bluuebunny/crossref_metadata_2025 huggingface dataset:
Management of School Operational Assistance Funds (Bos) at State Junior High School (SMP) Calang, Aceh Jaya Regency in 2020
Authors: Nurlizai Teuku Minjar , Amirulkamar Said
Published: March 2024

This research aims to determine the principles of using regular School Operational Assistance (BOS) funds at SMP Negeri 1 Calang, Aceh Jaya Regency and to determine the use of BOS funds during the Covid-19 pandemic at SMP Negeri 1 Calang, Aceh Jaya Regency. This research uses a qualitative approach and descriptive research type. In qualitative data analysis, there are three activity streams that occur simultaneously, namely data condentation, display, and conclusion drawing/verification. 1. The effectiveness of the use of BOS funds at SMP Negeri 1 Calang is in accordance with the Regular BOS technical guidelines, but there are still student learning outcomes that have not reached the KKM. Online and offline learning during the pandemic has not fully reached the National Education Standards, and the use of BOS funds has not met the Regular BOS components. The efficiency of using BOS funds at SMP Negeri 1 Calang is good, but there are problems with the minimum costs that must meet additional needs during the pandemic. The quality of learning decreases both online and offline. Transparency in the use of BOS funds in schools has been implemented, but the amount of funds is not published on notice boards, and school committees are not involved in preparing revised RKAS for additional needs during the pandemic. The allocation for using BOS funds during the pandemic has been fulfilled for face-to-face learning, but there are still students who do not comply with health protocols. Non-ASN teacher honorarium payments are in accordance with the agreement, but are often late, and honorary teacher data is not updated in Dapodik as of 31 December 2019. The use of BOS funds during the pandemic was carried out according to recommendations fromthe Ministry of Education and Culture, but was hampered by internet access and the ability of parents to provide online education facilities such as Android cellphone and data package.
Role of Knowledge Management Practices in Enhancing Innovation and Competitiveness in the Ethiopian Leather Industry
Authors: Tekle Kaleb
Published: March 2024

Purpose: The aim of the study was to investigate the role of knowledge management practices in enhancing innovation and competitiveness in the Ethiopian leather industry.

Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries.

Findings: The role of knowledge management practices in enhancing innovation and competitiveness in the Ethiopian leather industry is significant. Through effective knowledge management strategies, such as knowledge sharing, transfer, and utilization, firms can capitalize on their intellectual capital to foster innovation and improve competitiveness. By leveraging existing knowledge assets and creating a culture of continuous learning and innovation, Ethiopian leather companies can position themselves for sustained growth and success in both domestic and international markets.

Unique Contribution to Theory, Practice and Policy: Resource-based view (RBV) theory, dynamic capabilities theory & social capital theory may be used to anchor future studies on the role of knowledge management practices in enhancing innovation and competitiveness in the Ethiopian leather industry. Organizations within the Ethiopian leather industry should invest in capacity-building programs to enhance employees' knowledge management capabilities. Government policies should be formulated to support knowledge management initiatives and innovation in the Ethiopian leather industry.
Impact of Information Literacy on Academic Performance among Undergraduate Students in Nigeria
Authors: Ngozi Hellen
Published: March 2024

Purpose: The aim of the study was to investigate the impact of information literacy on academic performance among undergraduate students in Nigeria.

Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries.

Findings: A study on the impact of information literacy on academic performance among undergraduate students in Nigeria found a significant positive correlation between information literacy skills and academic achievement. The research highlighted that students with higher levels of information literacy were more likely to demonstrate better performance in their coursework, exams, and overall academic outcomes.

Unique Contribution to Theory, Practice and Policy: Social cognitive theory, information processing theory& constructivist learning theory may be used to anchor future studies on the impact of information literacy on academic performance among undergraduate students in Nigeria. Integrate information literacy instruction into the university curriculum across disciplines, ensuring that students acquire essential skills for locating, evaluating, and utilizing information effectively. Develop national guidelines for information literacy instruction within Nigerian higher education institutions, outlining standards and best practices for integrating information literacy into the curriculum.
Influence of Social Media on Information Seeking and Sharing Behavior among Young Adults in Kenya
Authors: Mbeeria Duncan
Published: March 2024

Purpose: The aim of the study was to investigate the influence of social media on information seeking and sharing behavior among young adults in Kenya.

Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries.

Findings: Social media heavily influences information seeking and sharing behavior among young adults in Kenya, facilitating quick access to diverse content despite concerns about reliability. To address misinformation and promote digital literacy, implementing educational programs and establishing guidelines for verifying information on social platforms are recommended.

