonization, unification and implementation of legislation aimed at convergence of the rights of the EAEU member states.
It should be noted that according to the results of the first half of 2024, trade turnover between the countries increased and researchers predict the creation of favorable conditions for its further growth. The relationship between legal norms and economic activity of the Kyrgyz Republic is considered. Some suggestions are presented to expand the potential for interaction and application of unification instruments of the EAEU Treaty.
Among the problems requiring prompt solutions, the authors identified the need to adjust the regulatory framework. Among the development of promising areas, the demand for digitalization of foreign economic activity processes and adjustment of customs instruments is noted.
It is substantiated that the unification of law is appropriate in areas where it is possible to use administrative and legal methods of regulating economic activity, as well as technical characteristics, norms and standards that provide an organizational framework for the interaction of economic actors. Some recommendations are given on the process of convergence of norms in the field of the financial market and taxation within the EAEU.
As a result, the authors note that the industrialization of the republic was stimulated by participation in the EAEU and the attraction of Russian investments.
Hybrid Ensemble Lightweight Cryptosystem for Internet of Medical Things Security
Authors: M. Swetha  , G. Appa Rao
Published: December 2024

Internet of Medical Things (IoMT) is a fast-developing area that includes the use of connected medical devices to enhance patient care and expedite the procedures involved in the delivery of healthcare. Concerns about the safety and confidentiality of patient information are a roadblock to the broad use of telemedicine technologies like IoMT. Encryption is an essential part of IoMT security, and there is a wide variety of encryption methods that are used to safeguard sensitive patient data.  This work implemented a hybrid ensemble lightweight cryptosystem (HELC) using probabilistic rivest cipher 6 (PRC6) encryption and modified feistel block cipher (MFBC) approaches. Initially, the data from users are applied to PRC6 encryption, which is symmetrical encryption and provides security at in abstract level. So, to provide more security to data, the MBFC is applied to PRC6 outcome. Then, the resultant data transferred over the IoMT environment to the destination. Finally, the MBFC decryption and PRC6 decryption operations are performed at receiver side, which resulted in decrypted outcome.  The simulations results show that the proposed HELC consumed 0.0021 seconds of encryption time, and 0.000276 seconds of decryption time, which are lesser as compared to other approaches.
Enhancing Ophthalmological Diagnoses: An Adaptive Ensemble Learning Approach Using Fundus and OCT Imaging
Authors: LAVUDIYA Narasimha Swamy , C.V.P.R Prasad
Published: December 2024

This study presents an innovative Ensemble Disease Learning Algorithm (EDL) for the detection and classification of retinal diseases using fundus images. We enhance our method by incorporating deep learning techniques and multi-modal imaging data, including optical coherence tomography (OCT) images alongside fundus photographs, to provide a more comprehensive understanding of retinal pathology. The advanced EDL integrates Convolutional Neural Networks (CNNs) and attention mechanisms with Capsule Networks (CapsNet) and Support Vector Machine (SVM) classifiers for more nuanced feature extraction and classification. We introduce a novel ensemble adaptive weighting approach that dynamically adjusts classifier weights based on performance across disease types and severity levels, significantly improving the algorithm's handling of complex and rare cases. To enhance model interpretability, we implement an explainable AI component that provides visual heatmaps of the most significant regions for each diagnosis to clinicians. We evaluate the enhanced EDL on a large, diverse dataset encompassing multiple retinal diseases, including diabetic retinopathy, age-related macular degeneration, and glaucoma, across various ethnicities and age groups. Our results demonstrate superior accuracy, sensitivity, and specificity compared to our previous model and other state-of-the-art approaches. A prospective clinical validation study assesses the algorithm's real-world performance. This research advances automated retinal disease diagnosis by making it more robust, accurate, and clinically relevant, potentially improving patient outcomes and global eye care through early disease detection and treatment planning.
Deep Learning Algorithm Design for Discovery and Dysfunction of Landmines
Authors: S. Leelavathy  , S. Balakrishnan  , M. Manikandan  , J. Palanimeera  , K. Mohana Prabha  , R. Vidhya
Published: December 2024

