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29,061 Article Results

An Enhanced Bandwidth Optimization in Un-reliable Network using Efficient Bandwidth Utilization based Scheduling Algorithm

10.11591/ijeecs.v10.i2.pp596-605
Sivashanmugam N , Jyoti Venkateshwaran
Nowadays, bandwidth utilization is a very challenging task for Subscriber Stations (SS) to predict a large amount of data. The existing techniques allow the SS to maintain the occupied bandwidth via risk of failure which does not satisfy the quality of services (QoS) needs.  Another challenge is the resource handling with QoS. In Web technology life, there is only few research focused on tackling the resource handling issues with different techniques. Current methods do not consider the data interchange during route switching.  To offer the best solution of above problems, An Efficient Bandwidth Utilization based Scheduling (EBS) Algorithm is designed to maintain proper bandwidth utilization in a real-time application. The EBS algorithm predicts the amount of bandwidth which should be requested according to backlogged traffic data. It’s also considering the data rate divergence between a packet received and transmissions in a queue to improve the bandwidth. The main objective of proposed design is to permits other complementary station (CS) and SSs to bring out the unutilized bandwidth by the availability of SS transmission. The unutilized bandwidth is not possible to get regularly. The proposed method is more flexible to apply in real time and research-oriented applications. The methods enhance the bandwidth utilization during maintenance of the same QoS guaranteed network services. A proposed method avoids the current bandwidth reservation collapse at the time of the same QoS guaranteed services.  The techniques permit SSs to find out the portion of un-utilized bandwidth accurately. Based on Experimental evaluations, proposed algorithm reduces 21.26 PLR (Packet Loses Ratio), 3.25 AD (Average Delay), and improves 8.65 BU (Bandwidth Utilization) and 51.2% (Throughput) compared than existing methods.
Volume: 10
Issue: 2
Page: 596-605
Publish at: 2018-05-01

The Influence of Internet and Social Media on Purchasing Decisions in Kuwait

10.11591/ijeecs.v10.i2.pp792-797
Khalid Abdulkareem Al-Enezi , Imad Fakhri Taha Al Shaikhli , Sufyan Salim Mahmood AlDabbagh
This research aims to measure the role of social networks in influencing purchasing decisions among consumers in Kuwait; the research used the quantitative methods, and analytical the technique to get the results, and the research developed a measure to study the relationship between the variables to the study and selection of a sample of consumers of (100). The results indicated that the social networking variables (exchange of information, evaluation of product) possess influence on purchasing decisions. Furthermore, the results indicate that majority of respondents do their digital scanning more often before intend to go to the store. The unexpected results came from the question “traditional advertising (TV, Newspaper, Magazine, Billboards) are more effective than the social networking; 23% agreed, 36% said no, and 41% said sometimes. In light of these findings, the study made a series of recommendations; the most important are; The executives and sales representatives need to understand the benefits offered by social networks, and understand the advantages and functions and tools of social communication, and knowing how to apply them effectively and efficiently, and then use the appropriate social networking tool.
Volume: 10
Issue: 2
Page: 792-797
Publish at: 2018-05-01

Speech Emotion Recognition Using Deep Feedforward Neural Network

10.11591/ijeecs.v10.i2.pp554-561
Muhammad Fahreza Alghifari , Teddy Surya Gunawan , Mira Kartiwi
Speech emotion recognition (SER) is currently a research hotspot due to its challenging nature but bountiful future prospects. The objective of this research is to utilize Deep Neural Networks (DNNs) to recognize human speech emotion. First, the chosen speech feature Mel-frequency cepstral coefficient (MFCC) were extracted from raw audio data. Second, the speech features extracted were fed into the DNN to train the network. The trained network was then tested onto a set of labelled emotion speech audio and the recognition rate was evaluated. Based on the accuracy rate the MFCC, number of neurons and layers are adjusted for optimization. Moreover, a custom-made database is introduced and validated using the network optimized. The optimum configuration for SER is 13 MFCC, 12 neurons and 2 layers for 3 emotions and 25 MFCC, 21 neurons and 4 layers for 4 emotions, achieving a total recognition rate of 96.3% for 3 emotions and 97.1% for 4 emotions.Speech emotion recognition (SER) is currently a research hotspot due to its challenging nature but bountiful future prospects. The objective of this research is to utilize Deep Neural Networks (DNNs) to recognize human speech emotion. First, the chosen speech feature Mel-frequency cepstral coefficient (MFCC) were extracted from raw audio data. Second, the speech features extracted were fed into the DNN to train the network. The trained network was then tested onto a set of labelled emotion speech audio and the recognition rate was evaluated. Based on the accuracy rate the MFCC, number of neurons and layers are adjusted for optimization. Moreover, a custom-made database is introduced and validated using the network optimized.The optimum configuration for SER is 13 MFCC, 12 neurons and 2 layers for 3 emotions and 25 MFCC, 21 neurons and 4 layers for 4 emotions, achieving a total recognition rate of 96.3% for 3 emotions and 97.1% for 4 emotions.
Volume: 10
Issue: 2
Page: 554-561
Publish at: 2018-05-01

