bluuebunny/crossref_metadata_2025 huggingface dataset:
Low-Carbon and Sustainable Urban Bike Lane Labelling System - A Case Study of Taichung
Authors: Chien Yu-Chen , Hu Wei-Han
Published: December 2020

According to the 2001 assessment report of the intergovernmental panel on climate change (ipcc) of the United Nations, in the past 50 years, climate warming, excessive human development caused environmental impact, global energy shortage and high oil price environment, began to promote green transport, among which the bike advocates environment-friendly and low-pollution transport mode. Under this trend, bike lanes are increasing in Taiwan. Signage systems should be improved to achieve road network safety, continuity, integration and ride friendliness. Traffic labelling system in cities is an integral part of infrastructure construction and urban aesthetics. Kevin Lynch mentioned in The Image of The City that people in modern cities rely on indicator devices, and a good labelling system can help users to identify the environment conveniently and quickly. This study attempts to establish the Taichung city bike lane labelling system design, in order to collect relevant literature review summarized evaluation index, the study points out that network build bike lanes marked by subject system to meet the “Modelling Style”," Chromatic Scheme” and “Material Selection” three as the main index, by the fuzzy Delphi method, collecting group expert advice, in accordance with the subsequent bike lane labelling system design and update.
Application of APP Technology to Promote Urban Low-Carbon Transportation
Authors: Chien Yu-Chen , Yang Chen-Tzu
Published: December 2020

According to the Economist Intelligence Unit’s annual ranking of cities in the liveability index, bicycle penetration is one of the top indicators of liveability in the world. As one of the transportation tools of low-carbon life, bicycle can provide convenient travel tools and leisure activities, effectively reduce the burden of man-made development on the environment, meet the spirit of relaxation, is both pollution-free, economic, convenient and other advantages of transportation. The 21st century is an era of smart technology, and the rise of APP has changed people’s life pattern and the way of obtaining information. However, it has become a current trend to take people and environment as design considerations [1]. The successful bike APP can meet the needs of cyclists of different ethnic groups when riding, improve the convenience of cyclists, so as to attract more people to use bicycles and promote low-carbon and energy-saving lifestyle. Based on a literature review and a survey of 50 existing bicycle apps, this study concluded that the “seven major functional categories, two navigation modes and two interface aesthetic” of the apps were the most important factors affecting users’ preferences and download intention.
Optimization Research of Rural House’s Envelope Parameters in Severe Cold Regions of China
Authors: Shao T , Jin H , Zheng WX
Published: December 2020

The thermal performance of envelope directly restricts the heating energy consumption and indoor thermal environment of rural houses in severe cold regions. However, with the improvement of thermal performance, the construction cost will be greatly affected, which is one of the main factors hindering the implementation of energy saving design for rural houses. The energy saving and economy of whole life cycle should be considered simultaneously when determining the optimal parameters of envelope. This paper, taking the benchmark model of rural houses as research object, the life cycle cost (LCC) as evaluation index, establishes the GenOpt-EnergyPlus optimization platform by coupling EnergyPlus and GenOpt software to carry out the optimization. In the analysis, the insulating layer thickness of exterior wall, roof and ground and the window types are selected as optimization variable. Considering that the length of life span may affect the effective utilization rate of operation and construction cost, three types of life span are set, including 10, 20 and 30 years. Through the analysis, the optimum thickness of insulating layer and the energy saving effect under different conditions were discussed, which provide the basis for the comprehensive optimization of energy saving and economic benefit of rural house’s envelope in severe cold regions of China.
A Green Infrastructure Strategy for Energy Efficiency in Urban Context
Authors: Hsu Kuo-Wei , Chao Jen-Chih , Zheng Jun-Jie
Published: December 2020

In the process of urban development, the more intensive areas are intensive, causing problems of urban congestion, traffic congestion and parking space, and they are the main source of energy consumption. Urban development guided by the development of the mass transit system is widely discussed. However, the problem of improving urban development is not only the construction of the mass transit system, but also the planning of the human environment system, as well as green infrastructure and green transportation. Through literature analysis and field investigation, this study hopes to create a friendly urban environment through the experimental design of roads, buildings and streets around the five power stations (Lilin, Toujiacuo, Songzhu, Jingwu and Wuquan) to truly reduce energy use.
A Study of Ecological Restoration Indicators of the Brownfields of Shuinandong, Taiwan
Authors: Feng Shih-Jen , Tung Chung-En
Published: December 2020

