bluuebunny/crossref_metadata_2025 huggingface dataset:
An Automated Timetable Generation System for Academic Expertise Matching
Authors: Arunachalam G  , Haripriya V
Published: March 2024

For educators, creating time tables is a laborious task that requires a lot of manpower and time. It will be easier to produce time tables automatically if an automatic time table generator is available. Our project's proposed solution will aid in its automatic generation and time-saving. It does away with the difficulty of manually creating and maintaining a schedule. We want to employ resource scheduling, heuristic, and genetic algorithms in our project to lessen the challenges associated with creating timetables. Several strategies are incorporated into these algorithms with the goal of making the search process more efficient. The number of subjects, teachers, workload of a teacher, semester, and subject priority are just a few of the inputs that the system will get. Based on these inputs, it will produce potential schedules for the working days.
Cyber Resilience Approaches for Cyber Physical Systems
Authors: Manjunath D  , Dr. M. N. Nachappa
Published: March 2024

Cyber-physical systems (CPS) integrate physical processes with computing, communication, and control systems to increase efficiency, reliability, and safety. However, these systems are also vulnerable to cyber attacks, which could have severe consequences, such as loss of life, property damage, and economic disruption. To ensure the safety and security of modern society, it is crucial to ensure that CPS are cyber- resilient, meaning they can continue to function and recover from cyber attacks. This requires a multi-faceted approach that includes secure design, risk assessment, monitoring and response, redundancy and backup, and training and education. By implementing these strategies, organizations can improve the cyber resilience of their CPS, reducing the risk of cyber attacks and promoting the safety and security of modern society.
Sign Language Recognition by Image Processing
Authors: Thiluckraj G K  , Dr. M. N. Nachappa
Published: March 2024

A prototype sign language interpreter that can converse in American Sign Language (ASL) is presented in this study. The visual stimulation of sign language aids in the development of speech and language. It promotes social contact, fosters the development of cognitive structures, and lessens harmful social behaviors. Early exposure to sign language supports language development in academic, social, and emotional domains. Building a user-hand gesture-only human-computer interface (HCI) is the foundation of the dependable paradigm. Using Python and OpenCV, hand gesture recognition is built using the theories of hand segmentation and the hand detection system. The training photos are labeled with different names based on what is in the database. A binary feature vector is created from each image. Convolutional neural networks (CNNs) and cameras are used to capture images from hand sign videos in real time, which are then used to carry out the feature extraction process. The algorithm generates output based on the projected maximum similarity between these features and the features of database photographs. With the aid of an application, this model provides adequate accuracy even in the absence of a constant or monochromatic background. The person's hand movements are captured on video with the camera; the video is subsequently processed and translated into text. The user hears the speech that has been transformed from the output. The suggested system recognizes letters, numbers, and certain common words in sign language. Raw photos and videos are transformed into corresponding text that can be read and comprehended by using image processing algorithms and neural networks to map the gesture to the right text in the training data. When paired with a sizable source database, this protocol will surely be highly beneficial for closing the communication gap between people who can talk and hear and those who cannot.
IoT Assistant-Based Secured System for Alzheimer’s Disease
Authors: G Anto Gabriel  , Dr. M N Nachappa
Published: March 2024

In many countries, the rise in the count of Alzheimer's disease (AD) is an indication that concerns. In order to prevent, detect and help people with AD, new techniques are required. These changes result in a decline in thinking ability, a type of intellectual capacity that is severe enough to interfere with daily life and independence. Relationships, emotions, and conduct are all impacted. When they lose track of familiar individuals or their connections to them, those with Alzheimer's disease are put in an awkward predicament. They tend to remain silent and avoid interacting with others on days when they are always uncomfortable, which is bad for their mental health. That makes it difficult for the patient and the guardians to stay in touch with one another. In order to protect the AD patient, the goal of this work is to build a working model for a system that provides psychological technical assistance and ensures secure transfer of data which may be inspected by a family member. The created transportable prototype can divide the identified images into two groups, including family and non-family persons, by using a Convolutional Neural Network (CNN). This framework combines the use of hardware with headphone-based IoT communication..
Development of Cyber Physical System Based Manufacturing System Design
Authors: Manikandan B  , Priyadharshini S  , Magesh Hariram K  , Girija P  , Sowmiya A
Published: March 2024

Cyber Physical System (CPS) is Informatics and computer science. Cyber physical manufacturing system is a new research field. In the fields of computer science and manufacturing science and technology Promote the Fourth Industrial Revolution known as Industry 4.0. CPS is generally focused. About the integration of the physical world and cyberspace. It`s the integration of communication, Computational, control, and physical elements. Currently, CPS is Science, government and industry. Systematic literature review on cyber. The physical system of the manufacturing system is not available. The purpose of the chapters in this bookis to gain insight into manufacturing systems and develop cyber-physical systems. Physical systems for intelligent manufacturing. CPS is written using the concept of CPS. A 5-tier architecture system for manufacturing systems. Continuous Key Release. It also describes the technology of cyber physical manufacturing systems. Combined with manufacturing, CPS enables intelligent manufacturing and provides technical support for manufacturing upgrades and conversions. This can be summarized in three aspects: internet-based manufacturing, process intelligence, and product intelligence. Future manufacturing is said to be personalized manufacturing based on cyber physical systems, intelligent manufacturing, digital manufacturing, and network-based manufacturing. CPS continues to transform the manufacturing trends of the industry, creating even more amazing value for future global manufacturing scenarios
Breast Cancer Detection System
Authors: Prof. R. Waghmare  , Ronak Jagade  , Swayam Chopda  , Varad Salgar
Published: March 2024

