bluuebunny/crossref_metadata_2025 huggingface dataset:
A Machine Learning Based Email Spam Classification Framework Model: Related Challenges and Issues
Authors:   Research Scholar, Osmania University, and Assistant Professor, Department of CSE, Neil Gogte Institute of Technology, Hyderabad, Telangana, India., Mallampati* Deepika , Hegde Dr. Nagaratna P ,   Professor, Department of CSE, Vasavi College of Engineering, Hyderabad, Telangana, India.
Published: February 2020

Spam emails, also known as non-self, are unsolicited commercial emails or fraudulent emails sent to a particular individual or company, or to a group of individuals. Machine learning algorithms in the area of spam filtering is commonly used. There has been a lot of effort to render spam filtering more efficient in classifying e-mails as either ham (valid messages) or spam (unwanted messages) through the ML classifiers. We may recognize the distinguishing features of the material of documents. Much important work has been carried out in the area of spam filtering which cannot be adapted to various conditions and problems which are limited to certain domains. Our analysis contrasts the positives methods as well as some shortcomings of current ML methods and open spam filters study challenges. We suggest some of the new ongoing approaches towards deep leaning as potential tactics that can tackle the challenge of spam emails efficiently.
Performance Improving of ANN with Preprocessing Stage in Human Face Expression Recognition System
Authors:   Research Scholar, Sethu Institute of Technology, Kariapatti, Tamilnadu, India., C. H.* Sumalakshmi , Vasuki Dr. P. ,   Professor, Department of ECE, Sethu Institute of Technology, Kariapatti, Tamilnadu, India.
Published: February 2020

In many face recognition systems, the important part is face detection. The task of detecting face is complex due to its variability present across human faces including color, pose, expression, position, and orientation. So, by using various modeling techniques it is convenient to recognize various facial expressions. The system proposed consists of three phases, the facial expression database, pre-processing and classification. To simulate and assess recognition efficiency based on different variables (network composition, learning patterns and pre-processing), we present both the Japanese Female Facial Expression Database (JAFFE) and the Extended Cohn-Kanade Dataset (CK+). Comparative approaches of data preprocessing include face detection, translation, normalization of global contrast and histogram equalization. Significant results were obtained with 85.52 percent accuracy particularly in comparison with some other pre-processing phases and raw data in single pre-processing phases. The result indicates the ANN classifier representation produces a satisfactory result which reaches more accuracy.
Common Bamboo Species Identification using Machine Learning and Deep Learning Algorithms
Authors:   Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India., Juyal* Piyush , Kulshrestha Chitransh ,   Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India., Sharma Sachin ,   Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India., Ghanshala Tejasvi ,   Faculty of Applied Science, The University of British Columbia, Vancouver, Canada.
Published: February 2020

Due to its growth rate and strength, bamboo's versatility is huge. Bamboo has been developed to replace hardwood naturally. But it can be difficult to recognize a bamboo as many appear in a cluster or singular. Each bamboo type has its applications. Because of the utility of bamboo, we have worked in Random Forest, naive bays, logistic regression, the SVM-kernel, CNN, and ResNET, amongst several machine-learning algorithms. A similar test was carried out and delineated using graphs based on uncertainty matrix parameters and training accuracy. In this paper, we have used the data of following five species such as Phyllostachys nigra, Bambusa vulgaris ‘Striata‘, Dendrocalamus giganteu, Bambusa ventricosa, and Bambusa tulda which are generally found in north India. We trained, tested and validated the species from datasets using different machine learning and deep learning algorithms.
Cost-Effective Spectrum Utilization for Futuristic Cognitive Radio based Services
Authors:   Professor and Head, Department of TCE, Kammavari Sangham Institute of Technology, Bangalore, India, Reddy* Dr. Chanda V.
Published: February 2020

The proliferation of various mobile users in the context of advanced wireless technologies, spectrum scarcity arises as a crucial problem. The notion of cognitive radio (CR) principle offers cost-effective spectrum reusability with intelligent mode of transmission model. It basically enables a radio-driven technology to utilize dynamic spectrum accessing to meet the quality-of-services (QoS) requirements by satisfying enormous communication and connectivity demands. To alleviate the spectrum scarcity problem the study proposes a novel analytical solution of spectrum allocation considering a simplified evolutionary learning model. The prime target of the formulated concept is to detects the spectrum holes effectively for reusability and the possibility of identification has be maximized for best possible spectrum allocation to the radios. And on the other hand also the occurrence of false positive identification has to be minimized. The outcome obtained after performing the simulation shows promising aspects in the context of effective spectrum allocation for higher priority user with better throughput performance.
Understanding Contribution of Physical Accessibility in Perceptual Conviviality of Public Open Spaces using Analytical Hierarchy Process
Authors:   Architecture and Planning, Maulana Azad National Institute of Technology (MANIT), Bhopal (M.P), India., Thombre* Leena , Kapshe Dr. Charumitra ,   Architecture and Planning, Maulana Azad National Institute of Technology (MANIT), Bhopal (M.P), India.
Published: February 2020

