• Clinical and Experimental Pediatrics
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• v.65 no.5
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• pp.239-249
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• 2022

Cells survive and proliferate through complex interactions among diverse molecules across multiomics layers. Conventional experimental approaches for identifying these interactions have built a firm foundation for molecular biology, but their scalability is gradually becoming inadequate compared to the rapid accumulation of multiomics data measured by high-throughput technologies. Therefore, the need for data-driven computational modeling of interactions within cells has been highlighted in recent years. The complexity of multiomics interactions is primarily due to their nonlinearity. That is, their accurate modeling requires intricate conditional dependencies, synergies, or antagonisms between considered genes or proteins, which retard experimental validations. Artificial intelligence (AI) technologies, including deep learning models, are optimal choices for handling complex nonlinear relationships between features that are scalable and produce large amounts of data. Thus, they have great potential for modeling multiomics interactions. Although there exist many AI-driven models for computational biology applications, relatively few explicitly incorporate the prior knowledge within model architectures or training procedures. Such guidance of models by domain knowledge will greatly reduce the amount of data needed to train models and constrain their vast expressive powers to focus on the biologically relevant space. Therefore, it can enhance a model's interpretability, reduce spurious interactions, and prove its validity and utility. Thus, to facilitate further development of knowledge-guided AI technologies for the modeling of multiomics interactions, here we review representative bioinformatics applications of deep learning models for multiomics interactions developed to date by categorizing them by guidance mode.

• Smart Structures and Systems
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• v.29 no.4
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• pp.561-576
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• 2022

Heritage timber structures represent the history and culture of a nation. These structures have been inherited from previous generations; however, they inevitably exhibit deterioration over time, potentially leading to structural deficiencies. Structural Health Monitoring (SHM) offers the potential to assess operational anomalies, deterioration, and damage through processing and analysis of data collected from transducers and sensors mounted on the structure. This paper reports on the design and implementation of a long-term SHM system on the Feiyun Wooden Pavilion in China, a three-story timber building built more than 500 years ago. The principles and features of the design and implementation of SHM systems for heritage timber buildings are systematically discussed. In total, 104 sensors of 6 different types are deployed on the structure to monitor the environmental effects and structural responses, including air temperature and humidity, wind speed and direction, structural temperatures, strain, inclination, and acceleration. In addition, integrated data acquisition and transmission subsystem using a newly developed software platform are implemented. Selected preliminary statistical and correlation analysis using one year of monitoring data are presented to demonstrate the condition assessment capability of the system based on the monitoring data.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.781-787
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• 2009

Training and process analysis in the construction industry has not taken full advantage of new technologies such as building information modeling(BIM). The purpose of this research is to develop a framework for the virtual interactive construction education system using three dimensional technologies. The modules will simulate the construction process for a facility from start to finish using information drawn from real projects in the built environment. These modules can be used as training tools for new employees where they attempt to optimize time and cost in a virtual environment given a limited number of equipment, time and employee options. They can also be used as a process analysis tool for new construction where a number of situational variables can change leading to exposure of potential risk. These modules would be particularly useful for repetitive construction where the initial project is analyzed for optimization and risk mitigation. This paper describes the framework and shows a residential construction example using a 900 square foot wood frame single family house designed for the United States.

• Journal of the Korean Institute of Educational Facilities
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• v.20 no.4
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• pp.23-34
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• 2013

This study focuses on the review of the present condition of schools and regional public facilities and finds out the basic direction and practical task to utilize a mixed-use school as a regional community hub reorganizing schools and regional public facilities. School facilities have enough potential to be a center of everyday life and educational function with accessibility in neighborhood living environment. Nevertheless it has institutional limitation to make school facility work for entire region because schools and regional public facilities are built and administrated without collaboration of the local governments and office of education. Also current mixed-use school facilities are planned separately or laid out monotonously without local resident's demands. This research analyzes the possibility of mixed-use facility of current operating schools and regional public facilities in Gang-nam gu and categorizes possible public facilities for mixed-use. For successful complex plan of schools and public facilities, next step will be the improvement of administration and laws and the analysis of facilities what local residents need from the preliminary stage with consultation of various stakeholders.

• 한국전기화학회:학술대회논문집
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• 1998.12a
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• pp.7-27
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• 1998

In order to design capacity of lithium ion battery, some calculations were carried out based on the characteristics of materials by the given battery shape and dimension. The principle of design was built by the interpretation of the correlation of material, electrochemical and battery factors. Parameters of materials are fundamental physical properties of constituent such as cathode. separator, anode, current collectors and electrolyte. Electrochemical factor includes potential pattern as a function of specific capacity, specific discharge capacity(or initial irreversible specific capacity or Ah efficiency) as a function of specific charge capacity and material balancing. Parameters of battery are dimension, construction hardware and performance. Battery capacity was simulated for a lithium cobalt dioxide as cathode and a hard carbon as anode to achieve 1100 mAh for the charge limit voltage of 4.2V, the weight ratio(+/-) of 2.4 and ICR18650. A fabricated test cell (ICR18650) which have weight ratio(+/-) of 2.4 discharged to 1093 mAh for the charge limit voltage of 4.2V. The sequential discharge capacity show good correspondence with designed capacity.

