bluuebunny/crossref_metadata_2025 huggingface dataset:
Density based Automatic Traffic Junction Synchronization
Authors:   Department of Electronics and Communication Engineering, School of Engineering and Technology, Jain(Deemed-to-be University) Bangalore, India., H.B Pallavi , Shrikanth Aishwarya ,   Department of Electronics and Communication Engineering, School of Engineering and Technology, Jain(Deemed-to-be University) Bangalore, India., S Sandeep ,   Department of Electronics and Communication Engineering, School of Engineering and Technology, Jain(Deemed-to-be University) Bangalore, India., S.A Sushanth S.P, Dr. Hariprasad ,   Department of Electronics and Communication Engineering, School of Engineering and Technology, Jain(Deemed-to-be University) Bangalore, India., M.P Sunil ,   Department of Electronics and Communication Engineering, School of Engineering and Technology, Jain(Deemed-to-be University) Bangalore, India.
Published: August 2019

Traffic congestion nowadays has become a chronic issue in the Metropolitan cities due to which it takes more time to travel than the same distance travelled during the off peak hours. This decreases the productivity of an individual by instances such as delayed delivery of services, unnecessary fuel consumption, air and noise pollution, delay in the case of emergency. The traffic congestion has become a predominant problem due to the rapid increase in the demand of vehicles. In places where junctions are closely spaced, encounter a typical issue of lingering in the same traffic signal for multiple times due to the slow moving vehicle caused by congestion. In order to control this issue, research works have been carried out in automating the traffic control system with the help of sensors, image or video processing and also by prioritizing emergency vehicles approaching the junctions. However, employing camera to monitor the traffic is an expensive task. Thus, we are proposing the Density based synchronous of junctions that are closely placed which helps us to save our commuting time significantly and thus enhancing one’s productivity.
Red Brick Dust as a Partial Substitute to Cement in Conventional Concrete
Authors:   Assistant Professor, Department of Civil Engineering, S R K R Engineering College, Bhimavaram, India., Raju J. N. S. Surya Narayana , Reddy S. Srikanth ,   Assistant Professor, Department of Civil Engineering, S R K R Engineering College, Bhimavaram, India., Raju P. ,   Assistant Professor, Department of Civil Engineering, S R K R Engineering College, Bhimavaram, India, Jagadeep K. ,   Assistant Professor, Department of Civil Engineering, S R K R Engineering College, Bhimavaram, India.
Published: August 2019

In emerging countries like India, the government plans for mega-infrastructure projects for the development of the country. These projects involve construction of high-rise buildings and high-speed rail and road networks. These constructions require higher quantities of concrete, which is a combination of cement, fine and coarse aggregate. The manufacturing process of cement results in emission of CO2, a pollutant which causes serious health hazards to living beings. The adverse effects are not only limited to posing threat to living beings, but also result in depletion of natural resources which are used as key ingredients in manufacturing cement. This mandates the need to search for cement replacing materials which maintain the same strength or improve the strength of conventional concrete. Red brick Dust is a highly siliceous waste material which is available near brick kilns or while dismantling buildings. Improper handling of red brick dust causes silicosis disease in human beings, when inhaled. Hence there is a need to dispose it off safely. It is reported by various researchers that red brick dust when used as an additive in concrete, improved the strength and durability aspects. Hence, in the present study, it is aimed to improve the compressive strength of conventional concrete by substituting cement partially with red brick dust in conventional concrete. The study has revealed that upon substituting cement with red brick dust, the compressive strength of conventional concrete is increased by about 13%. The present study reveals that red brick dust can be effectively used as a partial substitute to cement in conventional concrete thereby addressing the adverse effects of cement manufacturing and health hazards of improper disposal of red brick dust.
Axial Behavior of Corroded CHST Members Confined with AFRP Sheets
Authors:   Assistant Professor, Department of Civil Engineering, Anand Institute of Higher Technology, Chennai, (Tamil Nadu), India., Modak Nabajyoti , Sivasankar Dr.S. ,   Associate professor, Department of Civil Engineering, CMR Technical Campus, Hyderabad, (Telangana), India.
Published: August 2019

Strengthening of structural members is a mechanism of promoting structures to upgrade its attainment under existing loads or to boost the fortitude of structural members to carry further loads. Any frailty at the time of designing or any other construction errors may lead to the cause of structural deterioration causing failures of the structural members. This paper presents an experimental study on the behavior of corroded Circular Hollow Steel Tubular (CHST) members strengthened with Aramid Fiber Reinforced Polymer (AFRP) composites. In this field, the experimental investigation is narrowed up to the usage of Glass Fiber Reinforced Polymer (GFRP) and Carbon Fiber Reinforced polymer (CFRP) and also in the application procedure i.e., the wrapping scheme. Prime advantages of AFRP over steel members are low weight, highly durable, corrosion resistance and easy applicability. The workability and the consonance of AFRP were studied in this paper to evaluate the confinement of AFRP in the strengthening effect of CHST members. The main deprivation of AFRP is the cost alone. So, in this experimental process, instead of going full wrapping, a special technique of spiral wrapping was adopted to get the closed confinement of AFRP. Totally twelve specimens were casted and tested to execute the experimental work including both control and wrapped specimens by controlling different parameters up to the failure mode. The experimental results uttered the increment in the load carrying capacity of the wrapped specimens. The involvement of AFRP in the better confinement was observed in the experimental results with the increase in the number of layers of AFRP strips. From the series of experiments, the results which were collected were compared with the control sample to determine the variation and then the axial stress-strain curve and load deflection curve were studied. It was also observed that, the local buckling was getting delayed with the increase in the number of layers of AFRP strips.
Cloud Computing Model for Agricultural Applications
Authors:   School of Computer Science and Application, REVA University, Bangalore, India., M Vimala , Ranjan Rajeev ,   School of Computer Science and Application, REVA University, Bangalore, India.
Published: August 2019

