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30,376 Article Results

Automated Detection of Microaneurysmsusing Probabilistic Cascaded Neural Network

10.11591/ijeecs.v11.i3.pp1083-1093
Jeyapriya J , K S Umadevi , R Jagadeesh Kannan
The diagnosing features for Diabetic Retinopathy (DR) comprises of features occurring in and around the regions of blood vessel zone which will result into exudes, hemorrhages, microaneurysms and generation of textures on the albumen region of eye balls. In this study we presenta probabilistic convolution neural network based algorithms, utilized for the extraction of such features from the retinal images of patient’s eyeballs. The classifications proficiency of various DR systems is tabulated and examined. The majority of the reported systems are profoundly advanced regarding the analyzed fundus images is catching up to the human ophthalmologist’s characterization capacities.
Volume: 11
Issue: 3
Page: 1083-1093
Publish at: 2018-09-01

A Review of Crude Oil Prices Forecasting using Hybrid Method

10.11591/ijeecs.v11.i3.pp1114-1120
Nurull Qurraisya Nadiyya Md-Khair , Ruhaidah Samsudin
Crude oil is considered as a crucial energy source in modern days. Consequently, the fluctuation of crude oil prices can cause a significant impact on economic activities. Researchers have proposed many hybrid forecasting models on top of single forecasting methods which are utilized to predict crude oil prices movement more accurately. Nevertheless, many limitations still existed in hybrid forecasting models and models that can predict crude oil prices as accurate as possible is required. The motivations of this review paper are to identify and assess the mostly used crude oil prices forecasting methods and to analyse their current limitations. 12 studies that used “decomposition-and-ensemble” framework was selected for review. Wavelet transform is identified as the mostly used data decomposition method while some limitations have been recognized. Future researches should include more studies to further elucidate the limitations in existing forecasting method so that subsequent forecasting methods can be improved.
Volume: 11
Issue: 3
Page: 1114-1120
Publish at: 2018-09-01

Signal Processing in Telecommunications with Forward Correction of Errors

10.11591/ijeecs.v11.i3.pp868-877
Juliy Boiko , Oleksander Eromenko
The development of mechanisms of increase efficiency of frequency-shift keying signals processing in telecommunications using algorithms of noise immunity channel coding in obstacle effect conditions is held in the article. The synthesis of the frequency-shift keying signal processing unit accounting intersymbol communication which is inherent for such signals with continuous phase is held. The conditions of the compromise implementation in the telecommunication information transmission channel with frequency shift keying and error correction coding for setting the optimal encoding rate in the range of the bandwidth of the information transmission system are explored. Linear cyclic codes Bose-Chaudhuri-Hocquenghem (BCH) are used for studying. By means of Matlab the article focuses on the definition of energetic benefit compared to uncoded system in case of equality of the bandwidth of the information transmission system with coding and without coding.
Volume: 11
Issue: 3
Page: 868-877
Publish at: 2018-09-01

Homotopy Analysis Method for the First Order Fuzzy Volterra-Fredholm Integro-differential Equations

10.11591/ijeecs.v11.i3.pp857-867
Ahmed A. Hamoud , Kirtiwant P. Ghadle
A fuzzy Volterra-Fredholm integro-differential equation (FVFIDE) in a parametric case is converted to its related crisp case.  We use homotopy analysis method to find the approximate solution of this system and hence obtain an approximation for the fuzzy solution of the  FVFIDE. This paper discusses existence and uniqueness results and convergence of the proposed method.
Volume: 11
Issue: 3
Page: 857-867
Publish at: 2018-09-01

The Fuzzy Inference System with Least Square Optimization for Time Series Forecasting

10.11591/ijeecs.v11.i3.pp1015-1026
Samingun Handoyo , Marji Marji
The rule base on the fuzzy inference system (FIS) has a major role since the output generated by the system is highly dependent on it. The rule base is usually obtained from an expert but in this study proposed the rule base generated based on input-output data pairs with generating rule bases using lookup table scheme, then consequent part of each rule optimized with ordinary least square(OLS), so finally formed rule base from model FIS Takagi-Sugeno orde zero. The exchange rate dataset of EURO to USD is used for the development and validation of the system. In this study, 12 FISs were developed from a combination of linguistic values of n = 3,5,7, 9 with the number of lag (k) assumed to have an effect on output for k = 2,3,5. In training data, values R2 ranged between 0.989 and 0.993, MAPE values ranged between 0.381% and 0.473% where the FIS with the combination of n = 9 and k = 5 has the best performance. In the testing data, values R2 ranged between 0.203 and 0.7858, MAPE values ranged between 0.5136% and 0.9457% where FIS n = 3 and k = 2 perform best.
Volume: 11
Issue: 3
Page: 1015-1026
Publish at: 2018-09-01

