bluuebunny/crossref_metadata_2025 huggingface dataset:
Pendampingan Perencanaan Fasilitas Penunjang di Pura Dalem Desa Adat Sebunibus, Kecamatan Nusa Penida, Kabupaten Klungkung, Bali
Authors: Mustika Ni Wayan Meidayanti , Wijaya I Kadek Merta , Rahadiani Anak Agung Sagung Dewi
Published: June 2023

Pura Dalem Desa Adat Sebunibus adalah salah satu pura Tri Khayangan di Desa Adat Sebunibus yang belum memiliki fasilitas penunjang yang berfungsi untuk mewadahi kegiatan persiapan upakara keagamaan seperti memasak, membuat sesajen dan kegiatan servis lainnya. Dari permasalahan tersebut maka harus direncanakan fasilitas penunjang di Pura Dalem Desa Adat Sebunibus yang sesuai dengan kebutuhan fungsi dan standar teknis yang baik. Artikel ini memaparkan tentang pelaksanaaan kegiatan pengabdian kepada masyarakat dengan mitra masyarakat pangempon Pura Dalem Desa Adat Sebunibus. Kegiatan ini merupakan upaya pendampingan dan pemberdayaan potensi masyarakat mitra dalam merencanakan desain arsitektur fasilitas penunjang berupa pewaregan (dapur), bangunan reringgitan dan panggung pertunjukan tari. Metode pelaksanaan kegiatan ini dibagi dalam beberapa tahap yaitu: 1). Tahap persiapan dan identifikasi awal; 2). Tahap penyusunan desain alternatif; 3). Tahap Focus Group Discussion; dan 4). Tahap Finalisasi Desain. Bangunan fasilitas penunjang yang direncanakan menggunakan penerapan arsitektur tradisional Bali modern dengan pendekatan kontekstual berupa memaksimalkan penggunan material lokal. Hasil kegiatan ini adalah gambar rencana desain bangunan – bangunan fasilitas penunjang yang dapat menjadi dokumen perencanaan untuk tahap pembangunan selanjutnya.
Generating Smart Goals of Engineering Education Institutes in the Fast-Developing Countries
Authors: Vedhathiri Thanikachalam
Published: June 2023

India is facing many critical issues in meeting the challenges of human resource needs due to the globalization of its economy. Hence Indian engineering institutions have to upgrade their programs through appropriate educational goals to reach excellence as suggested by the National Educational Policy 2020. These goals center around capacity development, quality improvements, and efficiency improvements which are to be linked to industrial needs. Further, these institutes have to develop strategic plans. The educational goals are to be developed to improve the skills of the faculty members who can develop industry-specific programs based on human resource forecasts to avoid failures. A research study reveals that around 3% of engineering colleges have improved their programs, offered multidisciplinary programs, established linkages with industries, and offered consultancy programs. Most of the institutes have to develop strategic plans to meet the human and knowledge capital and they have to create linkages with various companies. Faculty members have to plan to reach excellence and undertake consultancy works and train the graduates with needed attributes. The administrators have to support and scaffold the growth of outstanding faculty members. Tracer studies and impact studies are to be undertaken to check the growth and contribution to knowledge capital and human capital.
A First Chat with ChatGPT: The First Step in the Road-Map for Artificial Intelligence ...
Authors: K R
Published: June 2023

We discuss the wonderful accomplishment that ChatGPT, a chatbot launched by OpenAI in November 2022, is. We connect this milestone to previous research, which suggests that language is but the first step towards creating Artificial Intelligence (AI). We list several steps to help all of us, with specific pointers related to ChatGPT, get to the next level in creating Artificial Intelligence (AI). We point out that OpenAI may not be as open as it sounds. As closed as OpenAI might be, their creation ChatGPT is undoubtedly an inspiration bound to evoke feelings of true love at first chat.

We highlight the principal requirement for all intelligent systems, including ChatGPT, which is the inclusion of the principle of inclusion. We suggest subject classification codes and headings, which are to be included in various disciplines as artificial as they are, aimed at incorporating the principle of inclusion and the creation of "The Universal Identity". We look at several crucial pedagogical possibilities, both for ChatGPT and the rest of us. We also have a discussion of the many concerns people have, about improvements in AI making jobs redundant, and why there might be a positive side to it.

We mathematically prove that taking the first step equals making infinite progress, in this quest for AI and everything else. We discuss computer code generation by computers and why computers are more naturally suited for writing computer programs. We describe reasons why the Turing Test is irrelevant in gauging intelligence. It is very likely that our pursuit of AI might be misleading. Intelligence could be an unintended consequence of curiosity left to roam free, best exemplified by a frolicking infant. This suggests that our attempts at AI could have been misguided. What we actually need to strive for can be termed artificial curiosity, AC, and intelligence happens as a consequence of those efforts.

