• The KIPS Transactions:PartC
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• v.16C no.6
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• pp.717-724
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• 2009

The most important issue for successful deployment of IPTV service is the service quality. In this paper, we first choose critical quality metrics belonging to each layer of IPTV service transmission architecture and then analyze the relation between the quality parameters. For this purpose, we implement a test network that emulates the most practical environment in which IPTV service is provided and repeat measurements on the test network for the chosen metrics. Based on the analysis result, it is shown that packet losses have greater effect on the video quality of IPTV service comparing to delay and jitter.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2456-2467
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• 2018

Wireless multimedia sensor networks (WMSNs) require real-time quality-of-service (QoS) guarantees to be provided by the network. The end-to-end delay is very critical metric for QoS guarantees in WMSNs. In WMSNs, due to the transmission errors incurred over wireless channels, it is difficult to obtain reliable delivery of data in conjunction with low end-to-end delay. In order to improve the end-to-end delay performance, the system has to drop few packets during network congestion. In this article, our proposal is based on optimization of end-to end delay for WMSNs. We optimize end-to-end delay constraint by assuming that each packet is allowed fixed number of retransmissions. To optimize the end-to-end delay, first, we compute the performance measures of the system, such as end-to-end delay and reliability for different network topologies (e.g., linear topology, tree topology) and against different choices of system parameters (e.g., data rate, number of nodes, number of retransmissions). Second, we study the impact of the end-to-end delay and packet delivery ratio on indoor and outdoor environments in WMSNs. All scenarios are simulated with multiple run-times by using network simulator-2 (NS-2) and results are evaluated and discussed.

• JSTS:Journal of Semiconductor Technology and Science
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• v.17 no.1
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• pp.65-78
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• 2017

Single Event Transient has a critical impact on highly integrated logic circuits which are currently common in various commercial and consumer electronic devices. Reliability against the soft and intermittent faults will become a key metric to evaluate such complex system on chip designs. Our previous work analyzing soft errors was focused on parallelizing and optimizing error propagation procedures for individual transient faults on logic and sequential cells. In this paper, we present a new propagation technique where a fault binary decision diagram (BDD) continues to merge every new fault generated from the subsequent logic gate traversal. BDD-based transient fault analysis has been known to provide the most accurate results that consider both electrical and logical properties for the given design. However, it suffers from a limitation in storing and handling BDDs that can be increased in size and operations by the exponential order. On the other hand, the proposed method requires only a visit to each logic gate traversal and unnecessary BDDs can be removed or reduced. This results in an approximately 20-200 fold speed increase while the existing parallelized procedure is only 3-4 times faster than the baseline algorithm.

• Journal of Communications and Networks
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• v.13 no.2
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• pp.149-159
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• 2011

In this paper, we study the problem of how to design a medical-grade wireless local area network (WLAN) for healthcare facilities. First, unlike the IEEE 802.11e MAC, which categorizes traffic primarily by their delay constraints, we prioritize medical applications according to their medical urgency. Second, we propose a mechanism that can guarantee absolute priority to each traffic category, which is critical for medical-grade quality of service (QoS), while the conventional 802.11e MAC only provides relative priority to each traffic category. Based on absolute priority, we focus on the performance of real-time patient monitoring applications, and derive the optimal contention window size that can significantly improve the throughput performance. Finally, for proper performance evaluation from a medical viewpoint, we introduce the weighted diagnostic distortion (WDD) as a medical QoS metric to effectively measure the medical diagnosability by extracting the main diagnostic features of medical signal. Our simulation result shows that the proposed mechanism, together with medical categorization using absolute priority, can significantly improve the medical-grade QoS performance over the conventional IEEE 802.11e MAC.

• Journal of Communications and Networks
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• v.16 no.4
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• pp.371-377
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• 2014

Localized topology control is attractive for obtaining reduced network graphs with desirable features such as sparser connectivity and reduced transmit powers. In this paper, we focus on studying how to prolong network lifetime in the context of localized topology control for wireless multi-hop networks. For this purpose, we propose an energy efficient localized topology control algorithm. In our algorithm, each node is required to maintain its one-hop neighborhood topology. In order to achieve long network lifetime, we introduce a new metric for characterizing the energy criticality status of each link in the network. Each node independently builds a local energy-efficient spanning tree for finding a reduced neighbor set while maximally avoiding using energy-critical links in its neighborhood for the local spanning tree construction. We present the detailed design description of our algorithm. The computational complexity of the proposed algorithm is deduced to be O(mlog n), where m and n represent the number of links and nodes in a node's one-hop neighborhood, respectively. Simulation results show that our algorithm significantly outperforms existing work in terms of network lifetime.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.513-522
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• 2016

We propose a mechanism for monitoring load in quality of service (QoS)-enabled wireless networks and show how it can be used for network management as well as for dynamic pricing. Mobile network traffic, especially video, has grown exponentially over the last few years and it is anticipated that this trend will continue into the future. Driving factors include the availability of new affordable, smart devices, such as smart-phones and tablets, together with the expectation of high quality user experience for video as one would obtain at home. Although new technologies such as long term evolution (LTE) are expected to help satisfy this demand, the fact is that several other mechanisms will be needed to manage overload and congestion in the network. Therefore, the efficient management of the expected huge data traffic demands is critical if operators are to maintain acceptable service quality while making a profit. In the current work, we address this issue by first investigating how the network load can be accurately monitored and then we show how this load metric can then be used to provide creative pricing plans. In addition, we describe its applications to features like traffic offloading and user satisfaction tracking.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.225-233
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• 2022

