bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing the Content Relevance of Gender-based Violence News Articles in Tanzanian Newspapers on Reducing the Problem
Authors: Hamad Ali Haji
Published: October 2024

Aims: The purpose of the study was to assess the content relevance of Gender-based Violence (GBV) news articles in Tanzanian newspapers on reducing the problem.
The study applied Agenda setting theory (McCombs and Shaw, 1972) as a leading theory complemented by the Priming theory (Iyengar, Peters, and Kender, 1982) and Framing theory (Gregory Bateson, 1972).
Study Design: The study adopted a triangulation approach where both quantitative and qualitative methods and tools were applied.
The study was conducted between September 2022 and January 2023 in six regions of Tanzania Mainland (Dodoma, Iringa, Kigoma, Mtwara, Mwanza, and Tanga) and two main Islands of Zanzibar (Unguja and Pemba).
Methodology: The study was cross-sectional and applied a triangulation approach whereby both qualitative and quantitative research methods were applied in data collection, analysis, and reporting. It involved 161 respondents and 297 copies of five daily newspapers for data.
Findings: From the study, it was revealed that GBV content had little relevance. It was scarcely reported; that was, only 2% of GBV articles out of 14,618 were identified. There was also a significant variation in GBV reporting between newspapers - the highest percentage of articles in newspapers was 0.76% and the lowest was 0.06%. In addition, the study revealed sexual violence was reported more frequently 36% and psychological violence less frequently 11%. Furthermore, Kiswahili newspapers carried 80% of all GBV articles compared to 20% of English newspapers.  GBV articles were geographically relevant but were not enough to motivate respondents to read newspapers. Hence the majority of the respondents 52% were not satisfied with the usefulness of GBV issues reported in newspapers.
Conclusion: The study concluded that most of the contents of GBV articles in the Tanzanian newspapers had little relevance and thus low contribution to reducing GBV in the country. It was therefore recommended that media houses/outlets should think of establishing special GBV reporting desks, investing in investigative reporting of GBV, and considering the recruitment of specialized GBV editors and reporters.
High Pressure Processing: Pros and Cons
Authors: Sharma Pinki S , Swami D.V. , Ramya M. , Khayum Arshad , Kapoor Manish
Published: October 2024

The food industry now uses high pressure processing to increase the shelf life of foods and maintain their nutritional value. This non-thermal preservation technique can successfully inactivate rotting and spoilage-causing bacteria and enzymes without the need for high temperatures during the preservation process. Food is exposed to high pressure, usually in the range of 100 to 600 MPa. High-performance processing keeps food at or slightly above room temperature to prevent heat-sensitive flavors and nutrients from being thermally destroyed during food preparation. This contributes to the preservation of the natural sensory and nutritional properties of the product. Because this process is able to eliminate bacteria and organisms responsible for spoilage, it is a very efficient way to increase the time available to eat foods. Unlike traditional heat-based methods, HPP inactivates harmful microorganisms and enzymes through the application of extreme pressure (100–600 MPa) at low temperatures, thereby reducing thermal degradation. HPP also helps retain bioactive compounds, making it an ideal choice for consumers looking for minimally processed, high-quality foods. This article explores the principles, applications, and benefits of HPP, as well as the challenges and future prospects of its integration into food processing systems.
Dragonfly: A Master of Migration
Authors: V Sandeep , S Chinmayi , K. M Sujith , Maheshwar Nallasamy , C N Amogh , G. N Tejashree , Varalaxmi Kota
Published: October 2024

Insect migration is vital for ecosystems, with trillions of individuals redistributing biomass and nutrients annually. Dragonflies, particularly Pantala flavescens are notable migratory insects capable of traveling over 6,000 kilometres across generations. Their migrations are influenced by resource availability, breeding needs, environmental conditions, and competition avoidance. This behaviour includes both seasonal movements and sporadic flights triggered by temperature and wind cues. Despite their well-known life cycle from aquatic nymphs to aerial adults, many aspects of their migration remain under-researched. Dragonflies exhibit diverse flight mechanisms, employing four distinct modes: counter-stroking for hovering, phased-stroking for cruising synchronized stroking for acceleration, and gliding for energy conservation. Migratory species show specific wing adaptations for improved endurance, such as elongated forewings and larger hindwings, along with sensory enhancements like enlarged thoracic setae. Specialized flight muscles allow for independent wing control, essential for complex movements. Additionally, physiological adaptations like fat accumulation and rapid development support their migratory behaviour. Recent studies also highlight nocturnal migrations, revealing unique flight patterns and adaptations. Together, these traits underscore the evolutionary success of dragonflies in diverse ecosystems.
Assessment of Yield and Economics under High Density Planting System in Cotton in Kachchh District of Gujarat, India
Authors: Singh Traloki , Singh S.P. , Anand K.B. , Rai Tralok Nath , Sahu Anjali , Gupta V. P.
Published: October 2024

