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31,456 Article Results

A hybrid content based image retrieval system using log-gabor filter banks

10.11591/ijece.v9i1.pp237-244
D. Madhavi , Khwaja Muinuddin Chisti Mohammed , N. Jyothi , M. Ramesh Patnaik
In this paper, a new efficient image retrieval system using sequential process of three stages with filtering technique for the feature selection is proposed. In the first stage the color features are extracted using color histogram method and in the second stage the texture features are obtained using log-Gabor filters and in the third stage shape features are extracted using shape descriptors using polygonal fitting algorithm. The proposed log-Gabor filter in the second stage has advantages of retrieving images over regular Gabor filter for texture. It provides better representation of the images. Experimental evaluation of the proposed system shows improved performance in retrieval as compared to other existing systems in terms of average precision and average recall.
Volume: 9
Issue: 1
Page: 237-244
Publish at: 2019-02-01

Integrated approach to detect spam in social media networks using hybrid features

10.11591/ijece.v9i1.pp562-569
Kurapati Subba Reddy , E. Srinivasa Reddy
Online social networking sites are becoming more popular amongst Internet users. The Internet users spend some amount of time on popular social networking sites like Facebook, Twitter and LinkedIn etc. Online social networks are considered to be much useful tool to the society used by Internet lovers to communicate and transmit information. These social networking platforms are useful to share information, opinions and ideas, make new friends, and create new friend groups. Social networking sites provide large amount of technical information to the users. This large amount of information in social networking sites attracts cyber criminals to misuse these sites information. These users create their own accounts and spread vulnerable information to the genuine users. This information may be advertising some product, send some malicious links etc to disturb the natural users on social sites. Spammer detection is a major problem now days in social networking sites. Previous spam detection techniques use different set of features to classify spam and non spam users. In this paper we proposed a hybrid approach which uses content based and user based features for identification of spam on Twitter network. In this hybrid approach we used decision tree induction algorithm and Bayesian network algorithm to construct a classification model. We have analysed the proposed technique on twitter dataset. Our analysis shows that our proposed methodology is better than some other existing techniques.
Volume: 9
Issue: 1
Page: 562-569
Publish at: 2019-02-01

Implementation of a frequency control in a biomass gasifier system

10.11591/ijece.v9i1.pp66-77
Yecid Muñoz , Adalberto Ospino , Carlos Robles , Carlos Arizmendi
Distributed power generation has grown in popularity in recent years, especially in areas not connected to the national grid. As a result, rural microgrids are becoming more common, involving great potential for energy based on biomass conversion such as gasification. After analyzing distributed power generation facilities in developing countries, the authors found problems with the frequency stability. This paper focuses on solving the problem of frequency control in energy supplied by microgrids based in biomass gasification. For that purpose, the authors have developed a physical model of a downdraft gasifier, this model was used for design a novel strategy for frequency control, which has been based and validated on an existing gasification system, which supplies power to a population in Necoclí (Colombia).
Volume: 9
Issue: 1
Page: 66-77
Publish at: 2019-02-01

Impact of clustering in AODV routing protocol for wireless body area network in remote health monitoring system

10.11591/ijeecs.v13.i2.pp689-695
Wan Aida Nadia Wan Abdullah , Naimah Yaakob , R. Badlishah Ahmad , Mohamed Elshaikh Elobaid , Siti Asilah Yah
Proper selection of routing protocol in transmitting and receiving medical data in Wireless Body Area Network (WBAN) is one of the approaches that would help in ensuring high network performances.  However, a continuous monitoring of health status through sensing of various vital body signals by multiple biosensors could produce a bulk of medical data and lead to the increase of network traffic. Occurrence of high traffic could result to network’s congestion which have high tendency to loss some of important (critical) data and cause longer delay that would lead to false diagnosis of diseases. In order to analyze and validate this issue, Ad-Hoc On Demand Distance Vector (AODV) which is known as reactive routing protocol is evaluated in WBAN scenario through varying number of nodes and clusters. The presence of clustering helps in reducing the burden of the sink nodes in handling high traffics. The network’s performances of this protocol are measured in terms of end to end delay, percentage packet loss, throughput and energy consumption using Network Simulator (NS-2). Based on the experimental results, the presence of cluster helps in improving network performances by achieving reduction in delay, packet loss and energy consumption. However, low throughput is achieved as number of clusters are increase due to low duty cycle of the nodes.
Volume: 13
Issue: 2
Page: 689-695
Publish at: 2019-02-01

