bluuebunny/crossref_metadata_2025 huggingface dataset:
Trust based Intrusion Detection System Architecture for WSN
Authors:   department, Amity University, Gurgaon, India., Jain* Abhishek , Jain Vishal ,   department, BVICAM, New Delhi, India., Tripathi Khushboo ,   department, Amity University, Gurgaon, India.
Published: April 2020

Today there are extraordinary attacks on all kind of networks. Security for Payload is considered one of the biggest agenda for all kind of organizations. To deal with new species if attacks like threat, which are blended in nature, no security platform can take guarantee for their intrusion protection. Among all security platforms, intrusion detection system (IDS) are being used to do the inspection of all the packets or data being transferred between two nodes, A software application , that is responsible doing the monitoring of any kind of unwanted or to monitor the activity which is malicious in nature. This research acquaints about handling unknown attacks through Intrusion Detection System. For improving security in wireless communication, Intrusion Detection System (IDS) plays significant role, which includes information about network and security scheme. Hence, this research paper focused on development of appropriate system architecture for IDS system
CCEODSP-Cloud Computing Environment Observation for Data Security and Privacy
Authors:   Professor & Director, Department of Computer Science, ChristhuRaj College, Trichy, Tamil Nadu, India., Sugumar Dr. R. , Leelavathy Mrs. L. ,   Assistant Professor, Department of Computer Science, Sri Meenakshi Vidiyal Arts and Science College, Trichy, Tamil Nadu, India.
Published: April 2020

Today’s world, the cloud computing concepts has developed rapidly in both the private and public area, it is mainly provide the basic services and resources that are open to all kinds of end users on a particular platform through internet on a rented basis have the ability to extend up or down their service necessities or needs. This cloud computing model has numerous benefits including elasticity, scalability, efficiency, flexibility, etc. activities of a business organization. It bids a ground-breaking business concept for organizations to accept information technology enabled services without advance investment. Cloud computing model enables convenient, on-request network accessibility to a shared pool of IT computing resources like servers, services, storage networks, and applications. In this computing model can be speedily provisioned and released with negligible management exertion or service provider interaction. Quick variation of cloud computing had resulted in increasing strictness of privacy and security concerns as well as permissible challenges. In this learning includes various cloud computing issues that weakens of security and privacy of users data, as well as presents on threat that impacts data residing in the cloud and also added with this, a secure cloud computing open issues are noted in paper
Application of Oobleck as a Speed Breaker
Authors:   Assistant Professor, Department of Civil Engineering, Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu, India., Revathi* S. , Kumar A.Senthil ,   UG Student, Department of Civil Engineering, Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu, India.
Published: April 2020

A fluid in which the shear stress is directly proportional to strain, then it is termed as a Newtonian law of viscosity. If a fluid which does not obeys this law, then it is named as a Non -Newtonian fluid and Oobleck is one of the non -Newtonian fluid i.e.., (shear stress is indirectly proportional to the velocity gradient) and Oobleck is made by mixing the corn starch and boiled water in the appropriate ratio of 1:1.25 to get the non -Newtonian fluid property. Then, the mixture made is stored in water proofing packaging material i.e., Kevlar fiber and it is used as replacement of existing conventional speed breaker. The aim of this project is to apply the Oobleck mixture for a speed breaker, study about it’s characteristics and compare it with Conventional as well as plastic speed breaker. It plays a major role in controlling the speed of the vehicle and helps in preventing the accidents. The Oobleck is stored as a packing material in Kevlar fiber which retains the properties of the inner material forever and is having low thermal conductivity and chemical reactivity. The result indicates that the usage of Oobleck in speed breaker is sensitive to the speed of the vehicles and cost of manufacturing Oobleck speed breaker is comparatively lower than the conventional speed breaker.
An Efficient Data Stream Analytics Model for Real Time Internet of Things (Iot) Applications
Authors:   Research Scholar, Department of Computer Science, Alagappa University, Karaikudi, Tamil Nadu 630003, India, Kumar Mr. Kranthi , Ramaraj Dr. E. ,   Professor and Head, Department of Computer Science, Alagappa University, Karaikudi, Tamil Nadu 630003, Indi
Published: April 2020

Internet of Things (IoT), data analytics is supporting multiple applications. These numerous applications try to gather data from different environments, here the gathered data may be homogeneous or heterogeneous, but most of the data collected from multiple environments were heterogeneous, the task of gathering, processing, storing and the analysis that is being performed on data are still challenging. Providing security to all these things is also a challenging task due to untrusted networks and big data. Big data management in the ever-expanding network may rise several non-trivial concerns on data collection, data-efficient processing, analytics, and security. However, the above said scenarios depends on large scale sensor deployed. Sensors continuously transmit data to clouds for real time use, which can raise the issue of privacy disclosure because IoT devices may gather data including a kind of sensitive private information. In this context, we propose a two-layer system or model for analyzing IoT data, collected from multiple applications. The first layer is mainly used for gathering data from multiple environments and acts as a service-oriented interface to ingest data. The second layer is responsible for storing and analyses data securely. The Proposed solutions are implemented by the use of open source components.
Detection of cracks in Micro structured Cantilever Beam using Wavelet Transforms
Authors:   Engineering Mathematics, Faculty of Engineering and Technology, Annamalai University, Annamalai Nagar, Tamil Nadu, India, K* Ravikumar , Priya B Ithaya ,   Department of Mathematics, Annamalai University, Annamalai Nagar, Tamil Nadu, India
Published: April 2020