Cotton (Gossypium hirsutum L.) possesses a position of major fiber and cash crop, which plays vital role to sustain national economy. It provides the basic raw material (cotton fiber) to cotton textile industry. Gujarat contributes substantially to the national cotton area (24%) and productions (37%). A field experiment was carried out during the kharif seasons from 2017-18 to 2019-20 at farmers' fields through ICAR-CAZRI Krishi Vigyan Kendra Kachchh-II to evaluate the impact of frontline demonstrations (FLDs) on cotton productivity and profitability. During the experiment period, a total of 30 FLDs on high density planting system (HDPS) in cotton with the high-yielding variety GTHH-49 were demonstrated in a 12-hectare area across 6 villages in the Bhuj, and Nakhatrana talukas of Kachchh district. The improved variety GTHH-49 with a full package of practices was demonstrated in the plots, while existing technology was treated as the local check. Based on three years of data, the improved practice (IP) resulted in an average seed yield of 2868 kg ha-1, which was an increase of 13.35% compared to the local check yield of 2530 kg ha-1. The demonstrated technology showed an average extension gap, technology gap, and technology index of 338.33 kg ha-1, 631.67 kg ha-1, and 18.05%, respectively. The economic analysis of the demonstrations revealed the viability of the improved technology, with a net return of 101670.3 Rs. ha-1 and a benefit-cost ratio (BCR) of 3.24, compared to 84964.67 Rs. ha-1 and a BCR of 3.02 for local check. A wide range of extension and technology gaps had a detrimental influence on crop output and net returns in general. The results revealed that the adoption of the high-yielding variety with a full package of practices significantly increased cotton productivity and reduced both extension and technology gaps.
First Global Host Report and New Distribution Record of Bactrocera penecorrecta Drew (Diptera: Tephritidae) from Bihar, India
Authors: Kumar Amit , Singh Maneesh Pal , Kunal Gautam , Sinha Mukesh Kumar , Prabhakar Chandra Shekhar
Published: October 2024

This study showed that brinjal, Solanum melongena Linnaeus is the first global host of the fruit fly, Bactrocera penecorrecta Drew (Diptera: Tephritidae) from Bihar, North India. Earlier report of B. penecorrecta was from Kerala, South India. In the present investigation, B. penecorrecta was recorded 22 years after its discovery in Kerala, South India in 2002 by R. A. I. Drew and S. Raghu. The record of brinjal as the first host of B. penecorrecta warrants in in-depth investigation of the level of infestation and sanitary and phytosanitary protocol development for the export as many recent invasions by different Bactrocera species in various part of the world beyond their native distributional records.
Assessment of Standard ChrysanthemumGenotypes for Morphological and Floral Attributes in Terai Region of West Bengal, India
Authors: Sarkar Dipayan , Sarkar Indrajit , Maitra Soumen , Chatterjee Ranjit , Khalko Surajit , Ojha Sankalpa
Published: October 2024

Aims: Chrysanthemum (Dendranthema grandiflora Tzvelev) is one of the most economically important and economically favoured floricultural crops used as cut flower, loose flower, potted plants, bedding and border plants, making garlands, flower decoration, bracelet, venis and religious offerings. The present study aimed to evaluate and select suitable large flowering chrysanthemum cultivars for commercial cultivation in Terai region of West Bengal.
Location of the Study: The experiment was conducted in the Instructional Farm, Department of Floriculture, Medicinal and Aromatic Plants, Faculty of Horticulture, Uttar Banga Krishi Viswavidyalaya during the period of September to February of 2022-23 and 2023-24.
Materials: Thirty five different cultivars of large flowering chrysanthemum were evaluated based on their growth and flowering parameters viz. Angel Bell, Autumn Blaze, Autumn Day Light, Bolare Deo, Cassa Granda Yellow, Chengis Khan, Coronation Gold, Cossak, Diamond Jubilee, Dignity, Dream Castle, Golden Yellow, Green Goddess, Innocence, J.S.Loyed, Jane Sharp, Jessie Hab Good, Kasturba Gandhi, Kenroken Pink, Kenroken White, Kikubiory, Lady Frank Klerk, Phil Houghton, Pink Cloud, Pinkling, Raja, Red Wine, Royal Prince, Royal Purple, Silk Brocade, Snowball, Sonar Bangla, Temptation, Willium Turner and Yellow Reonet.
Methodology: One month old rooted cuttings were planted at a spacing of 40 cm X 30cm (Row to row 40cm and plant to plant 30cm) in 1.6m X 1.2 m raised bed. Total 16 plants were planted in one plot.
Statistical Design: The experiment was laid out in completely randomized block design replicated thrice. Collected data was analyzed by one-way analysis of variance with the help of SPSS software.
Results: Significant variation was observed among the genotypes. Maximum plant spread (N-S) of 36.33±5.90, 39.00±1.55 and 37.67±4.13 cm was observed in Snowball in the year 2022-23, 2023-24 and pooled respectively whereas minimum plant spread (N-S) of 16.42±1.73 cm was observed in Cassa Granda Yellow. The maximum number of flowers per bed 282.74, 291.34 and 287.04 was recorded in Pinkling during the first year, second year, and pooled data, respectively, while the minimum number of flowers per bed (140.60 and 149.55) was observed in Autumn Blaze during the first year pooled data, respectively while in second year Pink Cloud (145.40) recorded the minimum numbers of flowers per bed.
Conclusion: From the study, it may be recommended that the cultivars like Snowball, Sonar Bangla, Pinkling, Temptation are suitable for cut flowers. The cultivars namely Silk Brocade, Pink Cloud, Diamond Jubilee, Corronation Gold, Innocence, Kenroken White and Kenroken Pink may be selected for pot plants and for garden display due to profuse uniform branching and blooming.
Combining Ability and Heterosis Analysis in Maize: Insights from Line × Tester Hybridization
Authors: Vardhini Talatam Ramya , Kumar I. Sudhir , Rajesh A. Prasanna
Published: October 2024

