bluuebunny/crossref_metadata_2025 huggingface dataset:
Study on Behaviour of Self-Healing Concrete Using Silica gel
Authors: Sumitha V , T. Ravichandran P , Krishnan K Divya
Published: April 2019

The procedures to enhance the strength and reliability of materials depend on the worldview of damage prevention, i.e. the materials are composed and arranged so that the development and expansion of damage is postponed however much as could reasonably be expected. The reinforced concrete structures are subjected to various loads such as heavy vehicles movement, earthquakes, and strong winds etc. which inevitably develop micro cracks. When micro cracks originates, a sequence of events begin within structures. These cracks affect the performance and strength of the structure, in addition withdurability of the structure.To overcome the above problems, it is required to consider the use the Self-Healing Concrete (SHC). In this work the attempt is made to study the use of silica gel as self-healing agent in M60 grade of concrete. The healing agent is mixed in varying proportions are 0.1%, 0.2%, 0.3% and 0.4% respectively by weight of cement inblended concrete mix grade of M60. The performance of silica gel as a self-healing agent was analyzed at different curing periods of 7, 14 and 28days. The concrete specimens were prepared to study the mechanical strength properties lie compressive strength, split tensile strength and flexural strength of blended concrete with and with addition of silica gel.The compressive strength of the blended cement concrete with addition of 0.3 % of silica gel gives 6.54% more strength compare to the control specimens at the age of 28 days testing. The performance of the 0.3% of Silica gel replacement in mechanical strength properties gives considerable effective enhancer compare to the control specimens. Based on the results it can be concluded that the optimum replacement is 0.3% silica gel. Silica gel can be used as one of the healing material in the construction of tunnel, underwater structures etc..
Investigation on Mechanical properties of Partial replacement of Saw-Dust to Fine-Aggregate in Coconut-Shell Concrete
Authors: S Anandh , K Gunasekaran
Published: April 2019

Concrete is the major composite material used in construction industry, it is strong in Compression and weak in tension and also has high self-weight. The light weight concrete was a alternative to conventional concrete due its low weight it decreases the self weight. Comparatively by using the light weight materials that occur either naturally or industrial waste, these material helps in reducing the cost and to improve the performance. Presently in India, more than 960 million tones of solid waste were being generated annually as by-products during industrial, agricultural mining and other processes. This paper deals with coconut shell concrete, which is one of the solid waste in the environment, and the use of this coconut shell as a replacement to coarse aggregate will reduce the weight of concrete by 25%. The other waste that was disposed mostly was sawdust. It was a byproduct of cutting or drilling of wood with saw or other tool. It is composed of fine particles of wood. It is having many advantages over traditional concrete like low bulk density, better heat preservation and heat insulation property. As said earlier to make concrete strong in tension coconut fiber is added, which is a waste material that left to disposal and as it is strong and stiff will hold the concrete material and also controls the crack. This study investigates on the use of sawdust as partial replacement for fine aggregates in concrete production. Sawdust was used to replace fine aggregates in Conventional and as well as in Coconut Shell concrete from 0%, 5%, 10% and 20%. M25 grade of concrete was selected and testing is evaluated at age of 3, 7 and 28 days. From the results, increase in percentage of saw-dust in concrete cubes led to corresponding reduction in compressive strength values, and the optimum saw-dust content was obtained at 5% in conventional as well as in coconut shell concrete , coconut fiber was added at the optimum value of sawdust on conventional and coconut shell concrete at 1%,2%,3%,4% and 5%. The better strength was obtained at 2% addition of fiber in coconut shell concrete and at 3% addition in conventional concrete.
Conductivity and structural studies of PVA based mixed-ion composite polymer electrolytes
Authors: Srivastava Sandeep , K. Varshney Pradeep
Published: April 2019

The solid membranes having different ratios of poly-vinyl alcohol (PVA), sodium perchlorate (NaClO4) and lithium perchlorate (LiClO4) were prepared using solution casting technique. The mixed-ion composite polymer electrolytes were characterized by X-ray diffraction analysis (XRD), Fourier transform infrared spectroscopy (FTIR) and conductivity measurement investigations. The XRD study confirms the amorphous nature of the mixed-ion composite polymer electrolytes. FTIR analysis has been used to characterize the structure of polymer which confirms the polymer and salt complex formation. The temperature dependent nature of ionic conductivity of the mixed-ion composite polymer electrolytes was determined by using conductivity meter (EC-035WP ERMA Inc, made in Japan). The ionic conductivity of the electrolyte was found in the range of 10-3 - 10-4 S/cm at room temperature.
Management Information System for Monitoring and Inspection of the Implementation of Universities
Authors: Gerit John Rupilele Frits , Soulis Irwan , Palilu Aram , Hasibuan Abdurrozzaq , Fransisca Winesty Tutupary Ontje , Alfret Goraph Frets , Sidete Herman , Mouw Erland , Laritmas Selfianus , Tondo Simson , Jamil Mohamad , Dara Utama Mutiara , Tahitu Amelia , Freedom Nanuru Ricardo
Published: April 2019

