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29,905 Article Results

Framework to predict NPA/Willful defaults in corporate loans: a big data approach

10.11591/ijece.v9i5.pp3786-3797
Girija Attigeri , Manohara Pai M M , Radhika M Pai
Growth and development of the economy is dependent on the banking system. Bad loans which are Non-Performing Assets (NPA) are the measure for assessing the financial health of the bank. It is very important to control NPA as it affects the profitability, and deteriorates the quality of assets of the bank. It is observed that there is a significant rise in the number of willful defaulters. Hence systematic identification, awareness and assessment of parameters is essential for early prediction of willful default behavior. The main objective of the paper is to identify exhaustive list of parameters essential for predicting whether the loan will become NPA and thereby willful default. This process includes understanding of existing system to check NPAs and identifying the critical parameters. Also propose a framework for NPA/Willful default identification. The framework classifies the data comprising of structured and unstructured parameters as NPA/Willful default or not. In order to select the best classification model in the framework an experimentation is conducted on loan dataset on big data platform. Since the loan data is structured, unstructured component is incorporated by generating synthetic data. The results indicate that neural network model gives best accuracy and hence considered in the framework.
Volume: 9
Issue: 5
Page: 3786-3797
Publish at: 2019-10-01

An efficient computational approach to balance the trade-off between image forensics and perceptual image quality

10.11591/ijece.v9i5.pp3474-3479
Shashidhar TM , K B Ramesh
The increasing trends of image processing applications play a very crucial role in the modern-day information propagation with the ease of cost effectiveness. As image transmission or broadcasting is the simplest form communication which determines easy, fastest and effective way of network resource utilization, thereby since past one decade it has gained significant attention among various research communities. As most of the image attributes often contains visual entities corresponding to any individual, hence, exploration and forging of such attributes with malicious intention often leads to social and personal life violation and also causes intellectual property right violation when social media, matrimonial and business applications are concerned. Although an extensive research effort endeavored pertaining to image forensics in the past, but existing techniques lack effectiveness towards maintaining equilibrium in between both image forensics and image quality assessment performances from computational viewpoint. Addressing this limitation associated with the existing system, this proposed study has come up with a novel solution which achieves higher degree of image forensics without compromising the visual perception of an image. The study formulates an intelligent empirical framework which determines cost-effective authentication of an image object from both complexity and quality viewpoint. Finally, the study also presented a numerical simulation outcome to ensure the performance efficiency of the system.
Volume: 9
Issue: 5
Page: 3474-3479
Publish at: 2019-10-01

Priority Based Data Transmission for WBAN

10.11591/ijece.v9i5.pp3671-3677
Jay Manalastas Ventura , Arnel Fajardo , Ruji Medina
Wireless Body Area Sensor Network (WBASN) or Wireless Body Area Network (WBAN) is a growing field in healthcare applications. It enables remote monitoring of patient’s physiological data through wireless communication. It is composed of sensor network which collects physiological data from the patient. There are several issues concerning WBAN such as security, power, routing protocol to address QoS metrics (reliability, end-to-end delay, and energy efficiency), etc. The focus of the study is the issue on different QoS metrics. There were several QoS aware routing protocol that has been proposed which implements multiple queues for different types of data. However, one issue on multiple queue system is starvation, end-to-end delay, and reliability. The study proposed an efficient priority queue based data transmission that improves the end-to-end delay, reliability, and queuing delay of QoS aware routing protocol.
Volume: 9
Issue: 5
Page: 3671-3677
Publish at: 2019-10-01

Implementation of FOAF, AIISO and DOAP ontologies for creating an academic community network using semantic frameworks