Wavelet Analysis, the improved version of Fourier transform is used to investigate and analyze the variant transient signals in time-frequency domain with higher accuracy and precision. Wavelet theory found its promising application in various fields not limited to Physics, Biology, Geophysics, Engineering and Medicine which becomes a common tool to analyze data. In this work we present new insight using wavelet transform to detect the cracks present in micro structured cantilever beam which found its application in various Micro Electro Mechanical System (MEMS) devices such as Transducers, Sensors, Switches, Actuators and Probes. Even a small change in microstructure will reflect in its dynamic output, so it is desired to locate the presence of cracks or damages over the device structure accurately. The modeling of such microstructure is designed and simulated using COMSOL Multiphysics. The displacement (Static Response) and stress of the beam for simulated damage were analyzed by wavelet transform using MATLAB. The obtained results highlights this method of analysis provides accurate location and effect of the crack over the Micro cantilever structure.
Eye Blink Detection System for Paralyzed Patients
Authors:   Assistant Professor and Research Scholar, Electronics and Communication Engineering, JSS Academy of Technical Education, Bengaluru., S. Mrs. Kavitha H. , C. Mrs.Suguna G. ,   Assistant Professor and Research Scholar, Electronics and Communication Engineering, JSS Academy of Technical Education, Bengaluru.
Published: April 2020

Paralysis of an human being is caused due to the degeneration of motor neurons which weakens the muscle, so that it does not allow patient to move, speak, breathe , and loss in the voluntary actions. It is an incurable disease. To understand the feelings of a paralyzed patients Brain wave technique and Electro-oculography techniques were used. These techniques are afflictive, discomfortable and leads to unconsciousness of the paralyzed patient. The real time video oculography system fills the communication gap between the patient and the world. Video Oculography (VOG) is video-based method of measuring the vertical, torsional and horizontal position components of both the eye blinks with the help of small cameras placed in the head-mounted mask .This paper presents different visual technologies, such as eye blink detection, eye center localization and conversion of the eye blink to speech. The video oculography could achieve accuracy of 0.968.
The External Value Creation Factors in Indonesian Fintech E-Wallet Based on Customer Perspective
Authors:   Information Systems Management Department, BINUS Graduate Program-Master of Information Systems Management, Bina Nusantara University, Jakarta, Indonesia 11480, Jakarta, Indonesia., Sfenrianto  , Fajri Ilham Al ,   Information Systems Management Department, BINUS Graduate Program-Master of Information Systems Management, Bina Nusantara University, Jakarta, Indonesia 11480, Jakarta, Indonesia, Bismoko * Radityo ,   Information Systems Management Department, BINUS Graduate Program-Master of Information Systems Management, Bina Nusantara University, Jakarta, Indonesia 11480, Jakarta, Indonesia., Gunawan Yonathan ,   Information Systems Management Department, BINUS Graduate Program-Master of Information Systems Management, Bina Nusantara University, Jakarta, Indonesia 11480, Jakarta, Indonesia.
Published: April 2020

Value Creation is very important in today's digital era, especially in adoption of E-wallet among millennials, of course, this development is very interesting because with the existence of value creation, it can increase the value of a fintech company from the customer's perspective. This study aims to find out what external factors can influence the development of fintech e-wallet in Indonesia. For a research, the methodology used is really important to define a good result. Questionnaires are an important tool in collecting data in this study to collect data from fintech e-wallet users. Literature review is used as a means of supporting theories or hypotheses put forward in this study. Related external factors to be discussed: government policy and legal, financial and capital investment, physical environment, and telecommunication infrastructure. Therefore, this research is intended to find out what external value creation factors that can help fintech e-wallet company to define what strategies that suitable with its culture, and also can increase the potential use of fintech e-wallets in Indonesia so that the fintech e-wallet climate can continue to compete and survive with uncertain economic conditions in the era recently.
Performance Analysis of Plug-in Electric Vehicle Supported DVR for Power-Quality Improvement and Energy Back-Up Strategy
Authors:   UG Student, EEE Department, Kallam Haranadhareddy Institute of Technology, Guntur, Andhra Pradesh, India, Ganesh* T. , Rao L. Shanmukha ,   Professor/EEE Department, Kallam Haranadhareddy Institute of Technology, Guntur, Andhra Pradesh, India
Published: April 2020

