基于智能手机的血糖监测系统

为了方便患者检测血糖值、长期存储检测数据并及时得到医生的诊断结论,设计了一种基于智能手机血糖监测系统。系统由无线血糖检测传感器、患者智能手机、医生智能手机组成,可实现远程会诊和远程监护。基于MSP430单片机的无线血糖检测传感器通过蓝牙与患者智能手机连接,不仅完成了检测功能,还可利用手机的短信功能发送检测值和接收医生的诊断;同时利用智能手机强大的软件平台完成数据的存储、管理、维护等功能。通过测试,该设计较好地满足了预定要求。     

基于智能手机的饮水监护装置

传统的饮水监护装置使用地点固定,不具有饮水提醒功能。设计了一种基于智能手机的饮水监护装置,能够通过智能手机更新饮水信息并提醒饮水。饮水量检测装置通过压力传感器检测饮水量,智能手机采用蓝牙无线通信方式接收由饮水量检测装置发送的饮水量数据,饮水监控App软件显示实时监测的饮水量数据表,并在饮水量不足时提醒饮水。功能测试表明,基于智能手机的饮水监护装置能够实时检测饮水量并提醒饮水。     

基于智能手机的心音监测系统的研究与设计

心音监测对心脏疾病的检测和预防有重要作用,研究并设计基于智能手机的心音监测系统。该系统由心音测量节点、智能手机节点、服务器端组成。测量节点实现心音信号的采集,智能手机节点接收测量节点的心音并将其经GPRS网络传递到服务器端,服务器端对心音进行远程的监测。其中智能手机节点是该系统的枢纽,其主要功能是分析处理心音：对心音进行小波去噪处理,通过LZ复杂度算法获取心音的特征指标,将特征指标用于心功能的分析评价及其异常预警。通过功能性测试表明该系统能稳定运行。     

基于异常流量监测的智能手机恶意软件检测研究

迅速发展的智能手机及移动通信技术在给人们带来极大便利和体验提升的同时,也带来了新的安全问题。总结了智能手机恶意软件的突出特点及危害和当前反恶意软件的发展状况,并结合设备及网络特点,提出了一种基于统计拟合方法的智能手机异常流量与恶意软件检测方法。该方法实时监控设备流量消耗情况,并以正常流量消耗的统计拟合曲线作为标准进行比对。仿真结果表明:该方法可以有效检测出异常流量。     

智能手机增强现实关键技术研究

将增强现实技术应用到智能手机上,实现增强现实系统的小型化和便携化,会大大拓展和深化增强现实系统应用的广度和深度。当前对于智能手机增强现实技术的研究,一般采用基于计算机视觉（即视频检测）的注册方式。首次提出了在智能手机上采用GPS/三维电子罗盘的注册方法,研究微型三维电子罗盘与智能手机的软、硬件接口,从底层开发并实现具有增强现实功能的软件模块,建立基于智能手机的空间信息三维可视化模型算法,并以三维管线为例进行实证研究,结果表明基于空间信息的智能手机增强现实构建的技术路线是可行的。     

带有人体跌倒检测的蓝牙耳机系统设计

随着智能手机的普及以及老年化程度的提高,提出一种基于加速度传感器的人体跌倒检测功能的、带有检测心率功能的蓝牙耳机的系统设计。该系统主要在蓝牙耳机的基础上增加了利用SVM阈值法的判别方法对跌倒行为进行检测,结合心率检测来判断跌倒后的人体健康状态的功能,并通过蓝牙技术传输相关情况给智能手机,由智能手机进行及时通知紧急联系人。     

基于智能手机的远程家电控制及安防监测系统的设计

设计了基于智能手机和GPRS网络的远程家电控制和安防监测系统.智能手机采用开放式操作系统,第三方可根据操作系统提供的API为其开发各种扩展应用.利用智能手机这一特性,开发用于系统的人机接口,方便了用户的操作.介绍了系统的结构和功能,详细阐述了智能手机监控软件的开发过程.     

