bluuebunny/crossref_metadata_2025 huggingface dataset:
Tool Condition Monitoring in Hard Turning of Inconel 718 by using Vibration Technique
Authors:   Research scholar, Dept. of Mechanical Engg, University college of engineering & Technology, Acharya Nagarjuna University, Guntur, Andhra Pradesh, India., Rao* D.Kondala , Srinivas Kolla ,   Professor, Dept. of Mechanical Engg., R.V.R. & J.C. College of Engineering, Guntur, Andhra Pradesh, India.
Published: September 2019

In various machining processes, the vibration signals are studied for tool condition monitoring often referred as wear monitoring. It is essential to overcome unpredicted machining trouble and to improvise the efficiency of the machine. Tool wear is a vital problem in materials such as nickel based alloys as they have high hardness ranges. Though they have high hardness, a nickel based alloy Inconel 718 with varying HRC (51, 53, and 55), is opted as work material for hard turning process in this work. Uncoated and coated carbide tools are employed as cutting tools. Taguchi’s L9 orthogonal array is considered by taking hardness, speed, feed and depth of cut as four input parameters, the number of experiments and the combinations of parameters for every run is obtained. The vibration signals are recorded at various stages of cutting, till the tool failure is observed. Taking this vibration signal data as input to ANOVA and Grey relation analysis (GRA) which categorizes the optimal and utmost dominant features such as Root Mean Square (RMS), Crest Factor (CF), Skewness (Sk), Kurtosis (Ku), Absolute Deviation (AD), Mean, Standard Deviation (SD), Variance, peak, Frequency and Time in the tool wear process.
A Quantitative and Qualitative Reasoning of Various Visual Cryptographic Schemes to Uphold Secrecy
Authors:   Research Scholar, Department of Computer Science & Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, India., Logeshwari* R , Parvathy Dr. L. Rama ,   Department of Computer Science & Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, India.
Published: September 2019

The secret sharing scheme plays a vital role in cryptography which allows to transmit the secret digital information (image, video, audio, handwritten notes etc.) over a communication channel. The Encoding is done in special way using Visual cryptographic schemes and decoding is carried out by the human sensory system without complexity. The secrets are encrypted into shares in these schemes, stacking these shares with minimal loss will disclose the secrets. These shares are presented in n number of transparencies. This paper provides an overview of various VC schemes of single secret and multi secret of grayscale and color secret images. Also, comparative analysis study on these schemes are presented, based on pel expansion, contrast, accuracy, capacity, security, type of share, number of shares, image format.
Modelling of Level Process
Authors:   School of Electrical Engineering, VIT, Vellore, Tamil Nadu, India., Thomas* Rhea Mariah , M* Manimozhi ,   School of Electrical Engineering, VIT, Vellore, Tamil Nadu, India., A Chitra ,   School of Electrical Engineering, VIT, Vellore, Tamil Nadu, India., Vanishree J ,   School of Electrical Engineering, VIT, Vellore, Tamil Nadu, India., Sultana W Razia ,   School of Electrical Engineering, VIT, Vellore, Tamil Nadu, India.
Published: September 2019

Industries such as, textile, food processing, chemical and water treatment plants are part of our global development. The efficiency of processes used by them is always a matter of great importance. Efficiency can be greatly improved by obtaining an exact model of the process. This paper studies the two main classifications of model development – First-Principles Model and Empirical Model. First-Principles Model can be obtained with an understanding of the basic physics of the system. On the other hand, Empirical Models require only the input-output data and can thus factor in process non-linearity, disturbances and unexpected errors.This paper utilizes the System Identification Toolbox in MATLAB for empirical model development. Models are developed for a single tank system, a classic SISO problem and for the two interacting tank system. Both systems are studied with respect to three operating points, each from a local linear region. The obtained models are validated with the real-time setup. They are satisfactory in their closeness to the real time process and hence deemed fit for use in control algorithms and other process manipulations.
Utilization of Iron Slag as Partially Replacement with Fine Aggrgate in High Strength Self-Compacting Concrete (HSSCC)
Authors:   M.E Final year student, Department of civil engineering , Chandigarh university ,Mohali,Punjab, India, singh* Khushhalpreet , singh Er. Gagandeep ,   Assistant professor Department of civil engineering Chandigarh university ,Mohali,Punjab, India, singh Er.Khushpreet ,   Assistant professor Department of civil engineering Chandigarh university , Mohali, Punjab, India
Published: September 2019

