The smart car seat: personalized monitoring of vital signs in automotive applications

Embedded wireless sensors are important components of mobile distributed computing networks, and one of the target applications areas is health care. The preservation of mobility for senior citizens is one of the key issues in maintaining an independent lifestyle. Thus health technologies inside a car can contribute both to safety issues (supervision of driver fitness) as well as healthcare issues by monitoring vitals signs imperceptibly. In this paper, three embedded measurement techniques for non-contact monitoring of vital signals have been investigated. Specifically, capacitive electrocardiogram (cECG) monitoring, mechanical movement analysis (ballistocardiogram, BCG) using piezo-foils and inductive impedance monitoring were examined regarding their potential for integration into car seats. All three sensing techniques omit the need for electroconductive contact to the human body, but require defined mechanical boundary conditions (stable distances or, in the case of BCG, frictional connection). The physical principles of operation, the specific boundary conditions regarding automotive integration and the results during wireless operation in a running car are presented. All three sensors were equipped with local intelligence by incorporating a microcontroller. To eliminate the need for additional cabling, a wireless Bluetooth communication module was added and used to transmit data to a measurement PC. Finally, preliminary results obtained during test drives on German city roads and highways are discussed.     

Filter-resistant code injection on ARM

Code injection attacks are one of the most powerful and important classes of attacks on software. In these attacks, the attacker sends malicious input to a software application, where it is stored in memory. The malicious input is chosen in such a way that its representation in memory is also a valid representation of a machine code program that performs actions chosen by the attacker. The attacker then triggers a bug in the application to divert the control flow to this injected machine code. A typical action of the injected code is to launch a command interpreter shell, and hence the malicious input is often called shellcode. Attacks are usually performed against network facing applications, and such applications often perform validations or encodings on input. Hence, a typical hurdle for attackers, is that the shellcode has to pass one or more filtering methods before it is stored in the vulnerable application??s memory space. Clearly, for a code injection attack to succeed, the malicious input must survive such validations and transformations. Alphanumeric input (consisting only of letters and digits) is typically very robust for this purpose: it passes most filters and is untouched by most transformations. This paper studies the power of alphanumeric shellcode on the ARM architecture. It shows that the subset of ARM machine code programs that (when interpreted as data) consist only of alphanumerical characters is a Turing complete subset. This is a non-trivial result, as the number of instructions that consist only of alphanumeric characters is very limited. To craft useful exploit code (and to achieve Turing completeness), several tricks are needed, including the use of self-modifying code.     

Investigating paper vs. screen in real-life hospital workflows: Performance contradicts perceived superiority of paper in the user experience

IntroductionAll hospitals in the province of Styria (Austria) are well equipped with sophisticated Information Technology, which provides all-encompassing on-screen patient information. Previous research made on the theoretical properties, advantages and disadvantages, of reading from paper vs. reading from a screen has resulted in the assumption that reading from a screen is slower, less accurate and more tiring. However, recent flat screen technology, especially on the basis of LCD, is of such high quality that obviously this assumption should now be challenged. As the electronic storage and presentation of information has many advantages in addition to a faster transfer and processing of the information, the usage of electronic screens in clinics should outperform the traditional hardcopy in both execution and preference ratings.This study took part in a County hospital Styria, Austria, with 111 medical professionals, working in a real-life setting. They were each asked to read original and authentic diagnosis reports, a gynecological report and an internal medical document, on both screen and paper in a randomly assigned order. Reading comprehension was measured by the Chunked Reading Test, and speed and accuracy of reading performance was quantified. In order to get a full understanding of the clinicians' preferences, subjective ratings were also collected.ResultsWilcoxon Signed Rank Tests showed no significant differences on reading performance between paper vs. screen. However, medical professionals showed a significant (90%) preference for reading from paper. Despite the high quality and the benefits of electronic media, paper still has some qualities which cannot provided electronically do date.     

From embedded sensors to sensorial materials—The road to function scale integration

Ubiquitous computing is about to become part of our everyday lives by integrating hundreds of “invisible” to us computing devices in our environment, so that they can unobtrusively and constantly assist us. This will imply more and smaller “invisible” sensors, homogeneously distributed and at the same time densely packed in host materials, responding to various stimuli and immediately delivering information. In order to reach this aim, the embedded sensors should be integrated within the host material, heading towards sensorial materials. The first step is to omit all parts that are not needed for the sensorial task and to find new solutions for a gentle integration. This is what we call function scale integration. The paper discusses sensor embedding in the human hand as an example of integration in nature, new technological applications and main challenges associated with this approach.     