Breast cancer "is a major global health concern is breast cancer, for which early detection is essential to effective treatment and higher survival rates. In this work, we suggest a unique method for detecting breast cancer by using cutting-edge machine learning techniques on data from medical imaging tests, especially mammograms. Our approach combines feature extraction and deep learning methods to improve detection efficiency and accuracy. We performed tests on a sizable sample of mammography pictures, and the overall performance, sensitivity, and specificity showed promise. The suggested solution has the potential to improve patient outcomes and healthcare management by supporting radiologists in the early diagnosis of breast cancer..
SEM, XRD and FTIR Analysis of Fly Ash Polymer Composite and Investigate the Micro Structural Changes, Physical, Mechanical, Thermal Conductivity and Wear Behavior at Different Proportions
Authors: Patil Sharad Mahohar  , Pravin Tathod  , Lavina Talawale
Published: March 2024

Industrial waste such as fly ash poses environmental problems, yet it is utilized as an inexpensive and readily available construction material. However, these bricks have low strength. Thus, extensive research aims to increase the strength of these bricks. The current study develops a new systematic procedure to produce fly ash composite bricks with higher compressive strength. Here, fly ash is blended with cold-setting resin at varying proportions and water treated at different temperatures to find a solution for the brick industry. Under optimal test conditions, the obtained fly ash-resin powder bricks have a compressive strength, hardness, water absorption, density and thermal conductivity of 11.24MPa, 47.37HV, 19.09%, 1.68 g/cm3, and 0.055 W/mK respectively. The sliding wear behavior is also examined. X-ray diffraction, FTIR analysis and scanning electron microscopy are used to study the structure-property correlation of these composites.
Glycosylated Haemoglobin Testing: A Review
Authors: Akansha Naithani  , Sakshi Yadav
Published: March 2024

The following article discusses the discovery, biochemistry, laboratory determination, clinical applications, and error for glycosylated haemoglobin. There is no one test method that is appropriate for all applications, and the development of widely recognized standards and reference ranges is unlikely in the near year. Nonetheless, the introduction of glycosylated haemoglobin tests represents a significant step forward. They provide the most accurate way of determining diabetic management. As a result of a growing awareness that chronic hyperglycemia is a substantial predictor of long-term issues, there has been a surge in interest in diabetes management monitoring. As a result, the discovery of glycosylated haemoglobin came at an ideal moment; measuring it should provide a more objective control evaluation than previously achievable. Therefore, before this promise can be fully fulfilled, technological difficulties must be solved
An Efficient Segmentation and Classification of Brain Tumor Detection using Deep Learning
Authors: Ms. Vijaypriya V  , Mr. Gokul B  , Mr. Gopinath G  , Mr. Hariharan A
Published: March 2024

In medical diagnostics, the identification of brain tumors is a crucial endeavour that frequently necessitates the careful review of intricate imaging data. With the development of deep learning methods, especially convolutional neural networks (CNNs), automated brain tumor detection has become a viable way to help radiologists diagnose patients accurately and quickly. This study provides an extensive overview of current developments in deep learning approaches for brain tumor identification. The suggested techniques usually start with preprocessing medical images, like CT or MRI scans, and then use CNN architectures to extract features. Different CNN architectures, such as U-Net and conventional CNNs, have been used to extract discriminative characteristics from brain pictures. The performance of brain tumor detection systems has also been improved using transfer learning techniques, which make use of pre-trained models on sizable datasets. These results are especially encouraging when there is a shortage of training data. Additionally, research has been done on using ensemble learning approaches to strengthen the generality and durability of brain tumor detection models. By combining several base models into one prediction, these methods improve overall performance and lower the likelihood of overfitting. Furthermore, the incorporation of sophisticated regularisation methods such batch normalisation and dropout has enhanced the deep learning models' capacity for generalisation in brain tumor identification tasks. Moreover, the use of deep learning models in practical clinical environments demands the resolution of issues of uncertainty estimation and model interpretability
Object Detection, Convert Object Name to Text and Text to Speech
Authors: Ms. Sathya G  , Mr. Kamesh S  , Mr. Rishi Kumar S  , Mr. Saai Sabapathi
Published: March 2024

Visually impaired persons (VIPs) comprise a significant portion of the population, and they are present around the globe and in every part of the world. In recent times, technology proved its presence in every domain, and innovative devices assist humans in their daily lives. This work presents a smart and intelligent system designed to aid visually impaired persons (VIPs) in mobility and safety. Utilizing real-time navigation through automated voice assistance, VIPs can sense and understand their surroundings, facilitated by a deep learning model for object detection and recognition. The system includes a hardware component that automatically alerts family members and shares the VIP's location and incident details in case of abnormal object recognition. This ensures the safety of VIPs while upholding their privacy. This innovative solution enables VIPs to visualize their environment, empowering them with increased security. The employed deep learning model demonstrates high accuracy in object detection and recognition, enhancing the overall effectiveness of the system
Cyber Crimes during COVID-19 Pandemic
Authors: Mr. Thakur Sadgurusingh Nareshsingh  , Prof. Sonali Doifode
Published: March 2024

