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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 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]

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 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 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]

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]

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]

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]

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]

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]

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 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]

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]

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]

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]

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]

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]

In this paper, we propose a clustered algorithm that possible more efficient user distinction within clustering using context-aware attribute information. In typically, the data provided to classify interrelationships within cluster information in the process of clustering data will be as a degrade factor if new or newly processing information is treated as contaminated information in comparative information. In this paper, we have developed a clustering algorithm that can extract user's recognition information to solve this problem in using K-means algorithm. The proposed algorithm analyzes the user's clustering attributed parameters from user clusters using accumulated information and clustering according to their attributes. The results of the simulation with the proposed algorithm showed that the user management system was more adaptable in terms of classifying and maintaining multiple users in clusters. [ABSTRACT FROM AUTHOR]

Wireless mesh networks consist of mesh clients, mesh routers and mesh access points. The mesh router connects wireless network services to the mesh client, and the mesh access point connects to the backbone network using a wired link and provides Internet access to the mesh client. In this paper, a limited number of mesh routers and mesh access points are used to propose optimization algorithms for network design for wireless mesh networks. The optimization algorithm in this paper has been applied with a sub-subscription algorithm, which is one of the meta-heuristic methods, and is designed to minimize the transmission delay for the placement of mesh routers and mesh access points, and produce optimal results within a reasonable time. The proposed algorithm was evaluated in terms of transmission delay and time to perform the algorithm for the placement of mesh routers and mesh access points, and the performance evaluation results showed superior performance compared to the previous meta-heuristic methods. [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]

Energy Efficiency in any WSN (Wireless Sensor Network) is a critical issue to elongate the life of the batteries equipped in sensors. LEACH(Low Energy Adaptive Clustering Hierarchy) is one of the mostly used routing algorithms which reduce the amount of transmitted data and save the energy in the network. In this paper, a new technique to select channels in routing algorithms is suggested and compared with the LEACH, ALEACH and PEGASIS. This technique forms clusters depending upon the node density as the deployement of the nodes is random. As a result, the proposed algorithm presents the better performance of the energy efficiency than those of the current algorithms [ABSTRACT FROM AUTHOR]

This paper presents a design of the Meta-Class Repository (MCR) which maintain syntactically analyzed and structured meta-class information from UML diagrams, and then proposes ‘meta-class,’ also known as super-class, to construct structured information analyzed syntactically. The MCR is a collection of these meta-classes which contains the information extracted from diagrams. This paper also presents a design of the Code Generation Engine (CGE) which roles generating codes corresponding classes from UML diagrams based on the MCR maintaining a collection of meta-classes which is syntactically-analyzed and constructed in previous process. The logics of CGE are designed to generate codes collaborated with MCR and CGE with integration. The logics of CGE mechanism is presented with the form of finite state machine to present the algorithms of code generation formally and have the advantages of simplicity and easiness in development. [ABSTRACT FROM AUTHOR]

This paper proposes a detection algorithm for group testing. Group testing is a problem of finding a very small number of defect samples out of a large number of samples, which is similar to the problem of Compressed Sensing. In this paper, we define a noiseless group testing and propose a probabilistic algorithm for detection of defective samples. The proposed algorithm is constructed such that the extrinsic probabilities between the input and output signals exchange with each other so that the posterior probability of the output signal is maximized. Then, defective samples are found in the group testing problem through a simulation on the detection algorithm. The simulation results for this study are compared with the lower bound in the information theory to see how much difference in failure probability over the input and output signal sizes. [ABSTRACT FROM AUTHOR]

In this paper, I propose an algorithm to generate an input digit image for a digit recognition system by detecting a digit string in an image and segmenting the digits constituting the digit string. The proposed algorithm detects blobbed digit string through blob detection, designates a digit string area and corrects digit string skew using the detected blob information. And the proposed algorithm corrects the digit skew and determines the boundary points for the digit segmentation in the corrected digit sequence using three CPgraphs newly defined in this paper. In digit segmentation experiments using the image group including digit strings printed with a range of the font sizes and the image group including handwritten digit strings, the proposed algorithm successfully segments 100% and 90% of the digits in each image group [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]

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]

