bluuebunny/crossref_metadata_2025 huggingface dataset:
Politeness Strategies Of The Characters In Becoming Jane Movie Script By Kevin Hood And Sarah Willimas
Authors: Imran La Ode , Moelier Dahlia D. , Asyrafunnisa Asyrafunnisa
Published: October 2024

Humans cannot survive alone if others are not present. Interaction as achieved through contact and communication as a social creature. Humans practically communicate with one another through the use of language. Language has an important part in human communication since it serves as a media tool for engagement. When a language is employed, something about the relationship among the individuals is exposed. This research aimed to explored the used of politeness strategies in Becoming Jane Movie Script and how the characters used politeness strategies in their utterance. The researcher used qualitative technique to explain more the types of politeness strategies and describe how the characters use politeness strategies in Becoming Jane movie Script. The data were analyzed applying politeness strategies theory by Brown and Levinson (1987, p. 68). The researcher found that there were two types of politeness strategies in Becoming Jane movie script namely Bald-on Record and Positive Politeness. The researcher also found how the characters used politeness strategies in their utterance which as the influenced factors were pay-off, relevant circumstances; power (P) and Social Distance (D)
Peran Modal Sosial Terhadap Peternak Ayam Bloiler Di Desa Punaga Kecamatan Laikang Kabupaten Takalar
Authors: Gilang Gilang , Bahri Syamsul , Harifuddin Harifuddin
Published: October 2024

Abstrak
Tujuan penelitian ini untuk mengetahui peran modal sosial terhadap peternak ayam broiler, dengan modal sosial yang dimiliki oleh peternak, peternak mendapatkan manfaat dari hubungan yang terjalin dengan orang lain. Lokasi penelitian ini terletak di Desa Punaga Kecamatan Laikang Kabupaten Takalar. Penelitian ini menggunakan pendekatan kualitatif dengan melakukan metode observasi, wawancara dan dokumentasi. Proses pengambilan data dilakukan dengan metode wawancara, observasi dan dokumentasi langsung ke lokasi penelitian. Dari hasil observasi dan wawancara dilakukan diketahui bahwa hubungan antara peternak dengan peternak, hubungan antara peternak dengan tetangga, dan hubungan antara peternak dengan pemerintah, maupun hubungan peternak dengan keluarga dapat memberikan manfaat informasi, barang, maupun jasa kepada peternak yang memiliki unsur modal sosial seperti jaringan, resiprositas, kepercayaan, norma sosial, dan nilai sosial. Dari hasil observasi dan wawancara diketahui juga bahwa tipe modal sosial peternak beragam seperti bonding, bridging maupun linking.
The purpose of this research to find out the role of social capital on broiler chicken breeder, with the social capital owned by the breeder, breeder benefit from relationships with other people. The location of this research is in Punaga Village, Laikang District, Takalar Regency. This research uses a qualitative approach by conducting observasion, interview, and documentation methods. The data collection process was carried out using observation, interviews, and documentation directly at the research location. From the results of observations and interviews conducted, it is knowing that the relationship between breeders and breeders, the relationship between breeders and neighbors, and the relationship between breeders and the government, as well as the relationship between the breeder and the family can provide beneficial information, goods and services to farmers who have elements of social capital such as networks, reciprocity, trust, norms, and social value. From the results of observations and interviews it is also known tha the types op social capital of breeders vary, such as: bonding, bridging, or linking.
A INTEGRALIDADE DO SER DE UMA MULHER-NEGRA-SURDA
Authors: Oliveira Waldma Maíra Menezes de , Oliveira Ivanilde Apoluceno de
Published: October 2024

Neste estudo, apresenta-se um recorte da tese de Oliveira (2023) para ilustrar as amarras coloniais que atravessam o corpo surdo e suas rupturas no campo teórico da decolonialidade. Assim, objetiva-se denunciar as identidades pressupostas, em uma perspectiva colonial, atribuídas a um mulher-negra-surda e anunciar a construção de sua integralidade do ser, em uma perspectiva decolonial na interseção com a integralidade do ser de Paulo Freire. A pesquisa caracterizou-se enquanto uma pesquisa de campo, de abordagem qualitativa tendo como campo teórico o pensamento decolonial e intercultural crítico de Paulo Freire, autor teórico-metodológico da investigação. Nos procedimentos metodológicos utilizou-se um roteiro de entrevista semiestruturada, com foco teórico das narrativas de vida, descritas no Círculo Dialógico Cultural (CDC) com uma mulher-negra-surda. As narrativas de vida da entrevistada ilustram o processo de combate as identidades de um modo essencialista e colonial para a transformação de sua identidade como produto histórico, relacional e dinâmico.
Frequency of Refractive Errors in the Students of Khawaja Fareed University of Engineering and Information Technology, Rahim Yar Khan Punjab Pakistan
Authors: Arslan Muhammad , Yasin Noman
Published: October 2024