lot of work within the field of normal mix concrete and Scc has been done in the last two decades. Utilization of different waste material from the different industries as the partial replacement of cement as well as aggregates both fine and coarse has been considered in the research work by different researchers as per their area of interest. No doubt use of Iron Slag has been in trend but only cement replacement is done with it. Research work in the replacing of Fine aggregate with iron slag in SCC has not been studied in detail. An aim was set to study the hardened properties and fresh properties of iron slag based HSSCC. Mix design of M60 grade of high strength self-compacting concrete is done as per EFNARC guidelines. Testing of rheological properties of HSSCC with U- Box, Slump Flow, L- Funnel, V- Box, apparatus were done. Testing of hardened properties of HSSCC for Split Tensile Strength, flexural strength, compressive strengthas per Indian standard guidelines. Replacement of Fine aggregate (20, 30, and 40%) was done with iron slag and further addition of Alccofine and super plasticizer was done.
Critical path through Interval valued Hexagonal Fuzzy Number
Authors:   Research scholar, Mathematics Department Hindustan Institute of technology and science, Chennai ,India, Begum S* Ghousia , Praveena N. Jose Parvin ,   Assistant Professor, St. Joseph’s College of Engineering, OMR, Semmenchery, Chennai – 600119, India, Rajkumar A. ,   Mathematics Department, Hindustan Institute of technology and science, Chennai ,India
Published: September 2019

This critical path method is very useful method in the project network to succeed the multifaceted jobs. The main benefit of this technique is to decrease the completion time of the jobs. In this paper the Interval valued Hexagonal fuzzy number is applied to determine the critical path. The procedure for critical path method is described. Finally Numerical example is presented.
Unsupervised Extraction of Common Product Attributes From E-Commerce Websites by Considering Client Suggestion
Authors:   M.Tech Computer Student in computer department, Bharati Vidyapeeth (Deemed to be University) college of engineering, Pune, India., Kore* Ms. Amruta A. , Thakore Dr. D. M. ,   Professor & HeadComputer Engineering Department, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune, , India., Kadam Dr. Amol K. ,   computer department, Bharati Vidyapeeth (Deemed to be University) college of engineering, Pune, , India.
Published: September 2019

Develop an unsupervised learning framework for extracting popular product attributes from product description pages originated from different E-commerce Web sites. Unlike existing information extraction methods that do not consider the popularity of product attributes, in this proposed framework is able to not only detect popular product features from a collection of customer reviews but also map these popular features to the related product attributes. Building an intelligent E-commerce systems typically involves a component that can automatically extract product attribute information from a variety of product description pages in different E-commerce Web sites. Web information extraction methods such as wrappers are able to automatically extract product attributes from the Web content One novelty in this framework is that it can bridge the vocabulary gap between the text in product description pages and the text in customer reviews. Technically,in this framework developed a discriminative graphical model based on hidden Conditional Random Fields. As an unsupervised model, this framework can be easily applied to a variety of new domains and Web sites without the need of labelling training samples. E-commerce is proposed for enhancing the capability. Covered by electronic commerce surroundings, facing therefore voluminous new recent business model, it's obligatory to conduct the analysis to the electronic commerce pattern analysis method and like this is often useful in North American nation uncover the new electronic commerce pattern as provide the approach for electronic commerce pattern modernization to be conjointly helpful within the enterprise outline the particular electronic commerce strategy and therefore the implementation step. Initiated from this encouragement, during this paper proposes the innovative construct of the E-commerce recent agricultural product selling supported the massive web knowledge platform later the rapid development of rebuilding and opening up, China's agriculture has entered a new historical stage of development. Evaluate the growth mechanism of agricultural production enterprises from the angle of resource dynamic provide. In the e-commerce environment, the enterprise data and economic information are relatively concentrated, so the economical accounting system can instantly grasp the current activities of the economical data, and quickly generate economical information.
Stochastic Variance-Reduced Gradient Based Medical Image Restoration
Authors:   Research Scholar, Research and Development Centre,Bharathiar University , Coimbatore-46, India., Senthilkumar* R , Senthilmurugan Dr.M. ,   Research Supervisor, Research and Development Centre, Bharathiyar University, Coimbatore-46, India.
Published: September 2019

Image reconstruction is an increasingly complex field in CT. Iterative Reconstruction (IR) is at present an adjunct to standard Filtered Back Projection (FBP) reconstruction, but could become a replacement for it. Because of its potential for filtering at lower radiation dosages, IR has gotten a ton of consideration in the medicinal writing and all sellers offer business arrangements. Its utilization in cardiovascular CT has been driven to some extent because of worries about radiation portion and picture quality. In this paper proposes a novel reconstruction algorithm for different medical image modalities and bring out their performance and utilization in various medical diagnostics. The performance parameters like efficiency, utility, noise characteristics, diagnostic values etc., these measured parameter values are compared with various existing reconstruction algorithm. Our novel algorithm Stochastic Variance-Reduced Gradient is mainly designed to improve the quality of an image and to bring their practical utility to medical practitioners. Various simulation studies with benchmark medical images will be carried out to highlight the utility of the algorithm in diagnostic and medical practice.
An Efficient Brain Stroke Image Classification Model Based on Artificial Bee Colony Optimization with Kernel Support Vector Machine
Authors:   Assistant Professor, Department of CSE, D.D.E, Annamalai University, Annamalai nagar, Tamilnadu, India., Manikandan* S. , Dhanalakshmi P. ,   Professor, Department of CSE, Annamalai University, Annamalai nagar, Tamilnadu, India., Thiruvengatanadhan R. ,   Assistant Professor, Department of CSE, Annamalai University, Annamalai nagar, Tamilnadu, India..
Published: September 2019

