• Title/Summary/Keyword: Memory Problem

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A Clonal Selection Algorithm using the Rolling Planning and an Extended Memory Cell for the Inventory Routing Problem (연동계획과 확장된 기억 세포를 이용한 재고 및 경로 문제의 복제선택해법)

  • Yang, Byoung-Hak
    • Korean Management Science Review
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    • v.26 no.1
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    • pp.171-182
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    • 2009
  • We consider the inventory replenishment problem and the vehicle routing problem simultaneously in the vending machine operation. This problem is known as the inventory routing problem. We design a memory cell in the clonal selection algorithm. The memory cell store the best solution of previous solved problem and use an initial solution for next problem. In general, the other clonal selection algorithm used memory cell for reserving the best solution in current problem. Experiments are performed for testing efficiency of the memory cell in demand uncertainty. Experiment result shows that the solution quality of our algorithm is similar to general clonal selection algorithm and the calculations time is reduced by 20% when the demand uncertainty is less than 30%.

A Psychological Model Applied to Mathematical Problem Solving

  • Alamolhodaei, Hassan;Farsad, Najmeh
    • Research in Mathematical Education
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    • v.13 no.3
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    • pp.181-195
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    • 2009
  • Students' approaches to mathematical problem solving vary greatly with each other. The main objective of the current study was to compare students' performance with different thinking styles (divergent vs. convergent) and working memory capacity upon mathematical problem solving. A sample of 150 high school girls, ages 15 to 16, was studied based on Hudson's test and Digit Span Backwards test as well as a math exam. The results indicated that the effect of thinking styles and working memory on students' performance in problem solving was significant. Moreover, students with divergent thinking style and high working memory capacity showed higher performance than ones with convergent thinking style. The implications of these results on math teaching and problem solving emphasizes that cognitive predictor variable (Convergent/Divergent) and working memory, in particular could be challenging and a rather distinctive factor for students.

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A Memory Configuration Method for Virtual Machine Based on User Preference in Distributed Cloud

  • Liu, Shukun;Jia, Weijia;Pan, Xianmin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.11
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    • pp.5234-5251
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    • 2018
  • It is well-known that virtualization technology can bring many benefits not only to users but also to service providers. From the view of system security and resource utility, higher resource sharing degree and higher system reliability can be obtained by the introduction of virtualization technology in distributed cloud. The small size time-sharing multiplexing technology which is based on virtual machine in distributed cloud platform can enhance the resource utilization effectively by server consolidation. In this paper, the concept of memory block and user satisfaction is redefined combined with user requirements. According to the unbalanced memory resource states and user preference requirements in multi-virtual machine environments, a model of proper memory resource allocation is proposed combined with memory block and user satisfaction, and at the same time a memory optimization allocation algorithm is proposed which is based on virtual memory block, makespan and user satisfaction under the premise of an orderly physical nodes states also. In the algorithm, a memory optimal problem can be transformed into a resource workload balance problem. All the virtual machine tasks are simulated in Cloudsim platform. And the experimental results show that the problem of virtual machine memory resource allocation can be solved flexibly and efficiently.

Fixed-Length Allocation and Deallocation of Memory for Embedded Java Virtual Machine (임베디드 자바가상기계를 위한 고정 크기 메모리 할당 및 해제)

  • 양희재
    • Proceedings of the IEEK Conference
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    • 2003.07d
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    • pp.1335-1338
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    • 2003
  • Fixed-size memory allocation is one of the most promising way to avoid external fragmentation in dynamic memory allocation problem. This paper presents an experimental result of applying the fixed- size memory allocation strategy to Java virtual machine for embedded system. The result says that although this strategy induces another memory utilization problem caused by internal fragmentation, the effect is not very considerable and this strategy is well-suited for embedded Java system. The experiment has been performed in a real embedded Java system called the simpleRTJ.

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An Artificial Immune system using Memory Cell for the Inventory Routing Problem (기억 세포를 이용한 재고-차량 경로 문제의 인공면역시스템)

  • Yang, Byoung-Hak
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2008.10a
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    • pp.236-246
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    • 2008
  • We consider the Inventory Routing problem(IRP) for the vending machine operating system. An artificial immune system(AIS) is introduced to solve the IRP. The IPR is an rolling wave planning. The previous solution of IRP is one of good initial solution of current IRP. We introduce an Artificial Immune system with memory cell (AISM) which store previous solution in memory cell and use an initial solution for current problem. Experiment results shows that AISM reduced calculations time in relatively less demand uncertainty.