The purpose of this study was to find out the frequency of refractive errors in the students of Khawaja Fareed University of Engineering & Information Technology (KFUEIT), Rahim Yar Khan. A Cross-sectional university-based study was carried out from March 1, 2023, to May 19, 2023, at KFUEIT. All enrolled students from various disciplines at KFUEIT were included, except those who were not KFUEIT students or had undergone ocular surgery, or had preexisting other eye diseases, systemic diseases, or syndromes. Out of a total of 623 students representing various disciplines who participated in the study, 603 met the predefined inclusion criteria. Visual acuity testing, non-cycloplegic objective refraction, and subjective verification were performed to evaluate refractive error measurements. Data analysis was carried out using SPSS version 21, employing descriptive statistics, frequency calculations, and cross-tabulations. According to the results of the study, 179 students out of the 603, which is approximately 29.7%, had refractive errors. Myopia emerged as the most prevalent refractive error, affecting 25.2% of students, followed by astigmatism (3.0%) and hyperopia (1.5%). Gender analysis demonstrated a slightly higher prevalence of myopia among male students compared to females. Moderate myopia was the most prevalent severity level observed. Male students predominantly exhibited compound myopic astigmatism, while simple myopic astigmatism was more prevalent in females. Conclusion: Our study at KFUEIT found that 29.7% of the 603 students had refractive errors. These findings can guide interventions and policies for a visually healthy environment at KFUEIT.
ԱՅԼԱԽՈՀԱԿԱՆ ԵՎ ԻՐԱՎԱՊԱՇՏՊԱՆ ՇԱՐԺՈՒՄՆԵՐԸ ԽՈՐՀՐԴԱՅԻՆ ՀԱՅԱՍՏԱՆՈՒՄ 1960-1980-ԱԿԱՆ ԹՎԱԿԱՆՆԵՐԻՆ / DISSIDENT AND HUMAN RIGHTS MOVEMENTS IN SOVIET ARMENIA IN 1960-1980
Authors: Badalyan Irina
Published: October 2024

Starting from the 1960s, a wave of dissent spread in Soviet Armenia. Intellectuals, writers, artists and activists became active participants in the movement, facing persecution and imprisonment for voicing their grievances.
Despite brutal reprisals by the KGB and state authorities, dissidents in Soviet Armenia continued their struggle for freedom of speech, human rights, and national autonomy.
This article draws on archival materials, memoirs, and scholarly works to provide a com- prehensive analysis of the dissident movement in Soviet Armenia.
ՀՆԱԳԻՏԱԿԱՆ ԱՌԱՐԿԱՆԵՐԻ ՎԵՐԱԿԱՆԳՆՈՒՄ. ԽԵՑԵՂԵՆԻ ՎԵՐԱԿԱՆԳՆՄԱՆ ԱՌԱՆՁՆԱՀԱՏԿՈՒԹՅՈՒՆՆԵՐԸ / RESTORATION OF ARCHAEOLOGICAL ARTEFACTS: SPECIFICITIES OF CERAMIC RESTORATION
Authors: Simonyan Astghik
Published: October 2024

The article is presenting the stages of restoration of archaeological ceramics: cleaning, conservation and subsequent restoration, as well as the specificities of the material’s pres- ervation. Reference was made to the materials and methods used in the restoration and preservation of archaeological pottery, a comprehensive study was conducted, and the variants currently accepted and applicable in the restoration of archaeological pottery were presented.
The problems arising during the restoration of archaeological pottery were outlined with their possible solutions. The preservation conditions of the pottery were cited and de- tailed description of the different stages of restoration was given. The content of the passport of restoration of museum artefacts was presented.
AI-Driven HSE management systems for risk mitigation in the oil and gas industry
Authors: Adeoye Taofik Aderamo  , Henry Chukwuemeka Olisakwe  , Yetunde Adenike Adebayo  , Andrew Emuobosa Esiri
Published: October 2024

The oil and gas industry faces numerous health, safety, and environmental (HSE) risks due to the complexity of its operations. Traditional HSE management systems often rely on manual processes and reactive approaches, which can lead to inefficiencies and delayed responses to potential hazards. This paper proposes the integration of Artificial Intelligence (AI) into HSE management systems to enhance real-time safety monitoring and predictive risk management. By leveraging AI-driven technologies such as machine learning, computer vision, and predictive analytics, companies can proactively identify and mitigate risks, significantly reducing accidents, equipment failures, and environmental incidents. AI-enabled systems can process vast amounts of data from various sensors, drones, and other IoT devices in real-time, enabling continuous monitoring of hazardous conditions. Furthermore, predictive models can analyze historical data and operational patterns to foresee potential risks before they materialize, providing actionable insights to decision-makers. This approach allows for more dynamic, data-driven safety protocols, optimizing risk management strategies and improving compliance with regulatory standards. The paper will also explore the role of AI in automating routine safety checks, enhancing worker safety through real-time alerts, and minimizing human error. It will highlight case studies where AI-driven HSE systems have been successfully implemented, leading to substantial improvements in safety performance and operational efficiency. Additionally, the challenges and limitations of integrating AI into existing HSE frameworks, such as data security, workforce training, and technology costs, will be discussed. Ultimately, this paper demonstrates that AI-driven HSE management systems offer a transformative solution to risk mitigation in the oil and gas industry. By adopting AI technologies, companies can enhance safety, reduce operational risks, and create more resilient, efficient operations in an industry known for its hazardous environments.
Micro-Chain: A Cluster Architecture for Managing NDN Microservices
Authors: Da Cruz Otávio A. R. , Da Silva Antonio A. S. , Mendes Paulo Milheiro , Do Rosário Denis L. , Cerqueira Eduardo C. , Dos Anjos Julio C. S. , Pereira Carlos E. , De Freitas Edison P.
Published: October 2024

