Journal of Analysis and Computation
Journal of Analysis and Computation
FITNESS SOCIAL MEDIA SOFTWARE SYSTEM
Geerija Lavania1, Shruti Arya2, Neelkamal Choudhary3, Amit Bohra4
1-3Assistant Professor, JECRC Foundation, Jaipur,India
4Assistant Professor, Global institute of Technology, Jaipur, India
Keywords – Parentropranour, Accuracy, Social media and Reliability.
DOI – 10.30696/JAC.XVII.1.2023.1-7
ABSTRACT
Parentropranour is a recently launched Fitness social media software system. As its influence continues to grow, there is increasing interest in understanding its impact on society and individuals. This paper reviews current research on the effects of Parentropranour, focusing on its influence on fitness, communication, self-esteem, mental health, and marketing. The findings highlight both positive and negative points, and point to the need for further research to fully understand the complexities of its use. The study also explores the role of these platforms in shaping fitness trends, influencing user behavior, and enhancing overall well-being.
A STUDY OF BLOCKCHAIN BASED SOLUTION FOR KYC VERIFICATION
Anima Sharma1, Dr. Manju Vyas2, Deepika Bansal3 and Mr. Gajendar Sharma4
Department of AI & DS1,2 , Department of IT3, Department of CSE4,
JECRC, Jaipur, India.
Keywords – Blockchain, KYC, SHA-1, SHA-2
DOI – 10.30696/JAC.XVII.1.2023.17-23
ABSTRACT
In the today’s world of digitization, it’s very important to identify the individual, in order to prevent the fake transaction, like sim card issue, bank loan disbursement and more. We need to go through KYC verification in banks and other related organization for updating our data and verifying our identity. Blockchain permits the secure transfer of KYC verification stamp from one entity to another. It offers a highly immutable and detailed audit trail on all actions on KYC files. The problem which the digitization is the duplicity, that single platform is not used by the organizations banking or other for the purpose of KYC of customer, so the blockchain based platform act as a single solution for the KYC related needs or requirement. This paper summarizes and analyses the related work which is applied in the field and further proposes an algorithm which uses a 2 step process for the implementation of digitization of the process.
ANALYZING THE EFFECTIVENESS OF MACHINE LEARNING ALGORITHMS FOR SOFTWARE FAULT PREDICTION
Jayanti Goyal¹ and Dr. Ripu Ranjan Sinha²
1Research Scholar, Department of Computer Science, Rajasthan Technical University (RTU) Kota India
2Professor, Department of Computer Science, SS Jain Subodh PG College, Research Center Rajasthan
Technical University (RTU) Kota India
Keywords – Machine learning, Software fault prediction, Algorithm.
DOI – 10.30696/JAC.XVII.1.2023.9-16
ABSTRACT
Software fault prediction is a critical task in software engineering that aims to identify and prevent faults in software code before they occur. Machine learning algorithms have been shown to be effective in this area, providing accurate and timely predictions of software faults. In this research paper, we examine the effectiveness of different machine learning algorithms for software fault prediction using publicly available datasets. We compare the performance of four popular machine learning algorithms, namely support vector machines (SVM), random forests (RF), k-nearest neighbors (KNN), and Naïve Bayes (NB), using various metrics such as accuracy, precision, recall, and F1-score. We also perform feature selection to identify the most relevant features for each algorithm. In conclusion, our research highlights the effectiveness of machine learning algorithms for software fault prediction and provides insights into the most suitable algorithm for specific datasets. By leveraging the power of machine learning algorithms, software developers can effectively predict and prevent software faults. These findings provide a reference point that can be used to evaluate the effectiveness and advancements of any novel approaches in software defect prediction.
ENSEMBLE MACHINE LEARNING AND SOFTWARE DEVELOPMENT EFFORT ESTIMATION
Rajani Kumari Gora¹ and Dr. Ripu Ranjan Sinha²
¹Research Scholar, Rajasthan Technical University, Kota, India
²Professor, S. S. Jain Subodh College, Jaipur, Research Centre, RTU, Kota, India
Keywords – Software Effort Estimation, Ensemble, Machine Learning.
DOI – 10.30696/JAC.XVII.1.2023.41-46
ABSTRACT
Effort estimation is a crucial component of software development that aids in re-source allocation and planning for project managers. While faulty estimation can lead to cost overruns and project failure, an accurate estimation can stop project delays and overruns. Increasingly used in recent years for software development effort estimation, ensemble approaches combine numerous models to increase pre-diction accuracy and stability. This study investigates various ensemble learning approaches and assesses how well they work on a dataset of actual software projects. The findings demonstrate that ensembles perform better than single models and can estimate effort with high accuracy. This work also offers insights into the parameters, such as the diversity of models and the quality of input information, that influence the performance of ensemble approaches. The results indicate that ensemble approaches, which can be implemented using a variety of techniques like bagging, boosting, and stacking, can be a feasible strategy for enhancing software development effort estimation. However, the success of these methods depends on the careful selection of models and characteristics.
ON CERTAIN INVESTIGATION OF PRODUCT OF SPECIAL FUNCTION USING FRACTIONAL CALCULUS
Vishal Saxena¹, Manoj Pathak² and Pradeep Kumar Sharma³
Keywords – Mellin Barnes Contour Intrgrals, Fractional Operators.