There are major advancements in the technological fields, which include the smart farming with the IoT, Big-data, Cloud-service oriented architectures along with the internet etc. While considering the current situation in the field of agriculture, there are many issues being faced. Some of the major problems are climatic-changes, lack of the fresh-water availability, much barren lands and decrease in the farming lands, less power availability, etc. The agricultural architecture that are cloud-based or the cloud-service oriented architecture includes the monitoring of farming and the warehousing-information. In this paper, we provide a work on IoT, aerial images and SOA and how they can be applied on the large and the smart farming systems, which is scalable and that can be easily configured. An event-driven SOA is necessary to facilitate the flawless and significant information and integration of distributed and heterogeneous internet agricultural services to help real-time user preferences.
Optimization of Store Layout using Market Basket Analysis
Authors:   Student, Rajagiri Business School, Kochi, India, Joe Tom , R Sreejith ,   Asst. Professor, Rajagiri College of Social Sciences, Kochi,India, Sekar Kannan ,   Asst. Professor, Rajagiri Business School, Kochi, India,
Published: August 2019

Store layout is a crucial factor for attracting customers in a retail store. Use of appropriate store layout results in an increase in sales of the store. Grid layout, free flow layout, spine layout is a few commonly used store layouts in the retail store. The grid layout is used for supermarkets but the placement of different products as per the preference of the customer is quite an arduous task there. Purchase history of a supermarket can be utilized to predict the preferences of the customers and can be utilized as an aid for designing a better store layout. Market basket analysis is employed to get insights from the POS data of the supermarket. Market basket analysis (MBA) helps to extract the various association rules from the purchase data of the shoppers. A customer can pick different items identified with the items that the person has just put in his or her shopping basket or cart which frames an association rule. The extraction of such rules can help in the appropriate product placement in the store as per the shopper’s preference.
Augmentation of Classifier Accuracy through Implication of Feature Selection for Breast Cancer Prediction
Authors:   B G, Assistant Professor, holds MCA in Computer Applications from VTU and B.Sc. in Computer Science from Kuvempu University., Mrs. Deepa  , Senthil Dr. S. ,   Professor and Director, School of Computer Science and Applications, REVA University, India.
Published: August 2019

Breast Cancer Examination and Prediction are great provocations to the researchers in the medical applications. Breast Cancer Examination distinguishes benign from malignant breast lumps, Breast Cancer Prediction has great deal in foretelling when Breast Cancer is expected to reoccur in patients that have had their cancers excised. Feature Selection is considered to be the preliminary step used in process to find best subsets of attributes. In this paper authors confer about the performance of five classifiers Sequential minimal optimization (SMO), Multilayer Perceptrons, Kstar, Decision Table and Random Forest with and without feature selection. The results manifest that after implying two feature selection techniques such as Correlation based and information based with ranker algorithm there is an augmentation in the accuracy rate of the classifier. It has been observed that after through implication feature selection techniques accuracy of the classifiers such as SMO, Multilayer Perceptrons, Kstar, Decision Trees, and Random Forest are enhanced.
Customer Segment Prognostic System by Machine Learning using Principal Component and Linear Discriminant Analysis
Authors:   Professor, Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi, Chennai, TamilNadu, India., Suguna R. , Devi M. Shyamala ,   Associate Professor, Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi, Chennai, TamilNadu, India., Mathew Rincy Merlin ,   Lecturer, Department of Computer Science, College of Science and Arts, Khamis Mushayt, King Khalid university, Abha, Asir, Saudi Arabia.
Published: August 2019

Recently, manufacturing industry faces lots of problem in predicting the customer behavior and group for matching their outcome with the profit. The organizations are finding difficult in identifying the customer behavior for the purpose of predicting the product design so as to increase the profit. The prediction of customer group is a challenging task for all the organization due to the current growing entrepreneurs. This results in using the machine learning algorithms to cluster the customer group for predicting the demand of the customers. This helps in decision making process of manufacturing the products. This paper attempts to predict the customer group for the wine data set extracted from UCI Machine Learning repository. The wine data set is subjected to dimensionality reduction with principal component analysis and linear discriminant analysis. A Performance analysis is done with various classification algorithms and comparative study is done with the performance metric such as accuracy, precision, recall, and f-score. Experimental results shows that after applying dimensionality reduction, the 2 component LDA reduced wine data set with the kernel SVM, Random Forest classifier is found to be effective with the accuracy of 100% compared to other classifiers.
Failure and Thermal Examination of Hybrid Materials for a Propeller shaft in Aerospace Applications
Authors:   Mechanical Engineering Department, Basaveshwara Engineering College, Bagalkot, Karnataka, India., Shivanand  , Kerur Dr. Shravankumar B. ,   Mechanical Engineering Department, Basaveshwara, Engineering, College, Bagalkot, Karnataka, India
Published: August 2019