Inspection of Universities infringement (PT) is one of Controlling, Supervising and Guidance (dalwasbin) activities aimed at developing problematic universities in order to be back on track and able to run Tri Dharma of Higher Education in accordance with National Standard of Higher Education. Based on the results of evaluation and inspection of Higher Education in 2017 at Coordination of Private Higher Education Region XIV there found 29 Universities out of 61 Universities that committed violations. Management of infringement inspection of Higher Education requires the role of information technology due to the geographic area of the Higher Education and management of Higher Education inspection that is still manual causing management to be ineffective and inefficient.  Coordination of Private Higher Education Region XIV requires an information system that can support and assist data of infringement in universities and management of universities inspection. The design of information system in this research used waterfall method. The design of system models used unified modeling language diagrams (UML) including use case diagrams and activity diagrams. The design of this information system generated a system that can support the management of integrated and centralized infringement inspection to facilitate the inspection, monitoring and reporting of inputs and information for Coordination of Private Higher Education and the ministry in mapping the institutional quality Higher Education.
Emprical Study of Iot Solution for The Security Threats In Real Life Scenario: State of The Art
Authors: Bala Murugan C , Koteeswaran S
Published: April 2019

IoT technology and applications represents security as a significant issue for facilitating the tremendous implementation.     Devoid of IoTs technology ensures the device level confidentiality, privacy and authenticity. The applicable users are not going to     undertake answers for security in IoT in huge scale. The earlier stage deployments of IoT devices are primarily based on RFIDs         technology which results in simplest, security solutions inside the principal been devised in an advert hoc manner [8]. This brings the fact that such deployments were typically vertically incorporated, with all additives beneath the manage of a single administrative entity. In the angle of an IoT eco-system, in which unique person may be worried in a given software state of affairs. One person owing the      physical operations of  sensors, one stakeholder deals with the statistics and processing them and other numerous stakeholders supplies different services based totally on such statistics to the customers. This leads to numerous variety of safety demanding situations and security for the IoT. In this paper, we address the revisited security issues and discuss the critical safety protection conditions of Internet of Things era into a mainstream. To support this, the three key problems requiring cutting-edge techniques includes are data               confidentiality, privacy and trust.In this review, we presented net factors with architectural design goals of IoT. We surveyed security and privacy issues in IoTs. Also the discussion on several open issues based on the privacy and security is addressed. Many real time applications of IoTs in real life treats the security issues of IoT as a main factor. Thus the IoT of complicated security issues have been anticipated the researchers to address.
A Study on Machine Learning: Elements, Characteristics and Algorithms
Authors: Chokkanathan K , Koteeswaran S
Published: April 2019

Machine learning algorithms are used immensely for performing most important computational tasks with the help of sample data sets.  Most of the cases Machine learning algorithms will provide best solution where the programming languages failed to produce viable and economically cost-effective results.  Huge volume of deterministic problems are addressed and tackled by using the available sample data sets.  Because of this now a days machine learning concepts are extensively used in computer science and many other fields.  But still we need to explore more to implement machine learning in a specific field such as network analysis, stock trading, spam filters, traffic analysis, real-time and non-real time traffic etc., which may not be available in text books.  Here I would like to discourse some of the key points that the machine learning researchers and practitioners can make use of them.  These include shortcomings and concerns also.
Analysis of modern construction projects using montecarlo simulation technique
Authors: Arunmohan A. M. , Lakshmi M.
Published: April 2019

Today, Construction based Industry is the prospering industry which has a high economical influence on any nation. Delay in the huge construction project increases the total project cost. Henceforth, uncertainties as well as risks must be significantly regarded during the project. For organizing and completing the projects in a financially, timely and qualitatively accountable manner, careful scheduling of projects is compulsory. Effectual scheduling of project assures project success. This study concentrates on qualitative analysis, risk identification, together with quantitative analysis. The targets are i) to ascertain the key risk aspects that disturb the project schedule, and ii) to find the probability of finishing the project within specified time. Questionnaires are distributed amongst 20 industry practitioners with disparate experience from [1] to [25] years.  Quantitative analysis is made by the methods like Monte Carlo simulation (MCS) and PERT. @RISK by Palisade corp. is utilized for MCS.
A Hybrid AFSS-SHC Optimization Methodology for Balancing the Load Efficiently in Cloud Environment
Authors: J Aswini , Malarvizhi N , K Anitha. , . .
Published: April 2019

Cloud computing helps to share data and provide many resources to users. Users pay only for those resources as much they used. Rapid increase in load to these cloud framework cannot be predicted. Load balancing is one of the issues in cloud computing that distributes the workload to the nodes in such a way no node is overloaded or under - loaded. Load balancing is a main challenge in cloud environment.  In this work,  scheduling algorithm is applied for load balancing by considering the cost of  task execution and make span. This scheduling algorithm efficiently maps task to available nodes in cloud and it is beneficial to user and service provider. Load balancing segregates assignments of tasks among all available virtual machines from datacenters. Assignment of tasks to virtual machines can be done with minimum delay. To enhance the make span, resource utilization, our proposed framework utilizes AFSS-SHC load balancing strategy.  A metaheuristics swarm intelligence algorithm which is NP-hard have been suggested to balance load across devices. The algorithms taken into account are-HEFT,PSO and PSO-HC. The proposed methodology AFSS-SHC optimized the task scheduling. Random tasks have been taken for this purpose and simulated to show that the proposed methodology works efficiently to reduce the make span of tasks to reduce the cost.
A Detail Study on Biometrics with Matlab
Authors: Avinash P , Venkateswarlu T , Anand Dama
Published: April 2019

