• 한국정보전자통신기술학회논문지
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• 제12권3호
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• pp.242-250
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• 2019

본 논문에서는 인공신경망(Artificial Neural Network) 모델 중, 시계열 데이터의 변환을 위한 모델인 Seq2Seq(Sequence to Sequence) 모델을 이용한 산업용 로봇 고장 예지 기술에 대하여 제안한다. 제안 방법은 고장 예지를 위한 추가적인 센서의 부착 없이 로봇 자체적으로 측정 가능한 관절 별 전류와 각도 값을 데이터로 사용하였고, 측정된 데이터를 모델이 학습할 수 있도록 전처리한 후, Seq2Seq 모델을 통해 전류를 각도로 변환하도록 지도 학습 하였다. 고장 진단을 위한 이상 정도(Abnormal degree)는 예측 각도와 실제 각도 간의 단위시간 동안의 RMSE(Root Mean Squared Error)를 사용하였다. 제안 방법의 성능평가는 로봇의 정상 및 결함 조건을 달리한 상태에서 측정한 테스트 데이터를 이용하여 수행되었고 이상 정도가 임계값 넘어가면 고장으로 분류하게 하여, 실험으로부터 96.67% 고장 진단 정확도를 보였다. 제안 방법은 별도의 추가적인 센서 없이 고장 예지 수행이 가능하다는 장점이 있으며, 로봇에 대한 깊은 전문지식을 요구하지 않으면서 수행할 수 있는 방법으로 높은 진단 성능과 효용성을 실험으로부터 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권3호
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• pp.941-955
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• 2015

In dual-channel networks (DCNs), all frequency hopping (FH) sequences used for data channels are chosen from the original FH sequence used for the control channel by shifting different initial phases. As the number of data channels increases, the hitting frequency point problem becomes considerably serious because DCNs is non-orthogonal synchronization network and FH sequences are non-orthogonal. The increasing severity of the hitting frequency point problem consequently reduces the resource utilization efficiency. To solve this problem, we propose a novel hitting frequency point collision avoidance method, which consists of a sequence-selection strategy called sliding correlation (SC) and a collision avoidance strategy called keeping silent on hitting frequency point (KSHF). SC is used to find the optimal phase-shifted FH sequence with the minimum number of hitting frequency points for a new data channel. The hitting frequency points and their locations in this optimal sequence are also derived for KSHF according to SC strategy. In KSHF, the transceivers transmit or receive symbol information not on the hitting frequency point, but on the next frequency point during the next FH period. Analytical and simulation results demonstrate that unlike the traditional method, the proposed method can effectively reduce the number of hitting frequency points and improve the efficiency of the code resource utilization.

• Interdisciplinary Bio Central
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• 제4권4호
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• pp.14.1-14.6
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• 2012

Splice site prediction in DNA sequence is a basic search problem for finding exon/intron and intron/exon boundaries. Removing introns and then joining the exons together forms the mRNA sequence. These sequences are the input of the translation process. It is a necessary step in the central dogma of molecular biology. The main task of splice site prediction is to find out the exact GT and AG ended sequences. Then it identifies the true and false GT and AG ended sequences among those candidate sequences. In this paper, we survey research works on splice site prediction based on support vector machine (SVM). The basic difference between these research works is nucleotide encoding technique and SVM kernel selection. Some methods encode the DNA sequence in a sparse way whereas others encode in a probabilistic manner. The encoded sequences serve as input of SVM. The task of SVM is to classify them using its learning model. The accuracy of classification largely depends on the proper kernel selection for sequence data as well as a selection of kernel parameter. We observe each encoding technique and classify them according to their similarity. Then we discuss about kernel and their parameter selection. Our survey paper provides a basic understanding of encoding approaches and proper kernel selection of SVM for splice site prediction.

• 경영과학
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• 제13권1호
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• pp.13-27
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• 1996

This paper considers the sequencing problem in mixed model assembly lines with hybrid workstation types and sequence-dependent setup times. Computation time is often a critical factor in choosing a method of determining the sequence. We develop a mathematical formulation of the problem to minimize the overall length of a line, and present a tabu search technique which can provide a near optimal solution in real time. The proposed technique is compared with a genetic algorithm and a branch-and-bound method. Experimental results are reported to demonstrate the efficiency of the technique.

• 대한산업공학회지
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• 제19권2호
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• pp.65-74
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• 1993

In this paper, a two-echelon production-inventory model is developed which integrates the production scheduling problem of the multi-products produced on a single facility and the inventory problem of the related raw materials. The setup costs of the final products are assumed to be dependent on the production sequence. The aim is to determine simultaneously the production cycle time and the production sequence of the final products, and the procurement cycle times of the raw materials. For the model developed, a solution algorithm is suggested and illustrated with a numerical example. And the result is compared with those obtained by two separate subproblems.

• Journal of Information Processing Systems
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• 제13권6호
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• pp.1554-1574
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• 2017

This paper introduces a new type of determining factor for Pseudo Random Strings (PRS). This classification depends upon a mathematical property called Finite Induction (FI). FI is similar to a Markov Model in that it presents a model of the sequence under consideration and determines the generating rules for this sequence. If these rules obey certain criteria, then we call the sequence generating these rules FI a PRS. We also consider the relationship of these kinds of PRS's to Good/deBruijn graphs and Linear Feedback Shift Registers (LFSR). We show that binary sequences from these special graphs have the FI property. We also show how such FI PRS's can be generated without consideration of the Hamiltonian cycles of the Good/deBruijn graphs. The FI PRS's also have maximum Shannon entropy, while sequences from LFSR's do not, nor are such sequences FI random.

