bluuebunny/crossref_metadata_2025 huggingface dataset:
Smart Class Room Monitoring System
Authors:   Professor, Department of ECE, Rajalakshmi Engineering College, Chennai, India, B Dr Priya , V. Radhamani ,   Assistant Professor, Department of ECE, Rajalakshmi Engineering College, Chennai, India, P. Santhana Prasanth ,   Department of ECE, Rajalakshmi Engineering College, Chennai, India, S. Suchitra ,   Department of ECE, Rajalakshmi Engineering College, Chennai, India, S. Suganthi ,   Department of ECE, Rajalakshmi Engineering College, Chennai, India
Published: January 2020

Now-a-days the class rooms are equipped with modern technologies like smart board, LCD projectors, flexible displays etc. These classrooms are called as smart classrooms. Due to diverse demands on student time, attendance is falling down even though the enrollment is rising. Our proposed system provides the solution to address this issue. The proposed system can be implemented in an economical and precision manner. It consists of students density monitoring system and digital notice board presentation. If the classroom has sufficient student strength, then the controller enables the smart display and plays a lecture corresponding to the scheduled subject. This ensures the student strength in the class and avoids the idle classroom scenario in the absence of teaching faculty.
Local Aggregation Scheme for Data Collection in Periodic Sensor Network
Authors:   Assistant Professor, Department of Computer Science & Engineering, Deenbandhu Chhotu Ram University of Science and Technology, Murthal, Sonipat, Haryana India., Verma Neetu , Singh Dinesh ,   Assistant Professor, Department of Computer Science & Engineering, Deenbandhu Chhotu Ram University of Science and Technology, Murthal, Sonipat, Haryana India.
Published: January 2020

Data aggregation is an important technique for data collection & aggregation in WSN where sensor nodes sense the raw data and sends the aggregated data to the sink node. In a cluster based periodic network, sensor node senses the data on a specific time interval, performs local aggregation and send aggregated data to Cluster Head (CH). Various Local aggregation algorithms are used to remove redundant data at sensor nodes but local outlier detection problem is still unsolved. Therefore, a local aggregation algorithm has been proposed which uses the temporal correlation property of WSN to eliminate redundant and local outlier data which improves the data sent ratio and data quality. Sensor measurement is collected at different time interval of a sensor, exhibits temporal correlation because measurements varies with small or same difference (δ) and measurements are treated as similar measurements. In proposed local aggregation approach, each sensor node finds similar measurements of sensors with their frequency (number of occurrence) in a specific time interval (Temporal correlation). Set having higher frequency is selected and transmitted the average values of measurements that lie in the selected set to the cluster head. If sensors don’t detect any reading between intervals it simple send a message ‘data not found’ instead of sending empty set. In this way we delete redundant and local outliers. The experimental result shows that algorithm improves the data quality and data sent ratio by eliminating redundant data and local outliers.
Gate Pass System
Authors:   Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India., Shree Medha , Chopdar Shreya ,   Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India., Shambhavi  ,   Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India., Sellam Dr .V. ,   Assistant Professor, CSE, SRM Institute of Science of Technology, Chennai, India.
Published: January 2020

The objective of this work is to make the hectic process of getting a gate pass easier and less stressful. This also saves time and is paperless unlike the traditional method. It uses the modern technology and is handled online. The process involves registration, verification and granting permission to the students on the same platform. Thus saves the legwork. It's a faster process. And various measures are taken to make it foolproof. This project helps the hostellers in SRMIST to apply for gate-pass. The goal is to create an easier platform to manage the out pass request rather a traditional method of writing in papers. The goal of this project is to create a user friendly application which will be time saving for both student as well as the authorization.
Energy Harnessing System using Thermoelectric Generator with Radiation Concentrator and Solar Tracker
Authors:   ECE Department, Don Honorio Ventura State University, Cabambangan Bacolor Pampanga., Castro Mark Anthony A. , Deysolong Jerwin F. ,   ECE Department, Don Honorio Ventura State University, Cabambangan Bacolor Pampanga., Tolentino Anthony S. ,   ECE Department, Don Honorio Ventura State University, Cabambangan Bacolor Pampanga
Published: January 2020

Harnessing systems gather the attention of many researchers today as the energy demand increase with an escalating price of fuel. Studies about renewable resources are kept being pursued by different countries to aid the deficiency of main power producers in their respective locality. Thermoelectric generators, which utilize the Seebeck effect to convert heat into usable electric energy, is the main focus of this study. It has been added with a radiation concentrator and solar tracker to maximize the heat accumulation for larger temperature difference which results to a great amount of stored energy. The energy coming from the sun is focused and concentrated using a Fresnel lens to optimize the heat and increase the output of the thermoelectric generator. The energy is then inserted in a charge controller to have a constant dc voltage output. The output voltage now will be utilized by low powered and devices and has a backup battery storage for the energy.
Medical Applications using Blockchain and Machine Learning
Authors:   Assistant Professor, (Sr. G), Department of CSE, SRM Institute of Science and Technology, Chennai, India, Kumar Mr. S. Arun , Chakraborty Agniva ,   Scholar, B Tech, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India.
Published: January 2020

