251 research outputs found
Classification of Different Shoulder Girdle Motions for Prosthesis Control Using a Time-Domain Feature Extraction Technique
AbstractâThe upper limb amputation exerts a significant burden on the amputee, limiting their ability to perform everyday activities, and degrading their quality of life. Amputee patientsâ quality of life can be improved if they have natural control over their prosthetic hands. Among the biological signals, most commonly used to predict upper limb motor intentions, surface electromyography (sEMG), and axial acceleration sensor signals are essential components of shoulder-level upper limb prosthetic hand control systems. In this work, a pattern recognition system is proposed to create a plan for categorizing high-level upper limb prostheses in seven various types of shoulder girdle motions. Thus, combining seven feature groups, which are root mean square, four-order autoregressive, wavelength, slope sign change, zero crossing (ZC), mean absolute value, and cardinality. In this article, the time-domain features were first extracted from the EMG and acceleration signals. Then, the spectral regression (SR) and principal component analysis dimensionality reduction methods are employed to identify the most salient features, which are then passed to the linear discriminant analysis (LDA) classifier. EMG and axial acceleration signal datasets from six intact-limbed and four amputee participants exhibited an average classification error of 15.68 % based on SR dimensionality reduction using the LDA classifier
Impact of web 2.0 and cloud computing platform on software engineering
Abstract-Current era of Web 2.0 is enabling new business models for using the semantic web. One such business model is leasing out computing platform of hardware and software over the internet to the tenants and is dubbed as Cloud Computing. The anticipated future trend of computing is believed to be this cloud computing as it promises a lot of benefits like no capital expenditure, speed of application deployment, shorter time to market, lower cost of operation and easier maintenance for the tenants. This paper analyses how cloud computing on the background of Web 2.0 is going to impact the software engineering process to develop quality software. As the cloud provider is an external entity or third party, how difficult will be the interaction with them? How to separate the roles of SW engineers and cloud providers? SW engineering should include framework activities to leverage all the benefits of cloud computing systematically and strategically. This paper extends the traditional agile process model named Extreme Programming (XP) and integrates interaction with the cloud provider to facilitate acceptance of cloud computing
Students' Perceived Image of the University before entering and during study
The study goals were to investigate what images have the high school and the university students about university, before entering and during study. A tool was developed consisting of (54) items. Face validity, Cronbach alpha coefficient, ANOVA, and Scheffe post-hoc tests were computed. Results show that university image mean is high among high school and university students, but the high school students' image is higher than that of the university students, and the university students' image during study is lower than theirs when they were in high school. All these differences are statistically significant. Keywords: perceived image, university climate, service quality
An Analytical Framework for Control Synthesis of Cyber-Physical Systems with Safety Guarantee
Cyber-physical systems (CPS) are required to operate safely under fault and
malicious attacks. The simplex architecture and the recently proposed cyber
resilient architectures, e.g., Byzantine fault tolerant++ (BFT++), provide
safety for CPS under faults and malicious cyber attacks, respectively. However,
these existing architectures make use of different timing parameters and
implementations to provide safety, and are seemingly unrelated. In this paper,
we propose an analytical framework to represent the simplex, BFT++ and other
practical cyber resilient architectures (CRAs). We construct a hybrid system
that models CPS adopting any of these architectures. We derive sufficient
conditions via our proposed framework under which a control policy is
guaranteed to be safe. We present an algorithm to synthesize the control
policy. We validate the proposed framework using a case study on lateral
control of a Boeing 747, and demonstrate that our proposed approach ensures
safety of the system
A Compositional Approach to Safety-Critical Resilient Control for Systems with Coupled Dynamics
Complex, interconnected Cyber-physical Systems (CPS) are increasingly common
in applications including smart grids and transportation. Ensuring safety of
interconnected systems whose dynamics are coupled is challenging because the
effects of faults and attacks in one sub-system can propagate to other
sub-systems and lead to safety violations. In this paper, we study the problem
of safety-critical control for CPS with coupled dynamics when some sub-systems
are subject to failure or attack. We first propose resilient-safety indices
(RSIs) for the faulty or compromised sub-systems that bound the worst-case
impacts of faulty or compromised sub-systems on a set of specified safety
constraints. By incorporating the RSIs, we provide a sufficient condition for
the synthesis of control policies in each failure- and attack- free
sub-systems. The synthesized control policies compensate for the impacts of the
faulty or compromised sub-systems to guarantee safety. We formulate
sum-of-square optimization programs to compute the RSIs and the safety-ensuring
control policies. We present a case study that applies our proposed approach on
the temperature regulation of three coupled rooms. The case study demonstrates
that control policies obtained using our algorithm guarantee system's safety
constraints
A Compositional Resilience Index for Computationally Efficient Safety Analysis of Interconnected Systems
Interconnected systems such as power systems and chemical processes are often
required to satisfy safety properties in the presence of faults and attacks.
Verifying safety of these systems, however, is computationally challenging due
to nonlinear dynamics, high dimensionality, and combinatorial number of
possible faults and attacks that can be incurred by the subsystems
interconnected within the network. In this paper, we develop a compositional
resilience index to verify safety properties of interconnected systems under
faults and attacks. The resilience index is a tuple serving the following two
purposes. First, it quantifies how a safety property is impacted when a
subsystem is compromised by faults and attacks. Second, the resilience index
characterizes the needed behavior of a subsystem during normal operations to
ensure safety violations will not occur when future adverse events occur. We
develop a set of sufficient conditions on the dynamics of each subsystem to
satisfy its safety constraint, and leverage these conditions to formulate an
optimization program to compute the resilience index. When multiple subsystems
are interconnected and their resilience indices are given, we show that the
safety constraints of the interconnected system can be efficiently verified by
solving a system of linear inequalities. We demonstrate our developed
resilience index using a numerical case study on chemical reactors connected in
series
Cross-Talk Between Clinical and Host-Response Parameters of Periodontitis in Smokers
Background and Objective
Periodontal diseases are a major public health concern leading to tooth loss and have also been shown to be associated with several chronic systemic diseases. Smoking is a major risk factor for the development of numerous systemic diseases, as well as periodontitis. While it is clear that smokers have a significantly enhanced risk for developing periodontitis leading to tooth loss, the population varies regarding susceptibility to disease associated with smoking. This investigation focused on identifying differences in four broad sets of variables, consisting of: (i) hostâresponse molecules; (ii) periodontal clinical parameters; (iii) antibody responses to periodontal pathogens and oral commensal bacteria; and (iv) other variables of interest, in a population of smokers with (n = 171) and without (n = 117) periodontitis.
Material and Methods
Bayesian network structured learning (BNSL) techniques were used to investigate potential associations and crossâtalk between the four broad sets of variables.
Results
BNSL revealed two broad communities with markedly different topology between the populations of smokers, with and without periodontitis. Confidence of the edges in the resulting network also showed marked variations within and between the periodontitis and nonperiodontitis groups.
Conclusion
The results presented validated known associations and discovered new ones with minimal precedence that may warrant further investigation and novel hypothesis generation. Crossâtalk between the clinical variables and antibody profiles of bacteria were especially pronounced in the case of periodontitis and were mediated by the antibody response profile to Porphyromonas gingivalis
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