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Performance analysis on telecommunication companies in malaysia with TOPSIS model

10.11591/ijeecs.v13.i2.pp744-751
Lam Weng Hoe , Lam Weng Siew , Liew Kah Fai
Emergence of telecommunication companies is springing up due to the high demand from the consumers. The invention of telecommunication has made the world more knowledgeable as information can be transmitted easily. Based on the past studies, telecommunication is not commonly investigated especially in financial management field. Thereore, this study aims to propose a conceptual framework to evaluate, compare and rank the financial performance of the listed telecommunication companies in Malaysia using TOPSIS model. Financial ratios are employed to examine the financial performance of the telecommunication companies. The data of this study consists of DIGI, MAXIS, AXIATA and TM which are listed telecommunication companies in Malaysia stock market. The results of this study show that DIGI achieves the first ranking, followed by MAXIS, AXIATA and TM within the study period of year 2011-2015. This study is significant because it helps to evaluate, compare and rank the financial performance of the listed telecommunication companies in Malaysia with the proposed conceptual framework based on TOPSIS model.
Volume: 13
Issue: 2
Page: 744-751
Publish at: 2019-02-01

A review on various optimization techniques of resource provisioning in cloud computing

10.11591/ijece.v9i1.pp629-634
K. Sumalatha , M. S. Anbarasi
Cloud computing is the provision of IT resources (IaaS) on-demand using a pay as you go model over the internet.It is a broad and deep platform that helps customers builds sophisticated, scalable applications. To get the full benefits, research on a wide range of topics is needed. While resource over-provisioning can cost users more than necessary, resource under provisioning hurts the application performance. The cost effectiveness of cloud computing highly depends on how well the customer can optimize the cost of renting resources (VMs) from cloud providers. The issue of resource provisioning optimization from cloud-consumer potential is a complicated optimization issue, which includes much uncertainty parameters. There is a much research avenue available for solving this problem as it is in the real-world. Here, in this paper we provide details about various optimization techniques for resource provisioning.
Volume: 9
Issue: 1
Page: 629-634
Publish at: 2019-02-01

Efficient energy, cost reduction, and QoS based routing protocol for wireless sensor networks

10.11591/ijece.v9i1.pp496-504
Ghassan Samara , Mohammad Aljaidi
Recent developments and widespread in wireless sensor network have led to many routing protocols, many of these protocols consider the efficiency of energy as the ultimate factor to maximize the WSN lifetime. The quality of Service (QoS) requirements for different applications of wireless sensor networks has posed additional challenges. Imaging and data transmission needs both QoS aware routing and energy to ensure the efficient use of sensors. In this paper, we propose an Efficient, Energy-Aware, Least Cost, (ECQSR) quality of service routing protocol for sensor networks which can run efficiently with best-effort traffic processing. The protocol aims to maximize the lifetime of the network out of balancing energy consumption across multiple nodes, by using the concept of service differentiation, finding lower cost by finding the shortest path using nearest neighbor algorithm (NN), also put certain constraints on the delay of the path for real-time data from where link cost that captures energy nodes reserve, energy of the transmission, error rate and other parameters. The results show that the proposed protocol improves the network lifetime and low power consumption.
Volume: 9
Issue: 1
Page: 496-504
Publish at: 2019-02-01

A dynamic K-means clustering for data mining

10.11591/ijeecs.v13.i2.pp521-526
Md. Zakir Hossain , Md.Nasim Akhtar , R.B. Ahmad , Mostafijur Rahman
Data mining is the process of finding structure of data from large data sets. With this process, the decision makers can make a particular decision for further development of the real-world problems. Several data clusteringtechniques are used in data mining for finding a specific pattern of data. The K-means method isone of the familiar clustering techniques for clustering large data sets.  The K-means clustering method partitions the data set based on the assumption that the number of clusters are fixed.The main problem of this method is that if the number of clusters is to be chosen small then there is a higher probability of adding dissimilar items into the same group. On the other hand, if the number of clusters is chosen to be high, then there is a higher chance of adding similar items in the different groups. In this paper, we address this issue by proposing a new K-Means clustering algorithm. The proposed method performs data clustering dynamically. The proposed method initially calculates a threshold value as a centroid of K-Means and based on this value the number of clusters are formed. At each iteration of K-Means, if the Euclidian distance between two points is less than or equal to the threshold value, then these two data points will be in the same group. Otherwise, the proposed method will create a new cluster with the dissimilar data point. The results show that the proposed method outperforms the original K-Means method.
Volume: 13
Issue: 2
Page: 521-526
Publish at: 2019-02-01