Energy and exergy analysis of air based photovoltaic thermal (PVT) collector: a review

10.11591/ijece.v9i1.pp109-117
Ahmad Fudholi , Mariyam Fazleena Musthafa , Abrar Ridwan , Rado Yendra , Ari Pani Desvina , Rahmadeni Rahmadeni , Tri Suyono , Kamaruzzaman Sopian
Photovoltaic thermal (PVT) collectors convert solar radiation directly to both electrical and thermal energies. A PVT collector basiccaly combines the functions of a flat plate solar collector and those of a PV panel. This review presents thermodinamics fundamentals, descriptions, and previous works conducted on energy and exergy analysis of air based PVT collector. Studies in 2010 to 2018 of the energy and exergy analysis of air based PVT collectors are summarized. The energy and exergy efficiency of air based PVT collector ranges from 31% to 94% and 8.7% to 18%, respectively. In addition, flat plate solar collector is presented. Studies conducted on air based PVT collectors are reviewed.
Volume: 9
Issue: 1
Page: 109-117
Publish at: 2019-02-01

Noise reduction in ECG Signals for Bio-telemetry

10.11591/ijece.v9i1.pp505-511
V. Jagan Naveen , K. Murali Krishna , K. Raja Rajeswari
In Biotelemetry, Biomedical signal such as ECG is extremely important in the diagnosis of patients in remote location and is recorded commonly with noise. Considered attention is required for analysis of ECG signal to find the patho-physiology and status of patient. In this paper, LMS and RLS algorithm are implemented on adaptive FIR filter for reducing power line interference (50Hz) and (AWGN) noise on ECG signals .The ECG signals are randomly chosen from MIT_BIH data base and de-noising using algorithms. The peaks and heart rate of the ECG signal are estimated. The measurements are taken in terms of Signal Power, Noise Power and   Mean Square Error.
Volume: 9
Issue: 1
Page: 505-511
Publish at: 2019-02-01

MPR selection to the OLSR quality of service in MANET using minmax algorithm

10.11591/ijece.v9i1.pp417-425
Alamsyah Alamsyah , I Ketut Eddy Purnama , Eko Setijadi , Mauridhi Hery Purnomo
Optimized link state routing (OLSR) is a routing protocol that has a small delay, low traffic control, support the application of denser networks, and adopts the concept of multipoint relays (MPR). The problem of OLSR is routing table updating which continually causes excessive packet delivery, and energy consumption becomes increased. This article proposes the improvement of OLSR performance using the min-max algorithm based on the quality of service (QoS) with considering the density of the node. The Min-max algorithm works in selecting MPR nodes based on the largest signal range. The QoS parameters analyzed with a different number of nodes are packet delivery ratio (PDR), throughput, delay, energy consumption, and topology control (TC). Simulation result of network simulator version 2 (NS-2) shows that OLSR performance using the min-max algorithm can increase PDR of 91.17%, packet loss of 60.77% and reduce topology control packet of 8.07%, energy consumption of 16.82% compared with standard OLSR.
Volume: 9
Issue: 1
Page: 417-425
Publish at: 2019-02-01

Dielectric properties characterization of the rice and rice weevil for microwave heating treatment