DOI – 10.30696/JAC.XVII.1.2023.25-40
ABSTRACT
The paper is devoted to study the generalized fractional calculus of arbitrary complex order for the H – function defined by Inayat Hussain [8]. The classical fractional integrals and derivatives of Riemann-Liouville type are treated. The considered generalized fractional integration and differentiation operators contain the Gauss Hypergeometric function as a kernel and generalize classical Riemann-Liouville, Erdelyi-Kober types ones. It is proved that the generalized fractional integrals and derivatives of H – function turn also out H -functions but of greater order. Especially, the obtained results define more precise and general ones than known. Corresponding assertion for Riemann-Liouville and Erdelyi-Kober fractional integral operators are also presented.
INTEGRATION OF AZURE COGNITIVE SEARCH WITH POWER APPS FOR ENHANCED DATA DISCOVERY AND USER EXPERIENCE
1Dr. Kashish Parwani, 2Sandeep Das, 3Sarvam Mittal, 4Rahul Raj
1Associate Professor, JECRC Jaipur, India
2Associate Consultant, Infosys, 3Associate Consultant, Infosys, 4System Engineer, Infosys, India
Keywords – Azure Cognitive Search, Power Apps, Query Processing, User Interface (UI) Design, Data Visualization, Data Indexing, Information Retrieval.
DOI – 10.30696/JAC.XVII.1.2023.47-53
ABSTRACT
This research paper explores the integration of Azure Cognitive Search with Power Apps to enhance data discovery and user experience. By leveraging advanced search capabilities, natural language processing, and machine learning algorithms, researchers and developers can enable intelligent data exploration within Power Apps. The paper investigates the technical aspects of the integration, examines benefits and challenges, and showcases real-world use cases. Considerations such as data security and scalability are addressed. The findings provide insights for organizations seeking to optimize data discovery and improve user engagement through the combination of Azure Cognitive Search and Power Apps.
ENHANCING INFORMATION RETRIEVAL IN AZURE COGNITIVE SEARCH
Dr. Kashish Parwani1, Sandeep Das2, Sarvam Mittal3, Rahul Raj4
1Associate Professor,JECRC Jaipur,India
2Associate Consultant, Infosys, 3Associate Consultant,Infosys, 4System Engineer, Infosys, India
Keywords – Cognitive Search, Information Retrieval, Natural language processing, Keyword-based search, Context-aware search, Semantic analysis.
DOI – 10.30696/JAC.XVII.1.2023.55-64
ABSTRACT
This paper explores the use of cognitive search in improving information retrieval for national paper publication. By leveraging artificial intelligence and natural language processing techniques, cognitive search systems enhance keyword-based search engines by understanding user queries holistically, extracting relevant concepts, and providing personalized recommendations. We discuss the specific requirements and challenges faced by researchers in the publication process, highlight successful case studies, and emphasize the need for continued innovation in this field.
SPECIFICATION FOR PRESERVING THE SECURITY AND PRIVACY OF THE CHAT APPLICATION
B.Umamaheswari, Priyanka Mitra, Anju Rajput, Somya Agrawal
Assistant Professor, Jaipur Engineering College and Research Centre, Jaipur, India
Keywords – Secure chat application, Security, Android, Secure session, Secure storage.
DOI – 10.30696/JAC.XVII.1.2023.91-99
ABSTRACT
One of the most significant and well-liked smartphone applications today is chat. It allows for the free sharing of text messages, photographs, and files, making it possible for users to stay in touch. Every message needs to be secure. The purpose of the study is to suggest a chat application that offers End-to-End security and enables secure data flow between users without concern. In addition to storage’s protection. This article presents a list of specifications for a secure chat application, and the program was created in accordance with these specifications. Based on those requirements, the suggested chat application was compared to other well-known programs and tested as evidence for delivering End-to-End security.
GOLDEN RATIO AND FACIAL BEAUTY WITH COMPUTER VISION
Devansh Bhatnagar¹, Dr. Tripati Gupta²
¹Jaipur Engineering College and Research Centre, Jaipur, Rajasthan, India
²Associate Professor, Department of Mathematics, Jaipur Engineering College and Research Centre, Jaipur, Rajasthan, India
Keywords – Golden Ratio, Computer Vision.
DOI – 10.30696/JAC.XVII.1.2023.83-90
ABSTRACT
Beauty is a controversial topic in itself. Beauty differs subjectively but in terms of Maths, beautiful things have one common factor, i.e. Golden Ratio. The golden ratio is quite intriguing as it provides solution of many difficult problems like the Tammes problem, etc. As studies show, the golden ratio is also found in some of the most symmetrical and beautiful faces. This paper discusses the concept of the golden ratio in
human faces with the help of modern technology.
PERFORMANCE ENHANCEMENT OF CLOUD SECURITY USING HOMOMORPHIC AUTHENTICATION APPROACH
Shreekant Sharma and Dr.Abid Hussain
Research Scholar, School of Computer Applications and Technology, Career Point University, Kota, Rajasthan, India
Keywords – Paillier Homomorphic Cryptography, Hadoop, Cloud Audit.
DOI – 10.30696/JAC.XVII.1.2023.65-74
ABSTRACT
The most dynamic and exciting area in the service delivery industry is cloud computing. Implementing security in the Cloud is currently very popular. As a result of the expansion of the Cloud environment, security limitations on users and service providers are growing. The goal of this study is to propose a more effective method of data integrity verification, “Cloud Audit.” Our method is based on a homomorphic tag and combinatorial batch code version of the Paillier homomorphic encryption system. To achieve homomorphic encryption on data blocks, use a Paillier Homomorphic Cryptography (PHC) system enabling us to launch data processes on this block. In order to allocate and store integral data into various distributed cloud servers, combinatorial batch codes are used. We have developed a Hadoop and Map Reduce-based programme to illustrate our methodology. We have evaluated this submission using a number of criteria. The results of the experiments have demonstrated the efficacy of the suggested technique. Our approach has significantly outperformed other contemporary approaches.