Electric vehicle technology becomes increasingly important as it takes care of the environmental issues related to ICE vehicle and reduces the dependency on fossil fuels. Electric vehicle being greatly dependent on the limited electrical energy provided by a battery, the power flow efficiency is very important in this context. Electric vehicle integration to the distribution grid is increased at a faster rate because it can act as power backup to the grid/local loads reducing the peak load and filling the valley point. Most of software engineers own an Electric Vehicle based on eco-friendly principles. The Batteries in the car are connected to the charging point (or) grid monitoring of State of Charging (SOC) facilities in the parking area of company. When the Renewable power (solar energy) is available, the batteries will be charged to hundred percentage of SOC. Then excess power from PV will connect to load as well as grid. When the electrical power supply cutoff the car batteries will act as a battery bank of UPS and support to the critical load with condition based Allowable SOC. The total capacity of the batteries depends upon the no of cars available at a particular shift in a day. This work proposes the power backup of EV is utilized as an UPS to Software Company as well as used to support the Dynamic Voltage Restorer (DVR) to mitigate the fault occurring in the distribution system. Additionally, the EV supported DVR compensates voltage harmonics, voltage sag-swell, voltage interruptions coming from distribution to enhance power-quality of entire EV system without any additional compensation devices. The entire system is modeled using MATLAB/SIMULINK and the results confer the feasibility of the proposed objective.
A Three-Layer Privacy Preserving Cloud Storage Scheme Based On Computational Intelligence in Fog Computing
Authors:   Engineeing Student From Saveetha Univeraity, Area of intrest cloud computing, Weslin Sherin John , Sinthia Gino ,   Assistant Professor Saveetha University , Research Area Data analytics, Image processing, Deep Learning .
Published: April 2020

Late years witness the improvement of distributed computing innovation. With the hazardous development of unstructured information, distributed storage innovation improves advancement. Notwithstanding, in current stockpiling pattern, client's information is completely put away in cloud servers. At the end of the day, clients lose their privilege of control on information and face security spillage chance. Conventional security assurance plans are normally founded on encryption innovation, yet these sorts of strategies can't viably oppose assault from within cloud server. So as to take care of this issue, we propose a three-layer stockpiling structure dependent on mist registering. The proposed structure can both exploit distributed storage and secure the protection of information. By at that point, we can place a little piece of information in neighborhood machine and mist server so as to ensure the security. In like manner, in context on computational information, this tally can figure the assignment degree put aside in cloud, darkness, and near to machine, autonomously. Through the theoretical security appraisal and primer assessment, the good judgment of our course of action has been supported, which is actually a historic Added to current dispersed amassing plot.
Developing a Model for Sentiment Analysis Technique in the field of Tourism using Deep Learning
Authors:   Assistant Professor, (IT) Institute of Innovation, Technology and Management, Janakpuri, New Delhi, India., Arora Ms. Harsh , Bansal Dr. Mamta ,   Professor, Shobhit University, Meerut, India.
Published: April 2020

This paper provides a platform for analyzing and summarizing the sentiments expressed by users or customers in the field of online tourism. The objective of this research is to analyze online reviews of all the users to propose a new optimized business model to improve present services of business organization to enhance profit and customer satisfaction. The proposed system filters tourism online reviews and classifies them using sentimental technique with the help of deep learning technique. Deep learning technique will not only identify the polarity of online reviews but also recognizes relevant patterns deeply to find the hidden reviews details. After applying the deep learning technique, the results will be generated through which we can find the inferences. These inferences would provide a great help for improvisation of the subject. In this research a new optimized business model will be implemented using deep learning technique so that we would be able to compare new business model with the present system [1]. The relevance of this research lies in helping tourism industries to understand the social sentiment of their brand, product or service while monitoring online conversations. It helps in enhancing business profits by running online websites throughout by giving best services to the online users or customers.
Assessing the Effectiveness of Agricultural based Entrepreneurship Development Programmes at RUDSETI
Authors:   Student, MBA Amrita Vishwa Vidyapeetham., K S Harshida , Bhasi Archana ,   Student, MBA Amrita Vishwa Vidyapeetham.
Published: April 2020

On the rural side, it appears that the job potential in the agricultural economy has reached saturation level that leads to large-scale migration of workforce from rural to urban areas adding woes and strain to over-stressed civic infrastructure. Millions of unemployed young people, especially those from rural and semi-urban backgrounds who have not been able to access higher/professional education but who are oriented towards white-collar jobs, is driven to despair because they cannot find a job. It calls for the need for entrepreneurial ventures among the unemployed youth to encourage self-employment. In this context, this study aims at understanding the impact of Agricultural Employment Development Programmes offered by RUDSETI. Moreover, the study analyses how RUDSETI was able to motivate, instil technical knowledge, management skills, resource management, and handhold trainees even after starting their own agricultural business. For the study, the purposive sampling method was applied to collect the primary data from the trainees at RUDSETI. Descriptive method of research was adopted. The result of study states that training programme was key factor to start and successful running of their business. The hypothesis testing also proved positive that RUDSETI is acting as a catalyst towards growth and sustaining of the Agricultural sector.
Search Engine Optimization (SEO) in Promoting E-Commerce Start Aja. Com
Authors:   Information Systems Management Department, BINUS Graduate Program – Master of Information Systems Management, Bina Nusantara University, Jakarta, Kosasih Adrian , Purnomo Lorio ,   Information Systems Management Department, BINUS Graduate Program – Master of Information Systems Management, Bina Nusantara University, Jakarta, Sidanta Oscar ,   Information Systems Management Department, BINUS Graduate Program – Master of Information Systems Management, Bina Nusantara University, Jakarta, Sfenrianto  ,   Information Systems Management Department, BINUS Graduate Program – Master of Information Systems Management, Bina Nusantara University, Jakarta
Published: April 2020

