Amicable Knowledge Solution University

The replay attack is a potentially serious threat to the dependability of Iris recognition systems, in which authentic biometric characteristics are reproduced from pre-recorded video recordings. To this end, we present a robust Iris Liveness detection framework based on best-frame selection, deep learning classification, and quality metric evaluation. To evaluate the performance, a real dataset of 115 eye samples of the users were used along with fake data. Video frames were presented to Laplacian sharpness variance algorithm for best frame selection. The best frames were categorized by passing them through a fine-tuned EfficientNetB7 model. Furthermore, biometric quality metrics (pupil-Iris ratio, grayscale utilization etc.) were combined to improve the Liveness. As testing dataset is divided into two subset 40 videos and 60 videos. The experiments demonstrated the accuracy of 92.50 % and 91.67% for 40 videos and 60 videos respectively. In addition, EfficientNetB7 exhibited excellent accuracy and robustness in distinguishing between real and spoofed samples. These findings validate our design's generalization across genuine and attack domains, and demonstrate that it can be used as a scalable solution for real-time Iris spoof detection

The global agricultural supply chain is of paramount importance, serving as the backbone of food production system and a significant contributor to the global economy. However, traditional agricultural supply chains have long faced challenges related to inefficiency, waste, and a lack of transparency. The emergence of the digital economy has ushered in a new era of agricultural innovation, offering solutions to these longstanding issues. This paper explores the transformative impact of digital technologies in enhancing agricultural supply chain efficiency and sustainability. The adoption of digital technologies, including the Internet of Things (IoT), blockchain, Artificial Intelligence (AI), and data analytics, has revolutionized agriculture. The paper highlights the positive environmental and social impacts of digital technology adoption in agriculture, such as reducing chemical use, improving water management, and enhancing food safety. However, it also addresses concerns about labor displacement and data privacy. As the agriculture sector continues to evolve to meet the demands of a growing global population and adapt to a changing climate, the digital economy is expected to play an increasingly significant role. The paper underscores the transformative potential of these technologies, shaping the future of food production and distribution, with a strong focus on efficiency and sustainability.

Insider threats pose a significant challenge to organizations, as malicious activities often mimic legitimate user behavior and bypass traditional security mechanisms. This paper presents a novel hybrid framework for insider threat detection based on anomalous user behavior analysis using multi-source log data. Detection of insider threats is a significant concern in the realm of cybersecurity. Insiders pose the greatest threat due to their unique access. Insider risks can be identified by the atypical activity of a user. The individual is engaged at his place of employment. All user activity on the device is recorded. The recorded data is utilized to analyze user behaviour and identify unusual activities. The user's log, device, and file data were curated, sanitized, and standardized in this study. Features are derived from insider log data. The statistical analysis has been conducted to determine the central tendency and dispersion of the data. It facilitated the classification of normative and abnormal user activity. The interrelationship between the user and the PC is depicted in an undirected bipartite graph. Anomalous user behaviour is analyzed for insider risks based on data. Significant risk mitigation measures may be implemented when the user is identified as a potential insider threat. A medium risk rating is established when the user is identified as anomalous in 50 percent of insider threat activities. Low-level risk measures are implemented against the user upon a determination of guilt in 25 percent of potential risk activities. The measures used against the user include warnings, penalties, account suspension, termination, and reporting to management for additional action on the insider danger about their risk level.

Biodegradable materials for food preservation are becoming more popular as a result of the growing need for environmentally friendly and sustainable packaging solutions. However, because biopolymers have a wide range of characteristics and behaviors, improving the sustainability, safety, and performance of such materials is still a difficult task. One promising way to speed up research and innovation in this field is through artificial intelligence (AI). The use of AI in the creation, formulation, and improvement of biodegradable packaging systems is examined in this review. Predicting material properties, designing polymer blends in reverse, integrating sensors into smart packaging, and automated quality control are some of the main uses. Case studies demonstrating effective applications of machine learning and deep learning methodologies in actual biodegradable packaging situations are also covered in the review. Limitations are also critically analysed, including regulatory barriers, model interpretability, and data scarcity. The study concludes by outlining potential future developments, highlighting how AI-driven technologies, digital twins, and autonomous labs could revolutionise the sustainable packaging sector. This review offers a thorough grasp of how AI can facilitate the shift to intelligent, secure, and environmentally friendly food packaging systems by highlighting recent developments and potential future paths.