The COVID-19 pandemic has accelerated the use of digital technologies online website causing significant changes in the way we live and work. While these developments provide the necessary tools for remote working, education and communication, they also create new opportunities for cybercriminals. This content explores the emergence and evolution of cybercrime in the context of the COVID-19 pandemic Examines increasingly common types of cybercrimes, including phishing attacks, ransomware, and online fraud. The details also reveal the motivation behind these cybercrimes, from financial gain to exploiting fear and uncertainty. It also emphasizes the importance of cybersecurity knowledge and measures to protect people, organizations and critical system in the digital age. Has the world’s grapple with the ongoing pandemic combating cybercrimes has become important parts of our response to this crisis.
Blockchain-Based Blood Donation System: Enhancing Traceability in Blood Supply Chain Management
Authors: Aljuhani Dina , Alabdulwahb Latifah , Alsaleh Sarah , Altalhi Shahad , Alabdulhafith Maali
Published: March 2024

With the ability to save three lives per donation, blood donation is an essential part of life preservation. This emphasizes the tremendous influence that blood donations can have on people's lives. This study explores the possibilities of a blockchain-based blood supply chain management system in Saudi Arabia. The goal of this study is to aid the blood management system with creative and practical solutions. By utilizing blockchain technology, the proposed system seeks to improve the blood supply chain's traceability, efficiency, and transparency, which should ultimately result in better patient care and fewer risks associated with blood management by carefully examining the shortcomings and difficulties.
Towards Self-Optimization of Publish/Subscribe IoT Systems using Continuous Performance Monitoring
Authors: Mohammed Djahafi , Nabila Salmi
Published: March 2024

Today, more and more embedded devices are being connected through a network, generally Internet, offering users different services. This concept refers to Internet of Things (IoT), bringing information and control capabilities in many fields like medicine, smart homes, home security, etc. Main drawbacks of IoTenvironment are its dependency on Internet connectivity and need continuous devices power. These dependencies may affect system performances, namely request processing response times. In this context,we propose in this paper a continuous performance monitoring methodology, applied on IoT systems based on Publish/subscribe communication model. Our approach assesses performances using Stochastic Petri net modeling, and self-optimizes whenever poor performances are detected. Our approach relies on a Stochastic Petri nets modelling and analysis to assess performances. We target improving performances, in particular response times, by online modification of influencing factors.
Research on Fuzzy C- Clustering Recursive Genetic Algorithm based on Cloud Computing Bayes Function
Authors: Xu Wang
Published: March 2024

Aiming at the problems of poor local search ability and precocious convergence of fuzzy C-cluster recursive genetic algorithm (FOLD++), a new fuzzy C-cluster recursive genetic algorithm based on Bayesian function adaptation search (TS) was proposed by incorporating the idea of Bayesian function adaptation search into fuzzy C-cluster recursive genetic algorithm. The new algorithm combines the advantages of FOLD++ and TS. In the early stage of optimization, fuzzy C-cluster recursive genetic algorithm is used to get a good initial value, and the individual extreme value pbest is put into Bayesian function adaptation table. In the late stage of optimization, when the searching ability of fuzzy C-cluster recursive genetic is weakened, the short term memory function of Bayesian function adaptation table in Bayesian function adaptation search algorithm is utilized. Make it jump out of the local optimal solution, and allow bad solutions to be accepted during the search. The improved algorithm is applied to function optimization, and the simulation results show that the calculation accuracy and stability of the algorithm are improved, and the effectiveness of the improved algorithm is verified.
Flagged: Cybersecurity Training and Awareness System Through Virtual Reality
Authors: Alhawas Haya , Althemali Noura , Alkhaldi Renad , Alziyadi Renad , Alabdulhafith Maali
Published: March 2024

With the persistent rapid growth and sophistication of cyberattack attacks, organizations and individuals have a growing need to prioritize cybersecurity measures. The variety of attacks has posed new challenges and made it difficult to defend against all attacks. The existing traditional training methods are inadequate to keep up with the changing nature of cyberattacks. This project will address the essential problems in cybersecurity training, which are lack of awareness, inadequate customization, and the ineffectiveness of traditional methods, and it will offer a streamlined solution to solve these issues. The metaverse is considered the next evolution of the internet and provides significant innovative solutions for various problems. The metaverse has recently entered the education and training sector as an effective tool to enhance immersive learning experiences. With the objective of leveraging metaverse technologies such as virtual reality (VR) for education, training, and awareness. Flagged aims to develop a comprehensive virtual reality (VR) experience for cybersecurity training and awareness, focusing on phishing attacks. The user will work in the security operations center (SOC) and be responsible for monitoring, investigating, and responding to security incidents, focusing on phishing detection. The environment adapts the gamification and peer instruction (PI) learning methods to ensure collaboration and enhance users' practical skills for achieving the best outcomes.
A Mobile Application to Assist in Tracking Alcohol Consumption using Machine Learning and Object Detection
Authors: Bai Felix , Taraba Jeremy , Sun Fangzhou
Published: March 2024

