bluuebunny/crossref_metadata_2025 huggingface dataset:
Performance Comparison between VM Based Webserver and Docker Container Webserver
Authors: Anand A. , Nisha Jebaseeli A.
Published: August 2021

Cloud computing is a type of Internet-based computing that provides shared computer processing resources, services and data to computers on demand. It offers an innovative business model for organizations to adopt IT services at a reduced cost with increased reliability and scalability. Virtualisation is one of backbone technology of cloud computing. But today, container based technology especially Docker offering better performance than Virtual Machine. It is famous for its light weight operation and better scaling. But still it is lagging in Disk I/O and network bandwidth intensive applications. So it is important to analyse and compare various performance parameters of VMs and Docker Images before implementation. Main Parameters will be CPU, Memory, Disk Utilization and Network Bandwidth. In this research paper, we compare performance metrics between Webserver deployed in Virtual machine and Docker webserver.
Developing a Fall Detection Technology for Mobility and System Level
Authors: Divya S.
Published: August 2021

Smartphone’s are programmable and embed various sensors; these phones have the potential to change the way how healthcare is delivered. Fall detection is definitely one of the possibilities. Injuries due to falls are dangerous, especially for elderly people, diminishing the quality of life or even resulting in death. This study presents the implementation of a fall detection prototype for the Android-based platform. The proposed system has three components: sensing the accelerometer data from the mobile embedded sensors, learning the relationship between the fall behavior and the collected data, and alerting preconfigured contacts through message while detecting fall. We adopt different fall detection algorithms and conduct various experiments to evaluate performance. The results show that the proposed system can recognize the fall from human activities, such as sitting, walking and standing, with 72.22% sensitivity and 73.78% specificity. The experiment also investigates the impact of different locations where the phone attached. In addition, this study further analyzes the trade-off between sensitivity and specificity and discusses the additional powers consumption of the devices.
An Efficient Predictive Paradigm for Software Reliability
Authors: Pagadala Srivyshnavi , Bathala Sony , Uma B.
Published: August 2021

Software Estimation gives solution for complex problems in the software industry which gives estimates for cost and schedule. Software Estimation provides a comprehensive set of tips and heuristics that Software Developers, Technical Leads, and Project Managers can apply to create more accurate estimates. It presents key estimation strategies and addresses particular estimation challenges. In the planning of a software development project, a major challenge faced by project managers is to predict the defects and effort. The Software defect plays critical role in software product development. The estimation of defects can be determined in the product development using many advanced statistical modelling techniques based on the empirical data obtained by the testing phases. The proposed estimation technique in this paper is a model which was developed using Rayleigh function for estimating effect of defects in Software Project Management. The present study offers to decide how many defects creep in to production and determine the effort spent in months. The estimation model was used on Software Testing Life Cycle (STLC) to complete product. The accuracy of the model explains the variation in spent efforts in months associated with number of defects. The model helps the senior management in estimating the defects, schedule, cost and effort.
Agriculture Land Classification Based on Climate Data Using Big Data Analysis
Authors: Sirish Kumar M. , Jyothi S. , Kavitha B.
Published: August 2021

The Agricultural Land Classification (ALC) provides a frame work for classifying land according to the extent at which it’s physical or chemical characteristics impose long-term limitations on agricultural use. The major physical factors that influence agricultural criteria for grading are based on their physical margins of land for agricultural use, such as climate (temperature, rainfall, aspect, exposure and frost risk), site (gradient, micro-relief and flood risk) and soil (texture, structure, depth and stoniness and chemical properties which cannot be corrected) and exchanges these factors as soil wetness, draughtiness and erosion. These factors together interact with the basis for classifying land into one of five grades, the grade or sub-grade of land being determined by the most limiting factors that can be classified into grades from 1 (excellent) to 5 (very poor). These grades are classified by using temperature and average rain fall. In this we classified Agriculture Land Classification (ALC) by using Big Data Analysis based on climatic conditions of England and Wales data.Here we analyzed England and Wales data because it has the accurate climatic grades data. These grades data is huge so we analyses the data in Big DATA analysis.
Cloud Computing Security Using Cryptographic Algorithms
Authors: Srilakshmi K. , Bhargavi P.
Published: August 2021

Cloud computing is a new and fast emergent technology in field of computation and data storage as a service at very eye-catching facilities. It provides fast and well organized on demand services for storage, network, software, and hardware through the Internet. Applications that run in the cloud can balance various elements comprising load balancing, bandwidth, security and size of data. Major problems to cloud adoption are data privacy and security, because the data owner and the service provider are not within the similar trusted domain. Safety issues are increasingly significant in lowest layer Infrastructure as a Service (IaaS) to higher Platform as a Service (PaaS). In this paper we present range of dissimilar techniques or security algorithms exploiting to uphold the secrecy and security of the cloud with cryptographic algorithms.
Big Data Integration with IoT to Achieve the Challenges
Authors: Bhagyasree V. , Rohitha K. , Kusuma K. , Kokila S.
Published: August 2021

