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检索条件"主题词=Detection algorithms"

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Improved modularity for community detection analysis in weighted graph

Improved modularity for community detection analysis in weig...

引用

International Conference of Information and Communication Technology (ICoICT)

作者： Maya Mairisha G. A. Putri Saptawati Sekolah Tinggi Elektro dan Informatika Institut Teknologi Bandung Bandung Indonesia Sekolah Tinggi Elektro dan Informatika Institut Teknologi Bandung Bandung Jawa Barat ID

ISBN: (纸本)9781467398800

Social networks become very popular in recent years seen from the popularity of online social networks. Relationship on social network consists of connection between users that can be modeled by a graph with nodes and edges. This relation graph can form a community that is a group of nodes within which connection is dense, but between them the connection is sparse. According to this property of communities, previous research has been conducted that proposes MC modularity for measuring how good a particular division into communities based on the concept of coupling coefficient. This research adopts that modularity by adding the network weight as a variable in the formula. The community detection system in this research used Girvan-Newman algorithm with computational of MC modularity. In order to make the value of modularity still in the range of 0-1, then does the mapping function in the calculation of the MC modularity. The experimental results in the form of communities that generated through MC modularity calculation by adding weight variable into calculation has compared with communities that generated under different modularity. The mapping function in computational MC modularity on a weighted graph can generate communities that meet the property of communities. Based on the test results, this modularity can be used for detecting community with average accuracy 99.275%.

关键词： Social network services Couplings Density measurement Silicon Image edge detection Flowcharts detection algorithms

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A more efficient message-optimal algorithm for distributed termination detection

A more efficient message-optimal algorithm for distributed t...

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International Symposium on Parallel Processing

作者： T.-H. Lai Y.-C. Tseng X. Dong Department of Computer and Information Science Ohio State Uinversity Columbus OH USA

Termination detection is a fundamental problem in distributed computing. Many algorithms have been proposed, but only the S. Chandrasekaran and S. Venkatesan (CV) algorithm (1990) is known to be optimal in worst-case message complexity. This optimal algorithm, however, has several undesirable properties. First, it always requires M'+2* mod E mod +n-1 control messages, whether it is worst case or best case, where M' is the number of basic messages issued by the underlying computation after the algorithm starts, mod E mod is the number of channels in the system, and n is the number of processes. Second, its worst-case detection delay is O(M'). In a message-intensive computation, that might not be tolerable. Third, the maximum amount of space needed by each process is O(M'), a quantity not known at compile time, making it necessary to use the more expensive dynamic memory allocation. Last, it works only for FIFO channels. This paper remedies these drawbacks, while keeping its strength. The authors propose an algorithm that requires M'+2(n-1) control messages in the worst case, but much fewer on the average, and in the best case, it uses only 2(n-1) control messages, no matter how large M' is.< >

关键词： IEL Delay Control systems detection algorithms Information science Switches Heuristic algorithms

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Ice detection and under-ice flow monitoring using a SonTek Argonaut-SW

Ice detection and under-ice flow monitoring using a SonTek A...

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Working Conference on Current Measurement (CMTC)

作者： C. Huhta Y. Choquette SonTek/YSI Inc. San Diego CA USA Expertise Chimie et matériaux Hydro-Québec (IREQ) Varennes QUE Canada

The Argonaut-SW is an acoustic Doppler current meter designed for water level, velocity and flow monitoring in rivers and channels. When working in ice affected rivers, some means of determining if ice is present is required to provide accurate flow data. Using data collected with an Argonaut-SW in the Chateauguay River in Quebec, Canada in 2004, algorithms were developed that allow the Argonaut-SW to detect the presence or absence of ice on a river in real-time. These algorithms were developed using data collected during winter and ice break up in the spring of 2004. The new algorithms have been tested at a number of sites during the freeze up and winter of 2004-2005. The ice detection algorithms provide a reliable and highly efficient means of detecting ice formation on the river. The Argonaut-SW also provides reliable stage, velocity and flow data while operating under ice. Combined with the ice detection data, this allows for substantial improvement in flow monitoring on ice affected rivers. Data from a number of Argonaut-SW installations involving flow under ice conditions will be presented, both with respect to the ice detection algorithms and the overall flow monitoring capabilities.