Statistics show that excessive alcohol consumption has been a problem and remains a problem in many countries. This paper proposes an application that encompasses a solution which allows users to log and track their alcohol intake over time. It leverages features such as object recognition for drink identification, a history calendar for reflective analysis, and a real time blood alcohol level indicator for health measurements. During experimentation we found that the accuracy of the AI to be exceptional when used on drinks that it has been trained on. Furthermore, the blood alcohol calculator demonstrated a level of accuracy comparable to, if not surpassing, that of online calculators. This heightened accuracy is attributed to its real-time updating capability, ensuring precision in the calculations throughout the user's engagement with the application. The ultimate goal of this initiative is to create a user-friendly, technologydriven solution that empowers individuals to make informed decisions about their alcohol consumption. It promotes responsible drinking behavior and contributes to overall health and well-being.
An Intelligent Mobile Application to Recommend Clothing using Machine Learning and Generative AI
Authors: Zou Yumeng , Wang Shuyu
Published: March 2024

This paper addresses the critical issue of sustainability within the fast-paced fashion industry, characterized by overconsumption and waste. We propose an innovative solution, the Slow Low Fashion app, which leverages advanced artificial intelligence (AI) technology to analyze users' body measurements, providing personalized, gender-inclusive clothing recommendations [4]. This approach aims to minimize overconsumption and reduce the environmental footprint by encouraging more thoughtful purchasing decisions. The core technologies of our program include AI for body ratio analysis, a secure and privacy-compliant data handling framework, and an intuitive user interface designed to enhance user experience. Despite challenges such as ensuring the accuracy of body measurements and maintaining data privacy, we addressed these through rigorous testing and implementing encryption protocols. Experimentation across diverse user scenarios demonstrated the app's effectiveness in reducing unnecessary purchases and promoting sustainability. The significant reduction in clothing waste and increased user satisfaction highlight the potential of Slow Low Fashion as a tool for promoting sustainable fashion consumption. Our project underscores the necessity and feasibility of integrating technology and personalization in addressing the environmental challenges posed by the fashion industry.
A Comprehensive Mobile Application to Monitor and Enhance Kidney Health for Dialysis Patients using Machine Learning
Authors: Sun Rachel , Zhang Yujia
Published: March 2024

In the evolving landscape of healthcare, timely and accurate medical predictions are paramount, especially in managing chronic conditions like kidney disease. This paper introduces an innovative AI-driven application designed to enhance renal health management by predicting the need for dialysis and anemia, critical aspects of kidney care. Utilizing advanced algorithms such as Support Vector Machine (SVM) and XGBoost, coupled with cross-validation techniques, the application aims to provide reliable health predictions based on patient data. Challenges including model accuracy and processing speed were meticulously addressed through algorithm optimization and efficient data handling, ensuring the system's responsiveness to varying data complexities. Experimentation with mock patient scenarios revealed the system's capability to deliver precise anemia predictions and identify dialysis needs promptly, highlighting its potential in clinical settings. The application's blend of accuracy, speed, and user-centric design positions it as a valuable tool for patients and healthcare providers, promising to improve outcomes and decision-making in kidney health management.
An Accessible Application to Foster Figure Skating Skills using Gamification
Authors: Xiao Yuxi , Lai Joshua
Published: March 2024

The world of figure skating involves more than meets the eye, with precise and difficult moves judged subjectively, leading to biases and cultural influences impacting scoring. Skaters face physical and mental challenges, including pressure to conform to beauty standards. Addressing these issues, a proposed skating companion app aims to democratize figure skating by providing affordable, engaging, and safe training. Recognizing financial constraints, the app offers lessons, tips, and interactive elements to assist learning. It introduces a gamification element for simulated competition experiences, creating a risk-free environment for younger skaters during their formative years. The app aspires to be a catalyst for positive change, promoting inclusivity, safety, and education within the figure skating community, empowering individuals to navigate the complexities of this captivating sport while fostering a supportive and inclusive environment.
A Machine Learning Model to Predict the Success of Broadway Shows using Neural Networks and Natural Language Processing
Authors: Zhou Zhenyun , Sun Yu
Published: March 2024

This paper addresses the challenge of predicting the success of Broadway shows, a complex problem given the multifaceted nature of theater productions and their reception. Traditional methods have struggled to accurately forecast outcomes due to the dynamic interplay of factors such as audience preferences, critical reviews, and social media trends. To tackle this issue, we propose a machine learning-based model that integrates a wide range of data sources, including historical performance data, online user engagement metrics, and expert critiques [4]. Our program employs advanced data pre-processing techniques, neural network algorithms for pattern recognition, and natural language processing to analyze textual reviews and feedback [5]. During the experimentation phase, we encountered challenges related to data sparsity and variability in success criteria across different types of shows. These were mitigated by employing ensemble learning methods and customizing success metrics to align with industry standards. The application of our model across various scenarios demonstrated its versatility and improved predictive accuracy compared to existing approaches. Our findings reveal significant correlations between online engagement patterns and show success, highlighting the potential of machine learning in transforming investment and marketing strategies within the entertainment industry. Ultimately, our solution offers stakeholders a data-driven tool for decision-making, enhancing the viability and sustainability of Broadway productions.
An Interactive Science Lab Game to Help Students Learn More about Science using Unity
Authors: Jiang Shangyang , Boulom Tyler
Published: March 2024