In present decade, identification of abnormalities in brain gains significant attention for medical diagnosis. Though numerous existing models are available, only a few methods have been proposed which classifies a set of different kinds of brain defects. This paper introduces an efficient hybridization model for classifying the provided MR brain image as normal or abnormal. The presented model initially makes use of digital wavelet transform (DWT) for extracting features and utilizes principal component analysis (PCA) for feature space reduction. Next, a kernel support vector machine (KSVM) with radial basis function (RBF) kernel is built by artificial bee colony (ABC) for optimizing the parameters namely C and σ. For experimentation, 5-fold cross validation procedure is involved and a detailed investigation of the results takes place by comparing it with the existing models. To select the parameters, ABC algorithm has undergone a comparison with the random selection approach. The presented model is tested using a benchmark MR brain dataset. The experimental values indicated that the ABC is highly efficient for constructing optimal KSVM.
Implementation of Low Power High Speed Adder’s using GDI Logic
Authors:   Professor, Department of ECE, Vishnu Institute of Technology, Bhimavaram, India., Ramesh* Addanki Purna
Published: September 2019

Addition is a vital arithmetic operation and is the base of other arithmetic operations such as multiplication, subtraction and division. Adder is a digital circuit that does addition of binary numbers. The 1-bit full adder is the basic block of an arithmetic unit. In VLSI, there are many efficient techniques to design digital circuits. Some of the techniques are Pass Transistor logic (PTL), Complementary metal oxide semiconductor (CMOS) and Transmitter gate (TG). There are several adder designs implemented to reduce the power. However, each design undergoes from precise disadvantage. The adder design with good driving capability requires more power and the design with more delay which consumes less power. In this paper 8-bit Carry Increment Adder (CIA), Carry Bypass Adder (CBA), Carry Skip Adder (CSKA), Carry Look Ahead Adder (CLA), Kogge Stone Adder (KSA), Han Carlson Adder (HCA), and Brent Kung Adder (BKA) are implemented using Gate Diffusion Input (GDI) logic. These designs are simulated and implemented using Tanner tool. The result shows that CBA, CLA, and KSA designs using GDI logic are more efficient compared to CMOS logic in view of power consumption, delay, and area (transistors count) respectively.
Modeling of Multi Layered ANN Architecture for Resistance Spot Welding Process
Authors:   Sri Krishna college of Engineering and Technology, Coimbatore, India., M* Vigneshkumar , Varthanan P Ashoka ,   Sri Krishna college of Engineering and Technology, Coimbatore, India., A Lakshmanaprabhu ,   Sri Krishna college of Engineering and Technology, Coimbatore, India., S P Kamal Prasad ,   Sri Krishna college of Engineering and Technology, Coimbatore, India., Kumar N Nithin ,   Sri Krishna college of Engineering and Technology, Coimbatore, India., kumar V Aravind ,   Sri Krishna college of Engineering and Technology, Coimbatore, India.
Published: September 2019

Resistance spot welding process was widely used in the automobile industry since the early nineteenth century and still being used in the production of automobiles. Several works were carried over the several years on spot welding of different materials. The recent researchers are focusing on welding different materials using resistance spot welding process using new techniques. The present study discusses about modelling of ANN architecture. Based on the results of the cross tension failure load of resistance spot welds, the ANN model is created. It is found that the architecture consisting of 4 neurons in the interface layer has least mean square error compared to other architectures. Mean square error of architectures with varying number of neurons in the interface layer is evaluated in the present study
An Efficient Method for Suspicious Activity Detection
Authors:   Department of E&TC, Sharad Institute of Technology, College of Engineering Yadrav, Ichalkaranji., Gurav* Mr. S. S. , Godbole Dr. B. B. ,   Professor, Department of Electronics, Karmaveer Bhaurao Patil,College of Engineering & Polytechnic,Satara
Published: September 2019

This paper contributes on suspicious activity detection from length of video with less complex processing algorithm. The proposed method in this paper is easy to implement and robust enough to monitor different suspicious activities such as sudden seating, standing up, hiding from midway path, entry from midway. The suspicious frame detection is a novel approach and then confirmation is done using SURF based descriptor matching for speedy processing requirements. The results obtained in terms of tracking window and detection capability are satisfactory.
Performance Analysis of Stiction Detection Methods
Authors:   Research Scholar, Department of Electronics and Instrumentation Engineering, Annamalai University, Chidambaram - 608002, India, Abirami*  , Sivagamasundari S. ,   Department of Electronics and Instrumentation Engineering, Annamalai University, Chidambaram - 608002, India.
Published: September 2019