Blockchain was particularly used in Cryptocurrency technologies. Prior to 20th century there was no other technologies for determining the health of a person naturally. At the dawn of the 21st Century machine learning played a vital role in determining the health of a person using various algorithms and natural language processing techniques. Now for every machine learning technique to work for it needs data. Data is very important as far as providing information is concerned. Data sharing plays a vital role in improving accuracy of techniques involved. Along the blockchain technology plays a vital role in this aspect. Thus, the merging of these two techniques involve provides highly accurate results in terms of machine learning with privacy and reliability of Blockchain technology. This technique uses natural language processing techniques which focuses basically mainly on healthcare techniques such as cancer detection, prediction of machines used in healthcare etc. Prior to healthcare which is used in blockchain it was used in cryptographic techniques only. Also, this technology can be used to provide medical suggestions to the doctors based on the condition of the patient. The accuracy of this method can be increased more using providing as much data as we can. This combination of Blockchain and machine learning algorithms can be used widely in healthcare, where the data is highly secured and there is no fear of data loss. This paper involves how combining these two technologies can be helpful in healthcare.
Optimization of Productivity Measures to Improve Performance of Selected Banks – Indian Perspective
Authors:   Asst. Professor in Finace, Dr. BR Ambedkar Institute of Management and Technology, Hyderabad-44, Sumalatha P.
Published: January 2020

Efficiency or productivity is one of the significant estimates which help in measuring the development and advancement of economy of the nation. The efficiency has a pivotal influence in authoritative accomplishment of greatness which is basic for dynamic culture. Ideal efficiency of an organization relies upon coordination between all data sources that yield most extreme gainfulness with least exertion. Thus the present research is centre around a goal of recognize and look at the components impacting the efficiency just as benefit execution of selected banks in India both in public and private sector. For which a sample of twenty banks were selected. The time frame considered for the research is ten years from 2008 to 2018. The procedure which is utilized in the present research is correlation analysis which explains the connection between the selected factors. Regression analysis is also utilized to dissect the effect of selected independent factors, for example, magnitude of sales, value addition, cost of sales, profit before tax (PBT) of each worker. Dependent factors encompass of return on assets and return on value addition by fixed assets. Furthermore, free example test is utilized to survey the connection among profitability and execution proportions of selected banks in India both in public and private sector. In this manner, the outcomes from correlation analysis demonstrate that practically all the independent factors aside except from sales volume and cost of sales in selected banks in India both in public and private sector. Results from regression analysis shows that business per worker is having noteworthy negative effect on ROA.
Estimation of Mode-III Interlaminar Fracture Toughness in GFRP Laminates
Authors:   Department of Aeronautical Engineering Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology Chennai, Kumar J.V. Sai Prasanna
Published: January 2020

The composite material is heterogenous in nature has several applications ranging from sports to defence industries replacing the conventional materials. Assessing the strength composite material for out of plane delamination characterization is a challenging task. One of the test specimens which can simulate the out of the plane loading is the Edge crack torsion (ECT) specimen, to study thedelamination growth in composite laminates in a controlled environment. For the present work a fixture was developed to simulate out of plane loading and hence to estimate mode-III fracture toughness. The testcoupons werecast using from bi-directional satin glass fibre woven mat, subsequently a starter crack was introduced in the mid plane. A 100 KNInstron Universal test loadingframe was used in static condition. It was observed that the crack growth did initiate from specimen centre.The fracture parameter experimentally measured was found to bedependent on the crack growth.
Optimisation of Smart Water to Enhance Oil Recovery Efficiency in a Part of Oil Field of Upper Assam Basin, India
Authors:   Department of Petroleum Engineering, DUIET, Dibrugarh University, Dibrugarh-786004, Assam, India., Saikia Bhaskarjyoti , Das Prof. Minati ,   Department of Petroleum Technology, Dibrugarh University, Dibrugarh, Assam, India,
Published: January 2020