The Internet of Things anticipates the combination of physical gadgets to the Internet and their access to wireless sensor data which makes it useful to restrain the physical world. Big Data convergence has many aspects and new opportunities ahead of business ventures to get into a new market or enhance their operations in the current market. The existing techniques and technologies is probably safe to say that the best solution is to use big data tools to provide an analytical solution to the Internet of Things. Based on the current technology deployment and adoption trends, it is visioned that the Internet of Things is the technology of the future; while to-day’s real-world devices can provide best and valuable analytics, and people in the real world use many IOT devices. In spite of all the advertisements that companies offer in connection with the Internet of Things, you as a liable consumer, have the right to be suspicious about IoT advertisements. This paper focuses on the Internet of things concerning reality and what are the prospects for the future.
Performance Improvement of Antilogarithmic Converter Using 28 Regions Error Correction Scheme
Authors: Kishore Kumar A. T. A. , Seshasayanan R.
Published: August 2021

Logarithmic conversion is a significant portion of numerous digital signals processing system and other applications. The anti logarithmic transformation presented in this paper is able to support the anti logarithmic conversion of data with the number of bits up to thirty-two. An efficient FPGA hardware implementation of logarithmic operations is an alternative option used in arithmetic operations. In this paper, we implemented an efficient anti logarithmic converter using FPGA. This implementation is compared with 28 regions error correction scheme. The proposed hardware architecture having less area, delay with less error cost. This design is implemented using HDL tool and synthesized using Xilinx CAD tool. The implementation has with respect to existing antilog converter.
The Art of Data Science and Big Data Analytics: Inspecting and Transforming Data
Authors: Subhadra Akella
Published: August 2021

Data Science is associated with new discoveries, the discovery of value from the data. It is a practice of deriving insights and developing business strategies through transformation of data in to useful information. It has been evaluated as a scientific field and research evolution in disciplines like statistics, computing science, intelligence science, and practical transformation in the domains like science, engineering, public sector, business and lifestyle. The field encompasses the larger areas of artificial intelligence, data analytics, machine learning, pattern recognition, natural language understanding, and big data manipulation. It also tackles related new scientific challenges, ranging from data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization, to integrative analysis across heterogeneous and interdependent complex resources for better decision-making, collaboration, and, ultimately, value creation. In this paper we entitled epicycles of analysis, formal modeling, from data analysis to data science, data analytics -A keystone of data science, The Big data is not a single technology but an amalgamation of old and new technologies that assistance companies gain actionable awareness. The big data is vital because it manages, store and manipulates large amount of data at the desirable speed and time. Big data addresses detached requirements, in other words the amalgamate of multiple un-associated datasets, processing of large amounts of amorphous data and harvesting of unseen information in a time-sensitive generation.
As businesses struggle to stay up with changing market requirements, some companies are finding creative ways to use Big Data to their growing business needs and increasingly complex problems. As organizations evolve their processes and see the opportunities that Big Data can provide, they struggle to beyond traditional Business Intelligence activities, like using data to populate reports and dashboards, and move toward Data Science- driven projects that plan to answer more open-ended and sophisticated questions.
Although some organizations are fortunate to have data scientists, most are not, because there is a growing talent gap that makes finding and hiring data scientists in a timely manner is difficult. This paper, aimed to demonstrate a close view about Data science, big data, including big data concepts like data storage, data processing, and data analysis of these technological developments, we also provide brief description about big data analytics and its characteristics , data structures, data analytics life cycle, emphasizes critical points on these issues.
Linear Regression Approach to Predict Crop Yield
Authors: Murugan R. , Thomas Flaize Sara , Geetha Shree G. , Glory S. , Shilpa A.
Published: August 2021

The agriculture plays a very big and important role for the country’s growth. The agriculture science system facing lots of problems from the environmental change. Machinelearning (ML) is the best approach to overcome the problems by building the good and effective solutions. Crop yield prediction include prediction of yield for the crop by analyzing the existing data by considering several parameters like weather, soil, water and temperature etc. This project addresses and defines the predicting yield of the crop based on the previous year’s data using Linear Regression algorithm. The approach of this project is to solve the problem of cost loss. Real agricultural data is used for making the models and the models tested with the samples. The prediction model will help the end users (farmers) to predict the crop yield before cultivation of the crop onto the agricultural field. To predict the accurate results Linear Regression machine algorithm is used. The presence of large dataset will help to improve the decision making model.
An Analysis of Data Security and Privacy for Cloud Computing
Authors: Subhadra Akella
Published: August 2021