Hybrid materials are an attractive option in case of aerospace and aviation applications since they are exceptionally strong. The current study presents the failure analysis of the hybrid material in ANSYS software. The main aim of this study is to check the suitability of the MATLAB results obtained from the previously selected composite material comprising of carbon steel + epoxy + S glass + T700 fibres using ANSYS software by creating a solid three-dimensional meshed model of the shaft. Layerwise shaft theory and finite element analysis have been employed for developing the model. The thermal analysis, delamination and buckling failure studies are conducted and found that increasing the thickness of the material will increase its load withstandability. The load failure point is found to be 8.4mm from the delamination studies. From analysis it was understood that the chosen composite material could be used for the propeller shaft of an aircraft.
A Security Key Management Method using Grid Routing for EDDK in WSNs
Authors:   Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Republic of Korea., Chung Won Jin , Cho Tae Ho ,   Department of Software Platform, Sungkyunkwan University, Suwon, Republic of Korea.
Published: August 2019

Wireless sensor networks (WSNs) utilize event data collected through sensor nodes, which can be employed in different environments. Sensor nodes used in WSNs have limited energy and can be easily compromised by attackers since they are placed in the external environment. Therefore, energy efficiency and security are core requirements in WSNs, and various schemes have been proposed to solve them. The energy-efficient distributed deterministic key management scheme (EDDK) is a security scheme that uses distributed pairwise keys. The EDDK encrypts the packet using the pairwise key of the neighboring node, and transmits the encrypted packet securely to the base station (BS). In addition, the pairwise key shared with neighboring nodes is updated to defend against network attacks such as Denial of Service. However, the energies of the sensor nodes decrease rapidly in environments where key updates occur frequently. Further, since EDDK does not encrypt the sequence number, the attacker can manipulate this sequence number. If such attacks are continually attempted, key updates occur frequently. This paper proposes a scheme that removes the local cluster key from the EDDK and instead uses a grid routing protocol. The proposed scheme reduces the number of key updates by removing the local cluster key. In addition, the proposed scheme constructs the routing as a grid and selects the sensor node nearest to the BS as the master node. the master node of the grid routing scheme transmits routing control messages to the corresponding sensor nodes. In this way, the proposed method improves the sensor network energy efficiency. Experimental results show that the energy efficiency of the sensor network is improved by about 7.8097% compared with EDDK. Additionally, since the proposed scheme removes the local cluster key, sequence number manipulation attacks can be avoided. As a result, the security rate of the proposed scheme is more than double compared with EDDK.
Supervised Machine Learning Techniques for Predicting Sugarcane Yield
Authors:   Department of Computer Science and Engineering, KLS Gogte Institute of Technology, Belagavi, India., Medar Ramesh , Rajpurohit Dr. Vijay S. ,   Department of Computer Science and Engineering, KLS Gogte Institute of Technology, Belagavi, India.
Published: August 2019

Agriculture is the most important sector in the Indian economy and contributes 18% of Gross Domestic Product(GDP). India is the second largest producer of sugarcane crop and produces about 20% of the world's sugarcane. Sugarcane is cultivated in tropics and subtropic regions, on a wide range of soils from fertile well-drained mollisols to through heavy cracking vertisols, infertile acid oxisols, peaty histosols, to rocky andisols. Minimum moisture of 60cms, rich water supply and plenty of sunshine. In this paper, a novel approach to sugarcane yield forecasting in Karnataka, India region using Long Term Time Series(LTTS), weather-and-soil attributes, Normalized Vegetation Index(NDVI) and Supervised Machine Learning(SML) algorithms have been proposed. Sugarcane cultivation life cycle(SCLC) in the Karnataka region is about 12 months, with plantation beginning at three different seasons in weather condition. Our approach has been verified using historical dataset and results have shown that our approach has successfully modeled crop prediction. The application of the Custom-Kernel gives us a considerable boost in accuracy with SVM-Kernel Multiple giving 86.31% of accuracy, SVM-RBF kernel in second with an accuracy of 83.40%, GPR producing an accuracy score of 81.75%, Lasso giving an accuracy score of 26.81% and Kernel Ridge-RBF with the least accuracy score of 21.46% for final yield prediction.
Prevention of Black Hole Attacks in Virtualized Cloud Network Using Trust-Aware Energy Efficient AODV Routing With Firefly Based AI Technique
Authors:   Department of Information and technology,University Institute of Engineering and Technology,Panjab University, Chandigarh, India., Sharma Priyanka , Kumar Saurabh ,   Computer Science and Engineering, Chitkara University, Punjab, India., Kaur Amandeep ,   Computer Science and Engineering, Chitkara University/ Punjab, India.
Published: August 2019