可穿戴式人体呼吸状态监测系统的设计

设计了一种基于蓝牙的可穿戴式睡眠呼吸暂停低通气综合征监测装置,通过该装置可以实时检测到睡眠呼吸暂停低通气综合征病人的睡眠呼吸状态。可穿戴技术实现基本生理信号的低负荷获取;蓝牙实现呼吸数据短距离无线传输且方便与PDA或Android智能手机等手持终端通信,保证了对病人的连续实时监测。     

智能手机GPS功能开发与研究

基于智能手机Android的应用开发多种多样,该文利用智能手机自带的GPS芯片,开发了一款能够实时对手机携带者进行定位和跟踪的系统。系统由前台界面和后台服务组成,并且后台Service能将位置数据发送到监测台。     

基于智能手机恶意代码防范模型的研究

随着智能手机市场的发展,智能手机已经变得越来越普及,然而其安全问题却成了重大潜在威胁。关于智能手机领域的恶意代码防范模型及其应用研究显得尤为迫切及重要,由此提出了智能手机恶意代码防范模型,以期为智能手机恶意代码防范提供理论依据,并通过开发基于恶意代码检测层的扫描引擎进一步验证了该模型的安全性及可靠性。智能手机恶意代码防范模型能够实现对智能手机各个层面上的立体防范,为智能手机多功能的快速发展而引发的安全问题扫除障碍。     

年龄对利用脉搏波估计心率和心率变异性的准确性的影响

由于测量简便,脉搏波被广泛用于替代心电计算心率和心率变异性,但其准确性颇受争议。该文探讨了年龄对利用脉搏波估计心率和心率变异性准确性的影响,实验招募了 100 名年龄广泛分布在 20～71 岁的健康者,同步采集静息脉搏波和心电图,利用脉搏波相邻峰值点的时间间隔序列,计算受试者的瞬时心率和心率变异性,并将其与利用心电相邻两个 R 波峰值点计算的心率/心率变异性(金标准)进行对比,计算利用脉搏波估计心率和心率变异性的误差。实验结果表明,心率估计误差在 40 岁以下的年轻人中较小(标准差在 0.3 搏/min 左右),在 40 岁以上的中老年人中较大(标准差在 0.7 搏/min 左右),时域的心率变异性参数的规律类似。因此,即使在静息条件下,利用脉搏波峰值点计算老年人的心率/心率变异性也要谨慎对待。     

联合率失真模型的帧级码率控制方法

在H.264/AVC视频编码框架下,基于联合率失真模型,提出了一种新的帧级码率控制方法。利用分块数量和平均运动矢量信息,发展了一种精确的头信息估计模型;联合头信息与残差信息模型,并结合残差失真模型,提出新的联合头信息与残差率失真模型;利用精确的估计方法进一步提高率失真性能。相对于最新的JVT H.264/AVC参考软件JM10.2中采用的JVT-G012方法,该方法提高了实际码率与目标码率之间的匹配率达到了98.06%,重构视频的平均亮度PSNR值增加了0.27 dB。     

A Novel Machine Learning–Based Hand Gesture Recognition Using HCI on IoT Assisted Cloud Platform