Deep Learning is a cutting-edge technology which has a noteworthy impact in the real-world applications. The multi-layer neural nets involved in the blueprint of deep learning enables it to deliver a comprehensive decision-making system with quality of “think alike human cerebrum”. Deep Learning assumes an essential part in various fields like horticulture, medication, substantial business and so forth. Deep Learning can be well prompted in the remote sensing applications especially in perilous military applications. The location of land mines can be detected using a deep learning algorithm design technique aided with distinctive machine learning tools and techniques. The intelligent system designed by the deep learning process involves a massive dataset including the assorted features of the landmines like size, sort, dampness, ground profundity and so on. Incorporation of Geographical Information System can give a prevalent statistical analysis of the varied landmines. The multiple layers present in the deep learning neural schema may increase the feature extraction and the knowledge representation through increase in the complexities of landmines’ input sets. The likelihood of brokenness of landmines can be increased by the utilization of deep learning prediction model which enormously helps the survival of militaries, creating a social effect.
Characterization of Destructive Nodes and Analysing their Impact in Wireless Networks
Authors: Srinivas Aluvala  , V. Srikanth
Published: December 2024

Mobile Ad hoc Networks (MANETs) are being used to meet new requirements for efficiency and coordination in a variety of new public and residential contexts. Certain essential functions, including as resource management among network nodes, trust-based routing, and security for network maintenance, are not performed as well as they should because of the dynamic nature of wireless networks. Ad-hoc networks can also be attacked from different tiers of a network stack, and they are susceptible to secure communications. Destructive nodes have the ability to alter or reject routing parameters. They may also provide bogus routes in an attempt to intercept source data packets and pass them through. To handle the complexity arising from secure data exchange, some protocols have been developed. However, not all attack types can be detected and eliminated by a secure protocol in every scenario. Since security is not a feature that is built into MANETs, new secure wireless protocols need to concentrate on these issues. Thus, the analysis of destructive nodes' characteristics and effects on wireless networks in this research paper examined the behaviour of multiple attacks, their activities through neighbour selection, the establishment of paths from sources to destinations, and the dissemination of attack presence detection information to regular devices during path discovery and data transmission mechanisms. In order to categorize as legitimate, nodes must be constructed with safe transmission knowledge to provide trustworthy communication, validation, honesty, and privacy.
Advancing Brain Tumour Detection and Classification: Knowledge Distilled ResNeXt Model for Multi-Class MRI Analysis
Authors: Prathipati Silpa Chaitanya  , Susanta Kumar Satpathy
Published: December 2024

Accurate and timely diagnosis of brain tumors is crucial for optimal patient outcomes. Despite advancements in medical imaging and deep learning, the accurate classification of brain tumors remains a significant challenge. Existing methods, including CNNs and VGG16, often struggle to differentiate between tumor types and capture subtle radiological features. To address these limitations, we propose a novel Knowledge Distilled ResNeXt architecture. By transferring knowledge from a complex teacher model, our model effectively learns discriminative features and improves classification accuracy. Our comprehensive experiments demonstrate the superiority of the Knowledge Distilled ResNeXt in classifying brain tumors (glioma, meningioma, pituitary tumor, and no tumor) compared to state-of-the-art methods. This research contributes to the development of more effective diagnostic tools and improved patient care.
Developing an AI-Powered Interactive Virtual Tutor for Enhanced Learning Experiences
Authors: P. Rathika  , S. Yamunadevi  , P. Ponni  , V. Parthipan  , P. Anju
Published: December 2024

The integration of artificial intelligence (AI) in education has opened new avenues for enhancing personalized learning experiences. This paper proposes the development of an AI-powered interactive virtual tutor designed to support students throughout their educational journey. The virtual tutor leverages advanced natural language processing (NLP) algorithms, sentiment analysis, and machine learning to engage students in real-time, providing tailored guidance, explanations, and feedback. By analyzing students' learning patterns, emotional states, and progress, the AI tutor offers personalized recommendations and interventions, enhancing both cognitive and emotional aspects of learning. The system’s interactive features, including voice recognition and conversational AI, allow students to interact naturally, facilitating a more engaging and immersive learning experience. This paper also presents the architecture of the proposed virtual tutor, key technologies involved, and its potential impact on student learning outcomes. Initial results demonstrate significant improvements in student engagement, satisfaction, and academic performance, suggesting that AI-driven virtual tutors could revolutionize personalized education..
Sequential Milkrun System
Authors: ÖZHAN DOĞAN Serap , Ahmet KARATAŞ  , Mücahit DEMİRCİOĞLU
Published: December 2024

Milk-Run system is a logistics supply method that aims to combine and place the products or materials required by companies into vehicles in the most efficient way. This system collects goods from multiple suppliers and ensures that vehicles are filled at an optimum level. It ensures controlled management of transactions with regular reporting, continuous monitoring and automatic information e-mails. Within the scope of the study, important processes related to the Milk-Run management process were emphasized and the reasons for the application were highlighted. Logistics and supply chain have played important roles in supporting the operations of businesses aiming to meet customers' demands. It is a sustainable management model that helps all businesses that implement it reduce their costs, optimize their processes and reduce their carbon footprint.
Penerapan Math-In: Mathematics Adventure Game Terintergrasi Augmented Reality Sebagai Inovasi Media Literasi Matematika Berbasis Gamification
Authors: Aghits Zulvia Rachmawati  , Isadur Rofiq
Published: December 2024

