• 제목/요약/키워드: end-to-end approach.

검색결과 1,383건 처리시간 0.037초

사용자 주도형 정보시스템 개발 (User-Led Information Systems Development)

  • 정승렬;서창갑
    • Asia pacific journal of information systems
    • /
    • 제10권3호
    • /
    • pp.41-59
    • /
    • 2000
  • The role of information systems(IS) is far more important in business operations today. Managers recognize information as a major resource of the organization, and non-expert end users positively participate in information system development processes. This phenomenon is considered user-led information system development(ULD), where users define the information requirements, oversee system testing, manage system development, and lead the overall project. Based on a socio-technical approach, this study examines the impact of ULD on IS success. This paper also investigates the moderating effects of various contextual factors on the relationships between ULD and the success. The questionnaire was developed and the data was collected from the end users who participated in implementing ERP systems. The results showed that ULD positively affects the success. For the moderating variables, IT complexity was found to have a strong effect on the relationship between ULD and the success while business complexity and top management support have partial effects. Surprisingly, resource adequacy was not found to have the effect. This study provides academia and practitioners with a number of implications and guidelines regarding why and when to introduce ULD in their IS development initiatives.

  • PDF

Distortional buckling formulae for cold-formed steel rack-section members

  • Silvestre, N.;Camotim, D.
    • Steel and Composite Structures
    • /
    • 제4권1호
    • /
    • pp.49-75
    • /
    • 2004
  • The paper derives, validates and illustrates the application of GBT-based formulae to estimate distortional critical lengths and bifurcation stress resultants in cold-formed steel rack-section columns, beams and beam-columns with arbitrarily inclined mid-stiffeners and four support conditions. After a brief review of the Generalised Beam Theory (GBT) basics, the main concepts and procedures employed to obtain the formulae are addressed. Then, the GBT-based estimates are compared with exact results and, when possible, also with values yielded by formulae due to Lau and Hancock, Hancock and Teng et al. A few remarks on novel aspects of the rack-section beam-column distortional buckling behaviour, unveiled by the GBT-based approach, are also included.

IP 네트워크의 대역폭 및 버퍼 관리 메커니즘에 관한 연구 (A Study on Bandwidth and Buffer Management Mechanisms of IP Networks)

  • Hai, Hoang Dang;Thuong, Pham Van;Hong, You-Sik
    • 한국인터넷방송통신학회논문지
    • /
    • 제10권2호
    • /
    • pp.143-149
    • /
    • 2010
  • 대역폭 및 버퍼는 엔드-투-엔드 품질 서비스를 결정하기위한 중요한 네트워크 리소스이다. 본 논문에서는 대역폭과 버퍼 관리에 관한 몇 가지 기법에 대해 조사 및 TCP / IP 네트워크의 처리량을 제어에 사용되는 유형에 따라 분류 하고자 한다. 뿐만 아니라, 본 논문에서는 모델링 활성 대역폭을 위한 새로운 접근법을 제시 및 TCP / IP용 네트워크에 대한 버퍼의 제어 메커니즘에 대한 새로운 접근법을 제시한다.

High Performance Implementation of SGCM on High-End IoT Devices

  • Seo, Hwajeong
    • Journal of information and communication convergence engineering
    • /
    • 제15권4호
    • /
    • pp.212-216
    • /
    • 2017
  • In this paper, we introduce novel techniques to improve the high performance of AE functions on modern high-end IoT platforms (ARM-NEON), which support SIMD and cryptography instruction sets. For the Sophie Germain Counter Mode of operation (SGCM), counter modes of encryption and prime field multiplication are required. We chose the Montgomery multiplication for modular multiplication. We perform Montgomery multiplication in a parallel way by exploiting both the ARM and NEON instruction sets. Specifically, the NEON instruction performed 128-bit integer multiplication and the ARM instruction performed Montgomery reduction, simultaneously. This approach hides the latency for ARM in the NEON instruction set. For a high-speed counter mode of encryptions for both AE functions, we introduced two-level computations. When the tasks were large volume, we switched to the NEON instruction to execute the encryption operations. Otherwise, we performed the encryptions on the ARM module.

Optimal SMDP-Based Connection Admission Control Mechanism in Cognitive Radio Sensor Networks

  • Hosseini, Elahe;Berangi, Reza
    • ETRI Journal
    • /
    • 제39권3호
    • /
    • pp.345-352
    • /
    • 2017
  • Traffic management is a highly beneficial mechanism for satisfying quality-of-service requirements and overcoming the resource scarcity problems in networks. This paper introduces an optimal connection admission control mechanism to decrease the packet loss ratio and end-to-end delay in cognitive radio sensor networks (CRSNs). This mechanism admits data flows based on the value of information sent by the sensor nodes, the network state, and the estimated required resources of the data flows. The number of required channels of each data flow is estimated using a proposed formula that is inspired by a graph coloring approach. The proposed admission control mechanism is formulated as a semi-Markov decision process and a linear programming problem is derived to obtain the optimal admission control policy for obtaining the maximum reward. Simulation results demonstrate that the proposed mechanism outperforms a recently proposed admission control mechanism in CRSNs.