Cloud networks are very widespread and unreliable because of the amount of VMs and presented nodes in their Virtual Cloud Network. Nodes might connect and revoke networks at any time. Resilience is a advantage of cloud computing, but it has many safety issues in routing and transmitting information between messages. VCN research is very similar to the portable ad-hoc network (MANET), which depends on the collaboration of all involved nodes to provide fundamental activities. Many safety assaults and risks exploit the safety of information transmission due to the decentralized environment in VCN and MANET. Malicious nodes can interfere and use information during wireless communications. Numbers of methods are there that has a diverse effect on such attacks for malicious nodes. Varied attacks are susceptible to security, but Black hole assault is one of the most common effective assaults, as fraudulent nodes dump all incoming emails reducing network performance and reliability. A black hole node is designed to lampoon every node in the network that conveys with some other node by saying it always has the easiest route to the target node. In this manuscript, a secure routing discovery method has been presented using Ad hoc on demand distance vector (AODV) routing protocol. For the detection of attack in the cloud, the concept of Artificial Intelligence (AI) has been used. Therefore, in this research, Artificial Neural Network (ANN) and Support Vector Machine (SVM)is adapted to determine Packet Delivery Ratio (PDR), Delay and Throughput measures. The comparative examination has been conducted to depict the proposed FNN-AODV effectiveness. There is an enhancement of 61.01% in FNN-AODV and 5.08% enhancement in Throughput in proposed FNN-AODV than R-AODV, 6.26% enhancement in PDR for FNN-AODV than R-AODV and 10.8% is the decrement in delay in FNN-AODV than of R-AODV.
The Feature based Image Stitching Techniques
Authors:   Department of IT, Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India, Kumar R Arun , Kumar K Sathesh ,   Department of IT, Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu India, Prasanth T ,   Department of CSE, Jain University, Bangalore, India, Balakrishnan K ,   Department of Information Science & Engineering, Sri Venkateswara College of Engineering, Bengaluru, India
Published: August 2019

The photographic images taken from different sources are integrated into one to form a new panoramic image which has high resolution when compared to the original image. Usually, image stitching can be done using any computer software. Image stitching helps us in extracting the actual information from shredded data. The torned paper can be reconstructed by means of image stitching process which is applied in forensic department. Digital maps and satellite photos can be reconstructed through image stitching algorithms which is also known as Image mosics. In recent days, many researchers introduced various algorithms to address the issues in Image stitching technique. Feature based Image stitching technique plays a vital role in most of these algorithms. In feature-based technique, local descriptor is used to compare an image’s feature points with another image’s feature points to predict the feature points for the given pair of image. In this paper different image stitching techniques, comparisons between various features descriptor and the steps involved in Feature extraction in Image stitching method are discussed.
Video based Face Recognition with limited resources
Authors:   Department of Computer Engineering, JSPM’s Rajarshi Shahu College of Engineering, Pune, (M.H.), India., Patil Yogini , Barkade V. M. ,   Department of Computer Engineering, JSPM’s Rajarshi Shahu College of Engineering, Pune, (M.H.), India.
Published: August 2019

Face recognition(FR) has multi-domain applications and video based FR is good area of research in terms of accuracy and performance. Recent research has proved that Convolutional Neural Network (CNN) is a one of best solution for object detection and recognition as it extracts features from on its own and performs classification as well. As we go for higher accuracy models, size of network increases and it requires more time to process a frame or video as it involves more computations. This paper aims at building a FR model which is smaller in network size, requires limited resources while building and still achieves good accuracy. The system uses combination of deep learning and machine learning based solution. FR system is built with CNN-Suport Vector Machine(SVM) model where CNN performs feature extraction and SVM performs classification task. Results shows that CNN-SVM model gives higher accuracy (94.05% validation and 90.17% testing) compared to conventional CNN-softmax model (93.37% validation and 88.77% testing) with a small network size and also requires less training time. Results can be improved by using cross validation techniques.
DevOps Intelligent Networking with Automated Deployment in Linux
Authors:   MTech Student, Dept of CS & E, Chh. Shahu College of Engineering, Aurangabad, India., Chavan Mr. Pushpendra M. , Abhang Prof. Sandeep P. ,   Professor & HoD, Dept of CS & E, Chh. Shahu College of Engineering, Aurangabad, India., Shinde Prof. U. B. ,   Principal, Chh. Shahu College of Engineering, Aurangabad, India.
Published: August 2019

DevOps shortly refers to the common intelligent practice of combining the Software Development and Operations to carry out certain set of tasks for automation of jobs. Methodologies in DevOps have become first choice for the system administrators to carry out operations [3]. Deployment of the Operating System, since a big task, can be carried out by many ways, like manual or an automated method [1]. Manual method is a time consuming and prone to errors whereas the automated method is much better in terms of management and repetition. This research paper covers the need of such Automated Deployment method including much needed tasks such as server and client side configurations, centralized monitoring, logging and software patch management. As as addition, the proposed network in itself is self healing at the Operating System level, without compromising security and removing corruption at libraries and binaries level. Use of this optimized method helps reducing administration effort and is prone to no errors. A Self healing service makes sure of no corruption for long term and centralized logging helps monitoring the network as well [5]. The Intelligent Networking for Automated Deployment is a DevOps reference project which can be useful for automation in the Organizations for heavy and uniform deployments along with additional monitoring configurations.
Effect of Alkaline Pre-Treatment on Cassava Pulp for Optimum Biogas Production
Authors:   Department of Physics, Mandalay University, Sagaing University, Mandalay, Myanmar., Hnin Aye Win Win Aye & Hnin , Aung Pyae Chatpet Yossapol & Htay ,   School of Environmental Engineering, Suranaree University of Technology, Nakhon Ratchasima, Thailand.
Published: August 2019

