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2018 14th International Conference on Emerging Technologies (ICET)最新文献

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Temporal Superpixels based Human Action Localization 基于时间超像素的人类动作定位
Pub Date : 2018-11-01 DOI: 10.1109/ICET.2018.8603608
Sami Ullah, Najmul Hassan, Naeem Bhatti
In this paper, we present human action localization in videos. It is a challenging task to localize actions performed in videos where the foreground areas containing video object as well as the background areas depict motion simultaneously. We set the main objective to identify action related spatio-temporal areas in a video. The proposed approach consists of two main steps. At first, we perform saturation (S plane of HSV space) based background subtraction to obtain foreground in video frames. Secondly, we compute the optical flow of video frames. Performing the superpixels segmentation of each video frame, we classify the superpixels as temporal or stationary using optical flow information and the extracted foreground. The collection of the classified temporal superpixels provide the required action localization in videos. We present qualitative as well as quantitative evaluation of our approach using UCF sports and Weizmann actions dataset. The visual results and quantitative performance measures show that the proposed approach well localizes the action areas in the taken action sequences for evaluation.
在本文中,我们提出了视频中的人类动作定位。在包含视频对象的前景区域和背景区域同时描述运动的视频中,对动作进行定位是一项具有挑战性的任务。我们设定的主要目标是识别视频中与动作相关的时空区域。所提出的方法包括两个主要步骤。首先,我们采用基于HSV空间S平面的饱和背景相减来获得视频帧中的前景。其次,我们计算了视频帧的光流。对每个视频帧进行超像素分割,利用光流信息和提取的前景将超像素分类为时间或静止。分类时间超像素的集合提供了视频中所需的动作定位。我们使用UCF体育和Weizmann动作数据集对我们的方法进行定性和定量评估。可视化结果和定量性能测量表明,该方法可以很好地定位已采取的行动序列中的行动区域进行评估。
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引用次数: 1
A CBR Model for Workload Characterization in Autonomic Database Management System 自主数据库管理系统中工作负载表征的CBR模型
Pub Date : 2018-11-01 DOI: 10.1109/ICET.2018.8603615
Nusrat Shaheen, B. Raza, Ahmad Kamran Malik
For effective workload management and performance tuning in Database Management System (DBMS) the Database Administrators (DBAs) have to deal with many issues. Workload monitoring and controlling can make the things easy for a DBA. Workload type prediction and adaptation can enable monitoring and controlling of workload that helps in DBMS performance tuning. In this study we propose a Case-Based Reasoning (CBR) model for workload type prediction that also has the ability to adapt dynamic workload behavior. To observe the accuracy, effectiveness, significance and adaptiveness of the proposed CBR model, it is compared with existing well-known machine learning approaches, such as, Support Vector Machine (SVM) and Neural Network (NN). For the validation of the proposed CBR model many standard benchmark workloads are experimented using the MySQL DBMS. The standard TPC-C and TPC-H like queries are used for generating training and testing data. In this study various experiments have been performed for Online Transaction Processing (OLTP) and Decision Support System (DSS) workloads. The proposed CBR model characterizes the workload through predicting its types. At the end, for result validation we have performed post-hoc tests which shows that the proposed CBR model produces better results.
为了在数据库管理系统(DBMS)中进行有效的工作负载管理和性能调优,数据库管理员(dba)必须处理许多问题。工作负载监视和控制可以使DBA的工作变得容易。工作负载类型预测和自适应可以监视和控制有助于DBMS性能调优的工作负载。在本研究中,我们提出了一个基于案例推理(CBR)的工作负载类型预测模型,该模型还具有适应动态工作负载行为的能力。为了观察所提出的CBR模型的准确性、有效性、意义和自适应性,将其与现有的知名机器学习方法,如支持向量机(SVM)和神经网络(NN)进行了比较。为了验证所提出的CBR模型,使用MySQL DBMS进行了许多标准基准工作负载的实验。标准的TPC-C和TPC-H类查询用于生成训练和测试数据。在本研究中,针对在线事务处理(OLTP)和决策支持系统(DSS)工作负载进行了各种实验。提出的CBR模型通过预测工作负荷的类型来表征工作负荷。最后,为了验证结果,我们进行了事后测试,结果表明所提出的CBR模型产生了更好的结果。
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引用次数: 5
Hand Electromyography Circuit and Signals Classification Using Artificial Neural Network 基于人工神经网络的手部肌电图电路及信号分类
Pub Date : 2018-11-01 DOI: 10.1109/ICET.2018.8603587
Muhammad Shahzaib, S. Shakil
Electromyography (EMG) is the study of electrical activity of muscles signals. This technique can be used for the control of prosthetic for amputees or for medical purposes in muscular disorders. Major challenge faced in this domain is high cost of the devices to control the prosthetic. In addition to the cost of the device, number of parameters used for classification is large for studies in this domain. In this study we propose a low cost circuit for EMG signal extraction. We used 4 channels of proposed EMG circuit to classify 6 different motion that includes individual finger motions and fist motion. Despite being low cost, our circuit provides the signals that can be classified with high accuracies comparable to other studies. For classification, we used artificial neural network with less number of parameters to achieve accuracies comparable to other studies using higher number of parameters. We collected data from 5 healthy subjects using our proposed circuit. Behavior of EMG signal varies from subject to subject depending upon different factors. We used six features from time and frequency domains, gave an accuracy of 98.8% and 96.8% for all combined subjects with two different algorithms and an average accuracy of 99% with standard deviation of 0.6 for all individual subjects.