Researchers have proved the significance of water injection by tuning its composition and salinity into the reservoir during smart water flooding. Once the smart water invades through the pore spaces, it destabilises crude oil-brine-rock (COBR) that leads to change in wettability of the reservoir rocks. During hydrocarbon accumulation and migration, polar organic compounds were being adsorbed on the rock surface making the reservoir oil/mixed wet in nature. Upon invasion of smart water, due to detachment of polar compounds from the rock surfaces, the wettability changes from oil/mixed wet to water wet thus enhances the oil recovery efficiency. The objective of this paper is to find optimum salinity and ionic composition of the synthetic brines at which maximum oil recovery would be observed. Three core flood studies have been conducted in the laboratory to investigate the effect of pH, composition and salinity of the injected brine over oil recovery. Every time, flooding has been conducted at reservoir formation brine salinity i.e at 1400 ppm followed by different salinities. Here, tertiary mode of flooding has been carried out for two core samples while secondary flooding for one. Results showed maximum oil recovery by 40.12% of original oil in place (OOIP) at 1050ppm brine salinity at secondary mode of flooding. So, optimized smart water has been proposed with 03 major salts, KCl, MgCl2 and CaCl2 in secondary mode of flooding that showed maximum oil recovery in terms of original oil in place.
Navigation Environment In A Medical Institution: An Eye-Tracking Examine
Authors:   Senior Research, Department of Biology, Research Institute of Physiology and Fundamental Medicine, Novosibirsk., Brak Ivan , Rusina Vlada ,   Laboratory Assistant, Research Institute of physiology and fundamental medicine, Novosibirsk.
Published: January 2020

Navigation and wayfinding are well-known issues that people face in their life every day. In many situations, and especially in the case of medical facilities, it is vital that users find the desired destination quickly and successfully. This is not only about comfort, but also about life and health safety. In this regard, the development of an effective navigation system becomes an extremely important mission for health care institutions. Therefore, the eye-tracking technology, which makes it feasible to look at the problem through visitor’s eyes, appears to be a pertinent tool for an objective assessment of the existing navigation, as well as finding ways to optimize it. This article considers present approaches to the analysis of navigation systems dealing with a large number of clients and describes our visual navigation study conducted in a health center. The first part of our study included the current navigation environment evaluation and the decision-making points detection, serving as a starting point for the implementation of a new, user-oriented navigation in the medical center. In the second part of the study the effectiveness of the applied system was confirmed. The results obtained show that navigation environment improvement can significantly reduce users’ time to reach the goal, as well as length of their route. Thus, we managed to apply the eye-tracking method to the improve user experience in a medical establishment.
Extracting and Transforming Heterogeneous Data from XML files for Big Data
Authors:   Department of Information Technology, Gauhati University, Guwahati, India., Das Tanuja , Saha Ramesh ,   Department of Information Technology, Gauhati University, Guwahati, India., Saha Goutam ,   Department of Information Technology, North Eastern Hill University, Shillong, India.
Published: January 2020

Digital technology is fast changing in the recent years and with this change, the number of data systems, sources, and formats has also increased exponentially. So the process of extracting data from these multiple source systems and transforming it to suit for various analytics processes is gaining importance at an alarming rate. In order to handle Big Data, the process of transformation is quite challenging, as data generation is a continuous process. In this paper, we extract data from various heterogeneous sources from the web and try to transform it into a form which is vastly used in data warehousing so that it caters to the analytical needs of the machine learning community.
Polytechnic Student’s Readiness Towards Project Based Employment
Authors:   Department of Engineering Education, Faculty of Technical and Vocasional Education, UTHM, Batu Pahat, Malaysia., Heong Yee Mei , Mohamad Nurfarah Aliah Binti ,   Faculty of Technical and Vocasional Education, UTHM, Batu Pahat, Malaysia., Zubir Raudhah Adibah Binti Ahmad ,   Faculty of Technical and Vocasional Education, UTHM, Batu Pahat, Malaysia., Ching Kok Boon ,   Department of Electrical Engineering, Faculty of Electrical and Electronic, UTHM, Batu Pahat, Malaysia., Kiong Tee Tze ,   Department of Professional Education, Faculty of Technical and Vocasional Education, UTHM, Batu Pahat, Malaysia.
Published: January 2020

Project Based Employment (PBE) is the current trend in employment that is gaining momentum. The growing need for PBE has led to the need for employees with high knowledge and skills as well as good attitude. The aim of this study is to identify the readiness of polytechnic students towards PBE in two Conventional Polytechnic from the southern zone states. This study employed a survey method. A total of 361 students comprised of first, second and third year from Civil Engineering, Electrical Engineering and Mechanical Engineering courses from Politeknik Melaka and Politeknik Port Dickson were selected as study samples. The instrument of this study is a questionnaire with the alpha value .919. Data obtained were analysed using SPSS software version 21.0. Descriptive analysis in the form of mean score was used to identify the readiness of polytechnic students towards PBE. The findings show that polytechnic student`s readiness is in high level in terms of knowledge, skills and attitude towards PBE. From the knowledge aspect, polytechnic students know that PBE can provide employers with skilled and knowledgeable employees. Meanwhile, from the employability skills aspect, it shows that polytechnic students have the ability to interact well when working in groups. From the technical skills aspect, polytechnic students can complete their practical work by using the right equipment corresponding with the current PBE demands. From the attitude aspect, polytechnic students are always trying to develop themselves in the field they are involved in. In conclusion, polytechnic students are ready to face PBE in the future and they have initiative to improve their knowledge, skills and attitudes to the higher level to align with current industry demand. Overall, the results of this research have been able to help graduates and other educational institutions to improve and enhance the quality of students in line with the country's demand.
Twin Band-Notched Ultrawideband MIMO Antenna
Authors:   Department of ECE, Sri Satya Sai University of Technology and Medical Science, Sehore, Bhopal, Madhya Pradesh, India,, Nayak R. Samba Siva , Karpagavalli Dr P. ,   Department of ECE, Sri Satya Sai University of Technology and Medical Science, Sehore, Bhopal, Madhya Pradesh, India
Published: January 2020

