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Drones are capable of exploring large areas due to their swift mobility and utilization efficiency, so their use in various fields such as surveillance is increasing. When a drone performs its mission, the estimation of drone's location relies on GPS signals. Therefore, it becomes difficult to accurately estimate the drone's location in environments where GPS signals are unstable or in denied areas, which directly affects the safety and mission performance of the drone. Drone missions by autonomous flight are often carried out along a given route. This can be done by extracting and comparing the feature points of the image data from the camera mounted on the drone and the image data on the already constructed map using the SIFT algorithm. It allows the drone’s location to be estimated under GPS-denied environments. In this paper, we aim to construct aerial map data and verify the technology for estimating and correcting the drone’s location through image data received from the drone. [ABSTRACT FROM AUTHOR]

This paper deals with the problem in which weighted jobs with equal processing time and deadline, arriving over times, are scheduled on a single machine. Here, the sum of weights of jobs completed after their deadlines is minimized. For this problem, the offline algorithm, knowing previously about all information of jobs, is studied. We will transform this problem to an equivalent problem in which all the jobs arrive at time 0 and have distinct deadlines. Dynamic programming as one of the algorithmic techniques is applied to the transformed problem. We propose an algorithm that computes the values in O(n²) time, setting up the recursive formula to get the values of the DP array. It shows that the time complexity is improved for the special case, while an O(n²)-time algorithm is proposed for the general problem in which the jobs may have distinct deadlines in the previous work [6]. [ABSTRACT FROM AUTHOR]

This paper proposes a method of estimating the position of a moving object equipped with a built-in camera by utilizing two-dimensional codes on the wall to support its mobility. A key idea of the proposed method is to acquire homography by matching a two-dimensional code image with image features obtained by the SIFT algorithm. Accordingly, estimating the position and direction of the moving object can be performed by analyzing the homography matrix. The proposed method has an advantage that it can perform position estimation from a greater distance than those of conventional methods and enables multiple devices to simultaneously utilize the same code. Since the proposed method also reduces the requirement of sensors for position estimation, it can be an effective method with lower cost. [ABSTRACT FROM AUTHOR]

Computation offloading services in Fog/Edge Computing (FEC) environments are an interesting technique for solving resource constraints on mobile devices through low latency and proximity capabilities, requiring a cost model for their commercialization. In this paper, we constructs a three-stage cooperative system prototype between mobile devices and fog/edge layers and cloud data centers, and proposes matching algorithm based on communication, offloading mechanism, and cost between them. The matching algorithm for offloading uses the basic configuration information required by the MD based on the preference rating of MD and resource specifications of ES, and it is implemented to suit the characteristics of the application service through correction of the matching context. In addition, this paper demonstrates the validity and justification of cost-based offloading services through 1:N and N:M matching experiments of MD and ES, providing great potential for application service processing in mobile devices. [ABSTRACT FROM AUTHOR]

Computation offloading technology in an FEC (Fog/Edge Computing) environment requires the process of transmitting code/data and execution results from a mobile device (MD) to an edge server (ES). In this case, a mobile agent may be used for efficient transmission of code/data. However, the mobile agent migrates with task processing commands and execution results at the time of migration, which can cause time delays and reliability degradation problems due to increased size. This paper proposes a method of securing the applicability and reliability of the mobile agent system by implementing migration algorithm and a method of reducing the weight of the mobile agent for computation offloading. In addition, we demonstrate the legitimacy of the proposed method based on the results of the migration and mounting module execution experiment of the mobile agent equipped with code/data in the FEC environment and the comparative analysis experiment of the migration time according to the size of the mobile agent. [ABSTRACT FROM AUTHOR]

This paper describes an efficient design of a point scalar multiplier for public-key cryptosystems based on binary Edwards curves (BEdC). For efficient hardware implementation of point addition and point doubling operations on BEdC, a mixed coordinates system is applied to finite field arithmetic, which improves the computational performance of point scalar multiplication. The modified Montgomery ladder algorithm and the differential point addition and doubling (dPAD) operations were adopted to make it resistant to side-channel attacks, and the optimization of finite field operation rearrangements for dPAD calculations resulted in a reduction in computation of about 50%. A BEdC point scalar multiplier core (BEdC_PSM) was designed to support five different field sizes (223, 257, 431, 479 and 521 bits) using a 48-bit digit-to-serial binary multiplier. The BEdC_PSM core was verified for hardware operation with FPGA implementation and was evaluated to operate at clock frequency up to 205 MHz, and it takes approximately 80 for a 223-bit point scalar multiplication [ABSTRACT FROM AUTHOR]

