bluuebunny/crossref_metadata_2025 huggingface dataset:
Metacognitive Awareness of Reading Strategies among Chinese EFL Tertiary Students for Quality Teaching and Learning
Authors: Li Qian , Gurnam Kaur Sidhu  , Arieff Shamida
Published: May 2023

Effective reading skills are often viewed as the foundation to learning a foreign language as it is a ‘comprehensible input’ when learning a language. Therefore, this study aimed to examine EFL tertiary students’ metacognitive awareness of reading strategies. The study was conducted in one provincial university in China, involving 424 EFL students. The study utilised an explanatory sequential research design. Data were collected via a reading test, a questionnaire and interviews. The findings revealed that students possessed medium levels of metacognitive awareness with global and problem-solving strategies significantly affecting EFL students’ reading comprehension performance.
Factors Predicting Interior Preferences for Vihara or Ubosot
Authors: Moorapun Chumporn , Lekhakul Kotchapong , Dechnitirat Chanumpa
Published: May 2023

Designers need to comprehend people's preferences to produce enjoyable environments. This research investigated how coherence, complexity, legibility, and mystery can anticipate the interior preferences of Vihara or Ubosot in various architectural styles. Forty-five students were taken to 19 temples and asked to complete an online survey. The findings revealed that coherence, legibility, and mystery were predictors of interior preferences, except for complexity. Moreover, coherence was the only predictor for the Sukhothai style, while coherence and mystery were predictors for the Ayutthaya style. On the other hand, all four variables predicted interior preferences for the Lanna style.
Thermal and Environmental Design for Human Comfort in Japanese-Designed Architecture in Thailand
Authors: Nanta Piyarat , Kuanprasert Ravij
Published: May 2023

These multiple case studies investigate thermal and environmental architectural details unique to the Japanese-designed educational facilities in Thailand, namely [1] King Mongkut Institute of Technology Ladkrabang 's Auditorium and Memorial Hall, [2] Lecture Halls, [3] Kasetsart University's Central Laboratory, [4] Thammasat University's Institute of Japanese Studies, and [5] Ministry of Natural Resources and Environment’s Research Center. Data sources include archival records, site surveys, and interviews. The findings reveal various design strategies, such as double-layer walls, complex roofing design, specific orientation, and water features that contemporary sustainable building designs may adopt to increase thermal comfort while reducing energy consumption.
Communication: topology of metadiscourse of social interactions
Authors: Kolinko Maryna , Petryshyn Halyna , Chumak Halyna
Published: May 2023

The article focuses on the definition and analysis of communication as a metadiscourse of social interactions in terms of the topological methodology. Socio-cultural transformations that shape the model of the global world and change the Ukrainian landscape, the intensification of cross-cultural contacts, international relations, relations of social communities on different levels actualize the problem of communicative interaction. Globalization processes, which involve representatives of different cultures in the general development of civilization, the challenges of military conflicts, in particular the war of Ukrainian people against the Russian invasion, require an adequately constructed discourse. In such contexts, the concept of communication as a metadiscourse, that is, a discourse about the discourses of social interactions, acquires a new meaning.
Spatial Turn and Situational Approach: Ethical Dimension
Authors: Golubovych Inna , Pavlenko Kateryna
Published: May 2023

The article is devoted to the explanation of the basic principles of the situational approach in the light of the modern "spatial turn", presented to the scientific community by the ideas of such world-famous modern theorists as D. Harvey and A. Lefebvre. Our main focus is the ethical dimension of the outlined problem field. The starting point is the ancient presumption of the etymological and semantic unity of ethos and space. The authors of the article conceptualize this synthetic unity, offer a set of certain principles and theoretical assumptions. The main result of the study is the interpretation of the situation as a space of a responsible individual act, a field of equal interaction of the individual with the external environment, circumstances, conditions, as well as a state of existence of a “specific material a priori/ a priori scene”. The authors formulate the following principles of situational vision: a) the primacy of the individual, the existential situation and the secondary nature of any external circumstances and conditions; b) the principle of “primary historicity”; c) the principle of “limit situation” as a transcendental-immanent unity; d) the principle of the situation as a mode of “a priori scene”. The most important constitutive procedures of the situation as a topos of the act of individuation are described: interiorization and immanentization, namely, situational and personal interiorization of the meaning of the main civilizational cultural-historical conflicts and immanentization of general ethical norms in one's own individual semantic field. The thesis is substantiated that the spatial-situational discourse has significant heuristic resources for the analysis of current socio-cultural and political processes in the modern world.
The discursive nature of modern science: philosophical understanding
Authors: Kubalskyi Oleh
Published: May 2023