OPTIMIZATION MODEL FOR MIXTURE CONTENTS IN COMPOUND WITH LPP MODEL
Sonu Kumar¹, Govind Shay Sharma², Sunil Kumar Srivastava³
1.,2Department of Mathematics, Vivekananda Global University, Jaipur, Rajasthan, India,
3Department of Mathematics, Jaipur Engineering College And Research Center, Jaipur, Rajasthan, India
Keywords – Algorithm, productivity, feasible, Gradient, Optimization, Vitamin, Cost, Minimization.
DOI – 10.30696/JAC.XVII.1.2023.75-81
ABSTRACT
The concepts of linear and non-linear programming are used for solve the optimization problems. The paper will discuss the linear programming method and then convert problem in quadratic to find the minimize function. We will discuss the modeling of the cost minimize function for a Pharmacy company which can also apply to another manufacturing unit, where the products are based on some conditions. The paper will present the comparative result with both linear and converted non-linear programming method.
A STUDY OF LI-ION BATTERIES AS AN APPLICATION IN ELECTRIC VEHICLE
Dharmesh Singhal1, Dr.Tripti Gupta2, Dr.Manoj Pathak3, Chinmay Mahawar4
1Jaipur Engineering College and Research Centre, Jaipur, Rajasthan, India
2Associate Professor, Department of Mathematics, Jaipur Engineering College and Research Centre, Jaipur, Rajasthan, India
Keywords – Power generation, Lithium-ion batteries, Electric vehicles.
DOI – 10.30696/JAC.XVII.1.2023.101-106
ABSTRACT
Lion Battery (Lithium-Oxygen or Lithium-Air) are the powerhouse for the digital electronic revolution in this modern mobile society that have gained significant attention in recent years due to its high energy density, longer lifespan, and improved safety compared to traditional methods of power generation. Lithium-ion batteries have become the focus of research interest especially for advancement and enhancement of application in the field of electric vehicles (EVs). This review paper provides an in-depth analysis of Lion Battery technology, basic concepts, including its working principles, current advancements, recent progress, challenges, and future directions especially in the field of Electric vehicles (EVs).
A REVIEW STUDY OF LITHIUM – SULFER BATTRIES FOR THE FUTURE ENERGY ASPECTS
Dharmesh Singhal1, Manoj Pathak2, S. K. Dixit3, U.K.Pareek4
1234Jaipur Engineering College and Research Centre, Jaipur, Rajasthan, India
Keywords – Lithium-sulfur battery, Lithium polysulfide, Cathode, Sulfur.
DOI – 10.30696/JAC.XVII.1.2023.199-205
ABSTRACT
Lithium-sulfur (Li-S) batteries have garnered significant attention in recent years due to their high theoretical energy density, low cost, and abundance of sulfur resources. An increasing amount of research has been conducted on Li-S batteries over the past decade to develop fundamental understanding, modelling, and application-based control. However, there are still some challenges impeding Li-S battery from practical application, such as the shuttle effect of lithium-polysulfide (LiPSs), the growth of lithium dendritic, and the potential leakage risk of liquid electrolytes. This review focuses on the most crucial issues of solid-state Li-S battery, recent advancements in Li-S battery technology. capacity fading, low sulfur utilization, polysulfide shuttling, and safety concerns associated with Li-S batteries It will be also presented that by preparing cathode of Li-S battery with suitable materials and morphological structure, high-performance LSB can be obtained.
IMPACT OF DIGITALIZATION ON EDUCATION WITH REFERENCE TO INDIA
Ms. Saguna Chaturvedi1, Dr. Rashmi Kaushik2
¹Associate Professor, JECRC, Jaipur, India
Keywords – Digital Technology globalization English Internet opportunities.
DOI – 10.30696/JAC.XVII.1.2023.207-211
ABSTRACT
Digital age has ushered in a complete new methodology of teaching and learning of English language which was hit hereto unknown to the world. It has opened up new opportunities which could not be visualized earlier.The new techniques of teaching have widened the scope of learning and have made it truly globalized.The virtual classrooms have replaced the traditional one. The first computer was created in England and America and consequently, English has become the main language of the internet . Historical circumstance has again ensured that English is widespread, as it continues to be the corporate language utilized by most companies. We are moving towards an era of globalized world in which English language dominates. Although there are challenges by way of providing cheap internet facilities, upgradation of knowledge, training of existing teachers etc. The future holds innumerable opportunities of development not only in terms of learning but also n terms of business opportunities as well.
SOFT SKILLS: NEED OF THE HOUR
Dr. Sonia Khubchandani1, Pratham Kabra2, Shyam Garg3
1Associate Professor, Jaipur Engineering College and Research Centre, Jaipur, India
2,3Students, Information Technology, Jaipur Engineering College and Research Centre, Jaipur, India
Keywords – Soft Skills, Professionalism, Engineering, Career.
DOI – 10.30696/JAC.XVII.1.2023.1-5
ABSTRACT
While technical expertise is essential, the lack of soft skills can hinder graduates’ ability to effectively communicate, collaborate, and thrive in their careers. Research conducted by the Stanford Institute International in collaboration with the Carnegie Mellon Foundation indicates that nearly 75% of job success relies on people skills, rather than technical skills alone. Employers increasingly prioritize candidates with strong interpersonal abilities, as evidenced by a LinkedIn survey where 57% of employers believed that graduates with good interpersonal skills have better long-term career prospects.
