bluuebunny/crossref_metadata_2025 huggingface dataset:
Dehazing of Images using Minimum White Balance Optimization
Authors:   Department of Electronics Engineering, Government College of Engineering Amravati, Amravati, Maharashtra., Mujbaile* Deoyani , Rojatkar Dinesh ,   Department of Electronics Engineering, Government College of Engineering Amravati, Amravati, Maharashtra.
Published: June 2020

The quality of image captured in presence of fog and haze is degraded due to atmospheric scattering. In order to restore such images, several dehazing algorithms have been proposed. These algorithms sometimes, results in either a contrast distorted dehazed image or a dehazed image that has influence of dense haze. In order to solve this problem, dynamic facsimile dehaze system built on minimum white balance optimization is proposed. This paper proposed a system that integrates some famous single image dehazing algorithms and enhance their outputs using histograms and adaptive histograms; then adaptively select the output with minimum white balance distortion in order to get the optimum output. Experimental results demonstrated that the presented system can attain better dehazing effect and further improves universality of dehazing methods. Also proposed system improves luminance and contrast of dehazed images to a certain extent.
Prognosis of Cancer and Proposition of Therapeutics
Authors:   Assistant Professor, Department of Computer Science & Engineering, Rajalakshmi Engineering College, Chennai, India., Bhavani* Ms. M. , Glory Ms. Sherine ,   Assistant Professor, Department of Computer Science & Engineering, Rajalakshmi Engineering College, Chennai, India., Ms. Pavithra  ,   Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai, India., Monesh Mr. R. ,   Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai, India.
Published: June 2020

Cancer is becoming one of the common diseases in day today life, identifying it in a prior stage is still difficult. Identification of environmental and genetic factors is necessary to predict the cancer. We developed a cancer prediction system to predict lung and oral cancer based on the symptoms. The gathered data is pre-processed and the data mining algorithm such as decision tree, logistic regression, Random Forest and Support Vector machines are used to measure the performance. The attribute selection algorithms are used to obtain the mandatory attributes. The main aim of this system is to predict the type of cancer and the suggested therapy using random forest algorithm.
Sdn in Edge Computing Based on Penguin Foraging Behaviour
Authors:   Assistant professor, Koneru Lakshmaiah Educational Foundation, Guntur, India., Pydi* HariKrishna , Reddy Allu Venkata Dattatreya ,   Student, Koneru Lakshmaiah Educational Foundation, Guntur, India., Rupesh Chowdavarapu Jeevan ,   Student, Koneru Lakshmaiah Educational Foundation, Guntur, India, Chandana Pothugunta ,   Student, Koneru Lakshmaiah Educational Foundation, Guntur, India, Bharath Chittamuru ,   Student, Koneru Lakshmaiah Educational Foundation, Guntur, India
Published: June 2020

Over the years usage of computational devices have been increased rapidly. 3G and 4G network evolution has helped in seamless usage of the modern devices. As the users are increasing rapidly and 4G spectrum is been congested way too fast. These situations resulted in development of 5G Spectrum by unlocking the millimetre waves. Milli meter Waves are originally shortrange waves and cannot be passed through heavy objects for these solution Small Base station concept has been implemented which provides high coverage and less latency while using. A small cell is basically a miniature base station that breaks up a cell site into much smaller pieces, and is a term that encompasses pico cells, micro cells, femto cells and can comprise of indoor/outdoor systems. For this implementation the SDN plays an important role for maintaining the connection between Base stations. Penguin foraging behaviour can be taken as a reference for the search algorithm in edge computing for getting faster results. Usually a penguin population comprises of several groups. Each group contains a number of penguins that varies depending on food availability in the corresponding foraging region. They feed as a team and follow their local guide which has fed on most food in the last dive. Similarly we follow the same process in small cell base station. Edge computing supports all devices simultaneous for processing and getting accurate results. They can be used for platform development for storage centric, server centric or even hybrid(storage-server) workloads. Related words: Edge computing, Software Defined Network, foraging behaviour, small cell base stations, Milli meter waves
Handoff Control in Satellite Communication Applying Multi Billboard Manager Method
Authors:   Assistant Professor, Department of Computer Science, Vidyasagar University, Midnapore, India, Sen* Priyajit , Das Monish Mukul ,   Department of Computer Science and Engineering, University of Kalyani, Kalyani, India,, Sarddar Debabrata ,   Assistant Professor, Department of Computer Science and Engineering, University of Kalyani, Kalyani, India, Pandit Rajat ,   Assistant Professor, Department of Computer Science, West Bengal State University, Barasat, Kolkata, India,
Published: June 2020

