Earticle

The large amplitude variations of OFDM signals generate in-band distortion and out-of-band radiation. In recent years, cubic metric (CM) has been verified as a more accurate metric to measure the amplitude variations. In this paper, the PTS technique is used to decrease the CM of OFDM signals. To overcome the search complexity of an exhaustive search based PTS technique, we introduce an improved backtracking search (IBS) optimization algorithm. Simulations are conducted to show the advantages of the proposed IBS based PTS approach compared with the conventional OFDM, and several state-of-the-art methods in terms of search complexity and CM reduction performance.

In cloud computing systems the continuous increasing need for a variety of applications has made workload distribution and resource allocation more difficult. These difficulties lead to a high degree of imbalance and poor system performance. To address these issues, this study presented a high scalable Improved Multi-Objective Hybrid Load Balancing (IMH_LB) Algorithm. It combines the Grey Wolf Optimization (GWO) algorithm with the velocity driven approach of Particle Swarm Optimization (PSO) technique. The suggested method has been developed to optimize cloud computing environments by improving resource utilization with high scalability. The quality-of-service (QoS) parameters are comparatively analyzed in CloudSim by benchmarking the proposed algorithm against standard (GWO and PSO) algorithms and state of the art (Hybrid GWO-PSO and Improved Hybrid Genetic Algorithm-GWO) algorithms. The experimental findings show the superiority of the proposed approach with average improvements of 72.16% in average response time, 67.27% in makespan, 5.18 times in throughput, in 7.51 times in average resource utilization and 78.51% in degree of imbalance over the standard (GWO and PSO) and state of the art (HGWO-PSO and IHGA-GWO) methods. The proposed algorithm achieves high scalability while stabilizing at an average utilization of 89 % at significantly high workloads.

라벨 패킹 문제는 고정된 개수의 라벨이 배치된 하나 혹은 그 이상의 템플릿을 반복 인쇄함으로써 라벨들을 생산할 때 초과 생산량이 최소가 되도록 템플릿을 구성하는 최적화 문제이다. 선행연구에서 이 문제가 NP-hard임이 밝혀 졌으며, 탐욕적 기법에 기반한 의사 다항시간의 근사알고리즘이 제안되었다[6]. 본 논문에서는 이 문제를 해결하기 위한 또 다른 근사 알고리즘을 제시한다. 먼저 3~4개 정도의 소수의 템플릿을 사용하는 경우에 대해서 최적 해를 찾는 분기한정법 탐색 알고리즘을 제시하고, 템플릿의 개수가 많을 경우 문제를 작은 규모의 부분 문제들로 분할하 여 해결하는 휴리스틱을 제시한다. 다양한 실험 데이터를 통해 제시한 알고리즘의 성능을 평가하였으며 선행 연구에 서 제시된 알고리즘과 비교하였다.

The label packing problem is to compose one or more templates each of which consists of a fixed number of labels of different types and print them multiple times to produce the required amount of labels. The goal is to minimize the over-produced quantities. In our earlier work [6], we proved that this problem is NP-hard and proposed an approximation algorithm based on greedy approach. In this paper, we present an improved approximation algorithm. We first give an optimal algorithm based on branch-and-bound search technique that is applicable when the number of template is a small constant. For the general cases where the number of templates is large, we partition the problem into small subproblems, solve each subproblem using the optimal algorithm, and then merge the results. We tested the algorithm for a variety of sample data and analyse its performance.

Based on local and global constrains, an improved DTW algorithm was proposed in this paper. Firstly, the collected voice data was trained, so the reference template and the test template are constructed by computing the MFCC feature parameters for the training data and the test data, and furthermore, the DTW algorithm was designed according to the local and global constrains. Finally, the proposed DTW algorithm was used to the pattern matching for the reference and test templates. The experimental results show that the proposed algorithm has the remarkable effect in reducing the recognition time and enhancing the recognition accuracy.