The hundred-year prosperity of the mining industry in Jinguashi, Taiwan, introduced the development of new industrial equipment and factory operation models to the settlements of Jinguashi and Shuinandong, and also established a modernized living and social framework. However, changes in global industrial and cultural structures brought on the progression of urbanization, which in turn caused the disuse of abandoned land previously used by the production industry. In the Shuinandong area, the operation of a smeltery polluted the land, damaged the ecology, produced waste and caused the content of heavy metals in the ocean to rise. This environmental destruction continued to impact the natural environment and ecology of the area even after the smeltery closed. Today, with the rise of environmental awareness, people, environmental protection groups and government agencies have begun to pay attention to the impact of “brownfields” around them. In the Shuinandong area, brownfields are mostly used as space for tourism, and not much has been done to restore the environment through ecological methods. Therefore, this study is aimed towards environmental sustainability, and looks at how to preserve the Remains of the Thirteen Levels in Shuinandong while rehabilitating the polluted natural environment and landscapes in the area. This study also establishes ecological restoration assessment indicators that will allow the Shuinandong area to contribute its value for sustainability.
Use Remote Sensing to Detect the Geomorphologic Change and its Effect around Barrow, Us Area
Authors: Li Zhiyu , Miao Yan , Fa Guifang , Wang Zhongsheng , Shao Xinjun
Published: December 2020

The erosion issue in the north coastal area in Alaska, US has increasingly serious. Landsat image has been downloaded to analyze the erosion. Several image analysis methods in remote sensing are used in this paper to analyze the water body erosion in study area. Erosion in the study area has a significant effect along the river and around the lake. It is inconspicuous in the urban area. The geomorphology in study area is temporarily steady due to the man-made anti-erosion construction. More attention should be paid to the erosion between the coast and lake; it can damage the whole city of Barrow once the erosion connects the sea and lake. By using analysis method discussed in this paper, it can help other coastal area in the world to prevent erosion issues.
Dynamic viscosity of dispersion of silica dioxide nanoparticles
Authors: Dembelova T S , Balzhinov S A , Makarova D N , Vershinina Ye D , Bazarova S B , Badmaev B B
Published: December 2020

Dynamic viscosity of silica dioxide suspensions in oils was investigated by acoustical, rotary and capillary methods. An installation has also been created for measuring the viscosity of a liquid at low gradients of the flow velocity, when one can expect that the structure of the liquid change little during elementary acts of viscous flow. It is shown that at low flow rate gradients of the investigated suspensions, an increased value of viscosity is found (relative to the viscometric one), which indicates the structuring of these suspensions with the formation of a supramolecular structure. The observed phenomenon of increased viscosity can be of practical importance for all processes where slow flows prevail.
HomeCloud Framework for Priority aware VM Allocation and Network Bandwidth Provisioning
Authors: Sidhardha Chintoju , Srinivas V. , Gopal M. , Mothe Rajesh , Kumar Komuravelly Sudheer
Published: December 2020

Various applications in a multi-tenant architecture based cloud computing comprises various requirements and priorities. Severe failure of a critical application may result if the network is congested in a data center. Hence, it is an important to use an efficient resource provisioning technique for ensuring transfer of high priority data to the other traffics still when the network is congested. Therefore, a new framework of Home Cloud architecture is proposed in this paper to provide an effective and flexible delivery of new applications in an edge-cloud architecture which integrates the two complementary technologies of Software-Defined Networking (SDN) and Network Function Virtualization (NFV). In SDN infrastructure, this presents a priority aware resource placement algorithms by taking into consideration of both host and network resources. The Virtual Machines (VMs) of high priority applications are placed at the strongly connected hosts by introducing the priority aware VM allocation (PAVA) algorithm for reducing the possibility of causing network congestion by other tenants. It also guarantees the critical applications for a required bandwidth by means of allocating bandwidth through the setting of priority queues for each network connection within the network of data center handled by SDN controller. The simulation result of the proposed system shows that the combination of proposed approaches will allocate sufficient resources for high-priority applications within a Home Cloud data centre to meet the QoS requirements.
Collaborative Filtering and Regression Techniques based location Travel Recommender System based on social media reviews data due to the COVID-19 Pandemic
Authors: Daya Sagar K. V. , Arunasri P. S. G. , Sakamuri Sridevi , Kavitha J. , Kamesh DBK
Published: December 2020

Nowadays, Dynamic industries like tourism is a enhance to boost many countries economy in recent years. The hotel sector leads to a significant role among all aspects of the tourism industry. Online travel platforms, in association with hotel management, are a part of hotel E-tourism that helps users to make travel plans online, suggest precise recommendations in consideration with the earlier feedbacks upon hotel stay. From the past few months, the user roaming ratio falls rapidly due to the COVID-19 Pandemic across the globe. In a business concern, this Pandemic affects all tourism sectors, specifically in the hotels’ occupancy. To retain business positions and attract the users in these problematic scenarios, hotel and travel platform management concerns about past preferences of users, which have a significant impact on gratification for a comfortable stay. The current market trends show that user reviews are playing a vital role to select a hotel based on a safe location. Our work tries to find and recommend the dimensions that contribute more towards higher satisfaction levels of users in Asian continental top tourism city hotels listed by the Master and VISA Inc survey with item collaborative filtering and regression techniques based on Tripadvisor reviews from social media in recent times. The outcome of the work is helpful for Asian continental hotel management to concentrate more on the dimensions for obtaining better reviews. From an online travel platform perspective, this work suggests the contexts for the travel recommender system to gain things effectively from users.
An overview of an automated essay grading systems on content and non content based
Authors: Dadi Ramesh , Pasha Syed Nawaz , Sallauddin Mohammad , Sidhardha Chintoju , Harshavardhan A.
Published: December 2020