Fifty hybrids were obtained by crossing twenty five lines with two testers and were evaluated to study heterosis and combining ability for kernel yield per plant and its components traits. The experiment was laid out in simple lattice design with two replications during kharif 2019 at Agricultural Research Station, Peddapuram, East Godavari District, Andhra Pradesh. Heterosis studies revealed that twelve out of fifty crosses exhibited significant positive heterosis over the mid-parent, five crosses showed significant positive heterosis over the better parent and one cross exhibited significant positive heterosis over the standard check, DHM117, for kernel yield per plant. The cross PDM1732 × BML6 recorded significant heterosis over mid parent, better parent and standard check in desirable direction for kernel yield per plant. Out of the 25 lines evaluated in the present investigation, the line PDM1733 for protein content and kernel yield per plant was found to be good general combiner in desirable direction and can be utilized as parent for production of good hybrids by crossing with other divergent lines and can also be employed in the development  of synthetic varieties. None of the fifty crosses recorded significant sca effect for kernel yield per plant.
Standardization of Recipes and Storage Behaviour of Value-Added Products from Knol-Khol (Brassica oleracea var. gongylodes L.)
Authors: Kaur Gurpreet , Sharma Ashutosh , Kumar Rahul , Sharma Neha , Sharma Shivam , Sharma Sonika
Published: October 2024

Knol-khol (Brassica oleracea var. gongylodes L.) is one of the most important cruciferous vegetable crops which belongs to the family Brassicaceae. Knol-khol is a fast growing, cool season vegetable cultivated primarily for its enlarged stem called ‘knob’ which is rich in nutritional components, especially vitamin A, C, minerals and is also a good source of potassium, phosphorus, calcium, iron and sodium. To exploit its high nutritional as well as antioxidant properties and also to ensure its year around availability, it needs value addition. Therefore, in the current investigation, value added products viz., nectar and squash were prepared from Knol-khol. Four recipes of prepared nectar and squash were subjected to physico-chemical and sensory evaluation soon after preparation and at 90 days of storage. During the storage, a slight increase in pH, TSS and total sugars, a considerable rise in reducing sugars, but a slight decrease in acidity and also a considerable decrease in non-reducing sugars and ascorbic acid was recorded in various treatments of nectar and squash. The treatments K2N2 (15% pulp, 15˚B), and K1T2 (25% pulp, 45˚B TSS) among different recipes of nectar and squash respectively were found to be the best on the basis of their physico-chemical and organoleptic evaluation. These findings suggest that specific compositional parameters significantly influence the quality and acceptability of fruit-based beverages during storage.
Comparative Evaluation of Antibiotic Therapies for Subclinical Staphylococcal Mastitis in Goats
Authors: Patel Manoj , Gupta Devendra Kumar , Singh Mrinal , Pratap Aditya , Rai Ajay Kumar , Jain Supnesh , Suryavanshi Nitesh , Jatav Ranbir Singh , Mudiya Bhoopendra Kumar
Published: October 2024

Subclinical mastitis (SCM) is characterized by inflammation of the udder without visible signs of inflammation in the animal, udder and milk and hence could be diagnosed by laboratory examination only. Effective treatment of SCM in goats is crucial for maintaining quality milk production. This study was conducted at the Department of Veterinary Medicine, College of Veterinary Science and Animal Husbandry, Nanaji Deshmukh Veterinary Science University, Jabalpur (M.P.), India. A total of 236 lactating goats irrespective of age, breed, parity and stage of lactation, from both organized and unorganized sectors in and around Jabalpur, were screened over a period of six month. Based on modified California mastitis test scores, 83 goats tested positive for subclinical mastitis resulting in an overall occurrence of 35.17% (83/236).  A total of 48 milk samples that tested positive for modified California mastitis test were further analyzed for bacterial isolation and identification. Among them, 34 (70.83%) samples were positive for only Staphylococcus spp., while 12 (25%) samples exhibited mixed infection with Staphylococcus spp. and Gram-positive bacilli. Then, 18 goats, positive for subclinical Staphylococcal mastitis were divided into three groups i.e. G1, G2 and G3 with six goats in each group for therapeutic study and six apparently healthy goats were taken as healthy control group (G4). G1 Goats were treated with Inj. Enrofloxacin LA @ 7.5 mg/kg b. wt. I/M single dose; G2 with Inj. Ceftizoxime @ 10 mg/kg b. wt. I/V single dose and G3 with Inj. Oxytetracycline LA @ 20 mg/kg b. wt. I/M single dose. The responses of therapeutic assessment were evaluated on the basis of somatic cell count and modified California mastitis test score. The most effective response for subclinical Staphylococcal mastitis in goats was observed with Ceftizoxime followed by Enrofloxacin LA and the least with Oxytetracycline LA.
Evaluation of Immunohistochemical Expression of IDH, ATRX and Ki-67 in the Diagnosis and Classification of CNS Gliomas
Authors: Elhalaby Rofyda Essam , Elazeem Mona Abd Elhaq Abd , Makshat Mohsen Mahmoud , Ellitty Mohammed Mosaad , Eid Asmaa Mustafa
Published: October 2024

