bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Polyethylene Strips Surface Roughness on Its Efficiency for Enhancement of Wastewater Treatment
Authors:   Sanitary and environmental Engineering, Public Work department, Ain Shams University/ Faculty of Engineering/ Ain Shams, Cairo, Egypt., Elsayed* Mahmoud Mohamed Abdelmomen , El Nadi Mohamed El Hosseiny ,   Sanitary and environmental Engineering, Public Work department, Ain Shams University/ Faculty of Engineering/ Ain Shams, Cairo, Egypt., Hussein Hossam Mostafa ,   Sanitary and environmental Engineering, Public Work department, Ain Shams University/ Faculty of Engineering/ Ain Shams, Cairo, Egypt.
Published: January 2020

This study aimed to determine the effect of roughness surface for polyethylene strips on its quality for enhancement the characteristics of wastewater treatment plant effluent as a very cheap method. The study was applied at Abu Rawash WWTP effluent channel using the smooth and rough polyethylene strips where a biofilm layer forms above its surface. The removal ratio for smooth polyethylene strips for BOD and TSS was 4.45 and 4.33% respectively, while for the rough polyethylene strips was 14.10 and 13.37 respectively. This shows the success of the polyethylene strips even smooth or rough to remove both the BOD and TSS from treated wastewater. The results show that the material roughness affected the treatment efficiency with proportional effect. And the rough surface has a good removal efficiency that makes it more applicable for such purpose of enhancing the treated wastewater with very low cost technique.
Dual Image Watermarking using Symmetrical IB Algorithm
Authors:   pursuing her Ph.D degree in Government Arts College, Thuvakudi, Tiruchirappalli,, Sasi* Mrs. J. Priscilla , Arul Dr. P. ,   Assistant Professor in the Department of Computer Science, Government Arts College, Thuvakudi, Trichy.
Published: January 2020

The technique of watermarking is used to safeguard the copyright protection and used to prove the proprietorship of certain images, documents, audio and video files. This paper presents a new scheme where the final digital image is created after embedding one watermark inside another watermark (dual watermark), scrambled the image to safeguard from intruders and then embedded into the main digital image. The dual watermark mechanism improves the capacity of the data to be watermarked and more importantly the dual watermarked image is encrypted using symmetrical encryption algorithm (IB algorithm) an improved version of the blowfish algorithm to increase the security and makes it harder for the intruders to crack the watermark.
Energy Efficient Fuzzy Based Dynamic Routing Protocol in Wireless Sensor Network
Authors:   School of Information Engineering and Technology, VIT University, Vellore, India, Kumar SVN* Santhosh , priya R. Shanmuga ,   School of Information Technology and Engineering, VIT University, Vellore,
Published: January 2020

A wireless sensor network is a collection of tiny nodes, which are deployed in the given environment to sense the events. The sensed events are transmitted to the base sensor through multi hop communication for the energy efficient purpose. Routing is an very important activity for WSN where source node transmits the information to destination node using multi hop communication. Due to the inherent characteristics of WSN, there exist frequent topology changes in WSN. Most of the existing routing protocols follow only static routing. In order to overcome the issues of existing system, a novel secure dynamic routing protocol is proposed, where the optimal route can be established even in case of topology change in WSN. The proposed protocol is implemented in NS3 simulation. This simulation results justifies that the proposed protocol will improve the energy consumption using routers and increases packet delivery ratio, throughput and reduces delay.
Simulating Manual Signature using Elman Back Propagation Model to Create Pseudo Digital Signature
Authors:   Department of Mathematics, Maharshi Dayanad University,Rohtak. India., Narwal* Ekta , Gill Sumeet ,   Department of Mathematics, Maharshi Dayanad University,Rohtak. India.
Published: January 2020

Manual Signatures are used in authentication worldwide. But they are still not used in VANETs and in ad hoc networks for security. In our research we try to use manual signature in place of Digital Signatures for the security of message and stimulated the same by pattern recalling mechanism of Artificial Neural Network using Elman Back Propagation Algorithm to create pseudo digital signature. These pseudo digital signatures are now used as the identity of message sender in communication. We also maintained the speed of manual signature recognition and verification to stop the delay in identification of the sender.
Sentimental Analysis of Twitter Health Data using Machine Learning Techniques
Authors:   Information Technology, Kongu Engineering College, Perundurai, India., Devi* E.M.Roopa , Rajadevi R. ,   Information Technology, Kongu Engineering College, Perundurai, India., Kumar S.Vinoth ,   Information Technology, Kongu Engineering College, Perundurai, India.
Published: January 2020