Assessment is considered to play an essential function inside the Educational System. The interest of using automatic tools by human beings has been increased. So in the same way student response evaluation in education system with automatic assessment systems has grown exponentially in the last couple of years. Due to the increasing number of students and the use of online MOOC courses and lack of time and lack of consistency, assessment is shifted to automatic assessment. In this regard many of the researchers worked on it to make the assessment process easy. And they succeeded in assessment objective-type questions: i.e. multiple choices. Now here comes an interesting part is to assess the essays with automated tools. In this area, more number of researches worked and invented some tools for grading the essays but not up to the mark. Most of the assessment tools were assigning grades based on the style that is the number of sentences, the number of words, parts of speech, length of an essay, and grammar but not on the content of the essay. But few of the tools grading the essays based on the content by using traditional methods, and very few tools are using natural language processing methods.
Glımpse On Blockchaın Technology And Applıcatıons
Authors: Rao Dr. V. Chandra Shekhar , Kolluri Johnson , Phridviraj M. S. B. , Moeed Syed Abdul , Srinivas Dr. C.
Published: December 2020

The term blockchain pasteurizes the chain of blocks like linked lists which will be linked to the previous block. A blockchain is a distribted ledger of digital transactions which is decentralized and no individual, team or company has its controllability over it. However, with time, the use of blockchain has come into existence. It has wide range of applications including risk management, credit money, Internet of Things ( IoT), social networks, and financial resources. Blockchain has many benefits like decentralization, persistency, anonymity, audit ability. Blockchain is trustable one and it is very efficient. In particular, this paper gives us the detailed information about the blockchain and its applications.
RETRACTED: Hybrid Learning Method to Detect the Malicious Transactions in Network Data
Authors: Edamadaka Gayathri , Chowdary Ch. Smitha , Kumar M. Jogendra , Sai N. Raghavendra
Published: December 2020

Network has carried comfort to the world by permitting adaptable change of information; however it likewise uncovered a high number of vulnerabilities. A Network Intrusion Detection System (NIDS) supports system to system executives to identify arrange security breaks in their associations. Distinguishing past and new attacks is one of the primary difficulties in IDSs inquiries about. Deep learning, which is a sub field of AI (1980‘s), is worried about classification that depends on the structure and capability of attention so-called neural structures. The progression on such learning and classification may improve the usefulness of IDS particularly in Industrial network Control Systems to build its location rate on obscure attacks. This work tells a deep learning method to deal with actualize a viable and also improved IDS for verifying modern system with the help of RNN.
Fundamental Perception of EDGE Computing
Authors: Mannanuddin Khaja , Ranjith Kumar M. , Aluvala Srinivas , Nagender Y. , Vishali S.
Published: December 2020

Edge computing is considered as a scattered computing process module where the end user data can be executed at the end corner or at the last node of the network which is indirectly represented as “Edge”. It creates an sensory impact where the end user data is executed very closely to the original data center Alex Reznik has defined edge computing as “anything that’s not a traditional data center” will be an edge to the client who is the end user. Edge computing is closely connected to equipments of IoT devices that are mostly operated by mobile user which helps in the reaching to the expected constraints based on the response time for the real world applications. Edge computing can be implemented on any hardware IoT equipment using any type of software tools. The major aim of Edge computing is to reduce the latency levels and perform the task from the nearest possible data source. Edge computing performs on instant data which is real time data processed by the sensors or end user clients whereas the cloud computing works on BIG DATA generated from different sources and locations. In this paper, We try to represent few basics of edge computing along with its pros and cons and how it is related to machine learning and IoT.
Deep learning time series to forecast COVID-19 active cases in INDIA: a comparative study
Authors: Shaik Mohammed Ali , Verma Dhanraj
Published: December 2020

In the present situation of “COVID-19 pandemic” which devastated worldwide socioeconomic implications that led by Indian government to initiate and to perform intense procedures to control the spread and impact by dispensing the capability to predict the outbreak, which hits the crest to decrease the impact of disease and guiding the government to update its policies as required for implementing protective steps needed for “Public Health System (PHS)”. These methodologies tend to be transforming among people for improvisation of vigor system. In this paper, we investigate thoroughly the precision of various “Time series” modeling techniques for detecting “corona virus outbreak” in topmost ten different states with the maximum number of “confirmed cases” as on 31 August 2020. We implemented six different deep learning approaches on time series for comparing the values associated in datasets that relates to the progression of the virus in each state based on the population as the attained results represent the scaling of time series methods accurately and predict various affected aspects in near future.
RETRACTED: Diabeties Predection Using Biosensors
Authors: Ravinder N. , Rajesh N. , Kantha Rao V. , Praveen T. , Sridhar M.
Published: December 2020

