Volume 13 | Issue 4 |

 Abstract

Glucose monitoring device is designed to reveal the glucose tiers inside the blood constantly. This machine collects the facts from the person with the help of a sensor and this information is despatched to the Alerting and Advising device. a blood glucose take a look at is commonly accomplished by using piercing the skin (commonly, on the finger) to attract blood and this blood is then tested for the quantity of concentration of glucose through monitoring the glucose degree constantly. This increase in the values of glucose can be observed in boom in current. these current values are converted into voltage form by means of a consistent resistance and the calibrated table is cited in program of Alerting system. those voltage values from sensor are interfaced to the Nedelcu. even though the fee of the usage of blood glucose meters seems high, it's far believed to be a fee advantage relative to the prevented scientific costs of the complications of diabetes. The advantages consist of a discount inside the prevalence price and severity of long-term complications from hyperglycaemia in addition to a reduction inside the brief-time period, probably existence-threatening complications of hypoglycaemia.

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 Keywords

Keywords - Glucose Monitoring, Electrochemical Sensors, Diabetes Management, Continuous Glucose Monitoring (CGM), IoT-based Monitoring, Real-time Data Processing, Machine Learning Predictions, Wireless Data Transmission.

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 Abstract

This paper outlines the design, development, and installation of a solar-powered advertisement board as an environmentally friendly and cost-effective means of replacing electric-powered signage. As the demand for energy-efficient solutions increases and the price of electricity continues to rise, it has become vital to incorporate renewable energy sources in commercial uses. This project revolves around using solar energy to drive advertisement boards and minimize the use of grid electricity and reducing environmental footprint. The system comprises photovoltaic (PV) panels for generating energy, a charge controller for effective power management, a battery storage device for sustained operation, and an LED screen for content display. Energy efficiency, ruggedness, and cost-effectiveness are the key considerations in the design to guarantee sustained usage. By conducting extensive tests and analysis, the performance of the system is quantified under varying environmental conditions. The findings reveal that solar-powered advertisement boards can function efficiently with little maintenance, and they are a viable option for contemporary advertising purposes. This research is an addition to the development of green technology in digital advertising, encouraging the use of renewable energy for commercial and public display applications

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 Keywords

solar energy, advertisement, LED display

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 Abstract

Abstract: The Advanced Encryption Standard (AES) is a widely used symmetric key cryptographic algorithm ensuring secure data transmission. This paper presents an optimized AES implementation using Verilog HDL, enhancing both performance and resource efficiency. The design incorporates fundamental AES operations, including SubBytes, ShiftRows, MixColumns, and AddRoundKey, while employing optimization techniques to reduce latency and hardware utilization. A key enhancement is the reuse of the S-box for both encryption and decryption, with a multiplexer selecting between the two modes. Additionally, the MixColumns and AddRoundKey operations are integrated into a single unit to streamline processing. The proposed design further improves efficiency by reducing S-box instances through optimized key expansion, generating a 128-bit key every five cycles. Security is reinforced by extending the key size to 256 bits, with unique transformations applied across different encryption rounds. Functional simulation and synthesis results validate the correctness and effectiveness of the implementation, demonstrating its suitability for resource-constrained environments such as IoT devices and FPGA-based secure communication systems. This study highlights the advantages of Verilog HDL in cryptographic hardware design, offering scalability and flexibility for future advancements in encryption techniques.

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 Keywords

AES, Cryptography, Verilog HDL, S-box optimization, FGPA

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The increasing influence of social media has turned into a defining feature of present day college experience, particularly in Bangladesh, where platforms like Facebook, Instagram and WhatsApp are deeply integrated into students' daily routines. While social media offers various benefits, such as facilitating connections, access to knowledge, and emotional support, its excessive consumption has been tied to the surge in anxiety level among college students. This article explores the dual impact of social media on anxiety among Bangladeshi college students, examining both the negative and positive aspects. On one hand, social media fosters social comparison, cyberbullying, and digital addiction, all contributing to heightened stress and anxiety. On the other hand, it also provides opportunities for creative expression, mental health support, and community-building. The article further discusses the cultural and academic pressures that intensify the anxiety students experience, emphasizing the need for mindful social media use. The article concludes with recommendations for students to adopt healthier social media habits and for institutions to recognize the importance of mental health awareness.

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 Keywords

Social Media, Anxiety, Facebook, Instagram, and WhatsApp, YouTube and TikTok

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Concerns have been raised about the possibility that the criminalization of medical negligence could serve as both a threat to the medical profession and a deterrent in the healthcare industry. When a healthcare professional fails to provide patients with the expected level of care, this is known as medical negligence. Historically, civil litigation was the primary means of addressing medical negligence; however, the growing trend toward criminalizing such conduct aims to provide a more stringent accountability mechanism. Critics contend that criminalizing healthcare providers is a necessary deterrent because it ensures that they are held accountable for their actions and upholds high standards of care, increasing patient safety and trust in the medical system. Critics, on the other hand, warn that making medical negligence a criminal offense could create a climate of fear and hesitation among medical professionals, which could lead to defensive medicine and lower quality care. Open communication, professional autonomy, and existing problems like physician burnout could all be exacerbated by the threat of criminal prosecution. The ramifications of criminalizing medical negligence are examined in this abstract, with the purpose of determining whether or not it poses a threat to the integrity and well-being of the medical profession or merely serves as an effective deterrent. In order to determine whether or not this strategy is effective and fair, it is essential to strike a balance between accountability and the maintenance of professional trust.