LEO satellites play an important role in global communication system. LEO satellites have some advantages over GEO and MEO satellites, in respect of power requirement, end-to-end delay & more efficient frequency spectrum. But the main problem of LEO satellite, is that they have large relative speed than the speed of mobile nodes (MN) and earth, so that the handover occurrence is more. As a result, the call blocking probability (Pb) and force call termination probability (Pf) is higher. To overcome this problem, Billboard manager based handover (BMBHO) was introduced to reduce the scanning time significantly and also to reduce the Pf. But the main problem of single billboard manager (BM) is that, since all handover requests have to be processed from a single point. In this paper, we have proposed the concept of multi-billboard manager based handover (MBMHO) method to resolve this problem. Thus, handover request will be served more efficiently so that both Pb and Pf are minimized than the BMBHO method.
Use of Machine Learning Models in Sales Forecasts
Authors:   Information Technology, Galgotias College of Engineering and Technology, Greater Noida, India., Jumnani* Shefali , Agrawal Shraddha ,   Information Technology, Galgotias College of Engineering and Technology, Greater Noida, India., Verma Samiksha ,   Information Technology, Galgotias College of Engineering and Technology, Greater Noida, India., Singhal Swasti ,   Information Technology, Galgotias College of Engineering and Technology, Greater Noida, India.
Published: June 2020

In this paper, we present a brief survey of usage of various machine learning models and their role in retail sales forecasts. The purpose of this paper is to enlist a few popular approaches in retail sales and study their scope and areas of application. We analyze how these models have evolved over time stating the significance of each model in brief.
Strength Enhancement on Mechanical Properties of Geopolymer Concrete with Magnetized Water and Recycled Coarse Aggregate
Authors:   Post Graduate, Department of Civil Engineering, Sri Krishna College of Technology, Coimbatore, India., R* Janarthanan , Vidya V* Dr.Sree ,   Associate Professor, Department of Civil Engineering, Sri Krishna College of Technology, Coimbatore, India.
Published: June 2020

Cement is probably the mostly widely used construction material in the world. However, the production of cement releases CO2 into the air. Greenhouse effect is mainly caused by carbon- di-oxide. Hence, there is a need to develop sustainable alternatives to Portland cement. One of the suitable alternatives is usage of Geo-Polymer Concrete (GPC) which is made from utilization of waste materials like fly ash and ground granulated blast furnace slag (GGBS) with suitable alkali activators. In general, chemical admixtures are added to get concrete with increased strength. The chemical admixtures for increasing the strength are not easily accessible in rural areas. The fresh and hardened properties of concrete are improved by using magnetic water. The scaling and corrosion are greatly reduced using magnetic water. It is due to the change in microstructure of water molecules making it soft water. Further, recycled coarse aggregate was used with coarse aggregate in the study. The specimens were cast and were investigated for Compressive strength, Split Tensile strength and Flexural strength test after 7 days and 28 days of ambient curing. It was observed that Compressive, Split Tensile and Flexural strength of the GPC specimen with magnetic water increased compared to other mix proportions.
Analysis on fog Network for Small Cell Network using Neuro Fuzzy
Authors:   Computer Science Engineering, SRM Institute of Science and Technology, Chennai, India, Kannan* Dr. N , Lishanth SK ,   Computer Science Engineering, SRM Institute of Science and Technology, Chennai, India, Hussain S Sajid ,   Computer Science Engineering, SRM Institute of Science and Technology, Chennai, India, Gauda Ashutosh ,   Computer Science Engineering, SRM Institute of Science and Technology, Chennai, India
Published: June 2020

In this manuscript we are establishing a new, remote backhaul system for small cell systems based on a powerful joint effort of Main Stations (MSs) that we call Fog-Radio Access Network (F-RAN) backhaul technology. By using fog, our proposed technique gives MSs the possibility to organize and methodology the signs obtained in various ways that can effectively extend the transmission limit of the backhaul network. We first model an F-RAN initiated and three backhauling procedures, explicitly Direct, DF, and Cloud-RAN (C-RAN), to be enforced. At this point we evaluate and think about the achievement of these methodologies. Numerical findings show that our proposed technique provides cell borders with the highest throughput to customers in most different territories and retains a comparable display. F-RAN thus performs better for minimized small cell systems with low backhaul channels than any other strategy.
Explanation Generation Mechanism for Black Box Recommendation Model
Authors:   Assistant Professor, Department of Computer Engineering, PCCOE&R., Koparde* Shweta , Bhondve Anuja ,   Assistant Professor Department of Computer Engineering, PCCOE&R., Latke Vaishali ,   Assistant Professor, Department of Computer Engineering, PCCOE&R.
Published: June 2020

The recommender system is everywhere, and even streaming platform they have been looking for a maze of user available information handling products and services. Unfortunately, these black box systems do not have sufficient transparency, as they provide littlie description about the their prediction. In contrast, the white box system by its nature can produce a brief description. However, their predictions are less accurate than complex black box models. Recent research has shown that explanations are an important component in bringing powerful big data predictions and machine learning techniques to a mass audience without compromising trust.This paper proposes a new approach using semantic web technology to generate an explanation for the output of a black box recommender system. The developed model is trained to make predictions accompanied by explanations that are automatically extracted from the semantic network.
Low Cost Handheld 3D Scanning for Egyptian Architectural Artifacts Acquisition
Authors:   Researcher, Ground Surveying Section, Aerial Photography & Aviation Dep., National Authority for Remote Sensing & Space Sciences (NARSS), Cairo, Egypt., Azeez* Ateaya B. , Shrawai Ashraf M. A. ,   Researcher, Aerial Photography Section, Aerial Photography & Aviation Dep., National Authority for Remote Sensing & Space Sciences (NARSS), Cairo, Egypt.
Published: June 2020