This paper proposes a CanSat system with a vehicle tracking function based on Jetson Nano, a high-performance small computer capable of operating artificial intelligence algorithms. The CanSat system consists of a CanSat and a ground station. The CanSat falls in the atmosphere and transmits the data obtained through the installed sensors to the ground station using wireless communication. The existing CanSat has the limitation of being simple data collectors, literally carrying out the mission of transmitting the collected data to the ground station as it is. The Jetson Nano-based CanSat proposed in this paper uses a pre-trained neural network model to detect the location of a vehicle in each image taken from the air in real time, and then uses a 2-axis motor to move the camera to track the vehicle. The performance of the proposed CanSat system is evaluated by measuring the accuracy and speed of vehicle tracking using self-produced image dataset. [ABSTRACT FROM AUTHOR]

The DTW algorithm is a method for similarity measurement between two time series and is used to find the optimal alignment between two time series through nonlinear warping. However, the DTW algorithm has a time complexity of O(mn), so its use in large-scale time series data is limited. This paper proposes an algorithm that reduces the number of operations by parallelizing the calculation of the DTW matrix to improve the time complexity of the DTW algorithm. Since the DTW matrix calculation cannot be parallel operation due to dependence between adjacent elements, the distance matrix was transformed by applying the Shear-Mapping method to enable parallel operation. To analyze the performance of the proposed method, the execution time of the algorithm was measured using time series data of various lengths, and as a result, it was confirmed that the longer the time series, the better the performance than the existing DTW algorithm. [ABSTRACT FROM AUTHOR]

The MCTS algorithm is frequently used in game AI. The commonly used tree policy is the UCT algorithm. In this paper, we propose the use of MLPT (Multi-Level Priority List) algorithm as a tree policy to ensure performance and optimize it for different game fields. MLPT selects the first available node from the top-level children of the node and adjusts its priority based on the outcome. As a result, when starting bet was 2% of the current amount, the average reward ratio was 101.237%, standard deviation was 0.0815, and winning rate was 51.739%. In games played until bankruptcy, the winning rate was 97.8% with 47.7 wins and 60.2 losses. MLPT provided the most stable profits compared to other tree policies and showed that it was a stable bet with a higher number of wins. The proposed MLPT algorithm outperforms existing methods by providing stable bets. [ABSTRACT FROM AUTHOR]

Recently, the entire industry is developing due to the application of the fourth Industrial Revolution technology. In the field of maritime, research is being conducted for unmanned ship and smart ships by applying new technologies. Although technologies are improving, the prevention effect of marine accidents is insignificant. Many ships are still causing accidents such as collision and stranding, which causes losses of both life and property every year. Such accidents are mainly caused by crew in operation, and support technology is needed to prevent accidents caused by human error. Therefore, this paper deals with a development of intelligent system that support ship safety management. This was designed with an intelligent safety management terminal and two types of safety management services provided through a planned route safety algorithm and a collision risk algorithm. A system was developed based on the design, and its usefulness was verified by testing based on a full mission ship simulator. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel design approach for a wideband non-uniformly spaced linear array (NUSLA) to suppress the effect of interference signals. Notably, a uniform linear array (ULA), which is easy to handle, is widely utilized to generate nulls over a wide band; however, its beamforming performance is limited owing to the ULA structure. Although a NUSLA with nonlinear spacing addresses nonlinear problems that are difficult to handle mathematically, it can exhibit performance improvements surpassing those of ULA structures. However, an additional constraint is required to generate nulls at a specific position, and this has not yet been studied for null generation using wideband NUSLA. In this paper, we propose a novel cost function for designing a wideband NUSLA, which generates a null at the desired position, and we utilize the modified reinforcement learning algorithm (MORELA), which is a heuristic optimization algorithm based on reinforcement learning (RL), to minimize the proposed cost function and analyze the optimized antenna array and weights. Further, we compare the performance of the proposed MORELA based on RL with that of existing heuristic optimization algorithms via computer simulations. [ABSTRACT FROM AUTHOR]