With the huge development of Internet, more users have occupied with wellbeing networks, for example, medicinal discussions to assemble wellbeing related data, to share encounters about medications, treatments, analysis or to associate with different clients with comparable condition in social media. A lot of lookup has focused on examining Twitter health tweets for subject matter modeling using quite a number clustering approaches, but few have mentioned it for sentiment analysis. The truth that such statistics carries potential information for revealing the opinion of humans about fitness services and behaviors make it an interesting study. In these paper, universal sentiments about Twitter health data was investigated. Twitter, measuring and monitoring the occurrence of social health problems. The approach is based on two stages: In first stage separating perhaps applicable tweets utilizing a lot of uniquely made standard articulations, and afterward arranges these underlying messages utilizing machine learning techniques. Using the Twitter search API and Twitter metadata geocoded content, social media tweets were selected to start filtering. Once Tweets are correctly identified, the classifier was applied to data in order to filter out the tweets. Classification results were improved by detecting the values of ROC and f-measure. This report indicates that such a method provides a viable solution for quantifying and tracking the progression of health status within society.
Design and Analysis of Dimple Arrangement on a Small Wind Turbine Blade
Authors:   Assistant Professor, Department of Aeronautical Engineering, Sri Ramakrishna Engineering College, Coimbatore., Johny K* Robin
Published: January 2020

This article predominantly focuses on the performance estimation of a small wind turbine blade when a dimple arrangement is made along its upper surface. The dimple arrangement is grooved at two locations: 0.25c and 0.5c, where c is the chord length of the turbine blade. A CFD analysis using the k-ε turbulence model is carried out on the selected blade sections NREL S823 and S822. The continuity and momentum equations are solved using ANSYS Fluent Solver to assess the aerodynamic performance of the proposed design. The effect of introducing a dimple on the blade surface has shown to delay the flow separation, with the formation of vortices. Further, the overall performance of the blade is simulated using GH BLADED and the results acquired are discussed.
Implementation of Modified Mask RCNN
Authors:   Sinhgad College of Engineering, Pune, India. (Savitribai Phule Pune University, Date* Archana , Shah Sanjeevani K. ,   Smt. Kashibai Navale College of Engineering, Pune, India
Published: January 2020

Detecting camouflage moving object from the video sequence is the big challenge in computer vision. To detect moving object from dynamic background is also very difficult as the background is also detected as moving object. Mask RCNN is a deep neural network which solves the problem of separation of instances of same object in machine learning or computer vision. Thus, it separates different objects in video. It is the extension of faster RCNN in which an extra branch is added to create an object mask simultaneously along with bounding box and classifier. After giving input, Mask RCNN gives the rectangle around the object, class to which object belong and object mask. This article introduces Mask RCNN algorithm along with some modifications for target detection from dynamic background and also for camouflage handling. After target object detection, contrast limited adaptive histogram equalization is applied. Morphological operations are used to improve results. For both challenges quantitative and qualitative measures were obtained and compared with the existing algorithms. Our method efficiently detects the moving object from input sequence and gives best results in both situations.
Forensic Prediction using Bias-Variance Tradeoff and Random Forest Algorithms
Authors:   Assistant Professor, CSE Department, St.Joseph’s College of Engineering, Chennai, India., Shanthini* S , Vinu S ,   Assistant Professor, CSE Department, St.Joseph’s College of Engineering, Chennai , India.
Published: January 2020

Every individual host after death has its own altered micro biome configuration. After death, postmortem microorganism communities change to represent the attributes of death. The micro biome act as a many roles in human health, usually done by the exclusive lens of clinical interest. By scouring 5 anatomical areas throughout regular demise exploration from 188 case to predict the Postmortem Interval (PMI), location of death and manner of death, the postmortem micro biomes were collected. The micro biome sequencing are not easy to analyze and interpret because it produces large multidimensional dataset. To overcome the analytical challenge Machine learning method can be used. The two supervised machine learning methods employed here are Random Forest and Bias-Variance Tradeoff. In training datasets, Random forest algorithm is applied. This algorithm makes predictions by choosing the most voted node from each decision tree as the output. The output is checked for any bias variance error, by the Bias-Variance Tradeoff algorithm in order to help the supervised learning algorithm to perform generalization beyond the training datasets. To obtain a prediction that is best fitted and accurate, these two algorithms are chosen for learning.
Prediction of Workplace Absenteeism Time Using Machine Learning
Authors:   College of software, Chungang University, Heugseoglo 84, Dongjaggu, Seoul, Korea,, Choi* Jae Won
Published: January 2020

Absenteeism in the workplace is a significant cause of lost productivity of the organization and the root cause of the company's performance to many employers. Managing absenteeism is inevitable, but making sudden changes without knowing the cause of the problem is a terrible mistake. This paper aims to develop a reliable workplace absenteeism prediction model using machine learning and natural language processing techniques to aid employers with analyzation of given minimal available information about the employees’ demographics. ‘Distance from residence to work,’ ‘disciplinary failure’ and ‘weight’ was negatively associated with absenteeism time in hours. ‘Age,’ ‘son,’ and ‘height’ were positively associated with absenteeism time in hours.
Full Adders using GDI (With Full Swing) Technique for Power Efficient Computing
Authors:   Assistant Professor, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India., Kumar* M. Lakshmana , Aditya M. ,   Assistant Professor, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India., Vineela Degala Kavya ,   Student, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India., Reddy Battini Ramesh ,   Student, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India., Lakshmi B.Vijaya ,   Student, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India., Bhargavi K. S. S. S. L ,   Student, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India.
Published: January 2020