StartAja.com is an e-commerce designed to help connecting business people who have similar interests in certain business area. Currently, StartAja.com hasn’t have digital marketing strategy yet to simplify keyword searches in promoting StartAja.com. This research’s objective is to formulate a Search Engine Optimization (SEO) strategy. By using SEO, StartAja.com is expected to be the top ranked e-commerce in search engine websites. Research data are obtained through observing the interface and functionalities of StartAja.com, and also its promotion requirements. This research has discovered the right combination of keywords to be used in SEO, to help optimize the promotion of StartAja.com.
FTmRP-NCS: Fault-Tolerant And Reliable mRPL Routing Protocol For W-NCS Communication
Authors:   Research Scholar, VTU, Belgaon, India., Hingmire Mr. Vishal Sharad , Desai Dr. Santosh R. ,   Department of Electronics and Instrumentation Engineering, BMS College of Engineering, Bangalore, India., Kanse Dr. Yuvraj Krishnrao ,   Department of Electronics Engineering, KBP College of Engineering, Maharastra, India.
Published: April 2020

The exponential rise in the demands for reliable and fault resilient communication over Wireless Network Control Systems (WNCS) across industrial monitoring and control ecosystems has alarmed academia-industries to develop more efficient wireless transmission solutions. On the other hand, the emergence of cloud-assisted Internet-of-Things (IoT) also has broadened the demands for reliable WNCS systems. To cope up with such irreplaceable needs, WNCS has exploited different wireless communication paradigms including IPv6 Routing Protocol for Low Power Lossy Networks (RPL) based WSN that enables reliable communication across the industrial setup to make optimal real-time process decision. However, being dynamic in nature WNCS with often undergo link-outage due to dynamic topology, node death, congestion etc. Though, a few researchers have addressed the routing problem in WNCS; however, integrating RPL with mobility to enable optimal communication has remained untouched. Additionally, no significant research addressed fault-resilient routing decision over WNCS setup, which motivates us to develop a highly robust Fault-Tolerant and Reliable mobile-RPL Routing Protocol for W-NCS (FTmRP-NCS). Unlike classical WNCS models, FTmRP-NCS employs dual objective-based routing decision by considering the Received Signal Strength Indicator (RSSI) and the number of control packets required (ETX). Here, the inclusion of RSSI ensures forwarding path formation with most reliable link condition, while ETX objective function helps maintaining low control packets and hence low energy exhaustion, low redundancy and high efficiency. FTmRP-NCS applies link-sensitive mobile node movement for data gathering across WNCS, which makes overall communication more reliable as well as time-efficient. Furthermore, fault-sensitive routing decision strengthens our proposed FTmRP-NCS protocol helps WNCS to yield optimal performance. FTmRP-NCS has been applied over standard IEEE 802.15.4 protocol stack and functions in parallel to the link and network layer, which retains backward compatibility with native RPL and hence assures easy implementation with real-time WNCS environment.
“Design of Automatic Organic Waste Shredder for Composting”
Authors:   Assistant Professor, School of Mechanical Engineering, REVA University, Bengaluru, India., V* Ashwini M. , P. Robinson ,   Assistant Professor, School of Mechanical Engineering, REVA University, Bengaluru, India., S. Nithin P. ,   U G Students, School of Mechanical Engineering, REVA University, Bengaluru, India., Charan Seella ,   U G Students, School of Mechanical Engineering, REVA University, Bengaluru, India.
Published: April 2020

Developing means of farming and agriculture is the reason humans live in the world they do today. It is a necessary means of survival, without which there would be famines all over the world. For thousands of years, agricultural was a natural process that did not harm the land it was done on. Environmental impacts caused due to the harmful effects of human activities are a worldwide problem causing global warming and climate change. Too much dependence on the usage of chemical inputs and the burning of farm wastes was identified as the major ones. Since this issues are threat to mankind and to the existing agriculture equipment’s and the shredder machine is one among them. The machines available in the market are powered via fossil fuels which is also contributing to global warming, this directed the researchers to design and develop a Solar-Powered Shredder machine which can be efficiently operated using solar energy without the dependency on fossil fuel. This project aims at providing solar powered automatized vertical shredder machine to our farmers that is compact and can be operated by using solar.
Enhancing IoT Security for Smart Energy Meter using Blockchain
Authors:   School of Computer Science and Engineering Department, Vellore Institute of Technology, Vellore, India, Vinay* Vasa , K S Sendhil Kumar ,   School of Computer Science and Engineering Department, Vellore Institute of Technology, Vellore, India
Published: April 2020