This paper considers a problem to find a set of intervals containing all the points for the given n points and m intervals on a line, This is a special case of the set cover problem, well known as an NP-hard problem. As optimization criteria of the problem, there are minimizing the number of intervals to cover the points, maximizing the number of points each of which is covered by exactly one interval, and so on. In this paper, the intervals have weights and the sum of weights of intervals to cover a point is defined as a membership of the point. We will study the problem to find an interval cover minimizing the maximum of memberships of points. Using the dynamic programming method, we provide an (omn) log n -time algorithm to improve the time complexity o(m²) log given in the previous work. [ABSTRACT FROM AUTHOR]

Clutter is the radar noise signal that is reflected from the elements surrounding the targets. Since clutter degrades the radar system’s range and doppler frequency detection capability, clutter suppression is a critical signal-processing algorithm that can improve the performance of a radar system. This paper proposes a ground-clutter suppression method using denoising encoder-decoder deep learning network with dual encoding channels, residual connections, and skip connections. Radar signal dataset pipeline was generated using MATLAB in order to train the network. In this paper, deep learning-based clutter suppression method that can be applied in various operating conditions, is discussed. [ABSTRACT FROM AUTHOR]

To reduce forgetfulness in continuous learning, in this paper, we propose an improved LwF model based on the knowledge transfer method, and we show its effectiveness by experiment. In LwF, if the domain of the learned data is different or the complexity of the data is different, the previously learned results are inaccurate due to forgetting. In particular, when learning continues from complex data to simple data, the phenomenon tends to get worse. In this paper, to ensure that the previous learning results are sufficiently transferred to the LwF model, we apply the knowledge transfer method to LwF, and propose an algorithm for efficient use. As a result, the forgetting phenomenon was reduced by an average of 8% compared to the existing LwF results, and it was effective even when the learning task became long. In particular, when complex data was first learned, the efficiency was improved more than 30% compared to LwF [ABSTRACT FROM AUTHOR]

This paper presents on-wafer measurement methods for the scattering coefficient, power, and noise figure of a semiconductor circuit in the D band (110∼170 GHz). The calibration algorithms for the S-parameter measurement were compared, and the effect of the total coplanar waveguide (CPW) width of the commercial calibration standards was examined. In the power measurement, the accuracy of the measurement value was improved through precision path loss evaluation. In addition, in the noise figure measurement, the system configuration and calibration method are presented, and the path loss compensation is examined. The detailed configuration and consid- erations for each measurement system are presented, and the measured results of the designed low-noise amplifier (LNA) chip are presented. [ABSTRACT FROM AUTHOR]

Deep web collection means entering a query in a search form and collecting response results. It is estimated that the information possessed by the deep web has about 450 to 550 times more information than the statically constructed surface web. The static method does not show the changed information until the web page is refreshed, but the dynamic web page method updates the necessary information in real time and provides real-time information without reloading the web page, but crawler has difficulty accessing the updated information. Therefore, there is a need for a way to automatically collect information on these deep webs using a crawler. Therefore, this paper proposes a method of utilizing scripts as general links, and for this purpose, an algorithm that can utilize client scripts like regular URLs is proposed and experimented. The proposed algorithm focused on collecting web information by menu navigation and script execution instead of the usual method of entering data into search forms. [ABSTRACT FROM AUTHOR]

The purpose of an interleaved mode is to simultaneously provide two or more modes to the user. For this, the time resources allocated to each mode are reduced, and thus, the performance of each mode is degraded. Therefore, a scheduling method is required that can minimize the performance degradation of each mode by appropriately allocating resources. In the interleaved mode that operates the ground imaging and air-to-air search/track modes, the image update interval is longer than that of the single mode operation, and air-to-air tracking performance can be degraded; therefore, scheduling must be planned considering them. In this paper, to always obtain images above a certain proportion of the current search area while minimizing the degradation of air-to-air tracking performance, a scheduling algorithm that adaptively adjusts the image update interval by utilizing the posture and position change of the radar-mounted aircraft is proposed. [ABSTRACT FROM AUTHOR]