The article attempts to find out the patterns of adequate discursive interpreta-tion of science in conditions of social turbulence. For this, based on the socio-communicative methodology, the author makes sense of the relationship between science and philosophy, and also characterizes the state of the modern scientific debate about science in domestic and foreign scientific discourse in such fields as understanding the tasks of post-nonclassical science (O. Polishchuk, I. Do-bronravova, G. Haken), possibilities of reality transformation by means of techno-science (H. Bashlyar, B. Latour, V. Maryniuk, V. Melnyk), risks of post-academic science development (J. Ziman, O. Kuz, V. Cheshko), modes/types of science (M. Gibbons, H. Novotny, S. Limoges, L. Ryzhko). The main result of the study is the author's definition of the strengths and weaknesses of science in a socially turbu-lent space. Among its strengths, the author attributes such properties as increased scientific attention to applied problems, a higher degree of scientific self-organization, multitasking at different levels and within different types of relation-ships, communicativeness. Among the weaknesses are the risks of science losing fundamentality, disciplinary boundaries, which is accompanied by a loss of clarity in the methodology and criteria of scientific success, as well as the risk of replac-ing scientific truth with non-academic success criteria, such as the economic suc-cess of science, political correctness, etc. It is concluded that in the situation of global transformations and uncertainty which humanity is currently experiencing, new characteristics of science are developing, which help to understand the risks and dangers of moving away from traditional academicism.
Tecnología NIRS para el análisis rápido y confiable de la composición química de forrajes tropicales
Authors: Ariza Nieto Claudia , Mayorga Mogollón Olga Lucía , Parra Forero Diana Marcela , Camargo Hernández Deisy Bibiana , Buitrago Albarado Claudia Patricia , Moreno Rodríguez Jenny Milena
Published: May 2023

La espectroscopía de reflectancia en el infrarrojo cercano (NIRS, por sus siglas en inglés), es una técnica que se fundamenta en la aplicación de métodos matemáticos sobre datos químicos y, en combinación con las ondas electromagnéticas de la región del NIR (780 a 2.500 nm), se relaciona la composición química con los cambios de energía, para generar ecuaciones por cada compuesto químico, por lo tanto, la lectura espectral de una muestra es suficiente para obtener información de múltiples valores químicos relacionados con la calidad de los recursos forrajeros del trópico.
INFORMATION MODELING TECHNOLOGIES AS A FACTOR IN INCREASING THE COMPETITIVE POTENTIAL OF DESIGN ORGANIZATIONS
Authors: Yakushev N. M. , Lekomtseva N. V.
Published: May 2023

This article describes the main points of the process of managing the competitiveness of organizations. Potential competitive advantages that a design organization may have and which should be paid attention to in the first place are considered. Information modeling technologies are becoming more and more in demand in recent years, so the use of such technologies in design gives the design organization a chance to increase its competitive potential by improving the quality of design work, reducing design time, obtaining more serious and responsible orders and other factors. BIM technologies are the technologies of the future. BIM design implies that all data on the designed object must be presented in the form of a single information model. For each element of the model, the necessary important characteristics are recorded (identification, physical, technical, cost). It is the automation of processes and the integration of all data in one model that allows to bring design work to a new level. The main advantages of using BIM technologies are considered, as well as the circumstances that may interfere with the implementation of BIM. Recommendations are given on what to look for when switching to innovative technologies so that the transition process itself is less costly and less problematic.
ESSENCE OF THE INVESTMENT POTENTIAL OF CONSTRUCTION ORGANIZATIONS AND ITS EVALUATION METHODS
Authors: Kislyakova Yu. G. , Lekomtseva N. V.
Published: May 2023

The paper considers and clarifies the definition of the concept of ’investment potential’, its essence and features. The existing methods of assessing the investment potential of organizations are analyzed, and the need to assess investment potential is described. The aim of this work is to analyze theoretical approaches to determining the investment potential of construction enterprises and to identify the optimal method for assessing it. The investment potential of an enterprise is a combination of external and internal investment resources that have been accumulated at the enterprise for the implementation of the company’s strategic goals with the available opportunities. The structure of investment potential should include groups of private potentials, such as financial, industrial, labor and market. Each particular potential, in turn, is determined by the corresponding factors (indicators). Analysis of the construction companies investment potential should contribute to accurate evaluation of their own resources and capabilities, the definition of an investment policy priorities of the organization. The increase and effective use of the organization’s potential determines its viability and sustainable development. The investment potential is constantly changing over time due to the fact that there are changes in the external and internal environment of the enterprise. The paper lists the main negative factors that negatively affect the activities of construction organizations.
STRUCTURAL-DYNAMIC ANALYSIS OF HEALTH LEVEL OF WORKING AGE POPULATION: REGIONAL ASPECT
Authors: Ketova K. V. , Vavilova D. D. , Kuzmin M. S. , Korepanova A. V.
Published: May 2023