Unique Contribution to Theory, Practice and Policy: Uses and gratifications theory, social cognitive theory & diffusion of innovations theory may be used to anchor future studies on influence of social media on information seeking and sharing behavior among young adults in Kenya. Develop and implement digital literacy programs tailored to the needs of young adults in Kenya, with a focus on enhancing critical evaluation skills, media literacy, and information verification techniques. Advocate for the development of policies and guidelines to regulate the dissemination of misinformation, hate speech, and harmful content on social media platforms, while preserving freedom of expression and information sharing.
Coding Local Weight Sensitivity in Wergaia
Authors: Lin Kuo-Chiao , Ho Kyle
Published: March 2024

Wergaia, an extinct language in Australian Wimmera region, exemplifies a generalized trochee language wherein heavy syllables generally do not bear stress, except when in final position in an odd-parity word to preserve a regular rhythmic alternation. This paper reviews the Wergaia stress pattern and provides a program in Python to model its local weight sensitivity in metrical parsing.
Ички ишлар органлари таълим муассасаларига номзодларни танлаш ва ўқишга қабул қилишнинг ташкилий ва ҳуқуқий жиҳатлари
Authors: Жуманов Тўлқин
Published: March 2024

Мақолада Ўзбекистонда олиб борилаётган кадрлар билан боғлиқ сиёсатнинг моҳияти ҳамда ушбу сиёсатнинг ички ишлар органлари тизимига бўлган таъсири ёритилган.
Ички ишлар органлари ходимлари томонидан жисмоний куч ишлатишни қўллаш соҳасида касбий ўқитишни методик таъминлаш муаммолари
Authors: Дўстмуродов Умидхон
Published: March 2024

Мақолада ички ишлар органлари ходимлари томонидан жисмоний куч ишлатишни қўллаш соҳасида касбий ўқитишни методик таъминлаш муаммолари, уларнинг ечимлари ёритилган. Касбий тайёргарлик тизимини, унинг асосий элементларини ташкил этувчи хизмат, жанговар, жисмоний, махсус-тактик, ахлоқий-психологик ва маънавий- маърифий тайёргарликни такомиллаштириш зарурияти асослаб берилган. Кадрларнинг самарали касбий ва жанговар тайёргарлигини ташкил этиш ва мувофиқлаштириш, ички ишлар органлари фаолияти самарадорлигини оширишнинг энг муҳим вазифалари қайд этилган.
Assessing the standard of emergency general surgical (EGS) operation notes in accordance with the Royal College of Surgeons guidelines
Authors: Zuberi Sharukh , Mustaq Yusuf , Ijaz Ali , Sundar Samyukta , Mohamedali Zahra , Patel Krashna , Joseph Janso , Gurprashad Roy
Published: March 2024

Objective: Operation notes are important for care in surgical patients. The objectives of this study were to analyze the emergency general surgery (EGS) operation note documentation in accordance with the Royal College of Surgeons of England (RCSEng) guidelines and to assess the impact of creating awareness of the guidelines and effect of a new proforma.

Material and Methods: A retrospective review of 50 EGS operation notes was conducted between December 2019 and March 2020 and compared to RCSEng guidelines. Education was delivered on the importance of documentation in accordance with RCSEng guidelines. A new electronic proforma was introduced. A further 50 EGS operation notes were analysed between August 2020 and December 2020.

Results: One hundred operation notes were reviewed, and each given a score out of 19. Our interventions showed significant improvement to the average score (15.64 vs 17.96; p< 0.001). Within the second cycle, there was a statistically significance difference when comparing electronic to handwritten notes (18.55 vs 17.50; p= 0.001).

Conclusion: Implementation of the new proforma showed improvement in operation note documentation when compared to the RCSEng standard. Therefore, this study emphasizes the need for surgeons to familiarize themselves with the current guidelines.
The role of C-reactive protein/albumin ratio and prognostic nutritional index in the diagnosis of complicated acute appendicitis
Authors: Zengin Akile , Murat Bağ Yusuf , Zeki Öğüt Mehmet , Sağlam Kutay
Published: March 2024

Objective: C-reactive protein (CRP) levels increase and albumin levels decrease in patients with inflammation. CRP/albumin ratio (CAR) is a new inflammation-associated prognostic indicator. The prognostic nutritional index (PNI) was described as a simple and neutral indicator of adverse outcomes not only in chronic diseases but also in acute conditions. The aim of this study was to investigate the clinical significance of the CAR and PNI value in differentiating complicated acute appendicitis (AA).

Material and Methods: We retrospectively examined the medical records of 187 patients with AA. Patients were divided into two groups according to pathological results [non-complicated (n= 161) and complicated (n= 26)]. Demographic, clinical, laboratory, and pathological data were examined and compared between the groups. Logistic regression analyses were performed to determine the independent predictors for complicated AA.

Results: Median age of the study group was 32 (23-41) years, and most of the patients were males (n= 101, 54%). Patients in the complicated AA group were significantly older compared to the patients in the non-complicated AA group [38 (32-49.5) years vs. 30 (22-41) years, p= 0.002]. The complicated AA group had significantly higher CAR level compared to the non-complicated AA group (p= 0.001). The length of hospital stay was significantly longer in the complicated AA group compared to the non-complicated AA group [2.5 (2-4.25) days vs. 1 (1-2) days, p< 0.001]. Other variables (including PNI) did not significantly differ between the groups. In univariate logistic regression analysis, only age was found to be a significant variable (OR= 1.045, 95% CI= 1.016-10.74, p= 0.002), but in multiple variate logistic regression analysis, no variable was found to be significant in predicting complicated AA.

