Volume 12 | Issue 2

 Abstract

The aim of this paper is to explore the notion of vague sets and to define a new class of vague generalized ? closed sets in topological spaces and investigate their properties

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Vague set, Vague topology, Vague generalized ? closed set, Vague point

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In this dissertation, we have studied the diverse examples illustrating the application of Brooks' Theorem in graph theory, elucidating its role in determining chromatic numbers for various graph structures and also the Johan colouring determining its rainbow neighbourhood

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Graph, colouring, edge, vertices, chromatic number, Brook's theorem, Johan colouring, Rainbow Neighbourhood.

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Resume screening is an important task in the recruitment process, and machine learning techniques have shown great promise in automating this task. However, most of the existing research in this area has focused on supervised learning algorithms, which rely on labeled data for training. While supervised learning can be effective, it has several limitations in the context of resume screening. First, obtaining labeled data can be time consuming and expensive, especially for smaller companies with limited resources. Second, labeled data may not always be available or may not be representative of the entire pool of resumes. Finally, supervised learning algorithms may be biased towards the labels in the training data, which can lead to inaccurate or unfair results. To address these limitations, this paper proposes the use of unsupervised learning algorithms for resume screening. Unsupervised learning algorithms do not require labeled data for training, and can identify patterns and structures in the data without external guidance. In the context of resume screening, unsupervised learning algorithms can be used to cluster resumes based on their similarities, and identify important keywords and phrases that can be used to rank and filter.

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Resume screening, Machine learning techniques, Supervised learning, Unsupervised learning, Clustering algorithms, Data preprocessing, Feature extraction, K-means clustering, Hierarchical clustering, Evaluation metrics, Silhouette score, Inertia metric, Natural Language Processing (NLP).

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Employing PySpark dataframes for analysis of the US domestic flight dataset. The goal of this is to forecast which flight and/or airline will most likely experience delays or cancellations.UsingPyspark,abigdatatechnologytool,wecanthereforeworkwithRDDs/Dataframes/DatasetsinPython.Inthisanalysiswillhelpusfindout what are the top airlines with the maximum delays/cancellations in the US.Also, this project will investigate whether there are any factors that cause flightdelays/cancellations. Further, this project predicts if a flight will get cancelled ornot. Machine learning approaches were used to model a binary classification problem using categorical variables, logistic regression, decision tree classifier, random forest, and gradient boosted tree in order to construct the predictory system.

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HIGH CLOUD AIRLINES

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This project introduces a real-time embedded Vehicle-to-Vehicle (V2V) Communication System using Arduino units, Zigbee modules, GSM connectivity, and various sensors. It aims to bolster road safety, aid breakdown assistance, and facilitate critical information exchange during emergencies. By employing Zigbee technology, seamless communication between vehicles is established. In instances such as breakdowns, accidents, or roadblocks, drivers can activate switches to instantly alert nearby vehicles, enhancing overall safety. Ultrasonic sensors monitor fuel levels and distances, allowing for convenient location of fuel stations. In emergencies, automatic GSM alerts containing the location and type of emergency are dispatched, ensuring swift response from authorities or nearby drivers. Vibration sensors detect road obstacles, while IR sensors help detect pedestrians and vehicles in blind spots. Additionally, MQ3 Alcohol gas sensors detect alcohol levels in drivers' breath, triggering automatic alerts. LCDs provide real-time updates on fuel levels, emergency alerts, and obstacle warnings, making transportation safer and more efficient.

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Arduino, LCD, Zigbee, GSM, Ultrasonic sensor, IR Sensor, Red LED, Buzzer, MQ3 Alcohol Gas sensor

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The most traditional technique for isolating phytoconstituents from plant extract is column chromatography. Column chromatography is a very inefficient method that can cause any process to stall out rapidly. This led to the invention of flash chromatography, a revolutionary preparative liquid chromatography method in which the mobile phase flows downward under positive air pressure. Flash chromatography is based on an air pressure system that combines short and medium column chromatography, and is designed to make the purification of synthetic products quick and simple. This method of preparative liquid chromatography is straightforward, quick, and affordable. In previous years, the use of such systems for the separation of complicated natural product combinations, like extracts, was disregarded; however, these days, flash chromatography is becoming more and more popular for the separation and isolation of phytopharmaceuticals from plant extract. For such ingredients, it has proven particularly challenging to purify a number of phytopharmaceuticals using traditional methods. The preferred technique is flash chromatography. This article focuses on the new Flash Chromatography method for isolating phytopharmaceuticals. .