Cloud Computing is the important buzzword in the today’s world of computer. Cloud is global platform that allows digital information to be stored and distributed at very less cost and very fast to use. In these days since the data is very big in size many users are interested to store their valuable data in the cloud .The application software and databases in cloud computing are moved to the centralized large data centers, where the management of the data and services may not be fully trustworthy. Cloud Computing is scalable, fast, flexible, and cost-effective technology platform for IT enabled services over the internet. There are various advantages of cloud computing but ultimately cloud service users have to put their data over the cloud i.e., third party servers which are not directly controlled by the data owner Data security has consistently been a major issue in information technology In cloud computing in users perspective mainly in government ,industry and business Data security and ivacy protection issues are relevant to both hardware and software in the cloud architecture. Cloud security is becoming a key differentiator and competitive edge between cloud providers. In spite of various benefits that are provided by the cloud computing services, cloud computing service users are very much afraid about the security of their data .So this paper focuses on various issues regarding cloud computing, data security and how cloud provides data integrity, confidentiality, availability over user’s data? How data stored over cloud storage servers will be protected from attackers? Risk management of data present on the Cloud is another challenge. There is a requirement to identify the risks an organization would be taking while hosting data and services on the Cloud. In this paper, we present those issues that are preventing people from adopting the cloud and to minimize risks of these issues.
Internet of Things: Wildlife Conservation and its Challenges
Authors: Choudhary Ratnesh Kumar
Published: August 2021

Right now there are more connected “Things” than there are people on this planet. Early last year, it is predicted that Internet of things (IOT) would have at least 8.4 billion connected “Things” in use rising to more than 21 billion by 2021. Today major percentage of wildlife is vulnerable to extinction. This is caused due to the destruction of forest areas for farming, logging and construction of new cities and towns. Many wild animals have been killed due to road accidents and speeding vehicles passes through the wildlife protected area. Animals crossing boundaries have led to be killed. The impacts of roads include habitat loss, habitat fragmentation and habitat degradation that affect wildlife and its habitats both directly and indirectly especially on larger mammals [6]. Recent studies into the extent of illegal logging estimate that illegal logging accounts for 50-90 per cent of the volume of all forestry in key producer tropical countries and 15-30 per cent globally [1]. Protection of wildlife has become an important now a days, because of human activities such as hunting of wild animals and cutting of trees which causes major threat to the wildlife. Recent advancements in IoT technology and sensor technology have the potential to wildlife conservation. Physical barriers are not suitable for animals because they may harm the animal physically. This can be prevented by using tracking of animal movement and keep them under a logical barrier. This paper focuses on implementation of animal monitoring and challenges of wildlife conservation. This paper also shows natural challenges and technical challenges while implementing animal tracking and health monitoring system.
Usability and Performance Analysis of E-Commerce Websites
Authors: Kaur Daljit , Kaur Harpreet
Published: August 2021

Online business or trade has become the buzz word in today’s Internet dominant era. The concept of using e-commerce sites for shopping the daily items and other goods have become also popular in the developing countries like India. The experience of users and study of their behaviour on e-commerce websites helps in determining the usability of these websites, which is acknowledged as a key factor for assessing the quality of any website. These quality measures along with performance measures are collected and compared for 28 e-commerce websites using two different approaches. The relative priority and preferences of the features and ease are investigated through a survey in this paper. Further, using GTmetrix-an online tool, speed tests and other parameters are garnered to analyze their performance. This research work is carried out with the objective to compare and analyze the performance of popular e-commerce websites and also to study its relationship with user preferences and behavior on these websites which can further guide the website developers and entrepreneurs in improving the performance and satisfying the customers.
A New Algorithm for Pattern Based Using Mining Association Rules
Authors: Selvam S.
Published: August 2021

It is indeed an art to match maximum number of preferences by utilizing limited number of resources. During the current academic year 75% of the admissions to Engineering Colleges have gone down, as only 30% to 40% of intake has been filled. Without reaching the breakeven point, the management of the institution becomes a complicated issue. The main aim of this paper is to discover a pattern to identify the choice of preferences of the candidates to seek admissions in any academic institutions. For the purpose of matching optimum number of candidates to suit our existing system, we have designed our algorithmic approach. Here our new system is used to extract frequent item sets from various preferences. By thresholds, it can fix the preferences either decrease or increase the level of frequent. The new algorithm is based on association rule classification which is one of data mining techniques. Here the frequency of itemset2 is combined with frequency to get itemset3 and continues until item set n. the new algorithm is easy to use and implement because its complexity is less. The application is designed to generate association rule until n-antecedent with one consequent. For this study purpose we have identified 15 most frequently used preferences among the students. The samples we have taken to get association rules are 100 students of Pannai College of Engineering and Technology at Sivagangai. The discovered pattern is common to all institutions. The pattern discovery may be accurate because it is computed by using factors like confidence and support. If this intelligent system is followed strictly, definitely the number of outcomes is increased. The applicant would prefer only when the supply is high. The result of this paper is an application that can generalize association rule among various academic institutions.
Potential of ICT in India to Cater Pandemics in Healthcare Sector with Special Reference to Covid-19
Authors: Rather Zafar Majeed , Ahmad Magray Ajaz
Published: August 2021