Conclusion: We concluded that CAR and PNI value are not independent predictors of complicated AA.
Integrating the new systemic treatment landscape and surgical therapy in hepatocellular carcinoma
Authors: Haber Philipp K. , Krenzien Felix , Sarıbeyoğlu Kaya , Pratschke Johann , Schöning Wenzel
Published: March 2024

The treatment landscape of hepatocellular carcinoma has evolved rapidly within the last decade. Minimally-invasive techniques have reached a new level of safety, affording surgeons to pursue more aggressive treatment strategies to ultimately improve oncological outcomes. These procedures have been increasingly applied to treat patients with more progressed tumors and in select case even patients with advanced stage disease confined to the liver. Concomitantly, a dramatic increase in research into immunotherapy has altered the treatment paradigm in advanced disease stages, where the emerging treatment regimens can provide durable responses in a subset of the patient population for whom prognosis is dramatically improved. These treatments are now tested in early-stage disease to address the pressing unmet need of high recurrence rates after resection and in intermediate stage to complement the proven efficacy of intraarterial embolization in delaying progression. This review provides an in-depth discussion of these trends and describes how the treatment landscape has already changed and which impediments remain.
Strategic Planning Impacts on the Performance Dynamics of Micro Enterprises in Kisumu County: An in-Depth Analysis
Authors: Caroline Dr. Oloo
Published: March 2024

Strategic planning is integral for the success of micro enterprises, as evidenced by this research. It involves envisioning a desired future, defining goals, and outlining steps to achieve them. The study focused on the effects of strategic planning on micro enterprises around Kisumu county, employing primary data collection through questionnaires and interviews. Utilizing the ‘Kobo collect’ app and printed questionnaires, a 73.33% response rate was achieved. Findings indicate that strategic planning aids micro enterprises in Kisumu county by identifying market opportunities, strengths, weaknesses, and formulating strategies for success. Benefits include improved performance, resource allocation, communication, and innovation. Challenges, such as limited resources and resistance to change, were also identified. Effectiveness depends on stakeholder involvement, alignment with company culture, use of social media, flexibility, and ongoing monitoring. Recommendations include aligning the strategic plan with the organization’s mission, vision, and goals, involving stakeholders, effective resource allocation, and frequent monitoring and evaluation to ensure success.
Effect of Parents’ Socio-Economic Background on Secondary School Students Career Choice in Kebbi State, Nigeria
Authors: Samaila DOMINIC , I.D Awoyemi , Gwandu Zainab Lawal , Isah Suleman , Murtala Abubakar
Published: March 2024

Careers are the reality of life that needs to be considered important in today’s modern societies. Choosing a career is a complex decision-making process that coincides with so many environmental, cultural, social and economic variables, which creates psycho-social stress for students especially those in secondary school. The study adopted a mixed-method approach. A sample of 250 senior secondary two (SS2) students was purposively drawn from 130 senior secondary schools in Kebbi State. A standardised Family Influence Scale (FIS) was adopted for this study. The scale was modified to have two sub scales: parents’ occupation and family income. The face and content validity of FIS was carried out using experts in the field of guidance and counselling from Adamu Augie College of Education, Argungu. FIS was further subjected to pilot testing, and a reliability coefficient of 0.82 was obtained using the Cronbach Alpha formula. Descriptive statistics of mean and standard deviation were used to answer the research questions, while inferential statistics of t-test were used to test the null hypotheses at 0.05 level of significance. The outcome of this study revealed the grand mean scores of 2.8 and 2.7 which are greater than the decision mean score of 2.5 to imply that parents’ occupational backgrounds and income levels from secondary school students’ career choice significantly. Equally, significant differences were found (t= .19, df= 248, p-value =0.03) regarding the influence of parents’ gender on the career choices of male and female students in secondary schools in Kebbi State. Considering the influence of parents on the career choice of their children, it was recommended that parents should seek the help of professional career counsellors to guide their children in making intelligent career decisions.
Off-Campus Admission and Girls’ Vulnerability: Spaces for Immorality and Sexual Oppression
Authors: Kamwamba Atanazio Ernest
Published: March 2024