本文基于局部约束条件和全局约束条件，提出了一种改进的DTW算法。首先，对采集到的语音数据进行训练，构造由MFCC特征参数构成的参考模板，同时计算测试数据的MFCC特征参数构成测试模板；其次，根据局部约束条件和全局约束条件形成本文的DTW算法；最后，利用改进的DTW算法对测试模板和参考模板进行模式匹配。实验表明，该方法可以明显缩短识别时间，而且具有较高的识别率。

Proposed a modified Nelder‐Mead simplex algorithm for training radial basis function neural networks (RBF‐NN). Traditional simplex algorithm consists of order, reflect, expand, contract and shrink operations, and to construct vertices on the subspace near the constraints. In the improved simplex algorithm, considered the new operate method in the feasible fields near the constrained boundary. This modified method is simple, accuracy and higher efficiency. Numerical experiments show that this method is promising for optimization design of temperature compensation networks.

Perceptual encryption (PE) is becoming popular for protecting image data as they are computationally inexpensive and retain certain image properties that are necessary for compression. PE methods not only provide security during transmission of image data but can also enable privacy-preserving computations on them. However, the presence of color information in the cipher image makes the existing PE algorithms vulnerable to jigsaw puzzle attacks. Therefore, this paper presents an extension of block-based PE methods that utilizes different keys for each color component when changing orientation of a block and pixel values in a block. Thus, offers better encryption performance as the color distribution of the original is changed significantly and the keyspace is expanded. The analysis on Tecnick dataset shows that the proposed PE method preserves compression performance of the existing methods while improving their encryption efficiency. In addition, the main advantage of the proposed method is that of being compatible with a widely used JPEG image standard, which makes it suitable for different outsourced multimedia applications such as, privacy-preserving deep learning, cloud-based photo storage, and social networking services.

인터넷이 발전해감에 따라 사이버 세계라고 하는 또 다른 세상이 창출되었다. 그러나 정보보호의 취약성 때문에 인터넷 게임과 인터넷 뱅킹 서비스를 이용하는 사용자들의 안전성이 보장되지 않고 있는 실정이다. 이처럼 불법 침입자들로부터 선의의 이용자를 보호하기 위한 대응책을 채택하고자 본 논문에서는 인터넷 게임과 뱅킹의 개선된 인증과정을 통하여 일반 사용자들도 이러한 정보들에 손쉽게 접근할 수 있게 하여 더욱더 인증보안이 강화된 알고리즘을 설계하고 구현해 보았으며 기존의 인증보안 방식과도 비교하여 설문조사를 해 본 결과를 바탕으로 새로운 인증방법을 적용해 보는데 그 목적이 있다.

The development of Internet has created a new world called the Cyber world. However, because of the weakness in the security service, Internet game and Internet Banking service users still reluctant to use Internet to accomplish high value business transactions. To overcome this situation we must develop various security services so that the Internet game and Banking service users can use any services freely as the development of Internet, the corresponding technologies are available for the general public and this makes the security services more important than ever before. In this paper, we are design and implementation of improved security certificate algorithm that are simulated to solve the Internet game and Banking security problems.

전기를 이용한 신 교통 시스템인 무인궤도차량은 도심교통 완화, 관광지 교통지원, 공항 및 고속철도와 거점지역을 연결하는 목적을 가지고 있다. 무인궤도차량의 무인 운용에 따른 안전성과 신뢰성 보장을 위해 안전장치의 개발을 필요로 하고 있다. UWB 레이더는 낮은 전력소모와 낮은 간섭 및 높은 정밀도의 장점을 가지고 있어 무인궤도차량에 적합한 시스템이다. 본 논문에서는 무인궤도차량의 안전한 운행을 위한 필수 요소인 레이더에 적합하고, 다양한 잡음환경에서 개선된 성능을 보이는 적응형 CFAR 알고리즘을 제안하였다. 제안된 CFAR 알고리즘은 Mean Level 계열의 CFAR 알고리즘에 비하여 균질한 잡음상황과 다중표적상황에서 개선된 성능을 보였으며, 기존의 VI-CFAR 이 가진 다중 표적 상황에서 성능저하를 개선하였다.

