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All Journal International Journal of Electrical and Computer Engineering Journal of Applied Pharmaceutical Research Indonesian Journal of Electrical Engineering and Computer Science Proceeding of the International Conference on Family Business and Entrepreneurship (ICFBF) Lentera Jurnal Pengabdian Maysarakat
Kumar, Suresh
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Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Medicine & Pharmacology Social Sciences

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Prevalence of vitamin B12 deficiency and its associated neuropathy in patients taking long term metformin therapy in Type 2 diabetes mellitus Kumar, Suresh; Varadan, Sivaprakash; P, Viswanathan; Sekar, Vaishnavi; Singh, Tanisha; Singh, RB Sudagar
Journal of Applied Pharmaceutical Research Vol. 11 No. 5 (2023)
Publisher : Creative Pharma Assent

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18231/j.joapr.2023.11.5.39.43

Abstract

Background: Diabetic people on metformin are more likely to develop vitamin B12 deficiency. There has been little research into the duration of therapy and dose of metformin that causes B12 deficiency and peripheral neuropathy. This study is being done to determine the same. Objective: To determine the association between vitamin B12 deficiency and its neuropathy to long-term metformin therapy in diabetic patients. Study design: This observational cross-sectional study was conducted at SRIHER Chennai. Patients on long-term metformin were taken and separated into two groups: B12 Vitamin deficiency and normal Vitamin B12 levels. Results: B12 Vitamin deficiency was found in 15.72% of 159 patients on metformin. Only 2 of the 59 people on vitamin supplements in our study showed Vitamin B-12 deficiency, whereas 23 out of 100 people in the non-supplemented group had Vitamin B-12 deficiency. The difference (OR - 0.11; P 0.005) was statistically important. There was a statistically important difference observed between the prevalence of deficiency of vitamin B-12, Duration (>5 years), and dosage (>1 g/day) of Metformin use (p-value - <0.0001). Among the study group with neuropathy, the duration of metformin in the normal b12 group is 5.6 ±4.69 yrs. vs. 11±4.019 yrs. in b12 deficiency group (mean difference = 5.4; p <0.0004). Conclusion: The study found that metformin uses for a long time (> 5 years) and dose > 1g/day are linked to B12 Vitamin deficiency and neuropathy in diabetic patients.
Neutrosophic enhanced convolutional neural network for occupancy detection: structured model development and evaluation Mittal, Ranjeeta; Kumar, Suresh; Chugh, Urvashi
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i6.pp6619-6627

Abstract

In this study, we introduce an advanced convolutional neural network (CNN) model tailored for house occupancy detection, designed to accommodate the inherent uncertainties and contradictory information often encountered in sensor data. By integrating neutrosophic layers into the CNN architecture, we enable the model to effectively handle indeterminacy, vagueness, and inconsistency present in real-world sensor readings. Our approach employs neutrosophic convolutional, max-pooling, and logic layers, providing a comprehensive framework for feature extraction and decision-making. Through a structured methodology encompassing data preprocessing, model initialization, training, evaluation, and optimization, we demonstrate the efficacy of the proposed model in accurately detecting occupancy status within residential environments. This enhanced CNN model offers improved accuracy, robustness, and interpretability, thereby facilitating its integration into smart home systems and building automation applications, contributing to enhanced efficiency, comfort, and energy savings.
Hesitant fuzzy clustering with convolutional spiking neural network for movie recommendations Shrivastava, Vineet; Kumar, Suresh
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 3: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i3.pp1849-1856

Abstract

The movie recommender system is one of the most influential and practical tools for aiding individuals in quickly selecting films to watch. Despite numerous academic efforts to employ recommender systems for various purposes, such as movie-watching and book-buying, many studies have overlooked user-specific movie recommendations. This paper introduces a novel approach for movie recommendations that combines the hesitant fuzzy clustering with a convolutional spiking neural network movie recommender system. The initial step involves acquiring input data from benchmark datasets like MovieLens 100K and MovieLens 1M. Further, content-based features are extracted from the dataset using ternary pattern and discrete wavelet transforms. After that hesitant fuzzy linguistic Bi-objective clustering (HFLBC) is applied for cluster selection based on the extracted features. Subsequently, a movie recommender scheme utilizing a convolutional spiking neural network is introduced to predict user film preferences. The efficiency of the proposed model is compared to existing methods such as multi-modal trust-dependent recommender scheme and graph-dependent hybrid recommendation scheme. The results show a significant improvement, with the proposed model achieving 13.79% and 16.47% higher accuracy than the existing methods. The findings highlight the potential of proposed system in enhancing the accuracy and personalization of movie recommendations.
Enhancing emotion detection with synergistic combination of word embeddings and convolutional neural networks Jadon, Anil Kumar; Kumar, Suresh
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i3.pp1933-1941

Abstract

Recognizing emotions in textual data is crucial in a wide range of natural language processing (NLP) applications, from consumer sentiment research to mental health evaluation. The word embedding techniques play a pivotal role in text processing. In this paper, the performance of several well-known word embedding methods is evaluated in the context of emotion recognition. The classification of emotions is further enhanced using a convolutional neural network (CNN) model because of its propensity to capture local patterns and its recent triumphs in text-related tasks. The integration of CNN with word embedding techniques introduced an additional layer to the landscape of emotion detection from text. The synergy between word embedding techniques and CNN harnesses the strengths of both approaches. CNNs extract local patterns and features from sequential data, making them well-suited for capturing relevant information within the embeddings. The results obtained with various embeddings highlight the significance of choosing synergistic combinations for optimum performance. The combination of CNNs and word embeddings proved a versatile and effective approach.
FACTORS INFLUENCING RETENTION OF REMOTE EMPLOYEES AT PLACEMENT INTERNATIONAL Purba, Wynona Sheehan; Kumar, Suresh
Proceeding of the International Conference on Family Business and Entrepreneurship 2024: PROCEEDING OF 8TH INTERNATIONAL CONFERENCE ON FAMILY BUSINESS AND ENTREPRENEURSHIP
Publisher : President University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33021/icfbe.v0i0.5695