The NASSCOM report highlights that 75% of engineers are deemed unemployable due to a focus on academic knowledge without sufficient attention to overall development. This narrow approach has created a culture that produces graduates lacking well-rounded skills, resembling the manufacturing of “robots” rather than nurturing individuals with diverse talents. The National Society of Professional Engineers (NSPE) stresses the evolving role of engineers, emphasizing the need for effective communication, teamwork, and interpersonal skills. Collaborative projects demand engineers who can navigate multidisciplinary teams and complex professional environments. This research paper underscores the importance of soft skills for students and graduates, emphasizing their benefits in career growth, teamwork, problem-solving, and adaptability. By striking a balance between technical expertise and soft skills, graduates can position themselves for long-term success in the dynamic and professional world.
ANALYSIS OF TRADITIONAL AND TECHNICAL TOOLS FOR ELT
Dr.Soniakhubchandani1, Pratham Kabra2
Associate Professor Jaipur Engineering College and Research Centre Jaipur, Rajsthan, India
Student at Jaipur Engineering College and Research Centre Jaipur, Rajsthan, India
Keywords – Log Analysis, Teaching, Result oriented, Traditional, Innovative.
DOI – 10.30696/JAC.XVII.1.2023.221-223
ABSTRACT
In ELT teaching plays an important role as it is lifelong learning , In this paper how traditional and innovative pedagogies tools play important role and the pedagogies in traditional time that is chalk and talk method which is now swapped by smart board and projectors and what not, this paper has tried to analyze that what techniques can be use to make teaching training more fruitful for the students by meeting the time of the hour , Focus on the innovative strategies for teaching and training has been analyzed in this paper to create a line of demarcation that how innovative ways should be use to make classroom teaching interesting and result oriented, irrespective of the fact that traditional way has its own importance but then going hand to hand making it more result oriented as needed by the young youth trend of using digital along with innovative techniques has swapped the old classroom teaching.
ADOLESCENT PREGNANCY: THE PREVALENCE, RISK FACTORS, AND MATERNAL-NEONATAL OUTCOMES: A COMPREHENSIVE REVIEW
Dr. Kanika Mathur
IIHMR University Jaipur, Rajasthan, India
Keywords – Teenage pregnancies, adolescent pregnancies, health risks associated with adolescent pregnancies, adolescent motherhood, and adolescent pregnancies in India.
DOI – 10.30696/JAC.XVII.1.2023.231-238
ABSTRACT
India, a land teeming with over 1.3 billion people, grapples with a pressing health challenge: pregnancies among young adolescent girls. The country harbours the largest adolescent population globally, with a staggering 253 million individuals aged between 10 and 19 years. However, this demographic advantage comes with grave concern. Numerous studies underscore the grave health risks accompanying adolescent pregnancies. These medical complications can have severe consequences for both mother and child, jeopardizing their physical and emotional well-being. The rising trend of teenage pregnancies demands urgent attention and concerted action. It is imperative to prioritize solutions that empower young girls, break the cycle of early marriages, and make them aware of the resources that help them make informed decisions about their reproductive health. The main aim of this review paper is to draw attention to the persistent prevalence of adolescent pregnancies and emphasize the urgent need for the development of effective strategies and policy formulations to advocate for this issue. The objective is to improve the physical and emotional well-being of both adolescent mothers and children affected by teenage pregnancies. Through the study, I have tried to highlight the grave complications of adolescent pregnancies ranging from miscarriages and preterm labour to low birth weight infants, pre-eclampsia, postpartum haemorrhage, sexually transmitted diseases, anaemia, and pregnancy-induced hypertension. Addressing this critical issue necessitates a multi-faceted approach at regional and national levels. Efforts should be directed towards preventing early marriages, promoting education, and empowering women and girls to reduce the prevalence and mitigate the risks involved with adolescent pregnancies.
ADVANCEMENTS IN REINFORCEMENT LEARNING – AN OVERVIEW
Sumedha Sharma1, Tanisha Jain2, Sanidhya Chaturvedi3, Swapnil Saraswat4, Ritvik Sharma5
JAIPUR ENGINEERING COLLEGE AND RESEARCH CENTRE (JECRC) FOUNDATION
Jaipur, Rajasthan, 302004, India
Keywords – Reinforcement learning, sequential decision-making, challenges, transfer learning, real-world problems.
DOI – 10.30696/JAC.XVII.1.2023.263-274
ABSTRACT
In the discipline of machine learning, reinforcement learning (RL) is a well-known study area that focuses on sequential decision-making in dynamic contexts. An extensive overview of reinforcement learning is provided in this publication, covering its key concepts, methodologies, and challenges. RL involves mapping situations to actions to maximize the associated rewards, having an agent discovering the behaviours that result in the greatest rewards through trial and error. Key challenges in RL, such as deriving optimal policies, credit assignment, dealing with complex environments, and temporal correlations, are explored. Additionally, the paper delves into the concept of transfer learning, where knowledge is transferred across related tasks to enhance RL performance. The use of transfer learning in single-agent and multi-agent systems is discussed, highlighting methods like instance transfer, representation transfer, and parameter transfer. This paper provides valuable insights into the foundations of RL and its application in solving real-world problems, offering a basis for further research and advancements in this exciting field.
ENHANCING IMAGE SUPER-RESOLUTION USING DEEP LEARNING AND MATHEMATICAL OPTIMIZATION TECHNIQUES
Kashish Parwani1, Sandeep Das2, Ruchi Mathur3, Sunil Kumar Srivastava4
1,2,3Department of Mathematics of Mathematics JECRC Jaipurr, India,
2Associate Consultant, Infosys, India
Keywords – Image super-resolution, Deep learning, Mathematical optimization, Convolutional neural networks (CNNs), Super-resolution algorithms, Image enhancement, Image reconstruction, Feature extraction, Up sampling techniques, High-resolution imaging, Neural network architectures.