A Novel Approach for Efficient Training of Deep Neural Networks

10.11591/ijeecs.v11.i3.pp954-961
D.T.V. Dharmajee Rao , K.V. Ramana
Deep Neural Network training algorithms consumes long training time, especially when the number of hidden layers and nodes is large. Matrix multiplication is the key operation carried out at every node of each layer for several hundreds of thousands of times during the training of Deep Neural Network. Blocking is a well-proven optimization technique to improve the performance of matrix multiplication. Blocked Matrix multiplication algorithms can easily be parallelized to accelerate the performance further. This paper proposes a novel approach of implementing Parallel Blocked Matrix multiplication algorithms to reduce the long training time. The proposed approach was implemented using a parallel programming model OpenMP with collapse() clause for the multiplication of input and weight matrices of Backpropagation and Boltzmann Machine Algorithms for training Deep Neural Network and tested on multi-core processor system. Experimental results showed that the proposed approach achieved approximately two times speedup than classic algorithms.
Volume: 11
Issue: 3
Page: 954-961
Publish at: 2018-09-01

Modified SHA-1 Algorithm

10.11591/ijeecs.v11.i3.pp1027-1034
Rogel Ladia Quilala , Ariel M Sison , Ruji P Medina
Hashes are used to check the integrity of data. This paper modified SHA-1 by incorporating mixing method in every round for better diffusion. The modification increased the hash output to 192-bits. Increasing the output increases the strength because breaking the hash takes longer. Based on the different message types, avalanche percentage of modified SHA-1 showed better diffusion at 51.64%, higher than the target 50%, while SHA-1 achieved 46.61%. The average execution time noted for modified SHA-1 is 0.33 seconds while SHA-1 is 0.08 seconds. Time increases as the number of messages hashed increases; the difference is negligible in fewer messages. On character hits, that is - no same character in the same position, modified SHA-1 achieved lower hit rate because of the mixing method added. The modifications’ effectiveness was also evaluated using a hash test program. After inputting 1000 hashes from random strings, the result shows no duplicate hash.
Volume: 11
Issue: 3
Page: 1027-1034
Publish at: 2018-09-01

Distribution Factor Method Modified for Determine of Load Contribute based on the Power Factor in Transmission Line

10.11591/ijeecs.v11.i3.pp1236-1242
Syarifuddin Nojeng , Syamsir Syamsir , Arif Jaya , Andi Syarifuddin , Mohammad Yusri Hassan
This paper proposes a modification of distribution factor methods for identifying the load contribute in a transmission open access, with regard to the load power factor. This method may be considered as the first pricing strategy to be proposed in bilateral transaction for transmission usage, based on the actual use of the transmission network. The merit of this method relies on the existence of a load power factor with GLDF  methods, which allocate the  transmission cost, not only based on the amount of power flow but also on the load characteristic. A case study utilizing the IEEE 30-bus system was conducted to illustrate the contribution of the proposed method in allocating the transmission usage to the user in a fair manner.
Volume: 11
Issue: 3
Page: 1236-1242
Publish at: 2018-09-01

Solving N-Queens Problem Using Subproblems based on Genetic Algorithm

10.11591/ijai.v7.i3.pp130-137
Ismail. A. Humied
Nowadays, permutation problems with large state spaces and the path to solution is irrelevant such as N-Queens problem has the same general property for many important applications such as integrated-circuit design, factory-floor layout, job-shop scheduling, automatic programming, telecommunications network optimization, vehicle routing, and portfolio management. Therefore, methods which are able to find a solution are very important. Genetic algorithm (GA) is one the most well-known methods for solving N-Queens problem and applicable to a wide range of permutation problems. In the absence of specialized solution for a particular problem, genetic algorithm would be efficient. But holism and random choices cause problem for genetic algorithm in searching large state spaces. So, the efficiency of this algorithm would be demoted when the size of state space of the problem grows exponentially. In this paper, the subproblems used based on genetic algorithm to cover this weakness. This proposed method is trying to provide partial view for genetic algorithm by locally searching the state space. This method works to take shorter steps toward the solution. To find the first solution and other solutions in N-Queens problem using proposed method: dividing N-Queens problem into subproblems, which configuring initial population of genetic algorithm. The proposed method is evaluated and compares it with two similar methods that indicate the amount of performance improvement.
Volume: 7
Issue: 3
Page: 130-137
Publish at: 2018-09-01