Mathematical literacy is an important factor in forming quality human resources. Someone wholiterate (literate) mathematics is not just understanding mathematics but also being able to use it in solving everyday problems. The problem is, Indonesian students' mathematical literacy skills are still very low. Based on survey resultsTrends in International Mathematics and Science Study (TIMSS) which is held every 4 years, in 2011 Indonesia was in 36th position out of 40 countries and in 2015 it was ranked 45th out of 50 countries, with a score of 397 and still below the international average score, namely 500. In addition, In the Program for International Student Assessment (PISA) survey, Indonesia is ranked in the bottom 10 of 70 countries, namely in 62nd position. This shows that Indonesian students have not shown satisfactory achievements. Therefore, mathematical literacy skills need to be improved, one of which is through MATH-IN. MATH-IN is a medium for learning mathematics through exploring games oradventure game which is integrated with augmented reality. Through MATH-IN, users will be invited to explore and explore further about mathematics, starting from basic concepts to its application in the form of games. MATH-IN will be designed in the form of an application mobile which contains games adventure which focuses on concepts, and solving actual problems related to mathematics in them. Technology integration augmented reality MATH-IN is able to combine multimedia into the real world using electronic devices, making it possible to provide information to students anytime and anywhere. The application of learning methods through games has great potential in honing brain skills for solving problems as well as becoming a motivational learning medium that can build student motivation in learning. Through MATH-IN goalsquality education as one of the pillars of SDGs 2030 can be achieved.
KONSEP KELUARGA SAKINAH MAWADDAH DAN RAHMAH MENURUT KIAI HUSEIN MUHAMMAD
Authors: Deny Marita Wijayanti  , Firda Imah Suryani
Published: December 2024

Penelitian ini berangkat dari hubungan gender dalam keluarga yang seringkali dipengaruhi oleh realitas budaya lokal di mana kontruks patriarki yang sangat tinggi. Setiap teori mengakui bahwa kontruksi sosial budaya berpengaruh atas peran pembagian yang dimainkan oleh laki-laki (suami) dan perempuan (isteri). Artinya konsep gender sangat berperan dalam menciptakan relasi antara laki-laki dan perempuan dalam keluarga untuk menghindari ketimpangan. Fokus dari penelitian ini adalah pemikiran Kiai Husein Muhammad tentang konsep gender dalam keluarga. Metode yang digunakan dalam penelitian ini adalah kualitatif dengan model systematic literatur riview serta pengambilan data secara langsung melalui wawancara dengan Kiai Husain Muhammad. Hasil dari penelitian ini menunjukkan bahwa konsep keluarga sakinah yakni pertama; memilih pasangan hidup berdasarkan keiman kepada Tuhan yang Maha Esa. Kedua; rumah tangga harus dilandasi cinta. Ketiga; membagun rumah tangga dengan nilai-nilai kesetaraan . Keempat; membagun rumah tangga yang baik dan dapat menyebarkan manfaat seluas-luasnya.
Uzaktan Eğitim Döneminde Suriyeli Sığınmacı Çocukların Yaşadığı Sorunlar: Şanlıurfa Örneği
Authors: Güneş Farize , Gülerce Hakan
Published: December 2024