Human capital in the modern world is the primary factor in ensuring the progressive development of society. The level of population health is an important part of human capital. It determines the quality of labor resources and labor productivity in the region. The purpose of this work is to study the structure and dynamics of the level of health of the working-age population and identify trends in its development. A numerical analysis of the structure and dynamics of the health status of the population is carried out on the example of the Udmurt Republic, using modern data reflected in the system of state statistical accounting for the period 2000-2019. Calculations have shown that the level of health of the working-age group of the region’s population has been declining in recent decades. The share of healthy people in the region in the 15-72 age group of the population decreased from 59.8% in 2000 to 42.1% in 2019. At the same time, the proportion of people with chronic diseases increased: 33.2% in 2000 and 48.5% in 2019. In general, the share of people with disabilities in the total population of the age group 15-72 years old increased from 7.0% to 9.4%. The trends in the structure and dynamics of the health of the working-age population of the region identified and analyzed in the work indicate a decrease in the rate of positive influence of human capital on the economic dynamics and the labor market. The analysis indicated the emergence of the need to create additional conditions to reduce the level of general morbidity and disability in the region.
COMPARATIVE ANALYSIS OF DESIGNING MULTIFUNCTIONAL RESIDENTIAL COMPLEXES MIDDLE FLOOR XX AND XXI CENTURIES
Authors: Soboleva M. S. , Korepanova N. S.
Published: May 2023

The paper describes and analyzes the methods and periods of evolution of the design of multifunctional residential complexes, the interaction of residential, commercial and retail functions in domestic and foreign practice. The relevance of the design and construction of buildings with an average number of storeys is confirmed by the demand for improving the quality of life, increasing the level of psychological comfort and environmental friendliness of buildings, taking into account the cost reduction. On the basis of studying the experience of foreign architects, the ways of solving the problem of designing domestic residential complexes and creating a comfortable environment were identified. The main tasks are solved by creating high comfort of the residential and public environment, competent functional zoning of the territory, uniqueness of space-planning and compositional solutions. The most pressing issue is the development of new standards that ensure the safety, comfort and convenience of people living, and the need for intensification in the construction of housing related to architectural, spatial and compositional solutions in the design of multifunctional residential complexes. On the basis of identifying and combining factors, relationships that affect the development of residential complexes, the basic principles of architectural and spatial organization are formulated. The principles of territory organization revealed as a result of the study can be applied in the design and construction of multifunctional residential complexes by new and young specialists.
Automatic Control of LED Lamp Using PIR Motion Sensor
Authors: Sharanbasappa A , S Bharath Kumar , A Naveen , M Praveen Kumar , B Tarun Raj
Published: May 2023

Abstract: This paper represents automatic lighting and security system design using PIR motion sensor Using this PIR sensor we can certainly minimize the consumption of electrical power. Power crisis is one of the most common problems in India. With the help of the sensors we can eliminate this shortage by minimizing the wastage of electrical power or saving our generated power PIR is the type of sensor that gives us signal when anything crosses its rays. It is an electronic sensor that measures infrared (IR) light radiating from objects in its field of view. It is a low-cost device used to detect a change in motion in its surroundings within different range of radius. A PIR-based motion detector is used to sense movement of people, animals, or other objects A PIR-based motion detector is used to sense movement of people, animals, or other objects Automatic Room Light Controller Using PIR Sensor can be used to turn ON and OFF the illumination system of home / office routinely by sensing the existence of human Such Automatic Room Lights systems can be implemented in your Classrooms, faculty cabins, garages, staircases, bathrooms, etc. where we do not need constant light but only when individuals are existing Also, with the assistance of this system, we can save the energy bill as power will be consumed only when hum is present i.e. when required lights will be spontaneously turned ON or OFF.
A Study-on-Study Habits and Attitudes Among Secondary School Students
Authors: C R Sharath Kumar
Published: May 2023

Abstract: Smart way of learning has to be the key to academic success for learners. This “Smart way” can be developed into strategies by studying the study habits and attitude of the student towards learning. Studying the study habits and attitude of students is of optimum importance to teachers, learners and caregivers, so as to promote and aid in the learning process of the students. Rote learning has been encouraged over time but there is a need of change in strategy of studying to meet the needs of the current competitive world. The main aim of this study is to determine the extent of study habitual patterns and a learner’s attitude studying in general as a single variable holistically. There was no significant difference found in the study habits of SBSE and ICSE secondary school students as well as any difference in the two genders study patterns. On an average it was found that the majority of the students in both the education systems had a poor study habit. This paper attempts at giving plausible solutions to improve the students study habits and attitudes. Here the researcher has used survey method and Test of Study Habits and Attitudes tool prepared and standardized by Dr. C.P. Mathur to collect data.
Automatic Classification of Music Genres Using the Deep Learning Approach
Authors: Janthakal Sheetal
Published: May 2023