10.11591/ijeecs.v13.i2.pp752-758
Maliki Ibrahim , Rosemizi Abd Rahim , Junita Mohd Nordin , Siti Zulaika Abdul Nyzam , Norzakiah Amira Amatkhri
This paper presents the dielectric properties characterization of the rice and rice weevil for microwave heating disinfestation treatment application. Infestations of insects in stored grain have become a major threat to food supply globally. It contributes to damage to the stored grain and had caused economic losses. The current method to control the infestation which is by using chemical fumigation could give harm to human health and cause environmental pollution. The ability of microwave energy to kill the insects using dielectric heating technique has a high potential as an alternative method to control the infestation of the insect. Knowledge of dielectric properties of the insects is important to understand the interactions of the insect with electromagnetic fields. Hence, this paper presents the evaluation of the dielectric constant, and dielectric loss factor, of the insects and grain using open- ended coaxial probe method. The dielectric properties of the rice weevil, S. Oryzae and rice are measured using an open-ended dielectric probe. Found that the dielectric constant, loss factor and loss tangent for both samples are inversely proportional to the frequency.  Knowledge of the moisture content and temperature of the insects and rice is very important to characterize the dielectric properties for future development of microwave heating disinfestation treatment effectively.
Volume: 13
Issue: 2
Page: 752-758
Publish at: 2019-02-01

Improved method for image security based on chaotic-shuffle and chaotic-diffusion algorithms

10.11591/ijece.v9i1.pp273-280
Sanjeev Sharma , Tarun Kumar , Ravi Dhaundiyal , Amit Kumar Mishra , Nitin Duklan , Ashish Maithani
In this paper, we propose to enhance the security performance of the color image encryption algorithm which depends on multi-chaotic systems. The current cryptosystem utilized a pixel-chaotic-shuffle system to encode images, in which the time of shuffling is autonomous to the plain-image. Thus, it neglects to the picked plaintext and known-plaintext attacks. Also, the statistical features of the cryptosystem are not up to the standard. Along these lines, the security changes are encircled to make the above attacks infeasible and upgrade the statistical features also. It is accomplished by altering the pixel-chaotic-shuffle component and including another pixel-chaotic-diffusion system to it. The keys for diffusion of pixels are extracted from the same chaotic arrangements created in the past stage. The renovation investigations and studies are performed to exhibit that the refreshed version of cryptosystem has better statistical features and invulnerable to the picked plaintext and known plaintext attacks than the current algorithm.
Volume: 9
Issue: 1
Page: 273-280
Publish at: 2019-02-01

Negative image amplifier technique for performance enhancement of ultra wideband LNA

10.11591/ijece.v9i1.pp221-230
Kishor G. Sawarkar , Kushal R. Tuckley
The paper aims at designing of two stage cascaded ultra-wideband (UWB) low noise amplifier (LNA) by using negative image amplifier technique. The objective of this article is to show the performance improvement using negative image amplifier technique and realization of negative valued lumped elements into microstrip line geometry. The innovative technique to realize the negative lumped elements are carried out by using Richard’s Transformation and transmission line calculation. The AWR microwave office tool is used to obtain characteristics of UWB LNA design with hybrid microwave integrated circuit (HMIC) technology. The 2-stage cascaded LNA design using negative image amplifier technique achieves average gain of 23dB gain and low noise figure of less than 2dB with return loss less than -8dB for UWB 3-10GHz. The Proper bias circuit is extracted using DC characteristics of transistor at biasing point 2V, 20mA and discussed in detail with LNA layout. The negative image matching technique is applied for both input and output matching network. This work will be useful for all low power UWB wireless receiver applications.
Volume: 9
Issue: 1
Page: 221-230
Publish at: 2019-02-01

Automatic detection of rust disease of Lentil by machine learning system using microscopic images

10.11591/ijece.v9i1.pp660-666
Kuldeep Singh , Satish Kumar , Pawan Kaur
Accurate and early detection of plant diseases will facilitate mitigate the worldwide losses experienced by the agriculture area. MATLAB image processing provides quick and non-destructive means of rust disease detection. In this paper, microscopic image data of rust disease of Lentil was combined with image processing with depth information and developed a machine learning system to detect rust disease at early stage infected with fungus Uromyces fabae (Pers) de Bary. A novel feature set was extracted from the image data using local binary pattern (LBP) and HBBP (Brightness Bi-Histogram Equalization) for image enhancement. It was observed that by combining these, the accuracy of detection of the diseased plants at microscopic level was significantly improved. In addition, we showed that our novel feature set was capable of identifying rust disease at haustorium stage without spreading of disease. 
Volume: 9
Issue: 1
Page: 660-666
Publish at: 2019-02-01