• Smart Structures and Systems
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• v.26 no.1
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• pp.23-33
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• 2020

Majority of the damage in engineering structures is nonlinear. Damage sensitive features (DSFs) extracted by traditional methods from linear time series models cannot effectively handle nonlinearity induced by structural damage. A new DSF is proposed based on vector space cosine similarity (VSCS), which combines K-means cluster analysis and Bayesian discrimination to detect nonlinear structural damage. A reference autoregressive moving average (ARMA) model is built based on measured acceleration data. This study first considers an existing DSF, residual standard deviation (RSD). The DSF is further advanced using the VSCS, and then the advanced VSCS is classified using K-means cluster analysis and Bayes discriminant analysis, respectively. The performance of the proposed approach is then verified using experimental data from a three-story shear building structure, and compared with the results of existing RSD. It is demonstrated that combining the linear ARMA model and the advanced VSCS, with cluster analysis and Bayes discriminant analysis, respectively, is an effective approach for detection of nonlinear damage. This approach improves the reliability and accuracy of the nonlinear damage detection using the linear model and significantly reduces the computational cost. The results indicate that the proposed approach is potential to be a promising damage detection technique.

• 한국전산유체공학회:학술대회논문집
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• 2005.04a
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• pp.47-50
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• 2005

The Grid'[1] means the collaboration of computing and experimental resources in dispersed organizations by high-speed network. It has been paid much attention for an unlimited number of potential resources available and the easiness to build collaborative environments among multiple disciplines. However, the difficulty in establishing the environments and accessing and utilizing the resources has prevented application scientists from conducting Grid computing. Thus, the present study focuses on building PSE(Problem Solving Environment) which assists application researchers to easily access and utilize the Grid. The Cactus toolkit, originally developed by astrophysicists, is used as a base frame for Grid PSE. Some modules are newly developed and modified for CFD(Computational Fluid Dynamics) analysis. Simultaneously, a web portal, Grid-One portal, is built for remote monitoring/control and job migration. Cactus frame through the web portal service has been applied to various CFD problems, demonstrating that the developed PSE is valuable for large-scaled applications on the Grid.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.396-401
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• 2008

The disc-pad brake system is an important part of automobile safety system. During braking, the kinetic energy and potential energies of a moving vehicle are converted into the thermal energy through frictional heat between the brake disc and the pads. Most of the thermal energy dissipated through the brake disc. The temperature could be exceed the critical value for a given material, which leads to undesirable effects, such as the brake fade, premature wear, brake fluid vaporization, bearing failure, thermal cracks, and thermallyexcited vibration. The object of the present study is to investigate temperature field and temperature variation of brake disc and pad during single brake. The brake disc is decelerated at the initial speed with constant acceleration, until the disc comes to stop. The pad-disc brake assembly is built by 3D model with the appropriate boundary condition. In the simulation process, the mechanical loads are applied to the thermomechanical coupling analysis in order to simulate the process of heat produced by friction.

• The KSFM Journal of Fluid Machinery
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• v.11 no.3
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• pp.22-29
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• 2008

Clean and renewable energy technologies using ocean energy give us non-polluting alternatives to fossil and nuclear-fueled power plants to meet establishment of countermeasures against the global warming and growing demand for electrical energy. Among the ocean energy resources, wave power takes a growing interest because of its enormous amount of potential energy in the world. Therefore, various types of wave power conversion system to capture the energy of ocean waves have been developed. However, suitable turbine type is not normalized yet because of relatively low efficiency of the turbine systems. The purpose of this study is to investigate the internal flow and performance characteristics of a cross-flow type hydro turbine, which will be built in a caisson for wave power generation. Numerical simulation using a commercial CFD code is conducted to clarify the effects of the turbine rotation speed and flow rate variation on the turbine characteristics. The results show that the output power of the cross-flow type hydro turbine with symmetric nozzle shape is obtained mainly from Stage 2. Turbine inlet configuration should be designed to obtain large amount of flow rate because the static pressure and absolute tangential velocity are influenced considerably by inlet flow rate.

• The KIPS Transactions:PartC
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• v.10C no.4
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• pp.397-404
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• 2003

Intrusion detection techniques based on program behavior can detect potential intrusions against systems by analyzing system calls made by demon programs or root-privileged programs and building program profiles. But there is a drawback : large profiles must be built for each program. In this paper, we apply $X^2$ distance-based multivariate analysis to profiling program behavior and detecting abnormal behavior in order to reduce profiles. Experiment results show that profiles are relatively small and the detection rate is significant.