Temporal Reasoning About Robotics Applications: Refinement and Temporal Logic

The challenges of verifying the behaviour of robotics systems has motivated the development of various techniques and tools for supporting the advancement and verification of robotics systems. This is due to the complex nature of verifying robotics systems as part of the category of hybrid dynamical systems that combine discrete and continuous parts. In contrast to the commonly-known computer systems, robotic sys- tems operate in a physical, real-world environment that may include humans, which raises a reasonable question of concern about the safety of the systems. Currently, one of the promising solutions is effective, rigorous verification techniques and tools that verify and guarantee the safe operation of robotics systems. Along this line, formal methods provide mathematical models that support the de- velopment of rigorous verification techniques and tools. In this work, we use formal methods for the verification of temporal specifications of robotics systems. The process algebra tock-CSP provides textual notations for modelling discrete-time behaviours, with the support of various tools for verification. Also, tock-CSP has been used to give semantics to a domain-specific language for robotics, RoboChart. Similarly, automatic verification of Timed Automata (TA) is supported by the real-time verification toolbox Uppaal that facilitates verification of temporal specifications using Time Computation Tree Logic (TCTL). Timed Automata and tock-CSP differ in both modelling and verification approaches. For instance, liveness requirements are difficult to specify with the constructs of tock-CSP, but they are easy to verify in Uppaal. In this work, we add a step forward in translating tock-CSP into TA to take advantage of Uppaal. We have developed a translation technique and tool; our work uses rules for translating tock-CSP into a network of small TAs, which address the complexity of capturing the compositionality of tock-CSP. For the validation of our proposed con- tributions, we use an experimental approach based on finite approximations to trace sets. We consider trace semantics for validating the translation technique. Thus, we develop a technique for generating and comparing traces of tock-CSP and TA. In order to evaluate the translation technique and its corresponding tool, we use two forms of test cases: a large collection of small processes and case studies from the literature. We illustrate a plan for using mathematical proof to establish the correctness of the rules that will cover an infinite set of traces

Vulnerability prediction for secure healthcare supply chain service delivery

Healthcare organisations are constantly facing sophisticated cyberattacks due to the sensitivity and criticality of patient health care information and wide connectivity of medical devices. Such attacks can pose potential disruptions to critical services delivery. There are number of existing works that focus on using Machine Learning (ML) models for predicting vulnerability and exploitation but most of these works focused on parameterized values to predict severity and exploitability. This paper proposes a novel method that uses ontology axioms to define essential concepts related to the overall healthcare ecosystem and to ensure semantic consistency checking among such concepts. The application of ontology enables the formal specification and description of healthcare ecosystem and the key elements used in vulnerability assessment as a set of concepts. Such specification also strengthens the relationships that exist between healthcare-based and vulnerability assessment concepts, in addition to semantic definition and reasoning of the concepts. Our work also makes use of Machine Learning techniques to predict possible security vulnerabilities in health care supply chain services. The paper demonstrates the applicability of our work by using vulnerability datasets to predict the exploitation. The results show that the conceptualization of healthcare sector cybersecurity using an ontological approach provides mechanisms to better understand the correlation between the healthcare sector and the security domain, while the ML algorithms increase the accuracy of the vulnerability exploitability prediction. Our result shows that using Linear Regression, Decision Tree and Random Forest provided a reasonable result for predicting vulnerability exploitability

Laboratory-confirmed hospital-acquired infections:An analysis of a hospital's surveillance data in Nigeria

Objective: Hospital-acquired infections (HAI) are a global problem and a major public health concern in hospitals throughout the world. Quantification of HAI is needed in developing countries; hence we describe the results of a 2-year surveillance data in a tertiary hospital in Nigeria. Methodology: This study is a 2-year review using secondary data collected at a tertiary referral center in northwestern Nigeria. The data was collected using surveillance forms modeled based on the Centre for Disease Control (CDC) protocol. Descriptive statistics were used to present results as frequencies and percentages. Result: 518 patients developed HAI out of 8216 patients giving an overall prevalence of 6.3%. The mean age of the patients was 35.98 years (±15.92). Males constituted 281 (54.2%). UTI 223 (43.1%) was the most prevalent HAI. Overall, E. coli 207 (40.0%) was the most frequent isolates followed by P. aerugenosa 80 (15.4%). There was a high prevalence of cloxacillin resistant S. aureus (67.9%) and gram-negative rods resistant to third-generation cephalosporins. Trimethoprim-sulfamethoxazole resistance across the board was more than 90%. Conclusion: There is a high burden of HAI especially UTI in our hospital with resistance to commonly used antibiotics documented. Keywords: Public health, Infectious diseas

Fall Detection System with Accelerometer and Threshold-based Algorithm

Most presently available fall detection systems that are marketed for commercial use predominantly consist of wearable technologies. These technologies often involve a device positioned on the wrist, which may lead to the occurrence of false positive alerts due to the movements of the wrist. This paper proposed a fall detection system that aims to improve both reliability and cost-effectiveness. The system is designed to promptly inform surrounding individuals of their need for assistance in emergency situations. The fall detection system we propose consists of an accelerometer and a gyroscope, which collectively calculate acceleration, orientation, and various other motion characteristics. The resulting system demonstrated a sensitivity of 90%, a specificity of 85%, and an accuracy of 87.5%