In this article, we have presented various techniques that are used for improving different parameters related to UWB antenna. In this Paper, we planned for MIMO antennas in contemporary wireless communication which enhances the bandwidth and gives compact antennas. The antenna band we notched is of planned MIMO which offers an bandwidth with the operational band-notched. The bandwidth capacity of the antenna is from 2.93-20 gigahertz with sharp rejection at WLAN-band with isolation of not exactly - 22 dB is accomplished for the whole band, by utilizing a simple modified shaped structure in the bottom plane, port isolation and transmission capacity are improved. The diversity execution performance is likewise contemplated and whole outcomes shows it’s a potential point of using MIMO based diversity antenna for ultra wide band applications which is demonstrate in this paper. The parameters to assess the performance of the MIMO are explained, the whole examination completed in different sections has been outlined.
Framework towards the Process of Estimating or Predicting Perceived QoE Based on the Datasets Obtained From the Mobile Network
Authors:   Faculty, Department of IT, Kakatiya University College of Engineering and Technology, Warangal, India., Priyanka Damera , Soujanya Mamidala ,   Faculty, Department of IT, Kakatiya University College of Engineering and Technology, Warangal, India., Moeed Syed Abdul ,   Assistant Professor, Department of CSE, Kakatiya Institute of Technology and Science, Warangal, India.
Published: January 2020

Nowadays, the research study community visualizes a standard shift that is going to put the focus on Quality of Experience metrics, which relate directly to complete consumer satisfaction. Yet, determining QoE coming from QoS sizes is a daunting job that powerful Software Defined Network operators are currently able to tackle through artificial intelligence strategies. In this paper, our experts pay attention to a few essential QoE factors, and we to begin with proposing a Bayesian Network design to anticipate re-buffering proportion. This paper suggested a structure for modeling mobile network QoE, making use of the vast records analytics approach. The planned platform explains the method of estimating or forecasting perceived QoE based upon the datasets obtained or collected from the mobile network to enable the mobile network operators efficiently to deal with the network functionality as well as supply the individuals an adequate mobile Internet QoE.
Detection and Prevention of Manet using Hybrid SVM with Ann
Authors:   PHD Scholar IGKPTU, Jalandhar, India, Walia Vishal , Malhotra Dr. Rahul ,   Director , Guru Teg Bahadur Khalsa Institute of Engineering & Technology, Chhapianwali, Malout, India
Published: January 2020

Mobile Ad hoc Networks (MANET) have been exceptionally vulnerable against attacks because of the dynamic and self-configurable nature of its system foundation. This kind of wireless network is appropriate for temporary communication linked due to its nature of less-foundation and there is no any control of centralized manner. Design a routing mechanism that are security aware with higher QoS parameter is very competetive and the major tasks involved in ad hoc types of network as per the limited power resources and their dynamic routing topology. This paper mainly focused on the design of a secure and trusts based on-demand routing mechanism using Ad-hoc on demand distance vector (AODV) protocol to compute trust-based produces path initialed from source up to destination that will fulfill minimum two end-to-end QoS parameters of network. So here, the generalized AODV routing protocol has been extended from traditional routing mechanism to analyze the performance of this model with combination of artificial intelligence concept. The proposed ad hoc based routing mechanism is used to found possible routes that are prevented through trust adjacent position of security validation protocols and enhanced link optimized route computes on the basis of Artificial Neural Network (ANN) as an artificial intelligence algorithm for well-organized communication in MANET. In addition, this research demonstrates the effectiveness of bio inspired Firefly Algorithm (FFA) as an optimization approach with the consideration of several performance QoS metrics of network. The results have been measured in terms of throughput and PDR with SVM and ANN approach. It has been observed that the throughput and PDR measured using ANN approach is better compared to SVM approach an average of 0.755 PDR value has been obtained using ANN approach.
Image Water-Marking/De-Watermarking using Spatial Domain Technique
Authors:   Assistant Professor, Department of Electronics & Telecommunication Engineering, G.H. Raisoni College of Engineering & Management, Amravati, Maharashtra, India., Honade Dr. Shrikant , Ingole Ruchita K. ,   Department of Electronics & Telecommunication Engineering, G.H. Raisoni College of Engineering & Management, Amravati, Maharashtra, India.
Published: January 2020