Biometrics is an emerging field of innovation utilizing one of a kind and quantifiable physical, natural, or behavioral attributes that can be prepared to recognize a man. It is a multidisciplinary subject that incorporates building, measurements, arithmetic, figuring, brain research, and approach. The requirement for biometrics can be found in governments, in the military, and in business applications. The Electrical Engineering Department at the U.S. Maritime Academy, Annapolis, MD, has presented a biometric flag preparing course for senior-level undergrad understudies and has built up a biometrics lab to help this course. In this paper, the creators exhibit the course content, the recently created biometric flag handling lab, and the intuitive learning procedure of the biometric course. They examine a portion of the challenges that were experienced in executing the course and how they were overcome. They additionally give some input from the course appraisal.
A Survey on Image Fusion Requirements, Techniques, Evaluation Metrics, and Its Applications
Authors: N. Narsaiah M , Vathsal S , Venkat Reddy D
Published: April 2019

Fusion refers to combining two or more distinct things, the main objective of employing fusion is to generate results that provides the most detailed, reliable and accurate information possible.  The image fusion is one of the main branchof data fusion. In image fusion the images are fused at different levels of images like pixel, feature and decision level. The necessity of image fusion for high resolution on multispectral and panchromatic images or realtime images for better vision. This paper reviews the general requirements of image fusion, widely used image fusion techniques such as PCA,IHS,DWT,NSCT etc.,summarizes the Quality Assessment Metrics in terms of  metric, description and its principle,  finally image fusion applications in various fields such as object detection, object identification, optimization and pattern reorganization, medical imaging, etc.,
Enhancing Data Security Using Audio-Video Steganography
Authors: Mudusu Rambabu , Nagesh A , Sadanandam M
Published: April 2019

Steganography may be a strategy for concealing any mystery information like content, picture, sound behind distinctive cowl document .In this paper we have a tendency to planned the mix of image steganography associated sound steganography with confront acknowledgment innovation as an instrument for verification. The purpose is to shroud the mystery information behind sound and therefore the beneficiary's face image of video, because it may be a use of various still casings of images and sound. During this technique we've chosen any casing of video to shroud beneficiary's face image and sound to hide the mystery data. Affordable calculation, maybe, increased LSB and RSA rule is been utilised to shroud mystery content and movie. PCA rule is employed for confront acknowledgment. The parameter for security and verification ar gotten at collector and transmitter facet that ar exactly indistinguishable, consequently the knowledge security is dilated.
Multinode Cluster Analysis for Prediction of Heart Disease Using Biglm Algorithm
Authors: Leelavathy J , S.Selva brundha Dr
Published: April 2019

The manuscript proposes a novel approach to uncover pattern from a huge chunk of data with minimal time consumption. The goal of the manuscript is to build a robust predictive model to handle big data in patient data. The manuscript follows a master-slave  approach. The training data is divided into n number of chunks and processed. The data involves 32,96,168 row vectors and each row vector holds 14 attributes. The model is given a row vector with 14 attributes whether the system could predict the target class by linear modeling. From the experimentation done in single master and four slave setup, we infer that the system could fit a linear model in 1800 seconds. A comparative study has been made on training the huge chunk of data in a standalone device and in master-slave devices. From the experimental analysis, we infer that the training time of the proposed approach has been reduced by more than half since the proposed approach divides the huge chunk of data into independent chunks and computation is done at multiple nodes.
Liquid Induced Vibrations of Truncated Elastic Conical Shells with Elastic and Rigid Bottoms
Authors: V. Naumenko Yury , I. Gnitko Vasyl , A. Strelnikova Elena
Published: April 2019

A method of estimating natural modes and frequencies of vibrations for elastic shells of revolution conveying a liquid is proposed. The vibration modes of the liquid-filled elastic shells are presented as linear combinations of their own vibration modes without liquid. The explicit expression for fluid pressure is defined using Bernoulli’s integral and potential theory suppositions. Non-penetration, kinematic, and dynamic boundary conditions are applied at the shell walls and on a free liquid surface, respectively. The solution of the hydro-elasticity problem is found out using an effective technique based on coupled finite and boundary element methods. Computational vibration analysis of elastic truncated conical shells with different fixation conditions is accomplished. Sloshing and elastic walls frequencies and modes of liquid-filled truncated conical tanks are estimated. Both rigid and elastic bottoms of shells are considered. Some examples of numerical estimations are provided to testify the efficiency of the developed method
Hydrogen Production Through Water Splitting Reaction Using Titanium Dioxide (Tio2) Nanotubes Photocatalyst
Authors: . Mohdhasmizamrazali , Ismail Nurarifah , Mat Amin Khairulanuar
Published: April 2019