In this paper, we propose an optimization algorithm that maximizes the network lifetime in wireless ad-hoc networks using the broadcast transmission method. The optimization algorithm proposed in this paper applies tabu search algorithm, a metaheuristic method that improves the local search method using the memory structure. The proposed tabu search algorithm proposes efficient encoding and neighborhood search method to the network lifetime maximization problem. By applying the proposed method to design efficient broadcast routing, we maximize the lifetime of the entire network. The proposed tabu search algorithm was evaluated in terms of the energy consumption of all nodes in the broadcast transmission occurring in the network, the time of the first lost node, and the algorithm execution time. From the performance evaluation results under various conditions, it was confirmed that the proposed tabu search algorithm was superior to the previously proposed metaheuristic algorithm. [ABSTRACT FROM AUTHOR]

In this letter, we investigate a beam placement problem to determine the optimal beam center position that maximizes the minimum transmission rate of users within a spot beam for a multicast transmission in low-Earth-orbit satellite communications. We make a system model for satellite beam placement and formulate an optimization problem that maximize the minimum transmission rate of ground nodes (GNs). Then, we propose a gradient ascent algorithm to calculate the optimal beam center position. The simulation results show that the proposed scheme optimally determines the position of the beam center and maximizes the minimum rate of GNs according to various satellite parameters. [ABSTRACT FROM AUTHOR]

Wireless sensor networks use the concept of connected dominating sets that can form virtual backbones for effective routing and broadcasting. In this paper, we propose an optimization algorithm that configures a connected dominating sets in order to balance the load of nodes to increase network lifetime and to perform effective routing. The proposed optimization algorithm in this paper uses the metaheuristic method of tabu search algorithm, and is designed to balance the number of dominatees in each dominator in the constituted linked dominance set. By constructing load-balanced connected dominating sets with the proposed algorithm, it is possible to extend the network lifetime by balancing the load of the dominators. The performance of the proposed tabu search algorithm was evaluated the items related to load balancing on the wireless sensor network, and it was confirmed in the performance evaluation result that the performance was superior to the previously proposed method. [ABSTRACT FROM AUTHOR]

We propose a two-tier cooperative computing system comprised of a mobile device and an edge server for partial offloading of multi-branch structures in Fog/Edge Computing environments in this paper. The proposed system includes an algorithm for splitting up application service processing by using reconstructive linearization techniques for multi-branch structures, as well as an optimal collaboration algorithm based on partial offloading between mobile device and edge server. Furthermore, we formulate computation offloading and CNN layer scheduling as latency minimization problems and simulate the effectiveness of the proposed system. As a result of the experiment, the proposed algorithm is suitable for both DAG and chain topology, adapts well to different network conditions, and provides efficient task processing strategies and processing time when compared to local or edge-only executions. Furthermore, the proposed system can be used to conduct research on the optimization of the model for the optimal execution of application services on mobile devices and the efficient distribution of edge resource workloads. [ABSTRACT FROM AUTHOR]

When designing chip, it considers design specification, timing problem, and clock synchronization on place & route (P&R) process. P&R process is complicated because of considering various factors. Chip uses clock tree synthesis (CTS) to reduce clock path delay. The purpose of this study is to examine shallow-CTS algorithm for checking clock tree synthesizable. Using open source Parser-Verilog, register transfer level (RTL) synthesizable Verilog file is parsed and it uses Pre-CTS and Post-CTS process that is included shallow-CTS. Based on longest clock path in the Pre-CTS and Post-CTS stages, the standard deviation before and after buffer insertion is compared and analyzed for the accuracy of CTS. In this paper, It is expected that the cost and time problem could be reduced by providing a pre-clock tree synthesis verification method at the RTL level without confirming the CTS result using the time-consuming licensed EDA tool. [ABSTRACT FROM AUTHOR]

When detecting targets of interest in satellite synthetic aperture radar (SAR) images, clustering is often required to construct the candidate pixels of an object. In this paper, we propose a new feature using principal component analysis to address the problem of dense targets that cause performance degradation when using the density-based spatial clustering of noise algorithm, which is suitable for the clustering process. Further, simulations are used to analyze the proposed features for different target and clutter clusters extracted from real TerraSAR-X (TSX) images, and the proposed dense target discrimination technique is applied to the TSX images. The simulation results reveal that the proposed feature is effective in distinguishing clusters composed of dense targets, and the target detection performance can be improved by re-separating dense target clusters from actual SAR images. [ABSTRACT FROM AUTHOR]