DOI – 10.30696/JAC.XVII.1.2023.239-247
ABSTRACT
This paper explores the use Mathematical models play a crucial role in image processing, offering a powerful framework for analysing, manipulating, and understanding digital images. This abstract emphasizes the significance of mathematical models in image processing and their potential to enhance accuracy and efficiency in this domain. Image processing techniques aim to extract meaningful information from images, enabling applications such as object recognition, medical imaging, and video surveillance. However, raw image data often contain noise, irrelevant details, or complex patterns that hinder accurate interpretation.
A REVIEW PAPER BASED ON ANDROID FOR SMART HOME AUTOMATION SYSTEM
Vijay Nigam1, S. K. Dixit2, U.K.Pareek3, Vishal Saxena4
1Research Scholar, CPU Kota,
2,3,4 Jaipur Engineering College and Research Centre, Jaipur
Keywords – Smart Home Automation, IOT Devices, User Friendly Applications, Android.
DOI – 10.30696/JAC.XVII.1.2023.249-254
ABSTRACT
In this era this is common to access and control you home through remote location, for this we use IOT. IOT stands for Internet of Things. This is use for internet connected device. It is network of all internet connected devices, and these devices easily accessed and controlled by IOT. This feature of IOT is use for smart home automation. Here smart means to manage home IOT devices through speech, command and gesture. We can create centralized system for home automation and also manage devices through remote locations through different technologies. All the technologies i.e. web based or android based are important for IOT.We need more user friendly applications and proper internet connection for this.
SOLUTION OF HEAT EQUATION BY FOURIER-BESSEL TRANSFORM
Dr. Sarita Poonia1, Dr Tripati Gupta2, Dr Ruchi Mathur3
1,2Associate Professor,
3Dean First Year Jaipur Engineering College and Research Centre Jaipur, India
Keywords – Integral transforms, fourier-bessel transform and heat equation.
DOI – 10.30696/JAC.XVII.1.2023.255-261
ABSTRACT
In this paper we have discussed certain boundary value problem of heat the cylindrical shell solve by fourier-bessel transform and also discussed temperature distribution in a cylindrical shell with heat source inside the cylinder. Measuring and finding the distribution and variation is one of the significant purposes of presenting different methods for solving heat equation.
COPPER NANOPARTICLES (CuNPs): SYNTHESIS AND CHARACTERIZATION
Seema Bansal¹, Deepti Chauhan²
¹Assistant Professor, Department of Physics, JECRC College, Jaipur
²Assistant Professor, Department of Physics, Kanoria PG Mahila Mahavidyalaya, Jaipur
Keywords – Copper Nanoparticles (CuNPs), Synthesis, Characterization, Scanning Electron Microscopy Technique, X-ray Diffraction.
DOI – 10.30696/JAC.XVII.1.2023.225-229
ABSTRACT
Nanotechnology is one of the most important and emerging technology these days which deals with understanding and control of matter at nano-scale. As, in the recent years, metal nanoparticles were highly used in diverse areas like in the fields of biology, chemistry and medicine, due to their unique physical, biological and chemical properties. So, now days a number of metal nanoparticles have been synthesised and characterized. There are several methods to make metal nanoparticles, the major techniques being used were chemical methods like chemical reduction, micro-emulsion, electrochemical and biological synthesis. In this context, the present paper, here, discuss, in detail the synthesis of copper nanoparticles by chemical reduction of copper sulphate with sodium hypophosphite in ethylene glycol, in the presence of a polymer surfactant polyvinylpyrrolidone (PVP). PVP was being included to prevent congregation and give dispersion stability to the resulting colloidal nanoparticles. The characterization then has been performed by using X-ray Diffraction (XRD) and Scanning Electron Microscopy (SEM) techniques.
PROSPECTS OF SOFT SKILLS IN THE GLOBALIZED WORLD
Dr. Rashmi Kaushik and Ms. Saguna Chaturvedi
¹Associate Professor, JECRC, Jaipur, India
Keywords – Technology, Professionals, Globalization, Soft Skills.
DOI – 10.30696/JAC.XVII.1.2023.107-113
ABSTRACT
In an increasingly global, technological economy it is not enough to be academically strong. One needs to be more focused for other skills also and soft skill is one them. This paper highlights the prospects of soft skills in this globalized world. It refers to a person’s knowledge and occupational skills. It helps in highlighting an individual’s ability to acquire any job. Soft skills are very important for those professionals who are ready to enter in the professional world.
TO PREDICT THE EFFECTIVE THERMAL CONDUCTIVITY OF NANOFLUIDS FILLED WITH METALLIC NANOPARTICLES CONSIDERING NONLINEAR EFFECT OF VOLUME FRACTION IN SERIES RESISTOR MODEL
Deepti Chauhan¹, Seema Bansal², Sumita Shekhawat³
¹Assistant Professor, Department of Physics, Kanoria PG Mahila Mahavidyalaya, Jaipur
²Assistant Professor, Department of Physics, JECRC College, Jaipur
³Assistant Professor, Department of Physics, Kanoria PG Mahila Mahavidyalaya, Jaipur
Keywords – Effective thermal conductivity, nanolayer thickness, interfacial resistance, effective volume fraction, artificial neural network technique.
