bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on the current status and trend of the application of machine learning in the field of literature and museums- Based on CiteSpace
Authors: Chen Jiayuan
Published: April 2024

With the development of the world economy and the rapid arrival of the digital era, machine learning technology continues to develop and is widely used in various fields, including the field of literature and museums. The article analyses and researches the relevant literature through citespace visualization software with machine learning research in the field of literature and museums as the main hotspot. It is found that in recent years, the attention to machine learning in the field of literature and museums has shown a significant growth trend, and the machine learning technology is concentrated in the conservation of cultural relics, museum management, cultural heritage protection, heritage identification, etc., which realises the automation, intelligence and personalization of the field of literature and museums and greatly improves the efficiency of work. Finally, this study summarises the current trend of machine learning research in the field of cultural and museums, and puts forward the outlook for the future development direction. By deeply analysing the current situation of machine learning research in the field of literature and exposition, it provides useful references and insights for future researchers, and helps to promote the in-depth development of the intersection between the field of literature and exposition and machine learning, and promotes the innovation and cooperation of related research.
Research on the mechanism of youth-friendly city impact based on structural equation model
Authors: Dai Mengping , Han Yang , Wang Yixuan , Wang Yuhan
Published: April 2024

For urban development, the focus must be on the youth, and the construction of youth-friendly cities is in line with the needs and trends of the times. However, existing research on youth-friendly cities mainly concentrates on policy principles, paying less attention to urban spaces closely related to the youth and lacking an evaluation mechanism for youth-friendly cities. Additionally, in current practices, the construction of youth-friendly cities is predominantly concentrated in economically developed first and second-tier cities, with insufficient implementation in county-level units. Against this background, this study employs a structural equation model to investigate the mechanism of youth-friendly cities. The research focuses on Suning County, aiming to explore the path of constructing a youth-friendly city at the county level and proposing effective strategies. The analysis involves the examination of existing resources, permanent population, age structure, and academic situations in Suning County. Subsequently, the study proceeds with model construction and fitting, followed by a fitness test of the model results to draw conclusions that aid in addressing challenges in the process of constructing a county-level youth-friendly city.
A method for generating the digital twin models of plants
Authors: Lin Yi , Zhao Xinyu , Zhang Chuyang
Published: April 2024

In the process of creating digital twin models of plants, the simulation accuracy of models generated by conventional 3D reconstruction methods is insufficient. Considering the increasing number of models over time, adopting deep learning-based models not only consume a significant amount of time but also require substantial computational resources consumption. Therefore, we proposed a method for generating digital twin models of plants, aiming to ensure the simulation credibility while effectively reducing resource costs. Experimental results show that this method is capable of generating plant models that closely resemble physical entities at different growth periods. Compared with other construction methods, this approach achieves higher simulation credibility (CD=0.089, EMD=0.034, KNN=0.005, RGB=4.97) with lower computational resources consumption (ROM=7.46MB, VRAM=2456MB, Time=0h5min48s) when generating a digital twin model.
Scientific calculation and application of safety marking principles
Authors: Chen Yuhui , Zhao Hongzhe , He Menghan , Pan Yanling
Published: April 2024

In today's era, trains have become an indispensable mode of transportation for people, yet safety hazards are inevitable during the process of trains entering stations. To study these safety hazards and the principles behind the design of safety markings, we combine the Bernoulli Effect and the conservation of mechanical energy in fluids, taking into account factors such as a person's weight, volume, and distance from the train. We derive an expression that relates the pressure experienced by individuals to the train's speed, the train's cross-sectional area, the distance between the individual and the train, and the area of the individual subjected to force. By comparing this with the general friction force that corresponds to real-life situations, we find that the distances for safety markings provided by the national "Railway Technical Management Regulations" for high-speed train and dynamic train stations are reasonable: for speeds not exceeding 120km/h, the distance is 1000mm; for speeds over 120km/h but not exceeding 160km/h, the distance is 1500mm; and for speeds over 160km/h up to 200km/h, the distance is 2000mm, regardless of the platform height. Based on the factors affecting the safety markings on railway platforms, four practical safety recommendations are proposed.
Secondary eclipse and day-night modulation of exoplanets observed by transiting exoplanet survey satellite
Authors: Ye Huanyu
Published: April 2024

Astronomers have identified over five thousand extrasolar planets since the discovery of the first solar-like star in 1995. These systems exhibit greater diversity than our solar system, providing insights into their formation and evolution. To understand these exoplanets and their habitability, it is crucial to examine their atmosphere composition. The Transiting Exoplanet Survey Satellite (TESS) can detect reflected light from exoplanets with high accuracy, providing valuable insights into their formation and potential for life in the Universe. Planetary reflection can be detected by monitoring the light curve, which is the sum of stellar flux and planetary reflection. Orbiting planets may also reveal their presence by modulating reflected starlight, showing day-night variations in observers sight lines. However, these flux variations are extremely small, at a level of 0.01%, making detection difficult. This study developed an efficient Python program to search for secondary eclipse and day-night modulation on the TESS light curves of over four hundred known short-period transiting exoplanets. The program automatically identifies and rejects low-quality photometric data points in light curves, folding high-quality light curves in the orbital phase determined by primary transits. The phase-folded average light curves have high photometric precision, suitable for detecting secondary eclipse and day-night modulation. The program successfully identified planetary reflection in seventeen transiting exoplanetary systems, larger than the current TESS sample by twice. The program plans to upgrade to search for orbital phase modulation in non-transit exoplanets, taking advantage of the high precision of TESS photometry.
Solvability of two-dimensional system of difference equations with constant coefficients
Authors: Aktaş Ömer , Kara Merve , Yazlik Yasin
Published: April 2024