肌电图(EMG)是对肌肉电信号的电活动的研究。该技术可用于截肢者假肢的控制或用于肌肉疾病的医疗目的。该领域面临的主要挑战是控制假肢的设备成本高。除了设备的成本之外,用于分类的参数数量对于该领域的研究来说是很大的。在本研究中,我们提出了一种低成本的肌电信号提取电路。我们使用4个通道的EMG电路对6种不同的运动进行分类,包括单个手指运动和拳头运动。尽管成本低,但我们的电路提供的信号可以与其他研究相比具有较高的分类精度。对于分类,我们使用了参数数量较少的人工神经网络,以达到与其他使用更多参数的研究相当的精度。我们使用我们提出的电路收集了5名健康受试者的数据。肌电图信号的表现因不同的因素而异。我们使用了来自时域和频域的六个特征,使用两种不同的算法对所有组合受试者的准确率分别为98.8%和96.8%,对所有单个受试者的平均准确率为99%,标准差为0.6。
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引用次数: 4
AlGaN/GaN FinFET: A Comparative Study AlGaN/GaN FinFET之比较研究
Pub Date : 2018-11-01 DOI: 10.1109/ICET.2018.8603581
U. F. Ahmed, S. Rehman, U. Rafique, M. Ahmed
In this paper, a comprehensive study is conducted on AlGaN/GaN FinFETs as a potential candidate for microwave and power applications. It has been described that due to superior material properties associated with GaN and electrical properties exhibited by the tri-gate structure, FinFETs offer superior results for radio frequency applications. The tri-gate structure of FinFET allows full depletion of the channel, which results in low leakage current and dynamic power loss. FinFETs offer higher current density and integration compared to other mainstream CMOS technologies.
本文对AlGaN/GaN finfet作为微波和功率应用的潜在候选器件进行了全面的研究。由于与氮化镓相关的优越材料特性和三栅极结构所展示的电学特性,finfet为射频应用提供了优越的结果。FinFET的三栅极结构允许通道完全耗尽,从而导致低泄漏电流和动态功率损耗。与其他主流CMOS技术相比,finfet具有更高的电流密度和集成度。
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引用次数: 2
Video Retrieval System Using Parallel Multi-Class Recurrent Neural Network Based on Video Description 基于视频描述的并行多类递归神经网络视频检索系统
Pub Date : 2018-11-01 DOI: 10.1109/ICET.2018.8603598
Saira Jabeen, Gulraiz Khan, Humza Naveed, Zeeshan Khan, Usman Ghani Khan
In recent times, there has been continuous interest in the area of content based information retrieval (CBIR) for images and video sequences. Exponential increase of multimedia data has triggered a cause for managing, storing and retrieving multimedia contents in convenient and efficient ways. Visual features from static images and dynamic videos are extracted to perform retrieval task. Once visual features are extracted, there is a need to search and retrieve relevant videos in efficient amount of time. This paper makes use of seven visual features; human detection, emotion, age, gender, activity, scene and object detection followed by sentence generation. Furthermore, generated sentence is used in multi-class recurrent neural network (RNN) to find genre of a video for retrieval task. Accuracy, precision and recall are used for evaluation of this framework on self generated dataset. Experiments show that our system is able to achieve high accuracy of 88.13%.