This study was conducted to investigate how the off-campus mode of university admission makes the girl-child vulnerable and creates spaces for immorality and sexual oppression. The study was conducted using questionnaires and oral interviews, both done online due to Covid-19 preventive measures. Using Gayatri Spivak’s idea of “The Female Subaltern”, the paper argues that admitting students on off-campus mode with little or no financial support increases girls’ vulnerability to such vices as prostitution and sexual abuse by ‘rich’ men, who take advantage of the girls’ suffering. The paper observes that this has negative effects on the girls’ education and lives as they may contract sexually transmitted infections, leaving them traumatized. This development also compromises the morality of university students, who are taken as role models in society. This immoral behaviour impacts negatively on the girls’ studies. The study observes that while the intentions to introduce this mode was in good faith, to ensure increased access to tertiary education, the challenges faced therein (regarding girls’ welfare) go a long way in defeating this rather good intention, and it becomes a gender issue considering the vulnerability of the girl-child, as men take advantage of the compromised welfare of these girls. With these girls losing their moral well-being, they cease from being reliable citizens after graduating from the university; not mentioning the fact that their life span is reduced should they contract deadly sexually transmitted infections.
METİNSEL TUTARLILIK ÇÖZÜMLEMELERİ KİTAP İNCELEMESİ
Authors: ADIGÜZEL Ahmet
Published: March 2024

Metin çözümlemesi üzerine çalışan araştırmacılar, özellikle yöntem ve teknik konusuna odaklanmıştır. Araştırmacılar bir metni, en doğru, en uygun şekilde çözümlemek amacıyla farklı disiplinlerin geliştirdiği yöntem ve teknikleri uygulamakta, metin merkezli, yazar merkezli, okur merkezli bakış açılarından yararlanmaktır. Metin çözümleme araştırmalarında yaygın olarak kullanılan Metin dilbilimi (text linguistics), Teun A. van Dijk’ın da belirttiği gibi, tek bir kuram ya da yönteme indirgenemez. Metin dilbilimi, metni birincil araştırma nesnesi olarak kabul eden bir dilbilimi disiplinidir. Yapısalcılıktan, üretici-dönüşümsel dil bilgisi anlayışından ve klasik filolojik incelemeden farklı olarak sözceyi ve sözceler arası bağlantıları önceleyen Metin dilbilimi, araştırmacılara metinsellik ölçütleri çerçevesinde inceleme olanağı sunmaktadır. Metin dilbilimi alanyazınında, yedi metinsellik ölçütünden ikisinin ön plana çıkarıldığı görülmektedir: Bağdaşıklık (cohesion) ve tutarlılık (coherence). Bağdaşıklık, metnin yüzey yapısındaki anlamsal ve mantıksal soyut bağlantıların çözümlenmesine dayanmakta ve kanaatimizce en temel metinsellik ölçüsü olarak karşımıza çıkmaktadır. Elinizdeki Metinsel Tutarlılık Çözümlemeleri kitabı, özellikli (spesifik) bir çalışmadır. Kitabın kapsamını; sözceler/ paragraflar arasındaki anlam ve mantık bağlantılarıyla sağlanan “bütüncül tutarlılık” ve bu doğrultuda yapılan Çağdaş Türk Edebiyatına ait özellikli hikâye çözümlemeleri oluşturmaktadır. Kitabın sınırlılığı gereği, metinlerdeki “sözcüksel tutarlılık” ve “bölgesel tutarlılık” ilişkileri kapsam dışı tutulmuştur. Metinsel Tutarlılık Çözümleri kitabında, hem kuramsal bilgilere yer verilmiş hem de uygulama örnekleri sunulmuştur. Kitabın yazılmasındaki temel amaç, edebî nitelik taşıyan anlatı metinlerininn çözümlenmesine yönelik yapılan araştırmalara, kuramsal ve uygulamalı boyutta katkı sunmaktır. Kitap beş bölümden oluşturulmuştur
Bayesian estimation : Number of species from Poisson mixed exponential-gamma distribution using objective priors
Authors: Kumar Sandeep , Pathak Anurag , Kumar Manoj , Singh Sanjay Kumar
Published: March 2024

In this paper, we have considered the Poisson-exponential-gamma mixture model as a species problem. The classical estimation of the parameter has been proposed through profile and conditional likelihood methods. While in the Bayesian paradigm, Bernardo’s reference and Jeffery’s priors have been used to estimate the number of species. Although a Markov Chain Monte Carlo (MCMC) technique has been used for obtaining the Bayes estimates of the number of species parameter. The performances of the proposed estimators are compared in terms of their risks through the simulation study. The applicability, and suitability of the proposed model have been performed using Mount Kenya insect species data.
Exploring explainable AI in pharmaceutical decision-making : Bridging the gap between black box models and clinical insights
Authors: Ghorpade V. S. , Jadhav Pradnya A. , Jadhav R. S. , Gujar Satish N. , Ashok Wankhede Vishal , Pandit Shraddha V.
Published: March 2024