Background: WHO blue book has emphasized on incorporating histopathological as well as molecular basis for accurately diagnosing and risk stratifying cases of brain gliomas. Using surrogate immunohistochemistry may substitute molecular testing especially in low-income countries.
Aim: this retrospective cohort study was carried out at the Pathology department, Tanta university to evaluate the immunohistochemical expression of IDH, ATRX and KI-67 in diagnosis and classification of brain gliomas.
Materials and methods: Two hundred and fifty (250) formalin-fixed paraffin-embedded tissue blocks from cases with CNS tumors were evaluated for immunohistochemical expression using IDH, ATRX and KI-67.
Results: In cases of diffuse gliomas; tumor types showed significant difference as regard age of patients (p<0.001), as well as IDH1 and ATRX immunohistochemical expression (p<0.001). The proliferation index of Ki-67 also showed significant difference amongst groups (p<0.001). One hundred and ninety-six cases of diffuse gliomas were classified following immunohistochemical staining into 89 IDH-mutant tumors (45.4%) and 107 IDH-wild type tumors (Glioblastomas) (54.6%). Eighty-nine cases of IDH-mutant gliomas were further sub classified based on cell of origin and WHO grade into astrocytomas; grades 2, 3 and 4, as well as oligodendrogliomas; grades 2 and 3. In cases of localized gliomas; No significant data were detected as regard age of affected patients, or tumor location. All cases showed negative staining for IDH1 and retained nuclear expression for ATRX. The proliferation index showed variance amongst tumors (p<0.001). A comparison group of patients with reactive gliosis was also studied and showed negative staining for IDH1, retained ATRX expression with low Ki-67 proliferation index.
Conclusions: IDH, ATRX and Ki-67 may be beneficial in categorizing and properly diagnosing patients with brain tumors; which may serve not only as a surrogate for molecular testing, but also can guide therapeutic decisions.
Assessing Farmers' Knowledge of Sugarcane Production Technology in Haryana, India
Authors: Agarwal Disha , Chahal P. K. , Ghanghas B. S. , Mishra Ishita , Mohit  , Joshi Akansha
Published: October 2024

Aim: This study aims to assess the knowledge level of sugarcane growers in Haryana, India, regarding sugarcane production technology and to propose strategies for enhancing their knowledge.
Methodology: A total of 120 sugarcane farmers were purposively selected from three key sugarcane-producing districts: Yamuna Nagar, Kaithal, and Rohtak. Farmers were interviewed using a well-structured knowledge assessment schedule covering ten key components of sugarcane production. Statistical tools including weighted mean score, correlation analysis, and ranking were employed to analyze and interpret the data.
Results: The study revealed that 68.34 per cent of farmers had a medium level of knowledge regarding production technology, with significant gaps observed in manure and fertilizer use (75.80% lacked full knowledge) and pest control. On the other hand, 85.00 per cent of farmers had full knowledge of irrigation practices. Positive correlations were found between knowledge levels and factors such as education, income, social participation, and media exposure.
Conclusion and Recommendations: Strengthening farmers' knowledge through systematic education and extension services is essential for bridging the technological gap and improving agricultural productivity. To address these knowledge gaps, the study recommends targeted extension programs, farmer training workshops, and the use of mass media to improve farmers' access to updated agricultural practices. Increased collaboration with agricultural cooperatives and research institutions could also play a vital role in enhancing farmers' knowledge and boosting sugarcane production in the region.
Cyber Insecurity For Internet Banking
Authors: Rana Mohammad Shohel , Islam Md. Majidul
Published: October 2024

Internet banking has become a crucial aspect of modern financial transactions, enabling customers to access their account information and perform various transactions from anywhere. Ensuring the security of these transactions is one of utmost importance, and this is where authentication protocols come into play. One such protocol is Kerberos, which is widely used for secure authentication in many applications, including internet banking. In this paper we discuss the basic operations and functionalities of Kerberos while pinpointing the advantages of using Kerberos as an authentication protocol in internet banking. We also discuss the security features of using Kerberos, including its use of encrypted tickets and its ability to prevent replay attacks
Neural Machine Translation Between English And Bangla: A Philosophical Survey Observing Architectures And Performances
Authors: Ansary MD. Abdul Awal
Published: October 2024