The objective of this study is to examine contribution of accessibility in creating conviviality at a public open space. In literature, conviviality is discussed as the subjective quality of public spaces, but its quantification is not adequately discussed. Conviviality means, being happy in the company of others. From different studies, it was found that there are physical aspects of built environment which can influence conviviality. Legibility, network integration and walkability in built environment can increase accessibility which can contribute in conviviality of a public open spaces. The methodology of this work is based on comparison between perceptual conviviality with physical parameters of accessibility in public open spaces. With the help of experts, weights are derived through Analytical Hierarchy Process (AHP) for perceptual conviviality parameters and physical accessibility attributes. Based on this work, it was empirically validated that accessibility plays important role in conviviality at a public open space.
Risk Analysis on Industrial Internet of Things (Iiot) Integration with Enterprise Resource Planning(ERP) Inmanufacturing
Authors:   Professor and Associate Dean,VIT Business School,Vellore, Tamil Nadu,India., S* Jose , Wilson Vincent Herald ,   School of Mechanical Engineering,Vellore Institute of Technology, Vellore, Tamil Nadu,India.
Published: February 2020

At the onset of liberalization, privatization and globalization, enterprise resource planning has become an integrated part of any business. It has become imperative for businesses to go in for IIoT. With implementation of IIoT and analytics companies can become more profitable and productivity can increase constantly. With this comes the risk of data security in ERP due to real time capturing huge volume of data in manufacturing plants, which are under security risk. This has forced the companies to implement measures to ensure that the product design and customer data are stored securely without compromising on business. This paper presents the possible sources of risk in IIoT and presents the solutions for preventing the risk.
Compressive Strength Prediction of Aa7075/ Sic/Fly Ash/Graphite -Hybrid Metal Matrix Composite
Authors:   Department Of Mechanical Engineering, SOT, GITAM Deemed to be University, Bengaluru, Karnataka, India., Singampalli* Rajasekhar , Ramji Dr. K. ,   Department Of Mechanical Engineering ,AUCE, Andhra Universitysity. Visakhapatnam, India., Kumar Santosh ,   Department Of Mechanical Engineering, SOT, GITAM Deemed to be University, Bengaluru, Karnataka, India.
Published: February 2020

The demand for light weight material with superior strength ,lead to many new inventions in the field of metal matrix composites. This need of composite materials are growing at faster rate in almost all Mechanical engineering applications. Components made with Aluminium metal matrix composites (AMMC) are found to be the best replacement for massive metal components and machine parts in various applications. In this context an aluminium composite designated as AA7075 has been taken for the present Investigation. AA7075 has high strength and high corrosion resistance, which has an extensive applications in Air craft, Automotive heat exchangers and widely utilized in Protective cladding due to its excellence corrosion property. The present work is intended at the determination of compression characteristics of AA7075 metal matrix composite by means of traditional analytical method and finite element method as well as. This began with the synthesis of composite material, which includes the reinforcement of alloying elements namely Silicon carbide, fly ash and graphite particulates together in the ratio of 6, 9 and 12 % by weight, with an increment of 1% each every time to pure AA7075 metal. This is accomplished by means of vortex method under stir casting route. Two standard sized specimen (H/D Ratio as 1 and 1.5 ) are fabricated from each of the 3 different compositions mentioned , along with the pure AA7075. The specimen were investigated for the compressive strength and strain behavior by means of Universal testing machine (INSTRON) under no friction condition. The plastic behavior of the specimen were studied as function of various stresses and the same were validated by results obtained from finite element analysis and found to be in good concurrent.
An IoT enabled Smart Garbage Management System for Smart Cities – Indian Scenario
Authors:   Department of Electronics and Communication Engineering, Kongu Engineering College, Perundurai, Erode, Tamilnadu, India., Vinod* Vibin Mammen , Sevan Dr. K. S. Tamil ,   Department of Electronics and Communication Engineering, KPR Institute of Engineering and Technology, Coimbatore., Priya P Visva ,   Department of Electronics and Communication Engineering, Kongu Engineering College, Perundurai, Erode, Tamilnadu, India., Devi M Vishnu ,   Department of Electronics and Communication Engineering, Kongu Engineering College, Perundurai, Erode, Tamilnadu, India., C.S. Thiruselvam ,   UG scholar in the Department of Electronics and Communication Engineering at Kongu Engineering College, Erode, India.
Published: February 2020