This paper considers the cooperative control problem for multiple leaders and a single follower with interactions. The leaders are controllable, and the follower has interactions with all leaders and is controlled by the interactions. Then, we study the cooperative control problem that achieves the consensus by controlling the leaders. The leaders and the follower are modeled by the single-integrator and the double-integrator, respectively, and it is assumed that the interactions have the nonlinearities. The leaders can estimate the interaction between the follower and exchange the estimated information with neighbors. Then, this paper proposes the consensus-based cooperative control algorithm using the information exchange of the estimated interactions and the virtual velocity variables to achieve the velocity consensus. We analyze the convergence of the agents to the common state based on the Lasalle’s Invaraince Principle. Finally, we provide the numerical example to validate the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, we propose a distributed routing algorithm for mobile ad hoc networks (MANET) where mobile devices can be utilized as relays for communication between remote source-destination nodes. The objective of the proposed algorithm is to minimize the end-to-end communication delay caused by transmission failure with deep channel fading. In each hop, the node needs to select the next relaying node by considering a tradeoff relationship between the link stability and forward link distance. Based on such feature, we formulate the problem with partially observable Markov decision process (MDP) and apply deep reinforcement learning to derive effective routing strategy for the formulated MDP. Simulation results show that the proposed algorithm outperforms other baseline schemes in terms of the average end-to-end delay. [ABSTRACT FROM AUTHOR]

To maximize performance in a high-performance multi- core processor system. it is essential to enable effective data communication between processing cores. Data communication between processor nodes can be broadly classified into collective and point-to-point communications. Collective communication comprises scattering and gathering. This paper presents a efficient message scattering and gathering based on processing node status. In the proposed algorithms, the transmission order is changed according to the data size of the pre-existing communication, to reduce the waiting time required until the collective communications begin. From the simulation, the performances of the proposed message scattering and gathering algorithms were improved by approximately 71.41% and 69.84%. [ABSTRACT FROM AUTHOR]

Relationship networks such as an interpersonal relationship network or navigation route search can be expressed in graph form. However, as the amount of data increase, there is a problem that it is difficult to search for the desired data when it is displayed on one screen. In this paper, we propose a visualization method for searching for people, searching for the shortest path between people, and using graphs to express an interpersonal relationship network with many nodes. Unlike the search for the shortest path in the routing table, the shortest path in the interpersonal relationship network should be changeable according to the intension or importance of the researcher or user who is analyzing it. To this end, the BFS algorithm was modified to apply the characteristics of the interpersonal relationship network. For the verification of the results, the data in the character relationship information of the Korean Classics DB in the Korean Classics Translation Institute was used. [ABSTRACT FROM AUTHOR]

Recently, many studies have been done on the data augmentation technique as a way to efficiently build datasets. Among them, a representative data augmentation technique is a method of utilizing Generative Adversarial Network (GAN), which generates data similar to real data by competitively learning generators and discriminators. However, when learning GAN, there are cases where a broken pixel image occurs among similar data generated according to the environment and progress, which cannot be used as a dataset and causes an increase in learning time. In this paper, an algorithm was developed to select these damaged images by analyzing the histogram of image data generated during the GAN learning process, and as a result of comparing them with the images generated in the existing GAN, the ratio of the damaged images was reduced by 33.3 times(3,330%). [ABSTRACT FROM AUTHOR]

This paper presents a subband affine projection algorithm with variable step size to improve convergence performance in adaptive filtering applications with long adaptive filters and highly correlated input signals. The proposed algorithm can obtain fast convergence speed and small steady-state error by using different step sizes for each adaptive sub-filter in the subband structure to which polyphase decomposition and noble identity are applied. The step size derived to minimize the mean square error of the adaptive filter at each update time shows better convergence performance than the existing algorithm using a variable step size. In order to confirm the convergence performance of the proposed algorithm, which is superior to the existing algorithm, computer simulations are performed for mean square deviation(MSD) for AR(1) and AR(2) colored input signals considering the system identification model. [ABSTRACT FROM AUTHOR]