Surface reconstruction of objects using photogrammetry and terrestrial laser scanning systems (TLS) has been a topic for research for many decades, especially for culture heritage data recording. Recently, many advances into these systems are now available in the market, which give the availability of collecting a huge number of geo-referenced 3-D points covering any object surface. Due to speed and efficiency of data acquisition by means of terrestrial laser scanners, researchers and designers can select the reliable technique, depending on their application, that can be complete to give good results for the complex surfaces such as heritage objects. As Grand Egyptian Museum (GEM), located nearby the Giza Pyramids, is set to open by 2020, which considered as the largest museum from its type all over the world, with a huge area covered about a half million m2. GEM is proposed to be a unique museum all over the world for presenting a huge number from old history Egyptian artifacts. Consequently, there is a vital need for building a huge digital database containing complete information for this large number of artifacts. Mobile applications are presently at the primacy of documenting historical and archaeological sites. The current paper examine the methodological framework adopted for one high copy of Pharaonic artifacts, namely Offering Carrier, using hand held laser scanning and convert the results to a mobile application.
FPGA Implementation in Robust FFT Architecture for Signal Processing Applications
Authors:   Assistant Professor, (Research Scholar of ANNA University, Chennai), Department of Electronics and Communication Engineering, Sri Ramakrishna Institute of Technology, Coimbatore, India, Malathi* L. , Bharathi Dr. A. ,   Professor & Head, Department of Information Technology, Bannari Amman Institute of Technology, Erode, India,, Jayanthi Dr.A.N. ,   Associate Professor, Department of Electronics and Communication Engineering, Sri Ramakrishna Institute of Technology, Coimbatore, India,
Published: June 2020

FFT architecture is the common and very efficient design in modern signal processing applications. Though so much of architectures are executed in now-a-days applications, This paper will give different approach of FFT design. In order to reduce the computation time, FFT structure is modified in the arrangement. This analyzed approach somewhat satisfies the low power, high performance and to useful in image, signal and wireless applications.
Diagnosis of Autism using Machine Learning as a Healthcare Technology
Authors:   Computer Science, Birla Institute of Technology & Science Pilani, Hyderabad, India., Ray* Camellia
Published: June 2020

Autism is one of the inborn disease, researchers are presently focusing on. The autistic child faces inflexibility in language, thinking and behavior together with the difficulties in understanding emotional states of others. There are lot of interventions going on to make them understand the feelings of others and vice-versa. Now a day, ASD became one of the quick spreading diseases all over the world. Therefore there is a huge need to provide a time-consuming and easy accessible diagnostic tool to detect autism at an early stage to help the clinicians in providing prior medications. Though there is no proper curability of autism, still easy detection helps to provide better therapy session and supports the autistic child to lead a comfort independent life. The thesis deals with the building up of a model where the parents and relatives of a suspected autistic child can easily detect if they are suffering from autism by providing their answers of some particular questions related to the characteristics of autism. In order to build that model, the data were collected manually from different autism therapy centers in India and those raw data are then classified by using three different classifiers namely Logistic Regression, Support Vector Machine and Random Forest with Python as a programming tool to find out the one with higher accuracy by various analyses after pre-processing. The Random Forest classifier with the highest accuracy is utilized in framing the question based model for the early discovery of autism which can be operated as a primary diagnostic model to assist medical professionals technologically.
An Improved Dragonfly Optimization Algorithm based Feature Selection in High Dimensional Gene Expression Analysis for Lung Cancer Recognition
Authors:   Research Scholar, Department of Computer science, Chikkanna Government Arts College-Tirupur, India., vinmalar* F. Leena , Kombaiya Dr. A. Kumar ,   Assistant Professor, Department of Computer Science Chikkanna Government Arts College-Tirupur, India.
Published: June 2020

