• Journal of Technology Innovation
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• v.28 no.4
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• pp.63-93
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• 2020

We suggest a new way of specifying the co-evolution of product and process technologies, and integrating it into one of the well-received technology intelligence tools - a technology radar. Cross impact analysis enables us to identify the core technologies of product-process co-evolution. Combining expert judgment with its results, we can clarify the technological co-evolution trajectory with mainstream as well as emerging core technologies. Reflecting these in the assessment process of a technology radar, we could improve reliance of the technology assessment process and technology portfolio. From the academic perspective, our research provides a point where the co-evolution theory encouners technology intelligence methods. Practically, strategic capability of future-preparedness and strategic management could improve by adopting our method based on our example of co-evolution of semiconductor product and process technologies.

• Journal of Computing Science and Engineering
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• v.9 no.2
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• pp.73-82
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• 2015

Understanding how the topic evolves is an important and challenging task. A topic usually consists of multiple related events, and the accurate identification of event evolution relationship plays an important role in topic evolution analysis. Existing research has used the traditional vector space model to represent the event, which cannot be used to accurately compute the semantic similarity between events. This has led to poor performance in identifying event evolution relationship. This paper suggests constructing a semantic aspect-based vector space model to represent the event: First, use hierarchical Dirichlet process to mine the semantic aspects. Then, construct a semantic aspect-based vector space model according to these aspects. Finally, represent each event as a point and measure the semantic relatedness between events in the space. According to our evaluation experiments, the performance of our proposed technique is promising and significantly outperforms the baseline methods.

• International Journal of Advanced Culture Technology
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• v.4 no.1
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• pp.31-36
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• 2016

Morphology evolution of the active layer in bulk hetero-junction organic photovoltaic is modeled and visualized. The width of the phase domain can be predicted using the relationship of characteristics length and evolution time of the process. The 3D numerical simulation of the PCBM/P3HT blend morphology evolution with respect to time is presented. It is observed that the domain width of composition phase can be predicted by using the relationship between value of characteristic length R(t) and evolution time t.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1355-1360
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• 2005

In this paper, we approach the problem of image filter design automation using a kind of intrinsic evolvable hardware architecture. For the purpose of implementing the intrinsic evolution process in a common FPGA chip and evolving a complicated digital circuit system-image filter, the design automation system employs the reconfigurable circuit architecture as the reconfigurable component of the EHW. The reconfigurable circuit architecture is inspired by the Cartesian Genetic Programming and the functional level evolution. To increase the speed of the hardware evolution, the whole evolvable hardware system which consists of evolution algorithm unit, fitness value calculation unit and reconfigurable unit are implemented by a commercial FPGA chip. The Celoxica RC1000 card which is fitted with a Xilinx Virtex xcv2000E FPGA chip is employed as the experiment platform. As the result, we conclude the terms of the synthesis report of the image filter design automation system and hardware evolution speed in the Celoxica RC1000 card. The evolved image filter is also compared with the conventional image filter form the point of filtered image quality.

• Industrial Engineering and Management Systems
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• v.10 no.3
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• pp.203-208
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• 2011

Job shop scheduling is well-known as one of the hardest combinatorial optimization problems and has been demonstrated to be NP-hard problem. In the past decades, several researchers have devoted their effort to develop evolutionary algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for job shop scheduling problem. Differential Evolution (DE) algorithm is a more recent evolutionary algorithm which has been widely applied and shown its strength in many application areas. However, the applications of DE on scheduling problems are still limited. This paper proposes a one-stage differential evolution algorithm (1ST-DE) for job shop scheduling problem. The proposed algorithm employs random key representation and permutation of m-job repetition to generate active schedules. The performance of proposed method is evaluated on a set of benchmark problems and compared with results from an existing PSO algorithm. The numerical results demonstrated that the proposed algorithm is able to provide good solutions especially for the large size problems with relatively fast computing time.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.146-156
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• 2020

Two High Tensile Strength Steel (EH47) plates with thickness of 70 mm were butt-welded together by multi-pass Submerged Arc Welding (SAW), also the hardness and welding residual stress were investigated experimentally. Based on Thermal-Elastic-Plastic Finite Element (TEP FE) computation, the thermal cycles during entire welding process were obtained, and the HAZ hardness of multi-pass butt welded joint was computed by the hardenability algorithm with considering microstructure evolution. Good agreement of HAZ hardness between the measurement and computational result is observed. The evolution of each phase was drawn to clarify the influence mechanism of thermal cycle on HAZ hardness. Welding residual stress was predicted with considering mechanical response, which was dominantly determined by last cap welds through analyzing its formation process.