近年来,图像和视频序列的基于内容的信息检索(CBIR)领域一直受到人们的关注。多媒体数据呈指数级增长,促使人们以方便、高效的方式管理、存储和检索多媒体内容。从静态图像和动态视频中提取视觉特征来执行检索任务。一旦提取了视觉特征,就需要在有效的时间内搜索和检索相关视频。本文利用了七个视觉特征;人的检测,情感,年龄,性别,活动,场景和对象检测,然后句子生成。然后,将生成的句子应用于多类递归神经网络(RNN)中,寻找视频的类型进行检索。在自生成数据集上对该框架进行了准确度、精密度和召回率评价。实验表明,该系统能够达到88.13%的准确率。
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引用次数: 7
An empirical Investigation of Motives, Nature and online Sources of Cyberbullying 网络欺凌的动机、性质和网络来源的实证研究
Pub Date : 2018-11-01 DOI: 10.1109/ICET.2018.8603617
Sidra Abbasi, A. Naseem, A. Shamim, M. A. Qureshi
Cyberbullying related with social, emotional and academic harms can be critical and enduring. Cyberbullying is where context has a dynamic impact. Pakistan is one of its late accepters of IT; yet, the IT sector has developed during recent couple of years. By utilizing more extensive proportion of cyberbullying and looking at what cause it to occur, the present investigation plans to inspect (i) motives of the cyber aggressor, by how do individuals get the opportunity to participate in cyberbullying? (ii) Negative influences on cyber victim, (iii) Obscurity of Cyber Aggressor, (iv) Omission in cyberbullying with respect to gender metamorphosis and (v) Sort of social sites used to commit. Data was collected through instrument survey that is grounded on 5-point Likert Scale and effective responses from 600 university students from different provinces and states were utilized, coded and evaluated by using SPSS. Type of electronic media used to commit cyberbullying by respondents were reported as Instant messaging, E-mails, Social Networking Sites, Online games, compromising photos, Videoclips, Phone calls, Raid on personal blogs and websites. Findings demonstrate that the foremost motive amongst respondents to commit electronic bullying is found to be Social Relationship. Main motive for males behind bullying others using cyber medium is "Unevenness of Power" and make themselves socially strong or weaken others. However, Secrecy and Namelessness caused by anonymity offered by cyberbullying is most prominent motive for females. The results showed that females are more affected by cyberbullying as compared to males regarding "Withdrawal and Isolation" and "Indulging in Harmful Habits". However Increased Psychological Distress caused by cyberbullying has no major difference between males and females. Anonymity through secrecy, namelessness and freedom of expression enables cyber bully to feel protected in virtual environments and they may take advantage when contrasted with traditional bullying.
与社会、情感和学术伤害相关的网络欺凌可能是严重和持久的。在网络欺凌中,情境会产生动态影响。巴基斯坦是较晚接受信息技术的国家之一;然而,IT行业在最近几年得到了发展。本研究拟通过更广泛地利用网络欺凌所占的比例,研究其发生的原因,来考察(1)网络欺凌者的动机,个人是如何获得参与网络欺凌的机会的?(ii)对网络受害者的负面影响,(iii)网络攻击者的默默无闻,(iv)网络欺凌在性别变态方面的遗漏,以及(v)用于实施暴力的社交网站类型。数据通过基于5点李克特量表的仪器调查收集,并利用来自不同省份和州的600名大学生的有效回答,使用SPSS进行编码和评估。受访者使用的网络欺凌的电子媒体类型包括即时通讯、电子邮件、社交网站、网络游戏、泄露照片、视频剪辑、电话、访问个人博客和网站。调查结果显示,受访者实施电子欺凌的首要动机是社会关系。男性利用网络欺凌他人的主要动机是“权力不均衡”,使自己在社会上变得强大或削弱他人。然而,网络欺凌所带来的匿名性和匿名性是女性最主要的动机。结果显示,与男性相比,女性在“退缩和孤立”和“沉溺于有害习惯”方面受到网络欺凌的影响更大。然而,网络欺凌导致的心理困扰增加在男性和女性之间没有显著差异。通过保密、匿名和言论自由实现的匿名性使网络欺凌者在虚拟环境中感到受到保护,与传统欺凌相比,他们可能会占上风。
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引用次数: 8
Finding Research Areas of Academicians using Clique Percolation 利用派系渗透寻找院士的研究领域
Pub Date : 2018-11-01 DOI: 10.1109/ICET.2018.8603549
Faisal Imran, R. Abbasi, Muddassar Azam Sindhu, Akmal Saeed Khattak, Ali Daud, Tehmina Amjad
Identifying research areas of academicians is a challenging task. Most of the researchers have used supervised machine learning to handle this task which requires labelled data. In this paper, we propose to use clique percolation (an overlapping community detection algorithm) to identify research areas of academicians. We propose a framework to collect data from digital libraries and websites of selected universities in Pakistan. We then identify researchers working in multiple research areas using clique percolation and present results of our analyses.