We conclude with a conundrum, which should not really be that much of a challenge since it is a no brainer that needs no intelligence, as to what it is that we really want: Artificial Intelligence or Real Consciousness. And once we start to search for real consciousness, another unintended yet welcome consequence might be that, we will find pure happiness. There is nothing artificial about the path to absolute happiness, it is very authentic and well within reach.
Coupling between Human Brain Cortical Thickness and Glucose Metabolism from Regional to Connective level: a PET/MRI study
Authors: Huang Qi , Yang Yihong , Qi Na , Guan Yihui , Zhao Jun , Hua Fengchun , Ren Shuhua , Xie Fang
Published: June 2023

OBJECTIVES: Disruption of the balance between brain structure and function is implicated in many brain disorders. This study aimed to investigate the coupling between the brain cortical thickness (CTh) and glucose metabolism using 18F-FDG PET/MRI.

METHODS: 138 subjects who performed brain 18F-FDG PET/MRI were retrospectively recruited and divided into two groups according to their ages. The Spearman’s rank correlation was calculated between the FDG uptakes and CTh across the cortex for each subject to explore the structural and functional coupling (S-F coupling) at the regional level, which was then correlated with age to explore its physiological effects. Structural connectivity (SC) based on CTh and functional connectivity (FC) based on glucose metabolism were constructed followed by exploring the network similarity and coupling between SC and FC. The global and local efficiency of the brain SC and FC were also evaluated.

RESULTS: 97.83% of subjects exhibited a significant negative correlation between regional CTh and FDG uptakes (p<0.05 with FDR correction), and this S-F coupling was negatively correlated with age (r=-0.35, p<0.001). At the connective level, SC-FC coupling was almost positive, with more regions in the old age group exhibiting significant coupling than in the middle age group. Besides, FC exhibited denser connections than SC, resulting in both higher global and local efficiency, but lower global efficiency when the network size corrected.

CONCLUSION: This study found there is a coupling between CTh and glucose metabolism from the regional to connective level. These findings may have implications for the diagnosis and treatment of neurological and psychiatric disorders.

CLINICAL RELEVANCE STATEMENT: The observed coupling between brain cortical thickness and glucose metabolism, both at the regional and connective level provides insights into the brain mechanisms and highlights potential implications for the diagnosis and treatment of neurological and psychiatric disorders.
Glycemic Fluctuations of Children and Adolescence Type 1 Diabetes Mellitus and the Impressive Aspects of SARS-CoV-2 Since the Onset of Pandemic Lockdown: A Review Paper
Authors:   Diabetes Research Center of Mazandaran, Mazandaran University of Medical Sciences, Sari, Iran., Zamanfar Daniel , Ghazaiean Mobin ,   Student Research Committee, Mazandaran University of Medical Sciences, Sari, Iran., Zahedi Mohammad ,   Department of Medical Biotechnology, School of Allied Medicine, Iran University of Medical Sciences, Tehran, Iran.
Published: June 2023

Background: The COVID-19 pandemic limited the daily activities of children and adolescents with type 1 diabetes mellitus, and several factors are impacting ongoing care. The role of pandemics on glycemic control is unknown. We plan to assess the glycemic status and the factors that influence it during the pandemic. Objectives: Our goal was to examine the impact of COVID-19 quarantine on the glycemic control of children and adolescents with type 1 diabetes mellitus. Methods: Databases including PubMed, Scopus, Web of Science, and Science Direct, with English-type articles extracted from December 31, 2019, to March 3, 2022, were searched. The article review was based on factors influencing glycemic control in type 1 diabetes mellitus cases younger than 18 years of age during the pandemic period such as psychological factors, telemedicine role, lifestyle changes, various diabetes technology (cost, availability…), caregivers’ role, and socioeconomic factors. Results: We scanned 573 articles as an initial search for titles/abstracts and full-text reviews, and 54 articles remained after title/abstract screening for full-text assessment among which 14 articles (cohort studies) were included. Most studies reported glycemic improvement based on blood glucose metrics while some studies reported stable glycemic control. Although the pre-pandemic glucose profile is important, factors such as telemedicine, diabetes technology, and lifestyle play a more tangible role in improving glycemic control during the pandemic. Conclusions: Overall, the studies did not contain strong evidence that glycemic control worsened in children and adolescents with type 1 diabetes mellitus during the pandemic. Although the assessment was conducted over a short period, long-term multicenter studies would be useful for a more precise assessment of the mentioned potential factors.
A Study on Teacher Information System
Authors: Nazish Khan  , Samina Anjum  , Rabiya Saba  , Shruti Rangari
Published: June 2023

Government agencies hire a considerable number of teachers each year and assign them to various government schools. The need to maintain their information increases as the number of teachers rises. We are developing an app that will track teachers' employment information. In order to do this, the user app for teachers will have sections for accounts, education, careers, expertise, and more. A check-in option for attendance is also available. Since everyone has a smartphone these days, teachers will find it simpler to use the application. The admin side is a web portal. The administrator will verify the files and data that the teacher uploads and will maintain the validated data in the database acquired from the user app. If the information turns out to be incorrect, the administrator may take additional steps to reject it. This system will help reduce the amount of manual work currently needed.
Visibility Analysis and Time Series Forecasting
Authors: Asoke Nath  , Swapnil Saha  , Himashri Basu  , Shalini Torcato
Published: June 2023