In recent years, the use of broadband bandwidth and redundant links for stable transmission in networks has resulted in excessive energy consumption and reduced transmission efficiency. In this paper, we propose an optimization algorithm that reduces the number of transmission links and minimizes transmission energy by removing redundant traffic in networks where traffic redundancy is allowed. The optimization algorithm proposed in this paper uses the meta-heuristic method using Tabu search algorithm. The proposed optimization algorithm minimizes transmission energy by designing a neighborhood generation method that efficiently routes overlapping traffic. The performance evaluation of the proposed optimization algorithm was performed in terms of the number of links used to transmit all traffic generated in the network and the transmission energy consumed. From the performance evaluation results, it was confirmed that the proposed algorithm is superior to other algorithms previously proposed. [ABSTRACT FROM AUTHOR]

This paper proposes an optimized hardware implementation method for existing CIE1931 color gamut control algorithm. Among the post-processing methods of dehazing algorithms, existing algorithm with relatively low computations have the disadvantage of consuming many hardware resources by calculating large bits using Split multiplier in the computation process. The proposed algorithm achieves computational reduction and hardware miniaturization by reducing the predefined two matrix multiplication operations of the existing algorithm to one. And by optimizing the Split multiplier computation, it is implemented more efficient hardware to mount. The hardware was designed in the Verilog HDL language, and the results of logical synthesis using the Xilinx Vivado program were compared to verify real-time processing performance in 4K environments. Furthermore, this paper verifies the performance of the proposed hardware with mounting results on two FPGAs. [ABSTRACT FROM AUTHOR]

In this paper, we propose a design method for a busbar-PCB type EMI filter using the deep deterministic policy gradient (DDPG) algorithm, which is a reinforcement learning method. Owing to the presence of several parasitic elements in the busbar-PCB type EMI filter, the accuracy in the differential mode and common mode insertion loss in the wideband equivalent circuits was first demonstrated replacing the EM-circuit co-simulation. The state and behavior were defined, and learning was performed to satisfy the necessary insertion loss using the DDPG method. Consequently, impedances satisfying the required insertion loss were derived from the open impedance at five positions on the given PCB, and it was confirmed that the CISPR 25 class 4 regulation condition was satisfied in all frequency bands compared to that in the model used in the existing analysis. [ABSTRACT FROM AUTHOR]

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]

In the metaverse environment, avatars perform various roles as alternative representations of individuals. Avatars can be expressed from the perspectives of enhancing immersion and providing flexible security measures within the metaverse space. This study aims to adjust the representation of avatar details based on the avatar's role in the virtual space. By tuning the hyper-parameters(such as Random Seed, Style Embedding Vector, Batch Size, Number and size of layers in the generator network, Number and size of layers in the discriminator network) of the styleGAN algorithm, a system is designed where the level of immersion, privacy preservation, and data exchange on the network can be controlled to automatically adapt the level of detail in the avatar. [ABSTRACT FROM AUTHOR]

Internet access is also increasing as online activities increase due to the influence of Corona 19. However, network attacks are also diversifying by malicious users, and DDoS among the attacks are increasing year by year. These attacks are detected by intrusion detection systems and can be prevented at an early stage. Various data sets are used to verify intrusion detection algorithms, but in this paper, CICIDS2017, the latest traffic, is used. DDoS attack traffic was analyzed using the decision tree. In this paper, we analyzed the traffic by using the decision tree. Through the analysis, a decisive feature was found, and the accuracy of the decisive feature was confirmed by proceeding the decision tree to prove the accuracy of detection. And the contents of false positive and false negative traffic were analyzed. As a result, learning the feature and the two features showed that the accuracy was 98% and 99.8% respectively. [ABSTRACT FROM AUTHOR]

Portable systems with built-in active noise control is required low power operation. Excessive anti noise search operation can lead to rapid battery consumption. A method that can adaptively cancel noise according to the operating conditions of the system is required and the methods of reducing power are becoming very important key feature in today's portable systems. In this paper, we propose the method of active noise control(ANC) using binary search algorithm in noisy systems. The implemented architecture detects a frequency component considered as noise from the input signal and by using the binary search algorithm, the system find out an appropriate amplitude value for anti-noise in a much faster time than the general linear search algorithm. Through the experimental results, it was confirmed that the proposed algorithm performs a successful functional operation. [ABSTRACT FROM AUTHOR]