An Hour Ahead Electricity Price Forecasting with Least Square Support Vector Machine and Bacterial Foraging Optimization Algorithm

10.11591/ijeecs.v10.i2.pp748-755
Intan Azmira Wan Abdul Razak , Izham Zainal Abidin , Yap Keem Siah , Aidil Azwin Zainul Abidin , Titik Khawa Abdul Rahman , Nurliyana Baharin , Mohd. Hafiz Bin Jali
Predicting electricity price has now become an important task in power system operation and planning. An hour-ahead forecast provides market participants with the pre-dispatch prices for the next hour. It is beneficial for an active bidding strategy where amount of bids can be reviewed or modified before delivery hours. However, only a few studies have been conducted in the field of hour-ahead forecasting. This is due to most power markets apply two-settlement market structure (day-ahead and real time) or standard market design rather than single-settlement system (real time). Therefore, a hybrid multi-optimization of Least Square Support Vector Machine (LSSVM) and Bacterial Foraging Optimization Algorithm (BFOA) was designed in this study to produce accurate electricity price forecasts with optimized LSSVM parameters and input features. So far, no works has been established on multistage feature and parameter optimization using LSSVM-BFOA for hour-ahead price forecast. The model was examined on the Ontario power market. A huge number of features were selected by five stages of optimization to avoid from missing any important features. The developed LSSVM-BFOA shows higher forecast accuracy with lower complexity than most of the existing models.
Volume: 10
Issue: 2
Page: 748-755
Publish at: 2018-05-01

Design of a New Cryptographic Hash Function – Titanium

10.11591/ijeecs.v10.i2.pp827-832
Mohammad A. AlAhmad
This paper introduces a new cryptographic hash function that follows sponge construction. Paper begins with outlining the structure of the construction. Next part describes the functionality of Titanium and cipher used. A competition between block cipher and stream cipher is presented and showed the reason of using block cipher rather than stream cipher. Speed performance is calculated and analyzed using state-of-art CPUs.
Volume: 10
Issue: 2
Page: 827-832
Publish at: 2018-05-01

Internet of Things based Wireless Plant Sensor for Smart Farming

10.11591/ijeecs.v10.i2.pp456-468
Monica Subashini M , Sreethul Das , Soumil Heble , Utkarsh Raj , R Karthik
About 10% of the world’s workforce is directly dependent on agriculture for income and about 99% of food consumed by humans comes from farming. Agriculture is highly climate dependent and with global warming and rapidly changing weather it has become necessary to closely monitor the environment of growing crops for maximizing output as well as increasing food security while minimizing resource usage. In this study, we developed a low cost system which will monitor the temperature, humidity, light intensity and soil moisture of crops and send it to an online server for storage and analysis, based on this data the system can control actuators to control the growth parameters. The three tier system architecture consists of sensors and actuators on the lower level followed by an 8-bit AVR microcontroller which is used for data acquisition and processing topped by an ESP8266 Wi-Fi module which communicates with the internet server. The system uses relay to control actuators such as pumps to irrigate the fields; online weather data is used to optimize the irrigation cycles. The prototyped system was subject to several tests, the experimental results express the systems reliability and accuracy which accentuate its feasibility in real-world applications.
Volume: 10
Issue: 2
Page: 456-468
Publish at: 2018-05-01