Network Functions Virtualization (NFV) and Information-Centric Networking (ICN) are promising networking paradigms for the future of the Internet. Concurrently, microservice architecture offers an attractive alternative to monolithic architecture for software development. This work addresses a scenario composed of these concepts, where an ICN network must be deployed and managed using ICN microservices. In this scenario, ICN microservices must be created, connected, configured, and monitored at runtime, which is not trivial. To address these challenges, this work proposes Micro-Chain, an architecture for deploying, scaling, and linking ICN microservices. The architecture consists of four modules, relationships between them, and core operations. A Micro-Chain implementation is presented as proof of concept, which has a threshold-based scaling process and a placement method to minimize the number of hops for an ICN microservice chain. The evaluation assesses a scale-on-demand scenario in a cluster with three nodes. The results demonstrate that 1) the developed solution can scale on demand, 2) the communication overhead is 0.632%, and 3) the placement of microservices affects network performance.
Zum Geschichtsbewusstsein von Sozialarbeiter:innen in der Jugendhilfe
Authors: Alting Thure
Published: October 2024

Wie setzen sich Sozialarbeiter:innen in der Kinder- und Jugendhilfe privat, im Zuge ihrer Ausbildung und pädagogischen Praxis mit dem Nationalsozialismus und der Professionsgeschichte Sozialer Arbeit auseinander? Der Beitrag präsentiert Ergebnisse einer quantitativen Studie. Hierfür war die These erkenntnisleitend, dass sich Sozialarbeiter:innen mit den Kontinuitäten des Nationalsozialismus beschäftigen müssen, um der pädagogischen Verantwortung für antisemitismussensible Bildungsräume gerecht zu werden.
Role of Leguminous Crops by Enhancing Soil Fertility and Plant Nutrition
Authors: Rajput Ambrin , Ali Panhwar Qurban , Babar Hafeezullah
Published: October 2024

Food legumes, such as lentils, chickpeas, mung bean, soybean, peas, and beans, have been cultivated worldwide. They are providing essential nutrients and contributing to overall food security. Legumes are rich in protein, ranging from 20 to 45%, and contain essential amino acids, fiber, vitamins, and minerals, making them a nutritionally balanced food source. Biological nitrogen is fixed (90%) by legumes for sustainable agriculture. Meanwhile, the production of various leguminous crops is reduced due to low yield potential, the blend of biotic and abiotic stresses, and environmental changes. The continued cultivation of food legumes in existing cropping patterns is supported by their substantial nutritive values, advantageous cost-benefit ratios, and positive influence on soil health. The strategic integration of legumes into agricultural practices to boost productivity has gained significant attention in response to global food demand. Moreover, legumes play a pivotal role in rejuvenating soil organic matter and addressing problems when included in crop rotations with non-leguminous crops. Research findings that underscore the procedure of N2 fixation stand out as the most environmentally friendly for meeting the substantial nitrogen requirements. This will increase food production in an eco-friendly manner by reducing reliance on agrochemicals and preserving nutrient balances in the soil.
Overview on Municipal Solid Waste
Authors: Priya Rajendren Mohana , Ramu Muthuminal
Published: October 2024

Waste generation around the globe has been enormous in past decades, and also growing rapidly. From statistical data, it is found that every waste generated around the globe is two billion metric tons and it will increase by 70% in 2050. As we all know, municipal solid waste is generated from households, hospitals, and business areas. The items can be paper, cardboard, clothes, kitchen waste, other miscellaneous waste, hospital waste, and a few business scrapes. It is said that each EU citizen produces on average more than 500 kg of MSW a year. Disposing of this effectively involves tedious processing as the material properties differ from each other. The disposing methods are evolving day by day with the help of government and non-government organization. This book chapter proposes to present collective data on municipal solid waste, types of municipal solid waste, policies promulgate with municipal solid waste, effective disposing methods of MSW and how government has established seven-step plans.
Perspective Chapter: Sleep-Related Breathing Disorders – Comprehensive Approach to Obstructive Sleep Apnea
Authors: Perla Sierra Martinez Dianelys
Published: October 2024

This chapter offers a detailed examination of obstructive sleep apnea (OSA), exploring its connection to respiratory physiology and the spectrum of sleep-disordered breathing types. It delves into the pathophysiology of OSA, alongside its epidemiology, risk factors, and clinical manifestations. The chapter outlines diagnostic criteria and severity classification, emphasizing the importance of polysomnography (PSG) and home sleep apnea testing (HSAT). It also addresses the various comorbidities linked with OSA, including cardiovascular, metabolic, and neurological conditions. A key focus is on patient education and the need for a multidisciplinary management approach, highlighting the effectiveness of positive airway pressure (PAP) therapy and alternative treatment options. Overall, this chapter provides healthcare professionals with a thorough understanding of OSA and its comprehensive management.
Blue carbon
Authors:   Parliamentary Office of Science and Technology, Furness Euan , Wentworth Jonathan
Published: October 2024