DOI – 10.30696/JAC.XVII.1.2023.121-130
ABSTRACT
Nanofluids, a mixture of nanoparticles in base fluids, have drawn keen attention in heat transfer applications due to their high thermal conductivity. Pertinent parameters, like fluid and the nanoparticle thermal conductivity, particle size and volume fraction and many others have shown significant but complex and remarkable effects on thermal performance of nanofluids, which is commonly characterized by the thermal conductivity enhancement. We have here, developed a series-resistor model considering various parameters majorly the impact of nanolayer thickness, size, nanoparticle volume fraction and ratio of particle to fluid thermal conductivity. Artificial neural network (ANN) technique has also been used to evaluate the ETC of nanofluids and then the results have been compared with experimental results present in literature and the results evaluated using ANN technique.
ENVIRONMENTAL IMPACT OF HYDROGEN FUEL
ILHAM JAMIL
B-tech Student, JECRC Foundation, Jaipur, Rajasthan, India
Keywords – Hydrogen, Clean fuel, Environment Friendly.
DOI – 10.30696/JAC.XVII.1.2023.131-134
ABSTRACT
This paper explains the use of hydrogen as a clean energy fuel and critically analyses its environmental impact. Globally there has been an increased focus on climate change among governments, corporates and the general population in recent years. As a result, hydrogen has emerged as a viable alternative to fossil fuels, especially in the automobile sector. The analysis shows that although hydrogen fuel has zero greenhouse gas emissions, the current production of hydrogen fuel isn’t exactly environmentally friendly. The different production processes release varying degrees of greenhouse gases and contribute towards global warming. In order to scale up the usage of hydrogen fuel in automobiles, there is a need for continued research in increasing the efficiency of green hydrogen and reducing the costs associated with its production. The goal of further research should be to minimise the negative impacts of producing hydrogen fuel to turn it into a viable and scalable fuel.
STUDY OF STRUCTURAL & OPTICAL LUMINESCENCE BEHAVIOR OF CdO: Mn SYSTEM FOR ENERGY APPLICATION
Manoj Pathak¹, Pradeep Kumar Sharma², Vishal Saxena³
a,b,cJaipur Engineering College and Research Centre, Jaipur-302022
Keywords – Thin film, Spin coating, Photoluminance, X Ray diffraction, FTIR Spectra.
DOI – 10.30696/JAC.XVII.1.2023.137-149
ABSTRACT
CdO thin films with and without Mn doping were deposited on glass substrates using sol-gel method at room temperature. The effect of Mn content (1,3,5 wt % ) on the optical, structural and morphological properties were studied. X Ray diffraction patterns shows that all the films are single phase and have cubic structure with (200) preferential orientation along c axis. Presence of functional group and chemical bonding as well as the surface changes on the particle determined by the FTIR spectra. Result of optical spectra shows that band gap decreases as increases the 1 at % Mn doping concentration and band gap increases with increasing 3 and 5 at % of Mn concentration. Photoluminance (PL) Spectra shows the broad peak in nearly U-V region with longer wavelength at 342, 343, 342 and 332 nm respectively have been found.
ANN APPROACH BASED STUDY TO PREDICT THE MECHANICAL PROPERTIES OF COPPER POWDER FILLED LLDPE COMPOSITES
Pradeep Kumar Sharma¹ Rajpal Singh² Manoj Pathak¹ & Vishal Saxena³
¹Department of Physics, JECRC College, Jaipur,
²Department of Physics, University of Rajasthan, Jaipur,
³Department of Mathematics, JECRC College, Jaipur
Keywords – Artificial Neural Network, Feed Forward Back Propagation, Training functions, Volume Fraction, Composite Materials.
DOI – 10.30696/JAC.XVII.1.2023.151-169
ABSTRACT
The effective mechanical properties of copper powder filled with linear low-density polyethylene (LLDPE) are studied by using artificial neural network (ANN) approach. It is a form of artificial intelligence, which deal with the function of human brain and nervous system. ANN technique is more important in many fields of engineering and research applications. This report presents the use of ANN technique for the accurate prediction of mechanical properties of copper powder filled LLDPE composites. ANN is based on Feed Forward Back Propagation (FFBP) using three different training functions (TRAINGDA, TRAINGDM, and TRAINGDX). The input parameters manipulated for prediction are Elongation at break, Stress at break, Young’s modulus, volume fraction of the filler and many types of K constants. Copper filled with LLDPE have complex structure which is difficult to predict mechanical properties accurately. This prediction is done using ANN approach. Theoretical model is being compared with experimental data and found that comparison is in good agreement.
APPLICATION OF MATHEMATICS IN MACHINE LEARNING: A REVIEW
Dr. Ruchi Mathur1, Dr Sarita Poonia2, Dr Tripati Gupta3, Ms. Yogita Punjabi4
1Dean First Year, 2,3Associate Professor, 4Assistant Professor, Jaipur Engineering College and Research Centre Jaipur, India
Keywords – Machine Learning, mathematics, algorithms, models, statistics, probability, linear algebra, calculus, optimization.
DOI – 10.30696/JAC.XVII.1.2023.171-175
ABSTRACT
Machine Learning has emerged as a powerful tool for extracting meaningful insights and making predictions from large datasets. Machine Learning Algorithms largely rely on Mathematical Principles for building Models, uncovering patterns, and making accurate predictions. This research paper discusses the role of mathematics in various Machine Learning algorithms and Models. It highlights how various branches of Mathematics work hand in hand to develop useful machine learning algorithms.
CUP SHAPED DUAL BAND MICROSTRIP ANTENNA WITH DGS FOR BIO-TELEMETRY
Sumita Shekhawat1, Deepti Chauhan1, Poonam Tiwari2, Kuldeep S Rathore3 and Deepak Bhatnagar4
1Department of Physics, Kanoria PG Mahila Mahavidyalaya,Rajasthan, Jaipur, India
2Department of Physical Sciences, Banasthali Vidyapith, Banasthali, Rajasthan, India
3Department of Physics, Arya College of Engineering and IT, Rajasthan, Jaipur, India
4Department of Physics, University of Rajasthan, Rajasthan, Jaipur, India
Keywords – Biotelemetry, Planar antenna, ISM (Industrial, Scientific Medical) Band, Body phantom.