Corona virus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome Corona virus 2 (SARS-CoV-2). The disease was first identified in December 2019 in Wuhan, the capital of China’s Hubei province, and has since spread globally, resulting in the ongoing 2019–20 corona virus pandemic. As of 9 June 2020, more than 7.12 million cases have been reported across 187 countries and territories, resulting in more than 406,000 deaths. More than 3.29 million people have recovered. The virus is primarily spread between people during close contact, often via small droplets produced by coughing, sneezing, or talking. The disease has been given official name as COVID-19[1]. Since its outbreak in china, infrared thermometers were used to check the body temperature in order to identify the infected people. Countries like China and Korea started the use of different technologies to detect, track and prevent the spread of this deadly virus. Among the major technologies used are Internet of Things (IoT), Artificial Intelligence (AI) and deep learning. With the invent of 5G technologies, we are able to transfer and process huge amounts of data on a real time basis. Health experts have argued that a key tool at governments’ disposal to contain the COVID-19 outbreak, and which was not around during the 1918 Spanish Flu, is the ability to harness digital technologies to track the spread. At the same time, deployment of contact tracing apps by governments or public health authorities has added to the debate on online privacy and personal data protection. In this research paper, we discuss the potential application of different information and communication technologies (ICT) like IoT, AI and 5G that can help in (i) Monitoring (ii) surveillance (iii) detection and prevention of COVID-19 and enhancing the healthcare to make it future-ready for any such diseases like COVID-19.
New Algorithm for Reverse Conversion in Residue Number System
Authors: Asiedu Daniel , Salifu Abdul-Mumin
Published: August 2021

Reverse conversion is an important exercise in achieving the properties of Residue Number System (RNS). Current algorithms available for reverse conversion exhibits greater computational overhead in terms of speed and area. In this paper, we have developed a new algorithm for reverse conversion for two-moduli set and three-moduli set that are very simple and with fewer multiplicative inverse operations than there are in the traditional algorithms like the Chinese Remainder Theorem (CRT) and Mixed Radix Conversion (MRC).
Automated Detection of Multiple Sclerosis Lesions in Normal Appearing White Matter from Brain MRI: A Survey
Authors: Khatokar Manoj V. , Hemanth Kumar M. , Chandrahas K. , Swetha M. D. , Satish Preeti
Published: August 2021

Multiple Sclerosis is an inoperable disease of the Central Nervous System (CNS) that irritates the myelin sheath by forming lesions. This affects all organs of the CNS; the vital of them is the brain. This disease can be detected by diagnosis like Magnetic Resonance Imaging (MRI). It is a non-invasive diagnostic test that provides detailed images of the soft tissues of the body. Out of the different variations of MRI, MS lesions are predominantly visible in the DTI (Diffusion Tensor Imaging) variant of MRI. DTI gives enhanced visualization of normal-appearing white matter tracts of the organs, hence providing a better image of the MS lesion. In this paper, the latest methodologies regarding the identification of the MS lesions in MRI scans like T2 FLAIR or DTI, using automated techniques like deep learning, computer vision, neural network and many more are surveyed. Furthermore, this paper consists of a proposed model which would focus on correlating the lesions found in DTI scan with the basic MRI scan like T2. It would identify the MS lesion in DTI scan and eventually highlight that lesion position in the T2 image scan. This would help radiologist in a way to effectively handle multiple MRI scans.
Ad Hoc Vehicle Networks: Recapitulation and Challenges
Authors: Neelambike S. , Amith Shekhar C. , Rekha B. H. , Patil Bhavana S.
Published: August 2021

Being ad-hoc in design, VA NET is a form of networks generated by the idea of building up a network of cars for a specific needs or circumstance. In addition to the benefits, VANET poses a large number of challenges such as providing QoS, high bandwidth and connectivity, and vehicle and individual privacy security. Each report discusses VANET 's state-of-the-art, explaining the relevant problems. We address in depth network design, signal modelling and propagation mechanisms m, usability modeling, routing protocols and network security. The paper's key results are that an effective and stable VANET satisfies all architecture criteria such as QoS, minimal latency, low BER and high PDR. At the end of the paper are addressed several primary work areas and challenges at VANET.
Experimental Study on Self Compacted Concrete Mix Using Admixtures and Accessing its Performance By Comparing with Conventional Concrete (M25)
Authors: . S .Vivek , . G. Sri Harin
Published: August 2021