Adders, Multiplexers and other arithmetic circuits have a crucial role in Digital Signal Processing and various real time applications. Among those, Full adder is a central for most of the digital operations that perform subtraction or addition. Major component is Adder with High performance and a power efficient in specific applications. In this paper, the adder with high performance and power efficient are designed using Gate Diffusion Logic which reduces threshold voltage problem. We designed the circuits with minimum power consumption and with high performance efficiency. For the simulation of the circuits Mentor Graphics with 130nm technology is used. The obtained result shows that the proposed designs consume the minimum power when compared to other designs which are taken for the comparison.
The Unprejudiced Stemmer to Prevent Etymological Behavior of Stemmed Morphemes Of Social Media Corpora
Authors:   Research Scholar, Department of Computer Science and Engineering, Hindustan Institute of Technology and Science, Chennai, India. Associate Professor, Dept. of CSE, SITE, Tadepalligudem, AP, India, Rao* Akula .V.S. Siva Rama , P Ranjana. ,   Professor, Department of Computer Science and Engineering, Hindustan Institute of Technology and Science, Chennai, India.
Published: January 2020

Sentiment Analysis is an application of Natural Langue Processing to analyze social media corpora to extract insights of corpora. Sentiment analytical results are the real feedback of the customers, which enables the organizations and companies to take appropriate decision on their products and business policies. Stemming plays in-evitable and vital role in sentiment analysis. Stemming is one of the phase of preprocessing the social media corpora. Today most of the researches uses strong stemmers to identify stem words of social media corpora. The most popular stemming algorithms such as Lancaster and Porter stemming algorithms causes prejudiced the meaning of the words. The over-stemmed words mislead the sentiment classification process. To prevent the over-stemming the Unprejudiced lighter stemming algorithm is proposed to sustain the meaning of the stemmed words. The propose Un-prejudiced algorithm uses lexical database and Parts of speech of Python Natural Language Tool Kit. There are a few stemming algorithm accuracy evaluation methods, in this paper we focused on Paice Error-rate relative to truncation (ERRT) measure to evaluate the accuracy of Lancaster, Porter and Unprejudiced stemming algorithms. The experiments were conducted on 25,758 source words and results were evaluated using Paice stem evaluation method and Sirsat method. The Paice Evaluation ERRT values 0.47209, 0.28703, 0.15502 of Lancaster, Porter, Unprejudiced respectively are proved that the Unprejudiced stemmer is more accurate than Lancaster and Porter. Sirsat’s stem evaluation method Average Words Conflation Factor (AWCF) results 10310.31, 14031.17, 23349.87 of Lancaster, Porter, Unprejudiced respectively are also proved the Unprejudiced stemming algorithm is more accurate than Lancaster and Porter stemming algorithms.
Experimental Examination on Blended Concrete by Incorporating GGBS and Fly ash
Authors:   B. Tech Student, Department of Civil Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India., Nishanth* CH. Lokesh , Swaroop Y. Sai ,   B. Tech Student, Department of Civil Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India., Jagarapu Durga Chaitanya Kumar ,   Assistant Professor, Department of Civil Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India., Eluru Arunakanthi ,   Professor, Department of Civil Engineering, JNTU Anantapur, Ananthapuram, Andhra Pradesh, India
Published: January 2020

Concrete is the highly used building material around the world. Tons of CO2 is evolved during manufacturing process of cement. This CO2 emission has massive effect on nature and to reduce it blended concrete has been used. Now days, use of cementitious materials are increasing rapidly. Blended concrete is the concrete in which cement is mixed with different proportions of mineral admixtures such as GGBS, silica fume, fly ash etc. In present study, partially replacing of cement with Fly ash and GGBS with three different proportions. Fly ash and GGBS are by-products from coal and iron industries. Here, M40 grade control concrete which is 0% replacement of cement and Blended concrete with 3 different combinations. Both the results will be compared. Cement is substituted by GGBS in 15%, 20% 25% proportion and substituted by Fly ash in 15%, 20% & 25% proportion. These specimens are tested for Split tensile strength, compressive strength and bending strength at the age of 7 and 28 days. Using these industrial wastes not only increases strength but also makes the concrete eco-friendly.
Spatial Distribution of Water Quality Parameters with using Gis
Authors:   Department of Civil Engineering, Government College of Engineering, Bodinayakkanur, Tamil Nadu.India., Venkataraman* T. , Manikumari Dr.N. ,   Department of Civil Engineering, FEAT, Annamalai University, Annamalainagar, Tamil Nadu.India.
Published: January 2020