10.11591/ijece.v9i5.pp4302-4310
Himanshu Ahuja , Sivakumar R
Web 2.0 delivers the information which is then displayed in human readable content, omitting the crucial information which can be drawn from the data by the applications. Web 3.0 or semantic web is an extension to the current web, with an ambition to determine the drawbacks of the current web. The semantic web has already proven its influence in several communities around the globe, such as social media, music industry, healthcare domain, online blogs or articles, etc.; Among the several tools and technologies, ontologies or vocabularies are the foundation pillar for the semantic web. In this paper, the developed system aims at improving the collaboration and academic relations among staff which is directly related to our education community by providing a better networking platform which lets the agents discuss their achievements, titles, domain interests, and various other activities. Results have been analyzed to show how new facts, information can be implied from the presented knowledge of several agents and help generate a relationship graph by utilizing various semantic tools. The system discussed in this paper processes all the information in a format which can be understood by both humans and the machines, to interpret the underlying meaning about it and provide effective results.
Volume: 9
Issue: 5
Page: 4302-4310
Publish at: 2019-10-01

Modified phase locked loop for grid connected single phase inverter

10.11591/ijece.v9i5.pp3934-3943
Eyad Radwan , Khalil Salih , Emad Awada , Mutasim Nour
Connecting a single-phase or three-phase inverter to the grid in distributed generation applications requires synchronization with the grid. Synchronization of an inverter-connected distributed generation units in its basic form necessitates accurate information about the frequency and phase angle of the utility grid. Phase Locked Loop (PLL) circuit is usually used for the purpose of synchronization. However, deviation in the grid frequency from nominal value will cause errors in the PLL estimated outputs, and that’s a major drawback. Moreover, if the grid is heavily distorted with low order harmonics the estimation of the grid phase angle deteriorates resulting in higher oscillations (errors) appearing in the synchronization voltage signals. This paper proposes a modified time delay PLL (MTDPLL) technique that continuously updates a variable time delay unit to keep track of the variation in the grid frequency. The MTDPLL is implemented along a Multi-Harmonic Decoupling Cell (MHDC) to overcome the effects of distortion caused by gird lower order harmonics. The performance of the proposed MTDPLL is verified by simulation and compared in terms of performance and accuracy with recent PLL techniques.
Volume: 9
Issue: 5
Page: 3934-3943
Publish at: 2019-10-01

Cloud computing adoption reference model

10.11591/ijeecs.v16.i1.pp395-400
Wan Abdul Rahim Wan Mohd Isa , Ahmad Iqbal Hakim Suhaimi , Nurulhuda Noordin , Afdallyna Fathiyah Harun , Juhaida Ismail , Rosshidayu Awang Teh
This paper presents a study to conceptualize a cloud computing adoption reference model. The case study on the cloud computing adoption was done in one local public university in Malaysia.  The case study was conducted to understand in-depth and real context phenomenon by investigating the influencing factors of cloud computing adoption. The main objective of this study is to design a cloud computing adoption reference model. This study applied Technology-Organizational-Environmental (TOE) Framework by Tornatzky & Fleischer and Diffusion of Innovation by Rogers as the theoretical background of the Cloud Computing Adoption Reference. Ten interviews were conducted with key informants. The theme pattern analysis of data were done by using qualitative computer programs, Atlas.ti. The findings are shown in summarize patterns that supports the conceptualization of cloud computing adoption reference model. Future work include the adaption of cloud computing adoption reference model specifically for the niche area of mobile computing.
Volume: 16
Issue: 1
Page: 395-400
Publish at: 2019-10-01

An overview of virtual machine live migration techniques

10.11591/ijece.v9i5.pp4433-4440
Artan Mazrekaj , Shkelzen Nuza , Mimoza Zatriqi , Vlera Alimehaj
In a cloud computing the live migration of virtual machines shows a process of moving a running virtual machine from source physical machine to the destination, considering the CPU, memory, network, and storage states. Various performance metrics are tackled such as, downtime, total migration time, performance degradation, and amount of migrated data, which are affected when a virtual machine is migrated. This paper presents an overview and understanding of virtual machine live migration techniques, of the different works in literature that consider this issue, which might impact the work of professionals and researchers to further explore the challenges and provide optimal solutions.
Volume: 9
Issue: 5
Page: 4433-4440
Publish at: 2019-10-01