In the present paper, the solutions of the following system of difference equations
\begin{equation*}
u_{n}=\alpha_{1}v_{n-2}+\frac{\delta_{1}v_{n-2}u_{n-4}}{\beta_{1}u_{n-4}+\gamma_{1}v_{n-6}}, \ v_{n}=\alpha_{2}u_{n-2}+\frac{\delta_{2}u_{n-2}v_{n-4}}{\beta_{2}v_{n-4}+\gamma_{2}u_{n-6}}, \ n\in \mathbb{N}_{0},
\end{equation*}
where the initial values $u_{-l}$, $v_{-l}$, for $l=\overline{1,6}$ and the parameters $\alpha_{p}$, $\beta_{p}$, $\gamma_{p}$, $\delta_{p}$, for $p\in\{1,2\}$ are non-zero real numbers, are investigated. In addition, the solutions of aforementioned system of difference equations are presented by utilizing Fibonacci sequence when the parameters are equal $1$. Finally, the periodic solutions according to some special cases of the parameters are obtained.
Inter-linkages Among Selected Stock Markets of South Asia: Revisit
Authors: Suman Suman
Published: April 2024

The present study investigates the inter linkages among South Asian stock markets namely India, Sri Lanka and Pakistan. The topic is important for international investors because if the stock markets are found integrated with each other then they cannot reap profits from portfolio diversification or reduction in risk. Daily closing prices of the bench mark indices of three countries are taken for a period from 1 Jan. 2001 to 23th Feb. 2023. The paper used statistical tools such as descriptive statistics and correlation analysis and on the other hand, the econometric techniques namely Johansen’s Co integration test, VAR, Variance Decomposition Analysis, Impulse response function and Granger causality test and the selected stock markets are found interlinked in long run as well as in short run.
Innovative Framework for Thyroid Disease Detection by Leveraging Hybrid AGTEO Feature Selection and GRU Classification Model
Authors: K Hemapriya , K Valarmathi
Published: May 2024

Thyroid disease remains a significant health concern, necessitating advanced diagnostic tools for swift and accurate identification. The initial step involves preprocessing datasets, employing an Outlier Detection Method with Isolated Forest in conjunction with data normalization techniques to eliminate noise and standardize the data, laying a robust groundwork for subsequent analysis. Subsequently, feature extraction is conducted utilizing an Enhanced AlexNet architecture augmented by a more intricate Chameleon Swarm Algorithm (CSA) model to discern finer patterns within the data, enhancing the discriminative nature of the extracted features. Following this, a feature selection strategy employing hybrid optimization is deployed, amalgamating the strengths of Equilibrium Optimizer and Artificial Gorilla Troops Optimizer (AGTO) into a hybrid model named HAGTEO, aiming to identify the most informative features, thus reducing dimensionality and enhancing classifier efficiency. Ultimately, the Gated Recurrent Unit (GRU) classifier is employed for thyroid disease classification based on the extracted and selected features. Renowned for its capability to capture temporal dependencies, the GRU model further enhances classification accuracy. The proposed framework is subjected to testing on two distinct datasets, demonstrating its efficacy in thyroid disease detection. Experimental outcomes reveal superior performance compared to conventional methods, achieving accuracies of 98.07% and 98.00% for dataset 1 and dataset 2, respectively. As an advanced diagnostic solution for thyroid disease, it holds promising potential.
Supplementation of Aloe Vera to Formulate the Fortified Bread by Managing its Nutritional Profile
Authors: Raza Nighat , Bano Naheed , Hamza Ali , Naz Ambreen , Shahbaz Muhammad , Murtaza Shamas , Khan Maha , Kaleem Muhammad , Mujtaba Ahmed , Shabbir Bisma
Published: April 2024

Aloe vera is the medicinal plant rich in bioactive compounds. It has a potential to cure many health related problems. The challenge for the food sector is to create novel food products with health promising properties. Objective: To fortify the bread with two different varieties of Aloe vera in different treatments in varying proportion (0, 10, 20, 30%). Methods: The raw material was analyzed and compositional results of proximate analysis of Aloe vera gel indicated the moisture content (98 ± 0.081, 98.5 ± 0.816), crude protein (0.39 ± 0.008, 0.34 ± 0.0081), crude fat (0.22 ± 0.081, 0.23 ± 0.016) crude ash (0.4 ± 0.081, 0.4 ± 0.081), crude fiber (0.59 ± 0.081, 0.31± 0.0816), and NFE (0.4 ± 0.163, 0.01 ± 0.0081) % for Aloe barbedensis miller and A. barbedensis marlothi respectively. The product was developed using different proportions of both varieties of Aloe vera. The proximate, mineral, color, texture and sensory properties of the Aloe vera fortified bread samples were evaluated. Results: Results of the proximate analysis showed that addition of 20% of marlothi variety of Aloe vera enhance the texture of bread. However, the sensory evaluation indicated that the 20% Aloe vera fortified bread was not significantly different from the bread produced from 100% wheat flour in terms of quality attributes evaluated in this study. Conclusions: Fortification of bread with Aloe vera gel increased the fiber content and macronutrient of conventional bread. In addition, the Aloe vera fortified bread was rich in minerals and also acceptable to consumers at 20% fortification level.
New reflections and strategies for social sustainability through the climate change crisis within inclusive participation and school
Authors: Bernaschina Diego
Published: April 2024