DOI – 10.30696/JAC.XVII.1.2023.177-187
ABSTRACT
Advancement of technology in the field of communication has made it possible to send biological information of human body to external intensive care systems and Biotelemetry is one such advance area of research. Being planar patch antennas are finding attention for RF biotelemetry due to their specific properties. In this paper we have proposed a compact cup shaped planar microstrip antenna with dual band performance. The proposed antenna is fabricated and measured. It operates efficiently in ISM, LTE and WLAN band and offers impedance bandwidth of 81.59 %( 1.72-4.1 GHz) in S-band and 17.12% (4.7-5.58 GH) in C-band. The fabricated antenna is also analyzed on body phantom gel and hence performance is optimized to get best possible matching between them. When antenna is measured on phantom gel its bandwidth degraded from 81.58% to 33.47% in S band and in C-band impedance bandwidth decreases from 17.12% to 7.5% but still antenna is covering ISM, LTE and 5.2 GHz Wi-Fi bands used in biotelemetry application.
FEDERATED-BASED APPROACH TO TWITTER SENTIMENT ANALYSIS
Vibhor Bhatt¹, Yogendra Sharma², Tisha Pareek³
Btech student¹, IT Department, JECRC college, jaipur, India
Keywords – Data Analysis, Text Mining, Machine Learning Algorithms, NLP.
DOI – 10.30696/JAC.XVII.1.2023.189-197
ABSTRACT
In this study, there is an investigation on how federated learning can be used to protect data privacy in Twitter sentiment analysis and detect hate speech in tweets. The drawbacks of conventional, centralized learning approaches suggest a federated learning strategy to resolve these problems. Here, it is also a case study that illustrates how the suggested approach works to protect user privacy while maintaining the precision of sentiment analysis.
SYNTHESIS AND CHARACTERIZATION OF SILVER NANOPARTICLES (AgNPs)
Seema Bansal¹, Deepti Chauhan²
¹Assistant Professor, Department of Physics, JECRC College, Jaipur
²Assistant Professor, Department of Physics, Kanoria PG Mahila Mahavidyalaya, Jaipur
Keywords – Silver nanoparticles, chemical reduction method, particle size, X-ray Diffraction (XRD), Transmission Electron Microscope (TEM) and scanning electron microscopy (SEM).
DOI – 10.30696/JAC.XVII.1.2023.115-119
ABSTRACT
A curiosity has been created as we are progressing towards the deep study of species in nano-metric size. Their scale of size and metallic character makes them more and more interesting and useful in various applications like petroleum refining, automotive catalytic converters, etc. They are being used increasingly as catalyst to boost the chemical reactions. The area of silver (Ag) nanoparticles research has also been witnessed tremendous growth due to their unusual chemical and physical properties. Production of Ag nanoparticles can be achieved through different methods like biological method, ion implantation method, and wet chemical method or chemical reduction method. Chemical approaches are one of the most popular methods for the production of nanoparticles. In the present paper, silver nanoparticles have been prepared by reducing the silver nitrate in polyvinylpyrrolidone (PVP) aqueous solution. Glucose was used as reducer and sodium hydroxide to accelerate the reaction. Characterization has also been done and discussed using techniques like X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM) and Transmission Electron Microscope (TEM).
APPLYING DATA MINING TECHNIQUES ON SOIL FERTILITY
PREDICTION
Akanksha Sunil Kadam1, Karan Manohar Gharale2, Nripesh Kumar Nrip3,Dr. Ajay Kumar4
1&2Student, 3Assistant Professor, Bharati Vidyapeeth (Deemed to be University) Institute of Management Kolhapur, Maharashtra, India
4Assistant Professor Bharati Vidyapeeth (Deemed to be University) Institute of Management and Research, New Delhi
Keywords – data mining, classification, regression, Naive Bayes, Soil Fertility, Soil Nutrient.
ABSTRACT
The techniques of data mining are very popular in the area of agriculture. The advancement in Agricultural research has been improved by technical advances in computation, automation, and data mining. Now a days, data mining is being used in a vast areas like healthcare, insurance, marketing, retail, communication, agriculture. The products of data mining system and domain specific data mining application software’s are available for trial made use, but data mining in agricultural on soil datasets is a relatively a young and contemporary research domain. Larger volume of data is harvested along the with the crop harvest in agriculture. Inferring the knowledge from huge volume of data is virtually a difficult task in the current scenario. This research uses the data mining techniques for analysis of soil dataset. This data mining algorithms are used for analysing the soil datasets for classification purposes. The various techniques of data mining are used and compared in this research.
NEWS APPLICATION USING ALAN AI
Aditi Bhalerao¹, Aparna Singh¹, Mugdha Goupale¹, Srushti Vaidya¹, Pinky Gangwani²
¹Students, ²Assistant Professor, Department of Computer Engineering, Cummins College of Engineering for Women, Nagpur, India
Keywords – ALAN AI, Alan studio, React JS, News APIs.
