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Patients with Parkinson's disease (PD) can be divided into two subtypes based on clinical features, namely tremor-dominant (TD) and postural instability and gait difficulty (PIGD). Detection of PIGD symptoms is crucial for early diagnosis of PD and timely clinical intervention. However, patients at the early stage may not exhibit obvious motor dysfunctions during normal straight walking leading to difficulties in PD identification. Researchers have found that patients would show significant motor deteriorations in turning due to their cognition limitation. Therefore, turning detection is essential for quantitative motion analysis in the gait assessment of PD patients. In this study, we proposed a novel inertial-sensor-based algorithm for turning detection. Ten healthy young participants were enrolled in the experiment where they were required to walk along a 7-meter pathway with two 180 degree turns at their comfortable walking speed. Five inertial sensors were attached to the upper trunk, the shank and the foot of both legs. The algorithm performance was validated using an optical motion capture system for reference and two sensor combination options (upper trunk and shank sensors, upper trunk and foot sensors) were compared. The results showed that the proposed algorithm achieved accuracy over 98% for identifying the turning state of both legs. The integration of the upper trunk and foot sensors had no significant effect on the detection accuracy compared to that with the use of the upper trunk and shank sensors. Our algorithm has the potential to be implemented in the motion analysis model for complicated gait tasks, which has great potential in the early diagnosis of PIGD.

The Sinkhorn divergence has become a very popular metric to compare probability distributions in optimal transport. However, most works resort to the Sinkhorn divergence in Euclidean space, which greatly blocks their applications in complex data with nonlinear structure. It is therefore of theoretical demand to empower the Sinkhorn divergence with the capability of capturing nonlinear structures. We propose a theoretical and computational framework to bridge this gap. In this paper, we extend the Sinkhorn divergence in Euclidean space to the reproducing kernel Hilbert space, which we term "Hilbert Sinkhorn divergence" (HSD). In particular, we can use kernel matrices to derive a closed form expression of the HSD that is proved to be a tractable convex optimization problem. We also prove several attractive statistical properties of the proposed HSD, i.e., strong consistency, asymptotic behavior and sample complexity. Empirically, our method yields state-of-the-art performances on image classification and topological data analysis.

Election verifiability aims to ensure that the outcome produced by electronic voting systems correctly reflects the intentions of eligible voters, even in the presence of an adversary that may corrupt various parts of the voting infrastructure. Protecting such systems from manipulation is challenging because of their distributed nature involving voters, election authorities, voting servers and voting platforms. An adversary corrupting any of these can make changes that, individually, would go unnoticed, yet in the end will affect the outcome of the election. It is, therefore, important to rigorously evaluate whether the measures prescribed by election verifiability achieve their goals. We propose a formal framework that allows such an evaluation in a systematic and automated way. We demonstrate its application to the verification of various scenarios in Helios and Belenios, two prominent internet voting systems, for which we capture features and corruption models previously outside the scope of formal verification. Relying on the Tamarin protocol prover for automation, we derive new security proofs and attacks on deployed versions of these protocols, illustrating trade-offs between usability and security.

Parameterized verification is shown to be a complicated and undecidable problem. The challenge of parameterized verification lies in how to construct appropriate invariants. Designing algorithms to find such invariants automatically has become an active research area since the last decade. With the advent of some recent works, automatically finding invariants has become possible, but most of these invariants are unreadable, making them difficult to be understood by protocol designers and researchers. Therefore, we propose an automatic framework that learns a set of readable and simple invariants to support in protocol design. It takes advantage of association rule learning, and combines the learning algorithm with parameterized verification. It is noteworthy that the gap between machine learning algorithms and parameterized verification seems to be huge, as they rely on statistical learning and symbolic reasoning, respectively. Our framework, however, builds a bridge through association rules and invariants, making their combination possible. Besides, we also propose an invariant-guided strengthening paradigm, providing an innovative perspective to existing abstraction-strengthening methods. Our framework has been successfully applied to several benchmarks, including an industrial-scale protocol FLASH.

Parameterized verification of parameterized protocols like cache coherence protocols is an important but hard problem. Our tool paraVerifier handles this hard problem in a unified framework: (1) it automatically discovers auxiliary invariants and the corresponding causal relations from a small reference instance of the verified protocol; (2) the above invariants and causal relation information are automatically generalized into a parameterized form to construct a parameterized formal proof in a theorem prover (e.g., Isabelle). Our method is successfully applied to typical benchmarks including snooping and directory cache coherence protocol benchmarks. The correctness of these protocols is guaranteed by a formal and readable proof which is automatically generated. The notoriously hard FLASH protocol, which is at an industrial scale, is also verified.