Internet of Things (IoT) is growing rapidly in recent days and increasing of IoT devices day by day producing vast amount of data, to store this data security is a major challenge in IoT. To avoid these security challenges, blockchain is the perfect solution. With its security by design, immutable nature, transparent nature and encryption methodology blockchain will solve architectural issues of IoT. In these days, the energy meters in our homes are not able send the information to the cloud and man power also needed to update readings every month, and manually errors also taken place some times to avoid these, in the paper a smart energy meter is proposed, that will measure the power consumption and that readings will be stored in to the blockchain to secure the data from the fraudsters and also to make the payment without any third parties like banks, in the blockchain technology amount can be transferred from one to one without any third parties using crypto currencies like bitcoin, ether.., etc. The user will be able to check the bills in the blockchain and do the payments. By using the blockchain technology the user data will be more secure and the IoT security issues also solvable.
Financial Appraisal of RRBs: Evidence from Eastern Uttar Pradesh
Authors:   Department of Finance, ICFAI Business School, Hyderabad, India, Tiwari Satish Chandra , Jee Kishan ,   FMS, GNS University, Rohtas, India., Ramaiah T. Sita ,   Department of Finance, ICFAI Business School, Hyderabad, India., Mathur Neeti ,   Department of Finance, NIIT University, Rajasthan, India.
Published: April 2020

India’s major population lives in rural area and adequate financial credit supply are much needed for speedy economic development of this region. Regional Rural Banks (RRBs) was established with the objective to provide financial support in rural areas. RRBs have been working as an economic agent and disbursing loan to the rural people since its inception. RRBs have performed to a great extent in terms of rural credit disbursement but Non Performing Assets (NPA) has become a key trouble. For the last few years RRBs have been facing a primary challenge of mounting NPAs, which is clogging the smooth credit supply in the rural areas. The present study aims to analyze the loan disbursement towards agriculture sector, overdue and NPAs of RRBs working in Eastern Uttar Pradesh.
Determinants of Micro Finance Bank Stability in Pakistan
Authors:   Universiti Kuala Lumpur Business School, Malaysia., Ali Muhammad , Jaafar Jimisiah ,   Universiti Kuala Lumpur - MITEC, Johor Bahru, Malaysia., Jahangiri M. Hassan ,   Universiti Malaysia Tererngganu, Malaysia., Fakhruddin Ahmad ,   Universiti Kuala Lumpur - MITEC, Johor Bahru, Malaysia.
Published: April 2020

In developing countries like Pakistan MF is anticipated to play a vital part in lowering poverty and raising the standard of living of people. The performance of MF is a key to the development of society and economy of Pakistan. A sustainable MF structure in a country can be helpful in developing small scale businesses. Success of MF in Bangladesh and other parts of the world is a signal that the field has major role in changing lives of low people. Despite the importance of the field of micro finance in a country like Pakistan, it has been explored rarely by academicians. The study is aiming to investigate the fiscal viability of MF banks in Pakistan. MF Banks are institutions that provide micro fiscal assistance to people. The study is based on the MF banks in Pakistan. Performance of MF can be judged through various dimensions. The study is limited to the analysis of fiscal sustainability of MF. The scope of study is limited to the MF banks in Pakistan. The time period of the analysis is from 2010 to 2017 due to availability of the data for this time period.
Optimization of Multi Objective Vehicle Routing Problem with Time Windows using Total Time Balance
Authors:   Department of Mechanical Engineering Andhra university college of engineering, Mengistu Dereje Dejene , Rao Prof. V.V.S.Kesava ,   Department of Mechanical Engineering Andhra university college of engineering
Published: April 2020

Vehicle Routing Problem time window (VRPW) used in supply chain management in the physical delivery of goods and services, and the determination of all routes for a fleet of vehicles, starting and ending at a depot and serving customers with known demands by increasing the efficiency and profitability of transportation systems. The main objective of this study is to refutes a multi-objective vehicle routing problem with time windows by minimization of the number of vehicles, the total distance traveled and rout balance not sufficient instead of using 'total time balance'. To test the performance of the objective it considers GA with the fitness Aggregation approach comparing with the related literature based on Solomon’s benchmark instance standard data. The time makespan produced by FAGA and the time makespan mentioned in related literature is compared. From the result, fitness Aggregation approach with genetic algorizim (FAGA) provides better result including the real-time window as compared to previous work .
Effective Video Saliency Mapping for Object Detection using Deep Learning Neural Networks
Authors:   Associate Professor/ECE, Francis Xavier Engineering College, Tirunelveli, India., Vedhapriyavadhana Dr. R. , Priya G. Shanmuga ,   PG Scholar/ECE, Francis Xavier Engineering College, Tirunelveli, India, Reddiar N. Renee ,   PG Scholar/ECE, Francis Xavier Engineering College, Tirunelveli, India, Priya M. Mano ,   PG Scholar/ECE, Francis Xavier Engineering College, Tirunelveli, Indi.
Published: April 2020