Nowadays, the most ideal process for hydrogen production is to use water as a hydrogen source through water splitting reaction with the present of the titanium dioxide photocatalysts. Titanium dioxide nanotubes (TiO2-NT’s) was synthesized using facile hydrothermal method. TEM micrograph shows that the synthesized TiO2-NT’s had tubular structure with “hair-like” nanoscopic filaments with large specific surface area, which is needed to be a high performance photocatalyst. The saiz of nanotube are 4 nm and 10 nm for inner and outer diameters, respectively. Meanwhile, their surface area was found to be 226.52 m2/g. XRD pattern revealed that the phase structure of synthesized TiO2-NT’s was anatase TiO2. Synthesized TiO2-NT’s was tested for hydrogen gas production managed to produce 80 µmol after 5 hours reaction.
A study on wavelet analysis of SSVEP Signals
Authors: Babu Bincy , Chandrasekaran R , Elsa Joseph Josline , Shalem Rahul Thella , R Thamizhvani T , Josephin Arockia Dhivya A
Published: April 2019

Almost every Brain Control Interfcae (BCI) system is framed based on Steady State Visual Evoked Potential (SSVEP) which is predicted through distinguishing overriding frequency components in Electroencephalography (EEG) signals. The proposed system aims in accurate feature extraction of SSVEP signals. Power spectral analysis and wavelet analysis are done for feature analysis. The feature set variation for male and female subjects are obtained. Compared power spectral estimation and wavelet analysis, merits and demerits of each approach can be identified from the outcomes. It offers a theoretical reference of practical choice for BCI application.
Automatic Synchronverter: Inverter Lacking a Devoted Synchronization Unit
Authors: Manoj S , Pradeep Kumar S , Ashok Babu N
Published: April 2019

The design of self-synchronized synchronverter is made by removing the keen synchronization unit. Synchronization with the grid takes place before connection and it will track the grid frequency after connection. Like the original synchronverter it functions in various modes to deliver the grid frequency as the reference frequency. The functions of frequency regulation, voltage regulation, real and reactive power control are maintained. Moreover, it can share the real power and reactive power accurately. Distributed energy sources delivers the major contribution to the power system operation. Generally the renewable sources are non-linear and uncontainable. Majority of renewable energy sources were associated to power systems through dc/ac converters. For this kind of application synchronizing the inverter with the grid is necessary before and after the connections to be made. It is one of the biggest challenges. So synchronverter is designed to deliver a scheme for power systems to regulate the renewable energy connected to the grid and enables smart grid integration.
Multi-input multi-output converter with battery charger for low power applications
Authors: Pradeep Kumar S , Krishnakumar R , N.Ganesh E
Published: April 2019

For low power applications an integrated type multi- input multi- output converter with battery charger was presented in this paper. Power can be delivered from different sources with low power switching device using the proposed topology. The circuit model is designed to reduce the switching losses and to improve the converter overall efficiency by charging the battery using transformer leakage inductance. The input power distribution includes two input sources are operated by this converter model. This paper proposed a 20 –W prototype to test the converter performance and the experimental results are shown.
Energy efficiency hybrid power management of electric vehicle (EV) charging through photovoltaic (PV) and micro grid (MG)
Authors: Rubini B , Krishnakumar R
Published: April 2019

To Analyze wireless charging system of solar PV, panel concept with electric vehicle (EV). In this developed type is a combination of solar photovoltaic (PV) and Micro grid. In this type, designed two type of operation initially the EV Charging with micro grid input supply and PV Panel. If any fault occur or grid power failure the EV battery system charge through PV panel ultimately the battery sys-tem always on line charging either grid source or PV arrays panel. The proposed methods are integrated with bidirectional converter back-to-back converter with grid source. This paper focus into the power enhancement depends upon the irradiation of solar panels, so that the conversion of electrical energy is in accordance with the needs of electric vehicle attain maximum as possible. The design type of EV wireless charging methodology analyzed using MATLAB/Simulink is to get the effective power enhancement and charging to the electric vehicle continuous on line charging system.
Detection and feature extraction of CT lung tumor using cad system
Authors: Josephin Arockia Dhivya A , J. Hemalatha R , R. Thamizhvani T , Elsa Joseph Josline , Babu Bincy , Chandrasekaran R
Published: April 2019

A 64 slice computed tomography is used for treating pulmonary related embolism diseases.Pulmonary embolism is a condition which causes death for all age group people.In a decade analyzing, computed tomography technique is regarded as the minimally painful technique.In this condition basically there are five steps involved in it.The first step involved is segmenting the lung sec-tion.The second step briefly delivers about PE extraction using a mask of high intensity.The third step involves in extracting the features in the image.The fourth step is reducing the features using artificial neural networks.The fifth step involves a multi fea-ture system having k as its neighbor,which is helpful for classifying positive and negative differentiation.There are few other methods to improve the performance.:They use tobogganing algorithm and they use the method of grouping and it attained the sensitivity of 80%Other scoring methods are achieved and performance has been enhanced.It also improves CAD performance.
Spectral analysis of electrogastrogram
Authors: Chandrasekaran R , J. Hemalatha R , J. Kowshic T , Arokiya Dhivya Josephin , R. Thamizh vani T
Published: April 2019