In this paper, we propose a general cross-chain solution based on the idea of modularity, abstraction, and layering, which decoupling the cross-chain function from the consensus algorithm and specific application logic, and utilize a Merkle proof to ensure the validity and legality of cross-chain operations. Since the underlying implementations of homogeneous and heterogeneous blockchains are different, we treat them separately. For homogeneous blockchains, we suggest a TCP-like cross-chain transport protocol (CCTP). While for heterogeneous blockchains, we present a method to construct the relay chain to realize the cross-chain function. The proposed scheme can enable the correct, effective, reliable, orderly, and timely transmission of cross-chain data. However, the essential difference between the operations within a single blockchain and the interoperability between different blockchains is that the trust domain is different. Cross-chain interoperation itself breaks the completeness of the blockchain，therefore, some efficiency and safety must sacrifice to trade-off. [ABSTRACT FROM AUTHOR]

Rendezvous is a process that assists nodes in a Cognitive Radio Networks (CRNs) to discover each other. In CRNs where a common control channel is unknown and a number of channels are given, it is important how two nodes find each other in a known search region. In this paper, I have proposed and analyzed a channel hopping sequence using Sidel'nikov sequence by which each node visits an available number of channels. I analyze the expected time to-rendezvous (TTR) mathematically. I also verify the Rendezvous performance of proposed sequence in the view of TTR under 2 user environment compared with JS algorithm and GOS algorithm. The Rendezvous performance of proposed sequence is much better than GOS algorithm and similar with JS algorithm. But when M is much smaller than p, the performance of proposed sequence is better than JS algorithm. [ABSTRACT FROM AUTHOR]

The electrocardiogram (ECG) signal is a good indicator for early diagnosis of heart abnormalities. The ECG signal has a different reference normal signal for each person. And it requires lots of data to diagnosis. In this paper, we propose an adaptive OpenCL-based FPGA-GPU hybrid-layer platform to efficiently accelerate ECG signal diagnosis. As a result of diagnosing 19870 number of ECG signals of MIT-BIH arrhythmia database on the platform, the FPGA accelerator takes 1.15s, that the execution time was reduced by 89.94% and the power consumption was reduced by 84.0% compared to the software execution. The GPU accelerator takes 1.87s, that the execution time was reduced by 83.56% and the power consumption was reduced by 62.3% compared to the software execution. Although the proposed FPGA-GPU hybrid platform has a slower diagnostic speed than the FPGA accelerator, it can operate a flexible algorithm according to the situation by using the GPU. [ABSTRACT FROM AUTHOR]

Nonlocal similarity of natural images leads to the fact that a patch matrix whose columns are similar patches of the reference patch has a low rank. Images corrupted by additive white Gaussian noises (AWGN) make their patch matrices to have a higher rank. The noise in the image can be reduced by obtaining low rank approximation of the patch matrices. In this paper, an image denoising algorithm is proposed, which first constructs the patch matrices by combining the similar patches of each reference patch, which is a part of the noisy image. For each patch matrix, the proposed algorithm calculates its low rank approximate, and then recovers the original image by aggregating the low rank estimates. The simulation results using widely accepted test images show that the proposed denoising algorithm outperforms four recent methods. [ABSTRACT FROM AUTHOR]

Recently, with the development of artificial intelligence and IoT technology, the importance of video processing such as object tracking, medical imaging, and object recognition is increasing. In particular, the noise reduction technology used in the preprocessing process demands the ability to effectively remove noise and maintain detailed features as the importance of system images increases. In this paper, we provide a modified weight filter based on pixel matching in an AWGN environment. The proposed algorithm uses a pixel matching method to maintain high-frequency components in which the pixel value of the image changes significantly, detects areas with highly relevant patterns in the peripheral area, and matches pixels required for output calculation. Classify the values. The final output is obtained by calculating the weight according to the similarity and spatial distance between the matching pixels with the center pixel in order to consider the edge component in the filtering process. [ABSTRACT FROM AUTHOR]