Industrial studies stated that, nearly 30% of badly performing process control loops are produced by nonlinearities in the pneumatic control valves, one among the main cause is stiction. The influence of this stiction nonlinearity is commonly detected as the process variable oscillations. As industrial plants contain several loops that are interacting, these oscillations will be spread to the whole system. Overhauling the defective valves will be the one among the top solution to this problem, which is probable only during the period of shut down process. But, this solution of process shut down to separate the defective valve is not cost-effective solution and hence it is taken into account as the prime one. So, there is a necessity for a technique to identify the effect of the control valve stiction. Detection algorithms available in literature are numerous and these techniques create either a quantitative or a qualitative statement about the occurrence of stiction in the control valve. While using available data, a detection method is considered to be effective only when its concluding result is relatively reliable. The main drawback while detecting stiction is that the stem position (MV) of the valve is not available in most of the situations. Quantifying the actual position of the control valve stem is always not probable. Commonly, process output and controller output are taken as the available data from most of the processes. The methods which use these data sets (PV and OP) are more appreciable by the control engineers. In this work, modified bispectral analysis technique is used as control valve stiction detection method and to prove its efficiency four different existing detection techniques available in literature are considered in this study and the performance of each method is reported. Here, eleven different data sets, seven from different laboratory processes and four from process industries are used to make the comparative analysis of performance.
Fractional Substitute of Fine Aggregates with Pozzocrete Foundary Sand
Authors:   M.Tech Student, Civil Engineering Department, Chandigarh University, Gharuan, India., Pervaiz* Farrakh , Sharma Nitish Kumar ,   Assistant Professor, Civil Engineering Department, Chandigarh University, Gharuan, India ., Kishor Brij ,   Assistant Professor, Civil Engineering Department, Chandigarh University, Gharuan, India.
Published: September 2019

To pass on immaterial effort concrete by mixing different degrees of fine total and bond with utilized foundry sand and Pozzocrete to decrease trade and sullying issues in light of utilized foundry sand and Pozzocrete. Pozzocrete P60 is a dealt with worth guaranteed fly slag, researched for its utilization as an inadequate swap for bond in cement (1:1.48:3.21). The usage of Pozzocrete P60 as bond substitution material in cement or as included substance in strong shows different focal points from sensible, explicit and ordinary perspectives. The creative use of utilized foundry sand in solid plans as a fine total substitution material was endeavored as a decision rather than standard cement. This paper demonstrates the results of the solid of blend proportion1:1.48:3.21 in which security is for the most part supplanted with PozzocreteP60 as 10% by weight of bond, and fine hard and fast isn't completely supplanted with utilized foundry sand as 10%, 30% and half by weight of fine total. Five courses of action of blend degrees were made. First (A0) were standard blend (without Pozzocrete and utilized foundry) sand with ordinary fine total (sand) and coarse total and the second (B0) blend contained 10% Pozzocrete P60obtained from DIRK India Private Limited, Nasik, Maharashtra state. Different blends (B1, B2, and B3) contained Pozzocrete P60 (10%) despite foundry sand (10%, 30%and half) solely got from ferrous and non-ferrous metal hurling associations. The compressive quality and water support has been gotten with halfway superseding of Pozzocrete P60 with bond and foundry sand with fine total. Test outcomes demonstrate the augmentation in the quality properties of cement and decreasing water assimilation of cement up to 10% overriding of security with Pozzocrete plus30% supplanting of fine total with utilized foundry sand for quality at 7, 14 and 28 days. Moreover it might be used in non-essential parts with the low range compressive quality where quality isn't required and negligible exertion brief structure is prepared.
Integration of Onsite Renewable Energy Sources and To Validate Zero Energy Buildings
Authors:   Department of EEE, GIET University, Gunupur, India. Research Scholar, JNTU Kakinada., Prasad* G R K D Satya , Reddy Dr. K. Vijaya Kumar ,   Professor in ME Department, JNTU Hyderabad, India., Babu. Ch Dr. Sai ,   Professor in EEE Department, JNTUK, Kakinada, India
Published: September 2019

At present, the buildings are account for about 40% of total global energy and also 1/3rd of GHG emissions. All buildings are having the provision of onsite renewable energy power generation, but unable to tap these resources in most of the cases. If, these resources can be tapped properly and integrated to the buildings will solve the problem of global energy shortage and also less impact on GHG emissions. In this paper, an analysis has been done by using HOMER software to estimate the capacity of onsite renewable energy sources and its integration to Zero Energy Buildings. Finally, an economical solution has been given towards integration of onsite renewable energy sources with any type of building and to make them as Zero Energy buildings.
Noise Power Spectral Density Analysis for Silicon Carbide Substrate MESFET
Authors:   taken under graduate 2010 on electronics and communication engineering in JNTUniversity, Anatapur. The master degree completed 2013 on VLSI in Sathyabama university, Chennai, India., Reddy* Boggadi Nagarjuna
Published: September 2019

