A Real Time Employee Attendance Monitoring System using ANN

Face recognition refers to the technology that examines and contrasts a person's face characteristics to recognise or verify their identity. Recently, this technology has drawn a lot of attention due to the potential uses it may have in security, marketing, and law enforcement. Face recognition involves studying a picture or video of a person's face to identify features like the space between their eyes, the contour of their nose, and the curve of their mouth. The person's identity is then established or verified by comparing these characteristics to a database of previously saved pictures. A series of techniques called facial recognition algorithms are used to identify and authenticate persons based on the features of their faces. These algorithms compare a person's facial attributes to those in a database of recognised faces by looking at things like the shape of their face, the distance between their eyes, and other distinctive facial features. There are many different types of face recognition algorithms, including geometric-based algorithms, appearance-based algorithms, and hybrid algorithms that combine both approaches. Geometric-based algorithms employ the geometry of face traits to identify and validate people, while appearance-based algorithms use image processing techniques to compare the patterns and textures of facial features. Recent advances in deep learning have significantly improved the accuracy of facial recognition algorithms. Artificial Neural Network (ANN) has shown to be highly effective and have been used in a range of applications, including mobile devices, security, and surveillance. Face recognition algorithms provide advantages, but there are also moral dilemmas with regard to its application, such as potential biases and privacy difficulties. As technology advances, it is imperative to address these problems and ensure that face recognition algorithms are used ethically and responsibly

Study and Comparison Performance of On-demand AODV and DSR, along with the traditional proactive DSDV Routing Protocols for MANET

Abstract- In wireless research area, efficient routing algorithms can provide remarkable benefits in Ad-hoc networks, including higher throughput, lower average end-to-end delay, less number of dropped data packets and generally an ameliorated network performance. Many routing protocols for such networks have been proposed so far. My research work, an attempt has been made to compare the performance of three prominent on-demand reactive routing protocols for mobile ad hoc networks: DSR and AODV, along with the traditional proactive DSDV protocol. A simulation analysis with MAC and physical layer models is used to study interlayer communication and their performance implications. Experimental results obtained, showed that the On-demand protocols, AODV and DSR perform much better than the table-driven DSDV protocol. Although DSR and AODV share similar On-demand behavior, the differences in the protocol mechanics can lead to significant performance differentials. For a variety of scenarios, as characterized by mobility, load and size of the ad-hoc network were simulated. The performance differentials are analyzed using varying network load, mobility pattern, and Network size

Study of inflammatory markers in seizure disorder

Background: Over the past 10 years an increasing body of clinical and experimental evidence has provided strong support to the hypothesis that inflammatory processes within the brain might constitute a common and crucial mechanism in the pathophysiology of seizures and epilepsy. Objective: The study aimed to focus on various markers for inflammation in seizure like WBC, elevated BT, HSCRP along with serum ferritin and ESR.   Methodology: A tertiary care hospital based prospective, observational and comparative study was conducted to study the inflammatory markers in seizures on 100 patients – 50 patients each of first episode of seizure and known case of seizure, who reported to the Department of General medicine (OPD, MMW and FMW), Geriatric medicine (MMW and FMW), Neurology (OPD) and Emergency medicine (ER) at Mahatma Gandhi Mission Medical college, Navi Mumbai.Result: Most of the study population who presented with 1st episode of seizure belonged to the age up to 25 years (26%) and 26 to 35 years (22%) while most of the study population who were known case of seizure disorder belonged to the younger age group of less than and equal to 25 years (36%). ESR was increased in 18% of cases with 1st episode of seizure and 16% of known case of seizure. It was most commonly increased in Drug Default Seizure (19.4%) followed by CNS Infections (16.1 %). Raised ESR levels were most commonly associated with generalized tonic clonic seizures. Serum Ferritin was equally increased in both cases with 1st episode of seizure (4%) and known case of seizure (4%). It was increased most commonly in CNS Infections (17.2 %) followed by Drug Default Seizure (16.1%), Post stroke seizure (15.1%),  Alcohol withdrawal seizure  (15.1%) and Scar Epilepsy (7.52%). Increased levels of ferritin was most commonly observed in Generalized tonic clonic seizure (76.3%) followed by complex partial seizure (10.8%).Conclusion: Inflammatory markers except ESR and FERRITIN, WBC and HSCRP were increased most commonly in GTCS. Markers of inflammation evaluated in the present study cannot not be used as diagnostic markers for different type of seizures since their correlation did not reach the statistically significant value. Study reported significant increase in HSCRP levels in GTCS (64%). It is observed that WBC levels were increased in 34% of cases with 1st episode of seizure and 50% of known case of seizur

Improved Security of E-Healthcare Images Using Hybridized Robust Zero-Watermarking and Hyper-Chaotic System along with RSA

With the rapid advancements of the internet of things (IoT), several applications have evolved with completely dissimilar structures and requirements. However, the fifth generation of mobile cellular networks (5G) is unable to successfully support the dissimilar structures and requirements. The sixth generation of mobile cellular networks (6G) is likely to enable new and unidentified applications with varying requirements. Therefore, 6G not only provides 10 to 100 times the speed of 5G, but 6G can also provide dynamic services for advanced IoT applications. However, providing security to 6G networks is still a significant problem. Therefore, in this paper, a hybrid image encryption technique is proposed to secure multimedia data communication over 6G networks. Initially, multimedia data are encrypted by using the proposed model. Thereafter, the encrypted data are then transferred over the 6G networks. Extensive experiments are conducted by using various attacks and security measures. A comparative analysis reveals that the proposed model achieves remarkably good performance as compared to the existing encryption techniques

Electric vehicles for low-emission urban mobility: current status and policy review for India

Urban areas account for around 70% of global GHG emissions, one-third of which is attributed to the transportation sector. Thus, decarbonising urban mobility is critical in the endeavours to mitigate climate change. Electric vehicles (EV) have potential to control global decarbonisation of transportation. India has air quality index of 141, which is amongst the highest in the world. Considering this troubling figure, government has initiated various schemes and initiative plans. This study reviews the progress and current status of EV adoption in India with regard to availability, manufacturing, charging infrastructure, commercial vehicle electrification and in-depth analysis of FAME-I and FAME-II schemes along with state level initiatives. This research explores the current state of EV adoption through the integrative perspective of financial resources, infrastructure and technology availability highlighting various complications. Based on these challenges, the study proposes points of improvment in each fragment such as policies, infrastructure,electricity demand and sustainable source of energy. A roadmap is recommended of primary factors that should be priortised for effective EV adoption