Personal Rapid Transit(PRT) is a new unmanned transportation system using electricity. The purpose of the PRT is relieving the congestion of city traffic and connecting between inner city and airport, high-speed railroad. PRT requires to develop devices for the guarantee of safety and reliability. PRT as the mean of rail transportaion must be equipped with control system for front rail sensing. Ultra Wide Band(UWB) radar system is suitable for PRT’s detection because it has the advantage of low power consumption, low interference and high resolution. In this paper, an improved adaptive Constant False Alarm Rate(CFAR) algorithm is proposed and studied in various noise environments. The proposed algorithm improves performance in various noise environments compared to the Mean Level CFAR algorithms and other adaptive CFAR algorithms.

자율주행 시스템을 비롯한 지능형 교통 시스템에서 측위는 매우 중요한 기술 요소이다. 본 연구는 정밀지도와 카메라의 차선 정보를 활용하여 차량 위치 정확도를 향상시키는 알고리즘 을 개발하고 평가하는 것을 목표로 한다. 이를 위해 정밀지도의 노면선 정보와 카메라 인식 차선을 비교하여 횡방향 오차를 보정 후, 확장 칼만 필터(Extend Kalamn Filter)를 이용하여 측 정 노이즈를 제거하는 알고리즘을 설계하였다. 실성능 검증을 위해 시험 차량을 구성하고 검 증하였다. 시험 차량을 이용한 시험 결과, 제안된 방법은 GNSS 단독 측위 대비 평균 2.74m 감소하였으며, 성능이 약 86.1% 개선됨을 확인하였다.

An algorithm was developed to enhance the vehicle localization accuracy using high-definition map lane information and camera-based lane detection. Lateral errors were corrected through lane matching, and measurement noise was reduced using an Extended Kalman Filter. The experimental results with a test vehicle showed that the proposed method reduced the positioning error from approximately 3.17m to 0.38m, corresponding to an 88.09% improvement compared to a standalone global navigation satellite system.

The objective of this paper is to develop the efficient heuristic method for solving the minimum makespan problem of the job shop scheduling. The proposed heuristic method is based on a constraint satisfaction problem technique and a improved randomizing search algorithm. In this paper, ILOG programming libraries are used to embody the job shop model, and a constraint satisfaction problem technique is developed for this model to generate the initial solution. Then, a improved randomizing search algorithm is employed to overcome the increased search time of constrained satisfaction problem technique on the increased problem size and to find a improved solution. Computational experiments on well known MT and LA problem instances show that this approach yields better results than the other procedures.

상관도표(correlogram)를 사용한 멀티채널 커널 퍼지 알고리즘(Multi-channel Kernel Fuzzy Correlogram: MKFC)은 이동 물체를 검출할 때, 픽셀기반 모델링 알고리즘 (pixel-based modeling)의 뚜렷한 이동 물체 검출의 장점과 히스토그램을 사용한 지역기반 모델링 알고리즘(region-based modeling)의 동적 배경(dynamic background) 에 강인한 장점을 동시에 갖는 알고리즘으로 알려져 있다. 그러나 높은 연산량을 보완하기 위해 양자화된 픽셀값을 사용하였기 때문에 조명 변화에 강인한 이동 물체 검출을 위해 사용되는 그래디언트 정보(예: local binary pattern(LBP), histogram of oriented gradient(HOG))를 적용하기 어려웠다. 이러한 문제 해결을 위해 최소한의 그래디언트 정보를 사용하는 알고리즘이 제안되었으나 그래디언트 특징 추출 과정에서 발생하는 잡음이 이동 물체 검출 성능을 저하시킨다. 본 논문에서는 이동 물체 검출을 위한 향상된 그래디언트 기반 MKFC 알고리즘을 제안한다. 먼저 그래디언트 영상 변환 결과에 잡음제거를 위한 중간값 필터를 적용한다. 다음으로 유사성 기반 이동 물체 검출 과정의 결과를 후보영역으로 설정하고, 저주파 통과 필터를 적용한 최종적인 잡음제거 과정을 통해 이동물체를 검출하는 알고리즘이다. 끝으로, 시뮬레이션 결과를 통해 기존 알고리즘과 제안한 알고리즘의 성능을 비교 검증하였다.