The self compacted concrete is an innovative product in civil engineering field of India. The necessity of this product was felt by civil engineers to overcome in the issue of workmanship, in structural concreting of heavily reinforced sections in execution of concrete. The introduction of SCC in the precast concrete industry was successful, with regard to application in situ; the development is slower because of the sensitivity of the product.The development of concrete that can be compacted in to every corner of a formwork by means of its own weight and without vibration is reviewed.SSC was developed to achieve durable concrete structures.This type of concrete has used by large construction companies.In recent years SSC has gained wide use for placement In reinforced concrete structures with difficult casting conditions. Sludge is a major issue since the they are the obtained from sewage and industrial waste where it causes many problems, so it can be used as admixture to the concrete because it attains more strength. In this paper, the mechanical properties of SCC in comparison to conventional concrete and concrete using sludge were discussed. The compressive strength results of hardened concrete showed that SCC gained strength slowly compared to theconventional cement concrete due to the presence of admixture and it’s 28 days strength was lower than conventional cement concrete ,but SCC eventually had potentials of higher strength beyond 90 days. Finally the effect of water cement ratio on the plastic properties of SCC was quite negligible compared to conventional method.
Assessment of Hydrocarbon Oil Spill Pollutants in Agricultural Land
Authors: . R. Arivarasan , . D. Sathishkumar
Published: August 2021

Hydrocarbon contamination is a very serious problem whether it comes from petroleum, pesticides or other toxic organic matters. Oil spill have number of effects on the environment when petroleum products are released into the environment, they interact with the soil, groundwater, and microorganisms. Studies have mainly focused on identifying and characterizing these hydrocarbon degrading microbes, as well as how they scope with the soil/water/hydrocarbon interface, and how to improve this capacity. The main aim of the present study was to evaluate the biodegradation potential of microbes which was isolated from the hydrocarbon contaminated soil such as bacillus species and pseudomonas species. Those isolated microbes were inoculated into the contaminated soil, after 20 days of degradation process the physicochemical properties such as pH, temperature, color, GC-MS were analyzed and also prominent microbe was identified from the isolated microbes. Comparative study also done between aerated and non-aerated condition from that, aeration process enhanced the degradation rate.
Simulation of Urban Drainage System Using a Storm Water Management Model (SWMM)
Authors: Rangari Vinay Ashok , Sai Prashanth Sriramoju
Published: August 2021

Urban floods are caused due to increase in population density, development of urban infrastructure without paying due consideration to drainage aspects and increase in paved surfaces. Storm water modelling plays an important role in checking issues such as flash floods and urban water-quality problems. The SWMM (Storm Water Management Model) has been an effective tool for simulating floods in urban areas. In this study a SWMM model is developed to analyze drainage network for the campus of National Institute of Technology, Warangal in the city of Warangal, Telangana, India. The model is simulated for one real storm event and 2-year return period of interval 1-hour design storm intensity. Frequency analysis is performed using best fitted distribution i.e., Gumbel’s distribution for different return periods and the frequency values are used for development of IDF (intensity-duration-frequency) curves. Design storm intensity derived from IDF curves for different return periods is used to estimate peak runoff from each sub catchment which is used as input parameter in simulation of runoff in SWMM. GIS methodology is employed for handling spatial data simultaneously. From results, it is observed that some part of campus are commonly affected with flooding, when analysis is performed for two design storms and one day continuous rainfall/precipitation values.
Effect of Lithium Based Admixtures on Alkali Silica Reaction in Concrete and Flexural Behavior of Reinforced Concrete Rectangular Beams
Authors: . S. Sathya
Published: August 2021

In recycling of lithium-ion batteries, lithium is a challenging element, which possesses great threat to the environment. The disposal of electronic waste is a major problem, which our country is currently facing, whereas, the lithium is one of the compound in electronic waste which challenges the recycling of lithium-ion batteries. If lithium is properly extracted, it can be used for structural engineering purpose. Lithium, if used in concrete, it controls the cracks due to alkali silica reaction (ASR), resulting in increased strength and durability of the concrete. Lithium based admixtures are effective in suppression of alkali silica reaction and delayed ettringite formation, if the dosage added in concrete is appropriate. The main objective of this paper is to assess the effectiveness of LiNO3 at various dosage levels in concrete. In this paper, the effect of LiNO3 on the mechanical properties of concrete, ASR gel formation and the flexural behavior of reinforced concrete rectangular beams are studied. The mechanical properties of concrete was investigated for six mix proportions comprising of control mix, lithium nitrate at 0.6M, 0.65M, 0.7M, 0.75M, 0.8M. LiNO3 not only prevents the ASR gel formation, but also it has great influence on mechanical properties of concrete. The results indicate that the concrete with 0.75M LiNO3 has higher strength values. SEM analysis has been performed for 0.75M and control mix to study the micro characteristics of concrete. The ASR gel formed in 0.75M has been suppressed as compared to that of concrete without lithium nitrate as an admixture. The durability studies are performed in concrete for water permeability, water absorption and rapid chloride penetration characteristics. The analytical study of flexural behavior of reinforced concrete rectangular beam is done using the software ANSYS 16.0.
Optimization of Design Mix Proportion for Saturated Water Absorption of High Performance Concrete
Authors: . M. Akila , . S. Chithra
Published: August 2021