Abstract: Music is divided into arbitrary groups known as genres. Music genre classification is a challenging task due to the subjective and ambiguous nature of musical genres. The existing systems for music genre classification suffer from low accuracy and poor generalization of new data. Therefore, there is a need to develop a robust and accurate machine-learning model that can overcome these challenges and classify music audio files into different genres with high accuracy. The main aim of the Music genre classification project is to develop a user-friendly application that accepts audio files as input and classifies the audio file into a particular category of sound to which they belong (to predict its genre) using machine learning models. This application automates the process to reduce manual error and time. It will take an audio file as input and categorizes each file into a particular category like audio belonging to Disco, hip-hop, etc. The final classification is obtained from the collection of individual data. This machine learning model makes use of Support Vector Machine(SVM) and Logistic Regression models. Both models will be integrated into a website to make the project easily accessible.
Depression Monitoring System via Social Media Data using Machine Learning frameworkk
Authors: Kashid Onkar , Bhumbare Rashmi , Dange Eshwar , Waghmare Ajit , Nikam Raj
Published: May 2023

Abstract: Stress and Depression is one of the most widely recognized and handicapping mental issue that relevantly affects society. Automatic health monitoring systems could be crucial and important to improve depression and stress detection system using social networking. Sentiment Analysis alludes to the utilization of natural language processing and content mining approaches planning to recognize feeling or opinion. Full of feeling Computing is the examination and advancement of frameworks and gadgets that can perceive, decipher, process, and mimic human effects. Sentiment Analysis and deep learning techniques could give powerful algorithms and frameworks to a target appraisal and observing of mental issue and, specifically of depression and stress. In this paper, the application of sentiment analysis and deep learning methodologies to depression and stress detection and monitoring are discussed. In addition, a fundamental plan of an incorporated multimodal framework for stress and depression checking, that incorporates estimation investigation and full of feeling processing strategies, is proposed. In particular, the paper traces the fundamental issues and moves comparative with the structure of such a framework.
Anticipation of Car Price Using Machine Learning Approach
Authors: K M Lakshmi Sharma , Kumar Praveen , Budur Manoj , G Sai Prasad Reddy , M Narayana
Published: May 2023

Abstract: This study aims to develop a predictive model for car prices using various parameters, such as car name, manufacturing year, km driven, fuel used, dealer type, transmission type, number of seats, torque in RPM, mileage of the car, engine power in cc, max power range, and ownership type. The model is developed using the forest regressor algorithm, which is a machine learning technique used for regression analysis. The data is collected from various sources, and after preprocessing, the model is trained to estimate the car price based on the input parameters. The results show that the developed model has a good accuracy in predicting the car price. This study contributes to the field of automotive industry and can provide valuable insights for car buyers and sellers.
An Efficient Approach for Data Encryption and Decryption
Authors: Kaushik Bharti
Published: May 2023

Abstract: Data security is an essential component of an organization in order to keep the information safe from various competitors. Cryptography is a technique used to avoid unauthorized access of data. It has two main components- Encryption algorithm and Key. Sometime, multiple keys can also be used for encryption. A number of cryptographic algorithms are available in market such as DES, AES, TDES and RSA. The strength of these encryption algorithms depends upon their key strength. The long key length takes more computing time to crack the code and it becomes difficult for the hacker to detect the cryptographic model. In this paper we suggest an innovation in the age-old conventional cryptographic technique of HILLCIPHER using the concept of self repetitive matrix. A numerical method has been stated, mathematically proved and later implemented in generating a random matrix of given periodicity. The method of self-repetitive matrix has then been used to simulate a communication channel with proper decompression techniques to facilitate bit saving.
A Blockchain-based approach for Drug Traceability in Healthcare Supply Chain
Authors: Bhagwat Kiran , Sudrik Pratibha , Pawar Shraddha , Waghchaure Vishwanath , Suryavanshi Prof. A. P.
Published: May 2023

Abstract: The blockchain typically described as a decentralized system in which transactional or ancient statistics are recorded, stored, and maintained throughout a peer-to-peer community of personal computers referred to as nodes. Counterfeit drugs are one consequence of such limitations within existing supply chains, which not only has serious adverse impact on human health but also causes severe economic loss to the healthcare industry. Blockchain technology has gained tremendous attention, with an escalating hobby in a plethora of several applications like safe and relaxed healthcare records management. Similarly, blockchain is reforming the traditional healthcare practices to an extra reliable means, in phrases of powerful prognosis and treatment through safe and cosy facts sharing using SHA Hash Generation Algorithm. Within the future, blockchain will be an era that can probably assist in personalized, authentic, and at ease healthcare by means of merging the entire actual-time scientific information of a patient’s fitness and offering it in an up to date cosy healthcare setup. In this paper, we evaluation each the present and modern day trends inside the subject of healthcare with the aid of imposing blockchain as a model. We also talk the packages of blockchain, at the side of the demanding situations confronted and destiny views. The proposed system executed blockchain implementation in distributed computing surroundings and it gives the automated restoration of invalid chain by using Consensus and Mining Algorithm. In this system, we present a Custom blockchain-based approach leveraging smart contracts and decentralized off-chain storage for efficient product traceability in the healthcare supply chain. The smart contract guarantees data provenance, eliminates the need for intermediaries and provides a secure, immutable history of transactions to all stakeholders. We present the system architecture and detailed algorithms that govern the working principles of our proposed solution. We perform testing and validation, and present cost and security analysis of the system to evaluate its effectiveness to enhance traceability within pharmaceutical supply chains.
Implementation of Online Mess Recommender System using Sentiment Analysis
Authors: Falke Mr. Nikhil , Dabhade Mr. Abhishek Kiranrao , Bansod Miss. Ashvini Rangraoji , Bajaj Mr. Nirmal Sureshkumar , Tayade Mr. Chaitanya Harish , Shelokar Prof. Y. R.
Published: May 2023