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Flash chromatography, Phyto-pharmaceuticals, Separation and isolation, Natural products.

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The advancement of women in STEM education is not just an academic goal but also a transforming force in Tamil Nadu's dynamic environment. Women's contributions to STEM (Science, Technology, Engineering, and Mathematics) fields break through gender stereotypes and promote variety, creativity, and advancement in society. Tamil Nadu can unleash a vast unrealized potential by fostering the intellectual power of women in STEM fields. This will create a harmonious synergy that will drive the state towards a future where innovation transcends gender boundaries. Thus, women's contributions to STEM education serve as a beacon pointing the way to a society that is more progressive, educated, and egalitarian.

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STEM (Science, Technology, Engineering, and Mathematics)

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This paper proposed IoT based solar powered water quality monitoring and purification of water. Nowadays we are facing water problems due to due to the pollution of water in rivers and lakes. So, to overcome this problem and to see if the water is good for using or not, we have thought about a certain system which can measure the quality of water and check whether it's useful or not. To examine the safe supply of water, the quality of water needs to be monitored in real time. In this paper we develop and design a system for real time monitoring for water monitoring using IOT (Internet of things). The proposed system consists of some sensors that are used to measure the parameters of the water. The parameters used in this system are conductivity, turbidity and pH value using solar panel and purification of water. The measured values can be processed by using ESP8266. Finally, the device information is shipped or delivered to web or cloud server using ESP8266 and Blynk Cloud.

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ESP8266, pH, Turbidity, Conductivity, Solar Panel, Water Purifier, IoT

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With technological advancements, real-time automation systems now require flawless data flow over wireless sensor networks. In the future, it appears that wireless sensor networks, or WSN, will cover the entire earth's surface. WSN currently plays a dominating role in the IoT for primary data gathering. But the focus now has shifted from typical scalar wireless sensors to Wireless Multimedia Sensor Networks (WMSNs), which consist of various multimedia devices that can extract scalar sensor data along with video, audio, and image data. WMSNs are designed to provide multimedia content due to the accessibility of low-cost CMOS cameras and microphones, as well as the substantial advancements in distributed signal processing and multimedia source coding techniques. This paper has been proposed to complete a thorough survey of WMSNs from different aspects. The detailed survey present in this work will be useful for researchers working in this area for future development in the given area.

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Keywords: Wireless Multimedia Sensor Networks, Protocols, Medium Access Control, QoS.

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This research paper explores the dynamic impact of artificial intelligence (AI) on the contemporary job market. Spanning from the conceptualization of AI to its diverse applications in our economy, the study meticulously analyzes the strengths and drawbacks of AI, offering insights into their specific applications. The research critically examines whether AI truly brings positive changes to the economy by analysing its impact in various industries. By delving into various industries, the paper assesses the extent to which AI can be seamlessly added into specific roles or if there still remains an essential human requirement in those jobs. This investigation aims to provide nuanced perspectives on the evolving relationship between AI and the job market, contributing to a deeper understanding of its implications for our economy.

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artficial intelligence

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Sustainable leadership can be achieved only when teams perform with high energy levels consistently. Resilience framework covers four categories - Physical, Mental, Social and emotional resilience. A resilient leader is one who exhibits resilience for survival, stability and growth for both self and team. Job life turning to be one of the stressor in life in present world, nurturing resilient leadership can bring back the positive work culture improving productivity and efficiency. This study aims at understanding the resilient leadership style of Generation Y/ Millennials working in private companies in Chennai.