The present paper describes the application of GIS to study the spatial and temporal variations of some important water quality parameters in the Veeranam tank drainage basin of cuddalore district, Tamil Nadu, South India. The water quality parameters were depicted by various colour combinations for different ranges of concentrations. Twenty four (24) groundwater samples were collected from bore wells for two different seasons, pre monsoon in July 2015 and post-monsoon in January 2016. The collected water samples were analyzed for chemical constituents, such as chloride, sulphate, bicarbonate, carbonate, nitrate, sodium, potassium, calcium and magnesium in the laboratory, by following the standard procedures described by the American Public Health Association (APHA 1998). Spatial distribution map for Electrical conductivity, Hardness, Calcium, Magnesium, Sulphate and Chloride in pre-monsoon and post monsoon samples was generated by ArcGIS 9.3 software. The study implies that the quality of groundwater is generally good and potable in the nearby Veeranam lake and the quality becomes moderate as it passes away from Veeranam tank of the study area.
Vertical Upgrading of Existing Water Treatment Plants by using Air Flotation Technique
Authors:   Sanitary Eng. Section, Public Works Department, Faculty of Engineering, ASU, Cairo, Egypt., Mostafa*  , S. N. ,   Sanitary Eng. Section Public Works Department, Faculty of Engineering, ASU, Cairo, Egypt., Nadi El ,   Sanitary Eng. Section, Public Works Department, Faculty of Engineering, ASU, Cairo, Egypt., H. M.E. ,   Sanitary Eng. Section, Public Works Department, Faculty of Engineering, ASU, Cairo, Egypt., Ibrahim  ,   Sanitary Eng. Section, Public Works Department, Faculty of Engineering, ASU, Cairo, Egypt., R. M.S.A. ,   Sanitary Eng. Section, Public Works Department, Faculty of Engineering, ASU, Cairo, Egypt., Nasar  ,   Sanitary Eng. Section, Public Works Department, Faculty of Engineering, ASU, Cairo, Egypt., H. N.A. ,   Sanitary Eng. Section, Public Works Department, Faculty of Engineering, ASU, Cairo, Egypt.
Published: January 2020

Due to the rate increase for potable water need, the general market trend is the vertical expansions for water treatment plants instead of the horizontal ones. By upgrading the existing plants using new technology to reach the maximum capacity and conserve the water quality parameters as the Egyptian Code states. The most benefits of plant upgrading are no new land is needed also, low cost solution, as we could upgrade the WTP as mentioned before without adding major civil works comparing with the construction of new water treatment. This study aims to upgrade the existing water treatment plants using dissolved air floatation system, in order to reach the maximum possible capacity using several possible scenarios without adding major civil works. The study shows that, the scenario which involves DAF technology then sedimentation and filtration has the best removal efficiency because it has three treatment phases. The use of one treatment phase from floatation or sedimentation followed by filtration achieved lower efficiency. At last direct filtration, considering low removal efficiencies due to the high rate of filtration which allowed the suspended solids to escape.For the application upon Al Ameriyah water treatment plant, the first proposal which involves five combined tanks, two tube settler and one filter tank is the most convenient proposal to be achieved. Since it has quiet high value 72 points in the technical evaluation with the least estimated cost 85,769,200 LE. The use of DAF technology combined with sedimentation gives the chance to increase the existing plant capacity from 520000 m3/day to 864815 m3/day with rate of increase equals 66.31% which is a cheap and happy solution.
On Prime Cordial Labeling of Crown, Armed Crown, H-graph and Butterfly graph
Authors:   Department of Mathematics, BIHER, Chennai, India., Babu* Shalini Rajendra , Ramya Dr.N. ,   Department of Mathematics, BIHER, Chennai, India.
Published: January 2020

The prime cordial labeling for crown graph, armed crown, H-graph and butterfly graph have been described in this paper.
Sensorless Based Torque Ripple Reduction in Brushless DC Motor
Authors:   Research Scholar, Department of Electrical & Electronics Engineering, Sri Ramakrishna Engineering College, Coimbatore, India., Mumtaj * S. , Ravichandran Dr.C.S. ,   Professor, Department of Electrical & Electronics Engineering, Sri Ramakrishna Engineering College, Coimbatore India.
Published: January 2020

Abstract— Brushless Direct Current Motor (BLDCM) has been commonly utilised in fields that necessitate high fidelity and specific control, owing to its simple structure, high power density, high efficiency, high starting torque, long operating life, and prolonged ranges of speed. While considering of the drive part of the motor, the most significant part is commutation control. During commutation, they generate some high torque ripples which is caused by non-ideal commutation currents in the stator windings which confines its application, exclusively at low-voltage fields. Some of the techniques for the mitigation of commutation torque ripples are reviewed here. A complete knowledge of commutation torque ripple was done by proposed phase advancing method for commutation control for diminishing torque pulsations for the complete ranges of speed. An analysis was made in order to design and implement an optimal current vector trajectory for reducing the torque pulsations for the complete speed range. This method utilises terminal voltage sensing technique and the terminal voltages are converted into d-q reference frame and hence those values are compared with specified values in order to generate the commutation signals. Initially the proposed system is simulated with Proportional Integral controller and then with Fuzzy Logic Controller. Simulation of the proposed system was done in MATLAB version 2013a and the results of comparison was made for both PI controller and fuzzy logic controller.
An Integrated Expert Water Management (IEWM) With IoT
Authors:   Department Of Computer Science, Shivaji University, Kolhapur, Yasir, AL-Zubaidi* Yasir Ahmed Taha , Al-Gabri Hayder Kareem ,   Department Of Computer Science, Shivaji University, Kolhapur, Gaikwad Dr.S.S. ,   M.Sc.Ph.D. Sheetal, Kamat Prof.(Dr.).R.K. ,   M.Sc. ,Ph.D, Head Of Department Computer Science , Shivaji University ,Kolhapur
Published: January 2020