Abstract: In this research paper we proposed mess recommender system using sentiment analysis. We proposed Wordnet based sentiment analysis. Users will submit ratings and reviews for mess as per their experience; our model will analyse the submitted reviews and find out the polarity of the review. Based on these reviews and ratings, user profile like city, area, likings etc. our proposed system will recommend appropriate messes to the user.
Brain Stroke Predictive Analysis using Various Machine Learning Algorithms
Authors: Niveditha Steffi , suresh  , Rao Yenaganti Purna Chandra , Ganesh Yarangalli , Manjunath Jangama
Published: May 2023

Abstract: Our project offers a reliable stroke detection technique. Data analysis and the creation of prediction applications are both done using the Pythonlanguage. The main goal of this project is to enable anyuser to perform a stroke self-test. The data on thepatients' characteristics is used to create the GUI interface and data analysis components. We collect the stroke training and test datasets and do exploratory data analysis. Through feature selection, the most effective and precise variables needed to predict strokein an individual are obtained, and according to thevariables obtained, the features that affect the prognosis of the disease are obtained. On this processed data, predictive modeling is done using different categorization models, including LogisticRegression, Support Vector Machine, Decision Treemodel and Random Forest algoritham. The bestaccurate model is used by the GUI interface to handle user inputs and forecast the incidence of stroke.
Predict, Identify and Alert on Suspicious Activity by Multiple Zone
Authors: Yadav Pratik , Ghodke Mayuri , Dhokane Vivek , Chavan Sanjana
Published: May 2023

Abstract: An active topic of image processing and computer vision research is the detection of suspicious human behaviour in surveillance footage. In order to stop terrorism, theft,accidents, illegal parking, vandalism, fighting, chain snatching, crime, and other suspicious activities, human activity can be observed through visual surveillance in sensitive and public places like bus stations, railway stations, airports, banks, shopping malls, schools, and colleges. It is highly challenging to continually monitor public spaces, thus an intelligent video surveillance system that can track people's movements in real-time, classify them as routine or odd, and send out an alert is needed. The field of visual surveillance to identify aberrant actions has seen a significant amount of publications in the last ten years. Furthermore There are a few surveys that canbe found in the literature for the recognition of various abnormal activities, but none of them have reviewed various abnormal activities. This study presents the state-of-the-art in the field of recognising suspicious behaviour from surveillance recordings during the past tenyears. We give a quick overview of the concernsand difficulties associated in recognising suspicious human activity. This article examines six aberrant behaviours, including the identification of abandoned objects, theft, falls, traffic accidents, and unlawful parking, as wellas the detection of violence and fire. Generally speaking, we have covered all the processes that have been [1] Foreground object extraction, object identification based on tracking or non-tracking approaches, feature extraction, classification, activity analysis, and recognition are some of the techniques that have been used to identify human activity from surveillance movies in the literature. This paper's goal is to give field researchers a literature assessment of six different suspicious activity identification systems together with its broad framework.[1]
Fake Drug Detection Using Blockchain Technology
Authors: Said Prof. A. G. , Gawali Triveni , Chavan Mayuri , Bendgude Sheetal , Hande Rutuja
Published: May 2023

Abstract: For a few decades, it is a getting challenging to keeptrack and monitor of non-counterfeit drugs in health care. Due to Lack a trust system and safe and secure monitoring, unauthorizerscan make fake drugs easily. Because fake drugs has a harmful effect on the human health and has deadly results. Fake medicinesare analyzed as a great challenge for the medical industry worldwide. As mentioned by statistics, due to these counterfeit drugs yearly business loss of around $200 billion is described by US pharmaceutical organizations. These fake medicines may not assist the patients to get well from health disorder but can have many other harmful ramifications. According to the World HealthOrganization (WHO) survey, in undeveloped nations each 10th medicine consumed by the patients is fake and has bad quality. To find the fake drugs, we are proposing a drug traceability system by using blockchain technology. Our system helps in detecting substandard and fake drugs from manufacturer to end user. Blockchain helps to make the system more reliable and transparent. Blockchain based system helps in detecting the fake drugs and ensures the transparency and security of e-health data. This paper aims to ensure transaction security, medicine quality, and data security by using blockchain technology.
Diagnosis of Diabetic Retinopathy using Fundus Images and Image Processing Methods
Authors: Deshpande Abhishek
Published: May 2023