In the evolving landscape of education, the integration of technology has become paramount, especially in adapting to the needs of digital-native students. Our paper addresses the challenge of engaging students in science, technology, engineering, and mathematics (STEM) subjects through traditional teaching methods, which often fail to capture the interest and imagination of today's learners [9]. We propose a solution through the development of an educational platform that combines gamification with virtual and simulation-based learning environments. This platform utilizes augmented reality (AR), virtual reality (VR), and adaptive learning algorithms to create immersive, interactive educational experiences that enhance student engagement and understanding of complex concepts [10][11]. The development process faced challenges, including balancing educational content with game engagement and ensuring equitable access to technology. These were addressed by integrating adaptive learning techniques to customize user experiences and forming partnerships with educational institutions to improve accessibility. Experimental application across diverse learning scenarios revealed significant improvements in student engagement, concept retention, and practical skills application. Our findings underscore the effectiveness of combining gamification with immersive technologies in education. Ultimately, this approach promises to revolutionize STEM education by making learning more engaging, accessible, and effective, thereby preparing students for the challenges of the 21st century.
La medicina es arte, el arte es medicina
Authors: Artigas Grandi Patricia
Published: March 2024

Desde pequeña me gustaron los colores y observarlos a mi alrededor, por lo que he tomado clases de pintura desde el colegio, he probado distintas técnicas, pero la que más me acomoda y apasiona es el óleo. Debido a mi profesión, no he podido pintar tanto como me gustaría, pero siempre ha sido parte de mi terapia de relajo y crecimiento personal.
Micosis pulmonar causada por Penicillium spp.: Reporte de caso en paciente con fibrosis quística
Authors: Flores Bonilla Raúl Arturo , Hernández Ruiz Juana
Published: March 2024

Se presenta el caso de un paciente masculino de 15 años con diagnóstico de fibrosis quística. Este desarrolló una sintomatología caracterizada por tos húmeda, no cianozante ni emetizante, sin un patrón temporal específico. Asociado a esto, nuevas lesiones nodulares bilaterales fueron identificadas en una tomografía de tórax. El abordaje diagnóstico incluyó una broncoscopia y la toma de un lavado broncoalveolar, que identificó la presencia de un microorganismo micótico poco común: Penicillium spp. Se inició tratamiento con voriconazol oral durante 14 días, resultando en una mejora clínica y radiológica significativa. El cultivo de expectoración posterior mostró un resultado negativo para Penicillium spp. Aunque la incidencia de exacerbaciones pulmonares causadas por agentes micóticos en pacientes con fibrosis quística es relativamente baja, se observa un incremento gradual, posiblemente relacionado con el uso prolongado de antimicrobianos de amplio espectro. La importancia de reportar este caso radica en el papel incierto que estos microorganismos juegan en la progresión del daño pulmonar, subrayando la necesidad de un seguimiento a mediano y largo plazo en estos pacientes.
Okul Müdürlerinin Dönüşümcü Liderlik Stilleri ile Öğretmenlerin Yaratıcı Düşünme Eğilimleri Arasındaki İlişkiler
Authors: Yüksel Serkan , Bilgivar Orkun Osman
Published: March 2024

Bu çalışmanın amacı, öğretmen algılarına göre okul müdürlerinin dönüşümcü liderlik stilleri ile öğretmenlerin yaratıcı düşünme eğilimleri arasında bir ilişki olup olmadığının belirlenmesidir. Araştırma, ilişkisel araştırma yöntemine göre gerçekleştirilmiştir. Araştırmanın örneklemi, 2022-2023 eğitim-öğretim yılında İstanbul ili Silivri ilçesinde resmi eğitim kurumlarında çalışan 322 öğretmenden oluşmaktadır. Araştırma sonucunda elde edilen veriler; ANOVA, korelasyon ve regresyon analizleri yapılarak çözümlemiştir. Bulgular incelendiğinde öğretmenlerin okul müdürlerinin dönüşümcü liderlik stiline yönelik algılarının yüksek düzeyde olduğu anlaşılmıştır. Yine veriler ışığında öğretmenlerin kendilerine yönelik yaratıcı düşünme eğilimlerini yüksek düzeyde algıladıkları tespit edilmiştir. Öğretmen algılarına göre okul müdürlerinin dönüşümcü liderlik stilleri ile öğretmenlerin yaratıcı düşünme eğilimleri arasında pozitif yönde, orta düzeyde ve anlamlı bir ilişki olduğu tespit edilmiştir. Ayrıca okul müdürlerinin dönüşümcü liderlik stilleri öğretmenlerin yaratıcı düşünme eğilimlerini pozitif yordamakta üzerindeki varyansın %15’ini açıklamaktadır. Öğretmenlerin yaratıcı düşünme eğilimleri ile pozitif ilişkisi sebebiyle üst yönetici ve politika yapıcılara okul müdürlerinin dönüşümcü liderlik stili sergileyebilecekleri ortamlar oluşturmaları veya bu ortamların sürekliliğini sağlayacak tedbirler almaları tavsiye edilmektedir. Bulgulardan yola çıkılarak araştırmanın son kısmında ise okul müdürlerinin dönüşümcü liderlik stili göstermeleri ve öğretmenlerin yaratıcı düşünme eğilimleri ile ilgili olarak değerlendirmeler ve tavsiyelerde bulunulmuştur.
MEVLÂNÂ CELÂLEDDÎN-İ RÛMÎ’NİN MESNEVİ’SİNDEKİ “KURTLA TİLKİNİN ASLANIN MAİYETİNDE AVA GİTMELERİ” HİKÂYESİ ÜZERİNE TEMATİK BİR ANALİZ
Authors: KARABULUT Mustafa
Published: March 2024