Matchmaking Problems in MOBA Games

10.11591/ijeecs.v11.i3.pp908-917
Muhammad Farrel Pramono , Kevin Renalda , Dedy Prasetya Kristiadi , Harco Leslie Hendric Spits Warnars , Worapan Kusakunniran
MOBA is a popular genre that requires teamwork to achieve victory. A close and tight match is what make MOBA fun to play and increase its user satisfaction, but some factor may ruin the matchmaking and create unbalanced match between the two team. Those problems factors are high latency, players with bad attitude, and players doing unfamiliar role. We use DOTA 2 as our case study. Then we compare the DOTA 2 matchmaking system in other sector to make comparison. Lastly, we discuss about solution to solve MOBA matchmaking problem such as displaying live information about online players, players searching for games, servers online and ETA for gaming to start. In addition, we proposed new variable to be considered in the matchmaking system, which are Preferences Role, player’s chosen preferences role will be considered while the system set up the game to minimize the number of unbalanced games in MOBA.
Volume: 11
Issue: 3
Page: 908-917
Publish at: 2018-09-01

Cascaded Neural Network Based Data Mining Strategy for Cloud Intrusion Detection

10.11591/ijeecs.v11.i3.pp1094-1101
P Purniemaa , R Jagadeesh Kannan
In recent years data mining has acquired huge popularity in the field of knowledge discovery. Thus, this approach has inspired several researches for anomaly detection, fraud detection and intrusion detection with higher accuracy, all round generalization of the problem and its sub cases; all giving higher performance in conditions subjected to continuous alteration. Though there remain quite a few challenging problems in design and implementation of a data mining based cloud intrusion detection system, as deception tactics and modeling of behavior remains a daunting problem to compute for anomaly owing to massive size of data to process in reasonable time. In this study we present a cascaded neural network based data mining strategy for cloud intrusion detection systems (IDSs) and presents the comparison and performance results tested on DARPA Intrusion Detection (ID) Data Sets, Knowledge Discovery and Data Mining Cup, NSL-KDD dataset. The study exhibits numerous advantages offered by the presented method and give reliable results of anomaly detection in real time scenario.
Volume: 11
Issue: 3
Page: 1094-1101
Publish at: 2018-09-01

Design Process to Reduce Production Cycle Time in Product Development

10.11591/ijai.v7.i3.pp125-129
Mahesh Mallampati , Kolla Srivinivas , Tirumala Krishna. M
In today’s business climate, the old adage “time is money” has been expanded to mean that time is competitive weapon. Today customer’s demands are quick delivery and good quality at reasonable price. When entering the global market the companies encounter several difficulties, the most important one being excessive time for new product development. Thus to perform in a global market, short lead times are essential to provide customer satisfaction. Lead time in manufacturer point of view is the time elapse between placing of an order and the receipt of goods ordered. There are various components of lead time such as setup time, process time, move time and waiting time. This paper deals with review of various tools and techniques to reduce lead time. This problem can be solved by transition from sequential engineering to concurrent engineering, A survey of published works in the field of designing teams in big companies has revealed that in big companies a three-level team structure is recommended, as well as a workgroup, consisting of four basic teams. Method study techniques use to examine current way of work and develop effective method base on elimination, combining, changing and simplification of activities. Various lean tools such as Single Minute Exchange of Dies (SMED), 5S, Poka-yoke, Kanban, Just-in-time (JIT), Value Stream Mapping (VSM), Jidoka, Cellular manufacturing etc. helps in reducing lead time. Also Manufacturing Resource Planning (MRPII), Theory of Constraints (TOC) classic approaches of Production Planning and Control (PPC) are use to reduce Work in Process (WIP) and flow time.
Volume: 7
Issue: 3
Page: 125-129
Publish at: 2018-09-01