There are various existing techniques for cryptography and watermarking. The multimedia data security can be achieved by means of encryption and decryption i.e. cryptography. While watermarking is employed for hiding multimedia data using images. The proposed work focuses on the new method combining these strategies for producing effective solution to improve security of secrete multimedia data. In the proposed dissertation work the images will be used as multimedia data. The proposed method involves the encryption of data to be hid. The cover image is then used as the media for hiding encrypted data. The encrypted data combined with cover image is treated as embedded image. The embedded image then compressed using wavelet transforms compression.
Early Dementia Diagnosis Based on DNN Based Correlational Analysis and Fisher Criterion Based LDA using Morphological Brain Multiplexes
Authors:   Research Scholar, PG Research and Computer Application, Hindustan College of Arts and Science, Coimbatore. India., V Ambili. A. , Kumar A.V. Senthil ,   Director, PG Research and Computer Application, Hindustan College of Arts and Science, Coimbatore. India., Dutta Amit ,   Deputy Director, All India Council for Technical Education New Delhi, India.
Published: January 2020

The expanding recurrence of dementia happening is a disturbing patterning that has incited dire research intending to avert the improvement of the sickness. Diagnosing dementia in its beginning periods is an urgent advance in averting the improvement of the ailment into exacerbated side effects. Early mild cognitive impairment (EMCI) is the early symptom of dementia. This can be analyzed using mapping mind associations utilizing Magnetic Resonance Imaging (MRI). In the approach, for improving the correlational block, we presented an enhanced classifier also, for improving the performance of discriminative block, an optimized LDA is to be proposed. For correlational analysis, Deep Neural Network (DNN) is presented in this work. Besides, for discriminative analysis, a novel and efficient feature selection method is presented. Fisher criterion is used to select the most discriminatory and appropriate features to ensure consistent feature selection and classifier learning goals and to improve the classifier's performance. In the Mat lab framework this proposed method is implemented. The performance of this proposed approach is evaluated concerning Accuracy, Sensitivity, and Specificity.
Hoax News Classification using Machine Learning Algorithms
Authors:   Information Security and Networking Research Group (In FORSNET), Faculty of Information Communication Technology, Universiti Teknikal Malaysia Melaka, Malaysia., Yuliani SY. , Sahib Shahrin ,   Information Security and Networking Research Group (InFORSNET), Faculty of Information Communication Technology, Universiti Teknikal Malaysia Melaka, Malaysia., Abdollah Mohd Faizal Bin ,   Information Security and Networking Research Group (InFORSNET), Faculty of Information Communication Technology, Universiti Teknikal Malaysia Melaka, Malaysia., Ruskanda Fariska Z. ,   School of Electrical Engineering and Informatics, School of Electrical Engineering and Informatics, Indonesia.
Published: January 2020

Hoax news on social media has had a dramatic effect on our society in recent years. The impact of hoax news felt by many people, anxiety, financial loss, and loss of the right name. Therefore we need a detection system that can help reduce hoax news on social media. Hoax news classification is one of the stages in the construction of a hoax news detection system, and this unsupervised learning algorithm becomes a method for creating hoax news datasets, machine learning tools for data processing, and text processing for detecting data. The next will produce a classification of a hoax or not a Hoax based on the text inputted. Hoax news classification in this study uses five algorithms, namely Support Vector Machine, Naïve Bayes, Decision Tree, Logistic Regression, Stochastic Gradient Descent, and Neural Network (MLP). These five algorithms to produce the best algorithm that can use to detect hoax news, with the highest parameters, accuracy, F-measure, Precision, and recall. From the results of testing conducted on five classification algorithms produced shows that the NN-MPL algorithm has an average of 93% for the value of accuracy, F-Measure, and Precision, the highest compared to five other algorithms, but for the highest Recall value generated from the algorithm SVM which is 94%. the results of this experiment show that different effects for different classifiers, and that means that the more hoax data used as training data, the more accurate the system calculates accuracy in more detail.
DCNN: The Density, Cluster Centers and Nearest Neighbors using Intrusion Detection Algorithm
Authors:   M. Tech Dept. of CSE, Chadalawada Ramanamma Engineering College, Tirupati, India., Lavanya Ms. M , Prasad Mr. K Munivara ,   Associate Professor, Dept. of CSE, Chadalawada Ramanamma Engineering College, Tirupati, India.
Published: January 2020