In India, one of the main reasons for grain losses during storage is insect infestation. Kodo millet (Paspalum scrobiculatum L.) is grown as a cereal in India only, although the wild grass is a widespread tropical weed. Kodo millet is said to be poisonous after rain. This could be due to a fungal infection. The current study examined how insects were stored in various packaging materials and how infestation affected the physical and chemical properties of dehulled kodo millet. Insects and pests that attack kodo millet include the khapra beetle (Trogoderma granarium), rice weevil (Sitophilus oryzae), grain moth (Sitotroga cerealella), and flour beetle (Tribolium castaneum). These pests and mites cause losses in both the quantity and quality of nutrients during the storage period. The current research focused on grain storage tests, quality trait analysis, and post-harvest practices. After being dehulled and ground on a Perfura dehulling and milling machine, raw kodo grains were kept at room temperature during different storage periods (0, 60, 120, and 180 days) in a range of packaging methods (such as vacuum packing, LDPE, HDPE, and gunny bags). The sample materials were properly cleaned, graded, hulled and milled by Perfura, hulling and stored at ambient room temperature for further use in experiments. The products' physical and chemical properties were assessed, together with the relevant insect observations. The maximum number of insects was found (83) in gunny bag storage milled kodo samples at 180 days, while vacuum-packed samples showed a nil number of insects. According to the data collected, samples packed in gunny bags appeared to contain the majority of insects during the six-month period, whereas samples packed in vacuums showed no change. According to the findings, six months of storage was when biophysical qualities changed, not when samples were vacuum-packed. As a result, during the six-month storage at the studies, it was found that the vacuum-packed kodo millet samples showed significant results for all of their quality characteristics. Dehulled kodo millet can be stored for longer by using vacuum packaging since it preserves its physico-chemical composition. In conclusion, millets have potential for protection against age-onset degenerative insect pests. Moisture is another critical factor in the safe storage of food grains. The vacuum-packed kodo millet samples were found to have significant results for all the quality parameters during the six-month storage study.

ABSTRACT In this paper, comparative performances of the supercapacitor based on different redox additives (vanadyl sulfate [VOSO 4 ] and potassium iodide [KI]) incorporated gel polymer electrolytes (redox additive gel polymer electrolytes [RGPEs]) are reported. RGPEs were prepared by entrapping liquid electrolyte solution NaClO 4 /ethylene carbonate (EC):propylene carbonate (PC) in host polymer PVdF‐HFP along with redox additives via conventional solution casting techniques. It is observed that the ionic conductivity of pristine gel polymer electrolyte (GPE) is dependent on the content of redox additives (VOSO 4 and KI) and temperatures. It is improved by adding redox additive 0.1 wt% VOSO 4 (RGPE‐1) and 0.3 wt% KI (RGPE‐2) with corresponding ionic conductivity values to ∼3.25 × 10 −3 and ∼4.02 × 10 −3 S cm −1 , respectively. Further, two quasi‐solid‐state supercapacitor cells are fabricated using the optimized GPEs RGPE‐1 and RGPE‐2 with honeycomb‐based activated carbon (HCAC) electrodes. The comparative performances of the supercapacitor cells are evaluated and analyzed in terms of different electrochemical characterization techniques such as impedance, electrochemical stability window (ESW), cyclic voltammetry (CV), linear sweep voltammetry (LSV), and galvanostatic charge discharge (GCD) characteristics.

The Right to Education (RTE) Act, 2009, is a landmark legislation in India that guarantees free and compulsory education to children between 6 and 14 years of age. This study analyses the implementation status of the Act, the issues and challenges faced in its execution, and explores potential solutions. Using data from various government reports, including UDISE+, ASER, and independent studies, the paper highlights infrastructure gaps, teacher shortages, financial constraints, socio-economic barriers, and policy implementation issues. It also presents tables to illustrate key statistics. The study concludes with recommendations to overcome these challenges to achieve the goal of universal quality education. This paper aims to critically examine these challenges using recent data and reports, focusing on key issues such as inadequate infrastructure, teacher shortages, insufficient funding, and social inequality. It concludes with policy recommendations to strengthen the implementation of the RTE Act and improve educational outcomes.

Background: The rising rate of caesarean sections (C-sections) has led to an increase in associated surgical complications, particularly urinary bladder injuries in patients with dense pelvic adhesions. Repeat C-sections elevate the risk of such injuries due to adhesions between the bladder and uterus. Cystoinflation, or retrograde bladder filling with saline, has been proposed to improve visualization and reduce injury risk, but its application in C-sections is underexplored. The present study aimed to evaluate the effectiveness of intraoperative cystoinflation in reducing urinary bladder injury during C-sections in women with previous caesarean deliveries and dense pelvic adhesions. Methods: This prospective cohort study was conducted at MGM medical college and MTH hospital, Indore, over 12 months (October 2022-October 2023). A total of 240 women undergoing C-sections with dense adhesions were divided into two groups: group 1 (n=120) with cystoinflation, and group 2 (n=120) without. Primary outcome was bladder injury; secondary outcomes included blood loss; duration of surgery, complications, and hospital stay. Results: Bladder injuries occurred in 3.3% of patients in group 2 and none in group 1 (p<0.001). Urinary tract infections and micturition issues were also significantly lower in the cystoinflation group. Mean hospital stay was shorter in group 1 (4.10±0.42 days) than in group 2 (4.88±1.86 days, p<0.001). Blood loss and operative time showed non-significant trends favouring cystoinflation. Conclusions: Cystoinflation is a safe, simple, and effective technique that significantly reduces bladder injury and postoperative complications during C-sections in high-risk women. Its routine use in such cases is recommended.