In this paper, we propose a new novel DNN-based video saliency prediction method.The main aim of this project is to separating foreground and background images and also finding the motion of the objects.The methodogy used in this project is to seperating the foreground images using background modelling techniques(Pixel searching algorithm).The another technique is Homography based search algorithm for block based motion estimation is used to finding the movement of the objects.Saliency object detection is also used to highlighting the particular region in the images.In our base paper[1],context subtraction algorithm is introduced.But in this paper,Convolutional neural networks is used to classifying the foreground objects from background images.We propose an deep convolutional neural network (CNN) Classifier is used to predict intra-frame salience by exploring object and object movement details .The CNN classifier is also used to separating the new objects from background. We also find from our database that a temporary correlation of human attention exists, with a smooth transition of saliency across video frames.Therefore, in our DNN-based approach we create a two-layer convolutionary long-term memory (2C-LSTM) network, using the extracted CNN features as the data.The fuzzy clustering is used to store the information as the processed images in this project.This project can be implemented in real time applications such as defence,forest and miltrary area.Saliency Mapping is also used to reduce the Zipper effect,it mainly occurs in edges.It gives High resolution too. Finally, the proposed system is developed using matlab simulation.The PSNR value is attained above 95%.
Adopting Numerical Models for Prediction of Ground Movements Induced by Deep Excavation
Authors:   Civil Engineering Department, Helwan University, Cairo, Egypt, Mansour* Mona A. , Rashed Dr. Ahmed ,   assistant Prof., Civil Engineering Dept, Shorouk Academy, Shorouk City, Egypt., Farag Dr. Ahmed ,   Assistant Prof., Civil Engineering Dept, Shorouk Academy, Shorouk City, Egypt.
Published: April 2020

Control of ground surface settlement induced by deep excavation is of major concern in order to attain safety of adjacent structures and utilities against excessive or differential settlements. Accurate prediction of ground surface movements is an important design criterion in the analysis and design of excavation supporting systems. Many codes of practice are based on a design criterion that satisfies a factor of safety preventing collapse of the system and its surrounding soil. In this research, finite element modeling is adopted to numerically simulate the performance of deep excavation systems and the associated ground movements. The soil behavior was simulated using two types of models; the Mohr-Coulomb model (MC) and the Hardening Soil Model (HS). Field data from monitoring a real deep excavation case history of a retaining system was considered to check the validity of the proposed numerical modeling. A simpler equivalent section replacing the multi-layered soil profile was verified. Then, a sensitivity study has been conducted to study the influence of major parameters that affect ground movements induced by deep excavation. The results of the parametric study were accomplished to construct design charts and drive empirical equations by implementing a design parameter, called the "Stiffness Ratio (R)”, that represents the supporting system stiffness. From these suggested charts and equations, the percentage of maximum vertical ground movements to wall height can be estimated.
Power Flow Regulation by UPFC in Networks with Voltage Dependent Loads
Authors:   is Head of Department & Professor in Electrical Engineering Department of Radharaman Engineering College, Bhopal, Madhya Pradesh, India., Mubeen* Dr. Samina E.
Published: April 2020

In this paper calculations are made to find out the power flow regulation capabilities of Unified Power Flow Controller (UPFC) in load flow analysis with loads which are voltage dependent. New equations for load flow analysis are developed that includes the models of voltage sensitive loads and voltage sources model of UPFC. Newton Raphson algorithm is used to solve the power flow equations of the network. UPFC voltage source model when included in the power equations has unique advantages over other modeling approaches. Analysis is done for two types of Loads. In the first analysis Constant current, Constant Power and Constant Impedance type of loads are examined. In the second analysis Composite loads are analyzed. The results of analysis on standard 5 bus system is presented here as a case study.
Numerical Modelling and Validation of Railway Vehicle
Authors:   Civil Department, Mohammedia Engineering School, Mohammed 5 University, Rabat, Morocco., Bouhlal* Laila , Touati Mohammed ,   Civil Department, Mohammedia Engineering School, Mohammed 5 University, Rabat, Morocco., Lamdouar Nouzha ,   Civil Department, Mohammedia Engineering School, Mohammed 5 University, Rabat, Morocco.
Published: April 2020

The objective of this study was to establish a theoretical model regarding the dynamic behaviour of the railway vehicle in the vertical plan while travelling on a track with irregularities. In this article the vehicle is modelled by seven bi-dimensional rigid elements respectively representing: the body, tow boogies and four wheels. The equations system was numerically integrated by the Newmark´s β and Wilson ɵ method. The model developped was subjected to a validation process based on the comparison between numerically derived acceleration spectra and experimental data.
CNN Architectures: Alex Net, Le Net, VGG, Google Net, Res Net
Authors:   Research Scholar* , Department of CSE, JJT University, Jhunjhunu, Rajasthan, India., Swapna M. , Sharma Dr.Yogesh Kumar ,   Associate Professor, Department of CSE, JJT University, Jhunjhunu, Rajasthan,India., Prasad Dr. BMG ,   Professor, Department of CSE, Holy Mary Institute.Hyderabad, India.
Published: April 2020

