• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.85-94
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• 2024

In this paper, we present the very first time the generalized notion of (α, β, γ, δ) - convex (concave) function in mixed kind, which is the generalization of (α, β) - convex (concave) functions in 1^st and 2^nd kind, (s, r) - convex (concave) functions in mixed kind, s - convex (concave) functions in 1^st and 2^nd kind, p - convex (concave) functions, quasi convex(concave) functions and the class of convex (concave) functions. We would like to state the well-known Ostrowski inequality via SVN-Riemann Integrals for (α, β, γ, δ) - convex (concave) function in mixed kind. Moreover we establish some SVN-Ostrowski type inequalities for the class of functions whose derivatives in absolute values at certain powers are (α, β, γ, δ)-convex (concave) functions in mixed kind by using different techniques including Hölder's inequality and power mean inequality. Also, various established results would be captured as special cases with respect to convexity of function.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.3
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• pp.348-357
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• 2013

This work describes an approach that contributes to derive from mission to critical functions of the attack helicopter under future battle space environment. An existing mission of the attack helicopter is limited to the only shooter oriented functions. In the future environment, mission and its functions of the helicopter might be much expanded. The functions should be derived by the top down approach based on systems engineering approach. In this point of view, this work describes network based future battle environment. From this environment, the missions of the attack helicopter are identified and optimized functions are derived through sequential procedures like from missions to tasks, tasks to activities, and activities to functions. The selected activities are obtained from the tasks using QFD. The weighting scores of the QFD are calculated by the AHP computational procedure. Finally the critical functions are presented through the similar procedure.

• Journal of information and communication convergence engineering
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• v.17 no.3
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• pp.185-190
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• 2019

The explosive growth of data traffic and services has created cost challenges for networks. Studies have attempted to effectively apply network slicing in fifth generation networks to provide high speed, low latency, and various compatible services. However, in network slicing using mixed-integer linear programming, the operation count increases exponentially with the number of physical servers and virtual network functions (VNFs) to be allocated. Therefore, we propose an efficient slice allocation method based on cluster technology, comprising the following three steps: i) clustering physical servers; ii) selecting an appropriate cluster to allocate a VNF; iii) selecting an appropriate physical server for VNF allocation. Solver runtimes of the existing and proposed methods are compared, under similar settings, with respect to intra-slice isolation. The results show that solver runtime decreases, by approximately 30% on average, with an increase in the number of physical servers within the cluster in the presence of intra-slice isolation.

• Korean Journal of Biological Psychiatry
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• v.4 no.2
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• pp.194-197
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• 1997

Neural network models, also known as connectionist models or PDP models, simulate some functions of the brain and may promise to give insight in understanding the cognitive brain functions. The models composed of neuron-like elements that are linked into circuits can learn and adapt to its environment in a trial and error fashion. In this article, the history and principles of the neural network modeling are briefly reviewed, and its applications to psychiatry are discussed.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.30A no.12
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• pp.1-9
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• 1993

In this paper, to realize the network management function in automated manufacturing network Mini-MAP, the network management requirements are analyzed and the network management system is implemented on the basis of this analysis. The implemented management system which has both local management and remote management mechanism is considered as a single domain on the Mini-MAP network. Here, the remote management functions consist of network status, monitoring and remote operations and the local management functions have parameter display and network self testing. The MAP network controller is designed according to the MAP version 3.0 specifications and IEEE 802 standards. the operations of network management system are certified througth the test environments which consists of the implemented network adaptor and softwares for Mini-MAP.