Abstract: Diabetes is a metabolic condition that causes organ failure, including retinal damage. Diabetic Retinopathy causes blindness by leaking blood vessel fluid into the retina also called as exudates. Thus, there has been a surge of interest in automated methods for detecting diabetic retinopathy using image processing techniques. Using real-time image dataset and image processing techniques, the proposed system is able to detect major retinal abnormalities such as enlarged retinal veins, blood spots, and white-yellow patches that indicate fluid leakage. The system analyses colour retinal images to determine the extent of damage and locate clusters of injured pixels within the region. The technique has a greater detection accuracy of 88%, and it has been demonstrated to be successful in detecting exudates and abnormalities from fundus images. In addition, the system is extremely helpful. To make suggestions for possible treatments based on an examination of the fundus images
Plant Leaf Disease Detection using Deep Learning
Authors: Shinde S. V. , Dhyade Hrithik D. , Meshram Yash , Mergel Swapnil , Neve Nirmal
Published: May 2023

Abstract: Pests damage plants and crops, which has an impact on the nation's agricultural output. Typically, farmers or professionals use their own eyes to monitor the plants to look for disease and identify it. However, this approach could be timeconsuming, expensive, and unreliable. Results from automatic detection employing image processing methods are quick and precise. In this study, deep convolutional networks are used to develop a novel method of classifying leaf images in order to recognise plant diseases. The technique of precise plant protection has the potential to grow and improve, and computer vision advancements have the potential to boost the market for applications in precision agriculture. Innovative training methods and the methodology employed make it simple and quick to implement the system in real-world settings. The deep convolutional neural network used in this method paper has been trained and fine-tuned to fit accurately to a database of plant leaves that was gathered independently for various plant illnesses. The innovation and advancement of the proposed model lay in its simplicity; by utilising deep CNN, the model can discriminate between ill and healthy leaves as well as between them and the environment. Healthy leaves and backdrop images are also in line with other classes.
Python Automated Tool to Detect Over Speeding of A Vehicle Through ANPR Technology
Authors: J Vedavyas
Published: May 2023

Abstract: Today, every country has serious issues with traffic management and car ownership identification. Car owners who violate traffic laws and drive too fast may be difficult to spot. It could be challenging for traffic officers to collect the license plate because of the speed of the moving car, making it impossible to identify and penalize such offenders. The creation of an automated system for number plate identification is crucial as a remedy for this problem. A web application that can identify license plates and display them will be created. To achieve the desired outcomes, EasyOCR and OpenCV will be combined with machine learning system models (such K-means or CNN). We'll make use of the YOLO dataset.
Weapon Detection System
Authors: Mudaraddi Kiran , T Keerthi , Yadav Likitha , Varsha M. , M Nivedita
Published: May 2023

Abstract: Security is always a main concern in every sphere, due to a rise in crime rate in a crowded event or suspicious lonely areas. Anomalydetection and observance have major applications of computer vision to gear various problems. Due to demand in the protection of safety, security of private properties placement of surveillance systems can recognize and interpret the scene and anomaly events play a vital role in intelligence observance. Detection of weapon and militant using convolution neural network (CNN). Proposed implementation uses two types of datasets. One dataset contains pre-labelled images. And the other one labelled manually contains a set of images. Results are tabulated, both algorithms achieve good efficiency, but their operation in real situations can be based on the trade-off between speed and efficiency. Crime is defined as an act dangerous not only to the person involved, but also to the community as a whole. It is to predict the crime using image dataset and finally calculate accurate performance of the detector. The propose algorithms that are able to alert the human operator when a weapon and militant is visible in the image. It is mainly focusedon limiting the number of false alarms in order to allow for real life application of the system. For future work, it is planned to use in live applicationand to improve the detection and reduce the crime.
Power Generation by Speed Breaker
Authors: Gaikwad Prof. Swapnil D. , Kamble Akshat Kishor , Dhanawade Prathamesh U. , Yevle Shivraj S. , Mane Sahil S.
Published: May 2023

