bluuebunny/crossref_metadata_2025 huggingface dataset:
Street-lights with Automated Weather Updating System and IOT Control
Authors:   Associate Professor in the Department of CSE, St.Joseph’s College of Engineering, Chennai., Justus* Dr.J. Jean , Mannish  ,   pursuing his B.E degree in Computer Science and Engineering at St Joseph’s College of Engineering, Chennai., Madhumithaa S. ,   pursuing her B.E degree in Computer Science and Engineering at St Joseph’s College of Engineering Chennai.
Published: October 2019

Street lights are very essential towards the development of a city and are unknowingly one of the most crucial factors in our day-to-day life. The street lights largely used today are based on providing lighting to citizens but, over looks on environmental issues such as heat dissipation or the amount of electricity consumed. As energy-saving and cost reduction has become crucial right now, it is necessary that we improve standards of the street lights with upcoming technologies to make it efficient. The street lights that focus on saving electricity and providing environmentally friendly lights are based on solar energy. But this implementation does not manage the solar energy used by the street lights nor supervise the power stored in the solar cell to extend the same capacity of power being used in a longer period. This results in street light wasting power in unwanted situations such as being turned on during daytime and most times not working when required such as in times of rain and during days when fog collects hindering visibility. Also, manual work is required to manage the street lights along with repairs and maintenance. Therefore, human error cannot be avoided. To overcome these situations, our solution is to automate streetlights that turn on during night and poor visibility also automatically turn off when there is sufficient light in that particular region. Battery management and street light control as a backup in case of failure or equipment damage via the network are also essential for complete automation in our implementation. Thus, this implementation accepts weather patterns via network and manages the power stored in the solar bank used to provide longer battery life in case of rain or storm in a region. Finally, it reduces the watts consumed and by extension the running cost which from the working prototype gives a power savings of 50 – 60% in terms of cost.
Food Recommendation using Classifier and Modified Apriori Algorithm
Authors:   Computer Science, Vellore Institute of Technology, Vellore, India., Dasgupta* Sreyam , Karmakar Suparna ,   Master Of Computer Applications (MCA), Cambridge Institute Of Technology (permanently affiliated to VTU), Bengaluru, India.
Published: October 2019

In today’s world, computer technologies have advanced a lot. One of its greatest gifts to the world is Artificial Intelligence. Natural Language Processing (NLP) and Machine Learning (ML) are two of its subdomains. In this paper, modified versions of two common NLP and ML algorithms have been used to classify food reviews and provide suitable recommendations from them. Currently, reviews can be classified into positive and negative reviews, but it becomes difficult when one review says positive about item A and negative about item B. Moreover, the current Apriori algorithm doesn’t consider the feedbacks from customers (reviews). Modified classifier algorithm and consequently, modified Apriori algorithm has been used to classify each statement part by part and provide recommendations, not just on previous purchases but also using the reviews about above-mentioned purchases. The algorithms can be used for purposes other than food analysis also – wherever purchases and reviews are involved. For e.g., e-commerce companies can use the algorithms to predict and recommend suitable items a user may be interested in.
Effect of Taper Manifolds with Different Slopes in Microchannel Heat Sink
Authors:   Department of Mechanical Engineering . Chandigarh University, Punjab, India, kumar* Devender , singh Harpreet ,   Department of Mechanical Engineering . Chandigarh University, Punjab, India
Published: October 2019

In this analysis, the liquid flow and heat transfer in micro channel heat sink (MCHS) to find the pressure drop are experimentally investigated by three degree slope in manifolds in addition to the arrangement of micro channels. This experimental analysis is executed with respect to the Nusselt Number and Heat transfer characteristics for three manifolds with different arrangement. We are working on this experiment at three different arrangement manifolds: Arrangement (A) is the three-degree slope in manifolds downward and upward, Arrangement (B) is the three-degree slope in manifolds upward and downward and Arrangement (C) is the three-degree slope in upward direction of the manifolds are selected. In this investigation we are using the Reynolds number ranging from 705-1411 for micro channel heat sink. The Arrangement (A) is the greater heat transfer coefficient within the increase Nusselt number and velocity and low pressure drop in comparison to Arrangement (B) and (C) type manifolds.
Feature Selection towards Soil Classification in the context of Fertility classes using Machine Learning
Authors:   Dept. of Computer Science, Graphic Era Hill University, Bhimtal, India, Pant* Janmejay , Pant Puspha ,   Dept. of Geography, M.B. Govt. P.G College, Haldwani, India,, Bhatt Ashutosh ,   Dept. of Computer Science , BIAS, Bhimtal, India, Pant Himanshu ,   Dept. of Computer Science, Graphic Era Hill University, Bhimtal, India, Pandey Nirmal ,   Dept. of Computer Science and Applications, Amrapali Group of Institute Haldwani, India
Published: October 2019