To Improve Feature Extraction and Opinion Classification Issues in Customer Product Reviews Utilizing an Efficient Feature Extraction and Classification (EFEC) Algorithm

10.11591/ijeecs.v10.i2.pp587-595
Palaiyah Solainayagi , Ramalingam Ponnusamy
Currently, customer's product review opinion plays an essential role in deciding the purchasing of the online product. A customer prefers to acquire the opinion of other customers by viewing their opinion during online products' reviews, blogs and social networking sites, etc. The majority of the product reviews including huge words. A few users provide the opinion; it is tough to analysis and understands the meaning of reviews. To improve user fulfillment and shopping experience, it has become a general practice for online sellers to allow their users to review or to communicate opinions of the products that they have sold. The major goal of the paper is to solve feature extraction problem and opinion classification problem from customers utilized product reviews which extract the feature words and opinion words from product reviews. To propose an Efficient Feature Extraction and Classification (EFEC) algorithm is implementing to extracts a feature from opinion words. The reviewer usually marks both positive and negative parts of the reviewed product, despite the fact that their general opinion on the product may be positive or negative. An EFEC algorithm is utilized to predict the number of positive and negative opinion in reviews. Based on Experimental evaluations, proposed algorithm improves accuracy 15.05%, precision 13.7%, recall 15.59% and F-measure 15.07% of the proposed system compared than existing methodologies
Volume: 10
Issue: 2
Page: 587-595
Publish at: 2018-05-01

Development of Smart Chicken Poultry Farm

10.11591/ijeecs.v10.i2.pp498-505
Hasmah Mansor , Ammar Nor Azlin , Teddy Surya Gunawan , Mahanijah Md Kamal , Ahmad Zawawi Hashim
In Malaysia, most agriculture industries are still using conventional method to operate. All routines in monitoring and control of chicken poultry farm, for example, utilise man power where the source and energy are very limited. However, the demand from consumers towards the agricultural output is increasing day by day and requires more advanced farming technology in order to obtain maximum efficiency. This paper is focused on the development of smart chicken poultry farm to provide monitoring and control of the farm condition. The electronics, embedded systems and wireless technology are integrated with farm monitoring. Using Master-Slave concept, sensors are used to measure the ambient temperature, ammonia and humidity of the hall of chicken poultry for each slave. The sensors’ readings are then transmitted wirelessly over radio frequency by serial communication using HC-12 RF module to master for further data processing. The design process of both master and slave involved the interfacing of microprocessor, ATMEL ATMega328 with several analogue sensors, LCD, buzzer, relay output, monetary push button and light indicator. Based on the readings from the sensors, the microcontroller produced the output which is connected to the fan for better air ventilation in the chicken poultry farm. Furthermore, PID controller has been integrated to optimize the output control method, hence optimizing hall condition which results to better output for the farm. The system has been successfully implemented and tested at Myra Farm & Services, located at Kalumpang, Tanjung Malim, Perak, Malaysia.In Malaysia, most agriculture industries are still using conventional method to operate. All routines in monitoring and control of chicken poultry farm, for example, utilise man power where the source and energy are very limited. However, the demand from consumers towards the agricultural output is increasing day by day and requires more advanced farming technology in order to obtain maximum efficiency. This paper is focused on the development of smart chicken poultry farm to provide monitoring and control of the farm condition. The electronics, embedded systems and wireless technology are integrated with farm monitoring. Using Master-Slave concept, sensors are used to measure the ambient temperature, ammonia and humidity of the hall of chicken poultry for each slave. The sensors’ readings are then transmitted wirelessly over radio frequency by serial communication using HC-12 RF module to master for further data processing. The design process of both master and slave involved the interfacing of microprocessor, ATMEL ATMega328 with several analogue sensors, LCD, buzzer, relay output, monetary push button and light indicator. Based on the readings from the sensors, the microcontroller produced the output which is connected to the fan for better air ventilation in the chicken poultry farm. Furthermore, PID controller has been integrated to optimize the output control method, hence optimizing hall condition which results to better output for the farm. The system has been successfully implemented and tested at Myra Farm & Services, located at Kalumpang, Tanjung Malim, Perak, Malaysia.
Volume: 10
Issue: 2
Page: 498-505
Publish at: 2018-05-01

