• Asia pacific journal of information systems
• /
• v.30 no.4
• /
• pp.719-740
• /
• 2020

The stock market changes continuously as new information emerges, affecting the judgments of investors. Online news articles are valued as a traditional window to inform investors about various information that affects the stock market. This paper proposed new ways to utilize online news articles with technical indicators. The suggested hybrid model consists of three models. First, a self-attention-based convolutional neural network (CNN) model, considered to be better in interpreting the semantics of long texts, uses news content as inputs. Second, a self-attention-based, bi-long short-term memory (bi-LSTM) neural network model for short texts utilizes news titles as inputs. Third, a bi-LSTM model, considered to be better in analyzing context information and time-series models, uses 19 technical indicators as inputs. We used news articles from the previous day and technical indicators from the past seven days to predict the share price of the next day. An experiment was performed with Korean stock market data and news articles from 33 top companies over three years. Through this experiment, our proposed model showed better performance than previous approaches, which have mainly focused on news titles. This paper demonstrated that news titles and content should be treated in different ways for superior stock price prediction.

• Computers and Concrete
• /
• v.14 no.1
• /
• pp.59-71
• /
• 2014

The paper is concerned with the analytical description of a resistance mechanism, not considered in previous models, by which the hoops contribute to the shear capacity of RC columns with circular cross sections. The difference from previous approaches consists in observing that, because of deformation, the hoops change their original shape and, as a consequence, their slope does not match anymore the original one in the neighborhood of a crack. The model involves two parameters only, namely the crack inclination and the hoop strain in the neighborhood of a crack. A closed-form analytical formulation to correlate the average value of the crack width and the hoop strain is also provided. Results obtained using the proposed model have been compared with experimental data, and a satisfactory agreement is found.

• Journal of Korean Neurosurgical Society
• /
• v.60 no.3
• /
• pp.275-281
• /
• 2017

Treating diseases in the field of neurosurgery has progressed concomitantly with technical advances. Here, as a surgical armamentarium for the treatment of cerebral aneurysms, the history and present status of the keyhole approach and the use of neuroendoscopy are reviewed, including our clinical data. The major significance of keyhole approach is to expose an essential space toward a target, and to minimize brain exposure and retraction. Among several kinds of keyhole approaches, representative keyhole approaches for anterior circulation aneurysms include superciliary and lateral supraorbital, frontolateral, mini-pterional and mini-interhemispheric approaches. Because only a fixed and limited approach angle toward a target is permitted via the keyhole, however, specialized surgical devices and preoperative planning are very important. Neuroendoscopy has helped to widen the indications of keyhole approaches because it can supply illumination and visualization of structures beyond the straight line of microscopic view. In addition, endoscopic indocyanine green fluorescence angiography is useful to detect and correct any compromise of the perforators and parent arteries, and incomplete clipping. The authors think that keyhole approach and neuroendoscopy are just an intermediate step and robotic neurosurgery would be realized in the near future.

• Journal of the Korea Safety Management & Science
• /
• v.17 no.2
• /
• pp.215-228
• /
• 2015

A creative innovation and an innovative problem-solving of industrial companies can be achieved by overcoming the challenges of technical and physical contradictions. The approaches to address conflicting and paradoxical problems, such as technical and physical contradictions have a crucial role in advancing the quality assessment for manufacturer and service provider. The term, technical contradiction, depicts the state that improvement of one ends of IFR (Ideal Final Result) leads to unfavorable condition of the other ends, and results in conflicting problem. Another type of contradictions that's discussed in this study is a physical contradiction which is due to two mutually opposing states of the means of ends, and gives paradoxical situation. By integrating the means-ends chain perspectives, the physical contradiction that is a specifically root-causes, "means", can be initially addressed to resolve the downstream problem of technical contradiction which represents a general and abstract goals, "ends". This research suggests IFR resolution processes to handle both physical contradiction of means and technical contradiction of ends by employing causal relationship with IFR, effects and causes. In summary, the study represents three major processes that resolve such contradictions are demonstrated as follows: 1) Derivation of causal and hierarchical relationship among IFR, ends and means by considering CAED (Cause-And-Effect Diagram) and LT (Logic Tree). 2) Identification of causal relationship between physical contradiction and technical contradiction by using TPCT (TRIZ Physical Contradiction Tree) and TCD (Technical Contradiction Diagram). 3) Application of integrated TRIZ principles by classifying 40 inventive principles into 4 general conditions of the separation principle of mutually opposite states in space, in time, based on conditions, and between the parts and the whole. In order to validate the proof of proposed IFR resolution processes, the analysis of the TRIZ case studies from National Quality Circle Contest in the years, 2011 to 2014 have been proposed. The suggested guidelines that are built based on TRIZ principles can uniquely enhance the process of quality innovation and assessment for quality practitioners.