For moving objects detection, the multi-channel kernel fuzzy correlogram algorithm(MKFC) has the following two advantages. It detects moving objects not only sharply by a pixel-based modeling algorithm, but also robustly against dynamic background by a region-based modeling algorithm. However, it uses a quantized pixel value to reduce computational complexity. For this reason, it is hard to apply the gradient feature (e.g., local binary pattern(LBP) and histogram of oriented gradient(HOG)) which is robust against the light change environment. To solve this problem, we propose an algorithm that detects the moving objects using gradient vector-based MKFC. However, performance of moving object detection can be degraded by the noise resulting from gradient vector-based image transform. In this paper, we propose an improved moving objects detection algorithm using gradient based MKFC. The algorithm uses a median filter for denoising the image from gradient vector-based image transform and determines the candidate region based on similarity estimate. Finally, the approach detects the moving objects by applying a Gaussian filter to the candidate region. Simulation results in a light changing environment show that the proposed algorithm yields better moving-object detecting performance than the conventional algorithm.

교통사고가 발생하면 사고 차량은 주변 차량에게 안전 메시지를 멀티 홉으로 브로드캐스트 해야 한다. 하지만, 순수한 플러딩 방식을 사용하면 잦은 충돌로 인해 통신 지연이 유발되고 이로 인해 연속 추돌 사고 예방이 어렵다. 본 논문에서는 이러한 문제점을 해결하기 위해 속도에 따른 이웃 노드의 수를 t-분포를 이용하여 추정하고 이를 백오프 알고리즘에 적용한다. 그리고 멀티채널을 이용하여 이웃 노드 개수의 수집 채널과 데이터 채널로 분리하여 통신 지연을 예방하는 MAC 프로토콜을 제안한다. 결과적으로, 기존 기법보다 제안된 프로토콜이 프레임 수신율이 10% 이상 개선되었음을 확인하였다.

When a car accident happened, the accident vehicle should broadcast a safe message to its neighbors in multi-hop. However, the pure flooding is difficult to protect a chain-reaction collision because of the frequent collision and the communication delay. To solve this problem, we proposes a back-off algorithm applied to the estimation of the neighbor node count using the t-distribution. And we proposes a MAC protocol preventing the communication delay by separating the neighbor’s count collection channel and data channel. As a result, we show the frame reception success rate of our protocol improved more 10% than the previous protocol.

Digital image forgery has become a serious problem due to the sophistication and accessibility of image editing software. Copy move forgery is the simplest type of forgery that involves copying portion of an image and paste it on different location within the image. There are many approaches to detect copy paste forgery, but all of them have their own limitations. In this paper visual and invisible feature based forgery detection techniques are compared and contrasted. The analysis shows that pros and cons of these two techniques compensate each other. Therefore, a hybrid of visual based and invisible feature based forgery detection that combine the merits of both techniques is proposed. The experimental results shows that the proposed algorithm has enhanced performance compared to individual techniques. Moreover, it provides more information about the forgery, like identifying copy and duplicate regions.

최근 클라우드 서비스가 주목받으면서 서비스 비용을 줄이기 위한 다양한 연구들이 진행되고 있다. 특히, 이기종 장치를 통해 클라우드 서비스의 상호호환성을 유지할 수 있는 클라우드 관리 방안 기술 연구가 필요하다. 본 논문에서는 클라우드 서비스가 무중단 없이 상호 호환성을 지속할 수 있는 작업 지향 분할 모델을 제안한다. 제안 모델은 클라우드 간 작업 정보 연계가 지속될 수 있도록  개의 작업을 선형 연결하는 것이 목적이다. 제안 모델은 N개의 작업 정보 간 정보 연계성이 높을수록 클라우드 작업 간 관계가 명확하고 작업 정보 간 강한 관계를 유지하기 위해서 작업 정보의 필수 연결을 반복적으로 필터링함으로써 작업의 매개변수 크기를 줄일수 있어서 안 정적인 작업 공유 관계를 작업 전반에 걸쳐 적용할 수 있다. 성능 평가 결과, 상관관계 정보를 이용하여 작업 지향 분할을 반복적으로 필터링함으로써 정확도와 효율성은 각각 평균 4% 향상시켰으며, 클라우드 작업 간 연계 처리의 지연시간은 평균 17% 향상시켰다.