Soil is recognized as one of the most valuable entity which is responsible for sustaining life on the earth. It is clear that Indian economy is largely dependent on agriculture. In India, for a large section of the population the sole or major source of earnings is agriculture. There are many factors which are responsible in yield production and also affect agriculture. Soil is one of them and plays a crucial role in yield production. Soil nutrients are important aspects that contribute to soil fertility. In this paper we classify soil in the form of fertility index level using machine learning. We induced rule model on training data and apply this model on test data for making predictions for fertility level classes. In this paper we have used Rough Set method to classify the data based on fertility level class and calculate the accuracy of the used classifier.
Proposed Track Classification for Egyptian Railway Lines
Authors:   Construction and Building Eng. Department, Faculty of Engineering and Technology, Arab Academy for Science & Technology & Maritime Transport, Cairo, Egypt, Kotb* Akram S.
Published: October 2019

The present research paper aims to reclassify the Egyptian Railway Network taking into consideration the safety and economy factors as Egyptian Railway suffers from track maintenance shortage. Lines are classified into several groups depending on dynamic load parameters to facilitate economic studies and comparisons between the worldwide railways. Then, discussions of four Railway line classifications are studied as follows: Theoretical classification of line Sections according to ENR, Actual classification of line sections according to ENR, UIC line classification and proposed classification of line sections for ENR by following the mentioned techniques. Three objectives are studied to reclassify the Egyptian Railway tracks: determine the traffic loads for all line sections of ENR based on official train schedule for year 2019, the track classification should be continuously defined each year taking the load, train type and the running speed as the main three effective parameters. The present methodology deduce some conclusion and recommendations to ensure both track safety and economical operational.
Design of Hybrid LUT/MUX FPGA Logic Architecture for size Reduction and Performance Improvement in FPGA
Authors:   M.Tech (Vlsi And Es) Godavari Institute Of Engineering And Technology, Rajahmundry, A. P. India., Aruna* V. , Srigiri Ch. ,   Asst.Professor, Dept. Of Electronics & Communication Engg In Godavari Institute Of Engineering And Technology, Rajahmundry, A. P. India.
Published: October 2019

Hybrid configurable logic block architectures for field-programmable gate arrays that contain a blend of LUT's and solidified multiplexers that are assessed towards the objective of higher rationale thickness and diminished region. Innovation mapping advancements that focus on the proposed models are likewise perform inside Xilinx programming. Both for complex rationale square and steering territory while keeping up mapping profundity, the named engineering of this paper examine the rationale size, region and power utilization utilizing Xilinx 14.5.
Bidirectional Dc to DC Converter with Ann Controller for Hybrid Electric Vehicle
Authors:   Electrical and Electronics Engineering, Anurag Group of Institution,, Teja* Tatoju Sai , Yaseen MD ,   Electrical and Electronics Engineering, Anurag Group of Institution, Kumar Dr.T.Anil ,   HOD, Electrical and Electronics Engineering, Anurag Group of Institution
Published: October 2019

A bidirectional chopper (BDC) is the one which can interface main source (HVS), auxiliary source (LVS) and a DC-Bus voltage at different levels which is implemented in Hybrid Electric Vehicle (HEV). This converter operation is of two modes namely dual source powering mode and energy re generation mode along with power flow control in both the directions. And also the independent power flow control across two sources (i.e. the dual source buck-boost mode). The operation, closed loop control of artificial neural network (ANN) and the comparison between PI and ANN control are provided in simulation results.
Similarity Based Prediction System using Machine Learning Algorithms in Big Data Analytics
Authors:   Research Scholar, Alagappa University Karaikudi, Vanitha* M. , Geetha Dr. P. ,   Associate Professor, Dr.Umayal Ramanatha College for Womens, Karaikudi, Ramaraj Dr. E. ,   Professor and Head, Dept. of Computer Science Alagappa University, Karaikudi
Published: October 2019

Big Data is a noteworthy environment to maintain the diversity of the huge amount of data. The big data utilizes machine learning algorithms to process large datasets which comes from various places such as histories, weblogs, and data repositories, large datasets and data warehousing, etc. In an existing method, most of the data mining approaches might not be able to maintain the large dataset. Using datamining, the big data are having lack of compatibility with database systems and analysis tools; large dataset clustering and analyzing is a big issue in big data. For this reason, the research work uses machine learning algorithms which are implemented in the Hadoop tool to collect and process the large amount of data which is structured, semi-structured or unstructured in a reasonable amount of time. Also, it gives more accurate prediction system and accurate information. Using Machine Learning Algorithm computational cost and complexities is minimized. The overall research work is implemented in the Hadoop tool with the help of the python programming language and it is compared with some existing algorithms. The proposed work tested with suitable parameters such as accuracy, Kappa T and Kappa M.
Using Social Media Trends to Provide Disaster Early Warning Systems and Disaster Assessment
Authors:   CSE department, Raghu Engineering College, Visakhapatnam, India., Rao* Ch. Chakradhara , Meena B. ,   CSE department, Raghu Engineering College, Visakhapatnam, India., Kumar K. Pavan ,   CSE department, Raghu Engineering College, Visakhapatnam, India.
Published: October 2019