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Formal Analysis of Distributed Shared Memory Algorithms

  • Muhammad Atif;Muhammad Adnan Hashmi;Mudassar Naseer;Ahmad Salman Khan
    • International Journal of Computer Science & Network Security
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    • v.24 no.4
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    • pp.192-196
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    • 2024
  • The memory coherence problem occurs while mapping shared virtual memory in a loosely coupled multiprocessors setup. Memory is considered coherent if a read operation provides same data written in the last write operation. The problem is addressed in the literature using different algorithms. The big question is on the correctness of such a distributed algorithm. Formal verification is the principal term for a group of techniques that routinely use an analysis that is established on mathematical transformations to conclude the rightness of hardware or software behavior in divergence to dynamic verification techniques. This paper uses UPPAAL model checker to model the dynamic distributed algorithm for shared virtual memory given by K.Li and P.Hudak. We analyse the mechanism to keep the coherence of memory in every read and write operation by using a dynamic distributed algorithm. Our results show that the dynamic distributed algorithm for shared virtual memory partially fulfils its functional requirements.

Bitmap-based Routing Protocol for Improving Energy and Memory Efficiency (에너지 및 메모리 효율성을 개선한 비트맵기반 라우팅 프로토콜)

  • Choi, Hae Won;Kim, Sang Jin;Ryoo, Myung Chun
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.5 no.3
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    • pp.59-67
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    • 2009
  • This paper proposes a improved bitmap routing protocol, which finds the best energy efficient routing path by minimizing the network overheads and prolongs the overall network lifetime. Jung proposed a bitmap scheme for sensor networks. His scheme uses a bitmap table to represent the connection information between nodes. However, it has a problem that the table size is depends on the number of nodes in the sensor networks. The problem is very serious in the sensor node with a limited memory. Thereby, this paper proposes a improved bitmap routing protocol to solve the problem in Jung's scheme. Proposed protocol over the memory restricted sensor network could optimize the size of bitmap table by applying the deployed network property. Proposed protocol could be used in the diversity of sensor networks due to it has minimum memory overheads.

A Survey on Neural Networks Using Memory Component (메모리 요소를 활용한 신경망 연구 동향)

  • Lee, Jihwan;Park, Jinuk;Kim, Jaehyung;Kim, Jaein;Roh, Hongchan;Park, Sanghyun
    • KIPS Transactions on Software and Data Engineering
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    • v.7 no.8
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    • pp.307-324
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    • 2018
  • Recently, recurrent neural networks have been attracting attention in solving prediction problem of sequential data through structure considering time dependency. However, as the time step of sequential data increases, the problem of the gradient vanishing is occurred. Long short-term memory models have been proposed to solve this problem, but there is a limit to storing a lot of data and preserving it for a long time. Therefore, research on memory-augmented neural network (MANN), which is a learning model using recurrent neural networks and memory elements, has been actively conducted. In this paper, we describe the structure and characteristics of MANN models that emerged as a hot topic in deep learning field and present the latest techniques and future research that utilize MANN.

Development and Application of Conducting Shape Memory Polyurethane Actuators (전도성 형상 기억 폴리우레탄 작동기의 개발 및 응용)

  • Paik, Il-Hyun;Jung, Yong-Chae;Cho, Jae-Hwan;Goo, Nam-Seo
    • Proceedings of the Korean Society For Composite Materials Conference
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    • 2005.04a
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    • pp.226-230
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    • 2005
  • This paper presents the actuation performance of a conducting shape memory polyurethane (CSMPU) actuator. We introduced a concept of shape memory polyurethane activated by electric power while conventional shape memory polyurethanes are activated by external heat source. A conducting shape memory polyurethane actuator was manufactured by adding cabon nano-tube to conventional shape memory polyurethane. The main problem of the previous CSMPU was bad dispersion of carbon nano-tubes in polyurethane. In this paper, we have tried to find manufacturing method to solve the dispersion problem. With a lot of elaborative works, we have developed conducting shape memory polyurethane actuator with good electrical performance. The actuation performance of the developed conducting shape memory polyurethane actuator was measured and assessed.

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