(Being produced in vast quantity as one of by-product from cassava starch processing chains, cassava pulp has great potential for energy recovery by harnessing biogas through anaerobic digestion (AD). This study aims to enhance biogas production by comparative investigation in batch mode digestion. 5%TS w/v of cassava pulp mixed with mill effluent were pre-treated with 10 molar potassium hydroxide (KOH), sodium hydroxide (NaOH), and calcium hydroxide (Ca(OH)2) solution for 6 hours contact time. Effects of different alkaline pre-treatment on cassava substrate were assessed in total dissolved solid (TDS), soluble chemical oxygen demand (SCOD), Volatile Fatty Acids to Alkalinity ratio (VFA/TA), and reducing sugars. Daily accumulated biogas yield was taken as final indicator of the effect of different pre-treatment. KOH pre-treatment in pH 11 resulted highest dissolved solid 13.07 mg/L, and improved soluble chemical oxygen demand (SCOD) formation up to 75.61% (480,000 mg/L) than control substrate. The experiment revealed peak biogas production by KOH pre-treated substrate was found at day 6 after digestion executed, and achieved 546 ml. The finding proves out of different pre-treatment method applicable to cassava pulp, KOH pre-treatment could realistically increase biogas yield for cassava mills. Biogas production increased up to 101%, 92%, and 70% using KOH, Ca(OH)2 and NaOH respectively. However, when future provision to the technology for AD system and design is concerned, the choice of highly reactive alkali could lead to complication in the system.
Massive MIMO: Achievable Energy Efficiency for 5G systems with Multi-user Environment
Authors:   ECE, ANU/ International School of technology and sciences (for owmen) / Rajamahendravaram, India., Rayi Prasad , Prasad M.V.S ,   ECE, ANU / Rayapati Venkata Rangarao & Jagarlamudi Chandramouli College of Engineering / Guntur , India.
Published: August 2019

Massive Multi-Input and Multi-Output (MIMO) antenna system potentially provides a promising solution to improve energy efficiency (EE) for 5G wireless systems. The aim of this paper is to enhance EE and its limiting factors are explored. The maximum EE of 48 Mbit/Joule was achieved with 15 user terminal (UT)s. This problem is related to the uplink spectral efficiency with upper bound for future wireless networks. The maximal EE is obtained by optimizing a number of base station (BS) antennas, pilot reuse factor, and BSs density. We presented a power consumption model by deriving Shannon capacity calculations with closed-form expressions. The simulation result highlights the EE maximization with optimizing variables of circuit power consumption, hardware impairments, and path-loss exponent. Small cells achieve high EE and saturate to a constant value with BSs density. The MRC scheme achieves maximum EE of 36 Mbit/Joule with 12 UTs. The simulation results show that peak EE is obtained by deploying massive BS antennas, where the interference and pilot contamination are mitigated by coherent processing. The simulation results were implemented by using MATLAB 2018b.
Steganographical Techniques in Hiding Text Images – System
Authors:   Research Scholar, Department of ECE, Bharath University, Chennai, India., Vinoth V. V. , Kanniga E. ,   Professor, Electronics and Communication Engineering Head Electronics & Instrumentation Engineering, Bharath University, Chennai, India.
Published: August 2019

In this era, internet has become a widespread entity all over the world. Sharing and communicating images, video contributes an essential role in this scientific era. In the meanwhile, secure transition of data has indeed become a major issue. Steganography is one of technology that contributes a vital role in protecting the secret data against an unauthorized access. In this type, secret data can be concealed into a cover file that includes audio, video, text and also image. In this paper, we propose different types of steganography methods for secure transfer of data in a confidential manner. The paper also explores stenographical techniques in terms of text, image and audio. The proposed work compares and discusses the stenographical methods in spatial domain, frequency domain derived under the image technique.
Maker Faire - Promoting Regional Innovation & Entrepreneurial Ecosystem by Empowering Students
Authors:   Dept. of Business Management, SR Engineering College Warangal, TELANGANA, Kumar Dr. N. Suman , Condoor Dr. Sridhar ,   Dept. of Aerospace & Mechanical Engineering Saint Louis University, USA, Shekar P V Dr. Raja ,   Center for Creative Cognition, SR Engineering College, Warangal, TELANGANA
Published: August 2019

To encourage entrepreneurship, schools and colleges are promoting activities and curricular innovations. Make 'n' Market is one such effort to engage and transform the mindset of the student community. It differs from other entrepreneurship events in its nature as it is not a competition or a workshop or a camp. It is not an idea or business plan generator. It is a celebration of peoples’ entrepreneurial skills requiring participants to conceive and market products thereby promoting making and marketing skills to bridge the gap between engineering and business disciplines. The paper describes the event, provides details of its implementation, documents the profile of participants and showcases the learning outcomes. The event has a transformative effect on the regional entrepreneurial eco-system in the long run.
Classifying Handwritten Digit Recognition using CNN and PSO
Authors:   Computer Engineering Department, JSPM's Rajarshi Shahu College of Engineering, Tathawade, Pune, India.., B. Barhate Ms. Priyanka , Upadhye Mr. G. D. ,   Computer Engineering Department, JSPM's Rajarshi Shahu College of Engineering, Tathawade, Pune, India..
Published: August 2019