This study involves the optimization of design mix proportion for saturated water absorption of high performance concrete (HPC) by Taguchi Method. In the present investigation, saturated water absorption test on 25 HPC mixes specimens made with colloidal nano silica and copper slag as replacement of cement and fine aggregate respectively has been conducted at the age of 28 days and 90 days of water curing. The concrete mixes has been replaced by 1%, 1.5%, 2%, 2.5%, 3% of nano silica and copper slag of 10%, 20%, 30%, 40%, 50%. From Signal-to-Noise ratio, the optimal parametric combination for saturated water absorption has been obtained. The Analysis of Variance has been done on experimental data values. The percentage contribution of the factors towards saturated water absorption is identified. The nano silica contributes towards less water absorption in 28 days curing, while the Copper slag found to the major contributing factor for the cause after the 90 days tenure of water curing.
Modelling and Analysis of Continuous Stirred Tank Reactor through Simulation
Authors: Anbu S. , Senthilkumar M.
Published: August 2021

A Continuous Stirred Tank Reactor (CSTR) finds its application in many chemical and petrochemical process industries. CSTRs exhibit reasonably high non-linear behaviour. CSTRs are open systems, where thematerial is free to enter or exit the system, which operates on a steady-state basis, where the conditions in the reactor don’t change with time. The reactants are continuously introduced into the reactor, while products are continuously removed.CSTRs are very well mixed, so the contents have relatively uniform properties such as temperature, density, etc. throughout. Further, the majority of chemical reactors are Multi-Input Multi-Output (MIMO) systems, which again develop a high degree of complexity in the development of control systems due to the process interactions, dead time and process nonlinearities. The control of CSTR throws a challenge to the control engineers to design a well-suited controller for its smooth operation. To develop effective control strategies, the behaviour of the reactor needs to be studied. Generally, CSTR behaves differently at different operating regimes. This article attempted to make a comprehensive study on the CSTR through modeling and simulation of the open-loop behaviour using MATLAB.
Channel Allocation Scheme for Cellular Network Using Fuzzy Logic
Authors: Shinde Vikas
Published: August 2021

This paper, deals fuzzy call admission control scheme to the requirement of quality of service. Quality of service is very critical issue in mobile communication because of dearth of spectrum resource and mobility of consumer and the main parameter is call dropping probable condition which shows the possibility of the extant relation being refusable during mobility. When the consumer’s call suddenly abolished in the term of the connection is more troubling than being obstructed likely on a new call try. Performance of channel allocation scheme is evaluated, using fuzzy control in terms of call dropping probability and channel utilization
Growth and Studies of Potassium Dihydrogen Phosphate Crystals Doped With Picric Acid
Authors: Manju T. , Selvarajan P.
Published: August 2021

Potassium dihydrogen phosphate (KDP) crystal has been doped with picric acid to alter its physical and chemical properties. Picric acid doped KDP salt was synthesized by adding 2 mole% of picric acid into the aqueous solution of KDP. Using the synthesized salt of picric acid doped KDP and double distilled water, single crystals were grown by solution method with slow evaporation technique. The grown single crystal was subjected to XRD method to find the crystal structure. The functional groups of the sample were found by FTIR method. The elements in the picric acid doped KDP crystal were identified by EDAX and CHN analyses. SHG studies of the sample were done to check the second order NLO property. Dielectric studies for picric acid doped KDP crystal were carried out using a multi-frequency LCR meter. Thermal stability of the sample was found by TG/DTA studies. The microhardness of the sample was also measured at different applied low loads and the results obtained from the various studies are discussed.
Static and Fatigue Analysis of Carbon Epoxy Reinforced Composite Leaf Spring
Authors: . Chatwant Singh Pandher , Brar Gurinder Singh , Singh Tejeet
Published: August 2021