• 한국지능시스템학회논문지
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• 제25권2호
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• pp.139-146
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• 2015

본 논문에서는 교정 제어에 의한 스위칭 비동기 순차 머신의 모델 정합 문제를 다룬다. 스위칭 비동기 순차 머신은 스위칭 신호에 따라서 여러 개의 비동기 순차 머신 특성을 번갈아 가면서 가지는 시스템이라고 정의한다. 이번 연구에서 스위칭 시스템이 가질 수 있는 스위칭 시퀀스(sequence)는 일정하게 고정되어 있다고 가정한다. 제어 목적은 폐루프 시스템의 안정 상태 동작을 주어진 기준 모델과 일치시키는 교정 제어기의 존재조건을 규명하고 제어기를 설계하는 일이다. 이를 위해서 스위칭 비동기 머신이 가지는 도달가능성을 표현하는 새로운 skeleton 행렬을 도입하고 모델 정합 교정 제어기의 존재조건을 기술한다. 또한 사례 연구를 통해 스위칭 신호를 생성하면서 동시에 교정 제어 입력을 변화시키는 새로운 교정 제어 알고리듬을 예시한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권2호
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• pp.538-561
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• 2020

Recommender Systems (RecSys) have a major role in e-commerce for recommending products, which they may like for every user and thus improve their business aspects. Although many types of RecSyss are there in the research field, the state of the art RecSys has focused on finding the user similarity based on sequence (e.g. purchase history, movie-watching history) analyzing and prediction techniques like Recurrent Neural Network in Deep learning. That is RecSys has considered as a sequence prediction problem. However, evaluation of similarities among the customers is challenging while considering temporal aspects, context and multi-component ratings of the item-records in the customer sequences. For addressing this issue, we are proposing a Deep Learning based model which learns customer similarity directly from the sequence to sequence similarity as well as item to item similarity by considering all features of the item, contexts, and rating components using Dynamic Temporal Warping(DTW) distance measure for dynamic temporal matching and 2D-GRU (Two Dimensional-Gated Recurrent Unit) architecture. This will overcome the limitation of non-linearity in the time dimension while measuring the similarity, and the find patterns more accurately and speedily from temporal and spatial contexts. Experiment on the real world movie data set LDOS-CoMoDa demonstrates the efficacy and promising utility of the proposed personalized RecSys architecture.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권3호
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• pp.1702-1721
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• 2019

A workflow process (or business process) management system helps to define, execute, monitor and manage workflow models deployed on a workflow-supported enterprise, and the system is compartmentalized into a modeling subsystem and an enacting subsystem, in general. The modeling subsystem's functionality is to discover and analyze workflow models via a theoretical modeling methodology like ICN, to graphically define them via a graphical representation notation like BPMN, and to systematically deploy those graphically defined models onto the enacting subsystem by transforming into their textual models represented by a standardized workflow process definition language like XPDL. Before deploying those defined workflow models, it is very important to inspect its syntactical correctness as well as its structural properness to minimize the loss of effectiveness and the depreciation of efficiency in managing the corresponding workflow models. In this paper, we are particularly interested in verifying very large-scale and massively parallel workflow models, and so we need a sophisticated analyzer to automatically analyze those specialized and complex styles of workflow models. One of the sophisticated analyzers devised in this paper is able to analyze not only the structural complexity but also the data-sequence complexity, especially. The structural complexity is based upon combinational usages of those control-structure constructs such as subprocesses, exclusive-OR, parallel-AND and iterative-LOOP primitives with preserving matched pairing and proper nesting properties, whereas the data-sequence complexity is based upon combinational usages of those relevant data repositories such as data definition sequences and data use sequences. Through the devised and implemented analyzer in this paper, we are able eventually to achieve the systematic verifications of the syntactical correctness as well as the effective validation of the structural properness on those complicate and large-scale styles of workflow models. As an experimental study, we apply the implemented analyzer to an exemplary large-scale and massively parallel workflow process model, the Large Bank Transaction Workflow Process Model, and show the structural complexity analysis results via a series of operational screens captured from the implemented analyzer.

• Plant Biotechnology Reports
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• 제2권1호
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• pp.59-73
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• 2008

Several aspects of photoperception and light signal transduction have been elucidated by studies with model plants. However, the information available for economically important crops, such as Fabaceae species, is scarce. In order to incorporate the existing genomic tools into a strategy to advance soybean research, we have investigated publicly available expressed sequence tag (EST) sequence databases in order to identify Glycine max sequences related to genes involved in light-regulated developmental control in model plants. Approximately 38,000 sequences from open-access databases were investigated, and all bona fide and putative photoreceptor gene families were found in soybean sequence databases. We have identified G. max orthologs for several families of transcriptional regulators and cytoplasmic proteins mediating photoreceptor-induced responses, although some important Arabidopsis phytochrome-signaling components are absent. Moreover, soybean and Arabidopsis genefamily homologs appear to have undergone a distinct expansion process in some cases. We propose a working model of light perception, signal transduction and response-eliciting in G. max, based on the identified key components from Arabidopsis. These results demonstrate the power of comparative genomics between model systems and crop species to elucidate several aspects of plant physiology and metabolism.