Machine learning is a technique for analyzing data that aids the construction of mathematical models. Because of the growth of the Internet of Things (IoT) and wearable sensor devices, gesture interfaces are becoming a more natural and expedient human-machine interaction method. This type of artificial intelligence that requires minimal or no direct human intervention in decision-making is predicated on the ability of intelligent systems to self-train and detect patterns. The rise of touch-free applications and the number of deaf people have increased the significance of hand gesture recognition. Potential applications of hand gesture recognition research span from online gaming to surgical robotics. The location of the hands, the alignment of the fingers, and the hand-to-body posture are the fundamental components of hierarchical emotions in gestures. Linguistic gestures may be difficult to distinguish from nonsensical motions in the field of gesture recognition. Linguistic gestures may be difficult to distinguish from nonsensical motions in the field of gesture recognition. In this scenario, it may be difficult to overcome segmentation uncertainty caused by accidental hand motions or trembling. When a user performs the same dynamic gesture, the hand shapes and speeds of each user, as well as those often generated by the same user, vary. A machine-learning-based Gesture Recognition Framework (ML-GRF) for recognizing the beginning and end of a gesture sequence in a continuous stream of data is suggested to solve the problem of distinguishing between meaningful dynamic gestures and scattered generation. We have recommended using a similarity matching-based gesture classification approach to reduce the overall computing cost associated with identifying actions, and we have shown how an efficient feature extraction method can be used to reduce the thousands of single gesture information to four binary digit gesture codes. The findings from the simulation support the accuracy, precision, gesture recognition, sensitivity, and efficiency rates. The Machine Learning-based Gesture Recognition Framework (ML-GRF) had an accuracy rate of 98.97%, a precision rate of 97.65%, a gesture recognition rate of 98.04%, a sensitivity rate of 96.99%, and an efficiency rate of 95.12%.     

Quantitative analysis of heart rate recovery profile during recovery from physical work

A mathematical model depicting a person's heart rate profile during the recovery period was developed. This model consisted of two heart rate parameters, namely, a resting heart rate (HRR) and a heart rate increase (ΓHR), and a model parameter (ß) representing the recovery rate of heart rate. A load-carrying experiment was conducted to study the following: (1) the relationship between work load and the recovery rate of heart rate, and (2) the possibility of using the model to estimate a person's heart rate recovery profile. From the experiment, heart rate recovery profiles from fourteen subjects were recorded and their recovery rates were determined. The results showed that for the load carrying activity the recovery rate of heart rate linearly correlated with work load; the higher the work load, the faster the recovery rate was. Furthermore, when comparing the heart rate recovery profiles estimated by the model to those previously recorded, remarkable similarities were found at every work load studied.     

Performance assessment of near-perfect machines

This is a short, practical note which provides some reference operating curves of false acceptance rate versus missed acceptance rate as a function ofN, the number of test samples andf ₀, the specified machine error rate requirement. The only important statistical assumption made is the statistical independence of the samples in the test. The analysis shows that, to equalize the false acceptance rate with the missed acceptance rate, the machine acceptance test must use a thresholdK ^*=Nf ₀ – 1. If there areK ^* or fewer failures, then the machine acceptance test is passed. Otherwise, it fails. Furthermore, with such an acceptance test, the probability that the test is accurate depends only on the productNf ₀. WhenNf ₀ = 10, the probability that the test is accurate is 0.875. WhenNf ₀ = 20, the probability that the test is accurate is 0.912. These results indicate the necessity of large sample sizes when performing acceptance testing of near-perfect machines whose required error ratef ₀ is very close to zero.     