This study explores the crucial nexus between artificial intelligence (AI) and clinical decision-making in pharmaceuticals, highlighting the need to close the growing gap between black box models and clinical insights. The opaqueness of black box models creates questions about regulatory compliance, interpretability, and transparency as AI becomes more and more integrated into clinical applications, drug development, and discovery processes. Acknowledging the importance of Explainable AI (XAI) in this regard, we thoroughly examine XAI methods, focusing on their use in medical environments. The review highlights the need for responsible AI solutions by taking ethical and regulatory factors into account. We highlight effective XAI implementations in clinical decision support systems and drug development through case studies and evaluations. The study highlights adoption and technical barriers and makes suggestions to improve model interpretability without sacrificing effectiveness. By providing insights into the complex world of XAI in the pharmaceutical sector, this research opens the door for ethically sound, transparent, and well-informed AI applications.
A pragmatic analysis of text-based sentiment analysis models from an analytical perspective
Authors: Khan Tabassum H. , Ridhorkar Sonali
Published: March 2024

NLP sentiment analysis involves pre-processing, feature extraction, feature selection, sentiment classification, and post-processing. Pre-processing can include PoS tagging, stopword removal, language-specific missing work detection and correction, etc. Word2vec, N Gramme, term frequency (TF), distance measures, etc. can extract and select features. CNNs, DNNs, and other machine learning and deep learning models can be used for classification and post-processing. These models form a sentiment analysis engine, which can be assessed for accuracy, precision, recall, analysis delay, computational complexity, etc. The wide variation in algorithmic combination and performance makes it difficult for researchers to choose the best model(s) for their application. This task requires a lot of model testing and validation, which increases time-to-market and product cost. This text surveys recently proposed sentiment analysis models to reduce ambiguity and speed up system development. This survey characterises reviewed models’ nuances, advantages, limitations, and future research scopes to help readers choose the best models for their application deployment. These models’ delay, accuracy, precision, recall, computational complexity, and probable use are also compared in this text. This comparison lets readers choose the best model(s) for their application deployment and use them without validation. Reducing testing delay will improve model performance for system design and deployment for multiple sentiment analysis applications
Efficient object tracking through machine learning and optimization strategies in computer vision
Authors: Thakur Uma , Thakur Reena , Somkuwar Sahil , Shendare Abhay , Ingole Rita , Verma Achal , Tidke Swejal
Published: March 2024

This research introduces an innovative approach for efficiently monitoring objects in computer vision systems through combining machine learning (ML) algorithms and optimization strategies. Tracking objects is crucial in applications like surveillance, selfdriving vehicles, and augmented reality. By harnessing advanced ML methods such as deep learning and integrating optimization strategies including gradient-based techniques, the proposed system aims to enhance accuracy and real-time performance during tracking. The collaborative synergy between ML algorithms and optimization methods empowers the system to dynamically adjust to diverse and challenging scenarios, ensuring resilient tracking across varying environments. Experimental results underscore the efficacy of the proposed methodology, demonstrating superior tracking precision compared to conventional approaches. This study contributes to the progression of computer vision applications, providing a scalable and adaptable solution for real-world challenges in object tracking.
Enhancing word sense disambiguation through contextual embedding and optimization techniques���
Authors: Dhopavkar Gauri , Takalikar Mukta , Kshirsagar Manali
Published: March 2024

This study presents a new strategy for determining the meaning of words based on their use in text. Traditional methods struggle because they do not fully grasp the context around ambiguous words. Our framework combines powerful models that understand context, like BERT and ELMO, to precisely identify a word’s sense based on its language environment. These representations depict word meanings in different situations more accurately. This helps the model to predict various meanings of an unclear word. Additionally, we apply techniques to refine the model’s performance. For instance, we customize the representations specifically for making sense of words. This increases the model’s awareness of subtle clues. Experiments show our approach notably outperforms basic methods in correctly determining word senses. The blending of contextual representations and refinement strategies not only boosts overall accuracy for defining ambiguous words but also demonstrates flexibility in handling difficult examples across diverse language contexts.
IoT-driven sprinklers : Revolutionizing landscape optimization through smart watering solutions system
Authors: Balani Nisha , Mulchandani Mona , Vaswani Sakshi , Tiwari Sejal , Gidwani Kashish , Nagwani Muskaan , Nagdeve Kameshwari
Published: March 2024

In India, intelligent sprinkler systems powered by the Internet of Things have transformed landscape care, replacing outdated watering practices. These systems dynamically adjust to environmental changes through connectivity, weather data, and monitoring. They ensure precise and effective water allocation, promoting conservation while fostering vibrant plant life. Sensors, real-time tracking, and meteorology have connected smart technologies to moisture management. This allows automatic adaptation to varying situations, enhancing resource preservation. Internet-connected sprinklers can analyze and respond to soil moisture, temperatures, and weather forecasts. This gives users unprecedented oversight, promoting sustainability and mitigating water waste. As we embrace landscape enhancement, these IoT sprinkler systems signify progress. They are reshaping intelligent and water efficient gardening and landscaping for the future.
MIDGNWD : Design of an efficient multimodal iterative deep graph network wearable interface for detecting drowsy drivers
Authors: Wakode Rashmi A. , Mohod Sharad W.
Published: March 2024