Mevlânâ Celâleddîn-i Rûmî, sadece Türk dünyasında değil, aynı zamanda bütün dünyada tanınan bir kişidir. O, mistik bir şair ve tasavvuf ehli bir şahıstır. Rumi, Şems-i Tebrizi ile tanıştıktan sonra hayatında büyük değişimler geçirir. Yapıtlarını ağırlıklı olarak Farsça yazmıştır. Onun Mesnevi adlı eseri bütün dünya tarafından bilinmektedir. Mesnevi’de dini, ahlaki, sosyal vb. birçok anlatı yer alır. Şair, bu hikayeleri Kur’an-ı Kerim’de ayetlerle ve Peygamber hadisleriyle destekler.

Mesnevi’de bulunan “Kurtla Tilkinin Aslanın Maiyetinde Ava Gitmeleri” adlı anlatıda şair, bir aslanın kurt ve tilkiyle birlikte ava gitmelerini ve avlarını paylaştırmaları sırasında gelişen olayları anlatır. Mevlana bu anlatıda “adaletli olma, ibret alma, bencil olmama, nefse yenik düşmeme, haddini bilme, aza kanaat getirme, açgözlü olmama, vesvese etmeme, ihsan, dünya nimetlerin aldatıcılığı, mizaç, kâmil insan olma, kendini Allah’a adama, Allah’ta yok olma, mutlak hakikatin Allah oluşu, fenafillah, Allah’ın kudretinin sonsuz oluşu, mülkün sahibinin Allah olması, doğru olma” vb. temalara ağırlık verir. Şair, bu şekilde okuyucuya nasihatler verir ve kişinin başkalarının başından geçen olaylardan ibret almasını ister. Bu makalede amaç, Mevlânâ’nın Mesnevi adlı eserinde yer alan “Kurtla Tilkinin Aslanın Maiyetinde Ava Gitmeleri” adlı anlatısını tematik bakımdan incelemektir.
AHMED PAŞA'NIN ÜSTÜNE REDİFLİ KASİDESİNDE KOZMİK UNSURLAR
Authors: DOĞAN Azize
Published: March 2024

Kâinattaki gizemi ve karmaşıklığı barındıran gökyüzü, yıldızlar, burçlar, gezegenler ve diğer kozmik unsurlar edebiyatın ilgi odağı olmuştur. Kozmik unsurlara dair merakını şiirleriyle açığa vuran 15. yüzyılın meşhur şairi Ahmed Paşa’nın “üstüne” redifli kasidesinde gök cisimleriyle ilgili çeşitli bilgiler verilmiştir. Birtakım remiz ve mazmunlarla birlikte teşbih, tevriye, leffü neşr gibi edebî sanatlara değinilmiştir. Kozmik okyanus olan gökyüzü farklı benzetmelere konu olmuştur. Fatih övgüsü için yazılan kaside, dönemin sosyal ve kültürel olaylarının, devletin yönetim şekli ve işleyişinin, toplumun yaşama biçimi ve inançlarının kozmik olarak işlenmesi bakımından önemlidir. Hatta kaside, 21 Mart’ta Nevrûzla birlikte ilkbaharın gelmesiyle burçlar kuşağının on iki eşit parçaya bölünmesi, gök kürelerinin birbirine göre konum alırken oluşturduğu musikî eşliğinde yapılan çalgılı çengili eğlence meclisi, Güneş’in Nevrûz’da Hamel burcunda olması itibariyle padişahın zaferine delâlet etmesi, padişahın kozmik bilgiyle ve marifet ilmiyle devleti yönetmesi gibi konular etrafında şekillenmiştir. Bahar tasviriyle gelişen kaside siyaset bilimi, coğrafya, musikî, astroloji, astronomi ve tasavvuf gibi çeşitli ilimlere ait bilgileri içermektedir. Kozmik ifade gücü içeren kasidede beyitlerin anlam dünyasına inilerek şairin daha iyi anlaşılması amaçlanmıştır. “Üstüne” redifli kasidedeki kozmik unsurlar tespit edilip şerh yönteminden yararlanılmıştır. Söz konusu çalışmanın birçok ilim dalına ait kozmik bilgiler içerdiği görülmüş, işlediği zengin konular sayesinde farklı bakış açılarının kazanılmasına imkân sunduğu anlaşılmıştır.
BEST PRACTICES IN STRATEGIC PROJECT MANAGEMENT ACROSS MULTINATIONAL CORPORATIONS: A GLOBAL PERSPECTIVE ON SUCCESS FACTORS AND CHALLENGES
Authors: Ifeanyi Onyedika Ekemezie  , Wags Numoipiri Digitemie
Published: March 2024

In today's highly competitive and dynamic business environment, multinational corporations (MNCs) face unique challenges in managing strategic projects across diverse geographical locations. This review explores the best practices in strategic project management from a global perspective, focusing on the critical success factors and challenges encountered by MNCs. Successful strategic project management in MNCs necessitates a comprehensive understanding of various factors, including cultural differences, regulatory requirements, and market dynamics across different regions. The review highlights the significance of effective communication, cultural sensitivity, and stakeholder engagement as fundamental success factors in managing projects within MNCs. Additionally, it emphasizes the importance of aligning project goals with overall business objectives to ensure strategic relevance and value creation. Challenges faced by MNCs in strategic project management include coordination and integration issues arising from diverse organizational structures, conflicting priorities, and resource constraints. Furthermore, navigating through geopolitical uncertainties, legal complexities, and compliance requirements presents additional hurdles for MNCs operating across multiple jurisdictions. Drawing on insights from academic literature and industry practices, this review provides an overview of best practices adopted by successful MNCs to overcome these challenges and achieve project success. It discusses the significance of establishing standardized project management frameworks, leveraging technology for virtual collaboration, and fostering a culture of innovation and adaptability within the organization. this review underscores the importance of adopting a holistic approach to strategic project management in MNCs, integrating people, processes, and technology to drive sustainable growth and competitive advantage in an increasingly globalized business landscape.