Marine ecosystems around the UK can both increase and decrease atmospheric carbon dioxide levels. Carbon loss and gain globally by these ecosystems has the potential to influence climate change. This POSTnote summarises the marine ecosystems in the UK that contribute to these processes, their current and potential future extent, and pressures on them.
Defence of space-based assets
Authors:   Parliamentary Office of Science and Technology, Smythe Lucy , Harriss Lydia
Published: October 2024

Space-based assets (satellites and the terrestrial ground stations that communicate with them) provide critical support to military and civilian operations. They are vulnerable to unintentional damage and disruption, and to deliberate attack. This POSTnote outlines how the UK uses and accesses satellites, potential risks to satellites, and approaches to mitigation.
Energy sector digitalisation
Authors:   Parliamentary Office of Science and Technology, Charalampous Rodosthenis , Christie Lorna , Harriss Lydia , Wentworth Jonathan
Published: October 2024

The incorporation of digital technologies in the energy sector can support progress towards key UK objectives such as achieving Net Zero emissions targets. It can also transform current methods of energy generation, transmission, regulation, and trading. This POSTnote presents an overview of key digital technologies and their main applications in the energy sector. It provides an overview of the potential benefits to using these technologies, and recent developments in this area. It describes the role of data in underpinning digital technologies in the sector, and some of the issues raised by its use. It also discusses broader challenges associated with energy sector digitalisation and measures that could help address them, including issues related to technology, regulation, and impact on consumers.
Advances in vaccine technologies
Authors:   Parliamentary Office of Science and Technology, Vagnoni Cristiana
Published: October 2024

This POSTnote provides an overview of vaccine development and technologies. It also covers opportunities and challenges to vaccine discovery and manufacture, as well as policy approaches to stimulate vaccine research and development (R&D) in the UK.
Conversion Therapy
Authors:   Parliamentary Office of Science and Technology, Edmunds Jack , Hobbs Abbi
Published: October 2024

The UK Government intends to prepare legislation in the new year to ban 'conversion therapy' (CT) in England and Wales, for introduction when parliamentary time allows. This POSTnote outlines data on CT and reviews the quality of available research evidence and the impact of CT. It summarises UK stakeholder perspectives on a CT ban and outlines key challenges for policymakers to consider.
Innovative technological advancements in solving real quadratic equations: Pioneering the frontier of mathematical innovation
Authors: S. Nagarani  , Amalraj P.  , Lakshay Phor  , Nishank S. Pimple  , Banashree Sen  , Ramaprasad Maiti  , Vikas S. Jadhav
Published: October 2024

The advancement of computational methodologies in solving real quadratic equations has emerged as a focal point in contemporary mathematical research. This study explores the efficacy of innovative technological tools and interdisciplinary collaboration in revolutionizing quadratic equation solutions. By integrating symbolic computation systems such as Mathematica and MATLAB with numerical libraries like NumPy and SciPy, alongside specialized software frameworks, researchers have unlocked new avenues for precise and efficient quadratic equation solving. Symbolic manipulation techniques, including factoring, completing the square, and utilizing the quadratic formula, provide closed-form solutions, offering a direct approach to solving quadratic equations. Numerical root-finding algorithms, such as Newton's method and the bisection method, along with iterative techniques like fixed-point iteration, contribute to approximating solutions iteratively, enhancing solution accuracy and convergence rates. Real-world quadratic equations from diverse domains, including physics, engineering, economics, and optimization problems, serve as test cases to evaluate the performance of computational methodologies. Performance evaluation criteria encompass accuracy, convergence rate, computational efficiency, and robustness, ensuring the reliability of computational solutions. Statistical analysis and validation techniques validate the accuracy and reliability of solutions against analytical solutions and established mathematical software packages. Interdisciplinary collaboration between mathematics and computer science drives innovation, pushing the frontier of quadratic equation solving.
Fuzzy inventory model with warehouse limits and carbon emission
Authors: Shiny Bridgette I  , Rexlin Jeyakumari S
Published: October 2024

The theory of optimization deals with some techniques to find optimal solutions for a given mathematical problem. This paper examines the use of the Yager ranking method to minimize the total cost in an EOQ. The assortment of goods and different costs with demand must be balanced for an inventory management system to operate without any issues. The sustainable approach takes carbon emissions to be considered with constraints on warehousing capacity. The order lot quantity is not allowed to exceed the capacity limit available warehouse. The parameters are fuzzified by using a trapezoidal fuzzy number. The Yager ranking method is used to find the total cost. Finally numerical example is carried out.
Stochastic artificial neural network for magdm problem solving in intuitionistic fuzzy environment
Authors: P. J. Robinson  , S. W. A. Prakash
Published: October 2024