Different fields of mechanical, automobile, aerospace, electronics and communication engineering uses composite material. The automobile industries have shown great interest to change traditional use of steel leaf spring with light weight composite leaf spring with same strength. This research paper presents the general study, fabrication, static and fatigue analysis on carbon epoxy composite leaf spring. A rear leaf spring of Tata Ace (mini truck) made of material EN45 spring steel was selected as practical application. Hand Lay-up technique was used to make a carbon epoxy leaf spring. A single carbon epoxy composite leaf spring is compared with EN45 steel leaf spring. Static test was performed on both steel spring and composite spring from initial load of 1000 N to full load of 5400 N. Results shows that deflection of carbon epoxy composite leaf spring is 14% less as compared to the steel leaf spring which means increase in stiffness. Also fatigue life of composite leaf spring is more than desire 100000 cycles.
Thermodynamic Analysis of Efficiency- NTU Parameters for Parallel Flow Type Heat Exchanger under the Effect of External Heat Leak
Authors: Tiwari Roopesh
Published: August 2021

The work presented here analyses theoretically a parallel flow type heat exchanger which is subjected to external heat leak, from the cold fluid side or from the hot fluid side. Efficiency-NTU relations are developed and the results obtained are presented graphically, reflecting the effect of heat capacity ratios and the heat leak on the efficiency of the heat exchanger. The graphs follow the similar pattern with increasing heat capacity ratios. Also, as the heat leak is increased, the graphs show opposite behavior when the minimum heat capacity is on the hot side to that when the minimum capacity is on the cold side. The derived expressions are reduced to the classical effectiveness-efficiency-NTU relations for the parallel flow type heat exchangers as the heat leak approaches zero.
Design and Applied Systematic Matrix Method for Orthogonal MIMO Channel over Fading Channel
Authors: Sinha Hemlata , Meshram M. R. , Sinha G. R.
Published: August 2021

In this paper we propose a systematic method for designing a space – time orthogonal MIMO scheme that employs an arbitrary number of transmitting and receiving antennas. Such systems is utilized to improve the bit error rate (BER) performance of wireless communication systems and counter the destructive effects of channel attenuation and alternative distortion phenomena and also propose a matrix method advance is proposed to maintain the orthogonal property, which is most essential, so that the channels may remain un correlated, due to this condition, interference do not occurs between the data transmitted through the channels and thus performance improvement is achieved, which is evaluated through simulation.
Studies on Effect of Different Environmental Conditions on CBR of Black Cotton Soil Reinforced with Coir Fibre
Authors: Swami Akhileshwar , Kushwaha Pushpendra Kumar , Gangwar Mohit
Published: August 2021

Expansive soil covers nearly 20 percent of the land mass in India. These soils are known to possess weak properties due to the presence of clay minerals known as “Montmorillonite”. Typical behaviour of soil results in the failure of structures, in form of settlements, cracks etc. Thus it is important to remove the existing weak soil and replace it with non-expansive soil or to improve the properties of weak soil by stabilization. Soil reinforcement is a technique that can be used to improve the engineering characteristics of expansive soils. Use of natural fibres to reinforce soil is an old and ancient idea. Randomly distributed fibre reinforced soil have recently attracted growing attention in geotechnical engineering. The present dissertation aims to study the effect of different environmental conditions on performance of coir fibres included in black cotton soil to enhance its strength and reduce the swelling behaviour. Coir fibre is known as a biodegradable material that tends to decay under extreme environmental conditions such as in contaminated and polluted water, in getting contact with the leachate, in alternate cycles of wetting and drying, also in alternate cycles of freezing and thawing and so on. In general, life of coir fibre in soil is expected to 8-10 years. Therefore under different environmental condition it may degrade fast. The gain in soil strength or decrease in swelling might be lost. This aspect is not studied so far. Hence in this work this is attempted. The work in the project is experiment based, California bearing ratio of soil is an important soil strength parameter used in design of pavements. Effect of some different possible environmental conditions on CBR of expansive soil improved by coir fibre reinforcement will be studied experimentally in the present work.
Effects of Different Substrates on Rectangular Microstrip Patch Antenna for X-band
Authors: Khan Imran , Geetha Devanagavi D. , Sudhindra K. R. , Prathibha S. , . C. Shruthi , Nirmala S.
Published: August 2021

In this paper, the performance of Microstrip Patch Antenna (MSPA) is analyzed by changing the substrate materials. MSPA is designed to operate with the fixed dimensions of ????????×????????×????.???????????????? for three substrate materials. A comparison has been done in terms of reflection coefficient (S11), gain, efficiency (η), radiation pattern and cost. The simulated results show very good performance with TLC substrate as compared to FR4 and RT Duroid by showing good radiation efficiency for all the three bands viz 7.0, 9.6 and 10.8 GHz with the efficiency of 99%, 99% and 96% respectively, stable radiation patterns, gain of 1.32, 1.81 and 2.0 dB. FR-4 and RT Duroid produces two bands each of 8.4/ 9.6 GHz and 11.1/12.0 GHz respectively which shows a gain of 1.29/1.36 dB for FR4 and 1.04/7.95 dB for RT Duroid along with efficiency of 68%/ 60% and 96%/96% respectively with acceptable bandwidth. The Antenna is simulated using HFSS simulator solution software.
Mobile Cloud Computing: A Literature Survey
Authors: Arun Lakshna , Ravi T. N.
Published: August 2021

