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Journal of ICT Research and Applications
Published by Institut Teknologi Bandung
ISSN : 23375787     EISSN : 23385499     DOI : https://doi.org/10.5614/itbj.ict.res.appl.
Core Subject : Science,
Computer Science & IT
Journal of ICT Research and Applications welcomes full research articles in the area of Information and Communication Technology from the following subject areas: Information Theory, Signal Processing, Electronics, Computer Network, Telecommunication, Wireless & Mobile Computing, Internet Technology, Multimedia, Software Engineering, Computer Science, Information System and Knowledge Management.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 302 Documents
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Efficient CFO Compensation Method in Uplink OFDMA for Mobile WiMax Lakshmanan Muthukaruppan; Parthasharathi Mallick; Nithyanandan Lakshmanan; Sai Krishna Marepalli
Journal of ICT Research and Applications Vol. 10 No. 2 (2016)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2016.10.2.4

Abstract

Mobile WiMax uses Orthogonal Frequency Division Multiple Access (OFDMA) in uplink where synchronization is a complex task as each user presents a different carrier frequency offset (CFO). In the Data Aided Phase Incremental Technique (DA-PIT) estimation is performed after FFT operation to use the received frequency domain pilot subcarrier information. As estimation is done in the presence of noise, there exists some offset error, which is called residual frequency offset (RFO). The Simple Time Domain Multi User Interference Cancellation scheme (SI-MUIC) is a time domain approach which takes a longer time delay to compensate the CFO effect for the last user. Decorrelation-Successive Interference Cancellation (DC-SC) and Integrated Estimation and Compensation (IEC) are frequency domain approaches that compensate the CFO effect with a more complex method for ICI cancellation. The Modified Integrated Estimation and Compensation technique (Modified IEC) is proposed for better residual CFO compensation. The proposed technique has better performance due to its efficient suppression of ICI and MUI. The difference between the CFOs of two OFDMA symbols lies within the range of RFO that is not considered in the conventional compensation techniques, such as the SI-MUIC, DC-SC and IEC compensation techniques.
NORM Technique based PAPR Reduction in MC-CDMA Systems Noor Mohammed Vali Mohamad; P. S Mallick; L. Nithyanandan; Srujan Dharmagadda; M. Surendrakumar; M. Palanivelan
Journal of ICT Research and Applications Vol. 9 No. 2 (2015)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2015.9.2.2

Abstract

Multicarrier code division multiple access (MC-CDMA) is one of the promising technologies for future-generation wireless networks. It offers high data rates, protection against frequency-selective fading and efficient utilization of the spectrum. The peak to average power ratio (PAPR) is very high in MCCDMA systems. The partial transmit sequence technique (PTS) and the selective mapping technique (SLM) reduce the PAPR with more computational complexity. In this study, the NORM technique was used for PAPR reduction in MC-CDMA systems. The performance of NORM was analyzed with PTS and SLM in terms of cumulative complementary distribution, power saving gain, amplifier efficiency, computational complexity and bit error rate. Simulation results showed that NORM has better PAPR reduction with less computational complexity.
SINR-based Network Selection for Optimization in Heterogeneous Wireless Networks (HWNs) Abubakar M. Miyim; Mahamod Ismail; Rosdiadee Nordin
Journal of ICT Research and Applications Vol. 9 No. 2 (2015)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2015.9.2.3

Abstract

To guarantee the phenomenon of "Always Best Connection" in heterogeneous wireless networks, a vertical handover optimization is necessary to realize seamless mobility. Received signal strength (RSS) from the user equipment (UE) contains interference from surrounding base stations, which happens to be a function of the network load of the nearby cells. An expression is derived for the received SINR (signal to interference and noise ratio) as a function of traffic load in interfering cells of data networks. A better estimate of the UE SINR is achieved by taking into account the contribution of inter-cell interference. The proposed scheme affords UE to receive high throughput with less data rate, and hence benefits users who are located far from the base station. The proposed scheme demonstrates an improved throughput between the serving base station and the cell boundary.
VLSI Architecture for Configurable and Low-Complexity Design of Hard-Decision Viterbi Decoding Algorithm Rachmad Vidya Wicaksana Putra; Trio Adiono
Journal of ICT Research and Applications Vol. 10 No. 1 (2016)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2016.10.1.5

Abstract

Convolutional encoding and data decoding are fundamental processes in convolutional error correction. One of the most popular error correction methods in decoding is the Viterbi algorithm. It is extensively implemented in many digital communication applications. Its VLSI design challenges are about area, speed, power, complexity and configurability. In this research, we specifically propose a VLSI architecture for a configurable and low-complexity design of a hard-decision Viterbi decoding algorithm. The configurable and low-complexity design is achieved by designing a generic VLSI architecture, optimizing each processing element (PE) at the logical operation level and designing a conditional adapter. The proposed design can be configured for any predefined number of trace-backs, only by changing the trace-back parameter value. Its computational process only needs N + 2 clock cycles latency, with N is the number of trace-backs. Its configurability function has been proven for N = 8, N = 16, N = 32 and N = 64. Furthermore, the proposed design was synthesized and evaluated in Xilinx and Altera FPGA target boards for area consumption and speed performance.
Topic Modeling in Sentiment Analysis: A Systematic Review Toqir Ahmad Rana; Yu-N Cheah; Sukumar Letchmunan
Journal of ICT Research and Applications Vol. 10 No. 1 (2016)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2016.10.1.6