With the ever increasing population and rapid urbanization, the challenge of efficient disposal is a bigger concern in a vast country like India. Numerous techniques and methods have been proposed by various authors but the implementation of the same has found very little patronage. The biggest challenge in waste management is the timely cleaning up of the community bins which are not happening leading to large scale pollution and degradation in the land structure. A novel smart garbage management system suitable for Indian conditions is proposed. The proposed scheme enables the civic body to schedule the clearing of all the bins in the locality by estimating a route map for the traversal. This drastically reduces the manpower, fuel and difficulty in navigation. The level of the waste is measured using the Ultrasonic Sensor. If the wastage level reaches a certain value., i.e. fixed threshold value, an SMS is send to the concerned authority and if the level of wastes is above 95% the call will be initiated to the municipal corporation. A path planner is developed which enables the traversal in the shortest possible route.
Interpretation on Energy Consumption of DYMO Protocol Towards Green Environment
Authors:   Department of Information Technology, SAP LABS India Pvt. Ltd., Bangalore, India., Suresh* Koduru , Raju K Narasimha ,   Department of Computer Science, Lendi Institute of Engineering and Technology, Visakhapatnam, India.
Published: February 2020

Mobile Ad hoc Network is a decentralized network which can be deployed instantly. Routing is a very challenging task in this network due to dynamic movement of mobile nodes. Various routing protocols such as OLSR, DYMO and ZRP are proposed to establish the route for the data packets in MANET’s. As deploying of the protocols into real environment is a cost expensive process, the protocols are initially evaluated through a simulated arena. Many of the mobile devices are battery equipped and each protocol consumes energy in different manner. In this paper, energy consumption evaluation is carried out on OLSR, DYMO and ZRP protocols in a grid environment. The experiments have shown that DYMO protocol has less energy consumption when compared to OLSR and ZRP protocols.
Field Level Security of the Sensitive Data in Large Datasets
Authors:   Professor, Department of Computer Science and Engineering, Sreenidhi Institute of Science and Technology, Hyderabad, Telangana State, India., Shirisha* K. , Kunta Haritha ,   Associate Success Agent, Salesforce.com India Pvt. Ltd. Hyderabad, India.
Published: February 2020

The process of deriving useful and knowledgeable information from enormous quantity of data is Data Mining. During mining procedures, handling of the sensitive data has become important to protect data against illegal attacks and malicious access either during transmission or at rest. Association rule algorithm is one of the rule extraction techniques. The rules determined are either to be transferred over the public networks or to be rested for further use.The main objective of the Field Level Security of the Sensitive Data in Large Datasets is to extract the strong association rules from the large data sets and the outcomes are crafted to conceal the sensitive data. The datasets and the association rules involving the attributes with relationships and dependencies are modified through several approaches and to see that no sensitive association rule is derived from it[1]. Privacy preservation of the sensitive association rules in large datasets is to provide secrecy for the sensitive data. Presently, it has become quite important to safeguard the privacy of the users’ personal data from unauthorized persons. The usage of association rules in voluminous datasets has emerged to be advantageous to organizations [2]. In this paper, we present a novel approach which is applied for hiding sensitive association rules by utilizing the techniques of compression, encryption method ology on the original dataset, providing dataset with better immunity.
Adhesion of Mineral Binders with Organic Aggregates
Authors:   Professor, Department of Civil Engineering, Tashkent Institute of Architecture, Tashkent. Uzbekistan., Khabibilla* Kamilov , Abdukabil Tulaganov ,   Professor, Department of Civil Engineering, Tashkent Institute of Architecture, Tashkent. Uzbekistan.
Published: February 2020

The article presents the results of studies of the adhesion properties of organic aggregates such as rice husks, cotton stalks, kenaf core and pine shavings with mineral binders Portland cement, gypsum and alkaline activated binder. It was shown that adhesion between the organic aggregate and mineral binders depends not only on the type of binder, but also on the type of organic aggregate and its surface structure
Spatial Monitoring of Urban Development Direction using Landsat 7 ETM+ and Landsat 8 OLI/TIRS in Balikpapan City, Indonesia
Authors:   Department of Geographic Information Science, Faculty of Geography, Universitas Gadjah Mada, Yogyakarta, Indonesia, Dewantoro* Bayu Elwantyo Bagus , Natani Pavita Almira ,   Departement of Civil Engineering and Planning, Institut Teknologi Kalimantan, Balikpapan, Indonesia., Islamiah Zumrotul ,   Departement of Civil Engineering and Planning, Institut Teknologi Kalimantan, Balikpapan, Indonesia.
Published: February 2020

