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

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Challenges of Cybercrimes to Implementation of Legal Framework 网络犯罪对法律框架实施的挑战
Pub Date : 2018-11-01 DOI: 10.1109/ICET.2018.8603645
Zunaira Sattar, Shazia Riaz, Shafia, A. U. Mian
With the progressing technology there is a new breed of crimes that is capable of crossing geographical boundaries. Regulatory authorities and legal reforms do not have much capacity to control these crimes. Pakistan as developing country, is determined to follow legal and regulatory frameworks to control cyber terrorism. With emergence of 4G technology, people of Pakistan are venturing into online business and social media entertainment or communication, with rising number of cybercrimes every day. The need to completely eliminate cybercrimes hazard is becoming more important. This study is conducted on the subjects which were either part of victimization by cybercrimes or could identify some of the steps to stop cyberterrorism. The reasons include lack of awareness about cybercrimes, unemployment, lack of education and less implementation of cyber laws. The effects of cybercrimes on the society include reducing the personal growth of people both moral and economical, wastage of time and misrepresentation to the country’s image. It also includes financial damages to large business. This research also focuses the awareness regarding offences to control the cybercrimes in Pakistan in context with legal reforms and cyber laws. Cyber act is the law for prevention of electronic crime act 2016. There is strong need of increasing social campaigns and against cybercrimes. People should adopt strong security measures to prevent themselves from cyber thieves.
随着科技的进步,出现了一种能够跨越地理边界的新型犯罪。监管当局和法律改革没有多少能力控制这些犯罪。巴基斯坦作为发展中国家,决心遵循法律和监管框架来控制网络恐怖主义。随着4G技术的出现,巴基斯坦人正在冒险进入在线商业和社交媒体娱乐或交流,每天都有越来越多的网络犯罪。彻底消除网络犯罪危害的必要性变得越来越重要。本研究的对象要么是网络犯罪受害者的一部分,要么是可以确定一些阻止网络恐怖主义的步骤。原因包括缺乏对网络犯罪的认识、失业、缺乏教育以及网络法律的执行不力。网络犯罪对社会的影响包括减少人们在道德和经济上的个人成长,浪费时间和歪曲国家形象。它还包括对大企业的经济损失。本研究还侧重于在法律改革和网络法律的背景下控制巴基斯坦网络犯罪的犯罪意识。《网络犯罪法》是《2016年防止电子犯罪法》。我们迫切需要加强社会运动,打击网络犯罪。人们应该采取强有力的安全措施,防止自己受到网络窃贼的攻击。
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引用次数: 5
Cloudlet-based Augmentation of Mobile Devices 基于云的移动设备增强
Pub Date : 2018-11-01 DOI: 10.1109/ICET.2018.8603627
A. Raza, Irfan ul Haq, Usman Shaukat
Although Cloud services support wide range of mobile applications, access to Cloud services suffer from several performance issues such as WAN latency, jitter, and packet loss. Frameworks based on the concept known as Edge Computing, Fog Computing or Cloudlet have been proposed to overcome these performance issues. More specifically, Cloud Edge or Cloudlet aims to bring the Cloud or a specific part of the Cloud closer to the mobile device by utilizing proximate computing resources to augment mobile devices. In our proposed framework AD-LET, proximate mobile devices come together to share their resources and create a Cloudlet. AD-LET is self-managing, scalable and can share resources among different types of mobile devices. Experimental results have shown that AD-LET can significantly improves the capability of a mobile device. It augments mobile device thus enabling it to perform resource intensive tasks in the absence of a Cloud or near by infrastructure resources. The layered structure of our framework makes it extensible and allows it to support many types of services and application frameworks.
尽管云服务支持广泛的移动应用程序,但是访问云服务会遇到一些性能问题,例如WAN延迟、抖动和数据包丢失。已经提出了基于边缘计算、雾计算或Cloudlet概念的框架来克服这些性能问题。更具体地说,Cloud Edge或Cloudlet旨在通过利用邻近的计算资源来增强移动设备,使云或云的特定部分更接近移动设备。在我们提出的AD-LET框架中,邻近的移动设备聚集在一起共享它们的资源并创建一个Cloudlet。AD-LET具有自我管理、可扩展、可在不同类型的移动设备之间共享资源的特点。实验结果表明,AD-LET可以显著提高移动设备的性能。它增强了移动设备,从而使其能够在没有云或附近基础设施资源的情况下执行资源密集型任务。我们框架的分层结构使其具有可扩展性,并允许它支持多种类型的服务和应用程序框架。
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引用次数: 1
Domain Specific Emotion Lexicon Expansion 特定领域情感词典扩展
Pub Date : 2018-11-01 DOI: 10.1109/ICET.2018.8603550
Hussain S. Khawaja, M. O. Beg, Saira Qamar
Emotion Classification using lexicons has vast number of applications ranging from social media analysis to pervasive computing. Lexicons are usually hand-crafted and cost a lot of time and effort to generate. The major research challenge in this area is the creation of a generalized lexicon which serves well for every domain. This work focuses on automatic expansion of emotion lexicons to ease the process of domain adaption. Our proposed approach — CB-Lex — relies on a seed lexicon and an unlabeled corpus from the target domain. In experimental results, our expanded lexicons show an improvement of over 6% in F-Measure.
