• The KIPS Transactions:PartD
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• v.10D no.2
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• pp.343-350
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• 2003

This paper presents a new agent which convert HTML contents to VXML contents automatically for voice services via web. In this paper, I propose an interactive hybrid sequential contents selection method to select desired contents fast and robustly from known web pages. It uses real time structural features as well as embedded text and/or priori structural knowledge such as link symbol position. To verify its effectiveness, a full agent system is implemented and tested. The method reflects user intention more accurately than conventional selections using structural features and is more robust to variations of HTML programming techniques. The agent is fast and has less computational burden than methods use XML or XHTML conversion as intermediate stage.

• Advances in materials Research
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• v.9 no.1
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• pp.1-14
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• 2020

The hybrid method of three-dimensional ion implantation and electric arc is presented as a novel plasma-ion technique that allows by means of high voltage pulsed and electric arc discharges, the bombardment of non-metallic and metallic ions then implanting upon the surface of a solid surface, especially out of metallic nature. In this study AISI/SAE 4140 samples, a tool type steel broadly used in the industry due to its acceptable physicochemical properties, were metallographically prepared then surface modified by implanting titanium and simultaneously titanium and nitrogen particles during 5 min and 10 min. The effect of the ion implantation technique over the substrate surface was analysed by characterization and electrochemical techniques. From the results, the formation of Ti micro-droplets upon the surface after the implantation treatment were observed by micrographs obtained by scanning electron microscopy. The presence of doping particles on the implanted substrates were detected by elemental analysis. The linear polarization resistance, potentiodynamic polarization and total porosity analysis demonstrated that the samples whose implantation treatment with Ti ions for 10 min, offer a better protection against the corrosion compared with non-implanted substrates and implanted at the different conditions in this study.

• Journal of Korea Multimedia Society
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• v.22 no.2
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• pp.260-270
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• 2019

As the growth of developing Islamic countries, Muslims are into the world. The most important thing for Muslims to purchase food, ingredient, cosmetics and other products are whether they were certified as 'Halal'. With the increasing number of Muslim tourists and residents in Korea, Halal restaurants and markets are on the rise. However, the service that provides information on Halal restaurants and markets in Korea is very limited. Especially, the application of recommendation system technology is effective to provide Halal restaurant information to users efficiently. The profiling of Halal restaurant information should be preceded by design of recommendation system, and design of recommendation algorithm is most important part in designing recommendation system. In this paper, an Intelligent Recommendation Service system for offering Halal food (IRSH) based on dynamic profiles was proposed. The proposed system recommend a customized Halal restaurant, and proposed recommendation algorithm uses hybrid filtering which is combined by content-based filtering, collaborative filtering and location-based filtering. The proposed algorithm combines several filtering techniques in order to improve the accuracy of recommendation by complementing the various problems of each filtering. The experiment of performance evaluation for comparing with existed restaurant recommendation system was proceeded, and result that proposed IRSH increase recommendation accuracy using Halal contents was deducted.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.87-96
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• 2021

The demand for e-learning through video lectures is rapidly increasing due to its diverse advantages over the traditional learning methods. This led to massive volumes of web-based lecture videos. Indexing and retrieval of a lecture video or a lecture video topic has thus proved to be an exceptionally challenging problem. Many techniques listed by literature were either visual or audio based, but not both. Since the effects of both the visual and audio components are equally important for the content-based indexing and retrieval, the current work is focused on both these components. A framework for automatic topic-based indexing and search depending on the innate content of the lecture videos is presented. The text from the slides is extracted using the proposed Merged Bounding Box (MBB) text detector. The audio component text extraction is done using Google Speech Recognition (GSR) technology. This hybrid approach generates the indexing keywords from the merged transcripts of both the video and audio component extractors. The search within the indexed documents is optimized based on the Naïve Bayes (NB) Classification and K-Means Clustering models. This optimized search retrieves results by searching only the relevant document cluster in the predefined categories and not the whole lecture video corpus. The work is carried out on the dataset generated by assigning categories to the lecture video transcripts gathered from e-learning portals. The performance of search is assessed based on the accuracy and time taken. Further the improved accuracy of the proposed indexing technique is compared with the accepted chain indexing technique.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.556-564
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• 2021

Numerous spatial and transform-domain-based conventional denoising algorithms struggle to keep critical and minute structural features of the image, especially at high noise levels. Although neural network approaches are effective, they are not always reliable since they demand a large quantity of training data, are computationally complicated, and take a long time to construct the model. A new framework of enhanced hybrid filtering is developed for denoising color images tainted by additive white Gaussian Noise with the goal of reducing algorithmic complexity and improving performance. In the first stage of the proposed approach, the noisy image is refined using a high-dimensional non-local means filter based on Principal Component Analysis, followed by the extraction of the method noise. The wavelet transform and SURE Shrink techniques are used to further culture this method noise. The final denoised image is created by combining the results of these two steps. Experiments were carried out on a set of standard color images corrupted by Gaussian noise with multiple standard deviations. Comparative analysis of empirical outcome indicates that the proposed method outperforms leading-edge denoising strategies in terms of consistency and performance while maintaining the visual quality. This algorithm ensures homogeneous noise reduction, which is almost independent of noise variations. The power of both the spatial and transform domains is harnessed in this multi realm consolidation technique. Rather than processing individual colors, it works directly on the multispectral image. Uses minimal resources and produces superior quality output in the optimal execution time.