Water is the most widely used by all the beings present in the world. Management of water is very crucial for people to organise the water resources. Now a day’s water resources are becoming more difficult to get from various sources. Water management with IOT is used in many applications such as water tanks, agriculture and other water management places to maintain the water levels constantly. Artificial Intelligence (AI) is most widely used for various types of water management resources. Many AI algorithms are used in daily life with the integration of IOT. In this paper, an Integrated Expert Water Management (IEWM) system adopted with IOT and AI algorithms are used to develop to maintain the usage of water resources in various applications. Results show the performance of the IWM.
Automatic Diagnosis of Glaucoma using Image Processing Technique
Authors:   Dept of ECE, Kongu Engineering College, Erode, India., Kavitha* N.S. , Kasthuri Dr.N. ,   Dept of ECE, Kongu Engineering College, Erode, India., Hemalatha K. ,   Dept of ECE, Kongu Engineering College, Erode, India.
Published: January 2020

Glaucoma is a human eye condition which will affect the optic nerve present in the retina. This condition occurs due to the abnormal ocular pressure in human eye. If it is not diagnosed and treated well in advance, it may lead to blindness. This is the major problem of elderly people all over the world. The best way to avoid vision loss due to glaucoma is to detect the disease at the early stage and treat it as soon as possible. These are the keys to prevent blindness. As vision is an important organ in human body it is advisable to keep it healthy. The optic cup in the retina will be pulled in towards the optic nerve away from the optic disc. At one point, the cup will be detached from the retina, causing blindness. So if one can monitor by measuring the optic disc to cup ratio, the progression of glaucoma can be diagnosed earlier. The proposed method detects the optic disc and cup using thresholding method. Direct least square fitting algorithm is used here to fit the ellipse in order to calculate the cup height and disc height. Then the ratio is calculated. If the calculated ratio is above the threshold value, it is considered as glaucoma affected eye otherwise not. The CDR is calculated using the formula VDH/VCH (Vertical Disc Height to the Vertical Cup Height). Thus, the proposed method helps to automatically detect the glaucoma disease with better sensitivity and specificity.
Human Activity Analysis using Machine Learning Classification Techniques
Authors:   B S AbdurRahman Crescent Institute of Science and Technology, Gulzar* Zameer , Leema A.Anny ,   Vellore Institute of Technology, Malaserene I. ,   Vellore Institute of Technology
Published: January 2020

In recent times, smart phones are playing a vital role to recognize the human activities and became a well-known field of research. Detail overview of various research papers on human activity recognition are discussed in this paper. Artificial Intelligence(AI) models are developed to recognize the activity of the human from the provided UCI online storehouse. The data chosen is multivariate and we have applied various machine classification techniques Random Forest, kNN, Neural Network, Logistic Regression, Stochastic Gradient Descent and Naïve Bayes to analyse the human activity. Besides building AI models, the dimension of the dataset is reduced through feature selection process.Precision and Recall values were calculated and a Confusion Matrix for each model was made. Experiment results proved that the Neural Network and logistic regression provides better accuracy for human activity recognition compared to other classifiers such as k-nearest neighbor (KNN), SGD , Random Forest and Naïve Bayes though they take higher computational time and memory resources.
Merged Local Neighborhood Difference Pattern for Facial Expression Recognition
Authors:   Department of Computer Applications, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India., Shanthi* P. , Nickolas S. ,   Department of Computer Applications, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India.
Published: January 2020

Facial expression based emotion recognition is one of the popular research domains in the computer vision field. Many machine vision-based feature extraction methods are available to increase the accuracy of the Facial Expression Recognition (FER). In feature extraction, neighboring pixel values are manipulated in different ways to encode the texture information of muscle movements. However, defining the robust feature descriptor is still a challenging task to handle the external factors. This paper introduces the Merged Local Neighborhood Difference Pattern (MLNDP) to encode and merge the two-level of representation. At the first level, each pixel is encoded with respect to center pixel, and at the second level, encoding is carried out based on the relationship with the closest neighboring pixel. Finally, two levels of encodings are logically merged to retain only the texture that is positively encoded from the two levels. Further, the feature dimension is reduced using chi-square statistical test, and the final classification is carried out using multiclass SVM on two datasets namely, CK+ and MMI. The proposed descriptor compared against other local descriptors such as LDP, LTP, LDN, and LGP. Experimental results show that our proposed feature descriptor is outperformed other descriptors with 97.86% on CK+ dataset and 95.29% on MMI dataset. The classifier comparison confirms the results that the combination of MLNDP with multiclass SVM performs better than other combinations in terms of local descriptor and classifier.
Design of A High Performance 4-Bit Ternary Multiplier using CNTFET
Authors:   M.Tech (VLSI System design) VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, India., Laxman* P.Venkat , Senapati Ranjan K. ,   Professor, Department of Electronics and Communication Engineering, VNR Vignana Jyothi Institute of Engineering and Technology , Hyderabad, India., Teja L.Dharma ,   Assistant Professor, Department of ECE, VNR Vignana Jyothi Institute of Engineering Technology from June 2011, Hyderabad, India.
Published: January 2020