As cloud services have recently attracted attention, various studies are being conducted to reduce service costs. In particular, there is a need for research on technology for cloud management plans that can maintain the interoperability of cloud services through heterogeneous devices. In this paper, we propose a task-oriented segmentation model in which cloud services can continue to be compatible without interruption. The proposed model aims to connect individual tasks linearly so that the linkage of task information between clouds can be continued. The proposed model can apply a stable task sharing relationship throughout the task by repeatedly filtering the essential connection of task information in order to maintain a strong relationship between task information and a clearer relationship between task information. As a result of performance evaluation, by repeatedly filtering the task-oriented segmentation using correlation information, accuracy and efficiency improved by 4% on average, respectively, and the delay time of linkage processing between cloud tasks improved by 17% on average.

스마트폰 게임 사용자들의 급속한 증가와 모바일 사용이 급증함에 따라 개인의 인증서 사용은 필수적으로 사용하도록 하고 있다. 이 개인 인증서는 편리하면서도 개인의 정보유출 및 도용의 우려가 항상 존재하게 되어 사용자들의 불안감은 항상 함께 공존하고 있다. 이에 즈음하여 본 논문에서는 기존의 아이디와 비밀번호를 입력하던 방식을 개선하여 보다 쉬우면서도 타인이 도용하지 못하게 대응하도록 철저한 개인인증 보안 알고리즘을 적용하여 실제 스마트폰 게임 인증 사용시에 적용할 수 있도록 시뮬레이션 해 보고자 하였다. 본 논문의 수행 결과로는 안전한 스마트폰 게임 인증 서비스의 활성화와 더불어 무선 인터넷 뱅킹 서비스, 온라인 쇼핑 등 무선 인터넷을 이용한 전자 상거래의 활성화에 기여할 것으로 기대된다.

Everyday demand of smart phone game is increasing. Security problem is certainly resolved for smart phone game activation. Especially problem is only wiretap in mobile communication with voice, but problems, user authentication, data integrity guarantee etc., are resolved in data-services that have commercial transaction over simple data information service such bill, banking. This paper analyze various smart phone game technology for offering safe smart phone game service and design of improved certificate security algorithm based on SOL(Security Oriented Language). Performance Result of this paper expect activity of safe certificate service and activity of electronic commercial transaction used smart phone game such banking service, bill transaction, online shopping.

Based on an analysis of the advantages and disadvantages of single-layer and multi-layer BOM structure, and combine with specific examples of products, a more practical—cross-type BOM structure method is presented. Aiming to solve the system efficiency problems brought by the BOM operation in manufacturing. Regarding the queue as a temporary table, we put forward an improved multi-layer BOM traversal algorithm, makes full use of the basic operation characteristics and setting marks in related fields queue and simplifies the complexity of the algorithm. Compared with the traditional recursive algorithm and hierarchical algorithm, the improved algorithm has the advantages of fast speed, low resource consumption, and high practicability. And the improved algorithm is verified through an example.

In order to improve the association matching of multiple pedestrians in occlusion scene, an improved algorithm is proposed in this paper that combines the similarity matching of pedestrian object’s major color spectrum histogram combination with joint probabilistic data association. The similarity to major color spectrum histogram of pedestrian’s object is calculated between the previous and the frame that current frames in this algorithm. And take the centroid location of pedestrian’s target which is with the most largest similarity to correct the state vector of the JPDA algorithm in the current frame. The experimental results show that the proposed algorithm could make the number of the targets’ label adhesion reduced to 40%, the number of the targets’ label confusion decreased about 33%, the recall rate of targets is increased by 6.8%, and the tracking accuracy is improved by 9.2% compared with the classical JPDA algorithm when the occlusion rate between pedestrians and intensity are not very high.