Abstract

With the expansion and acceptance of Word Wide Web, sentiment analysis has become progressively popular research area in information retrieval and web data analysis. Due to the huge amount of user-generated contents over blogs, forums, social media, etc., sentiment analysis has attracted researchers both in academia and industry, since it deals with the extraction of opinions and sentiments. In this paper, we have presented a review of topic modeling, especially LDA-based techniques, in sentiment analysis. We have presented a detailed analysis of diverse approaches and techniques, and compared the accuracy of different systems among them. The results of different approaches have been summarized, analyzed and presented in a sophisticated fashion. This is the really effort to explore different topic modeling techniques in the capacity of sentiment analysis and imparting a comprehensive comparison among them.
Rhetorical Sentences Classification Based on Section Class and Title of Paper for Experimental Technical Papers Afrida Helen; Ayu Purwarianti; Dwi H. Widyantoro
Journal of ICT Research and Applications Vol. 9 No. 3 (2015)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2015.9.3.5

Abstract

Rhetorical sentence classification is an interesting approach for making extractive summaries but this technique still needs to be developed because the performance of automatic rhetorical sentence classification is still poor. Rhetorical sentences are sentences that contain rhetorical words or phrases. Rhetorical sentences not only appear in the contents of a paper but also in the title. In this study, features related to section class and title class that have been proposed in a previous research were further developed. Our method uses different techniques to reach automatic section class extraction for which we introduce new, format-based features. Furthermore, we propose automatic rhetoric phrase extraction from the title. The corpus we used was a collection of technical-experimental scientific papers. Our method uses the Support Vector Machine (SVM) algorithm and the Naïve Bayesian algorithm for classification. The four categories used were: Problem, Method, Data, and Result. It was hypothesized that these features would be able to improve classification accuracy compared to previous methods. The F-measure for these categories reached up to 14%. 
Iris Segmentation using Gradient Magnitude and Fourier Descriptor for Multimodal Biometric Authentication System Defiana Sulaeman; Anto Satriyo Nugroho; Maulahikmah Galinium
Journal of ICT Research and Applications Vol. 10 No. 3 (2016)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2016.10.3.2

Abstract

Perfectly segmenting the area of the iris is one of the most important steps in iris recognition. There are several problematic areas that affect the accuracy of the iris segmentation step, such as eyelids, eyelashes, glasses, pupil (due to less accurate iris segmentation), motion blur, and lighting and specular reflections. To solve these problems, gradient magnitude and Fourier descriptor are employed to do iris segmentation in the proposed Multimodal Biometric Authentication System (MBAS). This approach showed quite promising results, i.e. an accuracy rate of 97%. The result of the iris recognition system was combined with the result of an open-source fingerprint recognition system to develop a multimodal biometrics authentication system. The results of the fusion between iris and fingerprint authentication were 99% accurate. Data from Multimedia Malaysia University (MMUI) and our own prepared database, the SGU-MB-1 dataset, were used to test the accuracy of the proposed system.
Dynamic Path Planning for Mobile Robots with Cellular Learning Automata Judhi Santoso; Bambang Riyanto; Widyawardhana Adiprawita
Journal of ICT Research and Applications Vol. 10 No. 1 (2016)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2016.10.1.1

Abstract

In this paper we propose a new approach to path planning for mobile robots with cellular automata and cellular learning automata. We divide the planning into two stages. In the first stage, global path planning is performed by cellular automata from an initial position to a goal position. In this stage, the minimum distance is computed. To compute the path, we use a particular two-dimensional cellular automata rule. The process of computation is performed using simple arithmetic operations, hence it can be done efficiently. In the second stage, local planning is used to update the global path. This stage is required to adapt to changes in a dynamic environment. This planning is implemented using cellular learning automata to optimize performance by collecting information from the environment. This approach yields a path that stays near to the obstacles and therefore the total time and distance to the goal can be optimized.
Voting-based Classification for E-mail Spam Detection Bashar Awad Al-Shboul; Heba Hakh; Hossam Faris; Ibrahim Aljarah; Hamad Alsawalqah
Journal of ICT Research and Applications Vol. 10 No. 1 (2016)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2016.10.1.3

Abstract

The problem of spam e-mail has gained a tremendous amount of attention. Although entities tend to use e-mail spam filter applications to filter out received spam e-mails, marketing companies still tend to send unsolicited e-mails in bulk and users still receive a reasonable amount of spam e-mail despite those filtering applications. This work proposes a new method for classifying e-mails into spam and non-spam. First, several e-mail content features are extracted and then those features are used for classifying each e-mail individually. The classification results of three different classifiers (i.e. Decision Trees, Random Forests and k-Nearest Neighbor) are combined in various voting schemes (i.e. majority vote, average probability, product of probabilities, minimum probability and maximum probability) for making the final decision. To validate our method, two different spam e-mail collections were used.
High Performance CDR Processing with MapReduce Mulya Agung; Achmad Imam Kistijantoro
Journal of ICT Research and Applications Vol. 10 No. 2 (2016)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2016.10.2.1

Abstract

A call detail record (CDR) is a data record produced by telecommunication equipment consisting of call detail transaction logs. It contains valuable information for many purposes in several domains, such as billing, fraud detection and analytical purposes. However, in the real world these needs face a big data challenge. Billions of CDRs are generated every day and the processing systems are expected to deliver results in a timely manner. The capacity of our current production system is not enough to meet these needs. Therefore a better performing system based on MapReduce and running on Hadoop cluster was designed and implemented. This paper presents an analysis of the previous system and the design and implementation of the new system, called MS2. In this paper also empirical evidence is provided to demonstrate the efficiency and linearity of MS2. Tests have shown that MS2 reduces overhead by 44% and speeds up performance nearly twice compared to the previous system. From benchmarking with several related technologies in large-scale data processing, MS2 was also shown to perform better in the case of CDR batch processing.  When it runs on a cluster consisting of eight CPU cores and two conventional disks, MS2 is able to process 67,000 CDRs/second.

Page 14 of 31 | Total Record : 302

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