Gastroparesis is a condition that affects the normal motility of muscle in the stomach and is commonly called as paralysis of stomach. Electrogastrography is the technique for measuring electrical activity of the stomach. The Electrogastrography is also used to measure the gastric mobility and various stomach disorders like tachy-gastria, brady-gastria, dyspepsia, peptic ulcer, gastric tumor etc. Electrogastrogram is the graphical representation of the Electrogastrography. The Electrogastrography procedure is recommended by the physician to diagnose the dis orders in the stomach. Electrogastrography procedure is taken generally under two conditions: Fasting condition and post prandial condition. This procedure is followed strictly to measure the gastric activity and gastric emptying test. The food is propelled into the stomach and the pacemaker of the stomach fails to contract the muscles of stomach that leads to gastroparesis condition. The diabetic patients often get into the gastroparesis condition. This remains as a major factor; stomach motility is slowed down. In this paper, data acquisition system for acquiring multichannel electrogastrogram is developed and the gastric signal is acquired and analysed using MATLAB. Through the spectral analysis of gastric slow-wave, the gastroparesis condition is diagnosed. The MEGG-Multichannel Channel Electrogastrogram signal is acquired in two states: Fasting state and Postprandial state.
Space Vector Pulse Width Modulation Method to Reducing a Switching Loss in Inverter
Authors: M.Revathi S. , R.Balamurugan C. , Shanmugasundaram N.
Published: April 2019

In This paper proposedÂ an area space Â vector PWMÂ technique Â thatÂ reducesÂ switchÂ  victims ofÂ anÂ electrical converter Â mainly efficiently by two-phase modulationÂ technique. This technique chooses the most favorable one Â that Â minimizes Â a replacement Â switchÂ (SW) defeat judgment Â supportedÂ lessening belongings in switch period allowing forÂ  sectionÂ currents in numerous lessening patterns. This paper proposes Â anÂ  basic Â curved Â PWM Â techniqueÂ . The Â planned Â techniqueÂ  created Â itÂ  attainable Â toÂ  scaleÂ  back Â range Â of Â switch Â of Â theÂ  biggest Â or Â secondÂ  major presentÂ  sectionÂ .Â  And itÂ willÂ  mechanicallyÂ  acclimatizeÂ  toÂ  weightÂ  circumstancesÂ  with Â variedÂ  power factors. Calculated switch woundedÂ area unit condensed toÂ regardingÂ  50% Â by theÂ planned technique.Â Â
Prediction of Layer Chicken Disease using Fuzzy Analytical Hierarcy Process
Authors: Muslihudin Muhammad , Wanti Risma , . Hardono , . Nurfaizal , K Shankar , M Ilayaraja , Maseleno Andino , . Fauzi , Rohmadi Mustofa Dwi , Masrur Muhammad , Mukodimah Siti
Published: April 2019

Chicken disease belong to the herpes group that often attacks poultry like laying hens. Various types of diseases that can attack such as marek, IB chicken, chicken NP, CA, EDS. Therefore it is necessary to be given a special vaccine for poultry that can anticipate the dominant diseases attacking poultry in particular chicken laying. So need a prediction model with the concept of fuzzy analytical hierarchy process. analytical hierarchy process is one of the methods in the decision-making system that uses several variables with a multilevel analysis process using criteria such as decreased egg production, cough, watery eyes, wings hanging down, a gray sprocket, legs paralyzed. From the test results obtained varied values with alternative results obtained: Marek 0.1487, IB chicken 0.3464, CA 0.1769, chicken NP 0.2407, EDS 0.0884. Then fuzzy analytical hierarcy process is good for predicting laying hens disease
Higher Education Selection using Simple Additive Weighting
Authors: Aminudin Nur , Huda Miftachul , Kilani Ahmad , Wan Embong Wan Hassan , Mohamed Ahmad Marzuki , Basiron Bushrah , Ihwani Siti Suhaila , Mohd Noor Sulaiman Shakib , Jasmi Kamarul Azmi , Safar Jimaain , L. Ivanova Natalie , Maseleno Andino , Triono Agus , . Nungsiati
Published: April 2019

The process of selecting a college should be based on the capabilities and needs of the community. When society is faced with a large selection of college criteria and most societies are confused about choosing the appropriate college for themselves and the job demands. From this it was made a decision support system aimed at helping the community to choose a college that suits the ability and demands of the work. Decision support system plays a role in helping people get the right recommendations in the selection of universities. This decision support system is also designed to help the community to choose a college that suits their needs so that the public is not confused because of the many criteria of universities faced by the community because the admin already has recommendations according to the needs of the community by using Simple Additive Weighting (SAW) method.
News recommendation system using machine learning
Authors: Rani Neha , Sudhir Pathak Sudhir
Published: April 2019

