• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.1-19
• /
• 2018

Since stock movements forecasting is an important issue both academically and practically, studies related to stock price prediction have been actively conducted. The stock price forecasting research is classified into structured data and unstructured data, and it is divided into technical analysis, fundamental analysis and media effect analysis in detail. In the big data era, research on stock price prediction combining big data is actively underway. Based on a large number of data, stock prediction research mainly focuses on machine learning techniques. Especially, research methods that combine the effects of media are attracting attention recently, among which researches that analyze online news and utilize online news to forecast stock prices are becoming main. Previous studies predicting stock prices through online news are mostly sentiment analysis of news, making different corpus for each company, and making a dictionary that predicts stock prices by recording responses according to the past stock price. Therefore, existing studies have examined the impact of online news on individual companies. For example, stock movements of Samsung Electronics are predicted with only online news of Samsung Electronics. In addition, a method of considering influences among highly relevant companies has also been studied recently. For example, stock movements of Samsung Electronics are predicted with news of Samsung Electronics and a highly related company like LG Electronics.These previous studies examine the effects of news of industrial sector with homogeneity on the individual company. In the previous studies, homogeneous industries are classified according to the Global Industrial Classification Standard. In other words, the existing studies were analyzed under the assumption that industries divided into Global Industrial Classification Standard have homogeneity. However, existing studies have limitations in that they do not take into account influential companies with high relevance or reflect the existence of heterogeneity within the same Global Industrial Classification Standard sectors. As a result of our examining the various sectors, it can be seen that there are sectors that show the industrial sectors are not a homogeneous group. To overcome these limitations of existing studies that do not reflect heterogeneity, our study suggests a methodology that reflects the heterogeneous effects of the industrial sector that affect the stock price by applying k-means clustering. Multiple Kernel Learning is mainly used to integrate data with various characteristics. Multiple Kernel Learning has several kernels, each of which receives and predicts different data. To incorporate effects of target firm and its relevant firms simultaneously, we used Multiple Kernel Learning. Each kernel was assigned to predict stock prices with variables of financial news of the industrial group divided by the target firm, K-means cluster analysis. In order to prove that the suggested methodology is appropriate, experiments were conducted through three years of online news and stock prices. The results of this study are as follows. (1) We confirmed that the information of the industrial sectors related to target company also contains meaningful information to predict stock movements of target company and confirmed that machine learning algorithm has better predictive power when considering the news of the relevant companies and target company's news together. (2) It is important to predict stock movements with varying number of clusters according to the level of homogeneity in the industrial sector. In other words, when stock prices are homogeneous in industrial sectors, it is important to use relational effect at the level of industry group without analyzing clusters or to use it in small number of clusters. When the stock price is heterogeneous in industry group, it is important to cluster them into groups. This study has a contribution that we testified firms classified as Global Industrial Classification Standard have heterogeneity and suggested it is necessary to define the relevance through machine learning and statistical analysis methodology rather than simply defining it in the Global Industrial Classification Standard. It has also contribution that we proved the efficiency of the prediction model reflecting heterogeneity.

• Journal of Popular Narrative
• /
• v.27 no.2
• /
• pp.215-262
• /
• 2021

This thesis focuses on Wandeuki and Elegant Lies - novels written by Kim Ryeo-reong and adapted into the film by Director Lee Han; this thesis analyzes the process of storytelling being transformed as the media is converted. Also, this thesis discusses cultural-political implications of transmedia storytelling where different narrative responses coexist concerning post-IMF family disorganization and "individualization." First of all, this thesis critically reviews existing discourses on the concept of transmedia storytelling and refers to 'transfictionality' the narratological concept of Marie-Laure Ryan in order to look into media conversion storytelling that starts from original novels. The novels Wandeuki and Elegant Lies show two aspects of "individualization" that adopts existential conditions of family disorganization. Wandeuki deviates from patriarchal family romance through self-discovery and exhibits loose family bond, which is something similar to companionship of close individuals. Elegant Lies shows individualization of pain by portraying a teenager who found herself completely isolated, while showing that it is impossible for the people left behind to mourn. On the other hand, director Lee Han's films and show stories in which family members, who are confronting family dissolution, rediscover and restore their families against family dissolution. The film promotes the expansion of family community through multicultural identity, and the film completes condolence of the people left behind by having the remaining families survive as survivors of suicide. The storyworld of the novels puts emphasis on 'self-discovery' of individual adolescents, while the storyworld of the movies puts emphasis on 'rediscovery of family'. Through transformation of storytelling - especially the redesigning of narrative structures called "modification" - transmedia storytelling shows that the relationship between media-converted texts is far from "faithful representation," but rather, shows conflicting themes and perspectives. With a reference point of 'the emergence of character' transmedia storytelling, which is predicated on the original work but aims to free itself from the original work by transforming storytelling through media conversion, opens up polyphonic storyworld by creating heterogeneous voices. In the post IMF-era, where uncertainty mounts over family dissolution and individualization, polyphonic storyworld created by transmedia storytelling provides an opportunity to experience disparate desires over individual freedom/risk and complacency toward community. We can call this the cultural-political implication of transmedia storytelling based on transferring, transcednding, and transforming.