Neural Machine Translation (NMT) is a state of the art of machine translations that uses neural network models to translate text from one language to another. Unlike traditional machine translation methods, which rely on statistical models and rule-based systems, NMT leverages the power of deep learning, specifically using techniques such as recurrent neural networks (RNNs), long short-term memory networks (LSTMs), or more recently, transformers. Neural Machine Translation represents a significant dive forward in the field of automatic translation, leveraging the latest advancements in deep learning to deliver more accurate and natural translations. The progress in NMT has been remarkable, driven by advancements in model architectures, multilingual training, pretraining techniques, increased computational power, and the availability of vast multilingual datasets and improved evaluation metrics. These developments have collectively enhanced the quality, efficiency, and applicability of NMT systems across various languages and domains. In this article we will explore the technologies and performances of NMT between English and Bangla Language pair from its launching periods to present.
Demystifying The Object-Oriented Features Of Popular Object-Oriented Programming Languages.
Authors: Onu Fergus U , Oliver Ifeoma Catherine , Hyginus Mamah Chukwurah , Yinka Afolabi Idris , O Nwodo John , Sunday Yunisa
Published: October 2024

Background: Indeed, Object-Oriented Programming (OOP) has emerged as one of the major fundamental paradigms in today’s world of software development as it contains principles that enhance modularity, reusability, and maintainability of software. This article explores deeper into some of the facets of OOP aspects as exhibited in some of the most frequently used programming languages ranging from Java, Python, C++, and C# with an intent of offering substantive information to aspects like encapsulation, inheritance, polymorphism, and abstraction. The article synthesizes the ones focusing on the relevance and conceptualization of OOP and problems related to it in the context of learners and practitioners. It also describes strengths and weaknesses of using C++, Python, and Java in relation to OOP while stressing peculiarity of these languages. Some of the core principles of OOP are highlighted such as encapsulation, inheritance, polymorphism, and abstraction and how they are complicated and significant in today’s software engineering. Materials and Methods: There was a presentation of a survey on which the research is based to determine the problems that programmers encounter when applying OOP features using a sample of 80 programmers in the computer science fields in some Nigerian Universities. Results: Findings reveal the significance of understanding OOP concepts in popular languages and suggest ways of increasing developers’ efficiency, minimizing errors, and improving the quality of developed software. Conclusion: Suggestions include a necessity for training and education to enhance software developers' understanding of OOP features. The findings can guide the creation of training materials and courses centered on OOP concepts, aiming to improve software development practices and elevate the quality of software products.
Automated Water Regulation Systems for Sustainable Management
Authors: Thiruchelvam Taejaayn
Published: October 2024

Finding new ways to manage water resources becomes even more relevant today, as the growing demand for food globally combines with challenges like climate change and water scarcity. This research paper attempts to discover the automated water regulation systems that utilize advanced technologies like Artificial Intelligence (AI), the Internet of Things (IoT), and data interpretation to upgrade irrigation practices and boost sustainable resource management. By using sensors that keep the soil moisture and the environmental conditions in check, accurate modifications can be made to the irrigation being provided. Keeping a check can help reduce water wastage by up to 30% and increase crop yield by an average of 15%. This study amplifies the productivity of smart meters and the demand for AI-driven prediction models that are capable of providing accurate forecasts and real-time data, both of which are very necessary for efficient water management. However, there exist challenges like the question of data security, high initial costs, and user acceptance. These challenges need to be addressed to make sure that these systems are widely adopted. The considerable potential of the automated water management systems to promote sustainable practices in agriculture and to ensure food security when water scarcity is increasing are highlighted via the findings made in this paper. 1 This paper has been written after taking several research papers written by scholars and professors in this field. Taking into consideration their findings and observations, and incorporating personal observations and the potential results that can be applied, this paper is drafted to recommend practices that will help support vegetation and sustainable practices.
A Review Of Autism SpectrumDisorder Detection Using Machine Learning
Authors: Khan Rubeena , Singh Devesh Sandeep , Hussain Shaikh Umme Hanni Aiyaz , Phadtare Sakshee Vijay , Aslaan Mohammed
Published: October 2024

A neurological condition known as an autism spectrum disorder (ASD) profoundly impacts an individual's lifelong ability to engage and interact with others. ASD is an illness that can be recognized at early stages in a person's life and is often classified as a "behavioral disease" due to the presence of numerous symptoms that frequently manifest within the first two years of life, as per what most people believe about autism theory, these challenges typically emerge during childhood and endure into adolescence and adulthood [1]. In response to the growing popularity of medical diagnosis, machine learning techniques [2] are used to help doctors make better decisions about a person's health, extensive efforts have been made to leverage various algorithms, including Naive Bayes, Support Vector Machine, Logistic Regression, K-Nearest Neighbors (KNN), Neural Networks, and Convolutional Neural Networks (CNNs) [3], to predict and analyze ASD-related issues across different age groups—children, teenagers, and adults. These endeavors have been detailed in a researchsurvey paper. These predictive models were assessed using the ABIDE dataset, which is openly accessible for research purposes. The study's findings underscore the effectiveness of CNN-based prediction models, which consistently outperformed other machine-learning techniques [4]. Notably, these models achieved impressive accuracy rates of 99.53%, 98.30%, and 96.88% for screening and diagnosing Autistic Spectrum Disorder in datasets representing adults, children, and adolescents, respectively.
Agile Supply Chain Management In FashionIndustry
Authors: Sampath.M Iyer Srilakshmi , Cholli Dr. Nagaraj.G.
Published: October 2024