The development of urban areas in the city of Balikpapan increases over time and is characterized by increasing population. The growth and development of urban areas needs to be monitored so that the control function on area spatial can be implemented. This research aims to determine the direction of urban areas and measure the density of the built-up as a leading indicator of the development of urban areas in Balikpapan. The method used in this study is the multispasio-temporal analysis of remote sensing data of Landsat 7 ETM+ and Landsat 8 OLI/TIRS which contain a combination of spectral transformation, classification supervised Maximum Likelihood, accuracy assessment and statistical analysis. The results showed the trend of urban development from 2001 to 2019 towards east and northeast with the highest built-up density located in the sub-district of Balikpapan Tengah by 82.07% and followed by the sub-district of Balikpapan Kota by 76.94%. The largest land conversion took place on the bare soil with low vegetation density class to be vegetation with the converted area of 7095.91 ha or approximately 14.10% followed by the bare soil with low vegetation density class to be built-up with the converted area of 5826.86 ha or about 11.58% of the total area of Balikpapan city during the period from 2001 to 2019. The accuracy of urban development map in 2001 reaches 92.39 % and the year 2019 reaches 95.69 %, while the accuracy of land cover map in 2001 reaches 85.57% and the year 2019 reaches 87.28 %.
SSW: Smart Steering Wheel for Real-Time Heart Rate Monitoring of Drivers
Authors:   Department of Information Technology, Bannari Amman Institute of Technology, Sathyamangalam, Tamil Nadu, India., J* Priya , T S Reshmi ,   Department of Information Technology, Bannari Amman Institute of Technology, Sathyamangalam, Tamil Nadu, India., Gunasekaran M ,   Department of Information Technology, Bannari Amman Institute of Technology, Sathyamangalam, Tamil Nadu, India.
Published: February 2020

It’s very hard to know that Over 467,044 accidents took place specifically on the road in our country in 2018 as per a report revealed by the MoRTH recently. Rapid increasing in numbers of vehicles on the road, stress level of drivers in traffic and even lethargic driving are few reasons for road accidents. Unfortunately, sudden heart attacks of drivers also a reason behind some road accidents; this can be preventable. During driving, monitoring heart rate is not a big deal in today’s hi-tech world. Health monitoring while driving is not only important in daily healthcare, also a prevention of bus accidents. Here the proposed work is designing a smart steering wheel based on the technology so-called the Internet of Things (IoT) that monitors the heart rate and foresees the onslaught of fatigue of a driver; also it shares the location to the rescue team. Pulse sensor, GPS and GSM modules are conjoined into the steering wheel. The setup once it gets powered-up, which transmits the data of a driver’s health condition and get stored in the cloud environment. By this approach, the steering wheel gives the real-time based monitoring. Therefore this work is aiming for the development of a system which includes multiple sensors incorporated with the steering wheel which is capable to measure the pulse rate and alert the rescue team dynamically about the health related data of a driver, to prevent accidents.
New Algorithm for Dht and Its Verilog Implementation
Authors:   Department of ECE, Maharaja Agrasen Institute of Technology(MAIT) affiliated to GGSIP University, Delhi, India., Jain* Anamika , Pandey Prof. Neeta ,   Department of ECE, Delhi Technological University(DTU) Delhi University, Delhi, India.
Published: February 2020

This paper presents a new algorithm for computing Discrete Hartley Transform (DHT) (type-2) of N with N=4r, where r>1.Paper also suggest VLSI architecture for the implementation of the newly developed algorithm. The computation of DHT using this algorithm is simple and requires less arithmetic operations compared with the general method for finding DHT. Also the suggested VLSI structure for the algorithm is regular and less complicated in terms of hardware requirement. Parallel processing of the algorithm make the processing further fast.
Efficient Horizon Line Detection using Clustering and Fast Marching Method
Authors:   Research scholar, Jawaharlal Nehru Technological University Ananthapuramu, AP, India., Sravanthi* Ravi , Sarma Dr ASV ,   Professor, Dept., of ECE, PBR VITS, Kavali, AP, India.
Published: February 2020

Video analysis of maritime scenarios typically includes detection of horizon line for reference. The horizon line is the imaginary line, which separates water and sky as well as water and land. The horizon line plays a major role in terms of demarcating the water region in the video frame for further analysis. Considerable research has been aimed at horizon line detection. Various approaches have been reported including (i) Canny based edge detection followed by Hough transform, (ii) machine learning combined with statistical methods. However, the Hough transform has several limitations, in terms excessive analysis time, deviation of estimated line from the actual horizon line, sensitivity to presence of floating objects on the horizon, error due to presence of large number of edges. Present paper describes an efficient method for detecting the horizon line for analysis videos obtained by cameras mounted on floating vessels such as unmanned surface vehicle in maritime and inland scenarios. The proposed method is based on K-means clustering followed by seed based region growing using Fast Marching Method. For detecting the horizon line, two clusters are used in water-sky region like in marine environment images whereas three or more clusters are used in water-land-sky region like in in-land rivers/lakes images. In most cases, the upper part of the frame belongs to sky region whereas lower part belongs to water region. After K means clustering, based on the selection of seed point in lower part of the frame, the water region is segmented using fast marching method from non water regions and hence the horizon line is detected. This proposed method performance is compared with edge detection followed by Hough transform for different datasets. Experimental results show that the proposed method detects efficient line without compromising the processing time.
GMM-UBM Based Modeling for Language Identification using New Feature Vectors
Authors:   Professor, Department of CSE, MGIT, Hyderabad, India., Nagesh* Dr. A. , Sadanandam Dr. M. ,   Assistant Professor & BOS, Department of Computer Science & Engineering at Kakatiya University, Warangal, India.
Published: February 2020

