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31,456 Article Results

The saturation of population fitness as a stopping criterion in genetic algorithm

10.11591/ijece.v9i5.pp4130-4137
Foo Fong Yeng , Soo Kum Yoke , Azrina Suhaimi
Genetic Algorithm is an algorithm imitating the natural evolution process in solving optimization problems. All feasible (candidate) solutions would be encoded into chromosomes and undergo the execution of genetic operators in evolution. The evolution itself is a process searching for optimum solution. The searching would stop when a stopping criterion is met. Then, the fittest chromosome of last generation is declared as the optimum solution. However, this optimum solution might be a local optimum or a global optimum solution. Hence, an appropriate stopping criterion is important such that the search is not ended before a global optimum solution is found. In this paper, saturation of population fitness is proposed as a stopping criterion for ending the search. The proposed stopping criteria was compared with conventional stopping criterion, fittest chromosomes repetition, under various parameters setting. The results show that the performance of proposed stopping criterion is superior as compared to the conventional stopping criterion.
Volume: 9
Issue: 5
Page: 4130-4137
Publish at: 2019-10-01

Microstrip multi-stopband filter based on tree fractal slotted resonator

10.11591/ijece.v9i5.pp3657-3663
Manju Bhaskar , Thomaskutty Mathew
This paper presents the design and development of a new microstrip multi-stopband filter based on tree fractal slotted resonator. A single square patch with tree fractal slots of different iterations are employed for realizing dual stopband and tri-stopband filters. The tree fractal slotted resonators are generated from conventional square patch using an iterative tree fractal generator method. First, second and third level iterations of the tree fractal slot resonator are used to design dual and tri-stopband filters respectively. The first level iteration introduced for the tree fractal slot realizes dual bands at 2.64 GHz and 3.61 GHz while the second level iteration provides better stopband rejection and insertion loss at 2.57 GHz and 3.56 GHz. The tri-stopband filter generates three resonance frequencies at 1.53 GHz, 2.53 GHz and 3.54 GHz at third level iteration. By varying the slot length and width of the tree fractal slot, the resonant frequencies can be adjusted and stopbands of the proposed filter can be tuned for the desired unwanted frequency to be rejected. The proposed narrowband filters finds application in removing the interference of GPS and Wi-Max narrowband signals from the allotted bands of other wireless communication systems
Volume: 9
Issue: 5
Page: 3657-3663
Publish at: 2019-10-01

Manifesting a mobile application on safety which ascertains women salus in Bangladesh

10.11591/ijece.v9i5.pp4355-4363
Md. Elias Hossain , Md. Wahidur Rahman , Md. Tarequl Islam , Md. Selim Hossain
This paper reflects on the indemnity of women in our society. The proposed model ensures the embodiment of a mobile application. The algorithm, we developed for this model focuses the safety issues which is applicable to both inside as well as outside of the house for the women in Bangladesh. The solution of this problems can be done through some interrelated features such as i) SOS button pressing which ensures automatic calling, instant location tracking system through GPS of the phone and sending tracked location to all trusted numbers, automatically secrete video recording system ii) voice command detection which assures exact same features as SOS button pressing iii) phone shaking features serve user instant immunity by calling a trusted number. This research also assures experimented data analysis at Dhaka city based on respond time, the time it takes to arrive the SMS and Phone call and current location of the victim. Also do a short comparison among the most popular safety related mobile applications.
Volume: 9
Issue: 5
Page: 4355-4363
Publish at: 2019-10-01

Biological landmark Vs quasi-landmarks for 3D face recognition and gender classification

10.11591/ijece.v9i5.pp4069-4076
Hawraa H. Abbas , Ammar A. Altameemi , Hameed R. Farhan
Face recognition and gender classification are vital topics in the field of computer graphic and pattern recognition. We utilized ideas from two growing ideas in computer vision, which are biological landmarks and quasi-landmarks (dense mesh) to propose a novel approach to compare their performance in face recognition and gender classification. The experimental work is conducted on FRRGv2 dataset and acquired 98% and 94% face recognition accuracies using the quasi and biological landmarks respectively. The gender classification accuracies are 92% for quasi-landmarks and 90% for biological landmarks.
Volume: 9
Issue: 5
Page: 4069-4076
Publish at: 2019-10-01

Handwritten digits recognition with decision tree classification: a machine learning approach

10.11591/ijece.v9i5.pp4446-4451
Tsehay Admassu Assegie , Pramod Sekharan Nair
Handwritten digits recognition is an area of machine learning, in which a machine is trained to identify handwritten digits. One method of achieving this is with decision tree classification model. A decision tree classification is a machine learning approach that uses the predefined labels from the past known sets to determine or predict the classes of the future data sets where the class labels are unknown. In this paper we have used the standard kaggle digits dataset for recognition of handwritten digits using a decision tree classification approach. And we have evaluated the accuracy of the model against each digit from 0 to 9.
Volume: 9
Issue: 5
Page: 4446-4451
Publish at: 2019-10-01

Trust model genetic node recovery based on cloud theory for underwater acoustic sensor network

10.11591/ijece.v9i5.pp3759-3771
Buddesab T , Thriveni J , Venugopal K R
Underwater Acoustic Sensor Networks [UASNs] are becoming a very growing research topic in the field of WSNs. UASNs are harmful by many attacks such as Jamming attacks at the physical layer, Collision attacks at the data link layer and Dos attacks at the network layer. UASNs has a unique characteristic such as unreliable communication, mobility, and computation of underwater sensor network. Because of this the traditional security mechanism, e.g. cryptographic, encryption, authorization and authentications are not suitable for UASNs. Many trust mechanisms of TWSNs [Terrestrial Wireless Sensor Networks] had proposed to UASNs and failed to provide security for UASNs environment, due to dynamic network structure and weak link connection between sensors. In this paper, a novel Trust Model Genetic Algorithm based on Cloud Theory [TMC] for UASNs has been proposed. The TMC-GA suggested a genetic node recovery algorithm to improve the TMC network in terms of better network lifetime, residual energy and total energy consumption. Also ensures that sensor nodes are participating in the rerouting in the routing discovery and performs well in terms of successful packet delivery. Simulation result provides that the proposed TMC-Genetic node recovery algorithm outperforms compared to other related works in terms of the number of hops, end-to-end delay, total energy consumption, residual energy, routing overhead, throughput and network lifetime.
Volume: 9
Issue: 5
Page: 3759-3771
Publish at: 2019-10-01

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
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