The goal of this paper corresponds to a small theory on the discovery of the incorporation of climate action to go deeper regarding educational treatment. There is no search to raise awareness in the social community for educational inclusion on current environmental problems such as pollution, loss of biodiversity, and climate change, among others. Social inclusion on ecology and the new treatment of sustainability through practice that allows us to assume and strengthen the greatest responsibility for the environment, this is, notable and conscious, of course, the transversal programs within the environmental matter together with the inclusive school. This educational operation seeks to strengthen the practice of values that allow us to assume the greatest responsibility of caring for the environment in a notable and conscious way, of course, the transversal programs within the environmental field along with the participation of students with cultural-functional diversity. It is possible to debate the use of a modernized model for inclusive ecology to improve the structuring of the educational strategy, depending on the teaching and learning process of the inclusive school.
Pengembangan Aplikasi General Affairs Berbasis Web Menggunakan Framework CodeIgniter Kasus PT. Rajawali Nusantara Indonesia
Authors: Efrizal Efrizal , Tawakal Hilmy Abidzar
Published: May 2024

Dalam PT. Rajawali Nusantara Indonesia (RNI) terdapat divisi yang menangani bagian umum dalam perusahaan. Divisi tersebut bernama divisi Pelayanan Strategis SDM dan Umum. Pada divisi ini menangani beberapa unit kerja seperti pemeliharaan aset perusahaan (Maintenance), pengemudi (Driver), dan pengiriman atau ekspedisi. Pada layanan pengiriman belum tersedianya sistem yang menanganinya, sehingga dalam penanganannya masih secara manual. Sedangkan untuk kedua layanan lainnya yaitu maintenance dan pengemudi sudah menggunakan sistem berbasis web dalam penanganannya. Walau sudah terdapat sistem yang menanganinya, berdasarkan hasil wawancara dengan ahli terkait, sistem tersebut masih terdapat kekurangan. Dalam penelitian ini akan merancang aplikasi General Affair berbasis web dengan menggunakan framework Codeigniter. Dalam pengembangan aplikasinya menggunakan metode extreme programming dengan penggunaan diagram UML untuk dokumentasi desain. Aplikasi yang telah dibuat akan dilakukan pengujian menggunakan metode blackbox dengan hasil 100% keberhasilan dari 31 skenario yang diuji, dan User Acceptance Testing untuk menguji apakah sistem sudah sesuai dengan keinginan pengguna atau tidak dan menghasilkan 100% keberhasilan. Hasil penelitian berupa aplikasi general affair berbasis web yang dikembangkan menggunakan framework Codeigniter. Berdasarkan hasil analisis hasil kuesioner aplikasi General Affair berbasis web ini dapat membantu proses aktivitas operasional di PT. RNI dengan interpretasi baik.
IoT-based Smart Farming System
Authors: Tan Yan Sen , Chew Li Wei , Tan Yi Xuen , Tan Sean Zhuang
Published: May 2024

The integration of Internet of Things (IoT) technologies into agricultural operations, known as smart farming, presents a transformative opportunity to revolutionize traditional farming methodologies and bolster productivity, efficiency, and sustainability within the agricultural sector. This paper investigates the challenges inherent to conventional farming practices, such as inefficient resource utilization and inadequate access to real-time data to inform decision-making. By leveraging an array of IoT sensors and devices are utilized for the purpose of gathering up-to-date information on various aspects such as environment factors and animal natural behaviors, agricultural producers can gain actionable insights, facilitating data-driven decision-making to optimize resource usage and enhance crop yields. The primary objectives of this study encompass enabling automation and precision agriculture to mitigate waste and bolster productivity, while concurrently emphasizing remote monitoring and control capabilities through mobile technologies to augment overall operational efficiency and crop quality. The background underscores the critical importance of integrating IoT technologies into agricultural practices to streamline farm management processes, reduce labour requirements, and increase profitability across all scales of agricultural operations. Through the implementation of IoT-enabled smart farming solutions, this paper endeavors to bridge the divide between advanced technology and practical agricultural needs, offering a cost-effective and user-friendly approach to modernizing farming methodologies.
Strategi Perusahaan Maskapai Penerbangan dalam Menghadapi Pandemi Covid-19: Pendekatan Akuntansi Manajemen
Authors: Natanael Johanes Abraham , Irawan Ferry
Published: April 2024

The Covid-19 pandemic has caused many companies to experience a decline in revenue and profits, including airline companies. PT Garuda Indonesia is one of the companies included in the tourism industry ecosystem which has also been affected by the Covid-19 pandemic. This research aims to investigate the strategies companies choose to face the Covid-19 pandemic. This research uses a qualitative method with a case study approach. The research results show that cost efficiency and product differentiation strategies are able to increase company revenues.
Impact Of Natural Disaster On Local Tax Revenue
Authors: Anugerah Bima Satria , Wijaya Suparna
Published: April 2024