• Journal of the Society of Naval Architects of Korea
• /
• v.53 no.2
• /
• pp.127-134
• /
• 2016

This paper presents practical issues for test and evaluation(T&E) methods to develop defense systems. Our argument is motivated by several domestic defense cases and the cases lead us to discuss two main factors for reliable defense systems development: 1) statistical approaches and 2) technical schemes. Specifically, statistical approaches enable to provide credible interpretations about T&E results in the decision-making process. With practical T&E results of the “Red Shark” torpedo, we performed statistical hypothesis tests and suggest a minimum sample size to accept the hypothesis. Next, technical schemes have more direct effects on improving reliability of developed defense systems and we shortly introduce tools development for systems verification that is required to integrate several sub-systems, e.g., combat, sensor, weapon, and communication systems, within a defense system. We additionally summary some domain cases using modeling and simulation techniques for successful T&E. In closing, we expect that the paper shows empirical investigation and lessons learned with these two practical issues, which provides a guide those who desire to make decisions about reliable defense systems development.

• Journal of Korean Society on Water Environment
• /
• v.38 no.4
• /
• pp.177-189
• /
• 2022

Nature-based Solutions (NbS) are defined as practical and technical approaches to restoring functioning ecosystems and biodiversity as a means to address socio-environmental challenges and provide human-nature co-benefits. This study reviews NbS-related literature to identify its key characteristics, techniques, and challenges for its application in climate-adaptive water management. The review finds that NbS has been commonly used as an umbrella term incorporating a wide range of existing ecosystem-based approaches such as low-impact development (LID), best management practices (BMP), forest landscape restoration (FLR), and blue-green infrastructure (BGI), rather than being a uniquely-situated practice. Its technical form and operation can vary significantly depending on the spatial scale (small versus large), objective (mitigation, adaptation, naturalization), and problem (water supply, quality, flooding). Commonly cited techniques include green spaces, permeable surfaces, wetlands, infiltration ponds, and riparian buffers in urban sites, while afforestation, floodplain restoration, and reed beds appear common in non- and less-urban settings. There is a greater lack of operational clarity for large-scale NbS than for small-scale NbS in urban areas. NbS can be a powerful tool that enables an integrated and coordinated action embracing not only water management, but also microclimate moderation, ecosystem conservation, and emissions reduction. This study points out the importance of developing decision-making guidelines that can inform practitioners of the selection, operation, and evaluation of NbS for specific sites. The absence of this framework is one of the obstacles to mainstreaming NbS for water management. More case studies are needed for empirical assessment of NbS.