The expression of genes is a fundamental process in living cells, both eukaryotic and prokaryotic. The regulation of gene expression is achieved via sophisticated networks of interactions between DNA, RNA, proteins, and small chemical compounds. The qualitative and quantitative characterisation of interactions between genes is one of the major current research targets in systems biology. In this PhD research project, we view gene regulatory networks as Markov chains, resulting from popular formalisation frameworks such as Dynamic Bayesian Networks and Probabilistic Boolean Networks. This will allow us to reason about both the structure and strength of gene interactions. Our goal is to develop new algorithms and tools, which are tailored for the modelling and analysis of gene regulatory networks, by exploring model checking techniques that have been developed and widely used in computer science. More specifically, we will combine model checking techniques with sampling and optimisation methods from the literature to derive new techniques to solve the parameter estimation problem of Markov models of gene regulatory networks.

Through real-life experiments, it has been proved, not only in theory but also in practice, that civil signals of Global Navigation Satellite Systems (GNSS) can be spoofed. Consequently, a number of spoofing detection techniques have been proposed to verify the integrity of GNSS signals. In this paper, we develop a novel trust framework based on subjective logic to evaluate the integrity of received GNSS civil signals. We formally define signal integrity for the first time in the framework and use it to precisely characterise different spoofing detection methods. Our framework captures the uncertainty during the inference of signal integrity which has been largely ignored or not explicitly specified in the literature. Our framework also gives rise to several natural ways to combine the outputs of various spoofing detection methods on signal integrity. We validate our framework through experiments using both real and simulated signals and the results show that our framework is effective.

The International Workshop on Engineering Safety and Security Systems (ESSS 2013) aims at contributing to the challenge of constructing reliable and secure systems. The workshop covers areas such as formal specification, (extended) type checking, model checking, program analysis/transformation, model-based testing and model-driven software construction. The workshop brings together researchers and industry R&D expertise to exchange their knowledge, discuss their research findings, and explore potential collaborations. The first edition of ESSS was held in Feb 2012 in Singapore, organised by National University of Singapore. The ESSS 2013 workshop is affiliated with the 6th IEEE Conference on Software Testing, Verification and Validation (ICST 2013) in Luxembourg. The main theme of the workshop is methods and techniques for constructing large reliable and secure systems. The goal of the workshop is to establish a platform for the exchange of ideas, discussion, cross-fertilisation, inspiration, co-operation, and dissemination. The topics of the workshop include, but are not limited to

Existing Global Navigation Satellite Systems offer no authentication to the open service signals and so stand-alone receivers are vulnerable to meaconing and spoofing attacks. These attacks interfere with the integrity and authenticity of satellite signals: they can delay signals, or re-broadcast signals. Positioning is thus compromised and location-based services are at risk.This paper describes a solution to mitigate this risk. It is a trusted third-party Localisation Assurance service that informs location-based services providers up to which level a location claimed by client can be trusted. It runs several tests over the localisation data of client receivers and certifies the level of assurance of locations. An assurance level expresses the amount of trust the third-party has that a receiver's location is calculated from integral and authentic satellite signals.

The aim of this study was to check the load resistance factored design (LRFD) codes for Korean softwood species. Three representative structural timber Lazix Kaempferi, Pinus koraiensis, and Pinus densiflora, in the northeastern South Korea were selected. For evaluating the bending strength, a full-sized specimen was used. In the test results, it seemed that the KFRI grading rule was suitable for grading the three species due to the high percentage of grade 1 or 2. However, in terms of modulus of rupture, the grading rule had a problem due to the large coefficient of variation in the grade class. Moreover, in case of Pinus densiflora, it is difficult to use LRFD design values by format conversion since the reference resistance values were much lower than the values. For greater reliability, the accumulation of additional data is necessary and further studies should be performed.

Portable ultrasonic system which is named KCT-200 was developed to detect deterioration in dismantled historical wooden member in Korea. For investigating inner state of wood, an experimental study was done with sound wood. It was confirmed that velocity to find deterioration in wood was 1200 m/s from experimental study. And that result could be used to detect inner state of dismantled historical wooden member. The method to predict ration of sound wood to deteriorated wood was also suggested in this study.

This paper puts forwards a novel method of second harmonic of multi-beam laser heterodyne measurement for the thickness of the glass, which is based on the combination of Doppler effect and heterodyne technology, loaded the information of the thickness to the frequency difference of the multi-beam laser heterodyne signal by frequency modulation of the oscillating mirror, which is in the light path. Heterodyne signal frequency can be obtained by fast Fourier transform, and can obtain values of the thickness accurately after the multi-beam laser heterodyne signal demodulation. This method is used for simulate values of different thickness of the glass through numerical simulation of MATLAB and the obtained result shows that maximal relative error is less than 0.02%.