Visibility prediction and time series forecasting are two important fields in the domain of data analysis and machine learning. Visibility prediction deals with the estimation of atmospheric visibility or the distance over which objects can be clearly seen in a particular location, while time series forecasting involves predicting future values based on historical data. Both these fields have a wide range of applications, including transportation safety, air quality monitoring, and renewable energy management. However, the current prediction of visibility is mostly based on the numerical prediction method similar to the weather prediction [1]. In the present study the authors proposed a method using XGBoost(Extreme Gradient Boosting) and Unsupervised Models(ARIMA, ARMA, LSTM) models to build a weather visibility prediction system. The results obtained were very close to actual dataset.
'Krishivanam' An Innovation to Prevent the Damages Caused by Fire and Wild Animals to The Agriculture Land
Authors: Vikram Shirol  , Vinayak M  , Anjali M D  , Manikant H  , Sheetal P K
Published: June 2023

Agricultural fields near forest areas often become the center of human-animal conflict. Due to increased
deforestation and destruction of wild-life habitat, animals venture out of forest areas in search of food. Other
major consequence of deforestation is forest fire and poaching. As solution to the issues specified, technology can
help to detect and warn potential human-animal interference near forest areas. On detection of fire near the
agricultural land, pump is turned on automatically to put off the fire. On detection of movement through IR
sensor, camera is turned on to identify the animal or human intruder using Objective induction algorithm. If
an animal is detected, animal specific sound repellent is played to drive the animal away. If any human with
weapons is identified, then an alarm is raised to alert neighbors of possible poacher and intruder. The farmer is
alerted by means of an alert message.
IOT Based Battery Swapping Station and Monitoring System for Electric Vehicle's
Authors: Mrs. Neeta. R. Kadam  , Atharva Narale  , Pratik Sabale  , Kaustubh Salegaonkar  , Tohid Patwekar
Published: June 2023

The transportation industry contributes a significant amount of carbon emissions and pollutants to the environment globally. The adoption of electric vehicles (EVs) has a significant potential to not only reduce carbon emissions, but also to provide needed energy storage to contribute to the adoption of distributed renewable generation. Similarly, providing adequate charging infrastructure plays a momentous role in rapid proliferation of Electric Vehicles (EVs). Easy access to such infrastructure would remove various obstacles regarding limited EV mobility range. A Battery Swapping Station (BSS) is an effective approach in supplying power to the EVs, while mitigating long waiting times in a Battery Charging Station (BCS). In contrast with the BCS, the BSS charges the batteries in advance and prepares them to be swapped in a considerably short time. Considering that these stations can serve as an intermediate entity between the EV owners and the power system, they can potentially provide unique benefits to the power system. Battery swapping stations are one of the best options for EV charging stations in India and even a solution to the lack of EV charging infrastructure in India. The battery swapping stations take less time to charge your electric vehicle 100%. Just Swap the Drain Lithium-Ion Battery with a new one and be ready for longer drives.
Smart Parking System for Institute
Authors: Sayee Gosavi  , Anjali Kokane  , Prof. Pallavi Utkarsh Nehete
Published: June 2023

As the number of vehicles on roads continues to rise, businesses are more likely to encounter a range of issues. To address such challenges, the "Smart Parking System" has been developed as an intelligent and automatic solution for parking vehicles. This system is designed to alleviate problems faced by urban areas on their roads. However, precisely tracking the availability of parking spots across different locations and times remains a significant difficulty. Nonetheless, the Smart Parking System enables parking attendants to easily locate empty parking spaces. Moreover, implementing this smart parking system can help minimize energy consumption and pollution levels in cities, ultimately contributing toward the country's economic growth.
Analysing Cyber Threats: A Comprehensive Literature Review on Data-Driven Approaches
Authors: Ayushi Monani  , Omkar Bhusnale  , Kunal Borade  , Rucha Madali
Published: June 2023