This paper mainly concentrates on the transistors working functions, electrical characteristics and noise analysis at various operating voltages and temperatures. For this improvement authors are developed simulation methods for better results. The high frequency transistors are exposed with bunch of silicon carbide crystalline substances like 3C, 4H and 6H-SiC MESFETs. Because of the good researchers work, now a day’s all are compared the parameter in between of cubic and hexagonal crystalline structure of silicon carbide MESFETs. Silicon carbide material is having wide band gap because of this reason it’s useful for high energy and high frequency applications. The silicon carbide transistors are having large operating voltage in channel region because of this reason in channel region flows large current and also very less noise is produced. In wide band gap semiconductor transistors are produced very less noise compared to the various categories of substrates.
A CDIO Framework on Instructor Teaching Effectiveness using Digitized Technology Concepts
Authors:   CSE, NITTTR, University of Madras, Chennai, India, Kamatchi* K.S. , Sambandan T.Gnana ,   CSE, NITTTR, University of Madras, Chennai, India
Published: September 2019

In Engineering education it is mandatory to provide a set of digitized, technology related skill development activities to enhance the faculties teaching ability to strengthen vital innovations in academic and digital skill expertise throughout their career and to improve the continuous learning outcome of their students. This study examines the teaching and learning with digital competence will motivate and improve the performance of student learning and effectiveness in teaching (Angelo, 1991). The CDIO approach (Standard 9) guiding the educators to advance their skills in the teaching includes personal, interpersonal, process, product, system building skills and their competence are integral to implement a CDIO-based education. It is essential to recognize that faculties at distinct points of their teaching path will have divergent skillful advancement in cooperation, utility, collaboration, knowledge exchange and require explicit technologically qualified to react productively to learner, institution and various national academic regulatory bodies. In the paper, we try to compare the faculties with digital learning skills in the integrated curriculum of engineering programmes in the state of Tamil Nadu, in India with the technology integrated framework of CDIO followed by various developing countries. The proposed method shows that the teachers from various disciplines are exposed to frequent ICT (Information & Communication Technology) based training had definitely gained higher levels in using instructional technology, creativity, knowledge skill, effectiveness in delivering their instructions to improve the student cdio based learning outcome to enhance overall digital competence
Machine Learning Techniques in Lung Nodule Diagnosis of Medical Health Care Data
Authors:   Research Scholar, Dept. of CSE, Acharya Nagarjuna University, Guntur, A.P., ramesh babu* Mr. Popuri , ramesh babu Dr. Inampudi ,   Professor, Dept. of CSE, Acharya Nagarjuna University, Guntur, A.P.
Published: September 2019

Machine learning is an essential domain of research and is efficiently used in various fields like finance, clinical research, knowledge, healthcare, etc. In healthcare, Machine learning is becoming more and more popular, if not habitually required. Machine learning techniques play a vital role in uncovering new trends in the healthcare organization in especially lung nodule diagnosis. Which is also for all the parties connected with this field. Further, the focus of this review on Research is to receive the state of art study work using machine learning approaches in the area of lung nodule diagnosis. In this approach, we further include some public analysis carried out in Medical field, producing different CAD systems in the medical domain in the area of lung nodule diagnosis using pattern recognition and image processing approaches. We focus on the work which is carried out with recent classifiers used on lung nodule diagnosis, and also, we list some research on machine learning techniques. The main reason for this survey paper is to present a survey on in advance used system gaining knowledge of techniques within the place of lung nodule analysis and provide legitimate results analysis.
Combustion of Plastic Pyrolysis Oil in Steam-Atomizing Burner and Its Application for Pyrolysis Process
Authors:   Petroleum Engineering Department, Proklamasi 45 University, Yogyakarta, Indonesia., Cahyono* M.Sigit , Prasetya Agus ,   Chemical Engineering Department, Gadjah Mada University, Yogyakarta, Indonesia., Syamsiro M. ,   Mechanical Engineering Department, Janabadra University, Yogyakarta, Indonesia.
Published: September 2019

In recent years, there has been growing interest in alternative energy sources to fossil fuels. One of them is plastic pyrolysis oil (ppo) that converted from plastic waste by the pyrolysis process. The oil could be used as a fuel for combustion process in some industries. The performance of ppo combustion in steam-atomizing burner was investigated to determine the feasibility of diesel oil displacing in pyrolysis process heating. A prototype steam-atomizing burner was installed to burn plastic pyrolysis oil, with variable 3, 6, and 9 bar steam pressure, to pyrolyze 10 kg/batch low density polyethylene (LDPE) waste in a batch reactor. The pyrolysis process was maintained at 3500C along 2 hours at atmospheric condition. The flame temperature, the length of flame, fuel consumption, heating rate, and pyrolysis yield was observed along the process. The experiment shows that the increase of steam pressure will increase all parameters. The most optimum condition is plastic pyrolysis oil combustion using steam-atomizing burner at 9 bar steam pressure, which consumes 28 litre of fuel and yields 57% of pyrolysis oil.
Development of Crispy Sweet Potato Chips Utilizing Vacuum Fryer
Authors:   Professor, Food Innovation Center, Cagayan State University, Tuguegarao City, Philippines, Ibañez Arthur G. , Policar Denis V. ,   Associate Professor, Food Innovation Center, Cagayan State University, Tuguegarao City, Philippines
Published: September 2019