Poverty is one of the problems that always become main concern in Indonesia, the problem of poverty is worsen when economic shocks occur, one of which caused by natural disasters, these two things adding the burden on the government, especially at the regional level both in the context of fiscal management and countermeasures. By using panel data from 34 provinces in Indonesia, this study aims to find the effect of natural disasters and poverty rate on regional tax revenues at provincial level with foreign direct investment (FDI) as a moderating variable. The results of the regression shows that natural disasters and the poverty rate have positive effects on local tax revenues, but these two variables become negatively affected when moderated by FDI so that moderation weakens the effect of the two independent variables, the FDI variable itself when tested as an independent variable has positive effects on local tax revenues. This research is expected to assist local governments in formulating fiscal policy in the event of a post-disaster economic shock and its countermeasures as well as poverty alleviation efforts when the economy is running normally.
Manajemen Pajak Perusahaan Alih Daya
Authors: Bangun Corleone AK , Putri Farah Oktaviani , Muna Jannatul , Alya Audrey , Sebastian Marcellino Ferdinan , Anjarwati Emilia Eni , Irawan Ferry
Published: April 2024

Perusahaan yang terdaftar sebagai wajib pajak pada umumnya membutuhkan manajemen pajak. Manajemen pajak bermanfaat agar pemenuhan kewajiban perpajakan dapat dipenuhi, pembayaran pajak seefisien mungkin, dan menghindari sanksi baik administrasi maupun pidana. Di sisi lain, manajemen pajak juga bertujuan untuk meningkatkan akuntabilitas organisasi. Manajemen pajak juga dilakukan oleh sebagian perusahaan yang bergerak dalam bidang penyediaan tenaga kerja. Penelitian ini bertujuan untuk mengelaborasi manajemen pajak yang dilakukan oleh perusahaan alih daya. Penelitian menggunakan metode kualitatif dan menggunakan PT ABC sebagai objek penelitian. Hasil penelitian memeroleh beberapa temuan. Pertama, kewajiban perpajakan PT ABC berupa PPh Pasal 21, PPh Pasal 23, PPh Pasal 4 Ayat (2), PPN, dan PPh Badan. Kedua, perusahaan telah melakukan kewajiban pajak sesuai dengan peraturan perundang-undangan yang berlaku.
Hotel, Restoran, dan Wisatawan Bertumbuh: Apakah Penerimaan Pajak Daerah Juga Meningkat?
Authors: Bagaskara Pius Aji Cakra , Wijaya Suparna
Published: April 2024

Penelitian ini bertujuan untuk mengetahui pengaruh sektor pariwisata terhadap penerimaan pajak daerah yang tercermin dari pajak hotel dan pajak restoran, adapun sektor pariwisata ini dilihat dari jumlah hotel, restoran, serta wisatawan. Adapun data yang digunakan merupakan data sekunder yang diambil dari DJPK Kementerian Keuangan, Badan Pusat Statistika serta Dinas Kepemudaan, Olahraga, dan Pariwisata Provinsi Jawa Tengah pada tahun 2018 sampai 2021, adapun objek yang diteliti adalah 35 kabupaten/kota di Provinsi Jawa Tengah. Metode yang digunakan adalah metode kuantitatif dengan regresi linear berganda data panel dengan model random effect. Hasil dari penerlitian ini menunjukkan bahwa secara simultan, seluruh variabel berpengaruh secara positif dan signifikan terhadap penerimaan pajak daerah. Secara parsial, jumlah hotel berpengaruh signifikan positif, begitu juga setelah dimoderasi dengan jumlah wisatawan. Jumlah restoran sendiri tidak berpengaruh terhadap penerimaan pajak daerah, meskipun dimoderasi dengan jumlah wisatawan, tetap tidak berpengaruh. Selanjutnya jumlah wisatawan justru berpengaruh negatif terhadap penerimaan pajak daerah. Penelitian ini diharapkan mampu memberi masukan bagi pemerintah daerah dalam merumuskan kebijakan khususnya dalam hal pengumpulan pajak daerah.
Determinan Kualitas Hasil Pengawasan Di Badan Pengawasan Keuangan Dan Pembangunan
Authors: Mubarok Danang Andrian , Usman Fadlil
Published: April 2024

Penelitian ini bertujuan untuk mengetahui pengaruh kompleksitas tugas, tekanan anggaran waktu, kompetensi auditor dan objektivitas auditor terhadap kualitas hasil pengawasan. Penelitian ini dilakukan dengan metode kuantitatif dengan jenis penelitian kausal. Data pada penelitian ini dikumpulkan dengan melakukan penyebaran kuesioner kepada auditor di Deputi 1 dan Deputi 2 Badan Pengawasan Keuangan dan Pembangunan (BPKP). Teknik analisa data yang digunakan adalah Structured Equation Model (SEM) untuk melakukan pengujian hipotesis. Hasil dari penelitian ini menyimpulkan bahwa kompleksitas tugas, kompetensi auditor dan objektivitas auditor bepengaruh positif dan signifikan terhadap kualitas hasil pengawasan. Sedangkan tekanan anggaran waktu tidak berpengaruh terhadap kualitas hasil pengawasan. Penelitian ini diharapkan dapat menjadi bahan masukan dan pertimbangan dalam rangka evaluasi desain, strategi dan kebijakan pengawasan intern.
Handwritten Telugu Character Recognition & Signature Verification
Authors:   Assistant Professor, Department of Computer Science Raghu Engineering College, Visakhapatnam, R Mr.Venkatesh
Published: April 2024