This literature review paper aims to examine and analyze the existing research on prediction models for different types of cyber-attacks. Four key research papers have been selected as the base for this review: "A Prediction Model of DoS Attack's Distribution Discrete Probability," "Apriori Viterbi Model for Prior Detection of Socio-Technical Attacks," "Cyber Attacks Prediction Model Based on Bayesian Network," and "Applying Data Science to Cybersecurity Network Attacks & Events.” An overview of the value of prediction models in cybersecurity and their function in reducing potential threats come first in the review. The methodology section outlines the search strategy used to identify relevant literature and the selection criteria for the base papers. The subsequent sections provide an overview of the field, highlighting the historical development and key theories or frameworks related to cyber-attack prediction. The themes or subtopics identified in the literature are discussed, focusing on the discrete probability distribution model of DoS attacks, the Apriori Viterbi model for detecting socio-technical attacks, the Bayesian network-based prediction model, and the application of data science in analyzing network attacks and events. The review critically evaluates the selected papers, analyzing their methodologies, findings, and limitations. It identifies gaps, controversies, and conflicting findings in the literature, paving the way for further research in the field. The synthesis and interpretation section integrates the findings from the different studies, compares various perspectives, and discusses the implications and significance of the literature for cyber-attack prediction. In conclusion, this literature review paper provides a comprehensive analysis of prediction models for cyber-attacks, based on the selected base papers. It highlights the strengths and weaknesses of existing approaches, identifies research gaps, and offers recommendations for future studies. This review contributes to the advancement of knowledge in the field of cybersecurity and aids in the development of more effective prediction models to combat evolving cyber threats.
IPL Data Analysis and Prediction Using Machine Learning
Authors: Dr. Vilas Joshi  , Yash Padol  , Kaiwalya Sevekar  , Chandan Sinha  , Rizwan Shaikh
Published: June 2023

The Indian Premier League (IPL) is a highly attended T20 cricket league founded by the Board of Control for Cricket in India (BCCI) in 2008. Valued at $6.7 billion in 2019, the IPL remains the most popular cricketing event in the world, even amidst the COVID-19 pandemic. Cricket is a beloved sport in India and enjoys significant media attention and financial investment. With the rise of technology, audiences can access affordable live streaming of matches from anywhere. Cricket analytics, powered by tools like NumPy, allow for the use of data to improve performance, study business opportunities, and provide insights and predictive intelligence on game outcomes.
Extraction of Character from Visuals and Images Using OpenCV
Authors: Fathima Chandhini S  , Rashad H  , Gowseelan K  , Jayasarathy S
Published: June 2023

To develop a computer vision system that can accurately extract characters from document pages and image data using the OpenCV library. The system is designed to process a wide range of visual inputs and extract characters with high precision and efficiency. The techniques used to implement the character extraction system, including pre-processing, feature extraction, and classification. The performance of the system is evaluated using a dataset of visual image data from a different type of visual inputs and the output of the system can be accurately extracting characters. In Future, Automated conversion of an image input into a machine-readable file.
A Discriminative Image Registration Model with Hybrid Feature Detector
Authors: Syed Abdul Hanan Ahmed Shah  , Shahnawaz Talpur  , Bushra Naz
Published: June 2023

Image registration is a manner of aligning two or more images of the same scene which achieves maximum accuracy. Analysis of geometric distortion, caused by the difference in viewing angle, sensor resolution and distance. The critical step in image registration is the collection of feature points and evaluate a spatial transformation mainly when outliers are present. In our proposed framework we have used the hybrid feature-based and area-based methods together. Before applying those methods, the Bilateral Filter is applied for the preprocessing of both the images, the reference image and the image that needs to be registered in order to make the images noise free. For feature detection, the ORB (Oriented FAST and Rotated BRIEF) is used which is basically a fusion of FAST key point detector and BRIEF descriptor with many modifications to enhance the performance. KNN (K-Nearest Neighbors) is used for matching similar points and for reducing the miss matches the efficient algorithm is used which is Random Sample Consensus (RANSAC). The template matching method is applied for the area-based matching.
Design and Fabrication of Automated Shopping Cart System
Authors: Pratik Raut  , Shubhamraj Prasad  , Vijay Prasad  , Raj Sawant
Published: June 2023

In cities, shopping malls experience high rush on holidays and weekends, particularly with offers and discounts. To minimize time spent at billing counters, a project proposes equipping merchandise in malls with RFID tags and trolleys with RFID readers and digital displays. This smart shopping trolley solution aims to enhance the shopping experience by addressing long queues, difficulty-finding products, and limited pricing visibility. The project focused on a small, cost-efficient, and user-friendly design, gathering ideas from group members. The trolley has been, successfully designed and fabricated, tested under loading conditions, meeting requirements. It is easy to use, requiring no special training, and benefits both retailers and customers by serving more customers simultaneously.
Home Automation Using Brain Signals
Authors: Mohan K  , Mallikarjun S M  , Beeresh  , Keerti Kulkarni
Published: June 2023

In this time of digitization and computerization, the life of individuals is getting more straightforward as nearly everything is programmed. This interconnection of the things can be used to help people with physical disabilities including paralysis. The brain signals of such people can be harnessed to create a home automation system. In this work, the concentration levels of such individuals are extracted using the EEG signals. These signals are then used to control the electronic devices. The designed system has been tested to operate the switching of an electric bulb using brain signals. This system can also be extended to assist a physically impaired individual to have effective control over electrical and electronic appliances and devices within a home.
All Aboard : Transforming the Tracks of Travel with an Innovative Railway Reservation System
Authors: Priyanshu Kumar Saw  , Nancy
Published: June 2023

