• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.178-185
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• 2021

The emergence of social networks has led to the flourishing of a new golden era of branding, which is a challenge for companies due to the need for creative positioning of companies with an emphasis on building trust and loyalty to the brand. Consumers are becoming more demanding and due to a wide range of products in different markets, make demands that are more stringent on companies. The goal of this article was to study the main trends of branding and advertising on social networks to develop a new approach to brand promotion. Methodology. The quantitative and qualitative research design was used to determine the main trends in branding and advertising on social networks. The methodology included the following methods: 1) analysis of the relationship between brand value and brand content strategy, 2) content analysis of the content of companies in social networks on the example of 10 world-famous brands with the highest value. The results allowed forming the criteria of effective content and communication: simplicity of content and simplicity of communication, lack of direct advertising of products, emphasis on global socio-economic problems and social orientation, unobtrusive communication, content creativity, indirect information about the product or work, the history of the company's development through various tools. The main content strategies of brands are defined: storytelling strategy; strategy of informing about the history of the company's development; entertainment and information strategy; strategy of joint interaction with the audience through the involvement of wellknown influencers or users of products. The theoretical and practical value of the results is confirmed by the conceptualization of the main content strategies of world-famous brands, which are pioneers in new ways to build relationships with users through social networks. The research proposes to use a customer-oriented approach to brand promotion. This means studying consumer behavior and predicting possible changes in behavior, which determines the level of interaction with the brand, the content strategy of the brand, and its effectiveness.

• Journal of Multimedia Information System
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• v.3 no.4
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• pp.135-140
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• 2016

To improve the throughput of Device-to-Device (D2D) communication, we focus on the scenario where D2D pair can reuse multi-channel of cellular communication. However, as sharing same channel with cellular communication can cause interference between D2D communication and cellular communication, a proper interference management is needed. In this paper, we propose interference-based channel allocation to select the channels to be used by D2D communication and a solution from game theory perspective to optimize the D2D communication throughput under multi-channel as well as guarantee the interference from it to cellular network. The simulation results verify the stability of the proposed method.

• Journal of the Semiconductor & Display Technology
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• v.12 no.2
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• pp.39-43
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• 2013

The semiconductor equipments generate necessary data through communication networks for the effective manufacturing processes and automation of semiconductor equipments. For transferring data between semiconductor equipments and sending data to monitor equipments, several standards for communication protocols have been proposed. Communication networks in semiconductor manufacturing systems will transmit a lot of data traffic, which can be vulnerable in data delay and network failure. Therefore, it is required that data traffic need to be distributed. To accomplish this objective, we recommend the use of a redundant and valuable communication path which is constructed by a wireless sensor network. In this paper, the directed diffusion method for wireless sensor networking is suggested for networking semiconductor equipments. It is shown that how the directed diffusion is employed to connect semiconductor equipments. Also, we show how to implement the SECS of semiconductor equipments communication protocols based on the directed diffusion.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1459-1461
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• 2005

This paper is proposed an efficiency optimization control algorithm for a synchronous reluctance motor which minimizes the copper and iron losses. The design of the speed controller based on fuzzy-neural networks(FNN) controller that is implemented using fuzzy control and neural networks. The control performance of the adaptive FNN controller is evaluated by analysis for various operating conditions. Simulation results are presented to show the validity of the proposed algorithm

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1479-1501
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• 2020

Dependable functioning of dynamic networks is essential for delivering ubiquitous services. Faults are the root causes of network outages. The comparison diagnosis model, which automates fault's identification, is one of the leading approaches to attain network dependability. Most of the existing research has focused on stationary networks. Nonetheless, the time-free comparison model imposes no time constraints on the system under considerations, and it suits most of the diagnosis requirements of dynamic networks. This paper presents a novel protocol that diagnoses faulty nodes in diagnosable dynamic networks. The proposed protocol comprises two stages, a testing stage, which uses the time-free comparison model to diagnose faulty neighbour nodes, and a disseminating stage, which leverages a Random Linear Network Coding (RLNC) technique to disseminate the partial view of nodes. We analysed and evaluated the performance of the proposed protocol under various scenarios, considering two metrics: communication overhead and diagnosis time. The simulation results revealed that the proposed protocol diagnoses different types of faults in dynamic networks. Compared with most related protocols, our proposed protocol has very low communication overhead and diagnosis time. These results demonstrated that the proposed protocol is energy-efficient, scalable, and robust.