In digital world, digital circuits are influenced by binary logic. Ternary logic which follows the multiple valued logic concept for designing the logic circuits which is an great alternate to the normal binary logic due to its less power consumption and chip area is reduces. Carbon Nano-tube Field-Effect Transistors (CNTFET) is selected to implement the ternary logic circuits due to its mechanical , electrical and thermal properties. The unique feature of CNTFETs has the potential of getting required threshold voltage by varying the diameter of carbon nano-tubes that makes them as a best appropriate type for implementing the ternary logic. In this paper a 4-Bit Ternary Multiplier is designed using 1-Bit ternary multiplier by CNTFET 32nm technology node and simulated in Hspice tool. The proposed 1-Bit multiplier has 10% less delay and 18% less power than the 1-Bit multiplier proposed by Srivasu et al.
Bond Behaviour of Steel and Concrete with Pull-Out Test
Authors:   Associate Professor, Civil department, Aarupadi Veedu Institute of technology, Chennai, India,, Vijayan* Dr.D.S. , Parthiban Mr.D. ,   Assistant Professor, Civil department, Aarupadi Veedu Institute of technology, Chennai, India., Abirami Mrs.R. ,   Assistant Professor, Civil department, Aarupadi Veedu Institute of technology, Chennai, India, Nivetha Mrs. C. ,   Assistant Professor, Civil department, Aarupadi Veedu Institute of technology, Chennai, India., Deepika Mrs. Pasupuleti ,   UG Student, Civil department, Aarupadi Veedu Institute of technology, Chennai, India.
Published: January 2020

This experimental investigation presents the influence of rebar’s which has protecting coating, rested rebar and fresh rebar and there bond strength development between the steel and concrete. Pull-out experiment was conducted Universal Testing Machine (UTM) which has a capacity of 400 KN as per IS code procedure. The tested rebar includes rusty rebar, acid preserved rebar and cement chemical compound anticorrosive coated rebar. The Concrete mix design for M25 grade of concrete were used and therefore 18 concrete cube specimens with external projection of steel rod were tested. The various load slip behaviour was studied at the free end finish and loaded end victimization dial gauges. The last word bond stress just like the lowest load worth of 0.025 mm metal slip and 0.25 mm slip was thought of as a result of the usable bond strength of steel rebar’s and concrete. The check results blatant correlation exists between Load at 0.025 mm free finish slip and 0.25 mm loaded finish slip. It had been found that presence of rust and cement compound anticorrosive coating among the steel concrete interface appreciably can increase the bond strength of the order of 20 % and 27 % severally for 16mm diameter bars as compared to rust free rebar. For 20mm dia. Bars has totally different bond strength for rusty rebar’s and therefore the increase in bond strength for coated bars are compared with 2 differing kinds of uncoated bars and rusted rebar’s were determined. It’s over that presence of rust influences in reduction / increase in bond strength hoping on the character of rust at the interface among the initial ages. Application of cement compound coating has been improves the bond strength of the order of 31% – 37 % to satisfies the necessities of Burse Indian Standards code (IS)
Robust Hybrid MPPT Controller for PV Pumping System
Authors:   Electrical Engineering Department, Mohammadia School of Engineers, Mohamed V University, Rabat, Morocco., El idrissi* Rafika , Abbou Ahmed ,   Electrical Engineering Department, Mohammadia School of Engineers, Mohamed V University, Rabat, Morocco., Mokhlis Mohcine ,   Electrical Engineering Department, Mohammadia School of Engineers, Mohamed V University, Rabat, Morocco., Skik Noureddine ,   Electrical Engineering Department, Mohammadia School of Engineers, Mohamed V University, Rabat, Morocco.
Published: January 2020