Drowsy driving is a significant contributor to road traffic accidents, necessitating the development of robust and efficient detection systems. Existing approaches for detecting drowsy drivers often rely on single modalities such as image-based facial analysis or vehiclebased metrics, which may lack precision and be susceptible to environmental variations. Furthermore, the existing models might be computationally expensive and result in delayed responses. To address these limitations, this paper proposes a novel Multimodal Iterative Deep Graph Network Wearable Interface that leverages a rich set of data including heart rate, respiration, accelerometer movement, location (speed), traffic, and weather data. These data samples are processed through a fusion of different Recurrent Neural Network processes. The Bidirectional Long Short-Term Memory (BiLSTM) which is used to generate augmented features, is fused with Bidirectional Gated Recurrent Unit (BiGRU) which assists in estimating multidomain feature sets. These features are then used to train an efficient Deep Graph Recurrent Network (DGRN), which facilitates the real-time identification of drowsy drivers. The proposed model significantly enhances the precision of drowsy driver detection by 8.5%, accuracy by 9.5%, recall by 8.3%, and Area Under the Curve (AUC) by 4.9%, while also improving specificity by 5.5% and reducing delay by 10.4%. These improvements collectively contribute to a substantial enhancement in road safety, potentially saving lives by preventing accidents due to drowsy driving. The proposed system, with its real-time processing capability and high accuracy, stands as a significant improvement for identifying drowsy drivers, paving the way for safer and smarter transportation systems.
Revolutionizing construction engineering education : A virtual reality approach for enhanced training and optimization
Authors: Raut Sweta , Bhura Sohel , Khushalani Jayesh , Kim Hyejin , Ramani Nisha , Bajaj Roshni
Published: March 2024

This research explores an innovative approach in construction engineering education, leveraging virtual reality for enhanced training and optimization. Traditional methods in this field often face difficulties offering hands-on experiences and practical simulations. The proposed method uses VR technologies to generate immersive and interactive learning environments, giving students authentic scenarios to refine their abilities. By integrating VR simulations into the curriculum, learners can participate in virtual construction projects, allowing experiential learning without constraints of physical space or safety issues. The optimization aspect focuses on refining educational processes, adapting material to individual learning styles, and incorporating real-time feedback mechanisms. This study aims to revolutionize construction engineering education, providing a dynamic, efficient, and safe platform for skill development, ultimately producing well-prepared professionals ready to address the complexities of the industry. The research contributes to the ongoing discussion on creative educational methodologies and their application to address challenges in construction engineering training.
Blockchain technology in pharmaceutical supply chain : Ensuring transparency, traceability, and security
Authors: Shete A. S. , Bhutada Sunil , Patil M. B. , Sen Praveen H. , Jain Neha , Khobragade Prashant
Published: March 2024

Transparency, traceability, and security are three major challenges that blockchain technology has addressed in the pharmaceutical supply chain, making it a disruptive solution. The incorporation of blockchain technology to produce an immutable, decentralized ledger that documents the full path taken by pharmaceutical products from producer to end-user is examined in this abstract. The solution ensures tamper-resistant records by utilizing smart contracts and cryptography concepts, hence mitigating the risk of counterfeit medications. Transparency is improved via real-time supply chain visibility, which gives stakeholders the ability to monitor batch information and confirm product authenticity. Blockchain’s decentralized structure improves security by reducing the possibility of fraud and unauthorized access. By means of blockchain implementation, the pharmaceutical business may create a strong, dependable, and effective supply chain ecosystem, thereby promoting safer and more dependable medicine access for patients across the globe.
Pharmacovigilance in the digital era : A machine learning approach for early detection of adverse drug reactions
Authors: Panda B. K. , Niranjane Pornima B. , Mali D. P. , Bainalwar Prachi A. , Aher Ujjwala Bal , Bhattacharya Saurabh
Published: March 2024

The revolutionary potential of machine learning (ML) in pharmacovigilance the early detection of adverse drug reactions (ADRs) in the digital era is examined in this study. It is difficult to promptly identify and address adverse drug reactions (ADRs) using traditional pharmacovigilance techniques. This study suggests an approach for combining structured and unstructured data sources for reliable ADR detection that makes use of machine learning. Many machine learning (ML) algorithms, including ensemble methods and neural networks, are used and contrasted with traditional techniques. Problems are tackled, such as ethical issues and the dependability of the data. Case studies present real-world implementations and shed light on how well ML models work. The study addresses the interpretability of these models, how to incorporate them into the current pharmacovigilance systems, and how data scientists and healthcare practitioners might work together. Upcoming developments and legal issues are highlighted in future directions. This study highlights how ML has the ability to completely transform pharmacovigilance by providing a proactive and more effective method of detecting ADRs and indicating a bright future for medication safety in the digital era.
Diabetes prediction using machine learning classifiers with oversampling and feature augmentation
Authors: Banday Mehroush , Zafar Sherin , Agarwal Parul , Alam M. Afshar
Published: March 2024