The fashion industry is one of the most globalized sectors, featuring a complex and widespread supply chain. Often, clothing is designed in one country, produced in another, and then distributed and sold across multiple international markets. This global scope and complexity necessitate an agile approach to supply chain management. Agile supply chains are engineered to be flexible, responsive, and adaptable, enabling companies to swiftly respond to shifts in consumer demands and market conditions. By adopting agile principles, fashion companies can more effectively navigate the intricacies of global operations, ensuring that products reach the appropriate markets at the right time, thereby sustaining competitiveness and meeting consumer expectations in a fast-paced industry
Plant Leaf Disease Detection System Using Machine Learning And Deep Learning: A Survey
Authors: Sharma Mr. Abhishek , Bansal Mr. Rohit
Published: October 2024

Plant diseases are becoming more common, which is a serious threat to profitability of agriculture worldwide and requires the creation of reliable and efficient disease detection technologies. This work uses machine learning (ML) and deep learning (DL) approaches to give an extensive assessment of previous research on plant leaf disease identification. We examine and evaluate the many approaches used in the last several research, emphasizing the advantages, disadvantages, and useful uses of each. The study covers both sophisticated deep learning designs, such as convolutional neural networks (CNN) and recurrent neural networks (RNN), as well as more conventional machine learning techniques, such support vector machines (SVM) and decision trees. According to our research, plant leaf diseases can be more accurately identified and classified using deep learning techniques, especially CNNs, when applied to a variety of crop categories. The study also looks at the field’s obstacles and promising directions, highlighting the use of multifaceted approaches and real-time illness monitoring systems.
A Review Of Autism Spectrum Disorder Detection Using Machine Learning
Authors: Khan Rubeena , Hussain Shaikh Umme Hanni Aiyaz , Singh Devesh Sandeep , Phadtare Sakshee Vijay , Aslaan Mohammed
Published: October 2024

A neurological condition known as an autism spectrum disorder (ASD) profoundly impacts an individual's lifelong ability to engage and interact with others. ASD is an illness that can be recognized at early stages in a person's life and is often classified as a "behavioral disease" due to the presence of numerous symptoms that frequently manifest within the first two years of life, as per what most people believe about autism theory, these challenges typically emerge during childhood and endure into adolescence and adulthood [1]. In response to the growing popularity of medical diagnosis, machine learning techniques [2] are used to help doctors make better decisions about a person's health, extensive efforts have been made to leverage various algorithms, including Naive Bayes, Support Vector Machine, Logistic Regression, K-Nearest Neighbors (KNN), Neural Networks, and Convolutional Neural Networks (CNNs) [3], to predict and analyze ASD-related issues across different age groups—children, teenagers, and adults. These endeavors have been detailed in a research survey paper. These predictive models were assessed using the ABIDE dataset, which is openly accessible for research purposes. The study's findings underscore the effectiveness of CNN-based prediction models, which consistently outperformed other machine-learning techniques [4]. Notably, these models achieved impressive accuracy rates of 99.53%, 98.30%, and 96.88% for screening and diagnosing Autistic Spectrum Disorder in datasets representing adults, children, and adolescents, respectively
Autism Spectrum Disorder DetectionUsingMachine Learning
Authors: Bodhke Prof. B. K. , Singh Devesh Sandeep , Hussain Shaikh Umme Hanni Aiyaz , Phadtare Sakshee Vijay , Aslaan Mohammed
Published: October 2024

Convolutional Neural Networks (CNNs) have made significant strides in various domains such as image classifica- tion, speech recognition, automotive software engineering and neuroscience. In this study we leverage CNNs for the automated detection of Autism Spectrum Disorder using brain imaging data,specificallywe utilize resting-state functional Magnetic Resonance Imaging (f-MRI) data from the Autism Brain Imaging Exchange (ABIDE) dataset. To identify ASD patients, our approach relies on analyzing patterns of functional connectivity to classify ASD and control subjects. Experimental results demonstrate that our proposed model achieves an accuracy of 96.40% on the ABIDEI dataset using the CC400 functional parcellation atlas of thebrain. Notably our CNN model exhibits computational efficiency by employing fewer parameters comparedtostate-of-the-art techniques. Our findings suggest that the developed model shows promise for prescreeningasdpatients and warrants further evaluation with additional datasets.
Sustainable Digital Transformation In Africa: Integrating Indigenous Knowledge Systems With Modern Technology
Authors: Nweke Nkem E.
Published: October 2024

Today, the continent of Africa is at an epoch in its digital transformation journey. As the continent embraces modern technologies, it often encounters a disconnect between them and its indigenous cultural practices and environmental contexts. This paper proposes a radical shift from the Western-centric technological paradigms to a model that integrates Indigenous Knowledge Systems (IKS) with digital transformation efforts. This study offers a unique view on sustainable and culturally congruent technological development by examining the limitations of current digital frameworks and presenting successful case studies where IKS have been harmoniously integrated with technology. We explore the potential of IKS to complement and redefine the global technological landscape. Our analysis predicts that by 2040, Africa could emerge as a trailblazer in global technology by embracing and amplifying its indigenous wisdom within its digital advancements. This paper challenges conventional wisdom and advocates for a transformative approach to digital development deeply rooted in Africa's cultural and environmental realities.
Role Of Digital Image Processing In Education And Medical Field
Authors: K P Rejil
Published: October 2024