In all nations across the world, the demand for safe, rapid, and dependable train services continues to be a source of worry. Safety, operational inefficiency and reliability of old railway systems and operations, as well as safety and security concerns that haunt many countries for changing rail infrastructure that exist the worldwide train sector is battling to stay afloat. to accommodate the rising freight and passenger demand because of the inefficient utilization of the rail network and Rail assets are being used inefficiently. This is predicted to cause train congestion. executives to design better and more efficient train systems efficiently. Indian Railways' passenger reservation system is one of the most extensive in the world. Approximately one million passengers travel with Indian Airlines every day in reserved accommodations. Another sixteen million passengers use unreserved flights.
Railways in India It are a huge job to navigate this large structure. We have investigated several aspects of implementing smart computing in reservation models for railway networks.
Secure and Transparent Crowdfunding using Blockchain
Authors: Prof. Kapil Hande  , Gitesh Sawarkar  , Pratik Kapse  , Raunak Modak  , Kaustubh Dharmare
Published: June 2023

Crowdfunding is a popular method for raising funds for various projects, where a large number of individuals contribute a small amount of money to finance a particular project. It provides an opportunity for entrepreneurs, startups, and artists to seek financial support from the general public, rather than relying on traditional funding sources such as venture capitalists, banks, and angel investors. This project aims to create a decentralized crowdfunding platform using Ethereum blockchain technology. The platform allows creators to post projects with funding goals and deadlines, and investors can contribute funds to these projects. Smart contracts are used to manage the crowdfunding process, ensuring that funds are released only when milestones are met, and that investors have a say in the progress of the project. The platform is designed to be transparent, secure, and accessible to anyone with an internet connection. By using blockchain technology, the platform eliminates the need for intermediaries, reduces transaction fees, and enables global participation. This project demonstrates the potential of blockchain technology in transforming traditional funding models and enabling decentralized innovation. The platform utilizes various features of Solidity, including structs, mappings, and events, to enable the creation, management, and tracking of projects, milestones, and investments. The web interface is developed using HTML, CSS, and JavaScript, with a Node.js backend that interacts with the smart contracts using the web3.js library.
An investigation and Environmental Aspects of Copper(II) Surfactant with Photocatalytic Degradation
Authors: Dr. Vandana Sukhadia
Published: June 2023

Surfactants have wide use all over the world in various field of the national economy, will continue to expand its scope of application and the consumption is also increasing. Photodegradation is a branch of science, which attracted the attention of science community all over the world due to selection of light as energy source to degrade large molecules to smaller size molecules which does not degrade easily. Copper(II) Soya Thiourea complex has been synthesised and photocatalytic degradation of this complex carried by using ZnO as semiconductor catalyst in non aqueous solvent benzene. Concentration effect on Copper (II) Soya Thiourea complex with reference of optical density, photodegradation and percent degradation has been studied here. Using light as an energy source to drive a reaction results in chemistry is much more ‘green’, helping to eliminate the requirement for harsh reactants which are often toxic and unrecoverable. Photocatalysis also has applications in wide area of renewable energy. Analysis of biological activities of Copper soap complex is also done with Staphylococcus aureus to anticipate that it will generate new hopes in the field of biological applications.
Effective Cardiovascular Disease Prediction on Different Parameters
Authors: Tanya Jain  , Dr. Anurag Jain
Published: June 2023

Globally, cardiovascular disease is the leading cause of death, according to WHO (World Health Organization) data, with more people dying from CVDs each year than any other cause. In 2016, an estimated 17.9 million people died as a result of cardiovascular disease (CVD), accounting for 31% of all deaths worldwide. A heart attack or a stroke is to blame for the majority of these deaths, at around 85%. Low- and middle-income countries account for nearly three-quarters of deaths from cardiovascular disease (CVD). A staggering 82% of the 17 million non-communicable disease-related deaths in 2015 occurred in countries with low or middle incomes, with cardiovascular disease accounting for 37% of all deaths under the age of 70. Tobacco use, an unhealthy diet, obesity, inactivity, and harmful use of alcohol can all be addressed through population-wide strategies to prevent most cardiovascular diseases [1].
Design of Microstrip Antenna for Satellite Applications at K-Band
Authors: V. Nagaraja  , Dr. B Anuradha
Published: June 2023

The Abstract-Satellite application's five-band microstrip patch antenna is suggested, and it is modelled using the HFSS studio software. The suggested microstrip patch antenna is constructed using templates that are square and rectangular in shape. The most crucial component of virtually every wireless advanced communication system is the microstrip patch antenna, which is crucial in transforming electrical signals into EM wave signals for electromagnetic transmission. This work develops an antenna that can function in the Ku/k/ku bands at frequencies between 10 GHz and 40 GHz. The majority of antennas for satellite applications are designed to have good wide bandwidth, high gain, and small size characteristics. Adjust and perfect the length using a rectangle and square patch of 4.3-4.4 dielectric constant substrate. Resize and improve the field's length; The microstrip patch antenna is made to operate in several frequency bands, including the ku, k, and ka bands.
Android Application for Complaint Management System
Authors: Ms. D. Rejees Jenifa  , Y. Savitha  , K. Theebika
Published: June 2023