Two of the leading causes of mortality in the US are diabetes and cardiovascular disease. The first step in halting the course of these disorders in patients is to recognize and anticipate them. Using survey data (as well as test findings), we assess the efficacy of machine learning algorithms for identifying patients who are at risk and pinpoint important characteristics in the data that are causing these diseases in the patients. Hunger, thirst, and frequent urination are signs of high blood sugar. Neglecting diabetes can lead to several issues. It’s critical to be able to identify diabetes early. In this study, we use supervised machine-learning techniques such as Decision Tree, KNN, (RF)Random Forest, Logistic Regression, Ada Boost, and Gradient Boosting to train on the actual data of 520 diabetics. The proposed work has achieved a more thorough comparative analysis between different datasets and their features that may be carried out to pinpoint all the essential characteristics for predicting diabetes.
An instance of negative variance-like ‘components’ in optics by way of applying multivariable calculus to a statistical problem
Authors: Siew Ronian
Published: March 2024

In the field of optics, the design of a lens often involves analyses of the variability in an optical parameter (such as lens focal length) under manufacturing conditions, which is done in order to identify sources of high variability that may cause the optical parameter to be out of its specification. In this interdisciplinary paper, the author shares his experience in lens design, where analyses of variability are often performed through examining the partial derivatives in a multivariable Taylor series expansion of an optical parameter to second order when interactions are expected. It is shown algebraically that when the second-order expansion is applied to express a sum of squares, negative terms in the sum can occur. This instance of negative-valued “variance-like components” is interesting pedagogically in applied mathematics and statistics, as well as from an engineering standpoint, as it suggests that, based on theory, the variance of a function of random variables may not necessarily be comprised of a simple sum of positive-valued squared deviations comprising its total variance.
Significance of Inflammatory Markers; C-reactive Protein, Hyperuricemia, and Albuminuria in type 2 Diabetes Patients
Authors: Jais Kumar Karmani  , Arif Mumtaz  , Syed Asim Ali Shah  , Rifat Yasmin  , Wajahat Sultan Baig  , Tazaeen Hina Kazmi
Published: March 2024

Objective:  To determine the significance of inflammatory markers, including C-reactive protein, hyperuricemia, and albuminuria, in individuals with type 2 diabetes.

Methodology: This cross-sectional analytical study was done at Diabetic Clinic and Nephrology Department of Akbar Niazi Teaching Hospital, Islamabad between Jan 2023 and July 2023. Total 150 consecutive patients aged between 35 and 60 years with type 2 diabetes were enrolled in study. Participants were divided in two groups on the basis of C-reactive protein and uric acid levels. Group-A comprised individuals with type 2 diabetes and C-reactive protein levels, while Group-B included individuals with type 2 diabetes and uric acid levels. Every patient underwent necessary clinical and laboratory assessments. The measurement of C-reactive protein was conducted through a particle-enhanced immunoturbidimetric assay.

Results: The study population demonstrates an average age of 49.41±7.66 years. In linear regression analysis, both C-reactive protein and uric acid emerged as independently predictor the albumin to creatinine ratio include (?=0.20, 95% CI 0.1-0.30, and p=0.001 for C-reactive protein, and ?=0.20, 95% CI 0.1-0.30, and p=0.001 for uric acid). In logistic regression, the albuminuria odd for C-reactive protein and uric acid groups was 4.05 (95% CI 2.60-9.15, p=0.001).

Conclusion: In individuals with type 2 diabetes, there was an association observed between albuminuria and heightened levels of C-reactive protein and elevated uric acid levels. Additionally, there was an interactive effect on albuminuria observed between C-reactive protein and uric acid.
Homeless migrants’ commoning practices. “Our House” solidarity project in Athens’ Omonia square
Authors:   School of Spatial Planning and Development, Aristotle University of Thessaloniki, Greece, Tsavdaroglou Charalampos
Published: March 2024

In recent years, Athens has been at the center of the so-called “migration crisis”, as thousands of newcomers have found temporary or permanent refuge in the city. However, because the state’s housing policies have reduced the available positions of those who have the right to settle in state accommodation structures, an ever-increasing number of newcomers facing homelessness and live in city’s streets, parks and squares. In this context, a solidarity collective kitchen named “Our House” was self-organized by a group of newcomers on the city’s central square, Omonoia Square, where it remained for two years. Our House project activities, based on mutual help and commoning practices, claimed the homeless migrants’ right to the center of the city. However, in 2019 the square was turned into a construction site and Our House activities were prohibited. This paper is based on ethnographic urban research and discusses the solidarity practices of homeless migrants through the theoretical approaches of the right to the city, as well as critical approaches to homelessness and urban commons. The main findings of the paper focus on highlighting the homeless migrants’ commoning practices, and the paper’s contribution lies in the enrichment of theoretical discussions on the right to the city and urban commoning practices through the case homeless migrants’s self-organization.
The Primary Reading/Writing Education Process in Light of the Views of Mothers, Who Learn Reading/Writing in Turkish, and Their Children
Authors: Yeniasır Mustafa , Gökbulut Burak
Published: March 2024