Robust Quality Adaptation for Internet Video Streaming

Internet video streaming is a widely popular application however, in many cases, congestion control facilities are not well integrated into such applications. In order to be fair to other users that do not stream video, rate adaptation should be performed to respond to congestion. On the other hand, the effect of rate adaptation on the viewer should be minimized and this extra mechanism should not overload the client and the server. In this paper, we develop a heuristic approach for unicast congestion control. The primary feature of our approach is the two level adaptation algorithm that utilizes packet loss rate as well as receiver buffer data to maintain satisfactory buffer levels at the receiver. This is particularly important if receiver has limited buffer such as in mobile devices. When there is no congestion, to maintain best buffer levels, fine grain adjustments are carried out at the packet level. Depending on the level of congestion and receiver buffer level, rate shaping that involves frame discard and finally rate adaptation by switching to a different pre-encoded video stream are carried out. Additive increase multiplicative decrease policy is maintained to respond to congestion in a TCP- friendly manner. The algorithm is implemented and performance results show that it has adaptation ability that is suitable for both local area and wide area networks. E. Turhan Tunali received B.Sc. Degree in Electrical Engineering from Middle East Technical University and M.Sc. Degree in Applied Statistics from Ege University, both in Turkey. He then received D.Sc. Degree in Systems Science and Mathematics from Washington University in St. Louis, U.S.A. in 1985. After his doctorate study, he joined Computer Engineering Department of Ege University as an assistant professor where he became an associate professor in 1988. During the period of 1992–1994, he worked in Department of Computer Technology of Nanyang Technological University of Singapore as a Visiting Senior Fellow. He then joined International Computer Institute of Ege University as a Professor where he is currently the director. In the period of 2000–2001 he worked in Department of Computer Science of Loyola University of Chicago as a Visiting Professor. His current research interests include adaptive video streaming and Internet performance measurements. Dr. Tunali is married with an eighteen year old son. Aylin Kantarci received B.Sc., M.Sc. and Ph.D. degrees all from Computer Engineering Department of Ege University, Izmir, Turkey, in 1992, 1994 and 2000, respectively. She then joined the same department as an assistant professor. Her current research interests include adaptive video streaming, video coding, operating systems, multimedia systems and distributed systems. Nukhet Ozbek received B.Sc. degree in Electrical and Electronics Engineering from School of Engineering and M.Sc. degree in Computer Science from International Computer Institute both in Ege University, Izmir, Turkey. From 1998 to 2003 she worked in the DVB team of Digital R&D at Vestel Corporation, Izmir-Turkey that produces telecommunication and consumer electronics devices. She is currently a Ph.D. student and a research assistant at International Computer Institute of Ege University. Her research areas include video coding and streaming, multimedia systems and set top box architectures.     

一种面向SVC的码率控制算法

H.264/AVC可伸缩性扩展视频编码系统(JSVM)提供了一种可伸缩视频编码(SVC)的解决方案,然而它本身并没有提供一种有效的码率控制算法.文中基于JSVM的分层预测结构,提出了一种全新的码率控制算法.首先在码率分配方面,考虑到分层B帧预测(或运动补偿时间域滤波(MCTF))结构,给出一种分层的码率分配方案;然后,针对不同类型和不同时间分解层各自的统计特性,分别为它们设计了不同的率失真(R-D)模型.实验结果表明,文中算法能够有效地控制码率,使得目标码率跟实际产生码率之间的偏差最大不超过2%;同时文中算法较大地提高了解码图像的质量,使得峰值信噪比(PSNR)在低码率端可提高1dB;另外,JSVM是通过不断调整量化参数(QP)使得实际产生的码率逐次逼近目标码率,较之这种尝试型的码率控制算法,文中基于模型的码率控制是在一次编码中产生最终的目标码率,从而大大降低了计算复杂度.     

电力文献搜索引擎系统设计

文献搜索引擎系统是一种计算机信息检索工具.提出一种全文检索系统的设计方案,对其中的索引数据库和全文数据库的建立、初始化问题、搜索函数的设计、结果页面设计等问题进行详细介绍.     

A psychophysiological approach to the assessment of work underload

The findings of a laboratory investigation of the relationship between the subjective and physiological components of work underload are reported. The subjective component is described in terms of the subjective work underload checklist, mental effort, and cognitive arousal. The physiological component is defined in terms of heart rate and heart rate variability. Evidence for an increase in work underload with a decrease in heart rate is provided. The relevance of this research to the aerospace environment is discussed and the need to investigate the behavioural component of work underload emphasized.     

FLASH教学中声音导入问题的浅析

目的:解决在FLASH中导入声音的问题.方法:对FLASH不支持的声音格式采取音频压缩的方法.结果:可成功将压缩后的声音文件导入到FLASH中.结论:在FLASH中使用声音可以使FLASH动画具有良好的动画效果.