2011 yılında Suriye'de yaşanan iç karışıklıklar, milyonlarca insanın göç etmesine sebep olmuştur. İnsanlar, daha iyi yaşam koşulları arayışı içinde farklı ülke ve şehirlere yönelmişlerdir. Türkiye, bu kitlesel göç akımından en fazla etkilenen ülkeler arasında yer almaktadır. Bu süreçte, Türkiye yaklaşık dört milyon yerinden edilmiş insana ev sahipliği yapmıştır. Göç, eğitim alanında önemli sorunları da beraberinde getirmiştir. Sığınmacı nüfusunun üçte birini eğitim çağındaki çocuklar oluşturmaktadır. Bu durum, Türkiye'deki sığınmacı çocuklar için eğitim hakkının sağlanmasının kritik önemde olduğunu ortaya koymaktadır. Ancak, sığınmacı çocukların bu haktan faydalanmaları önünde ekonomik güçlükler, barınma sorunları gibi engeller bulunmaktadır. 2019 yılında başlayan Covid-19 pandemisi bu sorunları daha da artırmıştır. Bu çalışma, Suriyeli sığınmacı çocukların pandemi sürecinde uzaktan eğitime geçişte yaşadıkları zorlukları, uyum süreçlerini ve eğitimlerinin önündeki engelleri incelemeyi amaçlamaktadır. Nitel araştırma yöntemi kullanılan bu çalışmada, veri toplama sürecinde yarı yapılandırılmış derinlemesine görüşmelerden yararlanılmıştır. Araştırma bulguları, pandemi döneminde uzaktan eğitim sürecinde sığınmacı çocukların teknolojik imkân eksikliği, ekonomik zorluklar, barınma problemleri ve dil engelleri ile mücadele ettiklerini ve bunun sonucunda öğrenme kaybı ve okul terk oranlarında artış olduğunu göstermektedir.
Examination the Academicians’ Opinions on Academic Freedom in the Turkish Higher Education System in Terms of Some Variables
Authors: Baytaş Özlem , Çoban Ömür , Bozkurt Balcı Süheyla
Published: December 2024

The aim of this study is to examine the opinions of academicians working in the higher education system in Turkey about academic freedom according to demographic variables. For this purpose, it has been investigated whether there is a significant difference in the teaching, research, and publication subdimensions at the implementation level of the Academic Freedom Scale according to gender, administrative duty, age, seniority, year of duty, appellation, and faculty variables. This study has been conducted in descriptive survey model which is a quantitative research technique. The working group of this study consisted of 311 academicians working in Karamanoğlu Mehmetbey University, Aydın Adnan Menderes University and Kütahya Dumlupınar University in 2022-2023 education and training year. The data were collected with the personal information form containing demographic information and the Academic Freedom Scale consisting of 27 items. The data analysis was done with SPSS testing techniques which includes independent samples T-test and one-way ANOVA. Findings indicated that there was no significant difference between gender, age, faculty variables and the subcategories of academic freedom -teaching, research, and publication. On the other hand, the results show that academicians at the research sub-dimension have significance difference according to their seniority and administrative duty. At the same time, significance difference was seen in terms of office and appellation variables in teaching, research, and publication subdimensions. In line with these results, various studies can be carried out to create culture and raise awareness about academic freedom.
Suriyeli Göçmen Özel Gereksinimli Öğrencilerin Eğitsel Değerlendirme ve Tanılama Süreci: Rehberlik ve Araştırma Merkezi Personeli Görüşlerinin İncelenmesi
Authors: Kocaoğlu Abdulkadir , Güner Nevin
Published: December 2024

Türkiye, küresel düzeyde en büyük Suriyeli göçmen nüfusuna ev sahipliği yapmasına karşın, alanyazında Suriyeli göçmen özel gereksinimli öğrenciler (SGÖGÖ) ve bu öğrencilerin eğitimlerini konu alan sınırlı sayıda araştırma bulunmaktadır. Bu çalışmanın amacı, Suriyeli göçmenlerin yaşamlarını sürdürmeleri için kurulan Geçici Barınma Merkezindeki bir okulun özel eğitim sınıflarında öğrenim gören SGÖGÖ’lerin eğitsel değerlendirme ve tanılama sürecine ilişkin Rehberlik ve Araştırma Merkezi (RAM) personelinin görüşlerini incelemektir. RAM personelinin SGÖGÖ’lerin eğitsel değerlendirme ve tanılama sürecini nasıl yürüttüğünü, bu süreçte karşılaştıkları sorunları ve personelin talep ve önerilerini ortaya çıkarmayı hedefleyen bu çalışma, nitel araştırma yöntemi desenlerinden durum çalışması olarak tasarlanmıştır. Araştırmanın verileri yarı yapılandırılmış görüşme formu kullanılarak yüz yüze görüşmelerle toplanıp, betimsel olarak analiz edilmiştir. Verilerin analizi sonucunda sekiz temaya ulaşılmıştır. Çalışmanın sonuçları, RAM personelinin SGÖGÖ'lerin eğitsel değerlendirme ve tanılama sürecinde dil ve kültür farklılığından, uygun olmayan değerlendirme araçlarından ve bilgi ve deneyim yetersizliğinden kaynaklanan sorunlar yaşadığını göstermektedir. Ayrıca bu sorunların SGÖGÖ'leri uygun eğitim ortamına yönlendirmeyi zorlaştırdığı anlaşılmaktadır. Ulaşılan temalar alanyazınla karşılaştırılarak tartışılıp çeşitli öneriler sıralanmıştır.
İki Dilli Öğrencilerin Türkçe Yazma Tutumlarının Bazı Değişkenler Açısından İncelenmesi
Authors: Can Furkan , Kardaş Mehmet Nuri
Published: December 2024