The most of the existing LID systems based on the Gaussian Mixture model. The main requirement of the GMM based LID system is it require large amount of speech data to train the GMM model. Most of the Indian languages have the similarity because they are derived from Devanagari. Even though common phonemes exists in phoneme sets across the Indian languages, each language contain its unique phonotactic constraints imposed by the language. Any modeling technique capable of capturing all these slight variations imposed by the language is one of the important language identification cue. To model the GMM based LID system which captures above variations it require large number of mixture components.To model the large number of mixture components using Gaussian Mixture Model (GMM), the technique requires a large number of training data for each language class, which is very difficult to get for Indian languages. The main objective of GMM-UBM based LID system is it require less amount of training data to train(model) the system. In this paper, the importance of GMM-UBM modeling for language identification (LID) task for Indian languages are explored using new set of feature vectors. In GMM-UBM LID system based on the new feature vectors, the phonotactic variations imparted by different Indian languages are modeled using Gaussian Mixture model and Universal Background Model (GMM-UBM) technique. In this type of modeling, some amount of data from each class of language is pooled to create a universal background model. From this UBM model each model class is adapted. In this study, it is found that the performance of new feature vectors GMM-UBM based LID system is superior when compared to conventional new feature vectors based GMM LID system.
Enhancing the Security in ElGamal Cryptosystem using Paring Functions
Authors:   Associate Professor, Department of Computer Science Department of Nehru Memorial College, Puthanampatti, Affiliated to Bharathidasan University, Trichy, India, K* Mani. , Begam A. Barakath ,   Department of Computer Science Department of Nehru Memorial College, Puthanampatti, Affiliated to Bharathidasan University, Trichy, India.
Published: February 2020

The potential disadvantage of ElGamal cryptosystem is the ciphertext produced is always twice as long as the plaintext i.e., the message expansion by a factor of two takes place during encryption. When the message is too long the ciphertext produced by the ElGamal cryptosystem is also too long. i.e., when the ciphertexts are transmitted through the communication channel which lead to provide less security because if anyone of the ciphertext from two ciphertexts for each character of the plaintext is intercepted by the adversary, the other may be retrieved easily because there is a relationship between the two ciphertexts. If two ciphertexts are reduced to one, the adversary may not be able to predict the two ciphertexts from one. To enhance the security of ElGamal cryptosystem, the binary Cantor function , Rosenberg pairing function and Elegant pairing functions are used in this paper. When the said functions are used, the two ciphertexts produced by each plaintext character are reduced to one, so that the adversary cannot easily be recovered the plaintext. Experimental results clearly revealed enhancing the security of ElGamal cryptosystem after incorporating the pairing functions into it.
A Comprehensive Research on Integration of Cloud with Software-Defined Network
Authors:   Department of Computer Science, Sukkur IBA University, Sindh, Pakistan, Sahito Sanam Fayaz , Detho Samreen ,   Department of Computer Science, Sukkur IBA University, Sindh, Pakistan., Shah Syed Asif Raza ,   Department of Computer Science, Sukkur IBA University, Sindh, Pakistan., Kim Tae-Hyung ,   Samsung Electronics, Seoul, Korea., Noh* Seo-Young ,   Department of Computer Science, Chungbuk National University, Cheongju, Korea.
Published: February 2020

Cloud computing, as one of the emerging technologies, is required to meet increasing and on-demand availability of all resources such as computing power, storage and networking. It provides the pool of resources and offers the mechanism to run various applications on Cloud Data Centers (CDCs). Cloud data centers are usually distributed across multiple sites. With the provision of distributed data centers, the need for their management and maintenance arises. Such circumstances lead networking capabilities to being implemented on larger scale. Software defined network (SDN) is the programming paradigm along with the NFV orchestration and incorporates the modular and dynamic network support for the cloud data centers provided and established by the cloud over the geographically separated places. In this paper, comprehensive study has been mainly conducted to highlight the need for the integration of both emerging and versatile technologies. We also cover challenges, issues and benefits which have to be considered in underlying architecture, models and devices.
Traceability System as a Component of Lifecycle Management of Radio-Electronic Products
Authors:   Department of Metrology and Standardization, Institute of Physics and Technology, MIREA - Russian Technological University, Moscow, Russia., Kirov* Alexey
Published: February 2020

This report is devoted to the review, analysis of the implementation and application of the traceability system in the lifecycle management of radio-electronic products. The main problems of traceability application at the enterprises of the radio-electronic industry, the ways of its integration into life cycle management are identified. The importance and the advantages of modern traceability systems are highlighted. The main issues of their implementation and related problems are addressed. The main ways to provide identification of electronic components, printed circuit boards, equipment and personnel are described. The technical requirements for project realization and its stages are numbered. Complex supply chains and high risks related to it make traceability systems with its advanced functions, tools for control, management and analysis necessary for the lifecycle management of electronic products. Their implementation not only reduces the risks, but also provides the enterprises with a number of advantages witch boost effectiveness and profitability.
Drilling of Ceramic Reinforced Aluminum Matrix Composite under Dry Condition
Authors:   Department of Mechanical Marathwada Institute of Technology, Aurangabad, India., Agrawal* Sachin M. , Patil Nilesh G. ,   Department of Mechanical Marathwada Institute of Technology, Aurangabad, India.
Published: February 2020