Tremors, floods, dry season, and other normal perils cause billions of dollars in monetary misfortunes every year around the globe. A huge number of dollars in philanthropic help, crisis credits, and advancement help are consumed every year. However endeavors to lessen the dangers of normal perils remain generally ungraceful crosswise over various risk types and don't really concentrate on regions at most astounding danger of debacle. Informal communities are assuming an undeniably significant job as early cautioning frameworks, supporting with quick debacle appraisal and post-fiasco recuperation. There is a requirement for both the general population and fiasco help offices to all the more likely see how web based life can be used to survey and react to catastrophic events. This work directs a various leveled multistage investigation dependent on numerous information assets, consolidating internet based life information and monetary misfortunes. This work attracts regard for the way that during a catastrophe, residents go to internet based life and most of tweets contain data about the tropical storm as well as its contact with negative estimation. This paper researches whether the mix of web based life and geo-area data can add to an increasingly proficient early cautioning framework and help with calamity evaluation.
CN Modeling for Predicting Discharge in Lesti Sub-watershed
Authors:   Doctoral Program in the Department of Civil Engineering, Faculty of Engineering, University of Brawijaya, Malang, Indonesia., Hoesein* Abdul Azis , Bisri Mohammad ,   Department of Water Resources, Faculty of Engineering, University of Brawijaya, Indonesia Indonesia., Limantara Lily Montarcih ,   Department of Water Resources, Faculty of Engineering, University of Brawijaya, Indonesia Indonesia., Suhartanto Ery ,   Department of Water Resources, Faculty of Engineering, University of Brawijaya, Indonesia Indonesia.
Published: October 2019

This research intends to accurately mapping the Curve Number (CN) that is as the function of cover type, land use treatment, hydrology condition, and hydrologic soil group in the Lesti sub-watershed,. The methodology consists of to build the suitable CN modeling for predicting discharge in the Lesti sub-watershed and then to evaluate the result accurately. The value of CN is obtained from the mathematical formula with the input is rainfall depth and discharge. The result of CN modeling for the Lesti sub-watershed is accurate enough as is made by the United States Department of Agriculture (USDA) in USA. In addition, the CN mapping can be directly used by the engineers of the manager and designer on the water resources structures in Lesti sub-watershed.
Farm to Fork: IOT for Food Supply Chain
Authors:   Department of Operations Management and Information Technology, Apeejay School of Management, New Delhi, India., Vermani* Dr. Shalini
Published: October 2019

Globally, population is growing and at the same time our natural resources are shrinking. Most nations are facing challenge to feed their population in 2050. To feed growing population with stressed natural resources, there is a need to produce more with less. To achieve the target of zero hunger in 2050, it is not only required to produce more but also to reduce waste-age during storage and transportation. This paper discusses the use of Internet of Things in Food Supply Chain to fulfils future demand.
Conflicts Identification among Stakeholders in Goal Oriented Requirements Engineering Process
Authors:   Sr. Full Stack Developer at T-Mark Inc., Tokyo, JP,, Suhaib* Muhammad
Published: October 2019

Requirements Analysis are the most important part of Software Engineering for both System Application Development, and project requirements. Conflicts often arise during the requirements gathering and analysis phase. This research aims to identifying conflicts during requirements gathering phase in software development life cycle, Research, Development, and Technology converted the world into a global village. During requirements elicitation/gathering phase it’s very difficult to understand the main objective of stakeholders, after completion of requirements elicitation task final results are used for Software Requirements Specification (SRS), SRS is the highly important outcome of the requirements analysis phase. this is the foundation between the developers and stakeholders or customers, proposed methodology will be helpful to identify those conflicts in very easy manner during the initial phase of the project.
Enhancement of Underwater Images using Pixel Arrangements and Image Enhancement Algorithm
Authors:   Assistant Professor in the Department of Computer Science And Engineering in SRM Institute of Science And Technology, Ramapuram, Chennai., Ashwini* Ms. C. , Yaduka Swarnim ,   student pursuing his bachelors in Computer Science Engineering in SRM Institute of Science And Technology, Ramapuram, Chennai., P.V Kiran Mayi ,   student pursuing her bachelors in Computer Science Engineering in SRM Institute of Science And Technology, Ramapuram, Chennai., Biswas Shubhankar ,   student pursuing his bachelors in Computer Science Engineering in SRM Institute of Science And Technology, Ramapuram, Chennai.
Published: October 2019