Behaviour reputation stands as one of the earliest applications in sample reputation. While spotting handwritten characters is an clean venture for humans, it is a formidable task for computer structures. Optical Character Recognition (OCR) is an crucial answer primarily based on optical systems, which enables automatic reputation of scanned and digitized characters This paper explores into optical man or woman popularity strategies in particular developed for handwriting Telugu within the characters. Telugu, a Dravidian language spoken especially in Andhra Pradesh and Telangana, India, offers precise challenges because of its complex alphabet Basic parts of Telugu script together with "vattu" which stands for vowels and "gunitalu" which means that tone the complicated syllables add to the complexity. Combining OCR strategies with Harris corner popularity, the paper affords insights into the accuracy and efficiency of handwritten Telugu person reputation and the fidelity of handwriting This have a look at contributes to the development of character reputation in particular on in complex written languages ​​which include Telugu and gives realistic explanations for handwriting verification processing. Key Words: Optical Character Recognition (OCR), Telugu, Vattu, Gunitalu, Harris corner detection, Handwritten Character Recognition, Signature Verification.
Optimizing Concrete Properties Utilizing Marble Waste Powder with Fine Aggregate and Coconut Shell with Coarse Aggregate
Authors:   Assistant professor, Department of Civil Engineering & Srinivasa Ramanujan Institute of Technology (Autonomous), Ananthapuramu, A.P, VENKATASUNEEL PITTI
Published: April 2024

The study delves into the innovative utilization of marble waste powder and coconut shell as potential additives in concrete production, aiming to enhance its mechanical and physical properties. By replacing 20% of coarse aggregate with coconut shell and varying the proportion of marble waste powder as replacements for fine aggregate at 25%, 50%, 75%, and 100%, a series of experimental mixes were formulated. Ordinary Portland cement of grade 53 served as the binding agent. Results indicated significant improvements in various engineering properties of the concrete, particularly in cube compressive strength, split tensile strength, and flexural strength. The study underscores the economic and ecological viability of incorporating these waste materials, highlighting their role in augmenting concrete performance while reducing environmental impact. This research contributes to advancing sustainable practices within the construction industry by optimizing material usage and enhancing concrete properties through innovative means. Key Words: Marble waste powder (MWP), Coconut shell (CS), Concrete.
The Role of Friction in Athletic Performance: A Descriptive Analysis
Authors:   Assistant Professor of Physics & Harda Degree College, Harda (M.P), Tiwari Ashish
Published: April 2024

Friction is a fundamental force that has a substantial impact on athletic performance across all sports disciplines. This descriptive research investigates the varied impact of friction in building athletic skill. This study looks at how friction affects running, jumping, throwing, and other sports activities by examining static and kinetic frictional forces, as well as elements that influence frictional interactions. The research examines the interaction of athletes, footwear, surfaces, and equipment to explain how friction governs propulsion, stability, and efficiency in sports activity. The findings of this study have important significance for players, coaches, and sports scientists, as they provide avenues for optimizing training techniques, equipment design, and performance tactics for increased athletic achievement. Keywords Friction , Athletic Performance , Role , Descriptive Analysis , Surface Friction , Footwear Friction , Sports Science , Biomechanics , Performance Optimization , Surface Interaction , Traction , Stability , Movement Efficiency , Injury Prevention ,Training Strategies
A study on Optimizing supply chain management to ensure efficient delivery of salon products and equipment to all locations in Groom India salon and spa private limited
Authors:   Dr. Joyce R, Associate Professor, Sathyabama Institute of Science and Technology, Chennai., R Ms. AKILA
Published: April 2024

This study aims to optimize the supply chain management of Groom India Salon and Spa Private Limited to ensure efficient delivery of salon products and equipment to all its locations. The research will begin by evaluating the current end-to-end supply chain processes, identifying bottlenecks, and exploring digital solutions for real-time tracking and inventory management. By implementing software tools to enhance visibility and coordination, the study seeks to reduce delivery lead times, achieve cost savings through optimized inventory levels, and improve customer satisfaction and loyalty. The methodology will involve a combination of qualitative and quantitative analysis, including interviews with key stakeholders, data collection on current processes and performance metrics, and simulation modelling to test various optimization scenarios. The study aims to provide actionable insights and recommendations for enhancing the supply chain management of Groom India Salon and Spa Private Limited, ultimately contributing to its overall operational efficiency and customer service excellence.
RAINFALL PREDICTION USING MACHINE LEARNING
Authors:   Student, Department of Computer Science and Engineering, Tirumala Engineering College, Devi Kanasani Renuka
Published: April 2024