Most current intrusion detection system employ signature based methods or data mining based methods which rely on labeled training dat. This training data is typically expensive to produce. Intrusion detection aims to detect intrusion behavior and serves as a complement to firewalls. It can detect attack types of malicious network communications and computer usage that cannot be detected by idiomatic firewalls. Many intrusion detection methods are processed through machine learn- ng. Previous literature has shown that the performance of an intrusion detection method based on hybrid learning or integration approach is superior to that of single learning technology. However, almost no studies focus on how additional representative and concise features can be extracted to process effective intrusion detection among massive and complicated data. In this paper, a new hybrid learning method is proposed on the basis of features such as density, cluster centers, and nearest neighbors ii(DCNN). In this algorithm, data is represented by the local density of each sample point and the sum of distances from each sample point to cluster centers and to its nearest neighbor. k-NN classifier is adopted to classify the new feature vectors. Our experiment shows that DCNN, which combines K-means, clustering-based density, and k-NN classifier, is effective in intrusion detection.
Decomposition of Regional Development Shifts
Authors:   Ufa Federal Research Center of the Russian Academy of Sciences, Ufa, Russia., Akhunov R.R. , Yangirov A.V. ,   Ufa Federal Research Center of the Russian Academy of Sciences, Ufa, Russia.
Published: January 2020

Subject. No breakthrough in the economic development of the Russian Federation could be achieved without the maximum utilisation of the inner regional potential. This implies high relevance of studies concerning the aspects of influence produced by internal and external factors on regional development, as well as analyses of the existing conditions at the macroeconomic level that support or hinder the engagement of inner regional reserves and opportunities in the regions' socioeconomic development. This would make the basis for a more comprehensive view of the regional system and its inherent properties, helping to identify ways to manage regional development. Objectives. Analysis and decomposition of developmental shifts in the Russian regions and their classification based on internal and external influences. Methods. The primary research method is the shift-share analysis method. The methods of logical and statistical analysis, particularly, correlation analysis, are also used. Results. The driver effects of shifts are calculated at the national, industry, and regional levels for 80 regions of the Russian Federation and the period comprising two time points, 2012 and 2017. The regional and industry effects are analysed by the types of economic activities. It is established that, firstly, the regional effect is negative for most regions and, secondly, the industry effect (in combination with the national effect) acts to smooth out the negative regional effect. Conclusions. A conclusion is made that positive shifts can be achieved both in strong and weak regional economies. Generally, the shifts in Russian regions are mostly influenced specifically by the internal regional conditions, which are mostly adverse, suggesting high importance of regional effects. The research highlights the significance of industry policies at the federal level, primarily in economic activities such as agriculture and manufacturing, and the need for improvement of regional policies implemented at the federal level to raise the number of self-developing regions.
Computer Based Bone Breakage Detection using Machine Learning Techniques
Authors:   Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India., Neelakanteswara P. , Chakravarthy G Kalyan ,   Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India., Madupu Ram Kumr ,   Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India., Sudarsa Dorababu ,   Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India.
Published: January 2020

X-Ray is one of the most commonly used medium to extract the images of any bone in the body.Fracture of a bone is most common in recent days due to accidents or any means.In order to detect whether there is a fracture or not the orthopaedics suggest for x-ray.In many places due to more patients there might be a delay of doctor consult which may leads to the increase in the severity of problem.In order to avoid this we have proposed an automatic bone fracture detection system where a system is trained about the fractures and further used to detect the fractures in a bone in the x-ray images.ANN,PNN.BPNN are the classifiers used for bone fracture detection where BPNN has given more prominent results compared to ANN and PNN with an accuracy of 82%.
SSR Based Slotted Patch Antenna with Integrated Wave Guiding structure for 5G Application
Authors:   Research Scholar, Department of Electrical & Electronics Engineering, School of Engineering, University of Petroleum & Energy Studies, Dehradun , India, Dandotia Rajeev , Mishra Ranjan ,   Department of Electrical & Electronics Engineering, School of Engineering, University of Petroleum & Energy Studies, Dehradun , India., Mishra Raj Gaurav ,   Department of Electrical & Electronics Engineering, School of Engineering, University of Petroleum & Energy Studies, Dehradun , India, Bhaskar S. M. ,   Scientist G, GoI, New Delhi, India., Kuchhal Piyush ,   Department of Physics, School of Engineering, University of Petroleum & Energy Studies, Dehradun , India
Published: January 2020

An electrical small microstrip patch antenna with guided SIW slotted configuration is investigated in this paper. In the proposed design the primary antenna patch includes a slotted SRR configuration which later converted into concentric SRR slotted configuration. Here the antenna patch with concentric slot contributes dual-band resonance. The impedance matching at both the resonance is improved with guided SIW slotted structure. The proposed antenna patch incorporates a slot inside the concentric slot to correct the pattern asymmetric. The proposed antenna shows resonance at 28 GHz and 37.5GHz for mmWave 5G applications. The proposed antenna is implemented with a physical dimensions of 4.7mm ×2.7mm × 0.8mm.
Identification of Traffic Accident Hotspots using Geographical Information System (GIS)
Authors:   Professor, Department of Civil Engineering, CMR Institute of Technology, Bengaluru, India, Srikanth Dr. Lakshmi , Srikanth Ishwarya ,   Graduate Research andTeaching Assistant, Department of Civil, Environmental and Geomatics Engineering, Florida Atlantic University, Boca Raton. FL 33431, USA., Arockiasamy Dr. Madasamy ,   P.E., P. Eng., Fellow ASCE, Professor, Department of Civil, Environmental and Geomatics Engineering, Florida Atlantic University, Boca Raton, FL 33431, USA
Published: January 2020