Underwater image processing is faced with a number of challenges from distinct resolutions, format variations, scattering, absorption of light etc. It is also affected by contrast difference and orientation. Conveying different resolved underwater images using enhanced pixel arrangement and image algorithm. This can be proceeded by converting the multi scale fused resolution images to high resolution images. Image enhancements has some in-built pixels properties having low intensities in at least one-color channel. Such kind of images are then converted to high resolution imaging by using the tools of enhanced pixel arrangement algorithm and then the output images are clarified.
Easy Payout, Advanced shopping, and Security in Super Market
Authors:   Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India., Priya* M.S Shiva , Agrawal Jatin ,   Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India., Roy Debayan ,   Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India., Chirra Raj Kumar ,   Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India.
Published: October 2019

Nowadays there is a very common issue among the general public that is lack of time. This lack of time has let the consumers to be impatient. Another most important threat to the shop or supermarket owners are theft. Many cases persist in robbery or theft in this modern era. Despite having security systems, alarms and security guards there exists the cases of theft. This leads to a huge loss to the market as well as the shop owners. They face a great challenge due to this. This idea is capable of reducing or rather preventing these issues to occur. This will provide consumers with an easy and time- efficient way. The idea if the project is to deduce a method for smart super-market stores that operate efficiently by reducing the time a customer spends at the billing desk. The target can be achieved by the use of smart bands designed especially for use by the super-market which will keep accumulating the price of the products taken off the racks by the customer. The total system will work on sensors and cloud monitoring which while the shopping will get updated by the user. When the customer is done with shopping, they can request an electronic bill that will allow payment in any of the available formats and will enable the customer to collect the physical bill after the successful payment of the total bill. This payment will be directly made by scanning the code in the billing counter through the band which will directly reflect the amount from the temporary cart and the payment will be proceeded in anyways according to the shopper.
The Strength Analysis of Hybrid (Bolted and Bonded) Single Lap joints for Composite Materials
Authors:   Mechanical department, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune, India., Patil* Mahesh J. , Patil Prof. Dr. Rajendrakumar N. ,   Principal, Bharati Vidyapeeth’s College of Engineering, Lavale, Pune, India.
Published: October 2019

The two joining techniques i.e. adhesive bonding and mechanical fastening combined are termed as hybrid joints. These kinds of joints mix the benefits of each the joining ways. The composite materials are used in structures at larger extend because of its properties like high strength to weight ratio, high fatigue resistance, high impact strength etc. The paper evaluates the mechanical behavior of Hybrid joint using composite as adherents subjected to tensile loading. The joint was observed to fail in two stages. Initially because of failure of adhesive and later by the failure of the bolt. The different parameters like overlap length, bolt size, tightening torque and adhesive thickness were studied and the significant factor were found to be overlap length, bolt size and tightening torque
Open Data Kit: Mobile Data Collection Framework For Developing Countries
Authors:   Mohammed V University in Rabat, EMI, Siweb Team, E3S, Morocco., Bokonda* Patrick Loola , Ouazzani-Touhami Khadija ,   MINES-RABAT School, Department of Computer Science, Morocco., Souissi Nissrine ,   MINES-RABAT School, Department of Computer Science, Morocco
Published: October 2019

To evaluate and improve the delivery of health care services and programs; to collect and share information on agro-biodiversity; to fill the gaps in the data of artisanal or industrial fisheries, the use of computer tools of data collection is a major asset. It is now obvious that most of these tools are difficult to use in developing countries. And this is because of the complexity of use, either because they are commercial solutions or simply because these tools require a stable internet connection. This study is the result of thorough research on Open Data Kit (ODK), a suite of tools fully compatible with the context of developing countries and fully open source software. This article traces the research work done for the design, implementation, and improvement of ODK. A description of the different ODK extensions that can be found in the literature is given in addition to the reasons that explain the success of ODK in developing countries. To highlight the utility of ODK, an analysis of the areas of use of ODK has been made. This analysis concludes that ODK is mainly used to improve the intervention effectiveness of health system agents in developing countries.
Export Specialization of India with Top Five Agricultural Economies: An Application of RCA and RSCA
Authors:   Mittal School of Business, Lovely Professional University, Phagwara, India., Nabi* Dr.Tawheed , Kaur Dr. Tushinder Preet ,   Mittal School of Business, Lovely Professional University, Phagwara, India.
Published: October 2019

The paper attempts to determine Revealed Comparative Advantage (RCA) and Revealed Symmetric Comparative Advantage (RSCA) of Indian agriculture sector with respect to top five agriculture exporting countries viz; USA, UK, UAE, Singapore and China. The study evaluates the structure of comparative advantage from 1995-2017. Data as per the Standard International Trade Classification (SITC-1) is used to compute RCA and RSCA index. The indices reveals the comparative advantage in case of majority of commodities like fish, fish preparations, fruits, vegetables, sugar, sugar preparations, miscellaneous food products, wood, lumber and cork. Increasing world demand for exports trailed by the competitiveness of Indian exports has played an important role in export performance..
Formation of Integrated System Development Models in the Information and Telecommunications Cluster
Authors:   Tver State Technical University (TvSTU), Tver, Russia., Samylina* Yulia Nikolaevna , Matveev Pavel Aleksandrovich ,   Russian State Social University, Moscow, Russia., Malysheva Elena Nikolaevna ,   Russian State Social University, Moscow, Russia., Fedorova Tatiana Nikolaevna ,   Tver State University, Tver, Russia., Repnikova Valentina Mikhailovna ,   Plekhanov Russian University of Economics, Moscow, Russia.
Published: October 2019

