• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2513-2530
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• 2021

With the fast development of information and communication technologies, video streaming services and applications are increasing rapidly. However, the network condition is volatile. In order to provide users with better quality of service, it is necessary to develop an accurate and low-complexity model for Quality of Experience (QoE) prediction of time-varying video. Memory effects refer to the psychological influence factor of historical experience, which can be taken into account to improve the accuracy of QoE evaluation. In this paper, we design subjective experiments to explore the impact of Short-Term Memory (STM) on QoE. The experimental results show that the user's real-time QoE is influenced by the duration of previous viewing experience and the expectations generated by STM. Furthermore, we propose analytical models to determine the relationship between intrinsic video quality, expectation and real-time QoE. The proposed models have better performance for real-time QoE prediction when the video is transmitted in a fluctuate network. The models are capable of providing more accurate guidance for improving the quality of video streaming services.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.46-63
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• 2024

One of the biggest dangers in the globe is water contamination. Water is a necessity for human survival. In most cities, the digging of borewells is restricted. In some cities, the borewell is allowed for only drinking water. Hence, the scarcity of drinking water is a vital issue for industries and villas. Most of the water sources in and around the cities are also polluted, and it will cause significant health issues. Real-time quality observation is necessary to guarantee a secure supply of drinking water. We offer a model of a low-cost system of monitoring real-time water quality using IoT to address this issue. The potential for supporting the real world has expanded with the introduction of IoT and other sensors. Multiple sensors make up the suggested system, which is utilized to identify the physical and chemical features of the water. Various sensors can measure the parameters such as temperature, pH, and turbidity. The core controller can process the values measured by sensors. An Arduino model is implemented in the core controller. The sensor data is forwarded to the cloud database using a WI-FI setup. The observed data will be transferred and stored in a cloud-based database for further processing. It wasn't easy to analyze the water quality every time. Hence, an Optimized Neural Network-based automation system identifies water quality from remote locations. The performance of the feed-forward neural network classifier is further enhanced with a hybrid GA- PSO algorithm. The optimized neural network outperforms water quality prediction applications and yields 91% accuracy. The accuracy of the developed model is increased by 20% because of optimizing network parameters compared to the traditional feed-forward neural network. Significant improvement in precision and recall is also evidenced in the proposed work.

• Proceedings of the Korean Society for Quality Management Conference
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• 2004.04a
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• pp.430-435
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• 2004

Nonhomogeneous Poisson Process is often used to model failure times which occurred in software reliability and hardware reliability models. It can be characterized by its intensity functions or mean value functions. Many parametric intensity models have been proposed to account for the failure mechanism in real situation. In this paper, we propose a Bayesian semiparametric approach based on beta-mixtures. Two real datasets are analyzed.

• Proceedings of the Korea Society for Simulation Conference
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• 1998.03a
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• pp.27-31
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• 1998

The growing usage of multimedia communication applications with specific bandwidth and real-time delivery requirements has created the needs for quality of service(QoS). In response to the growing demand for an integrated services, the Reservation Protocol(RSVP) has been designed to exchange resource reservation among routers in the internet. RSVP protocol provides the quality of service for real-time applications but the network efficiency is reduced because of the limited bandwidth. In order to use network resources efficiently. We compare the resource efficiency of traditional reservation methods with that of the proposed method and evaluate the performance of the internet phone.

• Proceedings of the Korean Society for Quality Management Conference
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• 2006.04a
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• pp.469-472
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• 2006

In this thesis, We analyzed success enterprise case which is well worked by knowledge management and is gained effect results. We searched key factor for success knowledge management and found problem which is able to happen when is introduced by success enterprise in knowledge management. We applied to in franchies real field with key factor found above results and experimented others real fields.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.606-611
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• 2002

Welding using lasers can be mass-produced in high speed. In the laser welding, performing real-time monitoring system of the welding quality is very important in enhancing the efficiency of welding. In this study, the plasma and molten metal which are generated during laser welding were measured using the UV sensor and IR sensors. The results of laser welding were classified into five categories such as optimal heat input, little low heat input, low heat input, partial joining due to gap mismatch, and nozzle deviation. Also, a system was formulated which uses the measured signals with a fuzzy pattern recognition method which is used to perform real-time evaluation of the welding quality and the defects which can occur in laser welding.

• The Journal of the Acoustical Society of Korea
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• v.27 no.3E
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• pp.84-94
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• 2008

Displacement estimation is a crucial step in ultrasonic strain imaging. The displacement between a pre- and postcompression signal in the current data window is estimated by first shifting the postcompression signal by the displacement obtained in the previous data window to reduce their decorrelation and then determining the remaining part of the displacement through autocorrelation and conversion of phase difference into time delay. However, since strain image quality tends to vary with the amount of compression applied, we propose two new methods for enhancing strain image quality, i.e., displacement normalization and adaptive persistence. Both in vitro and in vivo experiments are carried out to acquire ultrasound data and produce strain images in real time under the application of quasi static compression. The experimental results demonstrate that the methods are quite effective in improving strain image quality and thus can be applied to implementing an ultrasound elasticity imaging system that operates in real time.

• Journal of Korean Society for Quality Management
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• v.18 no.1
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• pp.21-28
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• 1990

In this paper, the capacity of system which provides the real time response call service to the customer is studied. The quality of call service depends on the response time of the service in the system. Therefore, the focus of this paper is to investigate the capacity of system under the restriction of response time. In this paper, the system is modeled by queueing network. The analytical method is applied to solve this queueing network. The solution of the model has product form solution. To get the reasonable capacities, nonlinear programming problem is formulated and is solved by GINO.

• International Journal of Korean Welding Society
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• v.3 no.1
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• pp.45-50
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• 2003

Welding using lasers can be mass-produced in high speed. In the laser welding, performing real-time monitoring system of the welding quality is very important in enhancing the efficiency of welding. In this study, the plasma and molten metal which are generated during laser welding were measured using the UV sensor and IR sensors. The results of laser welding were classified into five categories such as optimal heat input, little low heat input, low heat input, partial joining due to gap mismatch, and nozzle deviation. Also, a system was formulated which uses the measured signals with a fuzzy pattern recognition method which is used to perform real-time evaluation of the welding quality and the defects which can occur in laser welding.

• Journal of Korean Society for Quality Management
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• v.29 no.2
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• pp.1-16
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• 2001

The existing studies on measuring service quality have focused on moderating expectation. But one of real problems of measuring service quality is the assumption that customer's perceived quality is increased linearly by gap(performance-expectation). In this study, we assumed non-linearity of customer's perceived quality. The results of empirical study show that NL-SERVQUAL(suggested model in this paper) is better than SERVQUAL and SERVPERF.