Securing Data Communication for Data Driven Applications Using End to End Encryption

10.11591/ijeecs.v10.i2.pp756-762
Subhi Almohtasib , Alaa H Al-Hamami
Many users of smartphones have secret data they want to save it on their devices. The probability of a device damage or stolen prevents them from saving data. Therefore, data driven applications used to save user’s data on a remote server. Protection of the data during its transmission considered as one of the success aspect for these applications. In this paper, an enhanced method for data encryption proposed which guarantees data secrecy during its transmission over network. User’s data encrypted before transmission using Base64 class. Data encryption and decryption implemented to halt reverse encryption process. In this way, data is transmitting in a secure and efficient manner accomplishing the main goal of Cryptography.
Volume: 10
Issue: 2
Page: 756-762
Publish at: 2018-05-01

Performance Comparison of Controllers for Suppressing the Structural Building Vibration

10.11591/ijeecs.v10.i2.pp537-544
Normaisharah Mamat , Fitri Yakub , Sheikh Ahmad Zaki Shaikh Salim , Mohamed Sukri Mat Ali
This paper presents the modelling and simulation of controllers for controlling the position of two degree of freedom (2 DOF) mass spring damper system. Proportional integral (PI), fuzzy logic controller (FLC) and sliding mode controller (SMC) are design to minimize the vibration of the system that represent as building structure towards earthquake. A structural building is simulate based on real earthquake occur in El Centro on May 1940. The algorithm for building structure, actuator and controller is derived. Matlab/Simulink is used to analyze the performance of controllers towards the vibration building structure. At the end of the study the time response for two story building for uncontrolled and controlled system is present. Besides, the result for limitation voltage for each controller is also analyse to determine the maximum voltage consume for the system. The simulation results show the comparison of the controllers’ performance in suppressing the building vibration. From performance analysis, SMC provides better performance compared to PI and FLC based on structural vibration reduction.
Volume: 10
Issue: 2
Page: 537-544
Publish at: 2018-05-01

A MIMO H-shape Dielectric Resonator Antenna for 4G Applications

10.11591/ijeecs.v10.i2.pp648-653
S. Salihah , M. H. Jamaluddin , R. Selvaraju , M. N. Hafiz
In this article, a Multiple-Input-Multiple-Output (MIMO) H-shape Dielectric Resonator Antenna (DRA) is designed and simulated at 2.6 GHz for 4G applications. The proposed structure consists of H-shape DRA ( =10) which is mounted on FR4 substrate ( =4.6), and feed by two different feeding mechanisms. First, microstrip with slot coupling as Port 1. Second, coaxial probe as Port 2. The electrical properties of the proposed MIMO H-shape DRA in term of return loss, bandwidth and gain are completely obtained by using CST Microwave Studio Suite Software. The simulated results demonstrated a return loss more than 20 dB, an impedance bandwidth of 26 % (2.2 – 2.9 GHz), and gain of 6.11 dBi at Port 1. Then, a return loss more than 20 dB, an impedance bandwidth of 13 % (2.2 – 2.7 GHz), and gain of 6.63 dBi at Port 2. Both ports indicated impedance bandwidth more than 10 %, return loss lower than 20 dB, and gain more than 10 dBi at 2.6 GHz. The simulated electrical properties of the proposed design show a good potential for LTE applications.
Volume: 10
Issue: 2
Page: 648-653
Publish at: 2018-05-01