• Journal of Electrochemical Science and Technology
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• v.13 no.4
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• pp.417-423
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• 2022

With the emerging importance of catalysts for water electrolysis, developing efficient and inexpensive electrocatalysts for water electrolysis plays a vital role in renewable hydrogen energy technology. In this study, a 1nm thickness of TiC-supported Ru catalyst for hydrogen evolution reaction (HER) has been successfully fabricated using an electron (E)-beam evaporator and thermal decomposition of gaseous CH₄ in a furnace. The prepared Ru/TiC catalyst exhibited an outstanding performance for alkaline hydrogen evolution reaction with an overpotential of 55 mV at 10 mA cm^-2. Furthermore, we demonstrated that the outstanding HER performance of Ru/TiC was attributed to the high surface area of the support and the metal-support interaction.

• Journal of English Language & Literature
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• v.58 no.4
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• pp.655-678
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• 2012

Doris Lessing, who considers science and technology as instruments of capitalism, deals with the theme of 'biological evolution' in The Sirian Experiments, the third book in the Canopus in Argos: Archives series. One of her themes that repeats throughout is that of 'spiritual evolution,' and in The Four-Gated City she even used 'biological evolution' as its metaphor. This paper analyzes The Sirian Experiments using scientific knowledge such as the concept of 'biological evolution' from Charles Darwin's evolution theory and Edward O. Wilson's sociobiology. Lessing concludes that while 'biological evolution' not accompanied with 'spiritual evolution' puts humans in existential problems and mental breakdown, the one in equilibrium with the other can bring social and political revolution. Lessing's concept of 'spiritual evolution' is basically a product of her holistic view and her own philosophical view that human evolution is a necessary process following the Universal Order, which shows that she is influenced by Sufism. The basic tenet in Sufi philosophy is to achieve equilibrium between the rational and non-rational modes of consciousness. Lessing incorporates her rational and irrational ideas into The Sirian Experiments to make a field for confluence where the biological, the sociological, and the spiritual thinking converge.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.282-287
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• 2008

In distributed mobile robot systems, autonomous robots accomplish complicated tasks through intelligent cooperation with each other. This paper presents behavior learning and online distributed evolution for cooperative behavior of a group of autonomous robots. Learning and evolution capabilities are essential for a group of autonomous robots to adapt to unstructured environments. Behavior learning finds an optimal state-action mapping of a robot for a given operating condition. In behavior learning, a Q-learning algorithm is modified to handle delayed rewards in the distributed robot systems. A group of robots implements cooperative behaviors through communication with other robots. Individual robots improve the state-action mapping through online evolution with the crossover operator based on the Q-values and their update frequencies. A cooperative material search problem demonstrated the effectiveness of the proposed behavior learning and online distributed evolution method for implementing cooperative behavior of a group of autonomous mobile robots.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.686-693
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• 2013

Generation Expansion Planning (GEP) is one of the most important decision-making activities in electric utilities. Least-cost GEP is to determine the minimum-cost capacity addition plan (i.e., the type and number of candidate plants) that meets forecasted demand within a pre specified reliability criterion over a planning horizon. In this paper, Differential Evolution (DE), and Opposition-based Differential Evolution (ODE) algorithms have been applied to the GEP problem. The original GEP problem has been modified by incorporating Virtual Mapping Procedure (VMP). The GEP problem of a synthetic test systems for 6-year, 14-year and 24-year planning horizons having five types of candidate units have been considered. The results have been compared with Dynamic Programming (DP) method. The ODE performs well and converges faster than DE.