By eradicating corruption and saving time, the Android application for complaint management offers a solution for the general public to solve concerns online. An app to handle and answer user inquiries is essentially a complaint management app. It can be used by businesses to answer consumer questions or by the government to answer questions from the general public. By using our program to pinpoint issue areas, quickly track complaint handling performance, and make adjustments, the complaints management system aims to make complaints easier to submit. Customer requests and complaints are recorded, addressed, and handled using complaints management software, which is also used to enable any other input. An app for complaint management is essentially one that handles and responds to customer inquiries. It can be used by businesses to answer consumer questions, or by the government to answer questions from the general public.
Quantitative Analysis of Aquatic and Associated Macrophytes in Selected Wetlands of North Dinajpur District, West Bengal
Authors: Sudeshna Mukherjee  , Dr. Sujit Kumar Mandal
Published: June 2023

Aquatic macrophytes are the taxonomically most diverse and important biotic component of any aquatic ecosystem. They perform significant role in both structural and functional maintenance of the ecosystem. Depth, density, diversity and types of macrophytes also represent as bioindicator of overall water body health. The current research deals with the diversity of macrophytes from 3 selected wetlands of North Dinajpur District. Extensive wetland survey was conducted from November 2021 to March 2023, reporting the presence of total 31 species belonging to 20 families. Asteraceae is the most dominant family followed by Cyperaceae and Polygonaceae. Among various growth forms, helophyte with 12 species showed qualitative dominance over hyperhydrate(06 species) followed by pleustophyte (05 species) and vittate (04 species) consecutively decreased in other form. According to Raunkiaer’s life form classification therophytes (24 species) showed the dominance over other 5 life form followed by hydrophytes and hemicryptophytes (02 species each) Different ecological parameters such as dominance, diversity, species richness and evenness have also been described in the present study.
Bank Locker Authentication System using Facial Recognition
Authors: Prof. A .B. Gadewar  , Yash  D Satre  , Saurabh Y Girme  , Sagar Walunj
Published: June 2023

Security and Authentication of individuals is necessary for our daily lives especially in Bank lockers. A smart digital door lock system for bank automation is equipment that uses digital information such as a user’s data and face recognition as the method for authentication in the system. In this system the bank will collect the face imprints of each person for accessing the lockers. Only authenticated people can recover the money, documents from the lockers as faces are stored for the individual identity of a person. For facial recognition, this project uses the CNN algorithm. In this project, only authenticated user can access the lockers as faces are stored for the individual identity of a person. Facial recognition alone cannot determine whether the person is real or not. Therefore, liveness detection is implemented. In liveness detection, the system detects if it interacts with a real person or a spoof artefact used by other person such as a face photo. To detect whether the person is live or not the project uses eye blink detection. In this system the owner of a particular locker needs to authenticate his/her identity by verifying their face following with an One Time Password authentication feature. Here the person will receive an OTP received on their registered mobile number, proceeding with it; the valid one will allow the owner to access the particular locker whilst incorrect will not.
Determination of Deprotonation Constant of Glycine in 10, 20 and 30% Dioxane in Dioxane-Water System and Related Thermodynamic Quantities at 308.15K by E.M.F. Measurement
Authors: Md. Shamsuddin
Published: June 2023

The deprotonation constant (pK1) of glycine in 10, 20 and 30% dioxane in dioxane-water system at 308.15K was determined by potentiometric method using calomel electrode with the help of modified Davies equation, the dissociation of glycine is given as:

ZH+ Z± + H+

m2(1-?) m2? m2?

where ZH+ = NH3+-CH2-COOH

Z± = NH3+-CH2-COO- (Zwitter ion)

and Z = NH2-CH2-COOH = glycine

k1 = acidic dissociation constant

k1 is given by:

log k1 = log k1(A) - (2A¢√μ/(1+ √μ)) + ?1μ

where k1 real dissociation constant 

k1(A) = Apparent Dissociation Constant 

Rearrangingthe above equationwe have:

log K1 - ?1μ = logK1(A) - (2A1√μ) / (1 + √μ)

= q where q = log K1(A) - (2A1√μ) / (1 + √μ) 

or q = log K1- ?1μ

-q = pK1 + ?1μ

The constant value of mH+ was calculated by:

log mH+ = (E0 - E)/K - log mCl_ + (2A¢√μ/(1+ √μ)) - ?1μ

The value of deprotonation constant was calculated by extrapolating graph at μ = 0 where is μ is ionic strength.The related thermodynamic quantities ΔG0, ΔH0 and ΔS0 and free energy transfer ΔGt were calculated by the following least square method.The deprotonation constant was calculated by least square method:

log K1 = -A*/ T + D*-C*T 

The related thermodynamic quantities ΔG0, ΔH0 and ΔS0 and free energy transfer ΔGt was calculated by the following least square method:

ΔG0 = -19.1438(-A* + D*T - C*T2)

ΔH0 = -19.1438(-A*- C*T2)

