Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems最新文献

A malware detection system based on heterogeneous information network 基于异构信息网络的恶意软件检测系统

Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems Pub Date : 2018-10-09 DOI: 10.1145/3264746.3264784

Shang-nan Yin, Ho-Seok Kang, Zhi-Guo Chen, Sung-Ryul Kim

{"title":"A malware detection system based on heterogeneous information network","authors":"Shang-nan Yin, Ho-Seok Kang, Zhi-Guo Chen, Sung-Ryul Kim","doi":"10.1145/3264746.3264784","DOIUrl":"https://doi.org/10.1145/3264746.3264784","url":null,"abstract":"In this era of information networks, more and more malware (malicious software) poses a serious threat to security. How to detect malware attacks in a timely and effective manner becomes particularly important. The increasingly sophisticated malware calls for new defense technologies to detect and combat novelty attack and threats. In this paper, we propose a novel malware detection method that not only depends on API calls, further analyze the relationship between them and creates higher-level semantics to avoid attackers evading detection. We construct a heterogeneous information network (HIN) through their rich relationships between software and related APIs, and then use meta-path-based methods to describe the semantic relevance to software and APIs. We use each meta-path to calculate similarities between software and aggregate different similarities with Multi-kernel Learning (MKL) to construct a malware detection system. We collected real sample data and conducted a comprehensive experiment. Through experiments we have obtained a relatively high detection rate and a relatively low false detection rate, shows the effectiveness of our proposed method.","PeriodicalId":186790,"journal":{"name":"Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117062391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

OSAMIC

Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems Pub Date : 2018-10-09 DOI: 10.1145/3264746.3264755

C. Shih, Chang-Min Yang, Wei-Lun Su, Pei-Kuei Tsung

引用次数: 4

Scheduling algorithms for dynamical real-time tasks on multiprocessor systems 多处理器系统动态实时任务调度算法

Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems Pub Date : 2018-10-09 DOI: 10.1145/3264746.3264758

Chin-Fu Kuo, Yung-Feng Lu

{"title":"Scheduling algorithms for dynamical real-time tasks on multiprocessor systems","authors":"Chin-Fu Kuo, Yung-Feng Lu","doi":"10.1145/3264746.3264758","DOIUrl":"https://doi.org/10.1145/3264746.3264758","url":null,"abstract":"The purpose of this paper is to study the task scheduling problem of dynamical task sets on the system with DVS multiprocessor. A new task can arrive in the system and the system must do the admission test for the task. If the test is satisfied, the task will be accepted and then it can leave after an interval of execution. In this paper, we propose two kinds of admission control algorithms for the situations when the timing information about the departure time of an executing task is known. The Intuitive Admission Control Algorithm (IACA) is proposed to solve the problem of admission control where the departure time of a task is not known until the end of the active interval for its last job. The Positive Admission Control Algorithm (PACA) for the admission control where the departure time of a task is not known until the execution of its last job is finished. Besides, the related properties are presented and proved. A series of experiments were conducted to evaluate the proposed algorithms. From the experimental results, we can observe that the proposed algorithms with the Best Fit heuristic can reject fewer tasks than that with the First Fit and Worst Fit heuristics. Besides, if the departure time of a task can be known early, the information will be helpful to improve the rejected task numbers.","PeriodicalId":186790,"journal":{"name":"Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129552956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A prototype of a self-motion training system based on deep convolutional neural network and multiple FAMirror 基于深度卷积神经网络和多个fammirror的自运动训练系统原型

Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems Pub Date : 2018-10-09 DOI: 10.1145/3264746.3264788

Ki Yeol Baek, In Su Kim, J. Jang, Soon Ki Jung

{"title":"A prototype of a self-motion training system based on deep convolutional neural network and multiple FAMirror","authors":"Ki Yeol Baek, In Su Kim, J. Jang, Soon Ki Jung","doi":"10.1145/3264746.3264788","DOIUrl":"https://doi.org/10.1145/3264746.3264788","url":null,"abstract":"With the development of deep learning methods, there has been a significant development in motion and speech recognition technologies, which have become common methods in Human-Computer Interaction (HCI). In addition, a mirror-metaphor is something that can be easily found around us, and it has become one of the displays for augmented reality as it enables participants to observe themselves. This paper proposes a prototype of self-motion training AR system based on these two important aspects. In the self-motion training system, we propose a method to represent one motion as one image. This method enables faster deep learning and motion recognition. For a self-motion training system, there are two essential requirements. One is that the participants should have the ability to observe their motion as well as a reference motion model, and it should be possible to correct their motion by comparing with the reference model. The other requirement is that the system could recognize a participant's motion from among various motion models in a database. Here, we introduce the configuration of a self-motion training system based on AR and its implementation details. In addition, the system examines the accuracy of the participant's motion with a reference motion model.","PeriodicalId":186790,"journal":{"name":"Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115875845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