This article suggests a maximum power point tracking (MPPT) method for a photovoltaic (PV) pumping system based on a nonlinear robust method combining the backstepping and the sliding mode techniques, which is referred to us as the BSMC controller. The system’s power circuit comprises of a solar panel, a step-up converter and a DC motor feeds a water pump. Two loops are in the control system: the first, provides the reference voltage, that is given by intelligent method based on artificial neural network (ANN), according with the maximum power point (MPP), to the BSMC in the second loop that regulates the PV array voltage in MPP and allows the converter to produce the required power to set the motor at the maximum speed. This is done through adjustment of the DC-DC boost converter duty ratio. The system is, on one side, able to predict the desired optimal voltage quickly by using the ANN, and also to prevent unnecessary calculation and research of the MPP. On the other side, the sliding mode and the backstepping controllers are used to provide good performance and robustness against rapid changes in the insolation and temperature. Also, the system’s asymptotic stability is proven by lyapunov’s functions. The proposed approach is compared to the method, P&O, IC and the hybrid technique ANN-integral sliding mode controller. Simulation results depict the proposed regulator effectiveness and robustness in relation to rapidly irradiance and temperature changes, using Maltab/Simulink.
Millimeter Wave Antenna Array for 5G Smart City Applications
Authors:   Assistant Professor, Department of Electronics and Communication Engineering, Kumaraguru College of Technology, Coimbatore, TamilNadu, India., Darwin* R. , Sampath P. ,   Professor, Department of Electronics and Communication Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India.
Published: January 2020

The main objective of any antenna design in the rapid growing wireless communication sector are in terms of speed, bandwidth, energy efficient and vast data handling capabilities[1]. Here in this paper we propose an antenna array system design with 8x8 geometry (64 patches) which is capable of working in millimeter wave (mm wave) with high data rate and less power consumption[2]. The antenna is designed to operate in the frequency range of 28 GHz to 28.6 GHz. The bandwidth obtained in the antenna is of 600 MHz range. The maximum gain obtained in the array is 20.7 dB. The main drawback of millimeter wave communication is its short distance communication capability. So it will be the perfect candidate for smart city applications since the area coverage will not be that large but with increased demand in data rate, which can be perfectly addressed by millimeter wave communication antenna.
Mechanisms for Preserving the Institution of the Family: National Characteristics
Authors:   Astrakhan State University, Astrakhan, Russia., Topchiev* Mikhail Sergeevich , Dryagalov Vyacheslav Sergeevich ,   Astrakhan State University, Astrakhan, Russia., Bicharova Maria Mikhailovna ,   Caspian Institute of Sea and River Transport,Astrakhan, Russia.
Published: January 2020

The formation of family values in the younger generation begins at the earliest stages of personality formation within the family and continues in the socialization process in society. The value system associated with the institution of marriage and the family is transmitted through various channels, ranging from parenting to the virtual environment. The border areas, such as the Astrakhan Region, which are characterized by interfaith marriage unions, are a special environment, in which there are own mechanisms for preserving the institution of the family and special channels for transmitting family values. One of these mechanisms is the reconstruction of the traditional wedding ceremony. Within the framework of the present research, the authors studied archival documents containing information about the traditional wedding ceremonies of the peoples living in the Astrakhan Region. There was also a content analysis of ritual traditions related to the creation of a new family (matchmaking, wedding, etc.), in the reconstruction of which the modern cultural organizations of the region were involved. The research results show that the reconstructed wedding ceremony between partners, when one of them is a representative of another nationality and religion, is a kind of portal, through which the future spouse enters a new cultural environment for him or her and begins his or her adaptation already at the initial stage of creating a family union.
Risks and Legal Opportunities of National Projects: Modeling Security
Authors:   V.I. Vernadsky Crimean Federal University, Simferopol, Russia., Ivanov* Petr Ivanovich , Burkaltseva Diana Dmitrievna ,   V.I. Vernadsky Crimean Federal University, Simferopol, Russia., Arzumanov Robert Mosesovich ,   Kerch State Marine Technological University, Kerch, Russia., Grischenko Leonid Leonidovich ,   Management Academy of the Ministry of the Interior of Russia, Moscow, Russia., Zhirnov Yuriy Nikolaevich ,   Management Academy of the Ministry of the Interior of Russia, Moscow, Russia, Pestov Nikolay Nikolayevich ,   Management Academy of the Ministry of the Interior of Russia, Moscow, Russia., Oleynik Aleksandr Sergeevich ,   Management Academy of the Ministry of the Interior of Russia, Moscow, Russia., Uryadov Yuriy Yurievich ,   Management Academy of the Ministry of the Interior of Russia, Moscow, Russia.
Published: January 2020

The goal is to explore the interaction between the vector of economic security development and the vector of threat to the economic security, as well as the possibility of quantifying the result for management purposes. The fundamental possibility of the business socioeconomic system at the mesolevel to counteract the factors of threat to economic security based on the model of interaction between the vectors of development and threat has been reviewed. The linear differential equations have been transformed. Analytical expressions that describe the parameters of the model of interaction between the vectors of development and threat have been obtained. Possible combinations of parameters have been studied.The main risks of the implementation of national projects include financial risks, quality of state and municipal government, external global risks, risks of trade wars, sanctions, and differentiation of regions. The problems of public administration should include legal support, fraud, scale of corruption, speed of decision-making, terms of implementation, insufficient qualifications of civil servants, centralization of the budget process, and imperfection of control mechanisms.The problems of municipal management should include staff shortage, level of employees' qualification, outdated management system, outflow of qualified personnel/staff turnover, red tape, inconsistency of federal and regional laws, workflow, administrative barriers, and performance indicators for municipalities.Conclusion. Institutional support and measures aimed at solving problems in state and municipal administrations will allow to significantly mitigate risks in the implementation of national projects in the field of ensuring socioeconomic and national security. Risks are incomplete traceability of the movement of funds, overestimated indicators for regions that do not have the resources for this. Federal center subsidies hide the problem, but their size does not help the regions to be flexible enough, and this in turn affects efficiency. The conclusion is drawn on the appropriateness of applying the proposed model for the interaction between the vectors of development and threat in the economy. The area of further research is determined.
Machine Learning Algorithms based Skin Disease Detection
Authors:   Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India., Bhadula* Shuchi , Sharma Sachin ,   Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India., Juyal Piyush ,   Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India., Kulshrestha Chitransh ,   Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India.
Published: January 2020