Convolutional Neural Networks(CNNs) are a floating area in Deep Learning. Now a days CNNs are used inside the more note worthy some portion of the Object Recognition tasks. It is used in stand-out utility regions like Speech Recognition, Pattern Acknowledgment, Computer Vision, Object Detection and extraordinary photograph handling programs. CNN orders the realities in light of an opportunity regard. Right now, inside and out assessment of CNN shape and projects are built up. A relative examine of different assortments of CNN are too portrayed on this work.
Select to better learn: Fast and accurate deep learning using data selection from nonlinear manifolds
Authors: Joneidi Mohsen , Vahidian Saeed , Esmaeili Ashkan , Wang Weijia , Rahnavard Nazanin , Lin Bill , Shah Mubarak
Published: April 2020

Finding a small subset of data whose linear combination spans other data points, also called column subset selection problem (CSSP), is an important open problem in computer science with many applications in computer vision and deep learning. There are some studies that solve CSSP in a polynomial time complexity w.r.t. the size of the original dataset. A simple and efficient selection algorithm with a linear complexity order, referred to as spectrum pursuit (SP), is proposed that pursuits spectral components of the dataset using available sample points. The proposed non-greedy algorithm aims to iteratively find K data samples whose span is close to that of the first K spectral components of entire data. SP has no parameter to be fine tuned and this desirable property makes it problem-independent. The simplicity of SP enables us to extend the underlying linear model to more complex models such as nonlinear manifolds and graph-based models. The nonlinear extension of SP is introduced as kernel-SP (KSP). The superiority of the proposed algorithms is demonstrated in a wide range of applications.
Deep Learning for text in limted data settings
Authors: Patel Pathikkumar , Lad Bhargav , Fiaidhi Jinan
Published: April 2020

During the last few years, RNN models have been extensively used and they have proven to be better for sequence and text data. RNNs have achieved state-of-the-art performance levels in several applications such as text classification, sequence to sequence modelling and time series forecasting. In this article we will review different Machine Learning and Deep Learning based approaches for text data and look at the results obtained from these methods. This work also explores the use of transfer learning in NLP and how it affects the performance of models on a specific application of sentiment analysis.
Sentimentos vivenciados pela equipe de enfermagem perante o tratamento de pacientes com câncer: revisão integrativa
Authors: Beserra Jessica Helaine Gomes Nascimento , Aguiar Ricardo Saraiva
Published: April 2020

Objetivo: Compreender os sentimentos vivenciados por enfermeiros envolvidos diretamente no tratamento de pacientes com câncer. Método: Trata-se de uma revisão integrativa da literatura, realizada no período de 2013 a 2018, sendo o levantamento bibliográfico realizado nas bases de dados SCIELO e LILACS utilizando os descritores enfermagem oncológica; emoções; e cuidados paliativos. Resultados: Foram selecionadas 20 produções científicas que versavam sobre o objeto do estudo. Prevaleceram os estudos do ano de 2014. Optou-se pela definição de três categorias para a discussão dos resultados: sentimentos vivenciados pela equipe de enfermagem perante o tratamento de pacientes com câncer; reações dos profissionais da enfermagem perante o processo de morte e morrer de seus pacientes; a importância da enfermagem no tratamento de pacientes com câncer. Conclusão: Os profissionais da enfermagem envolvidos no cuidado de pacientes com câncer têm uma rotina onde estão expostos a sofrer sobrecarga emocional decorrentes da assistência, por este motivo é necessário que esses profissionais estejam preparados e capacitados para não sofrer ao presenciar pacientes e seus familiares em estado de sofrimento.
Development of a pheromone preparation for the detection and monitoring of boxwood moth Cydalima perspectalis Walker
Authors: Balykina E. B. , Glebov V. E. , Korzh D. A. , Kulakova N. I. , Nesterenkova A. E. , Rastegaeva V. M. , Trikoz N. N. , Sharmagiy A. K.
Published: April 2020

The results of field tests of different variants of synthetic pheromone blends and pheromone dispenser developed by the Department of synthesis and application of pheromones of the FSFI " All-Russia Plant Quarantine Center" for identification and monitoring boxwood moth is a dangerous invasive pest of boxwood in the Republic of the Crimea; the optimal material of the pheromone’s carrier is determined, the effective ratio and dosage are proposed.
The experience of introduction of representatives of the genus Liquidambar L. in Abkhazia
Authors: Bulgakova N. A.
Published: April 2020

The article presents the bioecological, ornamental, and silvicultural features of the growth and development of three species and one form of the genus Liquidambar under the conditions of Abkhazia. The promise of their use for practical purposes is confirmed. Among them, Liquidambar styraciflua L. is classified as the most valuable tree species for use in landscaping and forest cultures.
The use of root formers agents for vegetative reproduction of belladonna
Authors: Khazieva F. M. , Savchenko O. M.
Published: April 2020

For the first time the article presents data on the development of methods of vegetative reproduction of belladonna (division of rhizomes and green cuttings) to improve the efficiency of planting material. The method of optimization the breeding work will allow to receive homogeneous material of perspective samples of belladonna. Rooting of belladonna as a result of the use of growth regulators-rooters was: Zircon - 63%, Kornevin - 93%. When using a binary mixture of preparations Zircon and Kornevin rooting increased by 27% compared to the control. Survival of root cuttings of belladonna in the field in single-bud plants after treatment with Kornevin exceeded the control by 17%. The use of the root-forming agent "DvaU" is promising for vegetative reproduction of belladonna, since this drug provided almost 100% survival rate of plants and contributed to the strengthening of growth processes in the initial periods of plant growth.
Complexes of related elements of features of organs of Betonica officinalis L. as markers for searching for plants with high content of tannins
Authors: Morilov V. V. , Neuimin S. I. , Katsman S. I.
Published: April 2020