Limiting the number andseverity of traffic accidents is one of the major goals of road traffic safety management.The alarming rate of road accidents globally emphasizes the importance of an effective traffic safety management system. Identification of accident hotspots is the first step towards implementation of efficient traffic safety management.Until the arrival of Geographical Information System (GIS),traffic accident analyses have been performed based ontraditional statistical methods alone. The advent of GIS-based techniques has led toimproved traffic accident analysis by employing spatial statistics,enabling engineers and researchers to account for variation in the spatial characteristics of hotspot locations in the analysis. This paper discusses the different spatial and statistical methods that are employedintraffic accident hotspots identification. An example application of Planar Kernel Density Estimation (PKDE)for hotspot identification is presented based on crash data for Des Moines city of Iowa state. The effect of varying bandwidths in creating density mapsis investigated and the optimum bandwidth to obtain distinct hotspots is identified as 500 m for the chosen study area.The paper also discusses the scope for future research in traffic accident hotspot analysis.
Design of a Stand-Alone Rooftop PV System for Electrification of an Academic Building
Authors:   Saroj Mohan Institute of Technology, Guptipara, Hooghly, India., Misra Debajit
Published: January 2020

Solar energy is one of the most promising options of renewable energy in the context of energy sustainability. Nowadays, as the utilization of solar energy has been continuously expanded in wide scale, researches related to the topic have been carried out all over the world. The prime focus of this study is to provide sustainable energy generation for an academic building located in a rural place, where power outage is a frequent issue. In this study, individual power system components have been suitably designed which could electrify the building for yearlong use. A rooftop photovoltaic (PV) system with three days battery backup has been considered for the present case. Designing of the PV system is based on the selection of individual electrical appliances and its operating time in a day. For this purpose, a survey has been carried out over a year in order to identify the day in which maximum power was utilized. The study revealed that the total estimated capacity of the stand-alone PV system should be 138.6 KWp in which 446 PV modules bearing 300 Wp each are connected together in series parallel combination. Total 656 numbers of batteries (12V- 200Ah each) are required for power backup which store the excess PV generation. Suitable size also been considered for inverters and charger controller which are connected in parallel and series respectively. The area required to install PV modules on the rooftop without shadow effect has been properly assessed. Besides being PV system design, brief cost analysis has been carried out in terms of simple payback period, unit cost of power generation and cash flow in terms of present value.
RF Propagation Model for Wireless Sensor Network of MARs
Authors:   Research scholar, C. U. Shah University SUNR-AHD State Highway, University Road, Wadhwan, Surendranagar. Gujarat, India., Shekh Nilofar A. , Dwivedi Dr. Vedvyas ,   Department of Electronics and Communication, Birla Institute Of Technology Jharkhand, India., Pabari Dr. Jayesh P. ,   Lecturer, Department of Electronics Engineering, R.D. College, Jabalpur, India.
Published: January 2020

NASA exploration mission on Mars includes the use of rovers and sensors communicating via wireless sensor networks. The network components have a limited range of transmission, low power consumption, low price and a small lifespan. A wireless network's performance is mainly dependent on the RF environment. A Wireless Sensor Network (WSN) on the Mars ground is planned to deploy wireless sensors capable of operating under harsh environmental conditions to detect few properties of regolith on the Martian surface. The main interest property is dielectric permittivity and permeability. Since communicating on the Mars is a difficult and challenging task, the behavior of communications surfaces can be predicted by a channel model. So, efforts have been put to Develop a channel propagation Model to know the behavior of communication channel on the atmosphere of Mars. In order to study the model for radio propagation on Mars, two sites were selected from Gale crater and Meridian Planum at different sites for the Mars with near-flat surfaces, a certain area with peaks and a region with few craters.
Altered Structural Connectivity in Autism Spectrum Disorder
Authors:   Department of information science and technology, College of engineering, Guindy, Anna university, Chennai, Tamil Nadu, India., Ramani R.Geetha , Jabarani R,Sahayamary ,   Department of information science and technology, College of engineering, Guindy, Anna university, Chennai, Tamil Nadu, India.
Published: January 2020