In this work, we have presented the decision-making models based on ANN, which takes argument pairs, of the intuitionistic fuzzy values and defuzzifies the decision matrices and create Stochastic matrices for producing input for computations of ANN. Concepts from Stochastic processes namely Markov chains and limiting distributions are discussed in detail in this research work and has been applied for effective decision making in complex situations. The numerical illustration provided in this work will be solved using the Markov chain models and some linear space techniques and applied in Artificial Neural Network (ANN). A new Algorithm is also developed for solving the MAGDM problems applying the proposed methods. The Numerical illustrations are solved with defuzzyfication operators and the results are recorded for effectiveness and comparisons are made with some existing methods. The new method proves to be more effective than the previous methods of ANN for MAGDM problems
Neural net influenced magdm problem with modified choquet integral aggregation operators and correlation coefficient for triangular fuzzy intuitionistic fuzzy sets
Authors: P. John Robinson  , P. Susai Alexander
Published: October 2024

With respect to Multiple Attribute Group Decision Making (MAGDM) problems in which attribute values take the form of Triangular Fuzzy Intuitionistic Fuzzy Set (TrFIFS) values, a new decision-making analysis method is developed. First, a novel correlation coefficient for the TrFIFS is proposed and then utilized in the decision-making process for the ranking of the best alternatives. The new correlation coefficient is substantiated by several theorems proved to establish its effectiveness. Then, two TrFIFS Choquet integral aggregation operators are developed and utilized in solving the MAGDM problem. The Triangular  Fuzzy Intuitionistic Fuzzy Improved Choquet Integral Averaging (TrFIFIMCOA) operator for TrFIFS and Triangular  Fuzzy Intuitionistic Fuzzy Improved Choquet Integral Geometric (TrFIFIMCOG) operator for TrFIFS are proposed and some desirable properties are studied. The prominent characteristic of the operators is that they can not only consider the importance of the elements or their ordered positions, but also reflect the correlation among the elements or their ordered positions. Using the proposed two operators, the input vector is produced for Artificial Neural Network (ANN) which is solved to provide an effective solution for MAGDM problem. The newly proposed correlation coefficient and the aggregation operators are effectively utilized to solve real life decision problems. Finally, an illustrative example has been given to show the developed method and comparisons are made with existing methods.
Multi-fuzzy set similarity measures using S and T operations
Authors: P Priyanka , Sabu Sebastian  , Haseena C.  , Bijumon R.  , Shaju K.  , Gafoor I.  , Sangeeth S. J.
Published: October 2024

This paper introduces some similarity measures on multi-fuzzy set, enhancing multi-fuzzy set analysis through a weighting mechanism using S and T operations. Using a fuzzy matrix, we define a weighted relation, summarizing the characteristics of multi-fuzzy set M in relation to a weighted column matrix A. The relation A≤is established by comparing membership grades and weighted elements, expressing similarity or dissimilarity within elements of X.
BTEDD: Block-level tokens for efficient data deduplication in public cloud infrastructures
Authors: K Sabeerath , Manikandasaran S. Sundaram
Published: October 2024

In today's digital era, the exponential growth of data necessitates effective storage and management solutions. The cloud has vast storage possibilities to store huge amounts of data. Public access to the cloud leads to duplicate copies of data stored in the storage. Maintaining a single copy of data in the cloud is most important for efficient data storage management. This paper introduces a groundbreaking strategy for improving the efficacy of cloud storage through innovative data deduplication techniques at the block levels. The block-level duplication verification efficiently identifies the duplicate data in the storage. It helps to protect the duplicate storage in the cloud data storage infrastructure. The block-level deduplication technique uses variable-length blocks based on the duplicate content of the block. Initially, A file is divided into a number of blocks with a size of 5kb. According to the proposed method, If any block is partially matched with a block already stored in the cloud, then that block is further divided into smaller blocks based on the matching percentage. The smaller blocks help to deduplicate the data more effectively. The work is implemented in a live cloud setting with a C# application hosted on MyASP.NET. The proposed methodology's effectiveness is validated against existing deduplication techniques. The results reveal a marked improvement in storage utilization and data management, affirming the potential of the approach to revolutionize cloud storage efficiency.
A self-regulating optimization algorithm for locating and sizing a local power generation source for a radial structured distribution system in deregulated environment
Authors: Shaik Chanbasha  , N. Jayakumar  , N. Bupesh Kumar
Published: October 2024

The Indian power sector is a large and complex network. Maintaining that complex network with the present regulatory format is very difficult for the government as well as transco and discom companies in terms of cost, efficiency, and reliability. That is why the government encourages deregulation in the power sector. One of the deregulation concepts is the integration of local sources into the distribution network. While integrating local sources into the system, several challenges come up, like voltage fluctuations and losses, safety and stability, protection coordination, and mitigation strategies. From those problems, one of the problems is deciding ‘the right place with the right size’ for the local source in RSDS. This work proposes a modified pathfinder optimization algorithm that has a fast convergence rate and the best balance between exploration and mining ability compared to other methods and previous PFOs. Applying MPFO to the IEEE-12 and IEEE-33 test systems to find the optimal place and size of the local source with the help of VSI and LSF. Compare other traditional methods.
Adoption of health information systems in emerging economies: Evidence from Ghana
Authors: Amanda Q. Okronipa  , Jones Y. Nyame
Published: October 2024