Design and Analysis of a Smart Blind Stick for Visual Impairment

10.11591/ijeecs.v11.i3.pp848-856
Zulkhairi Mohd Yusof , Md Masum Billah , Kushsairy Kadir , Muhamad Amirul Sunni Bin Rohim Rohim , Haidawati Nasir , M. Izani , A. Razak
For a long time, visually impaired person uses a white cane to guide their way when travel outside. The white cane has been useful for the blinds in improving their mobility but unfortunately the white cane has its limitation. One of the shortcomings of the white cane is that, it could only detect the obstacles that are within the contact ranges of the white cane. This problem sometimes could cause the blind person to be in trouble because of insufficient time to detect and warn new obstacles in front of the blind person. This research proposes a walking stick system that has two functions; to classify an obstacles height whether it is low or high and to detect a front hole. The ability to detect the height of an obstacle will help the visually impaired to either step over or avoid the obstacle. The ability to detect a hole should help the visually impaired to avoid it in time. The walking stick will use two ultrasonic sensors for the detection of obstacle height, and a laser sensor for the detection of hole. A controller will be used to monitor and analyze the data from the sensors and feedback to the user through a vibration sensor and buzzer. The algorithm to differentiate the height of obstacles is working well and it is able to differentiate high or low obstacles. The laser ranging sensor has successfully been tested for hole detection. Therefore, the walking stick with ultrasonic and laser sensors will help more visually impaired to move around much faster and feeling more safer due to improved warning system for their movement.
Volume: 11
Issue: 3
Page: 848-856
Publish at: 2018-09-01

Discrete Chicken Swarm Optimization for the Quadratic Assignment Problem

10.11591/ijeecs.v11.i3.pp925-935
Soukaina Cherif Bourki Semlali , Mohammed Essaid Riffi , Fayçal Chebihi
The main objective of our research is to improve an adaptation of the chicken swarm optimization algorithm (CSO) to solve the quadratic assignment problem, which is a well-known combinatorial optimization problem. The new approach is based on the CSO without using a local search, the CSO-QAP is a stochastic method inspired from the behavior of chickens in swarm while searching for food. The experiments are performed on a set of 56 benchmark QAPLIB instances. To prove the robustness of our algorithm a comparative analysis is done with the known metaheuristic of Genetic algorithm based on SCX. The average percentage of error to get the best Known solution in our proposed work with the results obtained by applying a simple genetic algorithm using sequential constructive crossover for the quadratic assignment problem. The results show the effectiveness of the proposed CSO-QAP to solve the Quadratic assignment problem in term of time and quality of solutions. The proposed adaptation can be further applied by using a local search strategy to solve the same problem or another combinatorial problem.
Volume: 11
Issue: 3
Page: 925-935
Publish at: 2018-09-01

Performance Enhancement of Bidirectional NOC Router With and Without Contention for Reconfigurable Coarse Grained Architecture

10.11591/ijeecs.v11.i3.pp1068-1074
Yazhinian Sougoumar , Tamilselvan Sadasivam
Network on Chip (NoC) router plays a vital role in System on Chip (SoC) applications. Routing operation is difficult to perform inside the SoC chip. Because it contains millions of chips in one single Integrated Circuit (IC), in which every chip consists of millions of transistors. Hence NoC router is designed to enable efficient routing operation in the SoC board.  NoC router consists of Network Interconnects (NI), Crossbar Switches, arbiters, a routing logic and buffers. Conventional unidirectional router is designed by priority based Round Robin Arbiter (RRA). It produces more delay to find the priority, which comes from various input channels and more area is consumed in unidirectional router. Also if any path failure occurs, it cannot route the data through other output channel. To overcome this problem, a novel bidirectional NoC router with and without contention is proposed, which offers less area and high speed than the existing unidirectional router. A novel bidirectional NoC router consists of round robin arbiter, Static RAM, switch allocator, virtual channel allocator and crossbar switch. The proposed bidirectional router can route the data from any input channel to each and every output channel. So it avoids conflict situation and path failure problems. If any path fails, immediately it will take the alternative path through the switch allocator. The proposed routing scheme is applied into the coarse grained architecture for improving the speed of the interconnection link between two processing elements. Simulation is performed by ModelSim6.3c and synthesis is carried out by Xilinx10.1.
Volume: 11
Issue: 3
Page: 1068-1074
Publish at: 2018-09-01
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