Reduction of the number of faults caused by lightning for transmission line

10.11591/ijece.v9i5.pp3366-3374
Dinh Chung Phan
In this paper, author proposed an algorithm to determine method which is used to reduce the fault number caused by lightning on a transmission line. The algorithm is developed based on three methods including increase in the insulator string length, surge arrester installation, and surge arrester installation in combination with increase in the insulator string length. The output of algorithm is the proposed method which makes the number of faults caused by lightning satisfy the requirement and its investment is the cheapest in them. Based on this algorithm, the reasonable method (the number of tower positions needing to improve) to reduce the number of lightning caused faults of the transmission line can determine if we know the ratio of the required number lightning caused faults to the current value. This algorithm is applied to a transmission line to propose an improving method so that the fault number satisfies the requirement. This algorithm is implemented to a 220kV transmission line. The calculation results show the reasonable method and it also indicates in detail which towers should install surge arrester, which towers should increase the insulator string length.
Volume: 9
Issue: 5
Page: 3366-3374
Publish at: 2019-10-01

Performance evaluation of different classification techniques using different datasets

10.11591/ijece.v9i5.pp3584-3590
Abdulkadir Özdemir , Uğur Yavuz , Fares Abdulhafidh Dael
Nowadays data mining become one of the technologies that paly major effect on business intelligence. However, to be able to use the data mining outcome the user should go through many process such as classified data. Classification of data is processing data and organize them in specific categorize to be use in most effective and efficient use. In data mining one technique is not applicable to be applied to all the datasets. This paper showing the difference result of applying different techniques on the same data. This paper evaluates the performance of different classification techniques using different datasets. In this study four data classification techniques have chosen. They are as follow, BayesNet, NaiveBayes, Multilayer perceptron and J48. The selected data classification techniques performance tested under two parameters, the time taken to build the model of the dataset and the percentage of accuracy to classify the dataset in the correct classification. The experiments are carried out using Weka 3.8 software. The results in the paper demonstrate that the efficiency of Multilayer Perceptron classifier in overall the best accuracy performance to classify the instances, and NaiveBayes classifiers were the worst outcome of accuracy to classifying the instance for each dataset.
Volume: 9
Issue: 5
Page: 3584-3590
Publish at: 2019-10-01

Detection of electrocardiogram QRS complex based on modified adaptive threshold

10.11591/ijece.v9i5.pp3512-3521
Ehab AbdulRazzaq Hussein , Ali Shaban Hassooni , Hilal Al-Libawy
It is essential for medical diagnoses to analyze Electrocardiogram (ECG signal). The core of this analysis is to detect the QRS complex. A modified approach is suggested in this work for QRS detection of ECG signals using existing database of arrhythmias. The proposed approach starts with   the same steps of previous approaches by filtering the ECG. The filtered signal is then fed to a differentiator to enhance the signal. The modified adaptive threshold method which is suggested in this work, is used to detect QRS complex. This method uses a new approach for adapting threshold level, which is based on statistical analysis of the signal. Forty-eight records from an existing arrhythmia database have been tested using the modified method. The result of the proposed method shows the high performance metrics with sensitivity of 99.62% and a positive predictivity of 99.88% for QRS complex detection.
Volume: 9
Issue: 5
Page: 3512-3521
Publish at: 2019-10-01

A cost-effective 2-tier security paradigm to safeguard cloud data with faster authentication

10.11591/ijece.v9i5.pp3833-3842
Veena R.S , Ramachandra V. Pujeri , Indiramma M
The recent technological advancement has taken cloud computing (CC) infrastructure to a significant level where the increasing level of research interest laid upon cost-effective storage management.  Owing to the potential distributed and pervasive storage facility, it lacks efficiency towards fully preserving the integrity of user data attributes. Thereby, the collaborative sharing of user data leads to a situation which opens up various forms of security loop-holes. In the past various forms of security protocols are witnessed which have attempted to solve this similar issue with cryptographic solutions but at the same time lacks sustainability and robustness from a computational perspective. Thereby, the study introduces a 2-tier framework which offers higher-degree of access control along with Virtual Machine (VM) storage security. The study basically optimizes the performance of the model by speeding up the authentication process. The performance validation of the system has been done with respect to conventional encryption standards. The outcome obtained demonstrate that the proposed solution outperforms the existing security standards in terms of processing time, time to generate a secret key and key size for encryption.
Volume: 9
Issue: 5
Page: 3833-3842
Publish at: 2019-10-01