Robust speaker verification in band-localized noise conditions

10.11591/ijeecs.v13.i2.pp499-506
Ali O. Abid Noor
This research paper presents a robust method for speaker verification in noisy environments. The noise is assumed to contaminate certain parts of the voice’s frequency spectrum. Therefore, the verification method is based on splitting the noisy speech into subsidiary bands then using a threshold to sense the existence of noise in a specific part of the spectrum, hence activating an adaptive filter in that part to track changes in noise’s characteristics and remove it. The decomposition is achieved using low complexity quadrature mirror filters QMF in three levels thus achieving four bands in a non-uniform that resembles human hearing perceptual. Speaker recognition is based on vector quantization VQ or template matching technique. Features are extracted from speaker’s voice using the normalized power in a similar way to the Mel-frequency cepstral coefficients. The performance of the proposed system is evaluated using 60 speakers subjected to five levels of signal to noise ratio SNR using total success rate TSR, false acceptance rate FAR, false rejection rate FRR and equal error rate. The proposed method showed higher recognition accuracy than existing methods in severe noise conditions.
Volume: 13
Issue: 2
Page: 499-506
Publish at: 2019-02-01

Energy efficiency in virtual machines allocation for cloud data centers with lottery algorithm

10.11591/ijece.v9i1.pp546-553
Mehran Tarahomi , Mohammad Izadi
Energy usage of data centers is a challenging and complex issue because computing applications and data are growing so quickly that increasingly larger servers and disks are needed to process them fast enough within the required time period. In the past few years, many approaches to virtual machine placement have been proposed. This study proposes a new approach for virtual machine allocation to physical hosts. Either minimizes the physical hosts and avoids the SLA violation. The proposed method in comparison to the other algorithms achieves better results.
Volume: 9
Issue: 1
Page: 546-553
Publish at: 2019-02-01

Improvement of binarization performance using local otsu thresholding

10.11591/ijece.v9i1.pp264-272
Khairun Saddami , Khairul Munadi , Yuwaldi Away , Fitri Arnia
Ancient document usually contains multiple noises such as uneven-background, show-through, water-spilling, spots, and blur text. The noise will affect the binarization process. Binarization is an extremely important process in image processing, especially for character recognition. This paper presents an improvement to Nina binarization technique. Improvements were achieved by reducing processing steps and replacing median filtering by Wiener filtering. First, the document background was approximated by using Wiener filter, and then image subtraction was applied. Furthermore, the manuscript contrast was adjusted by mapping intensity of image value using intensity transformation method. Next, the local Otsu thresholding was applied. For removing spotting noise, we applied labeled connected component. The proposed method had been testing on H-DIBCO 2014 and degraded Jawi handwritten ancient documents. It performed better regarding recall and precision values, as compared to Otsu, Niblack, Sauvola, Lu, Su, and Nina, especially in the documents with show-through, water-spilling and combination noises.
Volume: 9
Issue: 1
Page: 264-272
Publish at: 2019-02-01

Business intelligence analytics using sentiment analysis-a survey

10.11591/ijece.v9i1.pp613-620
Prakash P. Rokade , Aruna Kumari D
Sentiment analysis (SA) is the study and analysis of sentiments, appraisals and impressions by people about entities, person, happening, topics and services. SA uses text analysis techniques and natural language processing methods to locate and extract information from big data. As most of the people are networked themselves through social websites, they use to express their sentiments through these websites.These sentiments are proved fruitful to an individual, business, government for making decisions. The impressions posted on different available sources are being used by organization to know the market mood about the services they are providing. Analyzing huge moods expressed with different features, style have raised challenge for users. This paper focuses on understanding the fundamentals of sentiment analysis, the techniques used for sentiment extraction and analysis. These techniques are then compared for accuracy, advantages and limitations. Based on the accuracy for expexted approach, we may use the suitable technique.
Volume: 9
Issue: 1
Page: 613-620
Publish at: 2019-02-01