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 Keywords

Negligence, Medical, Harm, Proffessional, Liability, Care, Patient, Criminalisation

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Cross-Lingual Sentiment Analysis (CLSA) has emerged as a vital instrument for comprehending public sentiment around the world as digital communication crosses language and geographic barriers. A thorough analysis of CLSA approaches, such as translation-based models, multilingual NLP strategies, and cross-lingual transfer learning, is presented in this research. We go over important issues including linguistic diversity, the scarcity of annotated datasets, and cultural differences in attitude. Lastly, we examine new prospects such as the creation of multilingual sentiment-aware AI systems, improved machine translation for sentiment preservation, and improvements in huge language models. The importance of cross-lingual sentiment analysis (CLSA) in a multilingual digital world is examined in this research. We go over the CLSA methods, the main language translation issues, cultural variations, and data accessibility. We also look at new approaches and potential paths forward to enhance sentiment analysis in various languages. The increasing requirement to analyses feelings in a multilingual, diversified global context has made cross-lingual sentiment analysis a crucial component of contemporary natural language processing (NLP). This work offers a thorough examination of cross-lingual sentiment analysis, examining the difficulties and methods employed to overcome linguistic and cultural differences in sentiment classification. To improve sentiment analysis across languages, the study focuses on the current approaches, the difficulties of working with low-resource languages, and the use of machine translation, transfer learning, and multilingual models. Furthermore, by using creative methods for data gathering, model adaption, and cross-lingual transfer, we highlight new trends and chances to raise the calibre of cross-lingual sentiment analysis.

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 Keywords

Cross lingual sentiment analysis, NLP

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Jhumpa Lahiri's The Lowland explores the complexities of cultural identity, displacement, and acculturation through the experiences of its characters, particularly Bela, the daughter of Indian immigrants. The novel delves into themes of cultural estrangement and hybridity, examining how Bela navigates her dual heritage as a second-generation immigrant in the United States. Drawing on W.E.B. Du Bois's concept of double consciousness, the analysis highlights Bela's internal conflict as she struggles to reconcile her Indian roots with her American upbringing. Her fragmented identity is further compounded by her mother Gauri's abandonment and her father Subhash's emotional distance, leaving her culturally adrift. The novel also embodies postmodern themes, such as fragmented narratives and the rejection of traditional structures, as seen in Bela's rootless existence and her defiance of familial and societal expectations. Through Bela's journey, Lahiri underscores the fluidity of identity in a globalized world, where cultural belonging is neither fixed nor singular. The study concludes that The Lowland portrays identity as a mosaic of experiences, shaped by dislocation, multicultural influences, and the absence of cohesive cultural anchors.

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 Keywords

Cultural Estrangement, Acculturation, Hybridity, Postmodernism, Displacement, Double Consciousness

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Accurate demand forecasting is critical in the food industry to minimize waste and optimize inventory management, particularly for perishable products. This study uses the "Food Demand Forecasting" dataset by Genpact to compare 16 forecasting models, including traditional machine learning (Random Forest, Gradient Boosting, LightGBM, XGBoost, CatBoost, ElasticNet, SVR), statistical methods (Prophet, TBATS, ARIMA), deep learning models (LSTM, BiLSTM, TCN, ETSformer, GNN), and a hybrid LSTM + XGBoost approach. We applied advanced feature engineering, such as lag features, Exponentially Weighted Moving Average (EWMA), and cyclical encoding of temporal features, to capture seasonality and trends. The primary focus was on achieving high accuracy, with the Hybrid LSTM + XGBoost model achieving the highest accuracy of 93.47%, followed closely by the BiLSTM model at 91.84%. The TCN model achieved a competitive accuracy of 90.66%, demonstrating its effectiveness in capturing temporal patterns. This study improves upon prior work by Panda and Mohanty (2023) by introducing a broader model set, explicit seasonality modeling, and a focus on maximizing prediction accuracy. We provide detailed reasoning for model selection, feature engineering, and evaluation metrics, emphasizing the practical implications of high accuracy in food supply chain management.

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 Keywords

Machine Learning, Artificial Intelligence , Time Series Analysis

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Women-owned businesses are in minority in India. The hurdles faced by women who have embraced entrepreneurship are vast and often different from those experienced by their male counterparts. Karnataka has always been a supporting ecosystem that has facilitated the growth of innovation and entrepreneurship. Universally, entrepreneurship is accepted as the main driver of profitable growth. It has appeared as an employment outlook and a way of adding women at diverse levels within an economy. Women entrepreneurs are gradually becoming one of the elements of growth, predominantly in India. Karnataka is one of the top five states in the whole of India, which is housing the maximum number of women entrepreneurs in the nation with a majority in small and medium-sized businesses. The influence that entrepreneurship has on the well-being of women is not sufficiently discovered.

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 Keywords

entrepreneurship, Women entrepreneurs, Kalaburagi city, motivation, E-commerce

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper shows that Ridesharing is becoming the most chosen transportation option over private transportation in big cities. Ridesharing is also very quick, affordable and safe. Ridesharing also helps lot of students who travel to college from very long distances and sometimes public transportation is also very limited. This helps them save both time and money and also helps them earn some money by listing their rides. So the paper presents the blueprint and application of a peer to peer or a dynamic pooling app which lets the users list themselves as drivers or riders and which allows them to find each other a ride within a specific area in particular bandwidth of time. The applications have some special features like fare recommendation according to distance, time, mileage and ride recommendation based on type of ride and the history of the rider.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Peer-to-Peer, Pooling, Ridesharing, Price Recommendation, Pool.

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Creative Commons Attribution 4.0 and The Open Definition