A normal human can easily recognize any written or typed or scanned text, numbers, etc., but when it comes to a machine, it is difficult to find out what exactly that given text or numbers. It will be difficult to recognize a handwritten digit for a machine. Many machine learning methods were used to fix the handwritten digit recognition issue. It is growing in more convoluted domains, so its training complexity is also increasing. To overcome this complexity problem, many algorithms have been implemented. In this paper, the Convolutional Neural Network (CNN) and Particle Swarm Optimization (PSO), those two approaches do use for recognition of the isolated handwritten digit. Customized PSO is used to reduce the overall computation time of the proposed system. The customized PSO used with CNN, to decreases the required number of epochs for training. It is used to identify digits in the MNIST handwritten digital database to predict the number. The system has achieved an average of 94.90% accuracy.
Effect Lime and Recron Fibre on Geotechnical Properties of Black Cotton Soil
Authors:   Civil Engineering, MANIT Bhopal, India, Tomar Devesh Singh , Kaur Dr. Suneet ,   Associate Professor, MANIT Bhopal, India
Published: August 2019

Clayey soils are considered as the weakest subgrade soil from civil engineering point of view under moist condition. These soils attract and absorb water and loses their strength. Because of this reason certain inherent properties of these clayey soils need modification for their bulk use in construction of highways, embankments etc. Recently, many synthetic fibres have emerged to strengthen soft soils. Synthetic fibres are low-cost materials, hydrophobic and chemically inert in nature which does not allow the absorption or reaction with soil moisture. The inclusion of synthetic fibres provides reinforcement to the soil and use of lime as a soil stabilizer in BC soil cut down the plasticity index and also increase its strength. For this an extensive laboratory test program was conducted to analyse the variation geotechnical properties of soil by changing the percentage of recron fibre at an optimum dose of lime. The laboratory tests include Atterberg Limit Test, Modified Proctor Test, Unconfined Compressive Strength Test and California Bearing Ratio Test. To conduct different tests on soil sample the proportion of lime is kept fixed and proportion of polyester recron fibre is varied from 0% to 1% by dry weight of soil sample for different lengths of fibre(6 mm, 12 mm & 18 mm separately). Optimum dose of lime is find out by plasticity index of BC soil mixed with varying percentages of lime (4%, 6%, 8% and 10%). Results of the experiments shows that with the increase in the appropriate percentage in recron fibre the Unconfined Compressive Strength and California Bearing Ratio increases. On increasing the length of Recron Fibre, the Unconfined Compressive Strength and California Bearing Ratio also increases. Combination of lime and recron fibre in BC soil give higher CBR value. Therefore it can be used in the improvement of Clayey Soil Subgrade in pavement design and in the construction of embankements.
Existential and Archetypal Architectonics of Social (Societal) Order
Authors:   Siberian Federal University, Krasnoyarsk, Russia., Pavlov Alexander Pavlovich , Pavlov Pavel Aleksandrovich ,   Siberian Federal University, Krasnoyarsk, Russia., Lvov Denis Vladimirovich ,   Siberian Federal University, Krasnoyarsk, Russia., Novikov Alexey Sergeevich ,   Siberian Federal University, Krasnoyarsk, Russia., Sinkovskaya Irina Georgievna ,   Siberian Federal University, Krasnoyarsk, Russia., Rakhinsky Dmitry Vladimirovich ,   Krasnoyarsk State Agrarian University, Krasnoyarsk, Russia.
Published: August 2019

The article deals with the modern order (world order) in the context of modern social reality. This is due to the need to identify and diagnose the current socio-cultural situation in the world. It is suggested that modern social and socio-political orders, as well as world order patterns and mechanisms, are unable to reproduce the value identity of societies. This is partly due to the disruption of the "super doctrines", "pictures of the world", which for many centuries held social identity around a common substantive core, namely, national, religious, or political ideology. The article also discusses the role of individuals in the course of social reproduction, as well as presents general arguments about the increasing role of the human factor and the need for more efficient use of human capital.
Efficient Technique for word identification and recognition in Telugu Documents
Authors:   Department of Electronics and Communication Engineering, CMR Technical Campus, Hyderabad, Telangana, India, Lakshmi Kesana Mohana , Babu Tummala Ranga ,   Department of ECE, RVR&JC College of Engineering, Guntur, A.P, India
Published: August 2019

Telugu language is one of the most spoken Indian languages throughout the world. Since it has an old heritage, so Telugu literature and newspaper publications can be scanned to identify individual words. Identification of Telugu word images poses serious problems owing to its complex structure and larger set of individual characters. This paper aims to develop a novel methodology to achieve the same using SIFT (Scale Invariant Feature Transform) features of telugu words and classifying these features using BoVW (bag of visual words). The features are clustered to create a dictionary using k-means clustering. These words are used to create a visual codebook of the word images and the classification is achieved through SVM (Support Vector Machine).
Improvisation of Dense Matrix of Reactive Powder Concrete By Zircon Sand and Sillimanite
Authors:   Faculty of Civil Engineering Department, Francis Xavier Engineering College, Tirunelveli, Tamil Nadu, India, Renisha M. , Valli S.Asvitha ,   Faculty of Civil Engineering Department, Francis Xavier Engineering College, Tirunelveli, Tamil Nadu, India, Sakthieswaran Dr.N. ,   Faculty of Civil Engineering Department, Anna University Regional Campus – Tirunelveli, Tamilnadu, India
Published: August 2019