A microarray gene expression data is an efficient dataset for analyzing expression of thousands of genes and related disease. The more accurate analysis can be obtained by comparing Gene expression of disease tissues with normal tissues which helps to recognize the type of cancer. The processing of microarray datasets such as feature selection, sampling and classification is highly challenged due to its high dimensionality. Many recent researchers used various feature selection techniques for dimensionality reduction. Dragonfly optimization Algorithm (DA) was a feature selection technique used to reduce the dimensionality of lung cancer gene expression dataset. The dragonflies in DA are flying randomly based on the model developed by using the Levy Flight Mechanism (LFM). Because of huge searching steps, LFM has some drawbacks like interruption of arbitrary flights and overflowing of the search area. In fact, DA lacks an internal resemblance that record past potential solutions that can lead to its premature convergence into local optima. So, in this paper an Improved Dragonfly optimization Algorithm (IDA) is introduced which effectively reduces the dimensionality of the lung cancer gene expression dataset. In IDA, Brownian motion method is used to solve the issues of LFM and pbest and gbest idea of Particle Swarm Optimization (PSO) is used to direct the search method for finding potential candidate solutions to further refine the search space for avoiding premature convergence. The wrapper feature selection approach is followed by IDA to select optimal subset of features. The Random Sub space (RS), Artificial Neural Network (ANN) and Sequential Minimal Optimization (SMO) classifiers are utilized for feature selection of IDA and recognize Lung cancer subtypes. The accuracy of the classifier for selected features of Dragon flies in training instances is used as fitness value of Dragon flies in each iteration. Finally, the experimental results prove the effectiveness of the IDA in terms of accuracy, precision, recall and F-measure.
Truth Discovery in Big Data Social Media Sensing Applications
Authors:   Computer Science Engineering Student, Chaitanya Bharathi Institute of Technology, Hyderabad, India., Ahmed* Omar , Gupta Dr Sangeeta ,   Associate Professor in Computer Science Engineering Department, Chaitanya Bharathi Institute of Technology, Hyderabad, India., Hasibuddin Mohammed ,   Computer Science Engineering Student, Chaitanya Bharathi Institute of Technology, Hyderabad, India.
Published: June 2020

The detection of truthful information amid data provided by online social media platforms (e.g., Twitter, Facebook, Instagram) is a critical task in the trend of big data. Truth Discovery is nothing but the extraction of true information or facts from unwanted and raw data, which has become a difficult task nowadays in today's day and age due to the rampant spread of rumors and false information. Before posting anything on the social media platform, people do not consider fact-checking and the source authenticity and frantically spread them by re-posting them which has made the detection of truthful claims more difficult than ever. So, this problem needs to be addressed soon since the impact of false information and misunderstanding can be very powerful and misleading. This mission, truth discovery, is targeted at establishing the authenticity of the sources and therefore the truthfulness of the statements that they create without knowing whether it is true or not. We propose a Big Data Truth Discovery Scheme (BDTD) to overcome the major problems. We have three major problems, the main one being "False information spread" where a large number of sources lead to false or fake statements, making it difficult to distinguish true statements, now this problem is solved by our scheme by studying the various behaviors of sources. On Twitter for example rumormongering is common. The second problem is "lack of claims" where most outlets contribute only a tiny small number of claims, giving very few pieces of evidence and making it not sufficient to analyze the trustworthiness of such sources, this problem is addressed by our scheme where it uses an algorithm that evaluates the claim’s truthfulness and historic contributions of the source regarding the claim. Thirdly the scalability challenge, due to the clustered design of their existing truth discovery algorithms, many existing approaches don't apply to Big-scale social media sensing cases so this challenge is managed by our scheme by making use of frameworks HTCondor and Work Queue. This scheme computes both the reliability of the sources and, ultimately, the legitimacy of statements using a novel approach. A distributed structure is also developed for the implementation of the proposed scheme by making use of the Work Queue (platform) in the HTCondor method (maybe distributed). Findings of the test on a real-world dataset indicate that the BDTD system greatly outperforms the existing methods of Discovery of Truth both in terms of performance and efficiency.
Speech Signal Analysis and Classification of Dominant Parameter for Pathological Voices
Authors:   School of Electronics Engineering, VIT University, Vellore, India., Subiksha W Christina , A Nandhini ,   School of Electronics Engineering, VIT University, Vellore, India., K P Bharath ,   School of Electronics Engineering, VIT University, Vellore, India., Sohail Mahalti Mohammed ,   School of Electronics Engineering, VIT University, Vellore, India., Kumar M* Rajesh ,   School of Electronics Engineering, VIT University, Vellore, India.
Published: June 2020

The primary objective of the project is to analyze speech signals by determining the important parameters that affect the voice of an individual which leads to various voice disorders. The analysis is carried out based on the individual’s age and gender with the help of the pattern recognized from each sample and the value of each parameter is compared with the nominal values of the healthy person with respect to their age and gender using the Praat software. The secondary objective is the classification of the voice signal into normal and abnormal voice samples using the machine learning software Konstanz Information Miner (KNIME).
Advantages of Spectrally Efficient Frequency Division Multiplexing Over Orthogonal Frequency Division Multiplexing
Authors:   Electronics and communication engineering, Vellore Institute of Technology, Vellore, India., Mahesh* A Goutham Sai , Nivash S ,   Electronics and communication Engineering, Vellore Institute of Technology, Vellore, India., Revathi S ,   Ph.D. in Optical Communication, Vellore Institute of Technology, Vellore, India.
Published: June 2020