Radial dynamics of electrons in two-section linear accelerator

10.11591/ijece.v9i1.pp215-220
Aleksandr Nikolaevich Filatov , Vladimir Kuz'mich Shilov
This article discusses possibility of harness wiring with the use of focusing system of high frequency eigenfields of accelerating resonators in standing wave linear accelerators on the basis of biperiodic slowing systems. The scopes of business activities and specificity of existing engineering processes applied in industry, especially in chemistry and metallurgy, require for special measures on environmental protection. At present electron linear accelerators operating in pulse mode are used for application purposes. Such accelerators can be characterized by sufficient beam power for efficient industrial use and for environmental protection. The results of numerical analysis of electron dynamics in two-section accelerator upon various initial conditions are presented. The obtained results are applied for development of actual accelerator, calculated and experimental data are given. The performed experimental study confirmed possibility of development of standing wave linear accelerator without external magnetic focusing system with output beam diameter of not higher than . The results of calculations of beam dynamics are experimentally verified.
Volume: 9
Issue: 1
Page: 215-220
Publish at: 2019-02-01

Design and analysis of routing protocol for cognitive radio ad hoc networks in Heterogeneous Environment

10.11591/ijece.v9i1.pp341-351
Hassan Al-mahdi , Yasser Fouad
Multi-hop routing protocol in cognitive radio mobile ad hoc networks (CRMANETs) is a critical issue. Furthermore, the routing metric used in multi-hop CRMANETs should reflect the bands availability, the links quality, the PU activities and quality of service (QoS) requirements of SUs. For the best of our knowledge, many of researchers investigated the performance of the different routing protocols in a homogeneous environment only. In this paper, we propose a heterogeneous cognitive radio routing protocol (HCR) operates in heterogeneous environment (i.e. the route from source to destination utilize the licensed and unlicensed spectrum bands). The proposed routing protocol is carefully developed to make a tradeoff between the channel diversity of the routing path along with the CRMANETs throughput. Using simulations, we discuss the performance of the proposed HCR routing protocol and compare it with the AODV routing protocol using a discrete-event simulation which we developed using JAVA platform.
Volume: 9
Issue: 1
Page: 341-351
Publish at: 2019-02-01

A transient current based micro-grid connected power system protection scheme using wavelet approach

10.11591/ijece.v9i1.pp14-22
S. Chandra Shekar , G.Ravi Kumar , S.V.N.L Lalitha
Micro-grids comprise Distributed Energy Resources (DER’s) with low voltage distribution networks having controllable loads those can operate with different voltage levels are connected to the micro-grid and operated in grid mode or islanding mode in a coordinated way of control. DER’s provides clear environment-economical benefits for society and consumer utilities. But their development poses great technical challenges mainly protection of main and micro grid. Protection scheme must have to respond to both the main grid and micro-grid faults. If the fault is occurs on main grid, the response must isolate the DER’s from the main grid rapidly to protect the system loads. If the fault ocuurs within the micro-grid, the protection scheme must coordinate and isolates the least priority possible part of the grid to eliminate the fault. In order to deal with the bidirectional energy flow due to large numbers of micro sources new protection schemes are required. The system is simulated using MATLAB Wavelet Tool box and Wavelet based Multi-resolution Analysis is considered. Wavelet based Multi-resolution Analysis is used for detection, discrimination and location of faults on transmission network.  This paper is discussed a transient current based micro-grid connected power system protection scheme using Wavelet Approach described on wavelet detailed-coefficients of Mother Biorthogonal 1.5 wavelet. The proposed algorithm is tested in micro-grid connected power systems environment and proved for the detection, discrimination and location of faults which is almost independent of fault impedance, fault inception angle (FIA) and fault distance of feeder line.
Volume: 9
Issue: 1
Page: 14-22
Publish at: 2019-02-01

Topic Discovery of Online Course Reviews Using LDA with Leveraging Reviews Helpfulness