• Journal of Communications and Networks
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• v.10 no.3
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• pp.268-286
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• 2008

In this work, we review the routing models that use game theoretical methodologies. A very common assumption in the analysis and development of networking algorithms is the full cooperation of the participating nodes. Most of the analytical tools are based on this assumption. However, the reality may differ considerably. The existence of multiple domains belonging to different authorities or even the selfishness of the nodes themselves could result in a performance that significantly deviates from the expected one. Even though it is known to be extensively used in the fields of economics and biology, game theory has attracted the interest of researchers in the field of communication networking as well. Nowadays, game theory is used for the analysis and modeling of protocols in several layers, routing included. This review aims at providing an elucidation of the terminology and principles behind game theory and the most popular and recent routing models. The examined networks are both the traditional networks where latency is of paramount importance and the emerging ad hoc and sensor networks, where energy is the main concern.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.494-494
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• 2000

This paper demonstrates that the largest Lyapunov exponent $\lambda$ of recurrent neural networks can be controlled by a gradient method. The method minimizes a square error $e_{\lambda}=(\lambda-\lambda^{obj})^2$ where $\lambda^{obj}$ is desired exponent. The $\lambda$ can be given as a function of the network parameters P such as connection weights and thresholds of neurons' activation. Then changes of parameters to minimize the error are given by calculating their gradients $\partial\lambda/\partialP$. In a previous paper, we derived a control method of $\lambda$via a direct calculation of $\partial\lambda/\partialP$ with a gradient collection through time. This method however is computationally expensive for large-scale recurrent networks and the control is unstable for recurrent networks with chaotic dynamics. Our new method proposed in this paper is based on a stochastic relation between the complexity $\lambda$ and parameters P of the networks configuration under a restriction. Then the new method allows us to approximate the gradient collection in a fashion without time evolution. This approximation requires only $O(N^2)$ run time while our previous method needs $O(N^{5}T)$ run time for networks with N neurons and T evolution. Simulation results show that the new method can realize a "stable" control for larege-scale networks with chaotic dynamics.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.67-76
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• 2024

The Internet of Things (IoT) has revolutionized communication and device operation, but it has also brought significant security challenges. IoT networks are structured into four levels: devices, networks, applications, and services, each with specific security considerations. Personal Area Networks (PANs), Local Area Networks (LANs), and Wide Area Networks (WANs) are the three types of IoT networks, each with unique security requirements. Communication protocols such as Wi-Fi and Bluetooth, commonly used in IoT networks, are susceptible to vulnerabilities and require additional security measures. Apart from physical security, authentication, encryption, software vulnerabilities, DoS attacks, data privacy, and supply chain security pose significant challenges. Ensuring the security of IoT devices and the data they exchange is crucial. This paper utilizes the Random Forest Algorithm from machine learning to detect anomalous data in IoT devices. The dataset consists of environmental data (temperature and humidity) collected from IoT sensors in Oman. The Random Forest Algorithm is implemented and trained using Python, and the accuracy and results of the model are discussed, demonstrating the effectiveness of Random Forest for detecting IoT device data anomalies.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1069-1074
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• 2021

Recently, mobile communication technology has new eras with supply of 5G commercial communication. 5G mobile communication service is currently supplied with city area, services will be quickly expanded to entire area of country. This mmWave based 5G mobile communication is under spreading for human communication with voice and Internet service. After completion of construction of this human communication, this technology will be expanded to industrial communications. Railway communication system is an example of this industrial communications. In this, performance of traffic transmission for railway communication network based on this 5G railway communication networks will be analyzed with computer simulations. Construction requirements of 5G railway communication networks will be suggested with this analysis results.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.178-188
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• 2024

In the near future, it is expected that there will be billions of connected devices using fifth generation (5G) network services. The recently available base stations (BSs) need to mitigate their loads without changing and at the least monetary cost. The available spectrum resources are limited and need to be exploited in an efficient way to meet the ever-increasing demand for services. Device to Device communication (D2D) technology will likely help satisfy the rapidly increasing capacity and also effectively offload traffic from the BS by distributing the transmission between D2D users from one side and the cellular users and the BS from the other side. In this paper, we propose to apply D2D overlay communication with cognitive radio capability in 5G networks to exploit unused spectrum resources taking into account the dynamic spectrum access. The performance metrics; throughput and delay are formulated and analyzed for CSMA-based medium access control (MAC) protocol that utilizes a common control channel for device users to negotiate the data channel and address the contention between those users. Device users can exploit the cognitive radio to access the data channels concurrently in the common interference area. Estimating the achievable throughput and delay in D2D communication in 5G networks is not exploited in previous studies using cognitive radio with CSMA-based MAC protocol to address the contention. From performance analysis, applying cognitive radio capability in D2D communication and allocating a common control channel for device users effectively improve the total aggregated network throughput by more than 60% compared to the individual D2D throughput without adding harmful interference to cellular network users. This approach can also reduce the delay.