关键词： Monitoring Ice Rivers Acoustic beams Acoustic measurements Springs detection algorithms Velocity measurement Acoustic signal detection Fluid flow measurement

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The Design of Collision detection Algorithm in 2D Grapple Games

The Design of Collision Detection Algorithm in 2D Grapple Ga...

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International Conference on Information Engineering and Computer Science (ICIECS)

作者： Yunlan Tan Changxin Liu Youru Yu College of Information Science and Communication Jinggangshan University Jian Jiangxi China China Department of P.E. China

ISBN: (纸本)9781424449934

It is necessary and important to make the collision detection among the objects or between the object and the scene. If we don't detect collisions, objects will intersect each other or object will intersect the scene. In this paper, we present three algorithms in 2D environment. The objects for collision detection are bounded by the axis-aligned rectangles or circles. The known information such as world coordinate system, collision object coordinate system and collision detection area coordinate system etc. are stored in the data files in advance. The data control systems load those information into the collision detection module to handle the collision among the roles and bullets, We set coordinate values of rectangular center and four vertexes and use the distance from a point to a line to see whether the object's vertexes are enclosed in the other object, if it is true, there is a collision occurring. Alg1. is suitable for the situation where the roles get translational movements, Alg2. is suitable for the situation where the role collide the wall, while Alg3. is suitable for the situation where the roles get rotating or flipping movements, which provides the transition for photography coordinates in 3D environment. The three proposed algorithms have less consuming time.

关键词： Algorithm design and analysis detection algorithms Object detection Layout Control systems Educational institutions Information science Photography Motion control Motion detection

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An Improved Model for People detection Based on YOLOv8

An Improved Model for People Detection Based on YOLOv8

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Information Technology and Digital Applications (ICITDA), IEEE International Conference on

作者： Yang Yuhong Song Zhuo Thelma D. Palaoag Li Shuning CITCS University of the Cordilleras Baguio City Philippines Software College Shanxi Agricultural University Taiyuan China

ISBN: (数字)9798331510732

ISBN: (纸本)9798331510749

People detection is vital for security in large-scale disaster outdoor rescue and large public spaces. Despite its success in various applications, people detection technology continues to face challenges such as low accuracy, difficulty in feature extraction, and slow model performance. This paper proposes an enhanced people detection algorithm based on You Only Look Once version 8 (YOLOv8). The algorithm introduces the Cross Stage Partial Networks with Focused Expansion and Feature Fusion Compressed Information Bottleneck (C2fCIB) module to optimize the backbone network, enhance feature extraction capabilities, and improve the detection accuracy of small and occluded targets, thereby increasing the model's overall detection accuracy. Additionally, a combined loss function incorporating Skew Intersection over Union (SIOU) and Complete Intersection over Union (CIOU) is employed to optimize the detection rate for small and occluded targets, further enhancing accuracy and expediting convergence. Experimental results demonstrate that the average detection accuracy of the improved model increased by 15.4%, and the training speed improved by 15.5%. Consequently, the enhanced model is more effective for people detection, contributing to safety in public spaces and other application scenarios. Furthermore, the model's enhancement methods offer valuable insights for researchers and experts in the field of people detection.

关键词： YOLO Training Accuracy Disasters Feature extraction Security Information technology detection algorithms Faces Convergence

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Local Outlier Factor Based False Data detection in Power Systems

Local Outlier Factor Based False Data Detection in Power Sys...

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Sustainable Power and Energy Conference (iSPEC)

作者： Yifan Ou Bin Deng Xuan Liu Ke Zhou The College of Electrical and Information Engineering Hunan University Changsha China State Grid Guangxi Electric Power Company Limited Research Institute Guangxi China

ISBN: (纸本)9781728149318

The rapid developments of smart grids provide multiple benefits to the delivery of electric power, but at the same time makes the power grids under the threat of cyber attackers. The transmitted data could be deliberately modified without triggering the alarm of bad data detection procedure. In order to ensure the stable operation of the power systems, it is extremely significant to develop effective abnormal detection algorithms against injected false data. In this paper, we introduce the density-based LOF algorithm to detect the false data and dummy data. The simulation results show that the traditional density-clustering based LOF algorithm can effectively identify FDA, but the detection performance on DDA is not satisfactory. Therefore, we propose the improved LOF algorithm to detect DDA by setting reasonable density threshold.