In this study an experimental investigation of effects of cutting parameters on surface roughness during drilling of silicon carbide particulate reinforced aluminium matrix composite material under dry condition was carried out. Cutting speed , feed rate and % SiC in aluminium matrix composites were chosen as cutting parameters. The experimental design adopted for this investigation was the central composite design of response surface methodology. Thirty one readings were taken on VMC machine for dry condition and the surface roughness measured using Mitutoyo surface tester. Surface roughness values for dry condition were lower with 30% SiC reinforced aluminium matrix composites when compared to 10 % and 20 % SiC reinforced aluminium matrix composites . As cutting speed increased Ra & Rz value also increased .% SiC was found most significant factor while drilling aluminium matrix composites.
Dynamic Response of Symmetric and Asymmetric Setback Buildings
Authors:   Research Scholar, Department of Civil Engineering, UVCE, Bangalore University, Bangalore, India., R.M* Thejaswini , Govindaraju L. ,   Professor, Department of Civil Engineering, UVCE, Bangalore University, Bangalore, India., Devaraj V. ,   Research Professor, Department of Civil Engineering, Dr.AIT, Bangalore, India.
Published: February 2020

Numerical studies have been carried out to study the dynamic behaviour of a five-storey regular building, symmetric setback and asymmetric setback buildings having three bays along longitudinal direction and one bay along transverse direction. The objective of the study is to compare the irregularity indices with respect to different codal provisions such as IS:1893-2016, Euro Code 8-2004 and ASCE 7.05-2005 as well as with the expressions proposed by Karavasilis et al. (2008), and Pradip sarkar et al.(2010). These buildings are subjected to seismic excitations with time history analysis and the response parameters such as fundamental period of vibration of the structures, displacements and storey drifts were evaluated.
Drilling of Ceramic Reinforced Aluminum Matrix Composite under Minimum Quantity Lubrication using Bio Cutting Fluid
Authors:   Research Scholar, Marathwada Institute of Technology, Aurangabad, Maharashtra, India., Agrawal* Sachin M. , Patil Dr. Nilesh G. ,   Research Guide, Professor & Principal, Marathwada Institute of Technology, Aurangabad, Maharashtra, India.
Published: February 2020

In this study an experimental investigation of effects of cutting parameters on surface roughness during drilling of silicon carbide particulate reinforced aluminium matrix composite material under minimum quantity lubrication (MQL) condition was carried out. Cutting speed , feed rate, flow rate and % SiC in aluminium matrix composites were chosen as cutting parameters. The experimental design adopted for this investigation was the central composite design of response surface methodology. Thirty one readings were taken on VMC machine for MQL condition and the surface roughness measured using Mitutoyo surface tester. Surface roughness values for MQL condition were lower with 30% SiC reinforced aluminium matrix composites when compared to 10 % and 20 % SiC reinforced aluminium matrix composites . As cutting speed increased Ra & Rz value also increased .% SiC was found most significant factor while drilling aluminium matrix composites.
Advanced Wireless Body Area Network
Authors:   Assistant Professor, QIS College of Engineering & Technology (Autonomous), Ongole, AP, India, Shakeela* Sk. , Krishna M. Nitya Rama ,   Assistant Professor, QIS College of Engineering & Technology (Autonomous), Ongole, AP, India
Published: February 2020

Wireless Body Area Networks (WBANs) is the most widely used in many fields to overcome the issues identified in various applications. In general, various authentication protocols are utilized with a novel certificateless signature (CLS) scheme, which is computational, efficient, and provably secure against existential forgery on adaptively chosen message attack in the random oracle model. Also, the proposed designs ensure that application or service providers have no privilege to disclose the real identities of users. Even the network manager, which serves as private key generator in the authentication protocols, is prevented from impersonating legitimate users. The performance of our designs is evaluated through both theoretic analysis and experimental simulations, and the comparative studies demonstrate that they outperform the existing schemes in terms of better trade-off between desirable security properties and computational overhead, nicely meeting the needs of WBANs.
Design and Construction of Indirect Solar Coffee Dryer
Authors:   Assistant Lecturer, Department of Mechanical Engineering, Madda walabu University, Bale Robe, Ethiopia, Gachen* Abeba , Hirpesa Zewude ,   Assistant Lecturer, Department of Mechanical Engineering, Madda walabu University, Bale Robe, Ethiopia, Woyessa Lemi Negera ,   HOD, Department of Mechanical Engineering, Madda walabu university, Bale Robe, Ethiopia
Published: February 2020