ΔS0 = -19.1438(D* - 2C*T)
Virtual Assistant With Sign Language
Authors: Dr. D. S. Hirolikar  , Hari Shelar  , Prajwal Berad  , Mohini Gawade  , Yogesh Pawar
Published: June 2023

This topic is all about developing a successful Sign language recognition and translation system which is helpful for people with certain disabilities who can’t use present voice enabled Virtual Assistants. Communication is important with people as it helps us understand them and gain knowledge. In case of Deaf & mute people, this becomes a problem. It is solved by creating a virtual assistant built to recognize hand gestures and translate them in normal language to perform tasks ordered by the user. This certainly helps other normal people to successfully communicate with deaf & mute people
Without worrying about any misunderstanding at the listener’s end. There are more than 300 sign languages used by various cultural groups worldwide. In this article, we provide a technique for generating a sign language dataset using a camera, followed by the training of a TensorFlow model using transfer learning to produce a real-time sign language recognition system. Despite the small amount of the dataset, the system still performs well.
Investigation On Mechanical Properties of Silicafume Blended High Strength Concrete
Authors: Guru Bramham S  , Nirosha  D  , Guru Jawahar J  , Anil A
Published: June 2023

The study of the mechanical properties of high performance concrete mixed with silica fume aims to study the effect of adding silica fume as a partial replacement of cement on grades M60, M70 and M80 of high performance concrete.In this study, silica fume was the cement and the resulting concrete was tested for compressive strength and splitting tensile strength. The results show that the 15 percent substitution of silica fume significantly improved the mechanical properties of concrete.It is observed that as the curing time increased, the values for compressive strength and splitting tensile strength are increased. It is concluded that the optimal proportion of silica fume contributed significantly to the strength of high-strength concrete.
Experimental Investigation on E-Waste Concrete with Silicafume
Authors: Narayanamma Velpula  , Thulasirajan Krishnan  , A. Anil
Published: June 2023

Electronic waste, commonly referred to as "E-waste," is any electronic device that is no longer useful or has reached the end of its useful life. This can include computers, smartphones, tablets, televisions, refrigerators, and other household appliances, as well as industrial equipment and medical devices. Many electronic devices contain hazardous materials such as lead, mercury, cadmium, and brominated flame retardants, which can be harmful to human health and the environment if not disposed of properly. Improper disposal of e-waste can lead to environmental pollution, as well as health problems for those who are exposed to the hazardous materials and is passing severe toxic waste issues to the human beings and the environment. E-waste is a growing problem worldwide, as electronic devices become more common and quickly become obsolete due to advances in technology. Recycling and proper disposal of e-waste is becoming increasingly important as more electronic devices.
From then literature review it is inferred that the E waste was added to the concrete by partial replacement of Fine Aggregates. Recommended dosage of E waste as partial replacement of coarse aggregate was 10 % concrete. Minimum studies were carried out as a partial replacement of fine aggregates. To recommend the optimum percentage of E waste as replacement of fine aggregate. No effective method to prevent the leaching of toxic components from E waste concrete. The Compressive Strength, Split-Tensile strength, Rebound Number, UPV test and Durability tests was carried.
Therefore, by incorporation of Silica Fume the mechanical properties such as Compressive strength and Tensile strength are improved. The increase in the % of E- waste decreases the density and hence E-waste concrete can be adopted for light weight construction. The quality of E-waste concrete improved by the incorporation of Silica Fume. which is evident from the rebound hammer and Ultrasonic Pulse velocity results. And also Durability Test results. The Optimum % of E-waste was found to be 5%.
Overall, the combination of E-waste and Undensified Silica Fume develop a sustainable concrete which can prevent the unnecessary dumping of E-waste and act as a light weight concrete.
Study of Raman Redshift of Nanoscale Semiconductors
Authors: Madan Singh  , L.M. Mafereka
Published: June 2023

Considering the Lu model and dangling bonds, we derived equations for the optoelectrical properties of semiconductors at the nanoscale. The size and shape-dependent band gap and phonon frequency of nanoparticles are studied. It is reported that the bandgap increases on decreasing the size, while the phonon frequency decreases on reducing the particle size in the nano range. The effect of shape is included in our research. It is projected that the effect is considerable on changing the shape from spherical to film shape. The developed model may provide new insight, into where the experimental findings are missing.
A Breast Cancer Diagnosis Framework Based on Machine Learning
Authors: Dr. Nikhat Akhtar  , Dr. Hemlata Pant  , Apoorva Dwivedi  , Vivek Jain  , Dr. Yusuf Perwej
Published: June 2023