• Asia pacific journal of information systems
• /
• v.21 no.2
• /
• pp.89-116
• /
• 2011

In collaborative tagging systems such as Delicious.com and Flickr.com, users assign keywords or tags to their uploaded resources, such as bookmarks and pictures, for their future use or sharing purposes. The collection of resources and tags generated by a user is called a personomy, and the collection of all personomies constitutes the folksonomy. The most significant need of the folksonomy users Is to efficiently find useful resources or experts on specific topics. An excellent ranking algorithm would assign higher ranking to more useful resources or experts. What resources are considered useful In a folksonomic system? Does a standard superior to frequency or freshness exist? The resource recommended by more users with mere expertise should be worthy of attention. This ranking paradigm can be implemented through a graph-based ranking algorithm. Two well-known representatives of such a paradigm are Page Rank by Google and HITS(Hypertext Induced Topic Selection) by Kleinberg. Both Page Rank and HITS assign a higher evaluation score to pages linked to more higher-scored pages. HITS differs from PageRank in that it utilizes two kinds of scores: authority and hub scores. The ranking objects of these pages are limited to Web pages, whereas the ranking objects of a folksonomic system are somewhat heterogeneous(i.e., users, resources, and tags). Therefore, uniform application of the voting notion of PageRank and HITS based on the links to a folksonomy would be unreasonable, In a folksonomic system, each link corresponding to a property can have an opposite direction, depending on whether the property is an active or a passive voice. The current research stems from the Idea that a graph-based ranking algorithm could be applied to the folksonomic system using the concept of mutual Interactions between entitles, rather than the voting notion of PageRank or HITS. The concept of mutual interactions, proposed for ranking the Semantic Web resources, enables the calculation of importance scores of various resources unaffected by link directions. The weights of a property representing the mutual interaction between classes are assigned depending on the relative significance of the property to the resource importance of each class. This class-oriented approach is based on the fact that, in the Semantic Web, there are many heterogeneous classes; thus, applying a different appraisal standard for each class is more reasonable. This is similar to the evaluation method of humans, where different items are assigned specific weights, which are then summed up to determine the weighted average. We can check for missing properties more easily with this approach than with other predicate-oriented approaches. A user of a tagging system usually assigns more than one tags to the same resource, and there can be more than one tags with the same subjectivity and objectivity. In the case that many users assign similar tags to the same resource, grading the users differently depending on the assignment order becomes necessary. This idea comes from the studies in psychology wherein expertise involves the ability to select the most relevant information for achieving a goal. An expert should be someone who not only has a large collection of documents annotated with a particular tag, but also tends to add documents of high quality to his/her collections. Such documents are identified by the number, as well as the expertise, of users who have the same documents in their collections. In other words, there is a relationship of mutual reinforcement between the expertise of a user and the quality of a document. In addition, there is a need to rank entities related more closely to a certain entity. Considering the property of social media that ensures the popularity of a topic is temporary, recent data should have more weight than old data. We propose a comprehensive folksonomy ranking framework in which all these considerations are dealt with and that can be easily customized to each folksonomy site for ranking purposes. To examine the validity of our ranking algorithm and show the mechanism of adjusting property, time, and expertise weights, we first use a dataset designed for analyzing the effect of each ranking factor independently. We then show the ranking results of a real folksonomy site, with the ranking factors combined. Because the ground truth of a given dataset is not known when it comes to ranking, we inject simulated data whose ranking results can be predicted into the real dataset and compare the ranking results of our algorithm with that of a previous HITS-based algorithm. Our semantic ranking algorithm based on the concept of mutual interaction seems to be preferable to the HITS-based algorithm as a flexible folksonomy ranking framework. Some concrete points of difference are as follows. First, with the time concept applied to the property weights, our algorithm shows superior performance in lowering the scores of older data and raising the scores of newer data. Second, applying the time concept to the expertise weights, as well as to the property weights, our algorithm controls the conflicting influence of expertise weights and enhances overall consistency of time-valued ranking. The expertise weights of the previous study can act as an obstacle to the time-valued ranking because the number of followers increases as time goes on. Third, many new properties and classes can be included in our framework. The previous HITS-based algorithm, based on the voting notion, loses ground in the situation where the domain consists of more than two classes, or where other important properties, such as "sent through twitter" or "registered as a friend," are added to the domain. Forth, there is a big difference in the calculation time and memory use between the two kinds of algorithms. While the matrix multiplication of two matrices, has to be executed twice for the previous HITS-based algorithm, this is unnecessary with our algorithm. In our ranking framework, various folksonomy ranking policies can be expressed with the ranking factors combined and our approach can work, even if the folksonomy site is not implemented with Semantic Web languages. Above all, the time weight proposed in this paper will be applicable to various domains, including social media, where time value is considered important.