Drying is the process of removing moisture contents from solid. Solar drying refers to a technique that utilizes incident solar radiation to convert it into thermal energy required for drying purposes. This project presents the design, construction and performance of an indirect type solar dryer for coffee product. In the dryer the air inters into the solar collector from the atmosphere through air inlet hole. This air will be heated in the collector and then pass to the drying chamber through the hole. Then the air exhausts through the outlet hole at the top of the drying chamber. The system designed can handle a capacity of up to 50kg of wet coffee per m2at a depth of 100 mm. The average sunshine at Bale Robe was found to be 12 hours per day. The daily solar insolation at the site was found to be 5.86kW/m2 of surface per day. By utilizing the solar collector in question and assuming a collector efficiency of 20 %, the total solar energy received is 5.86 kW-hrs/m2/day or 46.88 kW-hours per day (assuming the sunshine hours per day to be 8 hours). This solar dryer has a collector efficiency of 39.1%, a pick-up efficiency of 49.3%, and a system efficiency of 32.2%. the collector area of the system is calculated to be 1.11m2 and the total length of 1000mm by 300mm. The drying chamber is essentially a cabinetry dryer and measures 1020mm × 800mm × 30mm. It accommodates a drying bin which acts as the holding compartment for the wet coffee to be dried. The base of the drying chamber is made of a block of wood material 50mm deep, since wood is a good thermal insulator. The wood must be well seasoned and pre-treated to ensure it is protected from the humid environment. The air outlet is fitted at the top of the drying chamber which serves as the exit for the moisture ridden air. It is important since it ensures that moisture does not condense at the top of the drying chamber and speeds up the rate of drying through creating the suction effect. The drying bin measures 800mm × 800mm × 20mm.
Asymmetric key Cryptography using Laplace Transform
Authors:   Asst. Professor, Department of Mathematics, GIS, GITAM (Deemed to be University), Visakhapatnam, India., Nagalakshmi* G. , Sekhar A. Chandra ,   Professor, Dept of Mathematics, GIS, GITAM (Deemed to be University), Andhra Pradesh, India., Shankar N. Ravi ,   Professor, Dept of Mathematics, GIS, GITAM (Deemed to be University), Andhra Pradesh, India.
Published: February 2020

This paper presents a method of Asymmetric key cryptography using Laplace transform and inverse Laplace transform respectively on Maclaurin’s series to attain information and network Security. The public key and private key are used to encrypt and decrypt data in Asymmetric cryptography. Public and private key are generated using Encryption and Decryption algorithms with a numerical example. Frequency allocations of characters in plain text file and cipher text file with proposed algorithm are analyzed using bar diagrams. It has been observed that the repeated character in encipher file has same frequency while running ElGamal and RSA encryption algorithms but differ in proposed algorithm. Time complexity of each algorithm is tested for distinct file size and is presented in a suitable table. Statistical analysis for the proposed algorithm is performed using coefficient correlation and compared with ElGamal, RSA algorithms. All these tests ensure that the proposed algorithm provide network security and key recovery attack.
Intrusion Detection System on Big data using Deep Learning Techniques
Authors:   Manipal University Jaipur, Rajasthan. Department of School of Computing-CA, DIT University, Dehradun, India., Dahiya* Priyanka , Srivastva Devesh Kumar ,   Department of School of Computing & Information Technology, Manipal University Jaipur, Rajasthan, India.
Published: February 2020

Big data is the huge amount of data with different types of V’s: Velocity, Variety as well as Volume. It can be semi-structured, unstructured or structured, due to which it is not easy to analyze the data. To extract the hidden knowledge and to detect the attacks on large amount of data new architecture, techniques, algorithms, and analytics are required. Using traditional techniques to detect attacks is very difficult. In this paper, the detailed review has been done on intrusion detection on various fields using deep learning and gives an idea of applications of deep learning. The number of attacks has been increased in computer networks. A powerful Intrusion Detection System (IDS) is required to ensure the security of a network. Based on review, it is found that some studies have been done in this field, but a deep and exhaustive work has still not been done. Many researchers proposed an IDS using deep learning for unforeseen and unpredictable attacks but not for Big Data. The proposed work is based on Deep learning based intrusion detection System for big datasets named hybrid-DeepResNet-RNN run till 1,000 epochs with learning rate varying range [0.01-0.5] and three ensemble techniques, Random Forest, Decision tree regression and Gradient Boosting Tree (GBT). It is used to develop the hybrid, secure, scalable NIDS which is based on deep learning and big data techniques. The proposed classifiers produce a more reliable classification than a single classifier. The experimental results are in terms of detection rate (98.86%), false positive rate (1.110%), accuracy (99.34%) and F-Measure (97.90%). The results illuminate the better performance than existing anomaly detection techniques in the big data environment.
Performance Optimization of the MIMO-OFDM Based Adaptive Cognitive Radio System using a Hybrid Channel Access Scheme
Authors:   D.O.T., Shivaji University, Kolhapur, India., Itraj* Santosh , Bombale Dr. Uttam ,   D.O.T., Shivaji University, Kolhapur, India., Patil Pravinkumar ,   Visvesvaraya Technological University (VTU) Public university, Belgaum, Karnataka, India., Patil Dr. Meenakshi ,   Visvesvaraya Technological University (VTU) Public university, Belgaum, Karnataka, India.
Published: February 2020