Object recognition is to identify the location and class of a specific object by analyzing the given image when a specific image is input. One of the fields in which object recognition technology is actively applied in recent years is autonomous vehicles, and this paper describes the trend of image-based object recognition artificial intelligence technology in autonomous vehicles. The image-based object detection algorithm has recently been narrowed down to two methods (a single-step detection method and a two-step detection method), and we will analyze and organize them around this. The advantages and disadvantages of the two detection methods are analyzed and presented, and the YOLO/SSD algorithm belonging to the single-step detection method and the R-CNN/Faster R-CNN algorithm belonging to the two-step detection method are analyzed and described. This will allow the algorithms suitable for each object recognition application required for autonomous driving to be selectively selected and R&D. [ABSTRACT FROM AUTHOR]

The cause of the majority of vehicle accidents is a safety issue due to the driver’s inattention, such as drowsy driving. A forward collision warning system (FCWS) can significantly reduce the number and severity of accidents by detecting the risk of collision with vehicles in front and providing an advanced warning signal to the driver. This paper describes a low power embedded system based FCWS for safety. The algorithm computes time to collision (TTC) through detection, tracking, distance calculation for the vehicle ahead and current vehicle speed information with a single camera. Additionally, in order to operate in real time even in a low-performance embedded system, an optimization technique in the program with high and low levels will be introduced. The system has been tested through the driving video of the vehicle in the embedded system. As a result of using the optimization technique, the execution time was about 170 times faster than that when using the previous non-optimized process. [ABSTRACT FROM AUTHOR]

In modern society, various digital communication equipment is being used due to the influence of the 4th industrial revolution. Accordingly, interest in removing noise generated in a data transmission process is increasing, and research is being conducted to efficiently reconstruct an image. In this paper, we propose a filtering algorithm to remove the AWGN generated in the digital image transmission process. The proposed algorithm classifies pixels with high similarity by selecting regions with similar patterns around the input pixels according to block matching to remove the AWGN that appears strongly in the image. The selected pixel determines the estimated value by applying the weight obtained by the local steering kernel, and obtains the final output by adding or subtracting the input pixel value according to the standard deviation of the center mask. In order to evaluate the proposed algorithm, it was simulated with existing AWGN removal algorithms, and comparative analysis was performed using enlarged images and PSNR. [ABSTRACT FROM AUTHOR]

In this paper, an algorithm for determining the coagulant input rate in the drug-injection tank during the process of the water purification plant was derived through big data analysis and prediction based on artificial intelligence. In addition, analysis of big data technology and AI algorithm application methods and existing academic and technical data were reviewed to analyze and review application cases in similar fields. Through this, the goal was to develop an algorithm for determining the coagulant input rate and to present the optimal input rate through autonomous driving simulator and pilot operation of the coagulant input process. Through this study, the coagulant injection rate, which is an output variable, is determined based on various input variables, and it is developed to simulate the relationship pattern between the input variable and the output variable and apply the learned pattern to the decision-making pattern of water plant operating workers. [ABSTRACT FROM AUTHOR]

As technologies related to image processing such as autonomous driving and CCTV develop, fog removal algorithms using a single image are being studied to improve the problem of image distortion. As a method of predicting fog density, there is a method of estimating the depth of an image by generating a depth map, and various fog features may be used as training data of the depth map. In addition, it is essential to implement a hardware capable of processing high-definition images in real time in order to apply the fog removal algorithm to actual technologies. In this paper, we implement NLCV (Normalize Local Coefficient of Variation), a feature of fog based on coefficient of variation, in hardware. The proposed hardware is an FPGA implementation of Xilinx's xczu7ev-2ffvc1156 as a target device. As a result of synthesis through the Vivado program, it has a maximum operating frequency of 479.616MHz and shows that real-time processing is possible in 4K UHD environment. [ABSTRACT FROM AUTHOR]

In order to be able to interact with the user to experience it as if it were real in virtual reality contents, input/output devices that make them feel the five senses of humans are required . In virtual reality (VR), devices that stimulate sight and hearing are the most representative. For a more realistic experience, suits and gloves that stimulate the sense of touch have recently been released, but there are not many cases applied to actual contents due to the limitation of device . In this paper, we analyze a virtual reality glove that can detect hand movement and touch in a virtual world. Based on the analysis, we propose an algorithm that can sense the intensity of collision with a VR object by tactile sense by improving the UI/UX using the vibration of the feedback method used in the existing virtual reality glove. In addition, the system implemented by the algorithm is applied to an actual case. [ABSTRACT FROM AUTHOR]