Journal of Scientific Research and Technology

Experimental Investigation On Strength Properties Of Concrete With GGBS Sand, M Sand And Flyash

Dr. Girish Bandi — 2025-03-11

In order to lessen concrete's negative effects on the environment, this article explores the possibility of using fly ash as a cement substitute. It goes on to say that fly ash may make concrete last longer and work better mechanically. The compressive strength of concrete was determined to be unaffected by the substitution of M sand for natural river sand in this experimental investigation. Additionally, it was shown that although using up to 15% fly ash as cement substitute somewhat boosts compressive strength, further increases in fly ash steadily lowers it. The impact of using GBS in place of natural fine aggregate on concrete mix characteristics was the subject of this investigation. Compressive and tensile strengths were also enhanced in GBS-bound concrete, according to the research.

Federated Learning: A Comprehensive Study on Decentralized Machine Learning

Shameem Akhter — 2025-03-26

Federated Learning (FL) represents a paradigm shift in machine learning, enabling collaborative training across decentralized devices while preserving data privacy. This study comprehensively examines FL’s architecture, algorithms, and challenges using the MNIST dataset as a testbed. We compare two prominent algorithms—Federated Averaging (FedAvg) and Federated Proximal (FedProx)—under independent and identically distributed (IID) and non-IID conditions. Results show FedAvg achieving 97.5% accuracy on IID data, while FedProx outperforms it with 94.4% on non-IID data, a 2.1% improvement over FedAvg’s 92.3%. We also assess scalability, communication costs, and privacy vulnerabilities, supported by graphs, tables, and images. This work underscores FL’s potential in privacysensitive applications like healthcare and IoT, identifying key limitations and future research directions.

A Novel Approach For Silkworm Disease Detection And Classification By Using CNN And Image Processing Techniques

Shilpa B Kodli — 2025-03-28

Silkworms, scientifically known as Bombyx mori, are integral to the silk industry, which has substantial economic and cultural significance in various regions worldwide. However, silkworms are susceptible to several diseases that can severely impact their health and productivity, leading to significant economic losses. Common silkworm diseases include Flacherie, Grasserie & Muscardine, each caused by different pathogens such as bacteria, viruses, and fungi. Effective identification & timely behaviour of these ailments are crucial to maintaining the health of silkworm populations and ensuring consistent silk production. For this we propose an automated system for the identification of silkworm diseases and providing treatment recommendations using CNN and image processing. Leveraging deep learning techniques, the system is considered to accurately classify images of silkworms into categories of health status, including specific diseases such as Flacherie, Grasserie, Muscardine, and a healthy state. Experimental results analysis demonstrates 99% of accuracy using proposed model. This approach signifies a step forward in agricultural technology, demonstrating the potential of AI in solving practical problems in sericulture.

The Influence of Digital Marketing on Consumer Buying Behavior in the FMCG Sector

Manisha kumari — 2025-03-28

Digital marketing's meteoric rise has altered consumer habits, especially in fast-moving consumer goods (FMCG) industry.
Advertisements on social media, marketing via influencers, SEO, content marketing, and tailored email campaigns are just
a few examples of the digital marketing tactics investigated in this research. Consumers are more linked, knowledgeable,
and swayed by online material than in past due to widespread availability of cellphones and internet access. According to
the study's findings, digital touchpoints are crucial in creating brand awareness, encouraging customer participation, and
strengthening customer loyalty. It also delves at ways in which things like tailored ads, real-time discounts, and internet
reviews influence decision-making and impulsive purchases. This research sheds light on the efficacy of FMCG digital
marketing by studying engagement indicators and customer replies, and it gives marketers strategic advice on how to
improve customer connection and increase sales. Results highlight how important it is to use digital platforms to keep up
with fast-moving fast-food industry.
The study's overarching goal is to learn how fast-moving consumer goods (FMCG) sector has been affected by digital
transformation on consumers' propensity to make impulsive purchases. Consumer habits have changed drastically in last
few years due to proliferation of e-commerce and other digital technologies. Research utilizes quantitative research strategy
by surveying people who buy fast-moving consumer goods. After data collection is complete, statistical methods like
regression and correlation analysis can be used to the data. Results will shed light on how much of impact digital marketing
has upon FMCG sector impulse buys, how successful digital marketing campaigns have been, and how social media have
contributed to development of environmentally conscious consumers' impulse buys. Research will also compare the
impulsive purchase habits of those who buy FMCG online with those of people who buy them in physical places. The study's
findings will help FMCG firms boost their marketing and impulsive purchasing via digital transformation. In essence, our
research will add to what is already known about how digital transformation affects customer behavior, especially in the
fast-moving consumer goods industry.

Nutrient richness in the sediment of seven major lakes of Pokhara Valley, Kaski, Nepal

Dr. Md. Akbal Husen — 2025-03-28

Sediment is an active zone for accumulation and cycling of nutrients that supplies vital nutrients and minerals to promote lake productivity, ensuring the overall health and balance of lake ecosystem. The aim of this study was to assess the richness of nutrients in the sediment of Phewa, Begnas, Rupa, Khaste, Neureni, Dipang, and Gunde lakes of Pokhara valley. The results showed that pH level of all lakes sediment was found to vary from acidic condition to nearly alkaline. These lakes were found to organically rich sediments, ranging from 2.5-6.4%. The mean nitrogen content in the sediment of Begnas was within normal range 0.1-0.2%, however, rest of lakes were beyond the normal range. Phosphorus concentrations were found surplus, while potassium concentrations were found low in the sediments of these lakes. Anthropogenic and agricultural activities, landslides and siltation, urbanization and development activities in the catchments area of Pokhara valley lakes are major source of external nutrient loading into bottom of lakes. Therefore, it is necessity to initiate action towards conservation of these beautiful natural resources by controlling further external nutrient loading, which will improve the lake ecosystem for both fishery and tourism.