Intelligent Packet Delivery in Router Using Structure Optimized Neural Network

10.11591/ijeecs.v10.i2.pp545-553
R. Deebalakshmi , V. L. Jyothi
The Internet itself is a worldwide network connecting millions of computers and less significant networks. Computers communicated by routers. Crucial the role of a router is to our technique of communicating and computing. Routers are situated at gateways, the spaces where two or more networks connect, and are the decisive device that keeps data flow between networks and keeps the networks connected to the Internet. When data is sent between places on one network or from one network to a second network the data is always seen and intended for to the proper place by the router. The router carries out this by using headers and routing tables to establish the best path for routing the data packets. This trim down the effectiveness of edge router only when the path engaged, it will enhanced by classification method, predictable classification methods like port based ,deep packet inspection and  statistical classification are give less precision. In this system structured optimized neural network is used for more precise organization. Classification output forwarded to router dynamically for intellectual packet delivery. The method will improve router competence by greater than before throughput and decreased latency.The Internet itself is a worldwide network connecting millions of computers and less significant networks. Computers communicated by routers. Crucial the role of a router is to our technique of communicating and computing. Routers are situated at gateways, the spaces where two or more networks connect, and are the decisive device that keeps data flow between networks and keeps the networks connected to the Internet. When data is sent between places on one network or from one network to a second network the data is always seen and intended for to the proper place by the router. The router carries out this by using headers and routing tables to establish the best path for routing the data packets. This trim down the effectiveness of edge router only when the path engaged, it will enhanced by classification method, predictable classification methods like port based ,deep packet inspection and  statistical classification are give less precision. In this system structured optimized neural network is used for more precise organization. Classification output forwarded to router dynamically for intellectual packet delivery. The method will improve router competence by greater than before throughput and decreased latency.
Volume: 10
Issue: 2
Page: 545-553
Publish at: 2018-05-01

Maximally Spatial-Disjoint Lightpaths in Optical Networks

10.11591/ijeecs.v10.i2.pp733-740
M. Waqar Ashraf , Sevia M. Idrus , Farabi Iqbal
Lightpaths enable end-to-end all-optical transmission between network nodes. For survivable routing, traffic is often carried on a primary lightpath, and rerouted to another disjointed backup lightpath in case of the failure of the primary lightpath. Though both lightpaths can be physically disjointed, they can still fail simultaneously if a disaster affects them simultaneously on the physical plane. Hence, we propose a routing algorithm for provisioning a pair of link-disjoint lightpaths between two network nodes such that the minimum spatial distance between them (while disregarding safe regions) is maximized. Through means of simulation, we show that our algorithm can provide higher survivability against spatial-based simultaneous link failures (due to the maximized spatial distance).
Volume: 10
Issue: 2
Page: 733-740
Publish at: 2018-05-01

High Potential of Magnet on the Performance of Dual Piezoelectric Fans in Electronics Cooling System

10.11591/ijeecs.v10.i2.pp469-479
Abdul Razak Fadhilah , Robiah Ahmad , Sarip Shamsul
Recently, piezoelectric fan has gained attention as potential active cooling method for electronics devices. Even though the piezoelectric requires high voltage, there are findings to overcome the shortcomings. Adding on a magnet at the tip of the piezoelectric fan to activate other magnetic passive fans is one of the methods to increase the total amplitude generated by the fans. This paper will discuss on the performance of integrated piezoelectric fan with passive fans (later refer to magnetic fans) to enhance the heat transfer in cooling system. A repulsive force produced by the magnets will cause the magnetic blades to oscillate together with the piezoelectric fan. The paper will focus on the optimization parameters of the magnets for selected dimension of piezoelectric fan. The parameters under investigation are the position of the magnet on the piezoelectric fan, number of magnets on each blades and orientation of blades with respect to adjacent blade. Results show that the magnet at middle location of extensive blade with double magnets generate the largest amplitude, 80% better than fan without magnet and for dual integrated piezoelectric fan with magnetic fan, radial orientation gives better result by 25%. By increasing the total amplitude using magnetic force, power consumption can be reduced while the heat transfer performance can be enhanced. it shows a good agreement for positive heat transfer and thermal resistance improvement compared to natural convection.
Volume: 10
Issue: 2
Page: 469-479
Publish at: 2018-05-01

Improving the Cost Factor of DLBCA Lightweight Block Cipher Algorithm

10.11591/ijeecs.v10.i2.pp786-791
Sufyan Salim Mahmood AlDabbagh , Alyaa Ghanim Sulaiman , Imad Fakhri Taha Al Shaikhli , Khalid Abdulkareem Al-Enezi , Abdulrahman Yousef Alenezi
The needing to secure information in restricted environments is very important so that lightweight block cipher algorithm is suitable for these environments. This paper improved DLBCA algorithm by decreasing the cost factor through using the less number of S-boxes. Also, differential and boomerang attacks have been applied in this paper. Finally, all the results have been presented
Volume: 10
Issue: 2
Page: 786-791
Publish at: 2018-05-01
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