The article is devoted to the formation of integrated system development models in the information and telecommunications cluster. It has been established that the study of European experience in cluster development allows identifying the main participants in communication processes that significantly accelerate interaction using an integrated communication system. It has been proven that the key participants in communication platforms include information and telecommunications enterprises, professional communities, local authorities and government institutions that regulate the activities of cluster members, educational institutions and research institutes, technology transfer centers, business incubators, investors and cluster coordination councils. It has been determined that all these organizations will have equal access to platforms, which corresponds to the basic principles of partnership, especially the principle of transparency and openness to innovations based on mutual trust. It has been revealed that the structural-functional model of an integrated system of information and communication support for the interaction of participants shows the directions and ways of virtualizing communications on dedicated platforms.
Increasing Economic Efficiency of Cow Milk Production in the First Phase of Lactation
Authors:   Krasnodar Research Centre for Animal Husbandry and Veterinary Medicine, Kuban State Agrarian University named after I.T. Trubilin, Krasnodar, Russia., Yurina* Natalya Alexandrovna , Semenenko Marina Petrovna ,   Krasnodar Research Centre for Animal Husbandry and Veterinary Medicine, Krasnodar, Russia., Kuzminova Elena Vasilievna ,   Krasnodar Research Centre for Animal Husbandry and Veterinary Medicine, Krasnodar, Russia., Vlasov Artyom Borisovich ,   Krasnodar Research Centre for Animal Husbandry and Veterinary Medicine, Krasnodar, Russia., Konik Nina Vladimirovna ,   Saratov State Agrarian University named after I.V. Vavilov, Saratov, Russia., Galicheva Maria Sergeevna ,   Maykop State Technological University, Maykop, Russia., Chuprina Evgeny Gennadevich ,   LLC Protect & feed, Dinskaya, Krasnodar Region.
Published: October 2019

The article considers the economic efficiency of the use of the PassPro Balance feed product for lactating cows based on the increase of their productivity and reproductive qualities. The study has found that the use of the PassPro Balance feed supplement in the ration of Simmental cows during milking period increases the consumption of feed mixture by 0.9% and dry matter – by 5.4%, average daily milk yield – by 29.2% (P<0.01) and profitability level of milk production – by 7.8%, as well as reduces the service period by 5.0% and the consumption of concentrates for the production of 1 kg of basic fat milk by 22.8%.
MHD Flow between Two Parallel Plates under the Influence of Inclined Magnetic Field by Finite Difference Method
Authors:   Research Scholar, Faculty of Science, Pacific Academy of Higher Education & Research University, Udaipur, India, Sharma* Aruna , Dubewar Dr A. V. ,   Department of Mathematics, Datta Meghe College of Engineering, Airoli, Navi Mumbai, India
Published: October 2019

This study investigates the MHD flow between two parallel infinite plates. Here the upper plate is moving with constant velocity and the lower plate is held stationary and a constant pressure gradient is applied to the system which is under the influence of an inclined magnetic field. The governing equations are formulated and transformed into non dimensional form. Numerical solution of the transformed governing equations are obtained using the Finite Difference method. The fluid velocity at different inclinations of the magnetic field and different strengths of magnetic field have been shown graphically and it has been observed that the increase in the angle of inclination leads to a decrease in fluid velocity and also an increase in magnetic strength leads to a decrease in the velocity profile.
Performance of Outrigger System by Non-Linear Static Method
Authors:   Civil Engineering, Anurag Group of Institutions, JNTUH, Hyderabad, India, kumar* D. Arvind , Vimala Dr. A. ,   Civil Engineering, Anurag Group of Institutions, JNTUH, Hyderabad, India
Published: October 2019