The forecasting of financial news is yet becoming the main issue to divide the new into different classes on the basis of present time series. Moreover, it might be utilized for predicting and analyzing the stock market for the particular industry. Thus, the new content is significantly important to influence market forecast report. In this paper, the financial news from four countries namely America, Australia, India and South Africa along with their stop words are consider. The words along with their weighted values are determined and then the neural network is trained. Here, artificial neural network is used for classifying the appropriate results for the given input data. At last the comparison of ANN with SVM is shown. Experiments show that the ANN classification provides high accuracy to predict the news than the SVM classifier.
Determination of the best quail eggs using simple additive weighting
Authors: Abadi Satria , Huda Miftachul , Azmi Jasmi Kamarul , Shakib Mohd. Noor Sulaiman , Safar Jimaain , Kilani Mohamed Ahmad , Hassan Wan Embong Wan , Marzuki Mohamad Ahmad , Hehsan Aminudin , Basiron Bushrah , Suhaila Ihwani Siti , Maseleno Andino , Muslihudin Muhamad , Satria Fiqih , Irawan Dedi , Hartati Sri
Published: April 2019

Eggs are livestock products contributed greatly to the achievement of the nutritional adequacy of the public; the egg is a food that is very good for children who are growing because it contains nutrients such as a complete protein, fat, vitamins and minerals that are easy to digest. One of the eggs are much in demand by children are quail eggs. The nutritional value of quail eggs is not less than the nutritional value of eggs containing 12.8% protein and 11.5% fat. Quail eggs are good quality will have good nutritional value anyway. To determine the quality of a good quail eggs will require an expert system. The method used in determining the quality of a good quail eggs using Simple Additive weighting method. The criteria in this research that egg size, style/color of the shell, the shell thickness, shell texture, shape and cleanliness of quail eggs. With the expert system is expected to assist farmers in determining the quail eggs quail egg quality so that the people can consume quail eggs that have good nutritional value. The results of this study showed an alternative ranking first in C with a value of 0.95, ranking second D with a value of 0.7208, ranking third E with a value of 0675, ranking the fourth A with a value of 0.4542 and ranking last in the B with a value of 0.4541.
Automatic detection of ovarian cancer based on improved DWT transformation
Authors: Rashid Sabreena , Kaur Rajdeep
Published: April 2019

Ovarian cancer sub-kinds are distinct pathologic individual with dissimilar prognostic and therapeutic suggestions. Histo-typing by pathologists has good reproducibility; therefore, occasional cases are challenging and require immuno-histo chemistry and sub-specialty discussion. Motivated by the need for more accurate and reproducible diagnosis and to facilitate pathologist’s work-flow, implement an au-tomated system for ovarian cancer classification and identification. The main problem discussed for detecting procedure fields: (i) the cancer detection on ultra sound image is not easy to classify on the basis of clustering or segmentation. It can involve the False Acceptance Rate and False Rejection Rate higher at the interval of time recognition from the knowledge base. (ii)The working accuracy rate is 90 to 95 of Normal SVM existing systems. Our technique is implemented by detection of the cancer stage accordingly workflow. We implement im-ages of cancer at two enlargement and extract features like a, color, text and shape data using digital image processing techniques. We ana-lyze the machine-learning algorithm and spatial domain algorithm used to extract the features in four phases: LL, HL, LH and HH. Extract the features used to dimension reduction and a SVM classification to divide the 5 ovarian cancer stages. The research paper represents, the details of our implementation and its validate on (Govt. hospital) clinically derived database of high-resolution diagnosis images. The new system attained a linear classification accuracy 98% when classifying un-seen tissues. The method has been implemented using simulation tool using MATLAB 2016a. The Ovarian Stages were then tested for the accuracy using transformation software. Testing consequences defined an accuracy of 94%, Specificity 0.99 and Sensitivity value is 0.9978 for MRI Medical Images respectively.
Clustering and multicasting scheme for fog computing based vehicular ad hoc network
Authors: Pal Singh Tejinder , Nitika Kapoor Er.
Published: April 2019

The vehicular adhoc network is the data oriented in network in which information should be passed with least delay. The vehicle adhoc network is the decentralized type of network in which vehicles to vehicle and vehicle to road side communication is possible. The Fog computing is the advance computing scheme to store small amount of data. The routing is the major issue of vehicular adhoc network due to high mobility of the vehicle nodes. In this research work, multicasting based routing scheme is proposed for path establishment from source to destination. In the proposed scheme root vehicles are selected for path establishment from source to destination. When the data will be received on the road side unit then k-mean clustering will be applied which divide data into clusters which define that either it can be saved on cloud or on fog server based on quantity of data. The performance of proposed scheme is testing in NS2 and proposed scheme performs well in terms of PDR and route lifetime
Improved DCFR protocol for path recovery in mobile ad-hoc networks
Authors: Kaur Rupinder , Singh Kang Sandeep
Published: April 2019