关键词： local outlier factor anomaly detection false data attack dummy data attack density clustering power systems power systems data detection anomaly detection digital differential analyzers bis(p-chlorophenyl)acetic acid lines of force Power grids False Smart grids detection algorithms stability operations

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A feature-based filled pause detection system for Dutch

A feature-based filled pause detection system for Dutch

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IEEE Workshop on Automatic Speech Recognition and Understanding

作者： F. Stouten J.P. Martens ELIS Ghent University Ghent Belgium

Nowadays, automatic speech recognizers have become quite good in recognizing well prepared fluent speech (e.g. news readings). However, the recognition of unprepared or spontaneous speech is still problematic. Some important reasons for this are that spontaneous speech is less articulated, exhibits a high speaking rate and usually contains a lot of disfluencies. The latter occur when the speaker needs time to think about the continuation of his discourse, or when he needs to change/correct his last utterance. Although there are different types of disfluencies (interruptions, corrections, repetitions, etc.) the most common ones are filled pauses. They can take the form of an interjection like /uh/ or /uhm/, or an abnormal lengthening of one syllable of a word. In this paper we propose a new method for detecting such fillers prior to the speech recognition. Tests show that it is possible to improve the recognition accuracy by just removing the detected filled pauses from the recognizer input.

关键词： Computer vision Automatic speech recognition Search engines Detectors Databases Speech recognition Testing Indexing detection algorithms

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Computational efficiency of list sphere detection

Computational efficiency of list sphere detection

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Australian Communications Theory Workshop (AusCTW)

作者： M. Hedley H. Suzuki G. Daniels CSIRO ICT Centre Epping NSW Australia

In this paper the performance of a promising MIMO detection algorithm, list sphere detection, is evaluated for a range of list lengths and for four variations to the basic algorithm. The evaluation uses a MIMO-OFDM-BICM system simulation to show bit error performance versus the computational effort, and the results are compared to maximum likelihood detection. The results provide guidance on the selection of an appropriate list length and algorithm. In applications where a short list length must be used due to memory or computation constraints the results show the loss in performance that can be expected

关键词： Computational efficiency MIMO Computational modeling Australia detection algorithms Forward error correction Decoding Mathematics Gaussian noise Memory management

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detection of low, small, and slow targets in the air based on improved YOLOv5

Detection of low, small, and slow targets in the air based o...

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algorithms, High Performance Computing and Artificial Intelligence (AHPCAI), International Conference on

作者： Jinheng Li Bifeng Cui Yanxu Zhu Zhibin Liu Beijing University of Technology Beijing China

At present, the drone industry is very mature and has been widely used in many fields. While it brings us convenience, it also brings many hidden dangers. Since the target of the UAV is relatively small, the target detection effect of simply using YOLOv5 is poor. Based on this situation, a low-altitude UAV detection algorithm based on improved YOLOv5 is proposed. Targeted improvements have been made to YOLOv5's Backbone, Neck, and Loss. Experiments show that the new method achieves an accuracy of 0.918 and a mAP@.5:.95 of 0.529, which is significantly improved compared with the original.

关键词： Industries High performance computing Object detection Feature extraction Neck detection algorithms Artificial intelligence

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Improved Image Enhancement Method for License Plate detection

Improved Image Enhancement Method for License Plate Detectio...

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International Conference on Digital Signal Processing (DSP)

作者： Vahid Abolghasemi Alireza Ahmadyfard Shahrood University of Technology Shahrood Iran

A novel approach based on vertical edge extraction is proposed for car plate detection. In order to manage the detection in low quality images (low contrast, blurred images etc), we first enhance image contrast at candidate regions for car plate. The vertical edges of the enhanced image are then extracted. Using morphological filtering, several candidates are constituted as license plate. Some distinctive features for car plate such as shape, aspect ratio is used to filter out false candidates. Using the correlation between the candidate regions and the model of car plate, the most probable region in the image is declared as the car plate. The experimental results on out-door images confirms the robustness of the proposed method against the severe imaging condition.

关键词： Image enhancement Licenses Image edge detection Lighting detection algorithms Quality management Filtering Shape Filters Robustness

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