Biosensors are little investigative gadgets that join a component of natural acknowledgment and a physio-compound transducer to change an organic sign into an electrical perusing. Their specialized allure these days lies in their solid proficiency, high affectability, and consistent limit with regards to estimation. A biosensor embedded in contact central focuses to decide the degree of tear glucose and to hand-off the information to the patient’s body siphon. The siphon can mix insulin, the missing hormone, the necessary degree. This machine evades the distinctive blood checks and implantations for interesting sorts of diabetes that are really basic consistently. Diabetes characteristics are calculated by the sensor and the algorithms of machine learning are used to obtain the solution. Glucose measurements in blood plasma are positive, suggesting that the sensor is designed to estimate physiological blood glucose levels with negligible atomic effects. We are aimed at contributing to the growing biotechnology sector, with a focus on Glucose-Oxidise Biosensor (GOB) modelling from a regression perspective through quantitative learning methods. Blood glucose monitoring was developed as an effective tool for diabetes administration. Since it is suggested to maintain typical levels of blood glucose, a progression of appropriate biosensors of glucose has been developed. The technology of glucose biosensors, including treatment tools, reliable glucose monitoring systems and non-invasive glucose detection frameworks, has been fully developed over the last 50 years. In any case, a few steps are still associated with the achievement of accurate and reliable measurement of glucose. Utilizing a few AI calculations to demonstrate the amperometric reaction of a GOB with subordinate factors under various conditions, for example, temperature, benzoquinone, pH and glucose levels. In particular, kernel-based regression techniques, such as support vector machines, are being used today as one of the best machine learning techniques. Since a GOB reaction’s affectability is emphatically connected with these needy factors, their cooperations ought to be advanced to boost the yield signal for which a hereditary calculation and mimicked tempering is utilized. This dataset is modelled by a nonlinear regression approach which uses a rather simple model of the biosensor performance to allow a very low prediction error. This demonstrates the brief history, basic principles, analytical results, and the current status in clinical practice of glucose biosensors. We report a model that is consistent with the optimization and shows a good generalization error. The results obtained show that the sensor created is a contender for persistent blood glucose checking.
Machine learning intersections and challenges in deep learning
Authors: Jamalpur Bhavana , Korra Seena Naik , Rajanala Vijaya Prakash , Sudarshan E , Yadav Bonthala Prabhanjan
Published: December 2020

Deep learning is certainly not a limited finding tactic, however, it follows several procedures and also topographies which could be associated with a huge speculum of complex problems. The strategy knows the illustrator in addition to differential attributes in a stratified way. Deep learning strategies have created a notable innovation along with sizable effectiveness in an assortment of applications with useful protection units. It is taken into account to become the greatest choice for revealing the architecture in high-dimensional relevant information by using a backpropagation process and concepts analysis. As deep learning has assisted help make significant advancements and also significant performance in many therapies, the wide-spread domain names of deep learning are service, scientific study, cancer cells diagnosis, natural language processing, medical diagnosis, handwriting recognition, trumpet call recognition, stock market study. This paper provides the intersections towards machine learning and also the challenges of deep learning.
Evaluation and scrutiny of XML files, XML empowered records and native XML records
Authors: Tharun Reddy S. , Mothe Rajesh , Ghate Sukhaveerji , Sunil G.
Published: December 2020

With the expanding prevalence of XML information and a extraordinary requirement for an information base administration framework ready to store, recover and control XML-based information in an effective way, information base exploration networks and programming businesses have attempted to react to this necessity. XML-empowered information base and local XML information base are two methodologies that have been proposed to address this test. These two methodologies are an inheritance information base framework which are stretched out to store, recover and control XML-based information. The significant goal of this paper is to investigate and look at between the two methodologies and reach to a few measures to have a reasonable rule to choose the best approach in every situation. When all is said in done, local XML information base frameworks have greater capacity in correlation with XML-empowered information base framework for overseeing XML-based information.
Findings on detection of fraud smartphone apps by ranking using mining leading sessions
Authors: Sai Hanuman Prof A , Sujan Mohan P. , Chythanya Kanegonda Ravi
Published: December 2020