High rise building structures are highly affected by lateral loads and wind forces. To enhance lateral force outrigger systems are developed, which are one of the most popular and efficient, because they are easier to build and they provides good lateral stiffness. With the rise of building height, deep beam become concrete walls at least of one story height. Axial shortening effect between core and perimeter structure has to be considered.In the present work 20 story reinforced concrete structure has taken with outrigger walls attached from core to the outer perimeter column. By changing the different position of outrigger level are kept for analysis.The building without and with outrigger are compared with bareframe. These are different building models analysed (a) Bare frame of twenty story building (b) Bare frame with core shear wall building (c) Outrigger system at top of building (d) Outrigger system at top & 0.75 Height of building (e) Outrigger system at top & 0.50 Height of building (f) Outrigger system at top & 0.25 Height of building. Non-linear static analysis results were compared. The analytical methods used in the work are pushover method. In this work, various parameters like pushover curve, displacement vs base force, story displacement, hinges formation are obtained for all the models.Outrigger at optimum level at 0.5 Height gives better results in both displacements and base force. To sustain peak lateral loads these systems are provided half of the height. These study gives has inelastic behaviour of structure.
An Android Application for Plant Leaf Disease Detection using Convolution Neural Network
Authors:   Assistant Professor – Senior, Department of CSE, Vellore Institute of Technology, Vellore, India, M.* Anbarasi , Garg Kartik ,   Department of CSE, Vellore Institute of Technology, Vellore, India., Garg Sakshi Darpan ,   Student, Department of CSE, Vellore Institute of Technology, Vellore, India., Babu S Yogesh ,   Assistant Professor(Selection Grade), Department of CSE, Vellore Institute of Technology, Vellore, India, Durai M.A. Saleem ,   Associate Professor, Department of CSE, Vellore Institute of Technology, Vellore, India
Published: October 2019

Plant leaf diseases and ruinous insects are an important concern in the agricultural sector. The agriculture is dependent on the agricultural productivity by the country, the better is the agricultural productivity, the better is the economy, and hence better is the GDP. The most common and useful way of boosting this economy for any country is the identification of these diseases in the plant and agricultural product that has been obtained. Developments in Deep Learning have facilitated researchers to improve the performance and in exacting systems for object detection and recognition. In this paper, we propose an image processing and Convolutional Neural Network based approach to detect the diseases affecting plants. Our goal is to develop an Android application with a suitable algorithm that will help automate the process of monitoring and detecting plant health. The proposed android application can effectively detect and identify various types of diseases with the ability to handle complex plant-area scenarios.
An Embodied Conversational Agent using Retrieval-Based Model and Deep Learning
Authors:   Faculty of Computing and Information Technology, Tunku Abdul Rahman University College (TAR UC), Johor, Malaysia., Leong* Pui Huang , Goh Ong Sing ,   Centre for Advanced Computing Technology, Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka (UTeM), Melaka, Malaysia., Kumar Yogan Jaya ,   Centre for Advanced Computing Technology, Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka (UTeM), Melaka, Malaysia.
Published: October 2019

In accordance to the Fourth Industrial Revolution, the emergence of the digital transformation alongside with the collaboration between networked machines and human beings in decision-making has attracted much attention globally. The utilization of conversational agent to convey information on behalf of human have gained popularity and been used extensively. As a result, this research intends to examine and to innovate the current corporate website by providing the capabilities to deliver instantaneously replies and reliable information through the integration of a conversational agent via deep learning, comparable to communicating with the competent customer service consultant. This study is reliant on the Artificial Intelligence (AI) to offer natural language processing (NLP) by presenting retrieval-based model and Deep Learning to enable the conversation agent to make smarter and better decision in generating reliable and up-to-date responses. Furthermore, this research intends to automate the process of minimizing the need for human interference, specifically the botmaster to perform the knowledge maintenance manually.
Representation of Indian Migrants on Google Doodle: Evidence from India
Authors:   PhD Scholar, Department of Journalism & Mass Communication, Manipal University Jaipur, Jaipur. 303007, Rajasthan, India., Khan* Mohd Aleem , Kumar Dr. Subhash ,   Associate Professor, Department of Journalism & Mass Communication, Manipal University Jaipur, Jaipur. (303007), Rajasthan, India.
Published: October 2019

This paper investigated the peoples of Indian origin who are migrated or settled in different countries and contributing immensely in various aspects of life throughout the world. Their contributions have been recognized by different mediums of communication. One of the most popular and widely accessed medium Google has played a very important role in this regard. The well-known animated feature ‘Doodle’ of Google has been a recurring phenomenon on the front page of the search engine since 1998. It has celebrated the contribution of famous individuals and cultural events at global platform. The present study deals with the portrayal of Indian migrants by Google Doodles and analyses the news coverage of Doodles by digital news media. The findings of the paper show that the doodles represent the contribution of Indian migrants through its animated feature ‘Doodle’ and got a good amount of press coverage globally. Since 1998 to 2018 total 46 Indians and 16 People of Indian origin got homage by Google. Through the analysis of the news portals we have concluded that BBC.com is the only news portal that has never published any story related to Doodle but the news portal of Indian Express has given the maximum coverage for Google doodle. Thus, Google doodle has become a vital source of information and honorary tool for referencing contributions of individuals in the present society. It is also an established fact that the global reach of doodle is a significant aspect for the growing importance of doodles. Some of the doodles like Amrita Shergil, Chandrashekhar Subhramanyan, M.F Hussain, Hargovind Khurana, Abdul Sattar Edhi, Fazlur Rehman have reached around 8 to 28 countries Google’s home page. The present study has surprised to find that Doodles which are shown in India’s Google home page or visa versa, were not displayed in neighbouring countries.
A New Cygnus Optimization Algorithm for Prediction Of Cardio Vascular Disease
Authors:   Associate Professor, P.G & Research Dept. of Computer Science, Dr. Ambedkar Government Arts College(Autonomous), Chennai, Tamilnadu, India, Shyamala* K. , Marikani T. ,   Assistant Professor, Dept. of Computer Science, Sree Muthukumaraswamy College, Affiliated to University of Madras, Chennai, Tamilnadu, India
Published: October 2019