Digital image processing is a technique that uses computer algorithms to analyze images and transform images into better ones.It is an important branch of Telecommunication engineering that deals with the improvisation of reliability and accuracy of the digital communication by employing multiple techniques. Image processing involves many processes such as taking images, preprocessing, image enhancement, transformation and analysis. Variations in pixel values are one of the major challenges faced by image processing. Digital Signal Processing is at the core of virtually all of today's information technology, and its impact is felt everywhere in telecommunications, medical technology, radar and sonar, and in seismic data analysis.Digital Image Processing plays an important role in medical field and education. Various researches has been done and currently popularly used. In education, pictures can be used to enhance student learning and to develop students’ self-esteem, or their utilization can be of little or no value and, if used carelessly, can, in fact, undermine students' self-confidence. Digital health technologies include both hardware and software solutions and services, including telemedicine, wearable devices, augmented reality, and virtual reality. Generally, digital health interconnects health systems to improve the use of computational technologies, smart devices, computational analysis techniques, and communication media to aid healthcare professionals and their patients manage illnesses and health risks, as well as promote health and wellbeing. Digital imaging gives healthcare providers better and more accurate images, which leads to establishing diagnoses sooner, making treatment of the patient more successful.
Comparative Analysis Of Ai Governance In Africa Relative To Global Standards And Practices
Authors: Njoroge Joy Wanjiku
Published: October 2024

Africa as a continent recognizes the need for Artificial Intelligence (AI) governance frameworks. However, despite initiatives like the African Union's Continental AI Strategy, African nations grappled with challenges in formulating comprehensive AI policies, while established global frameworks provided advanced benchmarks for comparison. To address this disparity, this study conducted a comparative analysis of AI governance in Africa relative to global standards and practices. Employing a comprehensive document analysis methodology, the research examined key policy documents, strategic frameworks, and regulatory guidelines across African, European, American, and Asian contexts. The findings revealed that while the African Union demonstrated commitment to coordinated AI governance, African approaches generally lagged behind global benchmarks in comprehensiveness, formalization, and ethical integration. The study identified a notable fragmentation in AI governance across African nations, contrasting with more unified approaches in other regions. African frameworks emphasized leveraging AI for socio-economic development, diverging from the risk mitigation focus seen in EU regulations. The integration of indigenous African ethical perspectives in AI governance frameworks was limited, presenting both challenges and opportunities. Significant disparities in digital infrastructure and AI capacity between Africa and other regions were found to affect governance implementation. The study concluded that despite these challenges, there was potential for Africa to develop innovative, context-specific AI governance models that could contribute valuable insights to the global discourse on responsible AI development. Recommendations included accelerating the implementation of the Continental AI Strategy, prioritizing investment in digital infrastructure, developing Africa-centric AI ethics frameworks, establishing mechanisms for regular benchmarking against global standards, fostering increased collaboration, and implementing AI literacy programs across the continent.
An Overview Of Deep Deterministic Policy Gradient Algorithm And Applications
Authors: Sumalatha V. , Pabboju Dr. Suresh
Published: October 2024

This research summarizes the major developments of the Deep Deterministic Policy Gradient (DDPG) in reinforcement learning Motivated by the ideas, of Deep Q-networks, DDPG has proven capable of confronting more complex problems involving continuous action spaces. The core of DDPG lies in its actor-critic architecture, which enables the learning of highly competitive policies. By leveraging neural network function approximations, it can efficiently operate in large state and action spaces. DDPG has found practical applications across various real-world domains. However, like many model-free reinforcement learning methods, DDPG still faces the challenge of requiring a large number of training steps.
Improving Cloud Database Performance Using Storage Technologies
Authors: Abuhamra Eng.Abdalgader Egreira Ali , Ali Eng Nassreedin Mustafa Abdullah , Ali Eng Ashraf Mahfoudh Abdannabi
Published: October 2024

Cloud databases have become indispensable for modern applications due to their scalability, flexibility, and cost-effectiveness. However, optimizing performance in cloud environments can be challenging due to factors such as network latency, data distribution, and resource contention. This paper explores various storage technologies and techniques that can significantly enhance cloud database performance. We delve into the characteristics of different storage types, including solid-state drives (SSDs), hard disk drives (HDDs), and object storage, and discuss their suitability for various workloads. Additionally, we examine caching mechanisms, data compression, and deduplication strategies that can optimize data access and reduce storage costs. Furthermore, we explore the impact of database architecture choices, such as distributed databases and inmemory databases, on performance. We also discuss the importance of effective query optimization and indexing techniques. By understanding and implementing these storage technologies and techniques, organizations can achieve substantial improvements in cloud database performance, leading to better user experiences and increased application efficiency
Effect Of Strategic Innovation On Sustainability Of Mission Hospitals In Kiambu County, Kenya
Authors: Malua Mary Ndunge , Wandiga Dr. Eunice , Gachuru George
Published: October 2024