Abstract: In the present scenario, power becomes a major need for human life. Due to the day-to-day increase in population and lessening of conventional sources, it becomes necessary that we must depend on non-conventional sources for power generation. While moving, the vehicles possess some kinetic energy and it is being wasted. This kinetic energy can be utilized to produce power by using a special arrangement called “POWER HUMP”. The Kinetic energy of moving vehicles can be converted into mechanical energy of the shaft through the rack and pinion mechanism. This shaft is connected to the electric dynamo and it produces electrical energy proportional to traffic density. All these mechanisms can be housed under the dome-like speed breaker, which is called a hump. The generated power can be used for general purposes like streetlights, and traffic signals. The electrical output can be improved by arranging these power humps in series this generated power can be amplified and stored by using different electric devices. The maintenance cost of the hump is almost nullified. By adopting this arrangement, we can satisfy future demands to some extent
Prediction of Autism Spectrum Disorder based on Machine Learning Approach
Authors: Chandrappa Harshita , BR Swaathi , Pahuja Prof. Swimpy
Published: May 2023

Abstract: In recent years, awareness of autism spectrum disorder (ASD) has grown faster than before. As everyone is aware, ASD is a disorder of neurodevelopment that also encompasses problems with conduct and social interaction. The degree of symptom severity and each individual's experience with ASD vary. Any age can be used to diagnose autism. According to research, violence, self-harm, elopement. tantrums, preoccupation, and lack of obedience are behaviour patterns most frequently observed in people with autism. Therefore, it is imperative to spot any sign of severe ASD as soon as possible. ML methods like Random Forest, Naive Bayes, Decision Tree, K- Nearest Neighbour, Logistic Regression, and Support Vector Machine (SVM) are employed in this work. With the use of algorithms that have been used to decide which gives accurate results in terms of speed and accuracy, performance metrics assist in examining the degree of correctness of each piece of data across all users. ML methods like Random Forest, Naive Bayes, Decision Tree, K-Nearest Neighbour, Logistic Regression, and Support Vector Machine (SVM) are employed in this work. With the use of algorithms that have been used to decide which gives accurate results in terms of speed and accuracy, performance metrics assist in examining the degree of correctness of each piece of data across all users.
Mobile Botnet Detection: A Machine Learning Approach using SVM
Authors: Bramhane Milind , Bhusare Madhuri , Nimase Dhananjay , S.D. Prof. Bhondave
Published: May 2023

Abstract: Android is now the most widespread mobile operating system worldwide. Over the years the volume of malware targeting Android has continued to grow. This is because it is easier and more profitable for malware authors to target an operating sys-tem that is open-source, more prevalent, and does not restrict the installation of appsfrom any possible source. Hence, in this paper we present a deep learning approach that leverages Support Vector Machine (SVM) forAndroid botnet detection. The SVM model employs 342 static features to classify new or previously unseen apps as either ‘botnet’ or ‘normal
Topology Optimization of Sprocket and 3D Printing
Authors: Amonkar Krishna
Published: May 2023

Abstract: A chain drive is designed as a final reduction for an FSAE (Formula Student) Vehicle along with topology optimised geometry. Different geometrical shapes were iterated using the results from the topology optimisation and the design was finalised based on the magnitude of max stress concentration. The topology optimization was done under several constraints.
Automatic Hand Sanitizer Dispenser Using Arduino
Authors: Mishra Shreyansh
Published: May 2023

Abstract: The COVID-19 pandemic has had an effect on human life in many different fields. There have been several attempts to stop the virus from spreading, including working from home, avoiding social gatherings, and practicing hand hygiene. Since the COVID-19 virus can spread through touch and contact, there are WHO recommendations to regularly wash or sanitize hands to lower the risk of infection. Sanitizer storage and dispensing from the bottle would both require manual intervention. And the majority of the hand sanitizers that are currently on the market don't work automatically. In order to lower the risk from contact, this article intends to create an automatic hand sanitizer that is used in hospitals, workplaces, offices, schools, and much more.Here, the system uses an ultrasonic sensor to detect proximity and sends a signal to the microcontroller (Arduino UNO). The controller activates the solenoid valve and pump after processing the sensor data. As a result, a mist nozzle is used to disperse the sanitizing liquid.
e-Sammarjana: An Intelligent Robo-Cleaner Using IOT and AI Technology
Authors: Aurad Shivani S , Purohit Shreyas , Indoria Tanush , Soma Dr. Shridevi
Published: May 2023