使用词汇进行情感分类具有广泛的应用,从社交媒体分析到普适计算。词典通常是手工制作的,需要花费大量的时间和精力来生成。该领域的主要研究挑战是创建一个适用于每个领域的通用词典。本工作的重点是情感词汇的自动扩展,以简化领域适应的过程。我们提出的方法- CB-Lex -依赖于来自目标领域的种子词典和未标记的语料库。在实验结果中,我们的扩展词汇在F-Measure上提高了6%以上。
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引用次数: 21
Online Adaptive NeuroFuzzy Based Energy Management Schemes for Fuel-Cell Based Hybrid Power System 基于在线自适应神经模糊的燃料电池混合动力系统能量管理方案
Pub Date : 2018-11-01 DOI: 10.1109/ICET.2018.8603637
M. Basit, R. Badar
Hybrid power systems are now extensively being used due to their low fuel consumption and greater efficiency. In this context, fuel cell integration with conventional power sources is becoming an interesting solution. Choice of fuel cell as power source also serves to address many environmental concerns. Energy Management Schemes (EMSs) have great influence on dynamic performance and fuel consumption of these sources. EMS controls the power split between different energy sources to fulfill the power demand at load. In this paper, comparative analysis of different NeuroFuzzy based EMSs for emergency landing scenario of More Electric Air-Craft is presented. The performance validity of online adaptive NeuroFuzzy Wavelet Control has been checked against conventional NeuroFuzzy Takagi Sugeno Kang (TSK) control and classical PI control. State of the charge of battery and supercapacitor, fuel consumption and overall system efficiency have been chosen as performance metrics.
混合动力系统由于其低燃料消耗和更高的效率而被广泛使用。在这种情况下,燃料电池与传统电源的集成成为一个有趣的解决方案。选择燃料电池作为动力源也有助于解决许多环境问题。能源管理方案(EMSs)对这些能源的动态性能和燃料消耗有很大的影响。EMS控制不同能源之间的电力分配,以满足负载的电力需求。针对多电动飞机紧急降落场景,对不同的基于神经模糊的EMSs进行了比较分析。将在线自适应神经模糊小波控制与传统神经模糊TSK (Takagi Sugeno Kang)控制和经典PI控制进行了性能有效性检验。选择电池和超级电容器的充电状态、燃料消耗和系统整体效率作为性能指标。
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引用次数: 2
Sentiment Analysis of Polarity in Product Reviews In Social Media 社交媒体中产品评论极性的情感分析
Pub Date : 2018-11-01 DOI: 10.1109/ICET.2018.8603585
Marium Nafees, H. Dar, I. Lali, Salman Tiwana
Sentiment analysis is the study area in Natural language processing (NLP) that is concerned to identify the mood or opinion with in the text. This paper emphasizes on the different methods utilized for classifying the natural language text reviews in accordance with opinions expressed in text to analyze whether the extensive behavior is negative, positive or neutral. The abundance of discussion platforms, Weblogs, product reviews sites, e-commerce and social networking sites have encouraged stream of thoughts and articulation of opinions. Social media is considered to be a big platform of sentiments, reviews and opinion evaluation. Data used in this study are online product reviews collected from twitter and used to rank the best classifier for sentiments. The method of analysis on polarity classification was discussed in experimental work by using well known classifiers including Naïve byes, Support vector machine and Logistic regression for predicting the user reviews.