An analysis on Spectrally Efficient Frequency Division Multiplexing (SEFDM) is contrast with Orthogonal Frequency Division Multiplexing (OFDM) considering the impact on Peak to Average Power Ratio (PAPR) and nonlinearities within fibre. With respect to OFDM the sub-carriers in SEFDM signals are compressed adjacent to each other at a rate of frequency lesser than the symbol rate. At the receiver end we have utilized the Sphere Decoder which is used to recover the data to remunerate the Interference created by the compressed signals (ICI) faced in the system. This research shows the advantages by using SEFDM and evaluates its achievement. PAPR. when compared with OFDM, while effects of non-linear fibres are considered. The use of various formats of modulation going from 4-QAM to 32-QAM, shows that the SEFDM signals have a noteworthy increment in the transmission length with respect to ordinary signals.
Civil Liability to Nanotechnology Products: An Appraisal with Special Reference to Strict Liability
Authors:   West Bengal National University of Juridical Sciences, Kolkata, India, Chakrabarti Prof. Dr.Nirmal Kanti , Mitra* Dr.Arpita ,   School of Law, Kalinga Institute of Industrial Technology, Bhubaneswar, India
Published: June 2020

The present advantage of progress in terms of materials and their application is very much discernible in nanotechnology products. By using nanotechnology products there can be instances in which people will suffer harm and sometime death too. Some of these harm may be accidental and manufacturers may have no clue of it. However, in some cases it may happen that the producer or manufacturer knowingly release the products for economic benefits and undertook associated risks.In theoretical perspective strict liability focus more on the no fault theory rather than conduct or behavior of the manufacturers or the learned intermediaries. Thus, a manufacturer of nanotechnology product will be liable for distributing defective products directly to consumers or through retailers or distributors. At the same time the plaintiff must prove that the defect in question was the actual and proximate cause of injury and it incurred damages. In this paper an attempt has been made to examine critically the risks and civil liability, especially strict liability under Tort law of nanotechnology products.
Mathematical Modeling of the Processes Formations of Stocks in Low Water Period (on the example of the Kitab-Shahrisabz aquifer)
Authors:   Department of Computer Systems, Tashkent University of Information Technologies named after Muhammad al-Khworezmi, Tashkent, Uzbekistan., Djumanov* Jamoljon Х. , Zaynidinov Нakimjon N. ,   Department of Information Technology, Tashkent University of Information Technologies named after Muhammad al-Khworezmi, Tashkent, Uzbekistan., Elmurodovich Eshmurodov Dilshod ,   Associate Professor of the Department of Computer Systems of the Tashkent University of Information Technologies named after Muhammad al-Khworezmi., Egamberdiev Хojiakbar S. ,   Department of Computer Systems, Tashkent University of Information Technologies named after Muhammad al-Khworezmi, Tashkent, Uzbekistan.
Published: June 2020

In this study, we consider mathematical modeling of the dynamic state of groundwater aquifers, i.e., the process of groundwater formation in dry years under intensive (forced) groundwater intake withdrawal, i.e. operational selection exceeds the value of groundwater resources and depletion of capacitive reserves occurs) on the example of the Kitabo-Shakhrisabz groundwater deposits, of the Kashkadarya area of the Republic of Uzbekistan, which has a long period of regime observations and comparatively correct information on the groundwater level regime, groundwater intake withdrawal and interconnections within surface runoff. The data of hydrogeological area obtained as a result of analysis and schematization of hydrogeological conditions are generalized, and the hydrogeological parameters of the aquifer are calculated. The hydrogeological factors of groundwater formation are given and evaluated taking into account changes in water intake conditions, their current state is highlighted, and recommendations are given for substantiating the tasks of groundwater automations of monitoring in these territories..
Failure Probability and Reliability of Hatch Cover of Bulk Carrier Subjected To Lateral Pressure Load
Authors:   Department of Maritime Engineering, Amirkabir University of Technology, Hafez Ave, Tehran, Iran, Mohammadrahimi* Abdolhossein , Sayebani Mesbah ,   Department of Maritime Engineering, Amirkabir University of Technology, Hafez Ave, Tehran, Iran.
Published: June 2020

One of the situations that may cause severe damage and even sinking of bulk bulkheads is the destruction of the hatch cover and as a consequence of the ship's waterlogging. This destruction may be due to heavy loads on the page, such as shock wave loads. Considering this, it is very important to investigate the possibility of structural failure in this situation. In this paper, using a MATLAB programming language developed for the FORM method, we have tried to summarize the reliability analysis on two models of bulk carrier storage models. To achieve this, first, the algorithm of the method of expression, and then the limit state function of this failure state and its components are described, then the probability of failure of these two models of the storage compartment is calculated.
Product Quantization using Regression
Authors:   Department of Computer Science and Engineering, VR Siddhartha Engineering College, Vijayawada, Kanuru., Vadlamudi* Vasanthi , Ravi Divya Sree ,   Department of Computer Science and Engineering, VR Siddhartha Engineering College, Vijayawada, Kanuru., Dhulipalla Rishita ,   Department of Computer Science and Engineering, VR Siddhartha Engineering College, Vijayawada, Kanuru., Danduboyina Rohith Vamsi ,   Department of Computer Science and Engineering, VR Siddhartha Engineering College, Vijayawada, Kanuru., Lakshmi K.S.Vijaya ,   Assistant professor at the Department of Computer Science and Engineering, VR Siddhartha Engineering College, Vijayawada, Kanuru.
Published: June 2020