Steganography is a science of embedding secret data into innocent data and its goal is to conceal the existence of a carrier data. Many research on Steganography has been proposed by various hiding and detection techniques that are based on different algorithms. On the other hand, very few studies have been conducted to analyze the performance of each Steganography software. This paper describes five different Steganography software, each having its own algorithms, and analyzes the difference of each inherent feature. Image quality metrics of Peak Signal to Noise Ratio (PSNR) and Structural SIMilarity (SSIM) are used to define its performance of each Steganography software. We extracted PSNR and SSIM results of a quantitative amount of embedded output images for those five Steganography software. The results will show the optimal steganography software based on the evaluation metrics and ultimately contribute to forensics. [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]

The pressing process is a compression process in which a product is made by applying force to a heated or unheated material to transform it into the desired shape. Due to the characteristics of press equipment that produces products through continuous compression for a short time, product defects occur continuously, and systems for solving these problems are being developed using various technologies. This paper proposes a real-time defect detection system based on an artificial intelligence algorithm that detects defects. By attaching various sensors to the press device, the relationship between equipment status and defects is defined and collected based on a big data platform. By developing an artificial intelligence algorithm based on the collected data and implementing the developed algorithm using an embedded board, we will show the practicality of the system by applying it to the actual field. [ABSTRACT FROM AUTHOR]

There have been recently an increasing number of people working out at home. However, many of them do not have face-to-face guidance from experts, so they cannot effectively correct their wrong pose. This may lead to strain and injury to those doing home training. To tackle this problem, this paper proposes a video data-based pose classification and correction system for home training. The proposed system classifies poses using the multi-layer perceptron and pose estimation model, and corrects poses based on joint angels estimated. A voting algorithm that considers the results of successive frames is applied to improve the performance of the pose classification model. Multi-layer perceptron model for post classification shows the highest accuracy with 0.9. In addition, it is shown that the proposed voting algorithm improves the accuracy to 0.93. [ABSTRACT FROM AUTHOR]

Recently, with the development of artificial intelligence and IoT technology, automation, and unmanned work are progressing in various fields, and the importance of image processing, which is the basis of AI object recognition, is increasing. In particular, in systems that require detailed data processing, noise removal is used as a preprocessing step, but the existing algorithm does not consider the noise level of the image, so it has the disadvantage of blurring in the filtering process. Therefore, in this paper, we propose a modified Gaussian filter that determines the weight by determining the noise level of the image. The proposed algorithm obtains the noise estimate for the AWGN of the image using quadtree segmentation, determines the Gaussian weight and the pixel weight, and obtains the final output by convolution with the local mask. To evaluate the proposed algorithm, it was simulated compared to the existing method, and superior performance was confirmed compared to the existing method. [ABSTRACT FROM AUTHOR]

Converting boundary images to time-series makes it feasible to perform boundary matching even on a very large image database, which is very important for interactive and fast matching. In recent research, there has been an attempt to perform fast matching considering partial denoising by converting the boundary image into time series. In this paper, to improve performance, we propose an index-building method considering all possible arbitrary denoising parameters for removing arbitrary partial noises. This is a challenging problem since the partial denoising boundary matching must be considered for all possible denoising parameters. We propose an efficient single index-building algorithm by constructing a minimum bounding rectangle(MBR) according to all possible denoising parameters. The results of extensive experiments conducted show that our index-based matching method improves the search performance up to 46.6 ~ 4023.6 times. [ABSTRACT FROM AUTHOR]

This paper proposes a waypoint guidance algorithm for the Autonomous Underwater Vehicle(AUV). The proposed simplified guidance algorithm is presented, which is combined LOS guidance and cross-track guidance for path following. Cross-track error is calculated using the position of the AUV and reference path. LOS guidance and cross-track guidance are appropriately changed according to cross-track error. And the stability of the system has been improved using variable cross-track control gain by cross-track error. Also, in this paper, navigation hardware in-the loop simulation(HILS) is implemented to verify navigation algorithm of AUV that performs combined navigation using inertial navigation device and doppler velocity log(DVL). Finally, we design integrated system HILS (including navigation HILS) for performance verification of guidance algorithm of the autonomous underwater vehicle. By comparing the sea test result with HILS result, the proposed guidance algorithm and HILS configuration were confirmed be correct. [ABSTRACT FROM AUTHOR]