确定院士的研究领域是一项具有挑战性的任务。大多数研究人员使用监督式机器学习来处理这个需要标记数据的任务。在本文中,我们提出使用派系渗透(一种重叠社区检测算法)来识别院士的研究领域。我们提出了一个框架,从巴基斯坦选定大学的数字图书馆和网站收集数据。然后,我们确定在多个研究领域工作的研究人员使用集团渗透和我们的分析结果。
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引用次数: 3
A Configurable, Multi-Mode Comma Detection and Word Alignment Controller for High Speed Serial Interface in 130 nm CMOS Technology 一种用于高速串行接口的130纳米CMOS技术的可配置多模式逗号检测和字对齐控制器
Pub Date : 2018-11-01 DOI: 10.1109/ICET.2018.8603553
Imran Ali, Muhammad Asif, Muhammad Riaz ur Rehman, Muhammad Basim, Sung Jin Kim, Kangyoon Lee
In this paper, a comma detection with word alignment controller is proposed for high speed serial interface applications. Before the word alignment, a configurable number of successive comma detection enhances the reliability of the controller. The comma control word is also configurable to make it flexible for numerous applications. In the proposed multi-mode architecture, automatic and manual control are also incorporated. The presented architecture is fully synthesizable. It occupies a very small area of 110 × 100 µm² and it requires only 1.556 K gates for its implementation. The current and power requirements are 681.09 µA and 817.31 µW respectively from 1.2 V power supply. The design is integrated into 3.125 Gbps JESD204B serial interface which is fabricated in 1P6M 130 nm CMOS process. The simulation and measurement result ensures the reliability of the proposed architecture.
本文提出了一种用于高速串行接口的逗号检测与字对齐控制器。在单词对齐之前,连续逗号检测的可配置数量提高了控制器的可靠性。逗号控制字也是可配置的,使其灵活适用于许多应用程序。在多模式结构中,自动控制和手动控制相结合。所呈现的体系结构是完全可合成的。它占用非常小的110 × 100µm²的面积,只需要1.556 K的栅极即可实现。1.2 V供电时,电流要求为681.09µA,功率要求为817.31µW。该设计集成在3.125 Gbps的JESD204B串行接口上,该接口采用1P6M 130 nm CMOS工艺制造。仿真和测试结果验证了所提体系结构的可靠性。
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引用次数: 2
Semantic Analysis of News Based on the Deep Convolution Neural Network 基于深度卷积神经网络的新闻语义分析
Pub Date : 2018-11-01 DOI: 10.1109/ICET.2018.8603653
Muhammad Zeeshan Khan, Muhammad A. Hassan, S. U. Hassan, Muhammad Usman Ghanni Khan
Video data analysis is a fascinating field since the last few decades. It assists user to find the genre of a video without watching it. In this paper, an application for analysing Pakistani news data based on the scene classification using deep convolution neural network has been presented. For this purpose the dataset has been collected on our own, which consists of 200 videos of different news channels, and covers almost all categories which we possess in our methodology. The results have been evaluated using the 2D convolution neural network on the fine-tuned inception model. The methodology achieved the 92.2% accuracy on the proposed architecture, such a high accuracy on locally prepared dataset of the news for the video data analysis shows the novelty in literature.
视频数据分析是近几十年来一个引人入胜的领域。它可以帮助用户在不看视频的情况下找到视频的类型。本文提出了一种基于场景分类的深度卷积神经网络在巴基斯坦新闻数据分析中的应用。为此,我们自己收集了数据集,其中包括200个不同新闻频道的视频,几乎涵盖了我们在方法中拥有的所有类别。使用二维卷积神经网络在微调初始模型上对结果进行了评估。该方法在提出的体系结构上达到了92.2%的准确率,如此高的准确率在本地准备的新闻数据集上用于视频数据分析显示了文献的新颖性。
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引用次数: 4
ROBO-FLOCK: Development of a low-cost Leader-follower Swarm of Mobile Robots robot - flock:开发一种低成本的Leader-follower移动机器人群
Pub Date : 2018-11-01 DOI: 10.1109/ICET.2018.8603662
M. Rasheed, Rimsha Tanveer, M. Akhtar, Z. Khan
This paper describes a low-cost design for flocking control of mobile robots. The robots are in Master-Slave configuration with full duplex communication mode. Two important factors included in the present research are the co-design of coordination and communication. To provide coordination between master and slave, a wireless communication network is built between the master and the slave units. For practical implementation of coordination between robots we selected two basic problems in mobile robotics. One of which is line following technique and second one is collision avoidance using swarm based control. Both techniques comprise of one master and one slave unit. The master robot acts as a controller for the slave unit in order to control all the position, orientation and speed of slave.
本文介绍了一种低成本的移动机器人群集控制设计。机器人采用主从配置,全双工通信模式。本研究中包含的两个重要因素是协同设计和沟通。为了提供主从机之间的协调,在主从机之间建立了一个无线通信网络。为了实际实现机器人之间的协调,我们选择了移动机器人中的两个基本问题。一种是直线跟踪技术,另一种是基于群体控制的避碰技术。这两种技术都包括一个主设备和一个从设备。主机器人作为从机器人的控制器,控制从机器人的所有位置、方向和速度。
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引用次数: 1
期刊
2018 14th International Conference on Emerging Technologies (ICET)
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