At present, the region growing algorithm has been used as a segmentation technique of digital images. Most region growing algorithms are using fixed or determinate criterions to distinguish disease spots from leaf image with gray level differences between leaf and disease spot. But in practice, the objects in the disease leaf image have fuzziness and uncertainty, and edges of the objects are unclear. What's more, the color of leaf and disease spots is uneven, and the gray level is overlapping, so it is difficult to use fixed threshold or determinate criteria to determine the uncertain objects in leaf disease spot images accurately. In order to improve the crop leaf spot disease image segmentation accuracy, an adaptive segmentation algorithm by integrating local threshold and seeded region growing (LTSRG) is proposed. The algorithm was implemented on VC6.0. The segmentation algorithm uses the pixels of which the R-channel gray level is more than the G-channel gray level as initial seed points (pixels), and then local threshold C i is calculated for each connected seed region by Otsu. New seed pixels are included and the threshold C is re-calculated until no new seed pixel can be included. The results of LTSRG are compared with the results of threshold-based Otsu and clustering -based EM. The experiments show: The adapted segmentation method is satisfactory and highly efficient to separate disease spots from normal part of corn leaves. LTSRG algorithm is easy to realize, and can improve the precision of crop disease spot segmentation. Its image segmentation results have good region consistency and high efficiency. It is an adapting algorithm for image segmentation.

We formalise in a theorem prover the notion of provable anonymity proposed by Garcia et al. Our formalization relies on inductive definitions of message distinguish ability and observational equivalence over observed traces by the intruder. Our theory differs from its original proposal which essentially boils down to the existence of a reinterpretation function. We build our theory in Isabelle/HOL to have a mechanical framework for the analysis of anonymity protocols. Its feasibility is illustrated through the onion routing protocol.

Transparency is crucial to ensuring fair, honest elections. Transparency is achieved by making information (e.g. election result) public. In e-voting literature, this publication is often described in terms of a bulletin board. While privacy of voting systems has been actively studied in recent years, resulting in various analysis frameworks, to date there has not been an explicit modelling of bulletin board in any such framework. Privacy implications of bulletin boards are thus understudied. In this paper, we extend the semantics of the framework of Jonker, Mauw and Pang to model a bulletin board and capture coercion-resistance. The usage of the extended framework is illustrated by an application to the Pret a Voter voting system. Moreover, we present an information-theoretical measure of privacy loss in elections.

Cederquist et al. proposed an optimistic certified email protocol, which employs key chains to reduce the storage requirement of the trusted third party (TTP). We extend their protocol to satisfy the property of TTP transparency, using existing verifiably encrypted signature schemes. An implementation with the scheme based on bilinear pairing makes our extension one of the most efficient certified email protocols satisfying strong fairness, timeliness, and TTP transparency.

Blended learning is becoming one of the important applications by integrating e-learning and traditional face-to-face instruction together. As an introduction to the reader challenges in hybrid learning of physical education are provided firstly. In this paper, Video Annotation Module (VAM) is presented to improve blended learning of physical education. Through the user interface of VAM, the teacher can review the student's actions video, pick out the wrong actions and add still annotations. And the student can watch annotated video to find out mistakes and get instructions. In order to control over bandwidths Geometry Primitive Language is proposed, which presents the geometry primitives in XML. The results of experiment show that 80.9% out of students think that the VAM can afford the blended learning of physical education.

Blog clustering is an important approach of web public opinion analysis. In this paper, an integrated graph-based approach for representing and clustering Chinese blogs by embedded sentiment is proposed. Graph-based representation and relevant clustering algorithm are applied. This graph-based blogs representation model considers not only sentiment words but also some structural information. Experimental results show that comparing with applying initial graph-based document representation model and vector space document representation model, the integrated graph-based document representation model has better quality in clustering Chinese blog documents.

Service composition, which provides a more effective way to combine several single services into a composite service, is a kind of software reuse techniques. However, one of the most important problems is how to perform service composition correctly and effectively so as to produce high-quality source codes for describing the resulted composite service. In this paper, we propose a model-driven method to solve this problem, where UML 2.0 sequence diagrams are extended to model the composition of web services, extended statecharts are synthesized from sequence diagrams, then the statecharts are further transferred to the input language of a model checker for behavior consistency checking, and finally verified BPEL codes can be generated from improved sequence diagrams. Case studies have been performed to demonstrate the whole process and illustrate the significance of our approach.

The population protocol model has emerged as an elegant paradigm for describing mobile ad hoc networks, consisting of a number of nodes that interact with each other to carry out a computation. One essential property of self-stabilizing population protocols is that all nodes must eventually converge to the correct output value, with respect to all possible initial configurations. It has been shown that fairness constraints play a crucial role in designing population protocols. The Process Analysis Toolkit (PAT) has been developed to perform verifications under different fairness constraints efficiently. In particular, it can handle global fairness, which is required for the correctness of most of population protocols. It is an ideal candidate for automatically verifying population protocols. In this paper, we summarize our latest empirical evaluation of PAT on a set of self-stabilizing population protocols for ring networks. We report one previously unknown bug in a protocol for leader election identified using PAT.

