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 -
Along with the developments in the field of information technologies, the data in the electronic environment is increasing. Data mining methods are needed to obtain useful information for users in electronic environment. One of these methods, clustering methods, aims to group data according to common properties. This grouping is often based on the distance between the data. Clustering methods are divided into hierarchical and non-hierarchical methods according to the fragmentation technique of clusters. The success of both types of clustering methods varies according to the data set applied. In this study, both types of methods were tested on different type of data sets. Selected methods compared according to five different evaluation metrics. The results of the analysis are presented comparatively at the end of the study and which methods are more convenient for data set is explained.
 
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.