The design and development of integrated interface for provision BMC framework 提供BMC框架集成接口的设计与开发

Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems Pub Date : 2018-10-09 DOI: 10.1145/3264746.3264809

J. An, Chanyeong Kim, Younghwan Kim

引用次数: 0

Deep learning based customer product rating prediction model 基于深度学习的客户产品评级预测模型

Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems Pub Date : 2018-10-09 DOI: 10.1145/3264746.3264814

Yongcheon Park, Jeongmin Park, Eunkyong Lee, Kyoungchul Lee, Jiman Hong

引用次数: 1

A SSLBP-based feature extraction framework to detect bones from knee MRI scans 基于sslbp的特征提取框架在膝关节MRI扫描中检测骨骼

Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems Pub Date : 2018-10-09 DOI: 10.1145/3264746.3264778

J. Mun, Youjeong Jang, Seong‐Ho Son, Hyeun Joong Yoon, John Kim

引用次数: 4

On isolation-driven automated module decomposition 关于隔离驱动的自动化模块分解

Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems Pub Date : 2018-10-09 DOI: 10.1145/3264746.3264756

T. Cerný, Filip Sedlisky, M. Donahoo

引用次数: 1

Timestamp-based hot/cold data identification scheme for solid state drives 基于时间戳的固态硬盘热/冷数据识别方案

Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems Pub Date : 2018-10-09 DOI: 10.1145/3264746.3264790

Nguyen-Van Hiep, Jen-Wei Hsieh

{"title":"Timestamp-based hot/cold data identification scheme for solid state drives","authors":"Nguyen-Van Hiep, Jen-Wei Hsieh","doi":"10.1145/3264746.3264790","DOIUrl":"https://doi.org/10.1145/3264746.3264790","url":null,"abstract":"Flash memory is a non-volatile memory that has been widely used as a storage medium for various mobile devices, consumer electronics, and data centers due to its natures of lightweight, high performance, low power consumption, and shock resistance. However, flash memory requires erasing before it can be overwritten. Compared with other operations, the erase operation is the most time-consuming. In addition, flash memory can only endure a limited number of erasures. Out-place-update is adopted to hide the overhead incurred by erase operations. The space occupied by obsolete data are reclaimed during garbage collection. Garbage collection reclaims free space by migrating valid data from the victim block to another free flash block, and then erasing the victim block. To improve the performance of garbage collection and extend the lifetime of the storage device, we propose a new data separation scheme, referred to as the Enhance Dynamic Clustering (EDC) scheme. By this scheme, data are dynamically classified and clustered together according to their data lifetimes. Experiment results showed that the EDC scheme significantly improved the performance of garbage collection, compared with various schemes. The number of erase operations and extra write operations performed during garbage collection could be greatly reduced even under various types of host workloads.","PeriodicalId":186790,"journal":{"name":"Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130658295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Texture weighted fuzzy C-means algorithm for 3D brain MRI segmentation 纹理加权模糊c均值算法在脑MRI三维分割中的应用

Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems Pub Date : 2018-10-09 DOI: 10.1145/3264746.3264777

Ji Young Lee, Dongyoun Kim, J. Mun, Seok-Jae Kang, Seong‐Ho Son, Sung Y. Shin

{"title":"Texture weighted fuzzy C-means algorithm for 3D brain MRI segmentation","authors":"Ji Young Lee, Dongyoun Kim, J. Mun, Seok-Jae Kang, Seong‐Ho Son, Sung Y. Shin","doi":"10.1145/3264746.3264777","DOIUrl":"https://doi.org/10.1145/3264746.3264777","url":null,"abstract":"The segmentation of human brain Magnetic Resonance Image (MRI) is an essential component in the computer-aided medical image processing research. Fuzzy C-Means (FCM) algorithm is one of the practical algorithms for brain MRI segmentation. However, Intensity Non-Uniformity (INU) problem in brain MRI is still challenging to existing FCM. In this paper, we propose the Texture weighted FCM (TFCM) algorithm performed with Local Binary Patterns on Three Orthogonal Planes (LBP-TOP). By incorporating texture constraints, TFCM could take into account more global image information. The proposed algorithm is divided into following stages: Volume of Interest (VOI) is extracted by 3D skull stripping in the pre-processing stage. The initial FCM clustering and LBP-TOP feature extraction are performed to extract and classify each cluster's features. At the last stage, FCM with texture constraints refines the result of initial FCM. The proposed algorithm has been implemented to evaluate the performance of segmentation result with Dice's coefficient and Tanimoto coefficient compared with the ground truth. The results show that the proposed algorithm has the better segmentation accuracy than existing FCM models for brain MRI.","PeriodicalId":186790,"journal":{"name":"Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130791587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0