Abstract: Today’s households are getting smarter and more digital. Home automation adds flexibility and allows more time for people. Domestic robots are entering the homes and people’s daily lives, but it is yet a relatively new and immature market. However, a growth is predicted, and the adoption of domestic robots is evolving. Our work is an Automatic Robo-Cleaner that will be helpful to make household work convenient and much easier. This operates in autonomous along with additional features such as dirt container with auto-dirt disposal mechanism. They are seen as more convenient to use because they can clean on their own. To develop a system of such type requires the basic knowledge of mechanical design, power requirements and adding intelligence to the machine and connecting it to the internet. The research done is a Robo-cleaner that works in fourfold namely the mechanical part (curved rectangular shape, driving wheels, DC motor), electrical (rechargeable DC battery, Driver IC), Internet of things part (controlling whole device using android app) and intelligence part (Voice-controlled and sensors are trained to avoid obstacles). Here, artificial intelligence is adopted to enable intelligent scheduling and motion control for optimized operation of the Robo-Cleaner. The main novelty of this paper is its ability to identify any flames present near the robot and to clean staircases and also detect humans and other entities with the purpose of avoiding causing any harm to them. Through the android app, which will have certain modes, the user will be able to take control of the robot manually whenever he wants, and he will be able to make the robot move autonomously again whenever he wants.
Grief, Self-Compassion and Coping styles among Younger and Older Adults
Authors: Chopra Roshni , Waraich Dr. Sushmita Biswal
Published: May 2023

Abstract: Experiencing loss of a loved one is the most painful experience that can have a long-lasting impact on individuals. Coping with such a loss could seem extremely difficult at first however with the right coping strategies. The purpose of this study was to gain an understanding of how grief can have an impact on two categories of group namely; Younger and Older Adults and to further assess their self-compassion and coping strategies. With the help of tools such as “adult attitude to grief scale”, “the brief cope scale” and “the self-compassion scale” the data was generated from 100 Adults (50 younger and 50 older adults). In accordance with the research findings, it was found that the grief level was higher in younger adults who sort to use problem focused coping styles and had high level of self-compassion as compared to the older adults who tend to use more of avoidant focused coping styles and their grief levels were less than younger adults this could be due to more life experience and experience of loss more than younger adults. There existed a significant relationship between the three variables.
Chronic Radiation cystitis: a review of medical and surgical management
Authors: Kumar Manjeet , Sharma Sanjeev , Kaundal Pawan , Barwal Kailash Chander , Sharma Girish Kumar , Raina Pamposh
Published: May 2023

Radiation cystitis is a complication of radiation treatment given for pelvic malignancies. Radiation cystitis can present as mild symptoms of dysuria, frequency, and hematuria to severe life-threatening complications like intractable hematuria, bladder perforation and contracted non-functional urinary bladder, fistula etc. Treatment is tailored according to the severity of symptoms and available treatment modalities sequentially. Initial treatment of hematuria is intravenous fluids, blood transfusions, cystoscopy and fulguration, irrigation with intravesical agents like alum, hyperbaric oxygen therapy, angioembolisation, urinary diversion and surgery (cystectomy). Radiation cystitis is associated with short- and long-term complications in pelvic malignancies patients. Early diagnosis, follow up, treatment is crucial for decreasing morbidity and mortality in these patients. In this review article we describe the current protocol in diagnosing and managing radiation cystitis.

Keywords Pelvis, Radiation, Hematuria, intravesical treatments, Alum, formalin
Pharmacognostical, Phytochemical Screening and Evaluation of Anxiolytic activity of Alcoholic Extract of Withania somnifera (L) Dunal Roots
Authors: Pandey Umesh Chandra , Shukla Karunakar , Jatav Rakesh Kumar
Published: May 2023

The roots of Withania somnifera (L) Dunal (W. somnifera) are used extensively in Ayurveda, the classical Indian system of medicine, and W. somnifera is categorized as a rasayana, which are used to promote physical and mental health, to provide defense against disease and adverse environmental factors and to arrest the aging process. W. somnifera has been used to stabilize mood in patients with behavioural disturbances. The objective of this study was to investigate pharmacognostical, phytochemical features and anxiolytic activity of alcoholic extracts of W. somnifera roots. The various pharmacognostical variables were assessed using generally accepted techniques with certain variations. An established test technique that is documented in the literature was used to determine the qualitative analysis of different phytochemical elements. The anxiolytic efficacy of the alcoholic extract of W. somnifera roots in mice was evaluated using the elevated plus maze test (EPMT), light and dark test (L and DT), and open field test (OFT). Extract dosages of 250, 500, and 750 mg/kg were compared to the recommended dosage of diazepam (1 mg/kg) to determine its efficacy. Alcoholic extract underwent phytochemical examination, which identified the presence of fixed oils, lipids, proteins, amino acids, carbohydrates, tannins, and phenolics. The percentage of time spent and the number of entries in the open arm in EPMT were both considerably enhanced by the alcoholic extract of W. somnifera roots (250, 500, 750mg/kg, p.o.). The extract significantly increased time spent, the frequency of crossings, and decreased the length of immobility in the light box in L and DT. The extract in OFT significantly increased the number of rearings, increased ambulation, and decreased self-grooming and faecal dropping all signs of exploratory behaviour. The findings of the current investigation provide scientific support for the traditional use of W. somnifera by indicating that an alcoholic extract of its roots may have anxiolytic properties.

Keywords: Anxiolytic, Withania somnifera (L) Dunal, Elevated plus maze, Open field test, Light and dark test