Objectives: The study aimed to (1) develop a shelf-stable and acceptable vacuum fried sweet potato chips, (2) establish process schedule to conduct material balance, (3) evaluate the sensory characteristics of the chips and (4) determine its nutrient composition. Methodology: Sweet potato (Ipomoea batatas) was utilized and vacuum fried. The production of the crispy sweet potato chips comprised of selecting quality and newly harvested sweet potato, washing the selected sweet potato with 50ppm chlorinated water peeling and slicing the sweet potato with 2mm thickness cooking the sliced sweet potato for 10minutes, freezing the cooked sweet potato overnight, vacuum frying the frozen sweet psotato, cooling the vacuum fried sweet potato to room temperature and weighing and packing on an 89μm thickness laminated stand – up pouch. Then, material balance was evaluated accounting to wastage and moisture loss. Finally, the quality of the product was tested through sensory evaluation. There were three mass treatments used: Treatment A with 1.0kg; Treatment B with 3.0kg; and, Treatment C with 50kg. Each treatment had three (3) replicates and were fried at 100°C. Findings: Vacuum fried sweet potatoes for The three treatments recorded average bubble end – points of 42.33 (A), 47.67(B), and 52.67 (C) minutes. This shows that the weight to be processed per batch is directly proportional with the bubble end-point as temperature and pressure were held constant. Applications: Sweet Potatoes can be developed as crispy chips utilizing vacuum fryer.
Generation of Reduced Test Vectors for Multiple Stuck at Faults using Genetic Algorithm
Authors:   Department of Electronics and Communication Engineering, BMS College of Engineering, Autonomous University, Bangalore, India., A Mrs. Abhinaya , B Veena M ,   Department of Electronics and Communication Engineering, BMS College of Engineering, Autonomous University, Bangalore, India.
Published: September 2019

As seen in the fabrication of circuits faults free circuits are difficult to obtain, as the manufacturing process is narrowing down, hence finding faults is very essential at the design level to obtain fault free circuits. As seen many of circuits have single and multiple faults, as known many research has been carried out to generate test pattern set that detect MSA faults, here the proposed ATPG method makes use of test patterns of single stuck at faults to identify MSA faults. This paper implements a method for multiple faults, generated test patterns for multiple faults has proved to be efficient by adapting a complex method of the order 3n-1 for ‘n’ lines reduced test pattern sets were obtained. This method overcomes the limitations of continuous searching algorithms, as the initial value of population size was randomly set to produce test vectors for MSA faults. The CPU processing time is very less compared to other ATPG techniques. To understand the working of the proposed methodology, we have performed an analysis by considering the ISCAS Benchmark circuits, to which the proposed ATPG method is applied, which gives the complete test vector (pattern) generation for MSA faults in the limited interval of runtime which also covers the test pattern sets for single faults.
Performance Improvement of FTTH Architecture with OCDMA Technique
Authors:   Research scholar, Department of Electronics and Communication Engineering, Chandigarh University, Mohali, Punjab, India., Swati  , Prakash Davinder ,   Professor, Department of Electronics and Communication Engineering, Chandigarh University, Mohali, Punjab, India.
Published: September 2019

In proposed simulation model, Fiber to the home (FTTH) architecture with a filter called fiber Bragg grating (FBG) based the optical code division multiple access (OCDMA) technique used to provide access to number of users to share all the bandwidth simultaneously. FTTH provides higher bandwidth than the traditional existing technology of broadband, having the capability of providing all the servixces of communication like data services, voice services and video services. The traditional metallic cables are replaced with optical fibers in Fiber to the Home to end line consumers. OCDMA provides high reliable communication. The performance improvement of FTTH architecture is done through OCDMA technique. In paper at very first, FTTH, the system with OCDMA is explained after that the architecture of FTTH using OCDMA technique, its principle explained. The proper coordination of time plays an important role in OCDMA, otherwise there is more chances of overlapping of signals and noise which may some time lead to crosstalk. There is a use of FBG as an encoder and decoder because of its low cost and the investigation is done on eye opening, BER, Q factor. The proposed model provides high Q-factor and minimum BER which is required for demands of the future communication services.
Recycling Of The Mixture Resulted From Sanitary Ware Waste, Roller Kiln Waste And Ceramic Tiles Sludge Waste In The Manufacturing Of Ceramic Floor Tiles
Authors:   Chemical Engineering Department, Faculty of Engineering, The British University in Egypt, El-Sherouk City, Egypt., Roushdy M H
Published: September 2019