The variability of complexes of related elements of morphological characteristics and the content of tannins in plants of Betonica officinalis L. on the territory of the Southern and Middle Urals was analyzed. It has been established that the variability of morphological and biochemical characteristics of Betonica officinalis L. has a coordinated zonal character in the Southern and Middle Urals. It is shown that, based on the analysis of complexes of related elements of flower characteristics in Betonica officinalis L., the content of tannins can be predicted in natural populations.
Experiences from tsunami relief activity: implications for medical training
Authors: Manni Balasubramaniam Sudharsanam , Roy Gautam , Mohan Yogesh
Published: April 2020

A tsunami struck the coast of Tamilnadu and Pondicherry on 26 December 2004. Jawaharlal Institute of Postgraduate Medical Education & Research, (JIPMER) in Pondicherry played a vital role in providing medical relief. The experiences from the relief activities revealed areas of deficiency in medical education in regards to disaster preparedness. A qualitative study using focus group discussion was employed to find the lacunae in skills in managing medical relief measures. Many skills were identified; the most important of which was addressing the psychological impact of the tsunami on the victims. Limited coordination and leadership skills were also identified. It is recommended that activity-based learning can be included in the curriculum to improve these skills.
Experienced physicians benefit from analyzing initial diagnostic hypotheses
Authors: Bass Adam , Geddes Colin , Wright Bruce , Coderre Sylvain , Rikers Remy , McLaughlin Kevin
Published: April 2020

Background: Most incorrect diagnoses involve at least one cognitive error, of which premature closure is the most prevalent. While metacognitive strategies can mitigate premature closure in inexperienced learners, these are rarely studied in experienced physicians. Our objective here was to evaluate the effect of analytic information processing on diagnostic performance of nephrologists and nephrology residents. Methods: We asked nine nephrologists and six nephrology residents at the University of Calgary and Glasgow University to diagnose ten nephrology cases. We provided presenting features along with contextual information, after which we asked for an initial diagnosis. We then primed participants to use either hypothetico-deductive reasoning or scheme-inductive reasoning to analyze the remaining case data and generate a final diagnosis. Results: After analyzing initial hypotheses, both nephrologists and residents improved the accuracy of final diagnoses (31.1% vs. 65.6%, p < 0.001, and 40.0% vs. 70.0%, p < 0.001, respectively). We found a significant interaction between experience and analytic processing strategy (p = 0.002): nephrology residents had significantly increased odds of diagnostic success when using scheme-inductive reasoning (odds ratio [95% confidence interval] 5.69 [1.59, 20.33], p = 0.007), whereas the performance of experienced nephrologists did not differ between strategies (odds ratio 0.57 [0.23, 1.39], p = 0.2). Discussion: Experienced nephrologists and nephrology residents can improve their performance by analyzing initial diagnostic hypotheses. The explanation of the interaction between experience and the effect of different reasoning strategies is unclear, but may relate to preferences in reasoning strategy, or the changes in knowledge structure with experience.
Consistency in diagnostic suggestions does not influence the tendency to accept them
Authors: Van den Berge Kees , Mamede Silvia , Van Gog Tamara , Van Saase Jan , Rikers Remy
Published: April 2020

Background: Studies suggest that residents tend to accept diagnostic suggestions, which could lead to diagnostic errors if the suggestion is incorrect. Those studies did not take into account that physicians in clinical practice will mainly encounter correct suggestions. The present study investigated residents’ diagnostic performance if they would first encounter a number of correct suggestions followed by a number of incorrect suggestions, and vice versa. It was hypothesized that more incorrect suggestions would be accepted if participants had first evaluated a series of correct suggestions. Method: Residents (n = 38) evaluated suggested diagnoses on eight written clinical cases. Half of the participants first evaluated four correct suggestions and then evaluated four incorrect suggestions (C/I-condition). The other half started with the four incorrect suggestions followed by the correct suggestions (I/C-condition). Results: Our findings show that the evaluation score in the C/I condition (M = 2.87, MSE = 0.14) equaled that in the I/C condition (M = 2.66, MSE = 0.14), F(1,36) = 1.09, p = 0.30, ns, meaning that consistency in preceding suggested diagnoses did not influence the tendency to accept subsequent diagnostic suggestions. There was, however, a significant interaction effect between case order and phase, F(1,36) = 11.82, p = 0.001, ηp2 = 0.25, demonstrating that the score on cases with correct suggestions was higher than the score on cases with incorrect suggestions. Conclusion: These findings indicate that consistency in preceding correct or incorrect diagnostic suggestions did not influence the tendency to accept or reject subsequent suggestions. However, overall residents still showed a tendency to accept diagnostic suggestions, which may lead to diagnostic errors if the suggestion is incorrect.