• Journal of information and communication convergence engineering
• /
• v.12 no.4
• /
• pp.252-256
• /
• 2014

Traditional block cipher Advanced Encryption Standard (AES) is widely used in the field of network security, but it has high overhead on each operation. In the 15th international workshop on information security applications, a novel lightweight and low-power encryption algorithm named low-power encryption algorithm (LEA) was released. This algorithm has certain useful features for hardware and software implementations, that is, simple addition, rotation, exclusive-or (ARX) operations, non-Substitute-BOX architecture, and 32-bit word size. In this study, we further improve the LEA encryptions for cloud computing. The Web-based implementations include JavaScript and assembly codes. Unlike normal implementation, JavaScript does not support unsigned integer and rotation operations; therefore, we present several techniques for resolving this issue. Furthermore, the proposed method yields a speed-optimized result and shows high performance enhancements. Each implementation is tested using various Web browsers, such as Google Chrome, Internet Explorer, and Mozilla Firefox, and on various devices including personal computers and mobile devices. These results extend the use of LEA encryption to any circumstance.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2008.10a
• /
• pp.191-196
• /
• 2008

This paper presents an evolutionary algorithm for goal programming with preemptive priority. To do this, an evolutionary strategy is suggested which search for the solution satisfying the goals in the order of the priority. Two-sided assembly line balancing problems with multiple goals are used to validate the applicability of the algorithm. In the problems, three goals are considered in the following priority order: minimizing the number of mated-stations, achieving the goal level of workload smoothness, and maximizing the work relatedness. The proper evolutionary components such as encoding and decoding method, evaluation scheme, and genetic operators, which are specific to the problem being solved, are designed in order to improve the algorithm's performance. The computational result is reported.

• Journal of the Society of Naval Architects of Korea
• /
• v.51 no.3
• /
• pp.239-245
• /
• 2014

This paper deal with the block storage planning problem of storing and retrieving assembly blocks in a temporary storage yard with limited capacity, which is one of the critical managerial problems in shipbuilding. The block storage planning problem is required to minimize the number of relocations of blocks while the constraints for storage and retrieval time windows are satisfied. We first show NP-hardness of the block storage planning problem. Next we propose a heuristic algorithm to generate good quality solutions for larger instances in very short computational time. The proposed heuristic algorithm was validated by comparing the results with the mathematical model presented in the previous study.

• Journal of the Korea Safety Management & Science
• /
• v.7 no.3
• /
• pp.85-96
• /
• 2005

This paper is concerned with the integrated problem of line balancing and model sequencing in mixed model assembly lines(MMALBS), which is important to efficient utilization of the lines. In the problem, we deal with the objective of minimizing the overall line length To apply the GAs to MMALBS problems, we suggest a GA representation which suitable for its problems, an efficient decoding technique for the objective, and genetic operators which produce feasible offsprings. Extensive experiments are carried out to analyze the performance of the proposed algorithm. The computational results show that our algorithm is promising in solution quality.

• Journal of Korean Institute of Industrial Engineers
• /
• v.22 no.4
• /
• pp.533-549
• /
• 1996

This paper is concerned with a sequencing problem in mixed model assembly lines, which is important to efficient utilization of the lines. In the problem, we deal with the two objectives of minimizing the risk of stoppage and leveling part usage, and consider sequence-dependent setup time. In this paper, we present a genetic algorithm(GA) suitable for the multi-objective optimization problem. The aim of multi-objective optimization problems is to find all possible non-dominated solutions. The proposed algorithm is compared with existing multi-objective GAs such as vector evaluated GA, Pareto GA, and niched Pareto GA. The results show that our algorithm outperforms the compared algorithms in finding good solutions and diverse non-dominated solutions.