Approximate Nearest Neighbor (ANN) has developed an immense demand for many tasks. This ANN methodology was being used for product quantization. These product quantization methods were being used for e-commerce sites. However, this quantization maybe sometimes misleading due to a lack of accuracy in technique. So, we managed to increase the accuracy of quantization by adding Logistic Regression in the process. This helps to increase the accuracy of the method by having a probability value. This helps to make correlated items much more accurate when compared to pure quantization. This method is helpful for e-commerce sites for efficiency in the prediction of purchase by the customer.
Analog based Neuromorphic Systems on Low Power Current Mode Circuits
Authors:   Department of Electronics Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India., Parthasarathy* M. , R Dr. Sakthivel ,   Associate Professor, Department of Electronics Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
Published: June 2020

Neuromorphic computing is the process used to appliance the neural system models. Formerly, it is referred to as the biological process and later it turned out to be the computing algorithms. Many neuromorphic algorithms represented as the neural figures such as neural spikes, fluctuated graphs, and synapses. The biological nervous system for instance consists of huge number of neurons and they collectively work to encode the stimulus of various senses. In case of neuromorphic computing, automated brain brings in the concept of efficient work carried out through artificial means. The neuromorphic computing thus evolves as a major technological advancement and the need of such technique is the need of the hour in various scientific as well as field applications. In existing techniques, the scaling, power and area are not efficient. This study attempts to address the major issues such as scaling and power. This paper explains the design on a non-spiking network which is used for population coding architecture. The model which is discussed in this paper is based on the analog domain and the current mode circuits are also involved. The input neuron model consists of current direction selector block, current scale block and minimum current block which all comprise to form the neuron model. This paper also brings out the possible outcome of low power constraints. This paper involves 180nm technology with which the power is measured. This paper brings out the simulations of both 180 and 90nm technologies. Apart from current scale block, minimum current block and current direction selector block, there are other blocks such as current splitter block and current mode low pass filter block, where all the circuits work under the sub-threshold condition. The power consumption obtained in the 180 nm technology is 58.838 μW and its energy equivalent is 1.765pJ. Neuromorphic computing is used as an application where the machines are being automated and such machines come with self-thinking capability. Neuromorphic computing design which is evolved from this paper is found to be more power ad energy efficient. The tool used is Cadence Virtuoso.
Phase Recognition of Lung Cancer via Steerable Riesz Wavelets with Rf Algorithm
Authors:   School of Electronics Engineering, Vellore institute of technology, Vellore, India., Nishanth S. N. V. , Suryadev S. ,   School of Electronics Engineering, Vellore institute of technology, Vellore, India., Reddy Ch.Charan Teja ,   School of Electronics Engineering, Vellore institute of technology, Vellore, India., Kalaivani* S. ,   School of Electronics Engineering, Vellore institute of technology, Vellore, India.
Published: June 2020

Lung cancer is one of the diseases which has a high mortality. If the condition is detected earlier, then it is easier to reduce the mortality rate. This lung cancer has caused more deaths in the world than any other cancer. The main objective is to predict lung cancer using a machine learning algorithm. Several computer-aided systems have been designed to reduce the mortality rate due to lung cancer. Machine learning is a promising tool to predict lung cancer in its early phase or stage, where the features of images are trained using a classification model. Generally, machine learning is used to have a good prediction, but in some models, due to lack of efficient feature extraction value, the training has not been done more effectively; hence the predictions are poor. In order to overcome this limitation, the proposed covariant texture model utilizing the steerable Riesz wavelets feature extraction technique to increase the effectiveness of training via the Random Forest algorithm. In this proposed model, the RF algorithm is employed to predict whether the nodule in the image is benign or malignant ii) to find the level of severity (1 to 5), if it is a malignant nodule. Our experiment result can be used as a tool to support the diagnosis and to analyze at an earlier stage of cancer to cure it.
IoT Based Electrolyte level Monitoring System
Authors:   Student, Department of Computer Engineering MIT Academy of Engineering, Pune, India., Khandagale* Vinay , Agarwal Iti ,   Student, Department of Computer Engineering MIT Academy of Engineering, Pune, India., Ujalambkar Aditya ,   Student, Department of Computer Engineering MIT Academy of Engineering, Pune, India., Sanjay Mr. Ghodake ,   Assistant Professor, Department of Computer Engineering, School of Computer Engineering and Technology.
Published: June 2020