Many algorithms ofmemory access scheduling have been studied to attack the well-known memory-wall. However, some of them introduce unfairness problem in Chip-Multi-Processor (CMP) systems. Therefore a new approach called Fair-Priority-Expression-Based (FairPEB) burst scheduling is proposed in this paper to address both performance and unfairness problems. Experiment results show that this method improves data bus utilization of memory system by 15.4% and 31.87% over conventional First-Ready First-Come-First-Service (FR-FCFS) and original burst scheduling. Furthermore it keeps memory accesses of different applications fair.

The performance of modern computer system is greatly limited by the bandwidth of DRAM-based memory. Altering the sequence of main memory accesses can reduce observed access latency, therefore improve bus utilization. While previous reordering mechanisms consider factors related to memory access separately, this paper groups several factors together to build a priority expression for bank arbitration based on burst scheduling. The expression considers three factors: wait time of a burst, burst length, and priority of read or write accesses. To make the expression suitable for both read and write accesses, write queue in a bank is designed to buffer bursts, which are defined to be clusters of row hits, other than single write accesses. Experiment results from a modified M5 simulator running selected SPEC CPU2000 and Stream benchmarks show that the priority-expression-based burst scheduling improves the bus utilization about 74% and reduces the execution time 41% over the conventional in-order memory scheduling. It also outperforms burst scheduling 9% and 5% in bus utilization and execution time reduction respectively. The priority-expression-based burst scheduling is proved to be feasible.

The population protocol model [2] has emerged as an elegant computation paradigm for describing mobile ad hoc networks, consisting of a number of mobile nodes that interact with each other to carry out a computation. The interactions of nodes are subject to a fairness constraint. One essential property of population protocols is that all nodes must eventually converge to the correct output value (or configuration). In this paper, we aim to automatically verify self-stabilizing population protocols for leader election and token circulation in the Spin model checker [8]. We report our verification results and discuss the issue of modeling strong fairness constraints in spin.

A finite impulse compensation system is designed with charge coupled devices (CCD). The system can compensate the frequency response of various measuring device of network, such as instrument and sensor, etc. so as to extend their work frequency band. The main advantage of the design is its flexibility, the system can be easily changes in the weighting resistances of CCD, provide that the clock frequency can operate the CCD. At the end of this paper, the correctness of design principle has been verified in a simplified experimental condition, and some conclusions are introduced.

Real-Time Address Trace Compression (RTATC) is a very useful method for debugging or analyzing software programs running on a processor-based system. Address trace compression means that the instruction addresses, which are produced in the instruction-fetch stage of the microprocessor, are compressed and out putted for later reconstruction and analysis. This paper presents a kind of RTATC method which includes three phases: branch filtering, address encoding and address compressing. A synthesizable RTL code for this method is constructed and integrated with a DSP&CPU processor to analyze the compressing effect and evaluate the hardware cost. The results show that our hardware is capable of real-time compression and achieving a very high compression ratio.

This paper introduces a reconfigurable on-chip debugger (OCD) with a real-time tracer. By setting several parameters, the OCD is readily integrated with diversified microprocessor cores. Moreover, a trace unit is implemented with Lempel-Ziv compression algorithm to trace instruction address of target processor in real-time, to meet the demand of dynamic debugging. The OCD is successfully integrated with one 8 bit microcontroller and one 32 bit processor. The experiments results verify that our design is feasible.

Guttman and Javier Thayer introduced the notion of unsolicited authentication tests, and used it to prove the correctness of security protocols in which a key server authenticate its clients. As an example, they have applied unsolicited authentication tests to prove the authentication goals of the Otway-Rees protocol. However, unsolicited authentication tests seem not to be fully explored in that case study, and the proofs were complicated. In this paper, we revisit the unsolicited authentication tests, and show how to strengthen and apply them in more general cases. To justify our work, we also use this extension to prove all agents? authentication guarantee of the Otway-Rees protocol.

Peer-to-peer (P2P) networks and mobile ad hoc networks (MANET) share some key characteristics: self-organization and decentralization, and both need to solve the same fundamental problem: connectivity. We motivate a study for the convergence of the two overlay network technologies and sketch an evolving architecture towards integrating the two technologies in building overlay network applications.

A PC-based image system for measuring degree of fracture and union at lower end of radius has been developed. the system consists of three stages: preprocessing, restoration and measurement. In the first stage, histogram equalizat ion was utilized to normalize input rad i ograph and stretch contrast. A restoration algorithm was used in second stage. In measurement, the effect of soft-tissue on intensity of bone was removed, the mineral density of bone and osteotylus growth rate at fracture area were then measured. It provides the necessary information for clinic diagnos is and el iminates the subjective variations from the instability of human visual judgment.