• Steel and Composite Structures
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• v.30 no.3
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• pp.231-251
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• 2019

In the present study, a numerical and experimental investigation has been carried out on the seismic behavior of RC columns of a bridge which damaged under corrosive environments and retrofitted by various techniques including combined application of CFRP sheets and steel profiles. A novel hybrid retrofitting procedure, including the application of inner steel profiles and outer peripheral CFRP sheets, has been proposed for strengthening purpose. Seven large-scale RC columns of a Girder Bridge have been tested in the laboratory under the influence of simultaneous application of constant axial load and the lateral cyclic displacements. Having verified the finite element modeling, using ABAQUS software, the effects of important parameters such as the corrosion percentage of steel rebars and the number of CFRP layers have been evaluated. Based on the results, retrofitting of RC columns of the bridge with the proposed technique was effective in improving some measures of structural performance such as lateral strength degradation and higher energy absorption capability. However, the displacement ductility was not considerably improved whereas the elastic stiffness of the specimens has been increased.

• Journal of Power Electronics
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• v.19 no.1
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• pp.254-264
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• 2019

This paper proposes an indirect current control technique based on a proportional resonant (PR) approach for the seamless mode transfer of utility interactive inverters. Direct-current and voltage hybrid control methods have been used for inverter control under grid-connected and islanded modes. A large bandwidth can be selected due to the structure of single-loop control. However, this results in poor dynamic transients due to sudden changes of the controller during mode changes. Therefore, inverter control based on indirect current is proposed to improve the dynamic transients by consistently controlling the output voltage under all of the operation modes. A PR-based indirect current control topology is used in this study to maintain the load voltage quality under all of the modes. The design processes of the PR-based triple loop are analyzed in detail while considering the system stability and dynamic transients. The mode transfer techniques are described in detail for both sudden unintentional islanding and islanded mode voltage quality improvements. In addition, they are described using the proposed indirect control structure. The proposed method is verified by the PSiM simulations and laboratory-scale VDER-HILS experiments.

• Nuclear Engineering and Technology
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• v.50 no.7
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• pp.1006-1016
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• 2018

Since the early forties, researchers from around the world have been studying the phenomenon of deadtime in radiation detectors. Many have attempted to develop models to represent this phenomenon. Two highly idealized models; paralyzable and non-paralyzable are commonly used by most individuals involved in radiation measurements. Most put little thought about the operating conditions and applicability of these ideal models for their experimental conditions. So far, there is no general agreement on the applicability of any given model for a specific detector under specific operating conditions, let alone a universal model for all detectors and all operating conditions. Further the related problem of pile-up is often confused with the deadtime phenomenon. Much work, is needed to devise a generalized and practical solution to these related problems. Many methods have been developed to measure and compensate for the detector deadtime count loss, and many researchers have addressed deadtime and pulse pile-up. The goal of this article is to summarize the state of science of deadtime; measurement and compensation techniques as proposed by some of the most significant work on these topics and to review the deadtime correction models applicable to present day radiation detection systems.

• Fashion & Textile Research Journal
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• v.23 no.4
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• pp.480-490
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• 2021

Sales forecasting is crucial for many retail operations. For apparel retailers, accurate sales forecast for the next season is critical to properly manage inventory and plan their supply chains. The challenge in this increases because apparel products are always new for the next season, have numerous variations, short life cycles, long lead times, and seasonal trends. In this study, a sales forecasting model is proposed for apparel products using machine learning techniques. The sales data pertaining to outerwear items for four years were collected from a Korean sports brand and filtered with outliers. Subsequently, the data were standardized by removing the effects of exogenous variables. The sales patterns of outerwear items were clustered by applying K-means clustering, and outerwear attributes associated with the specific sales-pattern type were determined by using a decision tree classifier. Six types of sales pattern clusters were derived and classified using a hybrid model of clustering and decision tree algorithm, and finally, the relationship between outerwear attributes and sales patterns was revealed. Each sales pattern can be used to predict stock-keeping-unit-level sales based on item attributes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.96-98
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• 2014

Wireless Sensor Network(WSN) is a wireless real-time information(Acquired from the sensor nodes that have the computing power and wireless communication capabilities.) collected, and to take advantage of processing techniques. Currently it is very diverse, such as environmental monitoring, health care, security, smart home, smart grid applications is that. Thus it is required in the wireless sensor network, the algorithm for the efficient use of the limited energy capacity. Suggested by the algorithm for selecting a cluster head node for a hybrid type and clustered, by comparing the amount of energy remaining and a connection between the nodes In this paper, we aim to increase efficiency and accuracy of the wireless sensor network.