This research aims to assess the implementation of health information systems (HIS) in state-owned hospitals in Ghana, particularly focusing on teaching, regional, district, and quasi-government hospitals. The purpose is to evaluate the HIS application, training, data protection measures, internal system communication within hospitals, and the impact of internet connectivity and electricity supply on HIS adoption. The study employed a quantitative research design. Data were collected through questionnaires from 80 healthcare workers across 10 hospitals in Northern, Middle, and Southern regions. Quantitative data was analyzed using frequencies and percentages. The research revealed that although some hospitals had implemented HIS, there was inadequate training for healthcare workers. While data protection measures were in place, challenges included limited internal system communication, hindering effective HIS operation within hospitals. Additionally, poor internet connectivity and electricity supply hindered HIS usage and adoption. This study contributes by uncovering specific challenges in HIS implementation within Ghanaian hospitals, emphasizing the need for enhanced training, internal system communication, and addressing infrastructure limitations.
A resilience framework for fault-tolerance in cloud-based microservice applications
Authors: Punithavathy E  , N. Priya
Published: October 2024

Cloud-distributed systems offer significant opportunities for fault-tolerant applications. Microservices have gained significant acceptance as a cloud-based architecture for building fault-tolerant cloud applications. The primary aim of this study is to develop a dependable resilience framework, incorporating appropriate design patterns, that can be applied to any cloud applications. This framework combines a bulkhead utilizing a little law approach and an auto-retry circuit breaker, which can be seen as a fault tolerance pattern. This will eliminate the need for manual setting of design patterns, resulting in maximum throughput, availability of resources and the performance can be increased up to 55.3% from the average execution duration.
DRMF: Optimizing machine learning accuracy in IoT crop recommendation with domain rules and MissForest imputation
Authors: S Sindhu , L. Arockiam
Published: October 2024

In the realm of IoT-driven precision agriculture, addressing missing data is crucial for reliable crop recommendation systems. This paper proposes the Domain Rules and MissForest (DRMF) algorithm to handle the above mentioned challenge. The proposed DRMF algorithm was thoroughly tested on an IoT agriculture dataset with the introduction of a missingness mechanism in the form of MAR with 10 % of missing values. A comparison analysis with the usual imputation techniques such as Mean Imputation, kNN Imputation, Linear Regression, EM Algorithm, Multiple Imputation, and the standard MissForest was performed and the proposed method was found to perform better. The DRMF algorithm attained an unmatched Root Mean Squared Error (RMSE) value of 0.025 and a Mean Absolute Error (MAE) value of 0.012, displaying a significant superiority over its competitors. It is important to note that the algorithm also achieved a Mean Absolute Percentage Error (MAPE) of 5.0% and an R-squared value of 0.970, with the overall accuracy rate being 99.0%. The quantitative findings serve to emphasize the effectiveness of the DRMF algorithm in improving the prediction accuracy of crop recommendation models. The novelty of this research is in the combined approach that merges the computational power of the MissForest algorithm, and the insight offered by domain-specific agricultural rules.
Classification of glaucoma in retinal fundus images using integrated YOLO-V8 and deep CNN
Authors: R. Sathya , P Balamurugan
Published: October 2024

To propose a new system to identify glaucoma at an early stage with the help of deep learning-based AI method by utilizing Retinal Fundus Images (RFI). The method detects intrinsic key structures in the fundus images to predict retinal nerve layer thickness in order to improve the accuracy of glaucoma detection and classification. To learn complex and hierarchical image representations, the CNN model is used to identify the continuous value of retinal nerve layer thickness from RFI. The Binary Cross Entropy (BCE) loss function is used to perform multi-classification tasks to discover classes such as healthy eye, eye with glaucoma, and glaucoma suspect. In order to identify the local and global features in RFI, the YOLO-V8 object detection method is employed, which also helps to perform image localization, which includes image segmentation, deep optic disc analysis, and the extraction of ROIs. The main focus is given, especially for RNL thickness around OD regions and CDR measurement to perform glaucoma identification tasks. The PAPILA dataset is utilized with the ophthalmology records from 244 patients and includes 488 digital retinal fundus images, covering both left and right eyes for both male and female categories. The CNN model is trained on the PAPILA dataset with labeled RNL thickness values. The performance of CNN-BCE with YOLO-V8 is evaluated using MATLAB and compared against the prevailing approaches such as SVM, ADABOOST, and CNN-Softmax classifiers. The new model outperforms the existing methods with proven results of 98.88% accuracy rate, 0.9 dice-score, 97.74% and 98.03% sensitivity & specificity, 98.6% and 98.78% precision & recall, 98.06% f-score, and 0.92 true positive rates and 0.10 false positive rates under AUC-ROC. This clearly shows that the newly proposed CNN-BCE with YOLO-V8 detects and classifies glaucoma, which helps ophthalmologists perform potential screening and predict better treatments.
Enhancing classification accuracy on code-mixed and imbalanced data using an adaptive deep autoencoder and XGBoost
Authors: Ayesha Shakith  , L. Arockiam
Published: October 2024