The cognitive radio is a promising candidate to resolve the issues created due to the spectrum scarcity in wireless communication. The main motive of CR technology is to create communication opportunities by sensing and learning from the external environment thereby improving the spectrum usage efficiency. The integration of the link adaptation, MIMO-OFDM with CR technology gives the utmost performance. In this treatise, we propose the hybrid channel access (interweave-underlay) scheme for the MIMO-OFDM based adaptive CR system. We have investigated the performance of the CR system under a hybrid channel access (interweave-underlay) scheme as well as underlay channel access scheme. We consider the binary stochastic model to reflect the primary user (PU) activities. The performance is evaluated with different channel detection probabilities under perfect as well as imperfect (false alarm) spectrum sensing environment. The result shows the significant improvement in the throughput of the system in proportion with the higher-quality channel detection probability with perfect spectrum sensing. This exploits the hybrid channel access scheme as one of the techniques to optimize the performance of the system. This signifies the importance of the optimum channel sensing and its selection in improving the performance of the system. To show the performance improvement of the CR system using hybrid channel access scheme we have compared it with the performance of the CR system based on the conventional underlay channel access scheme. The proposed scheme can be used to improve the performance of the entire CR network.
Data Mining Application in Predicting Bank Loan Defaulters
Authors:   School of Informatics, Wolaita Sodo University, Ethiopia., Nixon* J. Sebastian , Desta Ashenafi Wubshet ,   School of Informatics, Wolaita Sodo University, Ethiopia
Published: February 2020

Data mining is the key tools for discoveries of knowledge from large data set. Nowadays, most of the organizations using this technology to maintain their data. This paper focuses on the Bank sector in Risk management specifically, detecting Bank loan defaulters through the data mining application to examine the patterns of different attribute which would contribute for detecting and predicting defaulters thus preventing wrong loans. This process can be done without change the current systems and the data. Then it helps to distinguish borrowers who repay loans promptly from those who don’t and avoid wrong loan allotment. In order to show the results of the study Classification model is implemented in order to find interesting patterns among attributes of customer. A total of 20461 sample data were taken by data base admin randomly from 3 consecutive years from the Bank database to build and test the model. In this research we used Classification model of decision tree and Naïve Bayes in Weka 3.7 tool for experiments. Modeling methodology applied to this paper was CIRSP-DM (Cross Industry Standard for Data Mining), which involves business understanding, data understanding, data preparation, model building, evaluation and deployment. Decision tree classifications with J48 implementation with 8 experiments were performed. Two experiments with different parameters were made for Naïve Bayes. Finally, evaluation and analysis of the models were performed then given a best solution to predict the defaulters.
Using of Artificial Neural Networks in Support System of Forensic Building-Technical Expertise
Authors:   Rector of Kyiv National University of Construction and Architecture, Kyiv, Ukraine, Kulikov Petro , Pasko Roman ,   Laboratory of Engineering and Technical Research, Kyiv Scientific Research Institute of Forensic Expertise of the Ministry of Justice of Ukraine, Kiev, Ukraine., Terenchuk Svitlana ,   Department of Information Technology Design and Applied Mathematics, Kyiv National University of Construction and Architecture, Kyiv, Ukraine., Ploskyi Vitalii ,   department of Architectural Structures, Kyiv National University of Construction and Architecture, Kyiv, Ukraine., Bohdan* Yeremenko ,   Department of Information Technology Design and Applied Mathematics, Kyiv National University of Construction and Architecture, Kyiv, Ukraine.
Published: February 2020

The article contains an analysis of the order of forensic building-technical expertise and expert research to determine the reasons for the deterioration of the technical condition of the structural elements of buildings. The conditions for forming expert conclusions about the possible correlation between the appearance of negative changes in the technical condition of the structural elements that have become the subject of forensic building-technical expertise and the various factors of influence of the environment are investigated. In doing so, the focus is on the impact factors associated with carrying out renovation work in adjacent premises. In addition, issues related to the fuzzy uncertainty of the different nature of the expert researches are highlighted. Some of these problems are proposed to be solved by the using of artificial neural networks in the fuzzy subsystem of the system of support of forensic building-technical expertise. It is shown that a considerable part of the materials of forensic building-technical expertise and expert research is represented by photographs of injuries. Fixation of damaged structures is reflected in the plans of premises and schemes of placement of structures in the buildings. The graphic information of the research materials is accompanied by textual information, the processing of which requires the use of models and methods of fuzzy mathematics. The fragment of the knowledge base is provided, which contains information on the geometric parameters of damage to building structures and an example of a fuzzy rule that reflects an expert conclusion. The expediency of using fuzzy neural networks of adaptive resonance theory of the Cascade ARTMAP category is substantiated. Cascade ARTMAP memory card schematic is shown.