Machine learning is an emerging field in the present day due to a massive improvement in the size of data. However, with the current studies, the prologue of artificial intelligence and medical sciences, help in averting any such category of disease. With the intention to take good decision in health care, data mining methodology and technology plays a foremost role to transmit the enormous data into valuable information. Emerging as a primary source of fatality in the early 20th century and peaking in prevalence from 1980s, Cardio-Vascular Disease (CVD) remains a major global threat. Early prediction of CVD is most vital for sensible preclusion and treatment. This paper is to investigate the work on the attribute selection approach and propose an improved Cygnus Optimization Algorithm by carrying a random search through the whole attributes, which was obtained from UCI machine learning repository. The proposed method shows 97% of accuracy, which is better than early.
Enhancing the Production Efficiency in Paper Recycling Plant through Thickness Measurement
Authors:   Department of Instrumentation Engineering, Karunya Institute of Technology and Sciences, Coimbatore, India., D* Hepsiba. , Anand L.D. Vijay ,   Department of Instrumentation Engineering, Karunya Institute of Technology and Sciences, Coimbatore, India.
Published: October 2019

The whole world is moving towards recycling or green campus; such an initiative is focused here. In order to make use of the recycled raw materials completely without any wastage, certain measurements are necessary. Such measurement is the paper or board thickness has been proposed in this paper. The paper thickness measurement plays a vital role in order to minimize the pulp wastage and increase the production rate. The measurement technique utilized for paper thickness measurement is the ultrasonic method. The ultrasonic sensor-based paper thickness measurement helps in getting optimized results of maximum utility and minimal wastage. The thickness measurement indicator is designed to monitor the paper or card board thickness in an effective way. The improves the productivity of the paper production plant.
Classification of Metabric Clinical Dataset using Naive Bayes Classifier
Authors:   Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Tirunelveli, India., Sweetlin* E. Jenifer , Ponraj D. Narain ,   Department of ECE, Karunya Institute of Technology and Sciences, Coimbatore, India.
Published: October 2019

The rapid growth of the internet and its applications makes data grow to huge volumes. The Relational Database Management Systems are inefficient to handle huge volumes of data and so nowadays, Big Data technology is being used by many organizations such as Facebook, Twitter etc. Big Data technology is very useful for organizations to take proper decisions to attain their goals and in mounting themselves organization to full fledge. The use of this technology is broadly widened across all fields of Science, Medicine, Technology, and Business, so it is mandatory to acquire knowledge about Big Data concepts. Thus, acquiring knowledge on the technological revolution from traditional Database Management System to Big Data is significant. In this paper, we have discussed about big data and its evolution, characteristics, data sources, formats, Stages of Big Data process. A huge volume of clinical dataset has been considered and it is analyzed using Naive Bayes Classifier.
Hybrid Intrusion Detection using Machine Learning for Wireless Sensor Networks
Authors:   Department of Computer Science & Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, G K* Revathi , S Anjana ,   Department of Computer Science & Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka.
Published: October 2019

This Wireless sensor network (WSN) is a network of sensors, which is capable of communicating with each other and sensing some changes in parameters such as temperature, humidity etc. Such networks are beneficial in many fields, such as military industries, health monitoring, environmental tracking, monitoring of traffic. However, WSN’s are easy to be attacked because of its properties such as untrusted broadcast transmission media, physical accessibility of sensors. So, protecting networks against attacks is one of most important issues in network and information security domain. As Sensor nodes have limited resources, authentication and encryption cannot be implemented directly to it. Hence, we propose a Hybrid Intrusion Detection System, which consists of Host Based Intrusion Detection system (HBIDS) and Network Intrusion Detection System (NIDS). In NIDS anomaly in network traffic, is detected. In HBIDS, patterns of misuse are detected from information collected at particular host or sensor. The main idea is to collect each sensor node’s data and anomaly is detected in network and this detected intrusion is compared with signatures of attack in misuse detection system.
Blockchain: To Improvise Economic Efficiency and Supply Chain Management in Agriculture
Authors:   Computer Science Engineering, Saveetha School of Engineering, Chennai, India., Reddy B* Harshavardhan , Reddy Y Aravind ,   Computer Science Engineering, Saveetha School of Engineering, Chennai, India., Rekha K Sashi ,   Computer Science Engineering, Saveetha School of Engineering, Chennai, India.
Published: October 2019

