International Journal of Modeling, Simulation, and Scientific Computing

We have developed a software framework for scientific visualization in immersive-type, room-sized virtual reality (VR) systems, or Cave automatic virtual environment (CAVEs). This program, called Multiverse, allows users to select and invoke visualization programs without leaving CAVE’s VR space. Multiverse is a kind of immersive “desktop environment” for users, with a three-dimensional graphical user interface. For application developers, Multiverse is a software framework with useful class libraries and practical visualization programs as samples.

Advances in mobile technology make most people have their own mobile devices which contain various sensors such as a smartphone. People produce their own personal data or collect surrounding environment data with their mobile devices at every moment. Recently, a broad spectrum of studies on Participatory Sensing, the concept of extracting new knowledge from a mass of data sent by participants, are conducted. Data collection method is one of the base technologies for Participatory Sensing, so networking and data filtering techniques for collecting a large number of data are the most interested research area. In this paper, we propose a data collection model in hybrid network for participatory sensing. The proposed model classifies data into two types and decides networking form and data filtering method based on the data type to decrease loads on data center and improve transmission speed.

Since the first outbreak of Middle East Respiratory Syndrome (MERS), Korea has a quite rapid MERS spread compared to other countries. Possible causes for such a sudden increase include the undiagnosed initial patient and lapses in infection control practices. To characterize MERS infection and transmission, this paper applies the period-based discrete SEIR model. Infected people of SEIR model shows a good fit to observed patients and MERS will become extinct around 113 days since the first outbreak. Through an effective quarantine plan, if we can reduce exposable people by 20%, it is estimated that the maximum number of infectious people may decrease by about 69% and MERS fade-out period will be shortened by about 30%. Simulations on assumed model support that Korean government’s two policies to control MERS infection rate are effective in lessening its spread. Simulation on reproduction ratio scenarios in SEIR model indicates that success in early infection control practices is critical for shortening the period of disease fade-out. Even there are some restrictions and assumptions on SEIR model simulation, our simulation results are to be helpful in developing strategies to prevent the infectious diseases like MERS.

Proteome patterns reflect the underlying pathological state of a human organ and it is believed that the anomalies or diseases of human organs are identified by the analysis of the patterns. This paper compares the three classification methods for the identification of breast cancer based on the proteome patterns generated from two-dimensional polyacrylamide gel electrophoresis (2D PAGE). The purpose of the classification is two folds: setting up a decision model for the identification of the proteome pattern associated with breast cancer and obtaining the marker spots that play important roles in the identification. Three classification methods are applied to the classification of proteome patterns into the cancer and the normal groups: (i) genetic algorithm and SVM, (ii) stepwise forward feature selection and $k$-NN classification technique, (iii) random forest classification technique. The results from the classification of the proteome patterns from actual clinical samples are presented.

The current research aims to simulate the flight trajectory of the North Korean submarine–launched ballistic missile (SLBM) and analyze its flight characteristics based on its range control method. Recently, North Korea has completed the test flight of SLBM and it has become a significant threat to international security. North Korea obtained SLBM technologies from Russia while disbanding decommissioned Russian submarines, and it is suspected that North Korea will continue to experiment in related fields along with its continued attempts to miniaturize nuclear weapons. If North Korea completes the development of SLBM and deploys the missiles, it means the completion of the three asymmetric warfare elements (nuclear weapon, ballistic missile, and submarine) and they will be the most significant threats to northeast Asia. Therefore, it is imperative to scientifically analyze SLBM to adeptly respond to such threat. One characteristic of SLBM is capability of attacking its target in a variety of ways based on its range control method. Based on this fact, the current research derives the flight equation of North Korean SLBM and simulates its flight trajectory based on various range control methods. The flight trajectories that we derive can be used to establish an effective anti-ballistic missile defense system in northeast Asia.

In recent years, scholars have made many research results on job-shop scheduling (JSP) problem, especially in single objective such as the maximum completion time. But most of the actual system scheduling problems are more than one object. Therefore, the research of multi-objective scheduling problem is very important and meaningful. In this paper, we proposed a multi-objective scheduling model which adopts weighted sum method to optimize two important indexes (makespan and total flow time). Genetic algorithm (GA) has diversified global search ability, while simulated annealing (SA) combined with tabu search (TS) have intensified capabilities in local neighborhood search. To overcome the drawback of the GA, we proposed a new hybrid GA (NewHGA) which produces initial solutions by GA firstly, and then take SA operator incorporate TS operator to search in the local space. By adding the novel local search strategy, the diversity of solutions will be improved greatly so that it can ensure the algorithm jump out of the local optimal value. We test this algorithm using the benchmark instances of different sizes taken from the OR-Library, and the results show that the algorithm is efficient than another hybrid algorithm.