Keywords: Project Management, Multinational Corporation, Global Perspective, Best Practices, Review.
DEVELOPING A STRATEGIC PARTNERSHIP MODEL FOR ENHANCED PERFORMANCE IN EMERGING MARKETS
Authors: David Olanrewaju Olutimehin  , Onyeka Chrisanctus Ofodile  , Irunna Ejibe  , Adedoyin Oyewole
Published: March 2024

This paper introduces a novel theoretical model aimed at elucidating the impact of strategic partnerships on organizational performance, particularly tailored to the dynamic landscape of emerging markets. In today's global economy, strategic partnerships have emerged as pivotal mechanisms for organizations seeking sustainable growth and competitive advantage. However, the effectiveness of such partnerships varies significantly across different contexts, especially in emerging markets characterized by rapid change, resource constraints, and cultural diversity. This paper proposes a comprehensive framework that integrates insights from strategic management, international business, and emerging market studies to delineate the intricacies of strategic partnerships and their implications for organizational performance. By elucidating the underlying mechanisms and contextual factors influencing partnership dynamics, this model seeks to provide practical guidance for organizations navigating the complexities of emerging markets. The proposed framework integrates insights from strategic management, international business, and emerging market studies to delineate the intricacies of strategic partnerships. It aims to shed light on the underlying mechanisms and contextual factors that influence partnership dynamics in emerging markets. By doing so, the model seeks to provide practical guidance for organizations navigating the complexities of these environments. At its core, the model recognizes that successful strategic partnerships in emerging markets require a nuanced understanding of the unique challenges and opportunities inherent in these contexts. It emphasizes the importance of factors such as cultural sensitivity, regulatory environments, and resource availability in shaping partnership dynamics and outcomes. By leveraging insights from diverse disciplines, the model offers a holistic perspective that goes beyond conventional approaches to partnership management. Through a rigorous review of existing literature and empirical evidence, the model aims to provide actionable insights for organizations seeking to optimize their strategic partnerships in emerging markets. By elucidating the complex interplay of factors influencing partnership dynamics, it offers valuable guidance for organizations navigating the intricacies of these dynamic environments and harnessing the full potential of strategic collaborations for sustainable growth and competitive advantage.

Keywords:  Strategic Partnership, Performance, Emerging Markets, Model.
A new contact zone in the Chiffchaff distribution range: Caucasian and European subspecies meet each other in the south of Russia
Authors: Marova Irina , Ivanitskii Vladimir , Ilina Irina , Pecheneva Anastasya , Kvartalnov Pavel , Belocon Yury , Belokon Maryana
Published: March 2024

The study of contact zones between closely related taxa of animals sheds light on many important issues of evolution biology and taxonomy. Several such zones were described earlier within the huge distribution range of the chiffchaff species complex (Phylloscopus collybita). We have documented for the first time the existence of a new contact zone between Caucasian (Ph. c. caucasicus) and European (Ph. c. abietinus) subspecies of the Chiffchaff in Ciscaucasia (southern Russia). We predicted the occurrence of hybridization between these subspecies belonging to the same group of “greenish” chiffchaff. In eastern Ciscaucasia, a population was found in which the abietinus and caucasicus haplotypes co-occur in a significant number. A mixed pair of Chiffchaff (male caucasicus and female abietinus) was also found here. The colour of the plumage of Chiffchaffs in Ciscaucasia varies more widely compared to allopatric populations. In many specimens bearing the abietinus haplotype in Ciscaucasia, the wing formula is identical to that typical for caucasicus and differs from that typical for abietinus in allopatric populations. The tret calls typical of caucasicus are included in the song of Chiffchaffs, which carry the abietinus haplotype and do not have notes characteristic of caucasicus in their song. Chiffchaffs from Ciscaucasia occupy an intermediate position between abietinus and caucasicus in the duration of individual song phrases and syllable time-frequency characteristics. During the captures, the males of caucasicus readily reacted to the broadcast of the abietinus song, and vice versa. Thus, all the results suggest hybridization between abietinus and caucasicus in Ciscaucasia.
Statistical precursor signals for Dansgaard–Oeschger cooling transitions
Authors: Mitsui Takahito , Boers Niklas
Published: March 2024

