• IE interfaces
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• v.24 no.2
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• pp.156-163
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• 2011

The radiopharmaceutical synthesis for PET (positron emission tomography) is composed of chemical reactions using automated synthetical equipment. Due to the radioactive material, the automated equipment is being frequently developed to replace human operators who conduct dangerous, repetitive and dexterous operations. As to operation, the manipulating program is commonly coded using the spread sheet while the whole actuators are mapped in every step. The process map (program) is changed according to such parameters as temperature of reactor, keeping time, mixture sequence and amount of reagent. In cases of customizing the automated synthetical equipment or developing the new radiopharmaceuticals, lots of experiments should be conducted and the programming mistake is not allowed as it can lead abnormal control of the equipment to leak the radioactive materials. The exact process map has depended on trial and error manner. Thus, this study developed the methodology to tabulate the synthetical process to convert the process map automatically while the synthetical module formation is represented by a network model. The proposed method is validated using the actual radiopharmaceutical synthetical procedure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.713-725
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• 2022

Mostly, artificial intelligence does not show any definite change in emotions. For this reason, it is hard to demonstrate empathy in communication with humans. If frequency modification is applied to neutral emotions, or if a different emotional frequency is added to them, it is possible to develop artificial intelligence with emotions. This study proposes the emotion conversion using the Generative Adversarial Network (GAN) based voice frequency synthesis. The proposed method extracts a frequency from speech data of twenty-four actors and actresses. In other words, it extracts voice features of their different emotions, preserves linguistic features, and converts emotions only. After that, it generates a frequency in variational auto-encoding Wasserstein generative adversarial network (VAW-GAN) in order to make prosody and preserve linguistic information. That makes it possible to learn speech features in parallel. Finally, it corrects a frequency by employing Amplitude Scaling. With the use of the spectral conversion of logarithmic scale, it is converted into a frequency in consideration of human hearing features. Accordingly, the proposed technique provides the emotion conversion of speeches in order to express emotions in line with artificially generated voices or speeches.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.256-263
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• 1998

Among process synthesis problems, the heat exchanger network (HEN) has been subjected to the most concentrated effort because this kind of problems was well defined for solving it and 20-30% energy savings could be realized in the present chemical processes. In this paper, we use an evolutionary approach for HEN synthesis because this approach can overcome the local optimum and combine some heuristic rules. The basic evolutionary approach is composed of three parts, that is, initialization step, growth step and mutation step, as in the simulated annealing and genetic algorithm. This algorithm uses the ecological rule that a better cell will live and worse cell should decompose after repeated generations. With this basic concept, a new procedure is developed and a more efficient method is proposed to generate initial solutions. Its effectiveness is shown using test examples.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2726-2728
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• 2001

This paper describes an optimal synthesis method of binary neural network(BNN) for an approximation problem of a circular region using a newly proposed learning algorithm[7] Our object is to minimize the number of connections and neurons in hidden layer by using a Newly Expanded and Truncated Learning Algorithm(NETLA) for the multilayer BNN. The synthesis method in the NETLA is based on the extension principle of Expanded and Truncated Learning(ETL) and is based on Expanded Sum of Product (ESP) as one of the boolean expression techniques. And it has an ability to optimize the given BNN in the binary space without any iterative training as the conventional Error Back Propagation(EBP) algorithm[6] If all the true and false patterns are only given, the connection weights and the threshold values can be immediately determined by an optimal synthesis method of the NETLA without any tedious learning. Futhermore, the number of the required neurons in hidden layer can be reduced and the fast learning of BNN can be realized. The superiority of this NETLA to other algorithms was proved by the approximation problem of one circular region.

• Journal of Energy Engineering
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• v.2 no.2
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• pp.215-224
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• 1993

Heat exchanger network synthesis is very useful to aspects of energy recovery and saving. In order to obtain the optimal network structure for minimum utility cost, multiple utilities were used. In this study, the practical matches of process streams were not considered, but only evaluation of targets was demonstrated. The program developed in this work was applied to the alcohol production process and it was possible to find the optimal cost targets.

• Journal of Energy Engineering
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• v.1 no.1
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• pp.87-96
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• 1992

Two major difficulties with finding an optimal solution to the heat exchanger network synthesis problems are the large solutionspace and the uncertainty in the formulation of the annual cost function. In this work, to overcome the first difficulty a problem reduction technique was developed. The second difficulty was also removed by dividing the annual cost function into four cost items. The optimal network structure for minimum equipment cost is then obtained by repeatedly applying the problem reduction technique and the heuristics in turn. The efficiency and the superiority of the method is demonstrated by examining two selected example problems.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.166-173
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• 2013

As the number of IPs and the communication volume among them have constantly increased, on-chip crossbar network is now the most widely-used on-chip communication backbone of contemporary SoCs. The on-chip crossbar network consists of multiple crossbars and the connections among the IPs and the crossbars. As the complexity of SoCs increases, it has also become more and more complex to determine the topology of the crossbar network. To tackle this problem, this paper proposes an on-chip crossbar network topology method for application-specific systems. The proposed method uses mixed integer linear programming to solve the topology synthesis problem, thus the global optimality is guaranteed. Unlike the previous MILP-based methods which represent the topology with adjacency matrixes of IPs and crossbar switches, the proposed method uses the communication edges among IPs as the basic element of the representation. The experimental results show that the proposed MILP formulation outperforms the previous one by improving the synthesis speed by 77.1 times on average, for 4 realistic benchmarks.

• Transactions of the Korean hydrogen and new energy society
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• v.33 no.5
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• pp.515-524
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• 2022

In this study, the on-site hydrogen production process for refueling stations that were not energy-optimized was improved through exergy analysis and heat exchange network synthesis. Furthermore, the process was scaled up from 30 Nm3/h to 150 Nm3/h to improve hydrogen production capacity. Exergy analysis results show that exergy destruction in the SMR reactor and the heat exchanger accounts for 58.1 and 19.8%, respectively. Thus, the process is improved by modifying the heat exchange network to reduce the exergy loss in these units. As a result of the process simulation analysis, thermal and exergy efficiency is improved from 75.7 to 78.6% and 68.1 to 70.4%, respectively. In conclusion, it is expected to improve the process efficiency when installing on-site hydrogen refueling stations.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.657-659
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• 2004

CAN is a serial communication bus for real-time controls and automations in distributed control systems. In distributed control systems, occasionally a sensor module and a controller are not in the same node and physically separated. In order for the signal from a sensor node to reach the controller node, the signal must travel through network. CAN has a certain capabilities to deal with real-time data. However, when many nodes on the networks try to send data on the same network, the arbitration mechanism to solve the data collision problem is necessary. This situation causes the time delay which has detrimental effects on the performance of the control systems. This paper proposes a method to solve the problem due to the time delay in distributed control system using CAN. Time delay is approximated to an element with a rational transfer function using Pade approximation and Mu~synthesis method is applied. Since time delay in the network is not constant, the time delay element is considered to be an uncertainty block with a bound. The proposed method is applied to the experimental system with CAN and proved to be effective.

• 전기의세계
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• v.24 no.4
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• pp.80-82
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• 1975

This paper presents a synthesis procedure of multi-channel active filters, which realizes an arbitrary N*N matrix of real rational functions in the complex variable s as a voltage transfer matrix. The resultant network reveals a transformerless grounded active RC(2N+1)-terminal network. The active network is consisted of six 2N-port RC networks with 2N single-ended operational amplifiers.