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Reslience Leadership, Millenial leaders, Positive Leadership, Resilience framework

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Pharmaceutical industry has a progressively multifaceted and energetic environment with some differences in the current years and this probably tends to continue for maximizing use of resources with highest levels of investments. Integrated management systems enhance organizations' performance through the management philosophy that allows the processes to be managed successfully and attain the desired results. The current study aimed to investigate the impact of workplace environment on development of integrated safety management system in pharmaceutical industries, review the key elements of integrated safety management system and describe benefits of implementation. The method used in this study was descriptive method making a simple random sampling conducted through gap analysis feasible to describe the actual requirements based on ISO 9001:2015, ISO 14001:2015, ISO 45001:2018 and cGMP for seven pharmaceutical companies from industrial zone in Alexandria, Egypt. The results revealed that the integrated management system has a constructive impact on production, employees, market, management, environment and occupational health & safety procedures. Gap analysis showed fluctuation over implementation of elements of the integrated management system. Also, the study illustrated that the developing management philosophy be situated internalized by executive managers and other employees has positive impact on sustainable development in addition to provide many benefits to organization. Thus, it can be concluded that integrated management systems (IMS) of quality, environment, and safety can pose significant competitive advantages for the companies. The main benefits of these types of systems are improvement for performance, also reduction of costs and time for implementation. The resistance to change is the greatest difficulty for these firms. These difficulties are resistance from employees and lack of top management commitment, and understanding of international standards.

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Safety, Workplace Environment, Pharmaceutical Industries, Integrated Safety Management, Integrated Management System

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In the medical realm, there are different types of modalities and in that computed tomography (CT) and magnetic resonance imaging (MRI), are combined to provide a fused image. Image fusion (IF) is a technique for merging relevant information from different images like MRI and CT of the same part of the body into a single fused image. In this work, brain MRI and CT images are fused together and will be classified as normal or abnormal. If the network is detected as abnormal, the part of the tumor region is detected. This process is done by using Convolutional Neural Network (CNN), You Only Look Once (YOLO) architecture and Image Fusion (IF) techniques. The experimental results are evaluated and give metric values. IF is a technique which is used for combining data from more than one image to provide much better images than single images. A Convolutional Neural Network (CNN) is a Deep Learning algorithm which can take in fused image and give importance to various aspects in the image. The processing required in a Convolution Neural Network is much lower as compared to other Deep Learning algorithms. The You Only Look Once (YOLO) algorithm is commonly used for real-time object detection. This gives better accuracy for speed-moving objects.

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Magnetic Resonance Imaging (MRI), Computed Tomography (CT), Image Fusion (IF), Convolutional Neural Network (CNN), You only look once (YOLO)

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The project proposes the development of a smart infant incubator monitoring and control system that uses IoT technology to customize the care and monitoring of premature and critically ill newborns. As the system is interfaced with advanced sensors, actuators, and connective solutions to create a smart and responsive incubator environment. The system adopts with some key components such as temperature and humidity sensor for precise check of environmental conditions, gas sensor, heartbeat sensor, sound sensor and accelerometer to monitor the infant's conditions inside the incubator and actuators such as Peltier module and humidifier are integrated to adjust the environmental conditions according to the threshold range on the processed sensor data. An LCD display provides the local feedback, while buzzer alerts the caretakers at time of critical periods. These sensors collectively provide data for the parameters as a Wi-Fi enabled microcontroller such as Arduino Wi-Fi R3 is utilized to process and transmit data which also communicates with cloud based IoT platforms. IoT application was developed using Thing speak to build an ideal communication through a Wi-Fi module, Healthcare providers can regularly monitor the infant's condition through a designed web or mobile interface. The developed IoT interface provides real-time data acquisition, and the system incorporates automated alert mechanism by integrating a GSM module. In the matter of change in normalities beyond the threshold ranges, an automated alert message will be forwarded to the attentive doctor or caretaker through GSM.