This study introduces a pioneering approach for enhancing classification accuracy on code-mixed and imbalanced data by integrating an adaptive deep autoencoder with dynamic sampling techniques. Targeting the intricate challenges of sentiment analysis within such datasets, this methodology employs an enhanced XGBoost classifier, optimized to leverage the nuanced features extracted by the autoencoder. The experimental evaluation across diverse datasets, predominantly involving Tamil-English code-mixed texts, demonstrates a notable improvement in performance metrics: accuracy reached 84.2%, precision was recorded at 74.8%, recall stood at 78.4%, and the F1-Score achieved 76.6%. This marks an enhancement over existing methods by 0.5% to 1.5%, substantiating the model's robust capability in effectively handling linguistic diversity and class imbalances. The novelty of this research lies in the seamless integration of dynamic sampling within the autoencoder's training loop, significantly boosting the adaptability and effectiveness of the machine-learning model in real-world applications.
A novel and an effective intrusion detection system using machine learning techniques
Authors: Remya Raj B.  , R. Suganya
Published: October 2024

Network environments become more and more diverse with the presence of many different network protocols, services, applications and so on. With this diversity, many different types of attacks appear and target at a computer or a network every day. A single type of intrusion detection systems (IDSs), which has its own advantages and disadvantages, seems to be insufficient to detect all the attacks. Since us don’t know which types of attacks are coming next, the primary difficulty lays on selecting of the best IDS at a certain time. In our scenario, we assume that each IDS has its own favorite types of attacks to detect. In this paper is investigated for intrusion detection system (IDS) and its performance has been evaluated on the normal and abnormal intrusion datasets (KDDCUP99). New technique of k-NN algorithm using NA (Network Anomaly) rules for intrusion detection system is experimented. The research work compares accuracy, detection rate, false alarm rate and accuracy of other attacks under different proportion of normal information. Comparison between Naive Bayes classifier, SVM and NA-kNN for same training data set and testing data set has carried out. Experimental results show that for Probe, U2R, and R2L, NA-kNN gives better result. Overall correct count to detect correct attacks is larger in NA-kNN than other classifier algorithms.
Exploring the mediating role of gastronomic experience in tourist satisfaction: A multigroup analysis
Authors: Berry Karan , Kumar Shiv
Published: October 2024

Gastronomic experience encountered by tourists in a famous local food outlet plays a crucial role in delivering overall satisfaction with the destination. Previous studies widely acknowledge the importance of region’s cuisine in enhancing gastronomic tourism, and have identified various types of tourists depending upon their interest in local food preparations. This empirical analysis presents a novel approach in investigating the mediating role of gastronomic experience in the relation between gastronomic motivation, and overall satisfaction of the tourists who are segmented according to the relevance of local gastronomy in their destination selection, in context of famous local food outlets which offer delectable traditional Punjabi cuisine in the holy city of Amritsar, proclaimed as the food capital of Punjab. Data was gathered through a well-structured, and self-administered survey questionnaire circulated amongst the tourists after their gastronomic encounter. The constructs of the study were specified as reflective or formative as per the nature of their measurement indicators. Hierarchical and K-means cluster analysis was used for segmentation, and PLS-SEM was further utilized to conduct Multigroup analysis, after ascertaining the common method bias, and measurement invariance using the MICOM process. The results reveal full mediation exhibited by gastronomic experience, and an insignificant difference between the tourist segments on the strength of proposed relationships amongst the study’s constructs. Implications and suggestions are provided for the owners, and managers of local food outlets, the government and all other stakeholders linked to the enhancement of tourist experience at the destination. Future studies may replicate the current model in other tourist destinations, to further validate the findings.
Study on the right to education with special references to public private partnerships
Authors: Nilay Shukla  , Ketan Desai
Published: October 2024

The Indian education system faces significant challenges in providing quality education to all its citizens, particularly in the context of limited government resources. Public-private partnerships (PPPs) have emerged as a critical strategy to bridge this gap, leveraging private sector participation in financing and managing educational institutions. This paper examines the evolving landscape of education under PPP models in India, focusing on the implications for the right to education. Through a comprehensive review of literature and analysis of case studies, the study explores how PPPs influence access, equity, and quality in education, while also addressing concerns related to privatization and accountability. By evaluating the successes, challenges, and policy implications of PPPs in education, this research contributes to the broader discourse on the role of private sector involvement in fulfilling the right to education in developing countries.
Navigating fake reviews in online marketing: Innovative strategies for authenticity and trust in the digital age
Authors: Thilagavathi K  , Thankamani K.  , P. Shunmugapriya  , D. Prema
Published: October 2024

