Volume 9, Issue 1, January 2017

 

 

Relay Selection Based on Simultaneous Wireless Information and Power Transfer for Wireless Sensor Networks
 

Relay Selection Based on Simultaneous Wireless Information and Power Transfer for Wireless Sensor Networks

Pages: 1-5 (5) | [Full Text] PDF (344 KB)
S Mahama, DKP Asiedu
Department of Electronic Engineering, Hanbat Nation University, 125, Dongseo-daero, Yuseong-gu, Daejeon, South Korea

Abstract -
Simultaneous wireless information and power transfer (SWIPT) is a promising new solution to provide a perpetual lifetime for energy constrained nodes in wireless networks. In this paper, we consider a wireless sensor relay network, where relay nodes forward a radio frequency (RF) signal from a source node to a destination node by first harvesting energy from the RF signal. For multiple relay nodes, the relay that is preferred for information transmission does not necessarily coincide with the relay that has the maximum harvested energy. We propose relay selection schemes in order to obtain the best rate performance in the relaying SWIPT system. We derive analytic expressions for the outage probability in the delay-limited transmission mode with our relay selection schemes. The simulation results show that the throughput of the system increases as the number of relay nodes increase.
 
Index Terms - SWIPT, Amplify-and-forward Relay, Outage Probability, Throughput, Ergodic Capacity

Citation - S Mahama, DKP Asiedu. "Relay Selection Based on Simultaneous Wireless Information and Power Transfer for Wireless Sensor Networks." International Journal of Computer Engineering and Information Technology 9, no. 1 (2017): 1-5.

Comparison of Hierarchical and Non-Hierarchical Clustering Algorithms
 

Comparison of Hierarchical and Non-Hierarchical Clustering Algorithms

Pages: 6-14 (9) | [Full Text] PDF (701 KB)
FK Gulagiz, S Sahin
Department of Computer Engineering, Kocaeli University, Kocaeli, Izmit, 41380 Turkey

Abstract -
As a result of wide use of technology, large data volumes began to emerge. Analyzes on this big size data and obtain knowledge in it very difficult with simple methods. So data mining methods has risen. One of these methods is clustering. Clustering is an unsupervised data mining technique and groups data according to similarities between records. The goal of cluster analysis is finding subclasses that occur naturally in the data set. There are too many different methods improved for data clustering. Performance of these methods can be changed according to data set or number of records in dataset etc. In this study we evaluate clustering methods using different datasets. Results are compared by considering different parameters such as result similarity, number of steps, processing time etc. At the end of the study methods are also analyzed to show the appropriate data set conditions for each method.
 
Index Terms - Data Mining, Hierarchical Clustering, Non- Hierarchical Clustering, Centroid Similarity

Citation - FK Gulagiz, S Sahin. "Comparison of Hierarchical and Non-Hierarchical Clustering Algorithms." International Journal of Computer Engineering and Information Technology 9, no. 1 (2017): 6-14.

Multi-word Aspect Term Extraction Using Turkish User Reviews
 

Multi-word Aspect Term Extraction Using Turkish User Reviews

Pages: 15-23 (9) | [Full Text] PDF (498 KB)
E Ekinci, H Turkmen, SI Omurca
Department of Computer Engineering, Kocaeli University, Kocaeli, Izmit, 41380 Turkey

Abstract -
Nowadays, when an individual wants to buy any product or a company wants to take the pulse of public opinion about its product, user reviews of this product have become a valuable source of information. As a consequence of that, aspect based sentiment analysis has become popular research field which has also attracted the attention of researchers. In this study, we devised a method which extracts multi-word aspects from the Turkish user reviews. To investigate the reliability and the performance of the system, the frequency basis method based on N-gram by unifying finite state automata which are set for the recognition of the Turkish grammar rules were preferred. The success of the system was measured by using cell phones and by using hotel reviews. As a result, the success obtained is averagely 82% for cell phone domain and averagely 79% for hotel domain.
 
Index Terms - Aspect Bases Sentiment Analysis, Aspect Extraction, Multi-word Aspect Extraction, Finite State Automata

Citation - E Ekinci, H Turkmen, SI Omurca. "Multi-word Aspect Term Extraction Using Turkish User Reviews." International Journal of Computer Engineering and Information Technology 9, no. 1 (2017): 15-23.