Late Corneal Thinning and Keratitis following Mitomycin-C use in Pterygium Surgery

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Classification of Different Shoulder Girdle Motions for Prosthesis Control Using a Time-Domain Feature Extraction Technique

Abstract—The upper limb amputation exerts a significant burden on the amputee, limiting their ability to perform everyday activities, and degrading their quality of life. Amputee patients’ 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) host‐response 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 cross‐talk 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. Cross‐talk 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