The prevalence of fake reviews and ratings in online marketing has become a significant issue, undermining consumer trust and damaging business reputations. This study aims to identify the extent and impact of fake reviews and explore innovative strategies for traders to combat this problem and maintain authenticity. A mixed-method approach was adopted, including a survey of 100 respondents to gauge public awareness and perception of fake reviews. The findings highlight the critical need for advanced detection methods, increased transparency, and consumer education to foster trust in online platforms. Statistical analyses, including ANOVA and Chi-Square tests, were used to analyze the data. The survey revealed that 75% of respondents encounter fake reviews frequently, with 40% being highly aware of the issue. The impact of fake reviews on purchasing decisions is significant, affecting 80% of the respondents. To address this issue, traders can implement advanced AI algorithms, encourage genuine reviews through incentives, increase transparency through verification processes, and collaborate with review platforms to establish stricter monitoring systems. Additionally, educating consumers about identifying fake reviews and promoting ethical online behavior are crucial steps towards mitigating this issue. This study concludes that by adopting these innovative strategies, traders can protect their reputations, foster consumer trust, and ensure the authenticity of online reviews and ratings. Future research should focus on developing more sophisticated detection technologies and exploring the long-term effects of fake reviews on consumer behavior and market dynamics.
Inclusive education for children with learning difficulties in Mauritius: An analytical study among select stakeholders
Authors: Pritee Rajaram Ray  , Bijal Zaveri
Published: October 2024

The present research explores the intricate terrain of inclusive education in Mauritius, providing insightful viewpoints on the implemented practices, policies, and support networks. Through the integration of quantitative and qualitative research approaches, this study offers a thorough examination of the situation of inclusive education, allowing for the identification of learning-disabled children in Mauritius. The results offer useful information that help improve policies and regulations to improve these kids' educational outcomes and experiences. Using both quantitative and qualitative methods, this study examines inclusive education for kids with learning disabilities in Mauritius in great detail. Parents, educators, and representatives from pertinent organizations participate in the research. The research delves deeply into their viewpoints, issues, and experiences. Twenty-five parents of children with learning disabilities participated in a survey that was part of the study's quantitative component. The purpose of the study was to collect quantitative information about parents' experiences and viewpoints on inclusive education in Mauritius. The qualitative phase involved conducting in-depth interviews with a wide range of individuals. ECCEA, SENA, speech and language pathologists, one integrated school, five parents, ten non-profit special education teachers, and a representative from academics were among them. These interviews were carried out in order to acquire more data on the various facets of inclusive education, including the difficulties encountered, workable solutions, and the duties of various stakeholders.
Dark web exploitation of women and children: Understanding the phenomenon and combating its impact
Authors: G GAYATHRI DEVI  , Dr R Radha
Published: October 2024

The hidden nature of the dark web makes it easier to exploit vulnerable groups, particularly women and children. This research explores how they are exploited on the dark web, including what causes it, common ways it happens, the difficulties law enforcement encounters, and steps to prevent and address it. By combining existing research, case studies, and expert opinions, this work aims to provide a comprehensive understanding of the issue and suggest practical solutions. While the internet has brought positive changes, its hidden parts like the Dark Web pose significant risks to vulnerable people. This study sheds light on the dangers women and children face online, such as human trafficking, child exploitation, and cyber bullying. Its goal is to safeguard their online safety and well-being by promoting prevention and policy adoption.
Evaluasi Kesesuaian Lahan untuk Pengembangan Tanaman Buah Naga di Kecamatan Tilatang Kamang
Authors: Asyifa Ifni , Triyatno Triyatno
Published: October 2024

The purpose of this reseach are : 1) To analyze the suitability of the actual land of dragon fruit plants in Tilatang Kamang District, 2) To analyze the distribution pattern of dragon fruit plantation in Tilatang Kamang Diztrict. This type of research uses a quantitative descriptive approach with the fuzzy logic method to analyze land suitability and Nearest Neighbor analysis to analyze the distribution pattern of dragon fruit plantation. The results of the reseach are: 1) The suitability of dragon fruit crops obtained using fuzzy logic analysis obtained the area for the value of the land suitability index of the category not less than 0 – 0,59 has an area of 1.393,75 Ha with a percentage of 26,63% and for the category index is quite suitable to 0,6 – 0,79 has an area of 3.840,52 Ha with a percentage of 73,34%. 2) The distribution pattern of dragon fruit orchards in Tilatang Kamang District is a grouping pattern with the value of Nearest Neighbor Ratio = 0,31.
Ruang Lingkup Administrasi Pendidikan: Tantangan dan Solusi dalam Meningkatkan Efisiensi Sekolah
Authors: Fathimah Meti , Ghafur Octa Abdul , Winarno Andhika Sarfatra
Published: October 2024

Educational administration plays a pivotal role in ensuring the smooth operation and efficiency of educational institutions at all levels. This paper discusses the scope of educational administration, focusing on key functions such as planning, organizing, implementing, and monitoring. In addition, it examines the common challenges faced in the practical implementation of educational administration, such as limited human resources, inadequate funding, and minimal external support. By offering practical solutions to these challenges, this study aims to contribute to the development of more efficient administrative practices, thereby enhancing the quality of education and achieving broader educational goals.