• Asian Journal of Turfgrass Science
• /
• v.23 no.2
• /
• pp.331-344
• /
• 2009

Buffalograss is an important turfgrass species with excellent cold, heat, and drought tolerance. Understanding the physiological integration of buffalograss under heterogeneous conditions helps to develop cultural practices that better use limited resources for uniform turf quality. The objective of this study was to evaluate physiological integration of buffalograss under water deficit stress and the involvement of lipid peroxidation and antioxidants in the process. In one experiment, buffalograss was planted in the center of a four-compartment growth unit. Watering frequencies, once a week(+) and once in two weeks(-), were combined with the sand(S) or peat(P) in each unit to generate five total treatments(P+S-P-S+, P+P+P+P+, S-S-S-S-, P-P-P-P-, and S+S+S+S+). The average number of shoot established from the heterogeneous root-zone medium was higher than the average of four possible homogeneous media. In second experiment, single ramet in Hoagland solution($S_0$) or single ramet in Hoagland solution with 20% PEG-6000($S_s$) were compared with two connectedramets under different treatments. Treatments for connected ramets were young ramet in Hoagland solution($Y_{os}$) and old ramet in Hoagland solution with 20% PEG-6000($O_{os}$), and old ramet in Hoagland solution($O_{ys}$) and young ramet in Hoagland solution with 20% PEG-6000($Y_{ys}$). Lipid peroxidation, antioxidants, and proline showedphysiological integration between ramets subjected to different levels of water stress. Superoxide dismutase(SOD), Guaiacol peroxidase(G-POD), malondialdehyde(MDA), and free proline also showed different time courses and relative activities during the physiological integration.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2010.11a
• /
• pp.14-17
• /
• 2010

Following the proliferation of three-dimensional video contents and displays, many terrestrial broadcasting companies prepare for starting stereoscopic 3DTV service. In terrestrial stereoscopic broadcast, it is a difficult task to code and transmit two video sequences while sustaining as high quality as 2DTV broadcast attains due to the limited bandwidth defined by the existing digital TV standards such as ATSC. Thus, a terrestrial 3DTV broadcasting system with heterogeneous video coding systems is considered for terrestrial 3DTV broadcast where the left image and right images are based on MPEG-2 and H.264/AVC, respectively, in order to achieve both high quality broadcasting service and compatibility for the existing 2DTV viewers. Without significant change in the current terrestrial broadcasting systems, we propose a joint rate control scheme for stereoscopic 3DTV service. The proposed joint rate control scheme applies to the MPEG-2 encoder a quadratic rate-quantization model which is adopted in the H.264/AVC. Then the controller is designed for the sum of two bit streams to meet the bandwidth requirement of broadcasting standards while the sum of image distortions is minimized by adjusting quantization parameter computed from the proposed optimization scheme. Besides, we also consider a condition on quality difference between the left and right images in the optimization. Experimental results demonstrate that the proposed bit rate control scheme outperforms the rate control method where each video coding standard uses its own bit rate control algorithm in terms of minimizing the mean image distortion as well as the mean value and the variation of absolute image quality differences.

• Journal of Broadcast Engineering
• /
• v.22 no.5
• /
• pp.570-577
• /
• 2017

Recently, with the development of broadcasting communication, users expect to receive high quality and various broadcasting services anytime, anywhere. In the case of terrestrial broadcasting, HD broadcasting and mobile broadcasting are provided at different frequencies. In the case of terrestrial UHD, which recently started trial broadcasting, 700MHz frequency is used which is different from the existing one. If the contents of the same contents are transmitted at different frequencies, it can be considered ineffective in terms of the use efficiency of the terrestrial broadcast frequency. As a method to solve this problem, a transmission system model and a service have been proposed for transmitting the hierarchical encoded UHD contents by SHVC on the basis of the multimedia transmission technology MMT in a heterogeneous network environment combining broadcast network and communication network. However, it is still in the initial stage of study the receiving model that can reliably receive various quality UHD contents in various environments such as mobile and fixed environment. Therefore, in this paper, we propose a receive buffer model that can reliably receive UHD contents layered on SHVC based on MMT.