This paper presents a comparative study of compressive strength and ultrasonic-pulse velocity of Reactive Powder concrete (RPC) blended with micro and Nano filler materials. The material composition of RPC includes partial replacement of High Alumina Cement by alccofine and Quartz sand by zircon sand and sillimanite in order to obtain a dense concrete matrix of low level porosity. Micro-steel fibers were used to enhance the ductility of concrete composite. Polycarboxylate based super plasticizer was used to improve the workability. The experimental program comprises of compressive strength test and ultrasonic-pulse velocity test of standard water cured samples and heat treated samples at elevated temperatures of 200°C, 400°C, 600°C and 800°C. The influence of micro-filler materials in hydrated samples and microstructure of RPC specimens were examined by Scanning Electron Microscope (SEM) analysis. The results showed that the combined role of zircon sand and sillimanite as a filler material and high alumina cement as a refractory material made the RPC to exhibit ultra-high performance with increase in temperature and tends to decrease after 600°C.
Flood Frequency Analysis in Sabarmati River basin and Estimation of Peak Discharge under Climate Change Scenario
Authors:   Associate Professor, Civil Engineering Department, Faculty of Technology & Engineering, The Maharaja Sayajirao University of Baroda, Post Box No. 51. Vadodara, India, Joshi Geeta S. , Makhasana Payal ,   Civil Engineering Department, Faculty of Technology & Engineering, The Maharaja Sayajirao University of Baroda, Post Box No. 51. Vadodara, India;
Published: August 2019

Due to climate change, there is an increased/decreased frequency of peak flood discharge in river and streams. The most important concern of planning is to safe passing of the extreme flood discharge influenced by extreme climatic changes. It is a concern for planning for the storage capacity to safely store extreme discharge/inflow of the river. In this paper, probability theories and statistics for flood frequency factor (K) are applied and based on the results; it is found that the Extreme value model results in to a best model for frequency factor K, as it is yielding the minimum relative error. Using the frequency factor, the flood frequency analysis for peak flood is carried out for climate change scenario/Advance scenario. The peak discharge in advance scenario is more as compare to the base line scenario at most of the stations except three stations located on the south-east of the Sabarmati river basin.
Smart Clustering LEACH (SC-LEACH) Protocol for Improved Network Survivability in Wireless Sensor Networks
Authors:   Dept of E&CE, P E S College of Engineering Mandya, Karnataka, India., P Ullas. , Shivaprakasha K. S. ,   Dept of E&CE, N M A M Institute of Technology, Nitte, Karkala, Karnataka, India
Published: August 2019

Wireless Sensor Networks (WSN) are becoming increasingly popular by the virtue of its diversified applications. Nevertheless WSN faces various research challenges despite its ease of implementation. One of the major issues of concern is the energy efficiency which is closely related to the lifetime of the network. Low-Energy Adaptive Clustering Hierarchy (LEACH) is proven to be an efficient way to route packets in WSNs. However the performance of the LEACH can be further enhanced by lessening the frequency of cluster reformation. In this paper we propose a novel Smart Clustering LEACH (SC-LEACH) protocol which is an advancement over the traditional LEACH protocol. The results of the proposed algorithm were validated through simulations.
HUBUNGAN ANTARA TINGKAT KEPARAHAN PMS DENGAN TINGKAT KECEMASAN DAN KUALITAS TIDUR PADA REMAJA PUTRI
Authors: Susanti Henny Dwi , Ilmiasih Reni , Arvianti Ari
Published: August 2019

Abstract : Pre Menstrual Syndrome (PMS) is a collection of physical symptoms, psychological, and emotions associated with the woman's menstrual cycle and consistently occur during the luteal phase of the menstrual cycle due to hormonal changes associated with the current cycle of ovulation (release of eggs from the ovary) and menstruation. Some of the complaints were felt during PMS, such as headache, back pain, breast pain, sleep disorders, and more than a few complaints can cause anxiety in women with PMS. This research was conducted observational analytic with cross sectional method. levels of anxiety and sleep quality in adolescent girls (as dependent variable). The sample used in this research were 30 students. Total sampling is a sampling technique in which the number of samples is equal to the population. there is a significant correlation between the severity of PMS with the level of anxiety. A positive correlation coefficient indicates that the relationship between the severity of PMS with anxiety levels. The more severe or severe PMS level, the level of anxiety is also heavier. Conversely, the mild severity of PMS, the anxiety level is also lighter. There is a significant correlation between the severity of PMS with the quality of sleep.Keywords : severity PMS, level of anxiety, quality sleep, adult Abstrak : Pre Menstrual Syndrome (PMS) merupakan kumpulan gejala fisik, psikologis, dan emosi yang terkait dengan siklus menstruasi wanita dan secara konsisten terjadi selama tahap luteal dari siklus menstruasi akibat perubahan hormonal  yang berhubungan dengan siklus saat ovulasi (pelepasan sel telur dari ovarium) dan menstruasi. Beberapa keluhan yang dirasakan saat PMS yaitu sakit kepala, sakit punggung, nyeri pada payudara, gangguan tidur, dan lain-lain.Akibat dari beberapa keluhan yang dirasakantersebut dapat menimbulkan kecemasan pada wanita yang mengalami PMS. Penelitian ini dilakukan secara observasional analitik dengan metode pendekatan cross sectional. tingkat kecemasan dan kualitas tidur pada remaja putri (sebagai variabel dependen). Sampel yang digunakan dalam penelitian ini berjumlah 30 siswi. Total sampling adalah teknik pengambilan sampel dimana jumlah sampel sama dengan populasi. terdapat hubungan yang signifikan antara tingkat keparahan PMS dengan tingkat kecemasan. Koefisien korelasi yang positif menunjukkan bahwa hubungan antara tingkat keparahan PMS dengan tingkat kecemasan. Semakin parah atau berat tingkat PMS, maka tingkat kecemasan juga semakin berat. Sebaliknya, semakin ringan tingkat keparahan PMS, maka tingkat kecemasan juga semakin ringan. Terdapat hubungan yang signifikan antara tingkat keparahan PMS dengan kualitas tidur.Kata kunci : tingkat keparahan,PMS, tingkat kecemasan, kualitas tidur, remaja.
HUBUNGAN INTENSI DENGAN PERILAKU PERAWAT DALAM PENDOKUMENTASIAN ASUHAN KEPERAWATAN DI INSTALASI GAWAT DARURAT
Authors: Kurniawan Ardhiles Wahyu
Published: August 2019