• Environmental Engineering Research
• /
• v.15 no.3
• /
• pp.163-166
• /
• 2010

Pulp and paper mill wastewater has been treated by biological treatment, but the secondary effluent still contains high lignin, chemical oxygen demand, color and total dissolved solids. Tertiary treatment by land application, referred to as 'Project Green,' has been implemented to treat such high quantities of undesirable matters. The impacts of seepage from Project Green diffusing into receiving streams on the water quality and fish pen aquaculture were studied via the integration of technical and social approaches. The determination of the water quality was performed for 13 sampling stations along the receiving stream, including the Chot stream, Chot lagoon and the Pong River. The water quality was generally at normal levels, with the exception of total dissolved solids. The levels of matter were higher at the Chot stream, but became more diluted at the Chot lagoon and the Pong River, respectively. The social approach was conducted through the voluntary participation of the villagers as research assistants for the fish aquaculture study. Fish could grow at three fish pens within the study sites at the location of Project Green, the Chot lagoon and the Pong River. Fish growth at the Chot lagoon was better at the site of Project Green and the Pong River. The integration of technical and social approaches was a meaningful tool not only for the technical feasibility but in helping to solve the conflict between the community and industry.

• Computers and Concrete
• /
• v.21 no.5
• /
• pp.559-567
• /
• 2018

In this study alkali activation of Electric Arc Furnace Slag (EAFS) is studied with a comprehensive test program. Three different silicate moduli (1-1,5-2), three different sodium concentrations (4%-6%-8%) for each silicate module, two different curing conditions (45%-98% relative humidity) for each sodium concentration, two different curing temperatures ($400^{\circ}C-800^{\circ}C$) for each relative humidity condition and two different curing time (6h-12h) for each curing temperature variables are selected and their effects on compressive strength was evaluated then regression equations using multiple linear regressions methods are fitted. And then to select the best regression models confirm with using the variables, the regression models compared between itself. An Artificial Neural Network (ANN) models that use silicate moduli, sodium concentration, relative humidity, curing temperature and curing time variables, are formed. After the investigation of these ANN models' results, ANN and multiple linear regressions based models are compared with each other. After that, an explicit formula is developed with values of the ANN model. As a result of this study, the fluctuations of data set of the compressive strength were very well reflected using both of the methods, multiple linear regression with quadratic terms and ANN.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.8
• /
• pp.399-407
• /
• 2021

Stock movement is difficult to predict because it has dynamic characteristics and is influenced by many factors. Even so, there are some approaches to predict stock price movements, namely technical analysis, fundamental analysis, and sentiment analysis. Many researches have tried to predict stock price movement by utilizing these analysis techniques. However, the results obtained are varied and inconsistent depending on the variables and object used. This is because stock price movement is influenced by a variety of factors, and it is likely that those studies did not cover all of them. One of which is that no research considers the use of fundamental analysis in terms of currency exchange rates and the use of foreign stock price index movement related to the technical analysis. This research aims to predict stock price movements in Indonesia based on sentiment analysis, technical analysis, and fundamental analysis using Support Vector Machine. The result obtained has a prediction accuracy rate of 65,33% on an average. The inclusion of currency exchange rate and foreign stock price index movement as a predictor in this research which can increase average prediction accuracy rate by 11.78% compared to the prediction without using these two variables which only results in average prediction accuracy rate of 53.55%.

• Wind and Structures
• /
• v.34 no.6
• /
• pp.511-523
• /
• 2022

Detecting the icing on wind turbine blades built-in cold regions with conventional methods is always a very laborious, expensive and very difficult task. Regarding this issue, the use of smart systems has recently come to the agenda. It is quite possible to eliminate this issue by using the deep learning method, which is one of these methods. In this study, an application has been implemented that can detect icing on wind turbine blades images with visualization techniques based on deep learning using images. Pre-trained models of Resnet-50, VGG-16, VGG-19 and Inception-V3, which are well-known deep learning approaches, are used to classify objects automatically. Grad-CAM, Grad-CAM++, and Score-CAM visualization techniques were considered depending on the deep learning methods used to predict the location of icing regions on the wind turbine blades accurately. It was clearly shown that the best visualization technique for localization is Score-CAM. Finally, visualization performance analyses in various cases which are close-up and remote photos of a wind turbine, density of icing and light were carried out using Score-CAM for Resnet-50. As a result, it is understood that these methods can detect icing occurring on the wind turbine with acceptable high accuracy.