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Arduino Wi-Fi R3, GSM, IoT (Thing speak), Peltier Module, sensor data acquisition, sensor data communication.

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The conflict values are the source of many conflicts and problems in contemporary world. In contrast to the traditional conflict of values, the contemporary conflict is distinguished by extensiveness, complicatedness, profoundness and continuousness. Traditionally, war has been understood as evolving state pitted against each other in armed combat over conflicting interests with the state resorting to violence. The changing nature of armed conflict explains how since the end of Cold War, the nature of warfare and its conduct had been challenged by various notable developments. This paper of mine will focus on the changing contour of armed conflict and its results in contemporary politics

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Conflict, traditional war, combat, armed conflict

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" ??????? ?? ??????? ??? ????? ????? ?? ??? ??????? ??????? ?? ?????? ?? ????????? ?????? ?????? ???"- ??????? ????? ?????? ????????????? ?? ????? ????? ?? -"?? ???? ?????????? ???? ????? ???????? ''??? ''?? ???? ?????????? ??????? ????? ???????? " ??? ???????? ?????? ?????? ?? ??????? ????? ??? ??? ?????? ???? ?? ?????? ?? ???? ?? ???? ???? ?? ???? ????? ????, ??? ?? ??? ????? ???????? ?? ???? 70 ??????? ??????? ??????? ????????? ??? ????? ???? ??? , ??? ??? ?? ????? ??? ??????? ??????? ?? ???????? ?????? ?? ???????? ???? ???? ?????? ?? ?? ???? ???? ????????, ???????, ???????, ???????, ??? ???????? ??? ??? ??????? ?? ??? ???? ?? ???? ?????? ??? ?? ????? ??? ?????? ???,???? ????? ?? ??????? ??????? ?????, ???????? ??? ???? ??????? ????????? ??? ???-??? ??? ???? ??? ?? ?????? ????? ??? ???? ?????? ?????? ?? ???? ???, ?? ???? ?????? ???? ??? ???? ????? ?? ??? ???? ???? ??,????? ??????? ??????? ?? ??????? ?? ???? ???????? ??? ? ???? ????? ?????? ??????? ????? ?? ????? ??????? ?? ??? ?? ????????? ???? ??, ?? ??????????? ??? ??????? ?? ????? ????? ?? ??? ???????? ???? ????? ???, ???? ????? ??????? ??? ?? ??????? ?? ?????????? ?? ?????? ?? ??????? ?? ????????? ??? ?????????? ?? ??? ????????? ??? ??? ??? ??: ???????? ?????? ?? ????? ???????? ??????? ???????? ? ???????? ?????? ?? ???? ?? ????? ????? ??? ???????? ????? ?????? ??????? ??????? ?? ????????? ??? ?????????? ?? ??? ????? ?? ??? ??????? ??????? ??? ??????????? ?? ??????????? ?? ?????? ???? ?? ??? ??? ?? ?? ??????? ?? ??????? ??????? ?? ???? ??? ???? ???? ???????? ?? ?????? ???? ?? ?

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????? ??????????,??????? ???????,?????? ?????? ,?????? ??????????,????? ????????,????? ?????????

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This paper delves into the narrative of violence against women amidst the tumultuous backdrop of the Partition of India in Jyotirmoyee Debi's novel, "The River Churning." The Partition of India in 1947 was a cataclysmic event that led to widespread displacement, communal violence, and untold suffering, particularly impacting women who bore the brunt of gender-based violence and upheaval. Through a close examination of Debi's work, this paper seeks to amplify the voices of women affected by Partition, shedding light on their experiences of violence, trauma, and resilience. Drawing upon feminist literary theory and postcolonial discourse, the paper analyzes the portrayal of women characters in "The River Churning" and their encounters with various forms of violence - physical, emotional, and psychological. It explores how Debi's narrative reflects the patriarchal structures and communal tensions that exacerbated violence against women during Partition, while also highlighting moments of agency, resistance, and solidarity among female characters. Furthermore, the paper examines the role of memory and storytelling in shaping the collective narrative of Partition, particularly from a gendered perspective. It explores how women's voices and experiences have been marginalized or silenced in dominant historical discourses, and how Debi's novel serves as a counter-narrative that foregrounds their perspectives and struggles. Through a nuanced analysis of "The River Churning," this paper aims to contribute to broader discussions on gender, violence, and memory in the context of Partition literature. It argues that by centering women's voices and experiences, Debi's novel offers a poignant and powerful reflection on the enduring legacy of violence and trauma, as well as the resilience and agency of women in the face of adversity. Ultimately, this paper seeks to illuminate the complexities of women's experiences during Partition and to underscore the importance of amplifying marginalized voices in narratives of historical trauma. By engaging with Debi's novel, it endeavors to deepen our understanding of the multifaceted impact of violence on women's lives and the imperative of bearing witness to their stories in the ongoing quest for justice, healing, and reconciliation.