As the population of the world is growing at a rapid pace. By 2050, projections show that there will be 9.2 billion people on the planet that needs to be feed. Farmers need more sustainable and productive ways to be employed to seize a prominent place in the market with compelling profits. One effective way to do that is by using Blockchain to eliminate the middleman and scaling the product effectively. A Blockchain is a distributed and immutable ledger that holds a permanent record of transactional data. It operates as a decentralised database managed by the peers in the network eliminating the middleman. Blockchain helps the farmers to secure more profits, achieving them at least 30% more than what they are earning by currently followed conventional techniques. Especially in the Indian market, the price gap is high between producer and retailer due to the intervention of a middleman. Blockchain not only increases the profits but also ensures the authenticity of the product in real time, providing the customers and peers more information about the product as it is easier to trace the details of the product back and forth through the chain. This also enhances and regulates the price variations providing farmers with the best price they can expect for their product. This will gradually increase the involvement of more people and drives more investors towards the agriculture industry, funding more agriculture-based businesses increasing food production that can be able to feed the massive population sooner.
Random Forest: A Hybrid Implementation for Sarcasm Detection in Public Opinion Mining
Authors:   Department of CSE, SGBAU, Amaravati University, Maharashtra, India., Joshi* Ashwini M , Prabhune Sameer ,   Department of CSE, SGBAU, Amaravati University, Maharashtra, India.
Published: October 2019

Modelling the sentiment with context is one of the most important part in Sentiment analysis. There are various classifiers which helps in detecting and classifying it. Detection of sentiment with consideration of sarcasm would make it more accurate. But detection of sarcasm in people review is a challenging task and it may lead to wrong decision making or classification if not detected. This paper uses Decision Tree and Random forest classifiers and compares the performance of both. Here we consider the random forest as hybrid decision tree classifier. We propose that performance of random forest classifier is better than any other normal decision tree classifier with appropriate reasoning.
A Proposed Three Tier Framework for E-Governance Services in Indian Context
Authors:   Assistant Professor, Master of Computer Applications Department, Government College of Engineering, Karad, Maharashtra, India., Kumarwad* Dr. Laxman L.
Published: October 2019

In the course of this study, the researcher is designed the framework for successful implementation of the e-governance services in Indian context for today’s scenario. The researcher is presents a Three Tier Framework for e-governance services by implementing latest and cutting edge information technology. Researcher proposed the framework for implementing successful e-governance projects in the district, which provides electronic services at the village, Tahasil, district and state level. Researcher achieved the wide range analysis of empirical transactional data and managed to gather the information in order to provide all inclusive responses to the research problem statement, therefore, considering the satisfactory outcomes.
Efficient Multilevel Polarity Sentiment Classification Algorithm using Support Vector Machine and Fuzzy Logic
Authors:   Research Scholar, Dept. of CSE, JNTUA, Anantapuramu, India., Krishna* B. Vamshi , Pandey Dr. Ajeet Kumar ,   Delivery Manager, Dept. of RAMS, L&T Technology Services, Bangalore India., Kumar Dr. A.P Siva ,   Asst. Professor, Dept. of CSE, JNTUA, Anantapuramu, India.
Published: October 2019

This paper discusses an efficient algorithm for sentiment classification of online text reviews posted in social networking sites and blogs which are mostly in unstructured and ungrammatical in nature. Model proposed in this paper utilizes support vector machine supervised learning algorithm and fuzzy inference system for enhancing the degree of sentiment polarity of text reviews and providing multilevel polarity categories. Model is also able to predict degree of sentiment polarity of online reviews. The model accuracy is validated on twitter data set and compared with another earlier model.
Development of CAGeD Observation Station and Its Impact on Coastal Process
Authors:   Department of Infrastructure and Geomatics, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia., Salleh* Sr. Dr. Anuar Bin Mohamad , Nadzir Nursyahillah binti ,   Department of Infrastructure and Geomatics, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia.
Published: October 2019

Universiti Tun Hussein Onn Malaysia (UTHM) collaboration with the Center of Applied Geomatics for Disaster Prevention (CAGeD) had developed an observation station as a catalyst for oceanographic and environmental research work and landmark of development in Tanjung Laboh. In conjunction with the construction of the station, monitoring of coastal process was carried out to identify the characteristics of sediment as input to the transportation of sediment around the construction area of the station in Tanjung Laboh. 20 points of surface sediment sampling were carried out along 200 meters of Tanjung Laboh bay during high tide. At the same time, the current speed test was carried out at the same point to identify the relationship of current speed to the transportation of sediment. All collected sediment samples have performed a test using wet sieve analysis (hydrometer), dry sieve analysis and specific gravity. The result found that the specific gravity of sediment at the study area is 2.53 and categorized as marine clay. The particle size distribution of sediment at the study area is silty clay due to the dominant of silt fraction. The percentage of sediment characteristics can be influenced by current velocity and sediment transportation.