• Asia pacific journal of information systems
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• v.27 no.4
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• pp.191-215
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• 2017

This study investigated the antecedents and the performance impact of two types of Smartphone functions (communication vs. computing functions) in organizational environment and the moderating impact of Smartphone users' organizational roles. More specifically, identifying two distinct types of Smartphone functions such as communication functions and computing functions (including informational, social network, and resource management functions), we investigated the impact of three antecedents (Smartphone dependency, task mobility, and perceived critical mass) on the use of the two Smartphone functions and how organizational workers' perceived performance gains differ by using these two different Smartphone functions for their workplace activities. We tested our hypotheses with survey data collected from 176 organizational workers. Our findings suggest that Smartphone dependency, task mobility and perceived critical mass of Smartphone use are significantly associated with the use of the two different functions, and that the use of computing functions is more strongly associated with perceived performance gain than the use of communication functions. We also found that managerial roles played by individual workers differently moderate the impact of Smartphone use on perceived performance gain. The present findings enable researchers and practitioners to better understand the impact of Smartphone use in workplaces.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.16 no.1
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• pp.285-314
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• 2005

The purpose of this study is to review and analyze the overlapping functions and activities of the nationwide scientific and technical information network system This study is helpful for users to gather information and for librarians and nations to reduce wastage of budgets through discarding the duplicated expenses of performing activities of the network systems. The research targets are KISTI and KERIS, which are functioning as the information network systems in the fields of science and technology. The research methods are literary reviews for theory background and analysis of their activities from internet homepages. As a result of the research, it is found and confirmed that there are some overlapping and duplicating functions and activities in the network systems.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.17-23
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• 2022

Network slicing is a promising paradigm and significant evolution for adjusting the heterogeneous services based on different requirements by placing dynamic virtual network functions (VNF) forwarding graph (VNFFG) and orchestrating service function chaining (SFC) based on criticalities of Quality of Service (QoS) classes. In system architecture, software-defined networks (SDN), network functions virtualization (NFV), and edge computing are used to provide resourceful data view, configurable virtual resources, and control interfaces for developing the modified deep reinforcement learning agent (MDRL-A). In this paper, task requests, tolerable delays, and required resources are differentiated for input state observations to identify the non-critical/critical classes, since each user equipment can execute different QoS application services. We design intelligent slicing for handing the cross-domain resource with MDRL-A in solving network problems and eliminating resource usage. The agent interacts with controllers and orchestrators to manage the flow rule installation and physical resource allocation in NFV infrastructure (NFVI) with the proposed formulation of completion time and criticality criteria. Simulation is conducted in SDN/NFV environment and capturing the QoS performances between conventional and MDRL-A approaches.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.993-996
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• 1993

This paper addresses the structure and its associated learning algorithms of a feedforward multi-layered connectionist network, which has distributed learning abilities, for realizing the basic elements and functions of a traditional fuzzy logic controller. The proposed neural-network-based fuzzy logic control system (NN-FLCS) can be contrasted with the traditional fuzzy logic control system in their network structure and learning ability. An on-line supervised structure/parameter learning algorithm dynamic learning algorithm can find proper fuzzy logic rules, membership functions, and the size of output fuzzy partitions simultaneously. Next, a Reinforcement Neural-Network-Based Fuzzy Logic Control System (RNN-FLCS) is proposed which consists of two closely integrated Neural-Network-Based Fuzzy Logic Controllers (NN-FLCS) for solving various reinforcement learning problems in fuzzy logic systems. One NN-FLC functions as a fuzzy predictor and the other as a fuzzy controller. As ociated with the proposed RNN-FLCS is the reinforcement structure/parameter learning algorithm which dynamically determines the proper network size, connections, and parameters of the RNN-FLCS through an external reinforcement signal. Furthermore, learning can proceed even in the period without any external reinforcement feedback.

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.717-722
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• 2004

This paper presents fuzzy rules to predict diagnosis of Wisconsin breast cancer using neural network with weighted fuzzy membership functions (NNWFM). NNWFM is capable of self-adapting weighted membership functions to enhance accuracy in prediction from the given clinical training data. n set of small, medium, and large weighted triangular membership functions in a hyperbox are used for representing n set of featured input. The membership functions are randomly distributed and weighted initially, and then their positions and weights are adjusted during learning. After learning, prediction rules are extracted directly from the enhanced bounded sums of n set of weighted fuzzy membership functions. Two number of prediction rules extracted from NNWFM outperforms to the current published results in number of rules and accuracy with 99.41%.