Breast cancer is becoming the leading cause of mortality among women. One of the most prevalent diseases in women, breast cancer is brought on by a variety of clinical, lifestyle, social, and economic variables. Predictive approaches based on machine learning offer methods for diagnosing breast cancer sooner. It may be found using a variety of analytical methods, including Breast MRI, X-ray, thermography, mammograms, ultrasound, etc. The most prevalent technique for performance evaluation uses accuracy measures, and the Convolutional Neural Network (CNN) is the most accurate and widely used model for breast cancer diagnosis. The Wisconsin Breast Cancer Datasets (WBCD) were used to evaluate the suggested method. Out of a total of 569 samples, 273 samples were chosen for this experiment as the test data, while the other samples were utilized for training and validation. The review's findings showed that the Convolutional Neural Network (CNN) is the most effective and widely used model for finding breast cancer, and that the most often used technique for judging performance is accuracy metrics. The application of deep learning to such a wide range of real-world issues is astounding.
Attendance System Using Face Detection and Face Recognition in Python Programming Language
Authors: R. Jeya Malar  , Reenathangam G  , Ranjani V
Published: June 2023

The programming language Python is gaining popularity. It has a fairly flat learning curve and is a free, high-level language. It features a large selection of free libraries. The first topic covered in this study is computer vision libraries. The capabilities of the existing libraries for face detection and identification are next examined. The algorithm utilised in the libraries is provided a basic description. An example of the generated image is given for each significant stage. Even though the study only includes two sample photographs, the technique was tested on a large number of images. The investigation proved that Python is the go-to programme for tasks requiring face recognition and detection.
LocoSpot – Smart Tourist Guide
Authors: Prof. R. M. Kawale  , Mukund H. Sutar  , Ayubkhan D. Nadaf  , Vishal M. Chormale  , Siddheshwar G. Pawar
Published: June 2023

The idea of creating an Android travel application with a retrieval-based chatbot that can assist users is investigated in this study. Our system provides reliable and accurate information on every tourist site in Pune, together with an online map. The recommended design will also incorporate a retrieval-based chatbot system, which will allow it to assist those in need and make the programme more user-friendly by providing text guidance so that users may communicate with the bot. We discovered that several websites provide various services. Websites provide booking services, but there is no method for travellers to find potential destinations.This bot will only react to questions regarding the programme and point users in the right direction so they can use it without any trouble. Our strategy will encourage all other travellers to use the easy routes and dramatically increase customer satisfaction and retention.The result of the project is an Android application with a chatbot that suggests hidden local tourist spots, providing an engaging and interactive experience for travellers seeking unique destinations. The application improves its responses and features location-based services and user authentication for personalized recommendations.
MITRA (For Music and Quotes)
Authors: Vasantha M  , M.V.P.S Chihinita  , Malini Arumugam  , Meghana S  , Sparshitha K
Published: June 2023

We all live in a time where nothing is certain. Likewise goes with our minds. Our attitudes, decisions, and priorities shift on a regular basis. We are pleased to announce that we have created "MITRA (for Music and Quotes)" in light of a solution for people's behavior continually evolving. Mitra means "Friend", as the name would imply. We employ machine learning techniques for the chatbot and facial recognition so that our interface will act as a friend to the users and make music and quotes suggestions depending on the emotion recognized in the text while messaging with the chatbot and the emotion recognized in the face using facial recognition. It also contains a notes part where you can record the necessary content, and it uses a database for storage purpose.
Characterization of Zn-Doped CdO Nanoparticles Thin Films Synthesized by Pulsed Laser Deposition
Authors: Hassan H. Darwoysh  , Ali A. Yousif  , Kadhim A. Aadim
Published: June 2023

In this investigation, thin films of CdO:Zn were synthesized by using the technology of pulsed lasers. Additionally, the effect of different concentrations of Zn doping on the material's physical properties was investigated. According to XRD research, the films have a polycrystalline structure, and it was discovered that the size of the crystallites changes depending on the amount of Zn doping. The morphology of the produced films reveals that there are spherical nanoparticles distributed evenly all over the surface of the films and ranging in size from nanometer to nanometer. The increase in Zn doping concentrations resulted in an improvement of the material's optical characteristics. The results of the Hall effect observations show that each of the films possesses n-type conductivity. This property, combined with the films' low resistivity, enables them to be utilized in a wide variety of contexts. In addition to this, each of the films has a large concentration of carrier molecules.
Early Detection of Plant Leaf Disease Using Deep Learning
Authors: Shivam Ardalkar  , Aishwarya Waghmode  , Aniket Jadhav  , Parimal Bhosale  , Prof. Afsha Akkalkot
Published: June 2023

As crop diseases spread, farmers need to prevent and control their contamination to increase productivity and yield. In addition to affecting plants, plant diseases affect market access and agricultural production. As one of the most important vegetable plants in the world, leaf images can be used to classify diseases early. In addition to Yellow Curved, Late Blight, and Leaf Spot, Bacterial leaf Spot, there are other diseases of plants. The dataset is taken from the Internet. In this paper, we take leaf images with various leaf diseases and train it with the best model Convolutional Neural Network (CNN). We then use the weights from CNN to test new leaf images. By using convolutional neural networks (CNNs) and deep learning techniques, we have proposed a system that classifies plant leaf diseases. With the hybrid approach, the model will demonstrate its accuracy. To identify the best model, performance analysis is done with accuracy and finds solution to the problem.