The world as we know now is full of mobile users everywhere and the majority leads with smartphone users which are filled with android and iOS applications. This has produced huge development in smartphone technology at a lightning rate because the apps have become popular and a common concept. For this we are dwelling into data mining in which the concept of mining data from a specific application is tough and pivotal job. These are the methodologies we are using in this paper. We are combining these two methods of mining data and ranking fraud in app store which will be a formidable task. According to report at google play store and apple store there are 2.4 million apps as of May 2019 so that shows quick surge in the past few years. Furthermore, above 500k independent app developers competing to for all the end users. Primarily finding fraud apps is done by scanning the top apps ranked apps which will be around 30-40 of them but they are on top for short period of time i.e. few days for verifying their authenticity. However, this can’t be applied when dealing with thousands of apps for each day. Hence, we have to go for an extensive approach in which we can apply a methodology to validate each app. As the importance of mining is established so we need to mine the critical data of app which includes reviews, ratings and rankings of an app that get integrated into an algorithm that can determine the fraud. So, in this paper of discovering the ranking fraud of smartphone app, we need to develop a precise and faultless methodology that gives result of trusted apps.
Performance of Vehicle Arrival Traffic Data at Fuel Station using Queuing System
Authors: Sarla Pushpalatha , Reddy Doodipala Mallikarjuna , Endla Purushotham
Published: December 2020

Vehicle arrival is a main criterion in the delay assessment of different fuel stations. In this paper, pragmatic studies are carried out to investigate the congestion traffic flow at fuel stations. The complications at fueling points have been measured and also found the length of the queue, waiting time of the customers. The results confirmed that the vehicle arrival pattern of arterial road near the fuel station exhibit traffic congestion this finding is helpful to model the fuel station in terms of planning and designing.
Characterization Of Size Dependent Thermal Properties In Strained Nanocrystalline Powder Using Williamson – Hall Method
Authors: Endla Purushotham , Reddy Ch Krishna
Published: December 2020

In this present investigation Williamson–Hall technique has been used for the size dependent thermal properties are crystallite size, effect of strain on the Debye Waller factors, root mean square amplitudes of vibrations and Debye temperatures of nickel nanoparticles. The ball milled nanopowders has been characterized by X-ray diffraction method. The values of the crystallite size and strain obtained from the Williamson-Hall method to the experimental data were reasonable. The ball milling time increased with decreasing particle size, Debye temperature, vacancy formation energy and increasing strain, mean square amplitudes of vibrations and Debye-Waller factor for the nickel sample. The change in lattice strain particle size of the samples was explained by Williamson-Hall method. All the thermal properties of nickel nanoparticles were explained more precisely using Williamson-Hall plots, and also milling time versus thermal properties plots. The results calculated were approximately similar with the standard values.
Mathematical Modelling Of Extraction Of The Underground Fluids: Application To Peristaltic Transportation Through A Vertical Conduit Occupied With Porous Material
Authors: Ravi Kiran G , Shamshuddin Md , Balarama Krishna C , Rajesh Chary K
Published: December 2020

This paper gives a theoretical idea for extracting the underground fluids through peristalsis. Due to the similarity in aforesaid problem, peristaltic transportation of a viscous Newtonian fluid over a vertical porous conduit is studied by considering the impact of heat transfer. Presuming the long-wavelength approximation, explicit solutions are found as asymptotic expansions with reference to free convection and porosity parameters. Mathematical expressions for coefficient of heat transfer, temperature and mean flux are derived. It is experiential that for few precise values of dissimilar parameters under contemplation, the coefficient of heat transfer increases significantly as Grashof number and Eckert number increases. This narrates to optimization of heat transfer in some processes. Further, it has been observed that mean flow enhances with amplitude ratio, porosity in addition to pressure drop. This authorizes auxiliary research on the impacts of peristalsis on the flow features in vertical channels.
How the collaborative learning can strengthen the Teaching and learning process in Engineering Education
Authors: Praveena D. , Purushotham E. , Sunil Kumar J. , Vijaya Lakshmi P.
Published: December 2020

Teaching is making a difference on the lifetime of the learner, making them to be a productive member of the society. The method of teaching is completed during a well organized manner then it can improves the learners constructive, innovative thoughts, inter personal skills and provides ability to guide to future learners. collaborative learning involves the pedagogies of learner in interactive mode and involves the co operation, interaction between the learners. By making the discussion as group wise, by sharing their ideas openly learners present their subject. Collaborative learning enhances co operative nature, communication skills, builds confidence about the topic and therefore the most vital thing is it provides good idea about time management. Students. were participated within the activity in agood interactive way.
Ion Conductance, Walden Product Pressure Coefficient And Hydrodynamic Radii Of Sodium Salt Of Methane Sulphonic Acid In Water-Methanol And Water-Dmf Compositions
Authors: Radhika V. , Sunil Kumar J. , Srivani N
Published: December 2020