쌍입력 기술함수를 갖는 비선형 보상기를 이용한 유연한 빔의 제어 (The Control of Flexible Beam using Nonlinear Compensator with Dual-Input Describing Function)

  • 권세현;이형기;최부귀
    • 제어로봇시스템학회논문지
    • /
    • 제4권5호
    • /
    • pp.644-650
    • /
    • 1998
  • In this paper , a state space model for flexible beam is presented using the assumed-modes approach. The state space equation is derived for a flexible beam in which one end is connected to a motor and is driven by a torque equation and the other end is free. Many of the transfer function proposed thus far use the torque to the flexible beam as the input and the tip deflection of the flexible beam as the output. The Technique for the analysis and synthesis of the dual-input describing function(DIDF) is introduced here and the construction of a non-linear compensator, based on this technique, is proposed. This non-linear compensator, properly connected in the direct path of a closed-loop linear or non-linear control system. The above non-linear network is used to compensate linear and non-linear systems for instability, limit cycles, low speed of response and static accuracy. The effectiveness of the proposed scheme is demonstrated through computer simulation and experimental results.

  • PDF

Molecular Dynamics Simulation of Liquid Alkanes III. Thermodynamic, Structural, and Dynamic Properties of Branched-Chain Alkanes

  • 이송희;이홍;박형숙
    • Bulletin of the Korean Chemical Society
    • /
    • 제18권5호
    • /
    • pp.501-509
    • /
    • 1997
  • In recent papers[Bull. Kor. Chem. Soc. 1996, 17, 735; ibid 1997, 18, 478] we reported results of molecular dynamics (MD) simulations for the thermodynamic, structural, and dynamic properties of liquid normal alkanes, from n-butane to n-heptadecane, using three different models. Two of the three classes of models are collapsed atomic models while the third class is an atomistically detailed model. In the present paper we present results of MD simulations for the corresponding properties of liquid branched-chain alkanes using the same models. The thermodynamic property reflects that the intermolecular interactions become weaker as the shape of the molecule tends to approach that of a sphere and the surface area decreases with branching. Not like observed in the straight-chain alkanes, the structural properties of model Ⅲ from the site-site radial distribution function, the distribution functions of the average end-to-end distance and the root-mean-squared radii of gyration are not much different from those of models Ⅰ and Ⅱ. The branching effect on the self diffusion of liquid alkanes is well predicted from our MD simulation results but not on the viscosity and thermal conductivity.

Implementation of Low-cost Autonomous Car for Lane Recognition and Keeping based on Deep Neural Network model

  • Song, Mi-Hwa
    • International Journal of Internet, Broadcasting and Communication
    • /
    • 제13권1호
    • /
    • pp.210-218
    • /
    • 2021
  • CNN (Convolutional Neural Network), a type of deep learning algorithm, is a type of artificial neural network used to analyze visual images. In deep learning, it is classified as a deep neural network and is most commonly used for visual image analysis. Accordingly, an AI autonomous driving model was constructed through real-time image processing, and a crosswalk image of a road was used as an obstacle. In this paper, we proposed a low-cost model that can actually implement autonomous driving based on the CNN model. The most well-known deep neural network technique for autonomous driving is investigated and an end-to-end model is applied. In particular, it was shown that training and self-driving on a simulated road is possible through a practical approach to realizing lane detection and keeping.

Managing the Back-end of the Nuclear Fuel Cycle: Lessons for New and Emerging Nuclear Power Users From the United States, South Korea and Taiwan

  • Newman, Andrew
    • 방사성폐기물학회지
    • /
    • 제19권4호
    • /
    • pp.435-446
    • /
    • 2021
  • This article examines the consequences of a significant spent fuel management decision or event in the United States, South Korea and Taiwan. For the United States, it is the financial impact of the Department of Energy's inability to take possession of spent fuel from commercial nuclear power companies beginning in 1998 as directed by Congress. For South Korea, it is the potential financial and socioeconomic impact of the successful construction, licensing and operation of a low and intermediate level waste disposal facility on the siting of a spent fuel/high level waste repository. For Taiwan, it is the operational impact of the Kuosheng 1 reactor running out of space in its spent fuel pool. From these, it draws six broad lessons other countries new to, or preparing for, nuclear energy production might take from these experiences. These include conservative planning, treating the back-end of the fuel cycle holistically and building trust through a step-by-step approach to waste disposal.

Variational autoencoder for prosody-based speaker recognition

  • Starlet Ben Alex;Leena Mary
    • ETRI Journal
    • /
    • 제45권4호
    • /
    • pp.678-689
    • /
    • 2023
  • This paper describes a novel end-to-end deep generative model-based speaker recognition system using prosodic features. The usefulness of variational autoencoders (VAE) in learning the speaker-specific prosody representations for the speaker recognition task is examined herein for the first time. The speech signal is first automatically segmented into syllable-like units using vowel onset points (VOP) and energy valleys. Prosodic features, such as the dynamics of duration, energy, and fundamental frequency (F0), are then extracted at the syllable level and used to train/adapt a speaker-dependent VAE from a universal VAE. The initial comparative studies on VAEs and traditional autoencoders (AE) suggest that the former can efficiently learn speaker representations. Investigations on the impact of gender information in speaker recognition also point out that gender-dependent impostor banks lead to higher accuracies. Finally, the evaluation on the NIST SRE 2010 dataset demonstrates the usefulness of the proposed approach for speaker recognition.