The primary reading and writing education process is one of the most crucial experiences that shape individuals’ future lives and influence their achievements throughout life. With the help of acquired reading and writing skills, individuals learn their societal values and ensure that the society, in which they live, will look toward the future more confidently. Today when information is intensively produced and consumed, whether a person’s existence is acknowledged and whether a person continues to succeed are directly connected to whether a good quality reading and writing education was received by the person in the past. The goal of this research is to evaluate and analyze the views of mothers, who participated in the primary education course on reading and writing in Turkish at the Turkish Cypriot Child Protection Institution in the Turkish Republic of Northern Cyprus approximately for five months in the spring semester of the 2022-2023 academic year, as well as the views of their children, who closely followed up the process. With this goal, a study was carried out with 15 mothers, who participated in the above course, and 15 children, who stood by their mothers during this process. Mothers and children participating in the study were asked to narrate the memories of their experiences during the primary education course on reading and writing in Turkish. The research data were collected via face-to-face interviews and written documents. The thematic analysis method was used in the analysis of research data, and themes produced from written documents were categorized into sub-themes and were evaluated.
Mapping Cloud Based Facilities for Academic Use
Authors: Dr. S. Sujatha
Published: March 2024

The pay-as-you-use service model is one of the key factors for the success of cloud computing paradigm: resources are used only when needed and charged on basis of their actual usage. There are ICT services through cloud which are even provided free to educational institutions and institutions can benefit from these services. Universities necessarily do not have enough resources to spend on subscribing or establishing ICT facilities but these facilities are essential for improving the way faculty & student interact, communicate, and carry research activities. Faculty, staff and students have access to services like institutional email, 1 TB drive space, Office applications free which otherwise require purchased licenses. In this paper, the different free services provided for educational use are discussed, analysed for perception of its adoption. Further, case study of these services implemented at university of Kashmir has been chosen as the research methodology to discuss and demonstrate the educational cloud services. According to the results, clear understanding and operational ease, high reliability, ease of accessibility with no financial implications is achieved. This guarantees the desired performance level and minimises the expenditure otherwise to be incurred on setting up or subscribing to such services
Learning Community In Argumentative Writing Using Audio Visual Through Lesson (The First Year Of MA Al-Muslim Islamic Boarding School)
Authors: Nurul Izzah  , Misnar
Published: March 2024

In learning English at school, argumentative writing is one of the materials that are considered difficult for students to understand. In general, the learning model developed by English teachers is in conventional learning activities. Therefore, it is necessary to apply the learning of Argumentative Writing Using Audio Visual Through Lesson Study (The First Year of MA Al-Muslim Islamic Boarding School). One of the types of lessons considered by researchers can motivate students to play an active and fun role in the teaching and learning process. This type of classroom action research is carried out through 4 stages, namely: planning, implementing actions, observing and reflecting. The data collected in this study were the students' scores in working on the questions given the initial and final tests, the results of observations on the learning steps and the results of interviews regarding students' understanding and difficulties. The results of this study can be concluded that students' learning mastery also experienced an increase, in the first cycle by 75% and becoming 85% in the second cycle. The increase in student learning outcomes was also followed by an increase in student learning activities by 83.64% in the first cycle and increased to 89.88% in the second cycle. This shows that learning argumentative writing through lesson study can improve student learning outcomes.
Effectiveness of media Instagram towards the students' vocabulary mastery
Authors: Muliana  , Silvi Listia Dewi
Published: March 2024

This research aims to see whether the mean score of XI students of SMA Negeri 3 Bireuen who taught using Instagram media to master vocabulary in writing recount texts got a higher score than the mean score of students who used conventional methods. The methodology of this research was a quasi-experimental (nonequivalent control group) design. The instrument used in this research was an achievement test. The data was analyzed quantitatively using the SPSS Statistics Output, such as Normality Test, homogeny test, and Independent-Sample T-test. Using Instagram as media for the student's vocabulary mastery in writing recount text is effective. It can be seen from the average score of the control and experimental classes, where the average value of the control class is 47.65 while the average value of the experimental class is 77.94. That way, there is a difference between the two classes, where the experimental class taught using Instagram has a higher value than the control class taught using the convection method. From the data analysis, the result of the Independent Sample T-test is 0.000 < 0.05, so it can be concluded that there is a difference in the average student learning outcomes between the learning model that uses Instagram media and the conventional learning model. Thus, the research alternative hypotheses (Ha) are accepted, and the null hypotheses (Ho) are rejected. Then, the effectiveness of the media Instagram towards the students' vocabulary mastery in writing recount text is effective.