Ion-conductance, prfencial solvation by Walden product pressure coefficient pressure coefficient and Hydrodynamic Radii correlated with different electrolytes with in solvents is formed by diverse aspects like cohesive energy density, relative viscosity, solvent dielectric constant values of intermediate, with in duel mixture associations of its solvent adesive solvent measures. Sodium saltion solvent interactions of solute ion with solvent core. Conductance data and physical properties of ion viscosity electrolytes are used by change of the sodium salt ion conductance values, Walden product pressure coefficient and Hydrodynamic radii behavior of the ions and these are measured for derived Sodium salt of Methane Sulphonic acid electrolytein water-MeOH and water-DMF of dissimilar composition in the heat choice of 283K to 313K. A
o values KA of electrolyle sodium saltion pair, Association constant values figured out with Shedlovsky Extrapolation method. A°rise with composition of pure water solvent in organic aqueous duel mixture composition in binary sheeth. KA value is more in 80% water-MeOH composition signifying sodium saltion of sodium solvention interactions are more at this binary composition of solvention and thermodynamic properties for the function of specified sodium saltion solvent interaction in composition for structural effects.
Analysis of Self-similar Nature Vehicle Arrival Data Pattern on Arterial Roads
Authors: Sarla Pushpalatha , Reddy Mallikarjuna , Reddy Archana
Published: December 2020

Traffic congestion is a main criterion of increasing the disturbance of the movements of traffic on roads. In various metropolitan areas managing the traffic congestion is a difficult task, it was investigated that busy traffic reveals self-similarity, influenced by this aspect, realtime road traffic arrival data pattern proven as self-similar paradigm by means of disparate Hurst index methods. The current article furnishes various proficiency used to measure Hurst index which is popular demarcate of self-similar behavior traffic. In this paper, real time data is used to investigate the pattern of vehicular arrival data traffic flow at Mancherial Chowrasta intersection of Karimnagar City. Traffic arrival data patterns are recorded from location is processed and analyzed using Hurst index method named as correlogram. Quantitative results finally reveal that analysis shown in this study is supportive to manage the traffic signals at that junction, and to discover methods to avoid congestion traffic streams.
A Prediction based Encryption Approach for Telemedicine Applications
Authors: Vallathan G. , Rajani T. , Kumaraswamy Eelandula , Srinivas C.
Published: December 2020

The rapid progression of health care technologies systems and transmission strategies makes it reliable to gain, dispense and manage data over medical devices and as well improves conventional hospital information systems (HIS) to deliver effective health care services. When the medical information is communicated through wireless network, there exists a high chance of modifying the information. Before examining the patient, the physician has to check for the integrity of received medical image. A futuristic tele healthcare framework has been proposed to ensure the security, for offering complete healthcare services at reduced cost. In this paper, the proposed framework encompasses the integration of three modules viz. Prediction, Padding and Chaotic map encryption. This work offers an enhanced security for both patient medical data as well as medical scan images to a great extent. Two processes are involved in the padding sequence namely: forward and backward snail tour. After the snail tour process, the adjacent pair of pixels in the original image is XORing in order to make it ready for further process using the chaotic map encryption algorithm. Three operations have been carried out in chaotic approach namely: permutation, diffusion and substitution. This encryption method arises, a valid confusion and diffusion in the image pixels such that, the security of the images/data is enhanced. The performance of the proposed approach is assessed and compared with existing schemes such as ECC and Chaotic map encryption on a set of MRI/CT medical images. Experimental outcomes demonstrate that the proposed framework offers robustness in terms of security, quality and reliability which alleviate misdiagnosis at the physician end in telemedicine applications.
Fire Detection and Direction Control of Fire Fighting Robot
Authors: Chitti Sridevi , Ramchandar Rao P. , Padmaja Ch. , Raghava Kumari D
Published: December 2020

Detecting fire and igniting it really is a risky job which endangers a fire-fighter’s life. There are numerous fire incidents all around the world where fire-fighters each year have to risk their life during the line of responsibility. The Artificial Intelligence study and engineering is contributed significantly to Robotics. Robots have been deployed in diverse industries such as mining, construction, drugs, etc. Robotics are also used to help fire fighters in carrying out this fire prevention and thereby mitigate the risk of loss of human life. For extreme environment conditions fire fighters has been designed. After locating the fire source can entirely control the situation of area by the internet. It has a system that will control and operate through the wireless system. The fire exposure platform is built using fire-fighter robot mounted sensors. It idea aims to stimulate awareness as well as advancement in the robotics world when striving for a realistic and feasible approach to save life and reduce the possibility of harm to assets.
Sustainable development in agriculture using internet of things-A Review
Authors: Padmaja Ch , Swathi N , Anuradha P , Prashanth B
Published: December 2020