Skin disease recognition and observing is a major challenge looked by the medical industry. Because of expanding contamination and utilization of lousy nourishment, the tally of patients experiencing skin related issues is expanding at a quicker rate. Well-being isn’t the main concern, however unfortunate skin hurts our certainty. Customary and appropriate skin checking is a significant advance towards early discovery of any destructive or starting changes in skin that may bring about skin disease. Machine learning methods can add to the improvement of capable frameworks which can order various classes of skin illnesses. To identify skin maladies, first, it is required to separate the skin and non-skin. In this paper, five diverse machine learning algorithms have been chosen and executed on skin infection data set to anticipate the exact class of skin disease. Out of a few machine learning algorithms, we have worked on Random forest, naive bayes, logistic regression, kernel SVM and CNN. A similar examination dependent on confusion matrix parameters and training accuracy has been performed and delineated utilizing graphs. It is discovered that CNN is giving best training precision for the right expectation of skin diseases among all selected.
Stressed State of Elements of Dismountable Drilling Tool with Spherical Cutters: Simulation in Software Environment
Authors:   Siberian Federal University, Krasnoyarsk, Russia., Bovin* Konstantin Anatol'evich , Shigin Andrey Olegovich ,   Siberian Federal University, Krasnoyarsk, Russia., Kritsky Dmitry Yuryevich ,   Siberian Federal University, Krasnoyarsk, Russia., Erofeev Alexander Igorevich ,   Siberian Federal University, Krasnoyarsk, Russia., Yarkov Vitaliy Aleksandrovich ,   Siberian Federal University, Krasnoyarsk, Russia., Vicelar Evgeniy Ilyich ,   Siberian Federal University, Krasnoyarsk, Russia.
Published: January 2020

Advance in extraction of mineral resources is one of the most prioritized problems of mining industry in Russia and other countries. Herewith, drilling and blasting operations are the most important mining stages, the relevant expenses reach up to 50% of total mining costs. Drilling tool is the most important and highly loaded element of drilling assembly determining the efficiency of blasthole drilling. Existing designs of drill bits of Russian and foreign manufacturers are nondismountable, that is, are beyond repair or reclaim, especially in field conditions. For instance, in the case of failure of one bearing support, the drill bit fails and is rejected. Despite numerous types of drilling tools, their stressed state has been studied sufficiently only for serially fabricated drill bits. Therefore, it is important to study strength properties of dismountable drilling tools which provide the maximum operation lifetime of the basic parts (body and coupling). Complete information about loads acting on the main elements of drill bits is required to improve designs of dismountable drilling tools. This work analyzes stress and strain state of dismountable drill bits with spherical cutters (RSShD) using finite element models in ANSYS software environment. Predictions are made for the cases of maximum loads exerted by highly efficient drilling rigs on the drill bit and heterogeneous distribution of these loads over elements of the drill bit. Distributions of equivalent stress fields occurring in drill bit body, bearing supports and cutters are presented. Drill bit operability in various operation modes is analyzed.
Handwriting Text Recognition using Neural Networks
Authors:   Computer Science and Engineering, Vidyavardhaka College of Engineering, Mysuru, India., H Parikshith , Rajath S M Naga ,   Computer Science and Engineering, Vidyavardhaka College of Engineering, Mysuru, India., D* Shwetha ,   Computer Science and Engineering, Vidyavardhaka College of Engineering, Mysuru, India., C M Sindhu ,   Computer Science and Engineering, Vidyavardhaka College of Engineering, Mysuru, India., P Ravi ,   Computer Science and Engineering, Vidyavardhaka College of Engineering, Mysuru, India.
Published: January 2020

Handwritten text recognition is a laborious task because humans can write a similar message in numerous ways or due to huge diversity in individual’s style of writing. The performance of text recognition systems implemented as neural networks has better results and accuracy than normal traditional classifiers. In this paper we explore the methods used to recognize and detect handwritten text or words in different languages. The major method used to recognize text is the Convolutional neural network (CNN) as a deep learning classifier. The other techniques used are Recurrent Neural Network (RNN) and a custom developed model called deep-writer, which is a variant of CNN architecture.