In hospitals, Electrolyte is fed to patients in many ways. One of the important functions is in the form of saline to treat dehydration and thus improve their health. In current health care measures, whenever a saline is fed to any patient, the patient needs to be continuously monitored by a nurse or any caretaker. Monitoring the Saline level in a bottle attached to a patients’ body is one of the most important tasks for a Nurse/caretaker. In cases involving ignorance or carelessness, the bottle may get empty and blood can start flowing reverse into the bottle from patients’ body. This is a risky situation and needs a better solution. We are developing an IoT based bottle level monitoring system that will detect the saline bottle level at all instances and will send an alert to the hospital's control room in case the bottle reaches it's critical level(30% of initial level) and if there is no response and the level goes beyond 20% on initial level, we stop the flow. We are using ESP8266 Wi-Fi module for processing and communication and load sensor for detecting the bottle weight. The proposed system is not electrolyte specific and can monitor any fluid. A Dc Motor controlled- screw actuated clamp mechanism is used for stopping the flow.
A Novel Impurity Measuring Technique for Decision Tree Learning in Machine Learning
Authors:   Department of Computer Science, Dravidian University, Kuppam, India., Mabuni* D.
Published: June 2020

Decision tree classification is one of the most powerful data classification techniques in machine learning, data mining, big data analytics and split functionality is a crucial and inherently associated integral part of the decision tree learning. Many split similarity measures are proposed to determine the best split attribute and then partitioning the node data in decision tree learning accordingly. A new impurity measuring based split technique called (IMDT) for decision tree learning is proposed in this paper and it is used in obtaining experimental results. Many UCI machine learning dataset are employed in experimentation. The algorithm C4.5 is the most using data classification algorithm. The results obtained with the proposed approach are outperformed than the many existing decision tree classification algorithms in particular C4.5 decision tree algorithm.
Influence of fly ash, lime Sludge and Polypropylene fibre on Compaction and Strength Properties of Subgrade
Authors:   Student, Department of Civil Engineering, Chandigarh University, Punjab, India., tasaduq* Ayani , Malik Mohd. Irshad ,   Assistant Professor, Department of Civil Engineering, Chandigarh University, Punjab, India., Tangri Amanpreet ,   Assistant Professor, Department of Civil Engineering, Chandigarh University, Punjab, India.
Published: June 2020

The development of population, quick urbanization and more development of structures and buildings has brought about the decrease of good quality land. To improve the accessibility of good quality land, strength and compaction properties of land should be improved. The fundamental goal of this examination is to explore the utilization of fly ash, lime sludge and polypropylene fiber in Geotech highway application and to assess their impact on quality and compaction of soil, utilized for subgrade. The soil samples were gathered from the zones of Chandigarh where clayey soil is present in abundance. The laboratory testing led to decide the strength and compactive effort of the clay soil. This investigation includes three principle tests. The primary test is standard proctor test. The subsequent test is California bearing ratio and the third test is the direct shear test. Proctor test gives the compactive effort of the soil and CBR gives the subgrade strength. The outcomes acquired are thought about for the examples and inferences are drawn towards the unstability and effectiveness of admixture support at different percentages, as replacement for high quality subgrade and cost-effective approach.
New Fusion Techniques to Extract Image Features and Recognition of Palm Vascular Pattern
Authors:   Electronics and Communication Engineering, Cauvery institute of Technology, Viswesharaya Technological University , Belagavi, Karnataka, India., A P* Savitha , Dr. Ramegwoda  ,   Viswesharaya Technological University, Belagavi, Karnataka, India.
Published: June 2020

A strong and efficient Feature extraction algorithm is highly recommended for individual recognition in human authentication systems. This paper presents the work carried on palm vein image to extract features of the person vein for recognition and classification using improved canny edge detector. This paper describes a novel method to extract valuable features of the people’s vein pattern and achieving high recognition rate. The experiments carried using two algorithms 1) PCACE (principal component analysis with canny edge) algorithm and 2) LDACE (linear discriminant analysis with canny edge) algorithm. These two methods are analyzed on palm vein image and found LDACE algorithm is a best extractor compare to PCACE method. An Equal Error Rate (EER) is applied to evaluate two algorithms. Hidden Markova Model (HMM) is utilized for image feature classification and matching using contactless Palm Under Test (PUT) palm vein database. The percentage of recognition is measured by False Acceptance Ratio (FAR) and False Rejection Ratio (FRR). This method shows robust response with respect to human palm vein identification process computation time and improved recognition rate.
Monitoring Urban Growth and Detection of Land Use/ Land Cover Change in Silchar City, Assam and Balurghat City, West Bengal
Authors:   Doctoral Student, Department of Geography, Gauhati University, Assam, India., Singh* Bhalindar , Sarkar Chandana ,   Doctoral Student, Department of Geography, Gauhati University, Assam, India.
Published: June 2020