- India is an agricultural country and its economy is largely based upon crop productivity and rainfall. For analyzing the crop productivity, rainfall prediction is require and necessary to all farmers. Rainfall Prediction is the application of science and technology to predict the state of the atmosphere. It is important to exactly determine the rainfall for effective use of water resources, crop productivity and pre planning of water structures. Using different data mining techniques it can predict rainfall. Data mining techniques are used to estimate the rainfall numerically. This paper focuses some of the popular data mining algorithms for rainfall prediction. Random Forest, K-Nearest Neighbor algorithm, Logistic regression, Decision Tree are some of the algorithms have been used. From that comparison, it can analyze which method gives better accuracy for rainfall prediction. Key Words: Rain fall, Agricultural, Economy , Farmers, Water resources.
Deepfake Face Detection Using Machine Learning with LSTM
Authors:   Tirumala Engineering College,  Narasaraopet, India, Samkeerthana Pasam
Published: April 2024

Deep fake videos, which employ artificial intelligence to manipulate and generate highly convincing fake content, have emerged as a significant threat to society, potentially undermining trust in visual media. Detecting these deceptive videos is outmost importance to combat the spread of misinformation and protect the integrity of digital media. In this study, we propose a novel approach for deep fake face video detection utilizing Long Short-Term Memory (LSTM) networks, a type of Recurrent Neural Network (RNN). Our approach capitalizes on the temporal patterns and context within video sequences, harnessing the unique strengths of LSTM in capturing sequential information. We demonstrate the effectiveness of our methodology by training the LSTM network on a diverse dataset comprising both real and deep fake videos. The network’s ability to learn temporal dependencies and identify inconsistencies in facial expressions, eye movements, and other subtle cues allows it to distinguish between genuine and manipulated content. To further enhance the accuracy and robustness of our deep fake face detection system, we integrate pre-processing techniques for frame- level analysis, such as optical flow computation and facial landmarks extraction. Additionally, we employ a comprehensive ensemble of LSTM models and other machine learning algorithms to improve the overall detection performance. In our experiments, we evaluate the LSTM-based deep fake detection system on a large-scale dataset of both known and unseen deep fake videos, achieving high detection accuracy and low false positive rates. We also compare our approach with existing methods, demonstrating its superiority in terms of robustness and generalization. The results of this study signify the potential of LSTM-based models for mitigating the adverse effects of deep fake content on society. As deep fake technology continues to evolve, our approach showcases a promising step towards combating the dissemination of deceptive multimedia, promoting media integrity, and upholding trust in visual information. Keywords: LSTM Networks, Recurrent Neural Network, Optical flow computation, Facial landmarks extraction, False positive rates.
A Python - Powered Keylogger Detection Tool
Authors:   TIRUMALA ENGINEERING COLLEGE, J . LAKSHMI
Published: April 2024

Keyloggers are a prevalent threat that record users' keystrokes to steal credentials and sensitive data. This paper presents a Python-based keylogger detection tool that scans running processes and checks them against indicators of compromise (IOCs). The detector integrates process inspection, signature matching, and automated remediation functions. A graphical user interface allows easy operation and threat response. The tool was tested against known keyloggers and demonstrated effective discovery with minimal false positives. This demonstrates Python's capabilities for building specialized security automation scripts to fill gaps in traditional anti- malware. The detector provides a straightforward yet extensible approach for defending against keylogging threats.
RFID AND GSM BASED ATTENDANCE SYSTEM
Authors:   Electrical Engineering and Shri Siddheshwar Women’s polytechnic, solapur, K.M. Ms. Kamble
Published: April 2024

We have developed a quick and simple solution to the challenge of tracking every student's presence in a class by using radio frequency identification (RFID) to control student attendance with little to no teacher intervention.This project is to use radio frequency identification (RFID) technology to streamline the attendance recording system. A web-based application called RFID based Attendance recorder with SMS alert system will be created to address the aforementioned issue. Database support and GSM (Global System for Mobile communication) technologies will be used in the development of the system. As a result, in addition to tracking students' attendance, the system notifies the students' parents by SMS when they are present or not. Key Words: Monitoring, Tracking, attendance, RFID
Health Benefits and uses of Neem Leaves
Authors:   M.Sc. (Final) Analytical chemistry, MVR Degree and PG College, Visakhapatnam, M . Lavanya
Published: April 2024

Neem is a very unique tree and neem leaves are the most complex leaves on the planet. The neem tree has over 130 different biologically active compounds, and the neem leaf is one of the most complex leaves you can find on the planet. According to the ancient science of Ayurveda texts describe how neem treats skin disorders, hair problems, enhances appetite, boosts digestion, kindles the fire in the belly, improves breathing, helps manage diabetic conditions, aids healing of wounds and relieves nausea. Neem has been declared the “tree of the 21st century” by the United Nations. The US National academy of science also recognized neem’s medicinal value in its 1992 report entitled “Neem: A tree for solving global problems.” Keywords: Biologically active, Azadirachta indica, Diabetes, Hypertension, Metabolic syndrome, Neem.
DRUGS IN SPORTS AND RIGHT TO HEALTH: AN INDIAN PERSPECTIVE
Authors:   M.Sc. (Final) Analytical chemistry, MVR Degree and PG College, Visakhapatnam, Choudhary, Dr. Anju
Published: April 2024