Abstract : The complex IGD work environment will affect the quality of care, health care, including inaccurate or incomplete documentation. Incomplete nursing documentation indicates that the nursing care process is not working properly and continuously. Intentionin documenting can predict the appearance of person behavior including the behavior of nurses, especially in documenting nursing care. The purpose of this study was to analyze correlation intention with nurse behavior in documenting nursing care in Emergency Installation. The research design used correlational analysis with cross sectional approach. The sample in this research is part of nurse of executing at IGD Rumkit TK II dr Soepraoen, IGD RS Panti Waluya Sawahan and IGD RS Islam Malang. The sample of 45 nurses IGD and 341 documents were selected according to inclusion and exclusion criteria. The result of statistical analysis of gamma that there is a significant correlation between intention and nursing documentation behavior evidenced by value of p = 0,000, positive correlation direction and strong correlation value is proved by r = 0,739. Hospital and nurse IGD is expected to develop a good intention then formed good nursing documenting behavior as well.Keywords : Nurse IGD, Intention, Nursing Documentation. Abstrak: Lingkungan kerja IGD yang kompleks akan mempengaruhi kualitas perawatan, pelayanan kesehatan, termasuk dokumentasi yang dilakukan tidak tepat atau tidak lengkap. Dokumentasi keperawatan yang tidak lengkap menunjukkan proses asuhan keperawatan tidak berjalan dengan baik dan berkesinambungan. Intensi dalam pendokumentasian dapat memprediksi munculnya perilaku seseorang termasuk perilaku perawat khususnya dalam pendokumentasian asuhan keperawatan. Tujuan penelitian ini untuk menganalis hubungan intensi dengan perilaku perawat dalam pendokumentasian asuhan keperawatan di Instalasi Gawat Darurat. Desain penelitian menggunakan analysis correlationaldengan pendekatan cross sectional. Sampel dalam penelitian ini adalah sebagian perawat pelaksana di IGD Rumkit TK II dr Soepraoen, IGD RS Panti Waluya Sawahan Malang dan IGD RS Islam Malang. Sampel berjumlah 45 perawat IGD dan 341 dokumen dipilih sesuai dengan kriteria inklusi dan ekslusi. Hasil analisis statistik uji gammamenunjukkan terdapat hubungan signifikan antara intensi dengan perilaku pendokumentasian keperawatan dibuktikan dengan nilai p = 0,000, arah korelasi positif, dan nilai korelasi kuat dibuktikan dengan nilai r = 0,739. Rumah Sakit dan perawat IGD diharapkan mengembangkan intensi yang baik sehingga diharapkan terbentuk perilaku pendokumentasian keperawatan yang baik pula. Kata Kunci : Perawat IGD, Intensi, Dokumentasi Keperawatan.
PERBEDAAN TINGKAT STRES MAHASISWA PRAKTIK KLINIK PADA TINGKAT II DAN III PROGRAM STUDI D-III KEPERAWATAN STIKES KEPANJEN
Authors: Fanani Qori
Published: August 2019

Abstract : Nursing students often experience stress or stress in undergoing clinical practice. There are several factors that cause students to experience stress, including lack of knowledge and skills, workloads and assignments, and the clinical environment itself. The purpose of this study was to determine the differences in stress levels of clinical practice students at level II and level III of Nursing Diploma III Program at STIKes Kepanjen. This type of research is descriptive quantitative with a causal comparative approach with a total of 60 respondents. Data analysis using Mann – Whitney so that the results show that there are significant differences in the level of stress level II and level III students in conducting clinical studies. While for the stressors of students who are undergoing clinical practice are lack of knowledge and skills, workload and assignments, hospital environment and when caring for patients. So that to achieve the goal of clinical learning is to prepare students both knowledge, skills and maturity in dealing with pressure when carrying out clinical learning.Keywords : Clinical practice, Nursing Student