A hybrid algorithm to reduce energy consumption management in cloud data centers

10.11591/ijece.v9i1.pp554-561
Mehran Tarahomi , Mohammad Izadi
There are several physical data centers in cloud environment with hundreds or thousands of computers. Virtualization is the key technology to make cloud computing feasible. It separates virtual machines in a way that each of these so-called virtualized machines can be configured on a number of hosts according to the type of user application. It is also possible to dynamically alter the allocated resources of a virtual machine. Different methods of energy saving in data centers can be divided into three general categories: 1) methods based on load balancing of resources; 2) using hardware facilities for scheduling; 3) considering thermal characteristics of the environment. This paper focuses on load balancing methods as they act dynamically because of their dependence on the current behavior of system. By taking a detailed look on previous methods, we provide a hybrid method which enables us to save energy through finding a suitable configuration for virtual machines placement and considering special features of virtual environments for scheduling and balancing dynamic loads by live migration method.
Volume: 9
Issue: 1
Page: 554-561
Publish at: 2019-02-01

Deep learning for pose-invariant face detection in unconstrained environment

10.11591/ijece.v9i1.pp577-584
Shivkaran Ravidas , M. A. Ansari
In the recent past, convolutional neural networks (CNNs) have seen resurgence and have performed extremely well on vision tasks.  Visually the model resembles a series of layers each of which is processed by a function to form a next layer. It is argued that CNN first models the low level features such as edges and joints and then expresses higher level features as a composition of these low level features. The aim of this paper is to detect multi-view faces using deep convolutional neural network (DCNN). Implementation, detection and retrieval of faces will be obtained with the help of direct visual matching technology. Further, the probabilistic measure of the similarity of the face images will be done using Bayesian analysis. Experiment detects faces with ±90 degree out of plane rotations. Fine tuned AlexNet is used to detect pose invariant faces. For this work, we extracted examples of training from AFLW (Annotated Facial Landmarks in the Wild) dataset that involve 21K images with 24K annotations of the face.
Volume: 9
Issue: 1
Page: 577-584
Publish at: 2019-02-01

A modified backward/forward sweep-based method for reconfiguration of unbalanced distribution networks

10.11591/ijece.v9i1.pp85-101
Michel Duran-Quintero , John E. Candelo , Jose Soto-Ortiz
A three-phase unbalanced power flow method can provide a more realistic scenario of how distribution networks operate. The backward/forward sweep-based power flow method (BF-PF) has been used for many years as an important computational tool to solve the power flow for unbalanced and radial power systems. However, some of the few available research tools produce many errors when they are used for network reconfiguration because the topology changesafter multiple switch actions and the nodes are disorganized continually. This paper presents a modifiedBF-PF for three-phase unbalanced radial distribution networks that is capable of arranging the system topology when reconfiguration changes the branch connections. A binary search is used to determine the connections between nodes, allowing the algorithm to avoid those problems when reconfiguration is carried out, regardless of node numbers. Tests are made to verify the usefulness of the proposed algorithm in both the IEEE 13-node test feeder and the 123-node test feeder, converging in every run where constraints are accomplished. This approach can be used easily for a large-scale feeder network reconfiguration. The full version of this modified backward/forward sweep algorithm is available for research at MathWorks.
Volume: 9
Issue: 1
Page: 85-101
Publish at: 2019-02-01

Opinion mining framework using proposed RB-bayes model for text classication

10.11591/ijece.v9i1.pp477-484
Rajni Bhalla , Amandeep Bagga
Information mining is a capable idea with incredible potential to anticipate future patterns and conduct. It alludes to the extraction of concealed information from vast data sets by utilizing procedures like factual examination, machine learning, grouping, neural systems and genetic algorithms. In naive baye’s, there exists a problem of zero likelihood. This paper proposed RB-Bayes method based on baye’s theorem for prediction to remove problem of zero likelihood. We also compare our method with few existing methods i.e. naive baye’s and SVM. We demonstrate that this technique is better than some current techniques and specifically can analyze data sets in better way. At the point when the proposed approach is tried on genuine data-sets, the outcomes got improved accuracy in most cases. RB-Bayes calculation having precision 83.333.
Volume: 9
Issue: 1
Page: 477-484
Publish at: 2019-02-01
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