Rapid growth and development of urban area is a worldwide phenomenon and it has become one of the certain issues facing by most of the urban areas in developing countries like India. The foremost reasons of this type of speedy growth are uncontrolled urbanisation coupled with accelerated population growth, massive influx of illegal immigrants and unorganized expansion of the urban areas. Accordingly, urban growth led to radical changes in land-use/ land-cover, which manifests profound impact on urban environment through the process of fast alteration of natural landscapes. In this context, the present study aims at comparing the pattern of urban growth and concerning land use and land cover change dynamics of two emerging frontier cities in India i.e., Silchar and Balurghat. For the purpose of the study, multi-temporal Landsat data have been used for analysing land use/ land cover changes in both cities for the period of 1988-2019.Hence, land use and land cover maps are prepared by applying maximum likelihood algorithm of supervised classification method with the help of ERDAS Imagine software. The accuracy assessment was also done by applying statistical method of Kappa coefficient. Further, the study reveals that both the cities have experienced with rapid rate of horizontal expansion. This has led to drastic change with sharpe conversion of vegetation and open field to built-up areas and which have caused innumerable environmental problems and hampers the sustainable growth of both two cities. Therefore, there has been dire need for proper planning to sustain balance of future urban growth and overall development of the areas.
Effect of Supervised and Unsupervised Algorithm for Cross Domain Sentiment Analysis
Authors:   Manav Rachna International Institute of Research & Studies, Faridabad, India., Arya* Vaishali , Agrawal Rashmi ,   Manav Rachna International Institute of Research & Studies, Faridabad, India.
Published: June 2020

Today we are living in the "information age" where data is the capital of the new economy. With the rapidly growing data every day on online portals and social networking websites, today industries are collecting and analyzing more data than before. Though data is readily available but finding valuable insights out of it is a real task. With easy accessibility of the data, new technologies, and a cultural shift towards data-driven decision making drives the need for Sentiment Analysis (SA) and makes it relevant in most of the domains like politics, marketing, healthcare, etc. This rapidly increasing information on different domains has motivated researchers to develop a cross-domain sentiment analysis model. For the development of this model, we have analyzed the performance of supervised and unsupervised models on benchmark datasets for the cross-domain analysis. The models chosen for the supervised is the Support Vector Machine (SVM) and for the unsupervised approach we have used a combination of Vader wherein the testing results showed that the supervised algorithms performed well in comparison to the unsupervised algorithm.
Deterioration Pattern of Flexible Pavement with the Help of Falling Weight Deflectometer
Authors:   M.Tech Scholar, Department of Civil Engineering, Lingaya’s Vidyapeeth, Faridabad, India., Alam* Mohd. , Nazim Mohammad ,   M.Tech Scholar, Department of Civil Engineering, Lingaya’s Vidyapeeth, Faridabad, India., Singh Dr. Sitesh Kumar ,   Assistant Professor, Department of Civil Engineering, Lingaya’s Vidyapeeth, Faridabad, India.
Published: June 2020

Maintenance and repair of the highway network system are major expenses in the state budget. For this reason, various concerned organizations are pointing out the need for developing an intelligent and efficient pavement performance model that can prioritize pavement maintenance and rehabilitation works. Such models can forecast the remaining pavement service life and pavement rehabilitation needs, and can help in the formulation of pavement maintenance and strengthening programmes which will reduce the road agency and road user costs. The flexible pavement performance or deterioration models involve the complex interaction between vehicles, environment, structure and surface of the pavement. Performance models relating to the pavement distress conditions like, cracking, ravelling, potholing, and roughness are analysed and developed by various researchers. Understanding the deterioration pattern of the flexible pavement is very important in order to take the decision for strengthening the pavement. The remaining life of the pavement depends on various factors such as Traffic, Environment and climatic conditions hence keeping in mind these factors. the thesis presents the pattern of the deterioration of remaining life of pavement. The thesis emphasis on determining the remaining life of pavement by conducting the FWD test. The FWD test is conducted on the same pavement for three time at regular interval to verify the remaining life of the flexible pavement.
Parking Space Efficiency Monitoring Near Metro Stations in Noida
Authors:   M.Tech Scholar, Department of Civil Engineering, Lingaya’s Vidyapeeth, Faridabad, India., Nazim* Mohammad , Alam Mohd. ,   M.Tech Scholar, Department of Civil Engineering, Lingaya’s Vidyapeeth, Faridabad, India., Singh Dr. Sitesh Kumar ,   Assistant Professor, department, Department of Civil Engineering, Lingaya’s Vidyapeeth, Faridabad, India.
Published: June 2020

This Study was based on data collection and calculation of the parking statistics such as occupancy, accumulation, parking volume, duration of parking, parking load. The study was performed in Noida of Gautam Budh Nagar which includes three parking’s. The two were for NA staff parking (two and four wheelers), and third for auto rickshaw stands. The parking data was collected by license plate method for five days and statically analyzed for off street parking. After the analysis it was found that the overall average parking efficiency of comes out to be 68.75 %, 65.22% and 69.22% for parking- 1, parking- 2 and parking- 3 (auto stand parking) respectively. It was found that efficiencies for all the parking were more than 65%. This concluded that these parking can be considered as satisfactory parking.
On the High Frequency Response of Grounding Electrodes: Effect of Soil Dielectric Constant
Authors: Salarieh Bamdad , De Silva H. M. Jeewantha , kordi behzad
Published: June 2020

This is the preprint of a work focused on electromagnetic transient modeling of grounding electrodes, taking the effect of soil dielectric constant into account. A full-wave numerical simulation model based on the Finite Element Method (FEM) is used in this work.