Student risk identification learning model using machine learning approach

10.11591/ijece.v9i5.pp3872-3879
Susheelamma K. H. , K. M. Ravikumar
Several challenges are associated with online based learning systems, the most important of which is the lack of student motivation in various course materials and for various course activities. Further, it is important to identify student who are at risk of failing to complete the course on time. The existing models applied machine learning approach for solving it. However, these models are not efficient as they are trained using legacy data and also failed to address imbalanced data issues for both training and testing the classification approach. Further, they are not efficient for classifying new courses. For overcoming these research challenges, this work presented a novel design by training the learning model for identifying risk using current courses. Further, we present an XGBoost classification algorithm that can classify risk for new courses. Experiments are conducted to evaluate performance of proposed model. The outcome shows the proposed model attain significant performance over stat-of-art model in terms of ROC, F-measure, Precision and Recall.
Volume: 9
Issue: 5
Page: 3872-3879
Publish at: 2019-10-01

Novel model for boosting security strength and energy efficiency in internet-of-things using multi-staged game

10.11591/ijece.v9i5.pp4326-4335
Bhagyashree Ambore , Suresh L
Security as well as energy efficiency is one of the most inevitable and challenging problems when it comes it large scale network deployment like INternet-of-Things (IoT). After reviewing existing research work on IoT, it was found that there are discrete set of solution for security as well as for energy. However, there is little research work that has jointly investigated both the problems with respect to IoT. Apart from this, there are also various form of attacks that cost energy of sensors that constitutes core physical devices in IoT. Therefore, these manuscripts present a novel idea for identifying and resisting the security breach within an IoT system ensuring energy efficiency too. Harnessing the modelling capability of game-theory, the proposed system offers a joint solution towards these problems. The simulated outcome of the study is found to offer balance performance for better energy efficiency and robust threat mitigation capability when compared with existing approaches.
Volume: 9
Issue: 5
Page: 4326-4335
Publish at: 2019-10-01

Design and implementation of the subsystem subject to emission of multicomponent high-frequency signals to ensure its reliability

10.11591/ijece.v9i5.pp4204-4216
Milad Daneshvar , Naser Parhizgar , Homayoon Oraizi
Telecommunication systems, especially digital ones, are mostly known to be immune to noise given their extensive range of applications. This study aimed to investigate the methods and tools used for the analysis of multicomponent signals input to high-frequency digital subsystems, including the analysis of changes in its electrical behavior. This research mainly focuses on analyzing a high-frequency telecommunication subsystem, recording the results, investigating the system behavior against signals with different amplitudes and phases, detecting the received signals, and measuring the phase differences. The study extended the mono-component signals to multi-component signals and accurately extracted the statistical signal specifications using analytic signals in the time-frequency domain. To this end, a method was proposed based on the switch matrix to relate the different components and parameters, and also a mathematical model based on the state-space equations was employed to evaluate the nonlinear system modes. Given that the decoupling of measurement parameters is a problem to be tackled from multiple aspects, the costs and test durations were also taken into calculations in addition to considering all the detection methods for interference signals, reliability and time under test.
Volume: 9
Issue: 5
Page: 4204-4216
Publish at: 2019-10-01

A new method for voice signal features creation

10.11591/ijece.v9i5.pp4092-4098
Majed O. Al-Dwairi , Amjad Y. Hendi , Mohamed S. Soliman , Ziad A. A. AlQadi
Digital audio is one of the most important types of data at present. It is used in several applications, such as human knowledge and many security and banking applications. A digital voice signal is usually of a large size where the acoustic signal consists of a set of values distributed in one column (one channel) (mono signal) or distributed in two columns (two channels) (stereo signal), these values usually are the results of sampling and quantization of the original analogue voice signal. In this paper we will introduce a method which can be used to create a signature or key, which can be used later to identify or recognize the wave file. The proposed method will be implemented and tested to show the accuracy and flexibility of this method.
Volume: 9
Issue: 5
Page: 4092-4098
Publish at: 2019-10-01
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