Ceramic tiles industry is a big source for wastes that have a bad effect on the environment. The first source of waste is associated with roller kilns as it needs a periodic surface grinding to its rollers which results in a waste powder. The second type of waste is ceramic tiles sludge which produced from a water treatment plant. The third waste is sanitary ware waste which coming out from sanitary ware industry. The main aim of this paper is to investigate the ability of substituting part of the main body mixture of floor tiles by these three types of waste powder. Many Experiments were done on the raw materials. Rectangular tile specimens were moulded, dried and fired. Sintering parameters and mechanical properties were determined. The sample that consist of 2% Roller Kiln, 39% Ceramic tiles sludge, 15% sanitary ware waste, and 44% Floor tiles mixture has the optimum properties.
An Efficient Automated Deep Learning Model For Diatom Image Segmentation And Classification
Authors:   Research Scholar, Department of Computer Science and Engineering, Annamalai University, India., Mary A. Victoria Anand , Prabakaran G. ,   Assistant Professor, Department of Computer Science and Engineering, Annamalai University, India.
Published: September 2019

Recently, diatoms, a type of algae microorganism with numerous species, are relatively helpful for water quality determination, and is treated as an important topic in applied biology nowadays. Simultaneously, deep learning (DL) also becomes an important model applied for various image classification problems. This study introduces a new Inception model for diatom image classification. The presented model involves two main stages namely segmentation and classification. Here, a deep learning based Inception model is employed for classification purposes. To further improve the classifier efficiency, edge detection based segmentation model is also applied where the segmented input is provided as an input to the classifier stage. An experimental validation takes place on diverse set of diatom dataset with various preprocessing models. The results pointed out that the presented DL model shows extraordinary classification performance with a classifier accuracy of 99%.
Voltage and Frequency Based Optimal Load Shedding using Improved Self Adaptive Harmony Search Algorithm
Authors:   Electrical & Electronics Engineering, Research Scholar, JAIN University , Assistant Professor , REVA University, Bengaluru, Karnataka, INDIA., C N Raghu , Manjunatha A ,   Electrical & Electronics Engineering, Sri Krishna Institute of Technology, Visvesvaraya technological university, Karnataka, INDIA., Raghavendra G ,   Electrical & Electronics Engineering, Sapthagiri college of Engineering , Visvesvaraya technological university, Karnataka, INDIA.
Published: September 2019

This study presents, two load shedding scheme that are simulated on IEEE-14 bus systems are voltage dependent priority based approach and voltage and frequency based NVSI methods. The frequency-based method is designed to consider the rate of change of frequency to estimate the power loss and thereby trigger the load shedding when the frequency or rate of change of frequency exceeds the corresponding thresholds. A novel method voltage and frequency-based load shedding scheme is designed to estimate the real and reactive power losses using frequency. After estimating the power loss, the buses are indexed using the Novel Voltage Stability Index (NVSI) to select the load buses for load shedding. The loads to be shed at each of the buses are determined using the improved self adaptive harmony search(ISAHS) algorithm. Simulation results of voltage and frequency based NVSI method are presented in comparison with voltage dependent priority based approach.
Mechanical Property Variation of a Rotating Cantilever FGSW Beam under Parametric Excitation
Authors:   Dept.of Mechanical Engg., Koneru Lakshmaiah Education Foundation, Guntur, India., Padhi Dr.S.N. , Raghuram Dr.K.S. ,   Department of Mechanical engineering, Vignan's Institute of Information Technology, Visakhapatnam, A.P., India., Rout Dr.T. ,   Dept.of Mechanical Engg., Parala Maharaja Engineering College, Berhampur,India., Sudha V.Naga ,   Dept.of Mechanical Engg., Parala Maharaja Engineering College, Berhampur,India., Kumar Gill Santosh ,   Dept.of Mechanical Engg., Parala Maharaja Engineering College, Berhampur,India.
Published: September 2019

We report here the dynamic stability of functionally graded sandwich (FGSW) rotating cantilever Timoshenko beams under parametric excitation. Power law with various indices as well as exponential law were used to find out the properties along the thickness of the FGSW beam. The stability boundaries were established using Floquet’s theory. The equation of motion was governed by Hamilton’s principle and solved by Finite element method. The power index was optimized for uniform variation of shear modulus along the thickness of FGSW beam.The shear modulus variation along the thickness of the FGSW beam was compared both by power law and exponential law.It has been confirmed that the Exponential distribution of constituent phases renders better stability compared to power law distribution of the phases in the functionally graded material(FGM).
Dual Band Minkowski Fractal Antenna for Maritime Radio Navigation Services
Authors:   Department of Electronics and Communication Engineering, Sant Longowal Institute of Engineering and Technology, Longowal, Sangrur, Punjab, India,, Kumar Ashwini , Pharwaha Amar Partap Singh ,   Department of Electronics and Communication Engineering, Sant Longowal Institute of Engineering and Technology, Longowal, Sangrur, Punjab, India,
Published: September 2019