The mobile ad-hoc network is the decentralized type of network in which mobile nodes can move from one location to another. Due to random mobility of the mobile nodes route establishment, route maintenance is the major issues of mobile ad-hoc networks. This research paper, focus on the route establishment and route maintenance properties of mobile ad-hoc network. The DCFR protocol is the route establishment and route maintenance protocol in which broker route will be recovered on the basis of node connectivity. The node, which has maximum connectivity, is selected as the best node for route recovery in DCFR Protocol. In this research work, the DCFR protocol is further improved by adding buffer size parameter for route recovery which also maintains quality of service in the network. The proposed DCFR protocol simulation results perform well as compared to existing DCFR protocol in terms of certain parameters
Getting parents involved in child’s school: using attendance application system based on SMS gateway
Authors: Susilowati Tri , Ihsan Dacholfany M. , Aminin Sudirman , Ikhwan Afiful , Mohd. Nasir Badlihisham , Huda Miftachul , Prasetyo Adi , Maseleno Andino , Satria Fiqih , Hartati Sri , . Wulandari
Published: April 2019

Along with the development of communication technology, and information system, more and more also made the attendance system, and academic information. The development of a more modern absentee system with respect to the honesty side needs to be built as a substitute for manual absence using paper. Attendance system is at once can be a new standard on attendance system in Education environment. The choice of fingerprint attendance system based on communication technology in the form of SMS is because it is more practical, cheap, and efficient to convey information. Parents do not have to bother anymore come to school just to know the presence or absence of his son / daughter. In the implementation of this application, in the early stages of the user must register their identity by using the application program absenteeism built with PHP programming language, to further stored the absence data into the database My SQL which has integrated SMS Gateway through the SMS sending software that is Gammu. In addition with SMS Gateway technology, parents will be easier to obtain information on the presence of his son / daughter. From the student side, it is hoped that it will foster discipline attitude in time because indirectly this application will grow the mental attitude on time to the students, and it is expected that this application can fix any deficiencies in attendance application that has been implemented earlier.
Semantic image annotation using convolutional neural network and wordnet ontology
Authors: Saji Chacko Jaison , B Tulasi
Published: April 2019

Images are a major source of content on the web. The increase in mobile phones and digital cameras have led to huge amount of non-textual data being generated which is mostly images. Accurate annotation is critical for efficient image search and retrieval. Semantic image annotation refers to adding meaningful meta-data to an image which can be used to infer additional knowledge from an image. It enables users to perform complex queries and retrieve accurate image results. This paper proposes an image annotation technique that uses deep learning and semantic labeling. A convolutional neural network is used to classify images and the predicted class labels are mapped to semantic concepts. The results shows that combining semantic class labeling with image classification can help in polishing the results and finding common concepts and themes.
Smart Energy Systems: The Need to Incorporate Homeostatically Controlled Microgrids to the Electric Power Distribution Industry : An Electric Utilities’ Perspective
Authors: Yanine Fernando , Sanchez-Squella Antonio , Barrueto Aldo , Kumar Sahoo Sarat , M. Cordova Felisa
Published: April 2019

For no one is a secret that nowadays electric power distribution systems (EPDS) are being faced with a number of challenges and concerns, which emanate not so much from a shortage of energy supply but from environmental, infrastructural and operational issues. They are required to preserve stability and continuity of operations at any time no matter what, regardless of what may occur in the surroundings. This is the true measure of what sustainable energy systems (SES) are all about and homeostaticity of energy systems seeks just that: to bring about a rapid, effective and efficient state of equilibrium between energy supply and energy expenditure in electric power systems (EPS). The paper presents the theoretical groundwork and a brief description of the model for the operation of SES and their role in energy sustainability, supported by theoretical and empirical results. The concept of homeostaticity in EPDS is explained, along with its role in SES.
Smart Technological Learning Conceptual model
Authors: Sarma Cakula
Published: April 2019

Lifelong learning in one of most important aspects of nowdays educational system, which is understood as continuation of the previously acquired education and the enrichment of the professional skills according to the demands of the vocation in question. It is very important to figure out the most effective technological solutions and principal directions for implementing work-based learning strategies in the learning process.  New smart learning individually oriented methodology has been developed based on human individual perception for fast growing information and big data society.
An Encrypted Log File Keylogger System for Parental Control
Authors: S. Li L , M. Fauzee Z , Zamin N , Kamarudin N , A.Sabri N , S.Nik Ab Aziz N
Published: April 2019

Keystroke logging, often referred to as keylogger, keylogging or keyboard capturing, is the process of recording all the pressed keys on a keyboard autonomously so that the person who is using the keyboard is unaware that their actions on the computer are being monitored.  In the world of cyber-crime, keylogger tool has been used mostly for malicious purposes such as stealing personal information and credit card details. However, for ethical purposes, keylogger can be useful in terms of monitoring user’s activities without being noticed. For instance, parents can use keylogger to monitor their child’s activity on the web. The log file is used to store the recorded keystrokes.  However, current log files in keylogger are not encrypted, which can be easily hacked for malicious purposes. This paper proposes a new software based keylogger with log file encryption to increase the keylogging security towards Industrial Revolution 4.0.
Traffic Flow Modeling on Road Networks Using Cellular Automata Theory
Authors: Chechina A , Churbanova N , Trapeznikova M , Ermakov A , German M
Published: April 2019