Abstract. Given growing concerns about climate tipping points and their risks, it is important to investigate the capability of identifying robust precursor signals for the associated transitions. In general, the variance and short-lag autocorrelations of the fluctuations increase in a stochastically forced system approaching a critical or bifurcation-induced transition, making them theoretically suitable indicators to warn of such transitions. Paleoclimate records provide useful test beds if such a warning of a forthcoming transition could work in practice. The Dansgaard–Oeschger (DO) events are characterized by millennial-scale abrupt climate changes during the glacial period, manifesting most clearly as abrupt temperature shifts in the North Atlantic region. Some previous studies have found such statistical precursor signals for the DO warming transitions. On the other hand, statistical precursor signals for the abrupt DO cooling transitions have not been identified. Analyzing Greenland ice core records, we find robust and statistically significant precursor signals of DO cooling transitions in most of the interstadials longer than roughly 1500 years but not in the shorter interstadials. The origin of the statistical precursor signals is mainly related to so-called rebound events, humps in the temperature observed at the end of interstadial, some decades to centuries prior to the actual transition. We discuss several dynamical mechanisms that give rise to such rebound events and statistical precursor signals.
Death Anxiety and Depression among Cancer Patients: Role of Perceived Social Support
Authors: Shahzadi Kiran , Mazhar Samia
Published: March 2024

The primary objective of this study was to investigate the relationship between death anxiety and depression in individuals coping with cancer, focusing specifically on the role of perceived social support as a protective factor. The sample consisted of 200 cancer patients (95 males, 105 females) from hospitals in Rawalpindi and Islamabad, spanning different age groups. Data were categorized by cancer stage and treatment types. Using a cross-sectional design and correlational approach, the study found excellent reliabilities for Perceived Social Support (? = .90) and good reliabilities for Depression and Death Anxiety (? = .83 and .85, respectively). Gender-based differences were not significant for depression (t = -.51, p > .05) or perceived social support (t = -.23, p > .05). Perceived social support was highest initially and declined as cancer progressed. Significant variance in social support was observed across cancer stages (p < .05), with post hoc tests showing that 1st stage patients had significantly higher support than 2nd, 3rd, and 4th stage patients (MD = 7.27, p = 0.09). The study also showed gender differences in death anxiety, suggesting that women exhibited higher levels of death anxiety compared to men. Moreover, perceived social support was high at the 1st stage and significantly declined as the level progressed (3rd stage). The findings can be helpful for health professionals, psychologists and caregivers.
Does Spiritual Intelligence Link with Happiness and Psychological Adjustment among University Students?
Authors: Arshad Tehreem
Published: March 2024

Spiritual Intelligence (SI) is considered the most basic form of intelligence which enables an individual to deeply understand him and others and thus helps in achieving happiness and well-being in life (Subraniam & Panchanatham, 2015). The objective of the present study was to examine the relationship between spiritual intelligence, happiness and psychological adjustment in university students. A total of 350 students (Men = 175; Women = 175) were recruited from the universities of Lahore, Pakistan. The age of participants ranges between 18-30 years (M = 21.76; SD = 2.07). Spiritual Intelligence Self-Report Inventory (SISRI-24), Subjective Happiness Scale (SHS), and Psychological Adjustment Scale were used to assess spiritual intelligence, happiness, and psychological adjustment, respectively. Results revealed that spiritual intelligence significantly relates to and predicts happiness and psychological adjustment. As compared to men, psychological adjustment and spiritual intelligence were found to be higher in women. To conclude, students having higher spiritual intelligence are more likely to be happier and show better psychological adjustment, when compared to those who showed lower spiritual intelligence. In the future, spiritual intelligence-fostering programs such as community activities, orientation programs, spiritual seminars, counseling, and classroom activities could be catered for students.
PENERAPAN PSIKOEDUKASI SEKSUAL BERBASIS MEDIA TERINTEGRASI PEMBELAJARAN SEBAGAI UPAYA MENCEGAH KEKERASAN SEKSUAL SISWA SEKOLAH DASAR
Authors: Andriani Opi , Nofrianni Elvima , Pratiwi Astriana
Published: March 2024

Pelaksanaan pengabdian masyarakat ini dilatarbelakangi adanya peran guru yang belum berdampak secara optimal dalam upaya mencegah kekerasan seksual pada siswa sekolah dasar. Beberapa hal menjadi kendala dalam penerapan pencegahan kekerasan seksual diantaranya, guru tidak berani dan tabu, guru tidak paham, guru tidak punya strategi secara edukatif dan integratif. Salah satu cara mencegah kekerasan terhadap siswa sekolah dasar adalah melalui psikoedukasi seksual berbasis media yang terintegrasi dalam pembelajaran. Tim pengabdian Universitas Muhammadiyah Muara Bungo melakukan sosialiasasi penerapan psikoedukasi seksual kepada guru SD 196/II Taman Agung. Kegiatan pengabdian menggunakan metode praktek dengan cara simulasi pendampinganya langsung dari tim pengabdian yang diawali penyampaian materi. Rangkaian Kegiatan dilaksakan diruang rapat dan dilanjutkan simulasi ke ruang kelas. Adapun metode yang digunakan selama pengbadian adalah ceramah, diskusi, simulasi, dan refleksi. Hasil dari pelaksanaan pengabdian ini adalah guru memperoleh pemahaman baru tentang pentingnya psikoedukasi seksual diberikan sejak dini, guru mampu membuat dan mengunakan media yang mengandung unsur psikoedukasi seksual sesuai usia anak serta memperoleh strategi penerapan bahasa dan nada yang tepat sesuai usia siswa agar pembelajaran dengan konten psikoedukasi seksual memang mengarah ke denotatif.