Research in Neurological field has been in great trend in recent days, since the need of detection and treatment of various neuropsychological disorders are in increasing order. Automated approaches for the detection are possible by various technological methods. Autism Spectrum Disorder (ASD) is a one such serious disorder which can be diagnosed in early ages of children. The Emerging technology had contributed the neuro imaging techniques to understand the various basic features and characteristics that cause the disorder. This neuro imaging had lead to a better perspective called connectome analysis which deals network structures (connectome) derived from the neuro images and are used in detection and treatment of the disorder. For these analysis functional and structural connectomes / network of brain are utilized. In this work structural connectomes derived from the Diffusion Tensor Imaging of Typically Developing and Autism Spectrum Disordered had been considered . This connectome / network consists of 264 regions (based on PowerNeuron_264 atlas) and thus 69696 connectivity features (connection between regions). Using the structural connectomes, average connectome analysis had been done and 91 connections had been identified as altered in ASD. There are 112 distinct regions involved in these altered connections and are having varied number of altered connections from one to six. 15 regions among them found to have much alteration since more number of (More than 2) altered connectivity are involved with these regions. To prove the finding , Data mining technique, Support Vector Machine was applied over 42 connectivity features (0.06% of original) out of 91 and are involved with the 15 regions filtered and the classification is done (with 82% accuracy) . Classifier rules are utilized in the diagnosis of ASD . The 15 regions extracted through thisprocess are found to be altered in ASD. These altered regions are related to sensory(touch and taste), memory, movements control, Lexical processing, Consciousness and sleep. This proposed system surely have effective use in the process of high dimensional and complex brain data and the identification of typically developed and autism spectrum disordered brain .This methodology can also be used in detection of other diseases, Role of various Regions, influential regions, etc.
Defending Against Sybil Attacks by Enhanced Event Based Reputation System in Vanet
Authors:   GTU-School of Engineering & Technology, Gandhinagar, India., Dutt Kunal J. , Joshi Seema B. ,   Assistant Professor, GTU-School of Engineering & Technology Gandhinagar, India.
Published: January 2020

In earlier times, vehicles were the realm of mechanical & automobile people, but with proliferation of computer technology & electronic components, vehicles are becoming “Computer on Wheels”. These technology lies in VANET (Vehicular Ad-Hoc Network) environment. VANET has various road safety applications, with the aim of communication interoperability between cars. In VANET, Sybil attack have been reckon as a major threat, by creating illusion or traffic congestion, it may lead mass destruction. Previously Event Based Reputation System (EBRS) named technique has been used to defend this Sybil attacks, but there was one major drawback that they were not considering RSU and TA modules security. For these both modules assumption has been made that it cannot be compromised thus it is trustable. But in this way VANET environment cannot be established thoroughly .In this paper we proposed enhance Event Based Reputation System to defend Sybil attacks in VANET environment, which is going to eliminate that major assumption by considering RSU and TAs security mechanisms.
A Computation Model for Planned and Functional Systems using Enterprise Information Technologies
Authors:   Department of Information Technology, AMET University, Chennai, India., Subramanian E. , Sanoj C. S. ,   Department of Computer Science and Engineering, Sri Venkateswara College of Engineering, Sriperumbudur, India.
Published: January 2020

All the large scale and medium scale companies have the anticipation of obtaining long term benefits perhaps of short term financial losses, probable breakdown as well. For that Enterprise Information Technologies (EIT) put into service by many large scale and medium scale companies in an increasing number in the expectation of achieving long term benefits. EIT is a very costly and risky asset of Information Technology and the assessment is done based on the increase in the production and the reinforcement of corporate restructure through the business integration process. To work out this, we propose Analytical Network Process (ANP) to handle distinguished assessment of associated set of evident, critical and operational attributes. To illustrate the stability and the consequential administrative significance, we perform analyzes and carry out experiments with real-world data.
Mechanical Characterization of FRBC prepared from Coir Fibres
Authors:   M.E. Dept., S.V.C.E., Indore, India., Shah Shubham , Sharma Manoj ,   M.E. Dept., S.V.C.E., Indore, India., Wankhade Vishal ,   M.E. Dept., S.V.C.E., Indore, India., Namdeo Avinash Kumar ,   M.E. Dept., S.V.C.E., Indore, India., Dhakad Atul ,   M.E. Dept., S.V.C.E., Indore, India.
Published: January 2020

This experimental study demonstrates the consequences of orientation of fibers in fibre reinforced biocomposite materials (FRBC) and its impact on their mechanical behaviour. Various samples of FRBC were synthesized from coir rope using hand layup method and epoxy resin in which orientation of coir rope was varied at 0°, 45° and 90° respectively. Test results reveal enhancements in tensile strength while reduction in flexural rigidity for all the samples of prepared composite in comparison to samples of pure epoxy material. The mechanical behavior of FRBCs is sensitive to the orientation angle of coir fiber in the matrix. The results show improved tensile strength for FE-90 samples by about 28%, but the flexural rigidity declined by about 59% as compared to E-samples. The minimum decline in flexural rigidity is about 16% for FE-00 samples while tensile strength enhanced by about 11% approx. It is concluded that, FRBCs prepared from coir fibres with hand layup method, are light weight and possess improved strength therefore, they are suitable for structural and reinforcement purpose.