• Asian Journal of Turfgrass Science
• /
• v.26 no.2
• /
• pp.129-134
• /
• 2012

Research was focused on the improvement of poor drainage problems on golf course fairway which had not been performed soil test or properly amended during the course construction. The analysis of the drainage problem basically was caused by a deterioration of soil physical properties by the top layer compaction. The soil hardness reached about 3,000 Kpa around 5~6 cm of soil profile. The slow infiltration speed to subsoil by the compaction was caused directly a poor drainage capacity. However, the properly amended sand soil showed an apparent value of 1,500 Kpa through the subsoil. The water content test showed a similar result that higher rate of 20~30% and ideal rate of 8~12% at poor drainage area and successfully amended area, respectively. However, an imported topsoil media which had higher content of silt and clay from a trans-planted sod had made a heterogeneous soil profile and that caused a poor drain capacity by a low infiltration rate. Those drainage problems triggered to buildup a reduced soil layer by poor soil gas exchange. The soil environment of deoxidation enhanced anaerobic microbial population and induced methane gas build-up to 55 ppm, and that resulted an adverse effect on turf growth by root growth retardation, consequently.

• Microbiology and Biotechnology Letters
• /
• v.16 no.3
• /
• pp.250-258
• /
• 1988

Lipases are well known as the enzymes which catalyze the hydrolysis of ester bonds combining aliphatic chains and glycerol on mono-, di- and triglycerides. Their reactions are characterized by be-ing heterogeneous and catalyzing the water-insoluble substrates. This property has been one of the Hurdles which delayed the application of lipases in fats and oils industry, However, with the development of biological reaction system of which organic solvent is introduced in part or whole as the reaction media, enzymatic manipulation of fats and oils is attracting increasing attention from the academic and industrial sectors. Trials in two-phase system and reversed micellar system to produce fatty acids through enzymatic hydrolysis of triglycerides preyed to be efficient in respect to volumetric productivity, fat hydrolysis rate, product separation, etc. In organic solvent system lipases have been found to have the ability to catalyze aminolysis, transesterification, esterification, thiotransesterification and oximolysis that are virtually impossible to catalyze in water. The organic solvent system is being extensively used in interesterifying glycerides to produce a fat with the modified physical and chemical nature.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.42 no.5
• /
• pp.9-20
• /
• 2005

In this paper, we propose ubiTrack, a system which tracks users' location in indoor environments by employing infrared-based proximity method. Most of recently developed systems have focussed on performance and accuracy. For this reason, they adopted the idea of centralized management, which gathers all information in a main system to monitor users' location. However, these systems raise privacy concerns in ubiquitous computing environments where tons of sensors are seamlessly embedded into environments. In addition, centralized systems also need high computational power to support multiple users. The proposed ubiTrack is designed as a passive mobile architecture to relax privacy problems. Moreover, ubiTrack utilizes appropriate area as a unit to efficiently track users. To achieve this, ubiTrack overlaps each sensing area by utilizing the TDM (Time-Division Multiplexing) method. Additionally, ubiTrack exploits various filtering methods at each receiver and utilization module. The filtering methods minimize unexpected noise effect caused by external shock or intensity weakness of ID signal at the boundary of sensing area. ubiTrack can be applied not only to location-based applications but also to context-aware applications because of its associated module. This module is a part of middleware to support communication between heterogeneous applications or sensors in ubiquitous computing environments.

• 한국지구물리탐사학회:학술대회논문집
• /
• 2006.06a
• /
• pp.201-206
• /
• 2006

Earth sciences is undergoing a gradual but massive shift from description of the earth and earth systems, toward process modeling, simulation, and process visualization. This shift is very challenging because the underlying physical and chemical processes are often nonlinear and coupled. In addition, we are especially challenged when the processes take place in strongly heterogeneous systems. An example is two-phase fluid flow in rocks, which is a nonlinear, coupled and time-dependent problem and occurs in complex porous media. To understand and simulate these complex processes, the knowledge of underlying pore-scale processes is essential. This paper presents a new attempt to use pore-scale simulations for understanding physical properties of rocks. A rigorous pore-scale simulator requires three important traits: reliability, efficiency, and ability to handle complex microstructures. We use the Lattice-Boltzmann (LB) method for singleand two-phase flow properties, finite-element methods (FEM) for elastic and electrical properties of rocks. These rigorous pore-scale simulators can significantly complement the physical laboratory, with several distinct advantages: (1) rigorous prediction of the physical properties, (2) interrelations among the different rock properties in a given pore geometry, and (3) simulation of dynamic problems, which describe coupled, nonlinear, transient and complex behavior of Earth systems.