Abstract

This study aims to explore and analyse the factors influencing the retention of remote employees, focusing on the role of a supportive remote work environment, organizational commitment, person-organization fit, and work fulfilment. The research seeks to understand how these variables interact and contribute to long-term employee retention within a remote work setting. By examining these relationships, the study provides valuable insights into the dynamics of remote work environments and their influence on organizational stability and employee satisfaction. A quantitative research design was employed, with data collected through an online survey distributed via Google Forms to remote employees at Placement International. Data were analysed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with Smart PLS 3. The findings reveal that a supportive remote work environment positively influences organizational commitment, person-organization fit, and work fulfilment. Additionally, organizational commitment and work fulfilment are shown to positively impact remote employee retention, while person-organization fit does not directly influence retention. This research offers actionable insights for companies employing remote workforces, highlighting the importance of fostering a supportive work environment to enhance employee commitment and fulfilment, which are critical for improving retention rates. These findings can guide HR policies and remote work strategies to ensure long-term workforce stability. The study contributes to understanding how remote work environments can be optimized to improve the quality of life for employees by focusing on factors that enhance their work experience and overall well-being, which is especially relevant in the growing shift toward flexible work arrangements. This research is pioneering in its investigation of remote employee retention, incorporating the variables of supportive work environment, organizational commitment, person-organization fit, and work fulfilment. Furthermore, it is the first to study these relationships within the context of Placement International, offering a novel contribution to both academic literature and business practice.
ANALYZING THE EFFECTIVENESS OF MARKETING STRATEGIES IN INCREASING RICE SALES: A CASE STUDY OF CV SURYA AGRO TANI USING 7P MARKETING MIX AND SWOT ANALYSIS Damayanti, Asty; Kumar, Suresh
Proceeding of the International Conference on Family Business and Entrepreneurship 2024: PROCEEDING OF 8TH INTERNATIONAL CONFERENCE ON FAMILY BUSINESS AND ENTREPRENEURSHIP
Publisher : President University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33021/icfbe.v0i0.5680

Abstract

This study aims to analyze the marketing strategies employed to increase rice product sales at CV SuryaAgro Tani, focusing on the company's use of the 7Ps marketing mix framework (Product, Price, Place,Promotion, People, Process, Physical Environment). Additionally, the research employs a SWOT analysis(Strengths, Weaknesses, Opportunities, Threats) to evaluate the effectiveness of these strategies and topropose actionable recommendations for enhancing sales performance. This study was initiated in responseto a significant decline in rice sales over three consecutive months, driven by both internal and externalfactors. Through this analysis, the research contributes to both academic literature and practical solutionsfor overcoming such challenges in the agricultural industry. The study provides valuable insights foragribusinesses like CV Surya Agro Tani, demonstrating how an effective use of the marketing mix,combined with a well-structured SWOT analysis, can be leveraged to improve sales performance. Thefindings suggest that companies in similar contexts can adopt an aggressive strategy to capitalize on theirstrengths and external opportunities, offering a roadmap for reversing declining sales trends. The researchalso highlights the broader social impact of effective marketing strategies in the agricultural sector,particularly in helping small and medium-sized enterprises (SMEs) like CV Surya Agro Tani thrive despitemarket fluctuations. By improving sales, such businesses can contribute to local economic stability,employment, and food security. This study is unique in applying the 7Ps marketing mix and SWOT analysisspecifically to the rice market at CV Surya Agro Tani. It offers a novel contribution to the academicliterature on marketing strategies in the agricultural industry, as prior research has predominantly focusedon other business sectors. Furthermore, it provides practical insights that can be applied to similaragribusinesses facing comparable challenges.Keywords: Marketing Strategy, 7Ps, SWOT Analysis, Sales Performance, Agribusiness, CV Surya AgroTani, Rice Products
Pengembangan Model Edutourism Di Pertanian Terpadu Bukit Tursina, Bogor Goenadhi, Felix; Komalasari, Farida; Kumar, Suresh; Witono, Aloysius Bambang Memet
Lentera Jurnal Pengabdian Masyarakat Vol. 2 No. 4 (2024): LENTERA JURNAL PENGABDIAN MASYARAKAT
Publisher : Lentera Ilmu Madani

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The Community Service Program (PkM) at Bukit Tursina Integrated Agriculture aims to develop the area into an edutourism destination based on sustainable integrated agriculture. With an environmentally friendly approach, Bukit Tursina is a food production center and an educational model for sustainable agricultural and livestock practices. This initiative is designed to enhance the community’s skills in managing educational tourism, encourage active involvement from local communities, and create interactive learning experiences for visitors. The methods used include initial observations, needs analysis, area development planning, the creation of educational modules, tour guide training, and pilot testing of the edutourism program. Additionally, the program involves structuring the tourism area, installing educational elements, and implementing social media promotional strategies. The expected outcomes of this program include improving the community’s capacity to manage educational tourism professionally, increasing the number of visitors, and raising awareness of sustainable agricultural practices.
Co-Authors Chugh, Urvashi Damayanti, Asty Farida Komalasari Goenadhi, Felix Jadon, Anil Kumar Mittal, Ranjeeta P, Viswanathan Purba, Wynona Sheehan Sekar, Vaishnavi Shrivastava, Vineet Singh, RB Sudagar Singh, Tanisha Varadan, Sivaprakash Witono, Aloysius Bambang Memet