基于LED的视频显示板设计

目前,所有顶尖视频显示板生产商都在使用不同色彩像素尺寸的LED视频显示模块,结构相似但又各具特色。将Maxim独特的LED视频显示技术应用于这一领域,推出了MAX6974 LED驱动器,并结合低成本、中等规模的FPGA芯片提供了一个基于LED视频显示板的参考设计。     

Platform‐independent profiling in a virtual execution environment

Virtual execution environments, such as the Java virtual machine, promote platform‐independent software development. However, when it comes to analyzing algorithm complexity and performance bottlenecks, available tools focus on platform‐specific metrics, such as the CPU time consumption on a particular system. Other drawbacks of many prevailing profiling tools are high overhead, significant measurement perturbation, as well as reduced portability of profiling tools, which are often implemented in platform‐dependent native code. This article presents a novel profiling approach, which is entirely based on program transformation techniques, in order to build a profiling data structure that provides calling‐context‐sensitive program execution statistics. We explore the use of platform‐independent profiling metrics in order to make the instrumentation entirely portable and to generate reproducible profiles. We implemented these ideas within a Java‐based profiling tool called JP. A significant novelty is that this tool achieves complete bytecode coverage by statically instrumenting the core runtime libraries and dynamically instrumenting the rest of the code. JP provides a small and flexible API to write customized profiling agents in pure Java, which are periodically activated to process the collected profiling information. Performance measurements point out that, despite the presence of dynamic instrumentation, JP causes significantly less overhead than a prevailing tool for the profiling of Java code. Copyright © 2008 John Wiley & Sons, Ltd.     

The effect of the microfluidic diodicity on the efficiency of valve-less rectification micropumps using Lattice Boltzmann Method

The efficiency of the valve-less rectification micropump depends primarily on the microfluidic diodicity (the ratio of the backward pressure drop to the forward pressure drop). In this study, different rectifying structures, including the conventional structures (nozzle/diffuser and Tesla structures), were investigated at very low Reynolds numbers (between 0.2 and 60). The rectifying structures were characterized with respect to their design, and a numerical approach was illustrated to calculate the diodicity for the rectifying structures. In this study, the microfluidic diodicity was evaluated numerically for different rectifying structures including half circle, semicircle, heart, triangle, bifurcation, nozzle/diffuser, and Tesla structures. The Lattice Boltzmann Method (LBM) was utilized as a numerical method to simulate the fluid flow in the microscale. The results suggest that at very low Reynolds number flow, rectification and multifunction micropumping may be achievable by using a number of the presented structures. The results for the conventional structures agree with the reported results.     

Polymorphic bytecode instrumentation

Bytecode instrumentation is a widely used technique to implement aspect weaving and dynamic analyses in virtual machines such as the Java virtual machine. Aspect weavers and other instrumentations are usually developed independently and combining them often requires significant engineering effort, if at all possible. In this article, we present polymorphic bytecode instrumentation(PBI), a simple but effective technique that allows dynamic dispatch amongst several, possibly independent instrumentations. PBI enables complete bytecode coverage, that is, any method with a bytecode representation can be instrumented. We illustrate further benefits of PBI with three case studies. First, we describe how PBI can be used to implement a comprehensive profiler of inter‐procedural and intra‐procedural control flow. Second, we provide an implementation of execution levels for AspectJ, which avoids infinite regression and unwanted interference between aspects. Third, we present a framework for adaptive dynamic analysis, where the analysis to be performed can be changed at runtime by the user. We assess the overhead introduced by PBI and provide thorough performance evaluations of PBI in all three case studies. We show that pure Java profilers like JP2 can, thanks to PBI, produce accurate execution profiles by covering all code, including the core Java libraries. We then demonstrate that PBI‐based execution levels are much faster than control flow pointcuts to avoid interference between aspects and that their efficient integration in a practical aspect language is possible. Finally, we report that PBI enables adaptive dynamic analysis tools that are more reactive to user inputs than existing tools that rely on dynamic aspect‐oriented programming with runtime weaving. These experiments position PBI as a widely applicable and practical approach for combining bytecode instrumentations. © 2015 The Authors. Software: Practice and Experience Published by John Wiley & Sons Ltd.     

Workload characterization of JVM languages

Originally developed with a single language in mind, the JVM is now targeted by numerous programming languages—its automatic memory management, just‐in‐time compilation, and adaptive optimizations—making it an attractive execution platform. However, the garbage collector, the just‐in‐time compiler, and other optimizations and heuristics were designed primarily with the performance of Java programs in mind. Consequently, many of the languages targeting the JVM, and especially the dynamically typed languages, are suffering from performance problems that cannot be simply solved at the JVM side. In this article, we aim to contribute to the understanding of the character of the workloads imposed on the JVM by both dynamically typed and statically typed JVM languages. To this end, we introduce a new set of dynamic metrics for workload characterization, along with an easy‐to‐use toolchain to collect the metrics. We apply the toolchain to applications written in six JVM languages (Java, Scala, Clojure, Jython, JRuby, and JavaScript) and discuss the findings. Given the recently identified importance of inlining for the performance of Scala programs, we also analyze the inlining behavior of the HotSpot JVM when executing bytecode originating from different JVM languages. As a result, we identify several traits in the non‐Java workloads that represent potential opportunities for optimization. © 2015 The Authors. Software: Practice and Experience Published by John Wiley & Sons Ltd.