The recent outbreak of corona virus (COVID-19) infectious disease had made its forecasting critical cornerstones in most scientific studies. This study adopts a machine learning based time series model - Auto Regressive Integrated Moving Average (ARIMA) model to forecast COVID-19 confirmed cases in Botswana over 60 days period. Findings of the study show that COVID-19 confirmed cases in Botswana are steadily rising in a steep upward trend with random fluctuations. This trend can also be described effectively using an additive model when scrutinized in Seasonal Trend Decomposition method by Loess. In selecting the best fit ARIMA model, a Grid Search Algorithm was developed with python language and was used to optimize an Akaike Information Criterion (AIC) metric. The best fit ARIMA model was determined at ARIMA (5, 1, 1), which depicted the least AIC score of 3885.091. Results of the study proved that ARIMA model can be useful in generating reliable and volatile forecasts that can used to guide on understanding of the future spread of infectious diseases or pandemics. Most significantly, findings of the study are expected to raise social awareness to disease monitoring institutions and government regulatory bodies where it can be used to support strategic health decisions and initiate policy improvement for better management of the COVID-19 pandemic.

• Journal of Internet Computing and Services
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• v.6 no.4
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• pp.37-46
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• 2005

Computer are being used in an increasingly wide variety of application areas, and their correct operation is often critical for business success and humasn safety. Developing high quality software products is therefore of prime important. The recent game software become popular, so we are interest in the game software testing. According to the kinds of game software, because it has the different characters, so game software testing is very difficult. According to enviroment change, Recently, online game is popular, so online game trade in the world market. In the company, developers try to develop the reliable game software. But we can experience many fault of game software in spite of the beta testing. Especially, Testing is very difficult on the game software because of various environment and functionality. We tried the survey for game user. In this paper, we study the quality testing metric of game software fault basis on the ISO/IEC 9126. Also, we consist of the check list of game software a point of view user. It apply for the reliability testing metrics of ISO/IEC 9126.

• Smart Structures and Systems
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• v.16 no.2
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• pp.243-262
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• 2015

Optimal sensor placement (OSP) is a critical issue in construction and implementation of a sophisticated structural health monitoring (SHM) system. The uncertainties in the identified structural parameters based on the measured data may dramatically reduce the reliability of the condition evaluation results. In this paper, the information entropy, which provides an uncertainty metric for the identified structural parameters, is adopted as the performance measure for a sensor configuration, and the OSP problem is formulated as the multi-objective optimization problem of extracting the Pareto optimal sensor configurations that simultaneously minimize the appropriately defined information entropy indices. The nondirective movement glowworm swarm optimization (NMGSO) algorithm (based on the basic glowworm swarm optimization (GSO) algorithm) is proposed for identifying the effective Pareto optimal sensor configurations. The one-dimensional binary coding system is introduced to code the glowworms instead of the real vector coding method. The Hamming distance is employed to describe the divergence of different glowworms. The luciferin level of the glowworm is defined as a function of the rank value (RV) and the crowding distance (CD), which are deduced by non-dominated sorting. In addition, nondirective movement is developed to relocate the glowworms. A numerical simulation of a long-span suspension bridge is performed to demonstrate the effectiveness of the NMGSO algorithm. The results indicate that the NMGSO algorithm is capable of capturing the Pareto optimal sensor configurations with high accuracy and efficiency.

• Journal of Computational Design and Engineering
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• v.3 no.1
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• pp.37-52
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• 2016

To injection mould polymers, designing mould is a key task involving several critical decisions with direct implications to yield quality, productivity and frugality. One prominent decision among them is specifying sprue-bush conduit expansion as it significantly influences overall injection moulding; abstruseness anguish in its design criteria deceives direct determination. Intuitively designers decide it wisely and then exasperate by optimising or manipulating processing parameters. To overwhelm that anomaly this research aims at proposing an ideal design criteria holistically for all polymeric materials also tend as a functional assessment metric towards perfection i.e., criteria to specify sprue conduit size before mould development. Accordingly, a priori analytical criterion was deduced quantitatively as expansion ratio from ubiquitous empirical relationships specifically a.k.a an exclusive expansion angle imperatively configured for injectant properties. Its computational intelligence advantage was leveraged to augment functionality of perfectly injecting into an impression gap, while synchronising both injector capacity and desired moulding features. For comprehensiveness, it was continuously sensitised over infinite scale as an explicit factor dependent on in-situ spatio-temporal injectant state perplexity with discrete slope and altitude for each polymeric character. In which congregant ranges of apparent viscosity and shear thinning index were conceived to characteristically assort most thermoplastics. Thereon results accorded aggressive conduit expansion widening for viscous incrust, while a very aggressive narrowing for shear thinning encrust; among them apparent viscosity had relative dominance. This important rationale would certainly form a priori design basis as well diagnose filling issues causing several defects. Like this the proposed generic design criteria, being simple would immensely benefit mould designers besides serve as an inexpensive preventive cliché to moulders. Its adaption ease to practice manifests a hope of injection moulding extremely alluring polymers. Therefore, we concluded that appreciating injectant's polymeric character to design exclusive sprue bush offers a definite a priori advantage.