ABSTRACT
Newspaper have been constant source of the news, information and data for us. There are many technological advancements which act as the medium of delivering the news and information through television, radio and many more technical ways. As time is passing innovation and transformation of the technologies are heading forward. One such technology is ALAN AI, there are also many advancements in field of Artificial Intelligence. Developers and researchers are also using these technologies in many fields. In this paper, we have presented a web-based service that is news application using ALAN AI with an interactive voice assistant which gives user a simplified version of application. This helps to the people who have very busy schedule and have difficulty in reading. The main advantage of this application is that it is voice based so it helps to interact with platform by voice commands. The user is able to get news from any topic of interest just by giving the voice commands. The application provides all features required to the user also it allows user to go through news in a very detailed manner by interacting with assistant. The voice assistant allows users not only to stay informed but also keeps updated. The users can access the news by category, terms, by popular news channels. The web application will reduce the amount of human physical work as well as mental efforts which are required by users and will give interesting way of getting news and information. This research paper is an attempt to make news reading more creative and interactive using the ALAN voice assistant.
CAR PRICE PREDICTION IN MACHINE LEARNING
USING PYTHON
Divya Katkar¹, Renuka Vanamala¹, Siddhanti Pampattiwar¹, Pinky Gangwani²
¹Student, Department of Computer Engineering, Cummins College of Engineering for Women, Nagpur, India
²Assistant Professor, Department of Computer Engineering, Cummins College of Engineering for Women, Nagpur, India
Keywords – Car Price Prediction, Machine Learning, Linear Regression, Lasso Regression, Random Forest Regression.
ABSTRACT
This work addresses the problem of car price prediction in Machine Learning; this work is an effort that tries to study and investigate the trends in used car prices and predicts the price of used cars with the help of supervised machine learning algorithms. And to suggest which machine learning algorithm performs well among the selected methods for predicting the cars price. We wanted to study which algorithm predicts the car price more reliably and accurately, So that this solution will be helpful for first time used car buyers and also for sellers for determining the selling cost of the car. For this research work and to predict the prices we have considered different machine learning regression models which are Linear Regression, Lasso Regression and Random Forest Regression. The research objective of this work is to predict used cars prices using machine learning techniques, by collecting data from websites like Kaggle, and analyzing the different aspects and factors that lead to the actual used car price valuation and To enable consumers to know the actual worth of their car or desired car, by simply providing the program with a set of attributes from the desired car to predict the car price. While buying a car it is very important to know its worth, so to make this work easy we may also use other more advanced regression models such as XGBoost Regression and so on for more better results and also we may add large historical data of car price which can help to improve accuracy of the machine learning model.
UNNAT KISAN APPLICATION
Anushtha Sharma¹, Neha Singh¹, Rithika Nethi¹, Radhika Purohit¹, Pinky Gangwani²
¹Student, Department of Computer Engineering, Cummins College of Engineering for Women, Nagpur, India
²Assistant Professor, Department of Computer Engineering, Cummins College of Engineering for Women, Nagpur, India
Keywords – Agriculture, Organic farming, Unnat Kisan, Crops, Soils, Smart Farming.
ABSTRACT
The timely management of crop fields requires constant planning and monitoring because agriculture is a demanding profession. The main goal of our research is to increase awareness of a serious issue that affects farmer life. There is no need to highlight the importance of timely information access for decision-making in agricultural and related areas. There are several prospects for social empowerment and grassroots innovation in developing nations, thanks to the advancement of mobile communication technologies. The right direction and consideration are required while identifying distressing activities such as crop illnesses, pest invasion, assessing soil quality, etc.
TWITTER SENTIMENT ANALYSIS
Sharmishtha Nasery, Saylee Sorte, Sakshi Choudhary, Nirmitee Awachat, Apurva Abale, Supriya Bani
Department of Computer Engineering, Cummins College of Engineering for Women, Nagpur, India
Keywords – Log Analysis, Failure Prediction, Text Mining, Machine Learning Algorithms.
ABSTRACT
Advancement in technology has led to a huge volume of data present in the internet. The Internet has become a platform for online learning, exchanging ideas and sharing opinions. Social networking sites like Twitter, Facebook, Google+ are rapidly gaining popularity as they allow people to share and express their views about topics, have discussions with different communities, or post messages across the world. There has been a lot of work in the field of sentiment analysis of twitter data. This survey focuses mainly on sentiment analysis of twitter data which is helpful to analyze the information in the tweets where opinions are highly unstructured, heterogeneous and are either neutral or negative, or positive in some cases. Twitter Sentiment Analysis helps in applications such as a firm which tries to find out the response of the production of the market , political election prediction and prediction of socioeconomic phenomena like stock exchange. Using various machine learning algorithms like Naive Bayes, Logistic Regression and Support Vector Machine, we have used them for conducting the research.
EXTRACTING USEFUL INFORMATION ABOUT WILDLIFE
SANCTUARIES TO IMPROVE TOURISM
Falguni Gulve¹, Tanmayee Jichkar¹, Swaroop Sakharkar¹, Sakshi Dhone¹, Abhilasha Borkar², Pinky Gangwani²
¹Student, Department of Computer Engineering, Cummins College of Engineering for Women, Nagpur, India
²Assistant Professor, Department of Computer Engineering, Cummins College of Engineering for Women, Nagpur, India
Keywords – wildlife conservation, eco-tourism, maps and navigation.
ABSTRACT
Mobile technology has revolutionized the way we interact with the world around us, and the conservation community has started to embrace this technology to aid in the management and protection of wildlife sanctuaries. This research paper explores the benefits, challenges, and best practices of developing an Android-based app for wildlife sanctuaries. The paper will discuss the potential uses of such an app, including tracking wildlife populations, promoting eco-tourism, and facilitating communication between stakeholders. The challenges associated with app development, including data privacy and ethical concerns, will also be examined. Finally, the paper will provide recommendations for the responsible development and deployment of Android-based apps for wildlife sanctuaries. The app provides a Map navigation feature that can give you directions from your location to your desired sanctuary using Google Maps.