情感分析是自然语言处理(NLP)中的一个研究领域,涉及识别文本中的情绪或观点。本文着重介绍了根据文本表达的意见对自然语言文本评论进行分类的不同方法,以分析广泛的行为是消极的、积极的还是中性的。大量的讨论平台、博客、产品评论网站、电子商务和社交网站鼓励了思想的流动和观点的表达。社交媒体被认为是一个情感、评论和意见评价的大平台。本研究中使用的数据是从twitter上收集的在线产品评论,并用于对情感的最佳分类器进行排名。在实验工作中讨论了极性分类的分析方法,利用Naïve byes、支持向量机和Logistic回归等分类器预测用户评论。
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引用次数: 6
Continuous and Noninvasive Blood Pressure Estimation by Two-Sensor Measurement of Pulse Transit Time 双传感器测量脉搏传递时间的连续无创血压估算
Pub Date : 2018-11-01 DOI: 10.1109/ICET.2018.8603612
Anam Rasool, Muqudas Rafiq, Aisha Nasir, Faisal M. Kashif
Continuous and noninvasive monitoring of blood pressure is of vital importance in critical care. Its role in management of patients with or at risk of cardiovascular disease is ever increasing. Pulse-transit-time based approaches for estimation of blood pressure hold potential to provide a convenient solution, however there is a need to improve their accuracy. We employ a novel two-sensor technique using photoplethysmogram and piezo sensors for a more accurate measurement of pulse transit time (PTT). PTT is then mapped to arterial blood pressure via calibration process. We implement two different techniques for the PTT measurement. The first technique uses two pulse sensors, while the second technique makes use of one pulse sensor and one piezo element. Clinical data is collected from 46 subjects in the form of systolic, diastolic and mean blood pressure to provide a reference for the calibration step in two techniques. The results show decrease in error of systolic arterial pressure (SAP) and mean arterial pressure (MAP) for the second technique. The root mean square (RMS) error, measured for the calibration equations, reduced from 7.72 mm Hg to 5.26 mm Hg for SAP and from 7.07 mm Hg to 6.30 mm Hg for MAP. RMS error, measured by leave-one-out method, reduced from 8.45 mm Hg to 5.77 mm Hg for SAP and from 7.67 mm Hg to 6.90 mm Hg for MAP.
在重症监护中,持续无创监测血压是至关重要的。它在管理心血管疾病患者或有心血管疾病风险的患者中的作用越来越大。基于脉冲传递时间的血压估计方法有可能提供一种方便的解决方案,但是需要提高其准确性。我们采用了一种新的双传感器技术,使用光电容积图和压电传感器来更准确地测量脉冲传递时间(PTT)。然后通过校准过程将PTT映射到动脉血压。我们实现了两种不同的PTT测量技术。第一种技术使用两个脉冲传感器,而第二种技术使用一个脉冲传感器和一个压电元件。收集46名受试者的收缩压、舒张压和平均血压的临床数据,为两种技术的校准步骤提供参考。结果表明,第二种方法的收缩压(SAP)和平均动脉压(MAP)误差减小。校准方程测量的均方根误差(RMS)从SAP的7.72毫米汞柱降至5.26毫米汞柱,MAP的7.07毫米汞柱降至6.30毫米汞柱。采用留一法测量的均方根误差,SAP从8.45 mm Hg降至5.77 mm Hg, MAP从7.67 mm Hg降至6.90 mm Hg。
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引用次数: 8
Stress Effects on Exam Performance using EEG 压力对考试成绩的影响
Pub Date : 2018-11-01 DOI: 10.1109/ICET.2018.8603652
Muhammad Adeel Hafeez, S. Shakil, Sobia Jangsher
Mental stress can be one of the most prominent factors of failure or poor performance in students. The traditional method of examination involves evaluating performance of students in limited time that may increase their stress level and may deteriorate their performance. Electroencephalogram (EEG) is one of the most commonly used methods to measure stress using brain waves. In this study, we investigate the influence of time limitation in exam on the performance of students and use EEG to explore the contribution of stress towards the change in performance. For this purpose, students performed mental arithmetic task (MAT) based on Montreal Imaging Stress Task of same difficulty level twice; once with time limitation accompanied by feedback for every question to induce stress and once without any time limitation and feedback. We observe vast difference in performance of the students for the two MAT tests and significant change in the power spectral density of theta, alpha, and beta frequency bands associated with increase in stress level for three chosen electrodes in EEG results. Our results show that stress may be one of the major factors for bad performance of the students in the exam resulting in failure.
精神压力可能是学生失败或表现不佳的最重要因素之一。传统的考试方法是在有限的时间内评估学生的表现,这可能会增加他们的压力水平,可能会降低他们的表现。脑电图(EEG)是利用脑电波测量压力最常用的方法之一。在本研究中,我们探讨了考试时间限制对学生成绩的影响,并利用脑电图来探讨压力对成绩变化的贡献。为此,学生在相同难度的蒙特利尔影像应激任务基础上进行了两次心算任务;一次有时间限制,每个问题都有反馈,以引起压力,一次没有时间限制和反馈。我们观察到学生在两个MAT测试中的表现存在巨大差异,并且在脑电图结果中,与压力水平增加相关的三个选择电极的θ、α和β频段的功率谱密度发生了显著变化。我们的研究结果表明,压力可能是学生在考试中表现不佳导致失败的主要因素之一。
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引用次数: 9
Structured Uncertainty Modeling, Control Synthesis & Tracking of Coordinated Fingers Movement 手指协调运动的结构不确定性建模、控制综合与跟踪
Pub Date : 2018-11-01 DOI: 10.1109/ICET.2018.8603551
Maryam Iqbal, A. Mahmood
A control paradigm can be created by the coordinated movement of the fingers with the central nervous system. In this paper we added a structured uncertainty to a system to study and investigate a biomechanical model of reflexive movement of human ring finger when the little finger is bent. We then applied a robust feedback H∞ control synthesisd by combining a full order estimator with a full information controller to achieve stable results. Structured uncertainties have been incorporated using µ-synthesis. Analysis with the help of µ-synthesis generates a better modeling and control strategy for a movement coordination of human fingers. We also introduced the reference input tracking problem for the model. We simulated the model for studying stability analysis and for comparison of performance. The simulation results help in understanding the coordination of human fingers with central nervous system which can be utilized in application of active prosthetics.
