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Subspace clustering for online data streams requires a large amount of memory resources as all subsets of data dimensions must be examined. In order to track the continuous change of clusters for a data stream in a finite memory space, in this paper, we propose a grid-based subspace clustering algorithm that effectively uses memory resources. Given an n-dimensional data stream, the distribution information of data items in data space is monitored by a grid-cell list. When the frequency of data items in the grid-cell list of the first level is high and it becomes a unit grid-cell, the grid-cell list of the next level is created as a child node in order to find clusters of all possible subspaces from the grid-cell. In this way, a maximum n-level grid-cell subspace tree is constructed, and a k-dimensional subspace cluster can be found at the k th level of the subspace grid-cell tree. Through experiments, it was confirmed that the proposed method uses computing resources more efficiently by expanding only the dense space while maintaining the same accuracy as the existing method. [ABSTRACT FROM AUTHOR]

Bluetooth is a common wireless technology that is widely used as a connection medium between various consumer electronic devices. The Bluetooth receiver usually adopts a Viterbi algorithm to improve signal-to-noise ratio performance, but requires complex hardware and calculations for continuous search and estimation for the irrational modulation indexes at the transmission. This paper proposes a non-coherent maximum estimation based 8-State Viterbi FSM to solve these complexity problems. The proposed optimal Viterbi FSM can detect Gaussian frequency-shfit keying symbol without any prior information and estimation for the modulation indexes. The HV1/HV2 packets are used for the estimation of the proposed algorithm and the simulation results have shown performance improvements with about 2dB for 10 -3 BER compared to other ideal approaches such as decision direct method. [ABSTRACT FROM AUTHOR]

The adaptation of smartfarm technology that converges ICT is increasing productivity and competitiveness in the agriculture. Technologies have been developed that enable environmental monitoring through various sensors and automatic control of the cultivation environment, and researches are underway to advance smartfarm technology using data generated from smartfarms. In this paper, an environmental control method to reduce the energy consumption of a smartfarm by using the environment and control data of the smartfarm is proposed. It was confirmed that energy consumption could be reduced compared to an independent environmental control method by creating an environmental prediction model using accumulated environmental data and selecting a control method to minimize energy consumption in a given situation by considering multiple environmental factors. In the future, research is needed to obtain higher energy efficiency through the advancement of the predictive model and the improvement of the complex control algorithms. [ABSTRACT FROM AUTHOR]

Given an undirected simple graph, k- club is one of the proposed structures to model social groups that exist in various types in Social Network Analysis (SNA). Maximum k- Club Problem (MkCP) is to find a k- club of maximum cardinality in a graph. This paper introduces a Genetic Algorithm called HGA+DROP which can be used to approximate maximum k- club in graphs. Our algorithm modifies the existing k- CLIQUE & DROP algorithm and utilizes Heuristic Genetic Algorithms (HGA) to obtain multiple k- clubs. We experiment on DIMACS graphs for k = 2, 3, 4 and 5 to compare the performance of the proposed algorithm with existing algorithms. [ABSTRACT FROM AUTHOR]

In this paper, we proposed the straight line determination method and the algorithm for 8 directions determination of straight line using the coordinate information and the property of trigonometric function. We conduct an experiment that is 8 hand gestures are carried out 100 times each, a total of 800 times. And the accuracy for the 8 derection determination algorithm is showed the diagonal direction to the left upper side shows the highest accuracy as 92%, and the direction to the left side, the diagonal direction to the right upper side and the diagonal direction to the right bottom side show the lowest accuracy as 82%. This method with coordinate information through image processing than the existing recognizer and the recognition through learning process is possible using a hand gesture recognition gesture. [ABSTRACT FROM AUTHOR]

Recently, blockchain technology accumulates and stores all transactions. Therefore, in order to verify the contents of all transactions, the data itself is compressed, but the scalability is limited. In addition, since a separate verification algorithm is used for each type of transaction, the verification burden increases as the size of the transaction increases. Existing blockchain cannot participate in the network because it does not become a block sink by using a server with a low specification. Due to this problem, as the time passes, the data size of the blockchain network becomes larger and it becomes impossible to participate in the network except for users with abundant resources. Therefore, in this paper, we are improved transaction as studied the zero knowledge proof algorithm for general operation verification. In this system, the design of zero-knowledge circuit generator capable of general operation verification and optimization of verifier and prover were also conducted. [ABSTRACT FROM AUTHOR]

The underlaying communication scheme in 5G cellular network is a very promising resource sharing scheme, and it is an effective scheme for improving service performance of 5G and reducing communication load between a cellular link and a device to device (D2D) link. This paper proposes the algorithm to minimize the resource interference that occurs when performing 5G-based multi-class service on gNB(gNodeB) and the cooperative priority-based resource allocation scheduling scheme (CPRAS) to maximize 5G communication service according to the analyzed control conditions of interference. The proposed CPRAS optimizes communication resources for each device, and it optimizes resource allocation according to the service request required for 5G communication and the current state of the network. In addition, the proposed scheme provides a function to guarantee giga-class service by minimizing resource interference between a cellular link and a D2D link in gNB. The simulation results show that the proposed scheme is better system performance than the Pure cellular and Force cellular schemes. In particular, the higher the priority and the higher the cooperative relationship between UE(User Equipment), the proposed scheme shows the more effective control of the resource interference. [ABSTRACT FROM AUTHOR]

The energy consumption problem in wireless sensor networks is investigated. The problem is to expend as little energy as possible receiving and transmitting data, because of constrained battery. In this paper, in order to extend the lifetime of the network, we proposed a location-based clustering algorithm for wireless sensor network with skewed-topology. The proposed algorithm is to deploy multiple child nodes at the sink to avoid bottleneck near the sink and to save energy. Proposed algorithm can reduce control traffic overhead by creating a dynamic cluster. We have evaluated the performance of our clustering algorithm through an analysis and a simulation. We compare our algorithm's performance to the best known centralized algorithm, and demonstrate that it achieves a good performance in terms of the life time. [ABSTRACT FROM AUTHOR]

As increasing the growth of the Internet in medical area, a new technology to transmit effectively massive medical data is required. In optical internet, all OBS nodes have fiber delay lines, hardware components. These components are calculated under some optimal traffic conditions, and this means that if the conditions change, then the components should be altered. Therefore, in this article a new service differentiation algorithm using the previously installed components is proposed, which is used although the conditions vary. When traffic conditions change, the algorithm dynamically recalculates the threshold value used to decide the length of data bursts. By doing so, irrelevant to changes, the algorithm can maintain the service differentiation between classes without replacing any fiber delay lines. With the algorithm, loss sensitive medical data can be transferred well. [ABSTRACT FROM AUTHOR]

Research and importance of legal services applied with AI so that it can be easily understood and predictable in difficult legal fields is increasing. In this study, based on the decision of the Tax Tribunal in the field of tax law, a model was built through self-learning through information collection and data processing, and the prediction results were answered to the user's query and the accuracy was verified. The proposed model collects information on tax decisions and extracts useful data through web crawling, and generates word vectors by applying Word2Vec's Fast Text algorithm to the optimized output through NLP. 11,103 cases of information were collected and classified from 2017 to 2019, and verified with 70% accuracy. It can be useful in various legal systems and prior research to be more efficient application. [ABSTRACT FROM AUTHOR]