A dual band low profile fractal antenna is proposed for Maritime Radio Navigation Services (MRNS). Minkowski fractal geometry is used on both the vertical boundaries of basic patch structure and by adjusting the fractal dimension desired operating frequency is achieved. The effect of antenna dimensions on the bandwidth is determined through the parametric analysis. Proposed antenna operates at 3 GHz and 9.4 GHz with a gain of 6.3 dB and 2.5 dB respectively. Furthermore, the resonating and radiation properties of the proposed antenna are measured experimentally. Measured results of the proposed antenna are highly convincing and in good agreement with simulated results.
Improved Classification Techniques to Predict the Co-disease in Diabetic Mellitus Patients using Discretization and Apriori Algorithm
Authors:   Department of CSE, JJTU, Jhunjhunu, Rajasthan, India, Khan Shahebaz Ahmed , Jabbar M A ,   Professor at Department of CSE, Vardhaman College of Engineering, Hyderabad
Published: September 2019

The demand for data mining is now unavoidable in the medical industry due to its various applications and uses in predicting the diseases at the early stage. The methods available in the data mining theories are easy to extract the useful patterns and speed to recognize the task based outcomes. In data mining the classification models are really useful in building the classes for the medical data sets for future analysis in an accurate way. Besides these facilities, Association rules in data mining are a promising technique to find hidden patterns in a medical data set and have been successfully applied with market basket data, census data and financial data. Apriori algorithm, is considered to be a classic algorithm, is useful in mining frequent item sets on a database containing a large number of transactions and it also predicts the relevant association rules. Association rules capture the relationship of items that are present in data sets and when the data set contains continuous attributes, the existing algorithms may not work due to this, discretization can be applied to the association rules in order to find the relation between various patterns in data set. In this paper of our research, using Discretized Apriori the research work is done to predict the by-disease in people who are found with diabetic syndrome; also the rules extracted are analyzed. In the discretization step, numerical data is discretized and fed to the Apriori algorithm for better association rules to predict the diseases.
Intermolecular Interaction of Aqueous Dextran with Urea
Authors:   Physics, Centurion University of Technology and Management, Odisha, India, Panda Subhraraj , Mahapatra Achyuta Prasad ,   Physics, KBRC Degree College, Cuttack, India.
Published: September 2019

In this paper, the authors have given information regarding intermolecular interactions of aqueous dextran solution in urea. The behavior of dextran in urea has been examined by the help of ultrasonic interferometer working at frequency 5MHz at different temperatures ranging from 303 K to 323 K in 5K interval. Ultrasonic speed, density, viscosity measurements have been used for the evaluation of thermodynamic parameters like Gibb’s free energy (ΔG) as well as acoustical parameters are acoustic impedance (Z), isentropic compressibility (β), intermolecular free length (Lf) and relaxation time (τ), etc. The results have been used to throw light on the nature of the interaction among solute and solvent, interpreted in the light of structural rearrangement occurs in the aqueous dextran and urea solution.
Senet Cnn Based Tomato Leaf Disease Detection
Authors:   Final Year student, Master of Technology RGPV University Bhopal Madhya Pradesh.india, Pragy Pankhuri , Sharma Varsha ,   Assistant professor at School of Information Technology Bhopal Madhya Pradesh.india, Sharma Vivek ,   assistant professor at School of Information Technology,RGPV University, Bhopal. Madhya Pradesh.india
Published: September 2019

Plants play important roles in the environment. Various plants are fulfilling many demands and basic requirements of the society. Saving such entities in the society is the uttermost necessity in today’s world to deal with plant degradations. Many diseases in plants are common and thus they face degradation. While mainly dealing with common plant such as tomato and potato plants, it is observed that they very often face bacterial and other diseases. A proper precaution can be made to save plant from such diseases. Thus the early prediction of such different diseases can be made, which can be a massive savings to the farmer as well as for the country economy. This paper has adapted a moderate different approach of convolutional neural network called SENet. In this approach, a hybrid process is discussed which uses the advantage of SENet and CNN layer concept for better classification. CNN is performed by using the number of layer and kernel selections. Classification of data is performed using the traditional CNN approach. In this scenario, the quick process occurrence is performed using suppression of less used information. It tries to add weight to each and every feature map in the layer. This approach is used to check, identify and detect the defects in leaf of tomato. The prime motive of the presented approach is; to obtain simple easiest method for the detection of disease in tomato leaf with use of minimal computing resources. Thus an improved, efficient algorithm can be made use in real time implementation of leaf disease prediction with high accuracy and efficiency parameters.