Mobile cloud computing (MCC) is the availability of cloud computing services in a mobile environment. By providing optimal services for mobile users, MCC incorporates the elements of mobile networks and cloud computing. In mobile cloud computing, all the data and complicated computing modules can be processed in clouds, and mobile devices do not need a powerful configuration like CPU speed, memory capacity, etc. However, the mobile devices are facing up with many struggles in their resources (e.g., battery life, storage, and bandwidth) and communications (e.g., privacy, mobility, and security). These challenges have a significant effect on the improvement of service qualities. In this paper, a literature survey on the MCC and security issues in MCC has presented.
Privacy Preserving Technique for Data Storage in Cloud Computing
Authors: Kaur Jagpreet , Goel Nitin
Published: August 2021

With the emergence of Cloud computing, the traditional computing process has undergone a sea change. Cloud Computing has been proving to be a boon for IT industries in terms of its ability to provide cost effective, power efficient, extensible and pliable computing. Because of its substantial flexibility, Cloud Computing has become an escalate platform for the services of next generation. But inspite of all the advantages, security and privacy of the data being shared on Cloud remains a cause of concern for the users as well as service providers. This paper proposes a ‘Tortoise technique’ aiming to provide more privacy to user’s data without any kind of security threats from outside. As a part of the technique, reduced data is sent to cloud instead of the original encrypted data. We observed an improvement to an order of 2n in the security of data with the help of the proposed technique.
FPGA IMPLEMENTATION OF REVERSIBLE ADDER/SUBTRACTOR
Authors: Gowthami P. , Satyanarayana R. V. S.
Published: August 2021

This work presents the new design of the reversible adder/subtractor circuit. The proposed design of reversible adder/subtractor is compared to the existing counterpart in terms of design constraints such as the total number of reversible gates, no. of constant inputs and quantum cost. The delay and power of the proposed reversible adder/subtractor circuit were calculated, compared with existing reversible and conventional adder/subtractors.
A Review Paper on Biodegradable Composites Made from Banana Fibers
Authors: Pannu Amrinder Singh , Singh Sehijpal
Published: August 2021

Composites are defined as mixture of two or more ingredients where one is called as matrix (larger in quantity) and other is called reinforcement (smaller in quantity). Now a days research is concentrated towards various methods of making biodegradable composites where either reinforcement or matrix are biodegradable or both are biodegradable. Composites have so many applications in industrial as well as commercial use due to their low weight to strength ratio that attracted the automobile manufacturers to use these materials in cars which in turn increases the efficiency as well as reduce the cost of the automobile. In this paper effort has been made to investigate various process of manufacturing composites manufactured from banana fibers using different matrix preferably PLA (Polylactic Acid). The methods of improving the bonding between the reinforcement and matrix, effect of fiber orientation, size of the fibers and percentage reinforcement has been studied.
A Novel Hybrid Framework for Medical Image Retrieval
Authors: Saravanan A. , Sathiamoorthy S.
Published: August 2021

A new hybrid framework for Content-Based Medical Image Retrieval (MCBIR) is proposed in this paper to deals with the accuracy issues related with the existing MCBIR. The proposed hybrid framework initially divides the images into number of non-overlapping rectangular regions. Subsequently, statistical based color autocorrelogram (CA) and texture autocorrelogram (TA) is extracted for each region respectively. Then the geometric based chordiogram descriptor (CD) is extracted for each region. Both the statistical based and geometric based descriptors are combined to create a feature vector. The corresponding image regionsor patches in the query and target medical images are compared using the Canberra distance measure. The proposed hybrid framework is evaluated using the benchmark database and it is confirmed that it significantly outperforms the state-of-the-art system in terms precision, recall and G-measure.
Self-Organization Map Based Segmentation of Breast Cancer
Authors: Arokiyamary Delphina A. , Kamarasan M. , Sathiamoorthy S.
Published: August 2021

Breast cancer is second major leading cause of cancer fatality in women. Mammography prevails best method for initial detection of cancers of breast, capable of identifying small pieces up to two years before they grow large enough to be evident on physical testing. X-ray images of breast must be accurately evaluated to identify beginning signs of cancerous growth. Segmenting, or partitioning, Radio-graphic images into regions of similar texture is usually performed during method of image analysis and interpretation. The comparative lack of structure definition in mammographic images and implied transition from one texture to makes segmentation remarkably hard. The task of analyzing different texture areas can be considered form of exploratory report since priori awareness about number of different regions in image is not known. This paper presents a segmentation method by utilizing SOM.