Kenya's healthcare sector plays a crucial role in economic growth and the realization of Vision 2030. Mission hospitals in Kiambu County, however, face sustainability challenges, including inadequate financial resources, staff turnover, weak health systems, and patient non-payment. This study investigated how strategic innovation affects the sustainability of these hospitals, focusing on business models, services, processes, and technological innovations. The research involved 100 managers from seven mission hospitals, using a census approach and a cross-sectional descriptive design. Data were analysed using SPSS, with multiple linear regression to determine relationships between variables. The study found that adopting innovative business models, aligning with market trends, improving service quality, and implementing technological solutions like telemedicine and electronic health systems significantly enhanced operational efficiency, patient satisfaction, and financial stability. The study recommended that mission hospitals regularly review and adapt their value propositions, while the government should support innovation through policies to ensure healthcare sustainability.
Discussões Preliminares: Os Impactos De Uma Gravidez De Estudantes Adolescentes Não Planejada E Seus Avós
Authors: Gomes Glauce Gonçalves Da Silva , Osório Neila Barbosa , Maia Giselle Carmo , Neiva Rosiane Rezende Vidal , Lira Valmir Fernandes De
Published: October 2024

A gravidez na adolescência, geralmente não planejada, pode gerar um impacto significativo nas relações familiares, trazendo consigo uma série de desafios e emoções complexas. O objetivo deste estudo é abordar os impactos de uma gravidez não planejada e relações socioemocionais familiares, segundo o Ministério da Saúde em 2020 o Brasil apresenta mais de 380.000 mil casos. Neste artigo utiliza-se métodos qualitativos, por meio de revisão bibliográfica e análise documental. Uma gravidez não planejada acarreta mudanças nos papéis e responsabilidades dentro da família. Os avós podem assumir um papel mais ativo na criação do bebê, enquanto outros familiares podem precisar contribuir com apoio financeiro ou emocional, outro fator a se considerar. Outro fator é o estresse e as incertezas relacionadas à gravidez podem gerar tensão e conflitos entre os membros da família, prejuízo na vida escolar e abalo nas ligações socioemocionais e por fim redefinição do que se planeja para o futuro e adaptações desta nova realidade. Os resultados da pesquisa servirão de base de dados para outros pesquisadores e promoverá mais informações de acesso aos estudantes no planejamento familiar e projeções sobre seu futuro.
How Can Revitalizing Traditional Handicraft And Cottage Industries In Rural India Contribute To Sustainable Economic Growth And Employment Generation In The 21st Century?
Authors: Alhawat Kevika
Published: October 2024

There exists tremendous potential for the growth of sustainable economic growth and employment generation in the traditional handicraft and cottage industry of rural India. Although these industrial activities are of cultural importance and have collectively contributed to local economies, they are disappearing as a result of rapid industrialization, globalization, and competition from mass production. This research investigates how these sectors can be revitalized to help India achieve sustainable development in the 21st century, by creating employment, reducing poverty, and preserving cultural heritage. This study draws on statistical data, case studies, and successful global examples to identify key barriers including lack of infrastructure, marketing challenges, lack of access to finance, and competition from mass-produced goods. It also provides strategies to cope with these challenges such as skill development, opening up of microcredit access, market diversification, export promotion, and regulatory reforms. The research shows that government policies play a critical role in subsidizing and incentivizing, promoting geographical indications for handicrafts, and simplifying business regulations. It encourages inclusive entrepreneurship in rural areas, empowering artisans and entrepreneurs (women and youth), along with creatively co-creating livelihood and business opportunities. Revitalizing traditional industries can help achieve multiple Sustainable Development Goals (SDGs) such as decent work, economic growth, and responsible consumption and production, according to the findings. This study offers a roadmap for policymakers, entrepreneurs, and other stakeholders to enable the sustainable growth of traditional industries across the villages of rural India while maintaining economic growth and cultural preservation for long-term resilience and prosperity
Navigating The Digital Shift: Challenges And Opportunities For Traditional Retailers In India's Evolving Marketplace
Authors: Bajaj Ananya
Published: October 2024

The retail industry in India is experiencing a monumental shift driven by the rapid adoption of digital technologies. As e-commerce platforms, digital payment systems, and data analytics become increasingly integrated into the retail landscape, traditional brick-and-mortar stores find themselves at a crossroads. This digital transformation is not merely a technological upgrade but a fundamental change that reshapes business models, consumer interactions, and market dynamics. India, with its burgeoning internet penetration and widespread smartphone usage, presents a unique environment where digital innovation meets a diverse consumer base. The proliferation of global and local e-commerce giants such as Amazon, Flipkart, and JioMart has set new standards for customer expectations and operational efficiency, compelling traditional retailers to reevaluate their strategies (Invest India). However, the transition to digital is fraught with challenges. High costs of technology adoption, lack of digital expertise, and resistance to change are significant barriers that traditional retailers must overcome to remain competitive in the digital age