Bu çalışmanın amacı; iki dilli öğrencilerin Türkçe yazma tutumlarının cinsiyet, sınıf düzeyi, baba eğitim düzeyi, anne eğitim düzeyi, evde konuşulan dil, evde TV izleme süresi, kitap okuma, günlük tutma durumu, okunan kitap türü değişkenleriyle ilişkisini tespit etmektir. Çalışma nicel araştırma modellerinden ilişkisel tarama modeline uygun olarak yapılmıştır. Araştırmanın çalışma grubunu Van ili merkez ilçelerindeki ortaokullarda öğrenim gören 207 iki dilli öğrenci oluşturmaktadır. Araştırmanın verileri “Yazma Tutumu Ölçeği” ve “Kişi Bilgi Formu (KBF)” ile toplanmıştır. Toplanan veriler SPSS 21 paket programı kullanılarak parametrik analiz teknikleri ile analiz edilmiştir. Çalışma sonucunda iki dilli öğrencilerin Türkçe yazma tutumlarının “yüksek” düzeyde olduğu tespit edilmiştir. Bağımlı değişkenin sınıf düzeyi, baba eğitim düzeyi, anne eğitim düzeyi, evde TV izleme süresi, kitap okuma, okunan kitap türü değişkenleriyle olumlu-olumsuz bir ilişkisinin olmadığı görülmüştür. Buna karşılık kadın öğrencilerin ve günlük tutanların yazma tutumlarının daha yüksek olduğu bulgulanmıştır. Ayrıca iki dilli öğrencilerin Türkçe yazma tutumlarında evde daha çok konuşulan dilin etkili olduğu sonucuna varılmıştır.
Detection of RPL-based Routing Attacks Using Machine Learning Algorithms
Authors: Aydın Burak , Aydın Hakan , Görmüş Sedat , Mollahasanoğlu Emin
Published: December 2024

This study analyzes various machine learning techniques for detecting attacks against Routing Protocol for Low-Power and Lossy Networks (RPL), a routing protocol commonly used in Internet of Things (IoT) applications. RPL is often employed in IPv6-based IoT applications that require low power consumption and limited bandwidth. The research reviews recent literature examining attacks on RPL-based networks and utilizes the ROUT-4-2023 dataset for detecting routing attacks. This dataset, created using the Cooja simulator, encompasses four types of routing attacks: Blackhole Attack, Flooding Attack, DODAG Version Number Attack, and Decreased Rank Attack. The attack types are detected using machine learning techniques like AdaBoost, KNN, Random Forest, Decision Tree, and Bagging. In the combined dataset, the Decision Tree and Bagging algorithm exhibited the highest performance with a 99.99% accuracy. To create a more accurate representation of the real world, we incorporate a 10% level of noise into the dataset. On the noisy dataset, Random Forest algorithm performed the best with about 84.80% accuracy. The high accuracy show that the employed methods can be effectively used as an Intrusion Detection System (IDS) to protect IoT networks. As a result, this study demonstrates that machine learning techniques offer a promising approach for detecting routing attacks in the RPL protocol. The findings provide useful information for researchers and practitioners in the field of IoT security. This study contributes to the potential of machine learning-based algorithms to enhance the security of IoT networks and contributes to future research in this area.
Long-Term Prediction of Coronary Artery Disease via Ensemble Machine Learning Algorithms
Authors: Aslan Şehmus
Published: December 2024

Coronary artery disease (CAD) is the leading cause of death worldwide, necessitating early detection methods that are non-invasive, cost-effective, and reliable. In this study, the effectiveness of various machine learning (ML) models in predicting CAD was evaluated, with a focus on addressing class imbalance using the Synthetic Minority Oversampling Technique (SMOTE). The Framingham CAD dataset was utilized, and SMOTE was applied with different k-values to balance the data, examining the impact on prediction performance. Eight significant features—age, diaBP, glucose, heart rate, sysBP, totChol, cigsPerDay, and BMI—were determined during preprocessing and used for further analysis. Among the models tested, the StackingC classifier demonstrated superior performance, achieving an accuracy of 95.81%, sensitivity of 95.9%, specificity of 95.7%, and an AUROC of 99.2% for k=1. These findings highlight the potential of the StackingC model as a robust tool for CAD prediction, offering a promising non-invasive method for early diagnosis.