|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Comparison of Gastrojejunal Anastomosis Techniques in Laparoscopic Roux-en-Y Gastric Bypass: Gastrojejunal Stricture Rate and Effect on Subsequent Weight Loss显示文摘 | Sangoh Lee Andrew R. Davies Sameer Bahal Daniel M. Cocker Gianluca Bonanomi Jeremy Thompson Evangelos Efthimiou | 2014 | Obesity Surgery2014，，9： | 1 |
| 2 | Securing elastic applications on mobile devices for cloud computing显示文摘 | Xinwen Zhang Joshua Schiffman Simon Gibbs Anugeetha Kuruithapatham and Sangoh Jeong | 2009 | Proceedings of the 2009 ACM workshop: Cloud computing security2009，，： | 1 |
| 3 | Image Retrieval Using Color Histograms Generated by Gauss Mixture Vector Quantization显示文摘 | Sangoh Jeong Chee Sun Won Robert M Graya | 2004 | Computer Vision and Image Understanding2004，9，13： | 1 |
| 4 | Cluster-Based Stable BSM Dissemination System for Safe Autonomous Platooning显示文摘Recently,the importance of vehicle safety supporting system has been highlighted as autonomous driving and platooning has attracted the researchers.To ensure driving safety,each vehicle must broadcast a basic safety message(BSM)every 100 ms.However,stable BSM exchange is difficult because of the changing environment and limited bandwidth of vehicular wireless communication.The increasing number of vehicles on the road increases the competition to access wireless networks for BSM exchange;this increases the packet collision rate.An increased packet collision rate impairs the transmission and reception of BSM information,which can easily cause a traffic accident.We propose a solution,the vehicular safety support system(V3S),which exchanges BSMs reliably even when many vehicles are on the road.The V3S uses a clustering scheme to decrease network traffic by reducing the amount of data exchanged between a vehicle and the roadside unit(RSU).In addition,the V3S reduces the collision rate of wireless network packets by broadcasting the vehicle’s BSM in an allocated timeslot using the time division multiple access(TDMA)MAC protocol.The V3S also deals with insufficient bandwidth for dedicated short-range communications(DSRC)by changing DSRC channels according to traffic flow.In evaluating the packet error rate for stable BSM packet delivery,the V3S demonstrates an excellent packet error rate of less than 1%,compared to the 802.11p with its packet error rate of 82%. | Jaehwan Lee Suhwan Kwak Seungwoo Park Sangoh Park | 2022 | Computers, Materials & Continua2022，，4： | 1 |
| 5 | An Efficient Memory Management for Mobile Operating Systems Based on Prediction of Relaunch Distance显示文摘Recently,various mobile apps have included more features to improve user convenience.Mobile operating systems load as many apps into memory for faster app launching and execution.The least recently used(LRU)-based termination of cached apps is a widely adopted approach when free space of the main memory is running low.However,the LRUbased cached app termination does not distinguish between frequently or infrequently used apps.The app launch performance degrades if LRU terminates frequently used apps.Recent studies have suggested the potential of using users’app usage patterns to predict the next app launch and address the limitations of the current least recently used(LRU)approach.However,existing methods only focus on predicting the probability of the next launch and do not consider how soon the app will launch again.In this paper,we present a new approach for predicting future app launches by utilizing the relaunch distance.We define the relaunch distance as the interval between two consecutive launches of an app and propose a memory management based on app relaunch prediction(M2ARP).M2ARP utilizes past app usage patterns to predict the relaunch distance.It uses the predicted relaunch distance to determine which apps are least likely to be launched soon and terminate them to improve the efficiency of the main memory. | Jaehwan Lee Sangoh Park | 2023 | Computer Systems Science & Engineering2023，47，10： | 0 |
| 6 | Mobile Memory Management System Based on User’s Application Usage Patterns显示文摘Currently,the number of functions to improve user convenience in smartphone applications is increasing.In addition,more mobile applications are being loaded into mobile operating system memory for faster launches,thus increasing the memory requirements for smartphones.The memory used by applications in mobile operating systems is managed using software;allocated memory is freed up by either considering the usage state of the application or terminating the least recently used(LRU)application.As LRU-based memory management schemes do not consider the application launch frequency in a low memory situation,currently used mobile operating systems can lead to the termination of a frequently executed application,thereby increasing its relaunch time.This study proposes a memory management system that can efficiently utilize the main memory space by analyzing the application usage information.The proposed system reduces the application launch time by leaving the most frequently used or likely to be run applications in the main memory for as long as possible.The performance evaluation conducted utilizing actual smartphone usage records showed that the proposed memory management system increases the number of times the applications resume from the main memory compared with the conventional memory management system,and that the average application execution time is reduced by approximately 17%. | Jaehwan Lee Sangoh Park | 2021 | Computers, Materials & Continua2021，，9： | 0 |