控制范例可以通过手指与中枢神经系统的协调运动来创建。在本文中,我们添加了一个结构化的不确定性系统研究和探讨人类无名指的反射性运动的生物力学模型时小指弯曲。然后,我们应用由全阶估计器与全信息控制器相结合合成的鲁棒反馈H∞控制来获得稳定的结果。结构不确定度采用微合成。在微合成的帮助下进行分析,可以为人类手指的运动协调提供更好的建模和控制策略。我们还介绍了模型的参考输入跟踪问题。我们对该模型进行了仿真,用于研究稳定性分析和性能比较。仿真结果有助于理解人体手指与中枢神经系统的协调性,为主动假肢的应用提供依据。
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引用次数: 1
Robot Localization in Indoor and Outdoor Environments by Multi-sensor Fusion 基于多传感器融合的室内外机器人定位
Pub Date : 2018-11-01 DOI: 10.1109/ICET.2018.8603597
Sofia Yousuf, M. Kadri
Robot Localization (robot pose determination) has become an important aspect for a variety of tasks accomplished by mobile robots. Also accurate localization is required for robot tracking, path planning and control. Today, many sensor technologies are utilized to determine the exact robot location, for instance, in indoor environments, odometers (wheel encoders) and inertial navigation system (INS) are used to ascertain the relative position and pose of the robot. In outdoor environments, Global Positioning System (GPS) can also be integrated in the sensor suite to determine the actual position of the robot in terms of latitude and longitude. This paper presents a robust methodology for robot localization in indoor as well as outdoor environments by a mechanism known as "data fusion" of multiple sensors also called Multi-Sensor Fusion (MSF) or Information Fusion (IF). In, outdoor environments, the sensor information collected from the embedded INS and GPS modules on mobile test robot are fused using a recursive state estimation and fusion algorithm known as Kalman Filter (KF). The estimated position obtained using KF is then combined with odometer based position data using weighting scheme to obtain the final position estimate of the robot. The main contribution of this work is to employ a multi-layer perceptron neural network (MLP-NN) to provide robot position estimates in an indoor environment where GPS signals are blocked. The MLP-NN is trained when the GPS data is available. As soon as the GPS signals are lost the trained MLP-NN provides predictions regarding the current position of robot. The proposed scheme is tested on the GPS-INS data obtained from on board sensors attached to a mobile robot. Simulation results have been presented which establish the efficacy of the proposed scheme.
机器人定位(机器人姿态确定)已成为移动机器人完成各种任务的一个重要方面。机器人的跟踪、路径规划和控制也需要精确的定位。如今,许多传感器技术被用来确定机器人的确切位置,例如,在室内环境中,里程表(车轮编码器)和惯性导航系统(INS)被用来确定机器人的相对位置和姿态。在室外环境中,还可以在传感器套件中集成全球定位系统(GPS),以确定机器人在经纬度方面的实际位置。本文提出了一种基于多传感器“数据融合”(也称为多传感器融合(MSF)或信息融合(IF))机制的机器人在室内和室外环境中定位的鲁棒方法。在室外环境中,移动测试机器人的嵌入式INS和GPS模块采集的传感器信息使用递归状态估计和融合算法Kalman Filter (KF)进行融合。然后利用KF得到的估计位置与基于里程表的位置数据结合,采用加权方案得到机器人的最终位置估计。这项工作的主要贡献是采用多层感知器神经网络(MLP-NN)在GPS信号受阻的室内环境中提供机器人位置估计。当GPS数据可用时,对MLP-NN进行训练。一旦GPS信号丢失,经过训练的MLP-NN就会提供关于机器人当前位置的预测。该方案在移动机器人的车载传感器获得的GPS-INS数据上进行了测试。仿真结果验证了该方案的有效性。
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引用次数: 5
期刊
2018 14th International Conference on Emerging Technologies (ICET)
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