Agriculture is the primary source of food grains and livelihood of rural people in India. The importance of agriculture cannot be ignored as it is also the backbone of country’s economy. There is a remarkable change in the farming conditions for the past several years. There is uncertainty in water availability for agriculture and scarcity of natural resources due to rapid degradation and use of these natural resources but the population across the globe has grown immensely. This addresses the need for implementation of better farming methods such as precision agriculture which contributes in several ways to provide sustainability of production agriculture over a long period by producing more in less time using available natural resources. Over the last few years, there is a gradual increase in the usage of such systems. Now a day’s farmers are being trained and are using information systems to improve the crop management and for increasing the productivity. This paves a path to create a platform to manage farm activities, improve biodiversity and also to reduce the consumption of water. Such new invention in turn enhances and develops the farming. This paper analyses about how IoT is laying a strong foundation for sustainable development in agriculture.
Raspberry Pi based Intelligent Classroom Information and Management System using LBP Method
Authors: Merugu Shyamsunder , Naga Sudha D , Juluru Tarun Kumar , Rao Ramchander , Ravula Shashi Kumar Reddy
Published: December 2020

Educational organizations are gradually using multi prevention models to deal with tutorial requirements of pupils. The underpinning of those methods is that the execution of widespread practices premeditated to backing the tutorial requirements of the overwhelming widely held scholars. Investigators and experts are trying to valid measures to support teachers for effective classroom practices, which are sensitive to vary over time. Knowing the information about the classwork, students’ strength in a particular class, faculty details, passing the vital information to the students, alerting faculty with their classwork information, and automatic attendance system plays a key role in the smooth running of educational institutes or organizations. Particularly, in women colleges, passing the information about the ward to the parents and video surveillance is crucial. This paper aims at providing solutions for manual work to a great extent. The proposed system works using RaspberryPi 3 board with the display, face detection algorithm, face recognition using Local Binary Pattern method (LBP), GSM900, 4x4 Keyboard, mobile, and serial communication protocols. The new entrant to the campus will easily know about the college information and punctual working of the stakeholders in the campus. The unauthorized entry is detected using a webcam, and information is passed to the central unit for further action.
Design and Analysis of Channel Estimation of MIMO-OFDM using Whale Swarm Optimization
Authors: Samala Srinivas , Chandraprakash Tallapalli , Ramchandar Rao P.
Published: December 2020

Pilots are inserted with the OFDM symbol in the transmitter in the pilot based channel estimate and it is detected on the receiver. Three approaches are known as random, orthogonal, and Whale Swarm optimization are included in the pilots. The optimized pilot delivers better performance than the orthogonally and randomly positioned pilots do. Random, orthogonal, and whale swarm methods are supposed to utilized to examine the pilot carrier position. It is calculated that three separate algorithms are used: Least Square (LS), Least Square modified (LS-Mod), and MMSE. Several optimization algorithms have been introduced in MIMO-OFDM device channels to increase data quality, reduce BER, MSE, and SER. The performance of both of the above-proposed optimization algorithms is contrasted with the current simple algorithm and have shown improved outcomes in the MIMO-OFDM networks. The proposed optimization algorithms are implemented with the software MATLAB. To optimize the channel, the Meta Heuristic algorithm such as the whale swarm algorithm (WSA) is proposed.
Understanding Soil Erosion Protection Capabilities of Four Different Plants on Silty Soil
Authors: Gobinath R , Ganapathy G P , Salunkhe A A , Raja G , Prasath E , Kavya T
Published: December 2020

Soil is a natural wealth to human which need to be preserved, huge amount of soil is normally eroded due to rain and other activities, also anthropogenic occurrences increases the chance of erosion. Multiple methods are being employed to preserve soil erosion along hill slopes but all most of them end up as non-viable or costly. Vegetation plays key role in protecting soil from erosion, presence of vegetation increases the soil burden stability along slopes which increases the shear strength and reduce the soil erosion. In this work we had tried to study the soil binding nature of four different plant roots via soil bioengineering procedures. Primary aim of this paper is to obtain information related to the method of soil binding by the plant roots on silty-clay soil. We had studied the root growth nature and how they really tie up the soil as a monolithic mass to provide soil erosion protection. Plants were grown in pot culture allowing the plants to reach full root growth potential since roots play major role in protection soil from erosion. Triaxial shearing tests were conducted on the soil-root mass obtained using cores from soil. Also pull out tests were done to obtain the load required to pull out a fully grown root which indicates its composite ability. Also, root properties like Root Area Ratio (RAR), Root Biomass (RB), Tensile strength of root, root angle, thickness of root, deep rooting, root length density, root decay rate.
Analytical Examination of Reinforced Concrete with Hybrid Fibres Exterior Beam Column Joint
Authors: Maruthachalam D , Shyamala G , Boobalan S C , Sandhya Rani B , Muthukrishnan V
Published: December 2020