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Partition of India, Violence against women, Trauma, Resilience, memory, story telling

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Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that affects social, communication, and behavioral skills. Early diagnosis of ASD can lead to better outcomes for individuals with this disorder. In recent years, machine learning techniques have been used to aid in the diagnosis of ASD using facial images. This paper presents an approach for ASD prediction using the ResNet50 architecture, a deep convolutional neural network. The proposed method extracts features from facial images and trains a classifier to predict the likelihood of ASD. The model was trained and evaluated on a publicly available dataset, achieving an accuracy of 90 percentages. The proposed approach has the potential to provide a cost-effective and non-invasive method for early diagnosis of ASD.

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Deep learning, ResNet50, Machine learning, Feature extraction, Facial Recognition, Computer vision, vgg16.

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There is no denial to the fact that crime rate is increasing in the developing contemporary India, inspite of various legislations to prevent crime in the country while maintaining law and order in the society. One of the highest levels of punishment awarded is "Capital Punishment" or "Death Penalty". As we know that different people live with different opinion and different way of thinking, capital punishment is one of the debatable topics among the people of nation. Such debates give rise to questions such as whether killing another human being in the name of justice is right or wrong and whether such killing helps in curbing crime rate in the society. This paper makes an attempt to answer these questions in light of the capital punishment. The paper makes a discussion about what capital punishment stands for, the mode in which capital punishment is awarded and executed and how it is linked to doctrine of "rarest of rare" in India. The paper also makes a detail purview on different case laws where criminal can get punishment of death penalty. The paper also discusses the various approaches that can be taken, such as the reformative and preventive approaches as opposite to capital punishment. Thereby, this article gives detailed view of capital punishment in India.

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: Capital Punishment, Death penalty, Legislation, Crimes

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In the contemporary educational landscape, the attainment of student attentiveness and engagement has emerged as a critical facet of effective teaching and learning. Yet, accurately gauging student attentiveness, especially within sizable classrooms, presents an intricate challenge for educators. To address this, cutting-edge technology solutions have surfaced, harnessing the prowess of Artificial Intelligence (AI) and computer vision techniques to introduce a Student Attentiveness System. This system capitalizes on AI algorithms, including Haar Cascade, DLIB, and Local Binary Patterns Histograms (LBPH), to meticulously monitor and scrutinize students' facial expressions and behavioral cues during class. Haar Cascade expertly detects faces, DLIB extracts intricate facial features, while LBPH orchestrates facial recognition, collectively enabling precise assessment of student attentiveness. The implementation of the Student Attentiveness System offers a plethora of advantages. Educators can promptly identify and support students who may be encountering difficulties, fashion personalized teaching methods, and optimize classroom dynamics to ameliorate overall learning outcomes. Moreover, the system affords valuable feedback mechanisms for teachers, empowering them to enhance their instructional approaches and tailor their teaching styles to align with the unique needs of individual students. Thus, this innovative system not only modernizes attendance tracking but also elevates the educational experience, substantially improving both student engagement and the effectiveness of teaching practices.

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 Keywords

Face Recognition, Open CV, DLIB, Haar Cascade, LBPH, Machine Learning

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