Despite India's best efforts, the country has been ranked third on the global doping charts for the past three years running, starting in 2019. Rules and regulations for elite sports must be logically formulated and applied fairly across countries. Doping regulations in India have been the subject of much discussion, drawing attention to the disarray in the country's sports administration. Images of syringes in stadium restrooms have been ubiquitous for decades. Competitions in remote regions of India don't have anti-doping officers present, and if they were, the number of people who fail tests would be far higher. Even if professional athletes have gotten away with doping in the past, amateurs at all levels are putting their health at danger by trying it out in the hopes of landing a job or making the national team.[1] Aiming to promote clean sport, the World Anti-Doping Agency has created and is implementing harmonised regulations under the “World Anti-Doping Code, 2021”. The anti-doping experience varies from country to country because WADA depends mostly on National Anti-Doping Organizations to execute the Code. The existing framework, according to some academics, has an outsized effect on athletes hailing from underdeveloped nations. By examining fundamental problems with the Code's implementation in one such country—India—this essay adds to this discussion. [1] Yuji Takazawa, 'Relationship Between the Level of Willingness to Learn About Anti-Doping and Objective Knowledge Among Japanese University Athletes: A Cross-Sectional Study' (2022) 4 FRONTIERS IN SPORTS AND ACTIVE LIVING 54-68.
Immutable Identity Validation Using Soul bound Token Abhishek Sharma,
Authors:   Galgotias University, Singh, Aditi
Published: April 2024

The "Immutable Identity Validation System: A Blockchain and Soulbound Token Approach" paper introduces an innovative method for verifying digital identities. By combining blockchain technology and Soulbound Tokens (SBTs), it enhances security and privacy in identity verification processes. SBTs, designed as non-transferable and tamper-proof digital assets, play a crucial role in bolstering the security and reliability of the system. Their unique properties ensure that user privacy is prioritized while also facilitating swift verification through blockchain transparency. This approach addresses the growing demand for robust identity verification solutions, particularly in sectors like education and corporations, where fraud prevention and streamlined processes are critical. The methodology involves various steps, including SBT generation, blockchain integration, user control mechanisms, and stringent security measures. Both frontend and backend development, along with the integration of blockchain using tools like Ganache and decentralized data storage through IPFS, contribute to building a secure and user-friendly system. Thorough testing, documentation, and knowledge transfer are essential to ensuring the system's reliability, security, and compliance with legal standards. Ultimately, the goal is to establish a globally accepted framework for identity verification in today's interconnected digital landscape. Keywords:; privacy; security; Blockchain; Cryptography; Decentralization; Soul Bound Token (SBT), distributed ledger.
Influence of Indian Directors on Popular Culture and Societal Views: A Comprehensive Study
Authors:   Journalism and Mass Communication Student, Amity University Uttar Pradesh, India, Kumari, Miss Priya
Published: April 2024

This study investigates the global impact of Indian cinema, focusing on the works of notable directors such as Sanjay Leela Bhansali, Rajamouli, Imtiaz Ali, Anurag Basu, and Anurag Kashyap. The study examines Indian cinema's rich cultural past and its power to alter societal views, influence popular culture, and promote inclusivity and diversity through an interdisciplinary viewpoint. Using a combination of qualitative analysis and case studies, including notable films such as Bhansali's "Padmavat," Rajamouli's "Baahubali" series, Ali's "Jab We Met," Basu's "Barfi!," and Kashyap's "Gangs of Wasseypur," the research examines the narrative techniques and thematic content employed by these directors to challenge stereotypes and promote unity among diverse communities. It also looks into the reception and cultural relevance of these films, both domestically and abroad, emphasising their role in promoting cross-cultural dialogue and understanding. This study seeks to shed light on the changing dynamics of cultural representation, diversity, and global influence in the film industry by contextualising these directors' contributions within the larger landscape of Indian cinema. Keywords: Popular Culture, Inclusivity, Diversity, Naaratives
BUILDING A MOUSE BY EYEBALL MOVEMENT USING MACHINE LEARINING
Authors:   Student, Department of Computer Science and Engineering, Tirumala Engineering College, Pujitha Muppalla
Published: April 2024

An individual Human computer interference system is being introduced. In olden times, as an input device the mouse and keyboard were used by human computer interference system. Those people who are suffering from certain disease or illness cannot be able to operate computers. The idea of controlling the computers with the eyes will serve a great use for handicapped and disabled person. Also this type of control will eliminate the help required by other person to handle the computer. This measure will be the most useful for the person who is without hands through which they can operate with the help of their eye movements. The movement of the cursor is directly associated with the center of the pupil. Implementing a controlling system in it enables them to move without the help of another person is very helpful. First detect pupil center position of eye. Then the different variation on pupil position different command set for virtual keyboard. The signals pass the driver to interface with virtual keyboard itself. The driver will control both speed and direction to enable virtual keyboard to move forward, left, right and stop. Key Words: Human computer interference, Keyboard, Mouse, Eye, Cursor, pupil.
CLASSIFICATION OF WBC USING CONVOLUTION NEURAL NETWORKS
Authors:   Dept. of Information Science and Engineering, JNNCE, Shimoga, India, L Prof.Prathima
Published: April 2024