This research paper pacts with the analytical examination of synthetic fibres (Polypropylene and Recycled polyethylene terephthalate RPET) and steel fibres in reinforced exterior beam column joint by using ANSYS. Based on IS 10262-2009, M40 grade of concrete was prepared along by volume fractions up to 0.5% of synthetic and steel fibre. 9 number of exterior beam column joint with various proportions of hybrid fibre incorporated reinforced concrete specimens were tested by means of monotonic loading. Their experimental results exhibited that reinforced concrete exterior beam column joint specimens with hybrid fibre specimens achieved superior performance along with high ductility, high strength and less crack patterns. The main aim of this research paper was based on the experimental input, analytical examination by ANSYS was carried out and related with the experimental results found. The comparison showed that both the experimental and numerical results similar.
Performance of Geogrid Reinforced Concrete Slabs under Drop Weight Impact Loading
Authors: Vijay T J , Rajesh Kumar K , Vandhiyan R , Mahender K , Tharani K
Published: December 2020

Reinforced concrete (RC) structures are often subjected to extreme dynamic loading conditions, mainly caused by effects of impact loading. A countable studies have been carried out on the structural behaviour of RC slabs under static and dynamic loadings. However, it is relatively infrequent to examine the impact behaviour of RC slabs that are embedded with non-conventional reinforcement layouts. Consequently, an experimental study was performed to examine the impact behaviour of geogrid reinforced concrete slabs. A total of six RC slab specimens embedded with different combination of steel and geogrid reinforcement layers was tested under drop weight impact test. The impact response in terms of failure modes, impact energy, impact ductility index and maximum deflection produced at each impact blow were studied. The results showed that, the RC slab specimens provided with geogrid reinforcement layer at both faces of slab specimens along with the conventional reinforcement resisted the crushing of concrete by spreading the impact stress to a larger area. This configuration of reinforcement also helps to withstand for higher impact forces, thereby influencing the enrichment in impact energy and impact ductility index.
Impact and Flexural Strength Prediction of Plain Concrete with Hybrid Fibres
Authors: Vinod Kumar M , Rajesh Kumar K , Sivakumar S , Madhuriya P , Chithambar Ganesh A , Vandhiyan R , Gurumoorthy N
Published: December 2020

An experimental study on effect of fibres in impact resistance and toughness behaviour of concrete is outlined in this paper. The investigation is carried out with steel, glass and polypropylene fibre in suitable combination. Hybrid Fibre Reinforced Concrete (HFRC) means advanced concrete form manufacturedby a specific fibre mix. The main motive for adding fibres in the composite is to control cracks, enhances the impact resistance and increases the toughness characteristics of the concrete. The impact test conducted using drop weight type test apparatus and the toughness value predicted using flexural testing machine as per the standards JSCE-SF 4 and ACI respectively. Experimental findings showed that the introduction of hybrid fibers into concrete can regulate the formation and propagation of cracks due to stress competently and increase concrete strength and impact strength.
Durability Studies on the Hybrid Fiber reinforced Geopolymer concrete made of M-sand under ambient curing
Authors: Chithambar Ganesh A , Rajesh Kumar K , Vinod Kumar M , Vyshnavi  , Vandhiyan R , Gurumoorthy N , Sivakumar S
Published: December 2020

In the recent decade, there have been a lot of significant developments made in the area of Geopolymer concrete. Geopolymer concrete has been proved for its remarkable durability properties but when alterations are done to the conventional geopolymer concrete through the incorporation of fibers, the durability of the fiber reinforced concrete is uncertain. In this analysis, high elasticity modulus and low elasticity modulus fibers were inserted into geopolymer concrete made of M-sand. As ambient curing is favored in this study, geopolymer concrete is GGBS dependent. As an alkali solution, a mixture of sodium hydroxide solution and sodium silicate solution is used. Durability properties such as water absorption, sorptivity, rapid chloride penetration test, resistance to HCL attack, resistance to H2SO4attack, resistance to sulphate and marine attack are determined in this study. Significant observance has been made with respect to different proportions of glass fiber and polypropylene fiber. Glass fibers yielded fairer results compared to the polypropylene fibers. This study reviews the scope of the use of hybrid fibers made of M-sand in Geopolymer concrete.
Experimental Investigations on Chloride Permeability and Strength Properties of Concrete using Alccofine
Authors: Thangapandi K , Gobinath R , Anuradha R , Sarla Pushpalatha , Shrihari S , Sahaya Jeevarethinam J , Khaja Mueenudeen T A , Archana N , Walter J T
Published: December 2020

This paper presents the test examination done on porousness qualities of solid utilizing “Alccofine”. The evaluation picked for the examination was M-20 evaluation of cement concrete. The variety was concentrated on the examples exposed to solidify supplanted by different rates of alccofine (0, 10, 12, 14 and 16 rates separately). Casted examples are relieved in climatic temperature and solidified properties of cement are tried at 7 and 28 days and RCPT was led at 28 and 35 days and the outcomes acquired are looked at. The test outcomes show that the specimen permits 2000 to 4000 Coulombs giving medium rating according to ASTM 1202. The RCPT esteems show improved opposition for chloride penetrability and low pace of consumption chance level.