• IE interfaces
• /
• v.12 no.4
• /
• pp.586-594
• /
• 1999

This paper introduces a production scheduling system for the block assembly shop in a shipbuilding company. We are to make a schedule for the assembly shop and related subassembly production shop. The objectives of the scheduling system are balancing of the workload of the subassembly shops as well as the assembly shop. There are a number of technological and resource constraints including assembly space restriction which is most important and critical resource in the shop. It is very hard and time consuming to consider the two problems, the workload balancing and the spatial allocation problem, simultaneously, and hence, we analyze the two problems independently. The first problem has already been introduced(고시근, 1996), and the overall appearance of the system and the spatial allocation algorithm are presented in this paper.

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10b
• /
• pp.318-323
• /
• 1992

The improvement of the production capability of multi PCB assembly line can not be simply done by improving the capacities of each assembly robot cells but must be done by controlling the production line effectively with the line host computer which controls over the whole assembly line. A real time production control, a real time model change and a real time trouble shooting compose the specific concepts of this technique. In this paper, we present and analyze the definition and application method of real time assembly concept. The meaning of real time model change, troubles and error sooting and its algorithm will be introduced. Also, the function of the host computer which is in charge of all of many different tasks mentioned above and the method are presented. The improvement of the productivity is mainly focused on the efficiency of multi-PCB production control. The importance of this aspect is gradually increasing, which we have presented the analysis and the solution.

• Journal of Institute of Control, Robotics and Systems
• /
• v.10 no.10
• /
• pp.878-886
• /
• 2004

Uncertainties are inevitable in robotic assembly in unstructured environment since it is difficult to construct fixtures to guide motions of robots. This paper proposes an augmented Petri net and an algorithm to adapt the assembly model on-line during actual assembly process. The augmented Petri net identifies events using force and position information simultaneously. Unmodeled contact states are identified and incorporated into the model on-line. The proposed method increases the level of intelligence of the robot system by enhancing the autonomy. The proposed method is evaluated by simulation and experiments with L-type peg-in-hole assembly using a two-arm robot system.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.35 no.5
• /
• pp.259-266
• /
• 2022

In this study, we developed a deep learning and vision sensor-based assembly performance evaluation method isfor prefabricated steel structures. The assembly parts were segmented using a modified version of the receptive field block convolution module inspired by the eccentric function of the human visual system. The quality of the assembly was evaluated by detecting the bolt holes in the segmented assembly part and calculating the bolt hole positions. To validate the performance of the evaluation, models of standard and defective assembly parts were produced using a 3D printer. The assembly part segmentation network was trained based on the 3D model images captured from a vision sensor. The sbolt hole positions in the segmented assembly image were calculated using image processing techniques, and the assembly performance evaluation using the k-nearest neighbor algorithm was verified. The experimental results show that the assembly parts were segmented with high precision, and the assembly performance based on the positions of the bolt holes in the detected assembly part was evaluated with a classification error of less than 5%.

• ETRI Journal
• /
• v.24 no.4
• /
• pp.311-322
• /
• 2002

Presently, optical burst switching (OBS) technology is under study as a promising solution for the backbone of the optical Internet in the near future because OBS eliminates the optical buffer problem at the switching node with the help of no optical/electro/optical conversion and guarantees class of service without any buffering. To implement the OBS network, there are a lot of challenging issues to be solved. The edge router, burst offset time management, and burst assembly mechanism are critical issues. In addition, the core router needs data burst and control header packet scheduling, a protection and restoration mechanism, and a contention resolution scheme. In this paper, we focus on the burst assembly mechanism. We present a novel data burst generation algorithm that uses hysteresis characteristics in the queueing model for the ingress edge node in optical burst switching networks. Simulation with Poisson and self-similar traffic models shows that this algorithm adaptively changes the data burst size according to the offered load and offers high average data burst utilization with a lower timer operation. It also reduces the possibility of a continuous blocking problem in the bandwidth reservation request, limits the maximum queueing delay, and minimizes the required burst size by lifting up data burst utilization for bursty input IP traffic.