Leukocytes, developed within the cartilage of the bone, account for barely 1% of the overall blood cell counts. Erratic flourishing of leukocytes induces an outbreak of blood cancer. Amongst three of the diverse sorts of cancer in blood, the suggested ponder provides a vigorous instrument for the sorting of subtypes of leukemia and multiple myeloma, utilizing the related dataset. White blood cells with leukemia are not normal that grow throughout cells present in the red blood. WBCs, and platelets and affect the blood and bone marrow. Whereas, multiple myeloma is a different type of cancer that affects plasma cells. It develops in the bone marrow instead of the blood stream. The suggested method uses a deep learning technology called as convolutional neural networks to lessen the likelihood of errors occurring during the human method. The model first extracts the leading highlights from the cell imaging by pre-processing it. Next, the model will be prepared using CNN, and lastly, the cancer type can be predicted. Furthermore, the model's accuracy of 97.33% is higher than Yolov8's and Naive Bayes. Keywords: Acute Lymphoblastic Leukemia (ALL), Acute Myelogenous Leukemia (AML), Chronic Lymphocytic Leukemia (CLL), Chronic Myelocytic Leukemia (CML), Multiple Myeloma (MM), Deep Learning, CNN
PROPOSED BY DISPOSAL OF MUNCIPAL SOLID WASTE BY BIO METHANATION IN GADHINGLAJ CITY
Authors:   DR. A. D. SHINDE COLLEGE OF ENGINEERING. Bhadgaon, Gadhinglaj. Dist: Kolhapur Pin: 416502  Department of Civil Engineering, D.S. Prof.KHORATE
Published: April 2024

In India Bio-Methanation in conventional biogas plant have been proposed as one of the appropriate alternative sources of energy which can counter the escalating demand of fossil fuels. In India large quantity of waste generates produce per day and hence the noof biogas installation of biogas plant is increasing rapidly and the trend is expected to continue at least for the foreseeable future. Biogas plant like many other energy generating technologies is not free from environmental problem. Biogas production requires anaerobic digestion. The biogas plant creates an organic processing facility to create biogas which will be more cost effective, eco friendly, cut down on landfill waste, generate a high quality renewable fuel and reduce Carbon Dioxide and Methane emission. The anaerobic digestion of kitchen waste produces biogas, which primarily consist of methane (CH4 ) and Carbon Dioxide (CO2). Biogas can be used as energy source and also for numerous purposes. But any possible application requires knowledge and information about composition and quantity of constituent in the biogas produced.
FACIAL EXPRESSION DETECTION USING DEEP LEARNING
Authors:   Professor, Department of Computer Science and Engineering, Tirumala Engineering College, Krishna Dr. N. Gopala
Published: April 2024

The use of machines to perform different tasks is constantly increasing in society. Providing machines with perception can lead them to perform a great variety of tasks, even very complex ones such as elderly care. Machine requires that machines understand about their environment and interlocutor’s intention. Recognizing facial emotions might help in this regard. During the development of this work, deep learning techniques have been used over images displaying the following facial emotions : happiness, sadness, anger, surprise, disgust, and fear. As results, such method best resolves issues of lighting variations and different orientation of object in the image and thus achieves a higher accuracy.In the field of education online learning plays a vital role.. The fundamental problem facing in the online learning environment is the low engagement of Listener to the Preceptor. The educational institutions and Preceptors are responsible to guarantee best learning environment with maximum engagement in educational activities for online learners. Key Words: Environment, interlocutor, happiness, sadness, anger, surprise, listener, educational.
Social Media WebApp “TweetSphere”
Authors: kumar, Ritesh
Published: April 2024

The paper presents a novel approach to addressing the challenges of multiuser operations in Twitter by focusing on the expense of queries and the existing solutions for data partitioning. It introduces a method for reducing server interaction by partitioning data based on user interactions and implementing selective replication for frequently requested user data. This approach significantly improves partition quality, especially with low replication ratios. Additionally, the paper delves into the issue of Twitter spammers and their evolving tactics, proposing new detection features to combat spam accounts. It also explores the detection of duplicate fake accounts on Twitter using feature based analysis and machine learning techniques, with SVM demonstrating the best performance at 93.3% accuracy
Vastradarpana A Novel Method to Detect Saree Using Image Processing Techniques
Authors:   Student, Information Science & Engineering  Dayananda Sagar college of Engineering, Bengaluru, BS Yogesh
Published: April 2024

Identifying authenticated sarees through human vision and feel is a challenging aspect. Secondly Saree industry is multibillion businesses in Indian Industry. Each silk saree cost range from Rs 10000 to Rs 500000. Every consumer tries to identify authenticated saree before purchasing. With today’s technology changes we have prepared novel approach to detect the authentication of the saree. This work offers a method for classifying and detecting saree types using computer vision techniques. The visual features of sarees are classified by machine learning and image processing; preprocessing improves the classification model. With the use of region based CNNs (RCNN) extract texture features that are essential for differentiating Kanchivaram Silk Sarees. The model ensures stability across datasets and training conditions, as demonstrated by experimental findings that show its improved accuracy and speed over traditional deep learning techniques. This research increases computer vision in apparel recognition and categorization with applications in e-commerce and fashion recommendation. Keywords-Sarees, Kanchivaram, Rcnn, Tensorflow