| 7 | Data Utilization-Based Adaptive Data Management Method for Distributed Storage System in WAN Environment显示文摘Recently,research on a distributed storage system that efficiently manages a large amount of data has been actively conducted following data production and demand increase.Physical expansion limits exist for traditional standalone storage systems,such as I/O and file system capacity.However,the existing distributed storage system does not consider where data is consumed and is more focused on data dissemination and optimizing the lookup cost of data location.And this leads to system performance degradation due to low locality occurring in a Wide Area Network(WAN)environment with high network latency.This problem hinders deploying distributed storage systems to multiple data centers over WAN.It lowers the scalability of distributed storage systems to accommodate data storage needs.This paper proposes a method for distributing data in a WAN environment considering network latency and data locality to solve this problem and increase overall system performance.The proposed distributed storage method monitors data utilization and locality to classify data temperature as hot,warm,and cold.With assigned data temperature,the proposed algorithm adaptively selects the appropriate data center and places data accordingly to overcome the excess latency from the WAN environment,leading to overall system performance degradation.This paper also conducts simulations to evaluate the proposed and existing distributed storage methods.The result shows that our proposed method reduced latency by 38%compared to the existing method.Therefore,the proposed method in this paper can be used in large-scale distributed storage systems over a WAN environment to improve latency and performance compared to existing methods,such as consistent hashing. | Sanghyuck Nam Jaehwan Lee Kyoungchan Kim Mingyu Jo Sangoh Park | 2023 | Computer Systems Science & Engineering2023，46，9： | 0 |
| 8 | An Efficient Attention-Based Strategy for Anomaly Detection in Surveillance Video显示文摘In the present technological world,surveillance cameras generate an immense amount of video data from various sources,making its scrutiny tough for computer vision specialists.It is difficult to search for anomalous events manually in thesemassive video records since they happen infrequently and with a low probability in real-world monitoring systems.Therefore,intelligent surveillance is a requirement of the modern day,as it enables the automatic identification of normal and aberrant behavior using artificial intelligence and computer vision technologies.In this article,we introduce an efficient Attention-based deep-learning approach for anomaly detection in surveillance video(ADSV).At the input of the ADSV,a shots boundary detection technique is used to segment prominent frames.Next,The Lightweight ConvolutionNeuralNetwork(LWCNN)model receives the segmented frames to extract spatial and temporal information from the intermediate layer.Following that,spatial and temporal features are learned using Long Short-Term Memory(LSTM)cells and Attention Network from a series of frames for each anomalous activity in a sample.To detect motion and action,the LWCNN received chronologically sorted frames.Finally,the anomaly activity in the video is identified using the proposed trained ADSV model.Extensive experiments are conducted on complex and challenging benchmark datasets.In addition,the experimental results have been compared to state-ofthe-artmethodologies,and a significant improvement is attained,demonstrating the efficiency of our ADSV method. | Sareer Ul Amin Yongjun Kim Irfan Sami Sangoh Park Sanghyun Seo | 2023 | Computer Systems Science & Engineering2023，46，9： | 0 |
| 9 | Task Offloading Based on Vehicular Edge Computing for Autonomous Platooning显示文摘Autonomous platooning technology is regarded as one of the promising technologies for the future and the research is conducted actively.The autonomous platooning task generally requires highly complex computations so it is difficult to process only with the vehicle’s processing units.To solve this problem,there are many studies on task offloading technique which transfers complex tasks to their neighboring vehicles or computation nodes.However,the existing task offloading techniques which mainly use learning-based algorithms are difficult to respond to the real-time changing road environment due to their complexity.They are also challenging to process computation tasks within 100 ms which is the time limit for driving safety.In this paper,we propose a novel offloading scheme that can support autonomous platooning tasks being processed within the limit and ensure driving safety.The proposed scheme can handle computation tasks by considering the communication bandwidth,delay,and amount of computation.We also conduct simulations in the highway environment to evaluate the existing scheme and the proposed scheme.The result shows that our proposed scheme improves the utilization of nearby computing nodes,and the offloading tasks can be processed within the time for driving safety. | Sanghyuck Nam Suhwan Kwak Jaehwan Lee Sangoh Park | 2023 | Computer Systems Science & Engineering2023，46，7： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员