The paper deals with mathematical modeling of traffic flows on urban road networks. The original model is based on the cellular automata theory and presents a generalization of Nagel-Schreckenberg model to a multilane case.Numerical realization of the model is represented in a form of the program package that consists of two modules: User Interface and Visualization module (for setting initial conditions and modelling parameters and visual representation of calculations) and Computation module (for calculations).Computations are carried out for each element of the road (i.e. T or X type intersection, straight road fragment) separately and in parallel, that allows performing calculations on various complex road networks. Different kinds of average characteristics (e.g. the capacity of the crossroad) can be also obtained using the program package.
Decision Support Systems on Complex Situation Governance Based On Scenario Approach
Authors: V. Chernov I , I. Makarenko D
Published: April 2019

Governance of modern situations arising in regional systems requires the development of distributed decision support systems in governance network. The paper proposes a strategic decision support scheme based on a combination of tools supporting the process of constructing multifactor situation models, and agreed models, taking into account different stakeholders’ opinions, scenario analysis tools for forecasting and searching for control actions as well as tools for monitoring situation change by factors. At an acceptable level of maturity of technologies of structuration and formalization of knowledge about the situation in the form of models, the means of supporting scenario analysis and synthesis of control activities on complex situations are critical.
Quasi-optimality under pseudo f statistic in clustering data
Authors: Hochin Teruhisa , Hayashi Yoshihiro , Nomiya Hiroki , U. Chowdhury Morshed
Published: April 2019

Pseudo F statistic is often used in deciding the number of clusters. A set of clusters having the largest pseudo F value is selected as the op-timum set of clusters. This paper proposes the quasi-optimum set of clusters, whose pseudo F value is larger than those of other sets of clusters, whose numbers are around the number of clusters in the quasi-optimum set. The before and behind (BB) difference of pseudo F values is proposed to find the number of clusters in the quasi-optimum set. The relative BB difference of pseudo F values, which is the ratio of the BB difference of pseudo F values to the pseudo F value itself, is also proposed to find it when the pseudo F value severely varies. This paper shows some examples to demonstrate that the BB differences of pseudo F values and the relative ones work well in finding qua-si-optimum sets of clusters.
Non-orthogonal multiple access: basic interference management technique
Authors: Khan Rabia , Nalin K. Jayakod Dushantha , Chen Bin
Published: April 2019

Non Orthogonal Multiple Access (NOMA) is a technique that offers spectral efficiency, Quality of Service (QoS), user fairness, low latency, high data rate, and overall better performance as compared to Orthogonal Multiple Access (OMA). The main feature of NOMA is the efficient utilization of spectrum due to increasing demand of data rate. We have introduced a new technique known as MNOMA (Modulation based NOMA) which will help in reducing the interference and complexity of signals decoding, not only in uplink but downlink as well. We have achieved the target of proposed technique by working on superposition coding (SC) of the system. In NOMA interference between users is certain due to removal of orthogonality in spectrum. The problem of interference has been tackled with superposition coding and a number of SIC’s (Successive Interference Cancellation) performed on the receiver's end. With MNOMA technique we have tried to reduce the complexity of system by integrating the basic orthogonality in the transmitter instead of spectrum. In this paper, we have shown the reduced expression of data rate for the proposed technique, which shows reduced complexity of the system in terms of SIC, Symbol Error Rate (SER), and better data rate of the proposed technique as compare to conventional OMA.
Emotional Classification of Acoustic Information With Optimal Feature Subset Selection Methods
Authors: Swarna Kuchibhotla Dr , Niranjan M.S.R Mr
Published: April 2019

This paper mainly focuses on classification of various Acoustic emotional corpora with frequency domain features using feature subset selection methods. The emotional speech samples are classified into neutral,  happy, fear , anger,  disgust and sad  states by using properties of statistics  of spectral features estimated from Berlin and Spanish emotional utterances. The Sequential Forward Selection(SFS) and Sequential Floating Forward Selection(SFFS)feature subset selection algorithms are  for extracting more informative features. The number of speech emotional samples available for training is smaller than that of the number of features extracted from the speech sample in both Berlin and Spanish corpora which is called curse of dimensionality. Because of this  feature vector of high dimensionality the efficiency of the classifier decreases and at the same time the computational time also increases. For additional  improvement in the efficiency of the classifier  a subset of  features which are optimal is needed and is obtained by using feature subset selection methods. This will enhances the performance of the system with high efficiency and lower computation time. The classifier used in this work is the standard K Nearest Neighbour (KNN) Classifier. Experimental evaluation   proved  that the performance of the classifier is enhanced with SFFS because it vanishes the nesting effect suffered by SFS. The results also showed that an optimal feature subset is a better choice for classification rather than full feature set.