10.11591/ijece.v9i1.pp426-438
Fetty Fitriyanti Lubis , Yusep Rosmansyah , Suhono H. Supangkat
Despite the popularity of the Massive Open Online Courses, small-scale research has been done to understand the factors that influence the teaching-learning process through the massive online platform. Using topic modeling approach, our results show terms with prior knowledge to understand e.g.: Chuck as the instructor name. So, we proposed the topic modeling approach on helpful subjective reviews. The results show five influential factors: “learn easy excellent class program”, “python learn class easy lot”, “Program learn easy python time game”, and “learn class python time game”. Also, research results showed that the proposed method improved the perplexity score on the LDA model.
Volume: 9
Issue: 1
Page: 426-438
Publish at: 2019-02-01

Generating similarity cluster of Indonesian languages with semi-supervised clustering

10.11591/ijece.v9i1.pp531-538
Arbi Haza Nasution , Yohei Murakami , Toru Ishida
Lexicostatistic and language similarity clusters are useful for computational linguistic researches that depends on language similarity or cognate recognition. Nevertheless, there are no published lexicostatistic/language similarity cluster of Indonesian ethnic languages available. We formulate an approach of creating language similarity clusters by utilizing ASJP database to generate the language similarity matrix, then generate the hierarchical clusters with complete linkage and mean linkage clustering, and further extract two stable clusters with high language similarities. We introduced an extended k-means clustering semi-supervised learning to evaluate the stability level of the hierarchical stable clusters being grouped together despite of changing the number of cluster. The higher the number of the trial, the more likely we can distinctly find the two hierarchical stable clusters in the generated k-clusters. However, for all five experiments, the stability level of the two hierarchical stable clusters is the highest on 5 clusters. Therefore, we take the 5 clusters as the best clusters of Indonesian ethnic languages. Finally, we plot the generated 5 clusters to a geographical map.
Volume: 9
Issue: 1
Page: 531-538
Publish at: 2019-02-01

Augmented reality application for chemical bonding based on android

10.11591/ijece.v9i1.pp445-451
Alexander Setiawan , Silvia Rostianingsih , Timotius Reinaldo Widodo
Augmented Reality can provide information that can be more easily understood by the user. Because of its advantages, Augmented Reality can be utilized to create learning applications that can support teaching and learning process. Chemical learning about chemical reactions is usually boring by students. This is because students only know the theory of the book and the explanation of teachers only. This research utilized Augmented Reality to be able to see 3D model of each chemical element and also can see animation of merging between elements. In order to bring up 3D objects of chemical elements then made a card that will be used as a marker / tracker. In addition, there can be a combination of several chemical elements based on several cards detected from the camera. The test is performed for chemical elements with periodic table such as H, Ca, Na, K, C, Cl, Br, O, S, SO2, CO2, OH. Testing the application by performing several merge elements such as HCl, NaCl, H20, CO2, MgS, SO2, O2, CaCl2, HCN, N2, and others. The results of this study will be tested on several students to see the benefits of student learning.
Volume: 9
Issue: 1
Page: 445-451
Publish at: 2019-02-01

Iterative improved learning algorithm for petrographic image classification accuracy enhancement

10.11591/ijece.v9i1.pp289-296
Ashutosh Marathe , Priya Jain , Vibha Vyas
Rock image classification using image processing has been practiced to assist trained geologists in decision making. However, the study of microstructures of rocks and their use in geological investigations offer challenges in the areas of Image processing and Pattern Classification due to the stochastic nature of the mineral textures that is revealed at the microscopic level. Locally relevant Igneous Rock Microstructure images were classified from Volcanic and Plutonic Rock subtypes. The imaging method used mineral grain size as the key physical feature of classification. Three algorithms, namely Radial Basis Function (RBF) Support Vector Machine classifier; Improved (RBF) Support Vector Machine classifier; and AdaBoost algorithm with Improved RBF Support Vector Machine algorithm as base classifier, were used as a base classifier in a novel ‘Iterative Improved Learning (IIL)’ approach. Implementing the IIL approach in the chosen algorithm resulted in accurately classified images that were added to the training set to enhance the ‘breadth and depth’ of the learning knowledge. The algorithm iterated through all available classifier approaches and compared the inter-classifier performance and knowledge of the misclassified images accumulated during the execution of all algorithms.
Volume: 9
Issue: 1
Page: 289-296
Publish at: 2019-02-01
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