Multilayer Architecture for Fault Diagnosis of Embedded Systems

This work presents a multilayer architecture for fault diagnosis in embedded systems based on formal modeling of Discrete Event Systems (DES). Most works on diagnosis of DES focus in faults of actuators, which are the devices subject to intensive wear in industry. However, embedded systems are commonly subject to cost reduction, which may increase the probability of faults in the electronic hardware. Further, software faults are hard to track and fix, and the common solution is to replace the whole electronic board. We propose a modeling approach which includes the isolation of the source of the fault in the model, regarding three layers of embedded systems: software, hardware, and sensors & actuators. The proposed method is applied to a home appliance refrigerator and after exhaustive practical tests with forced fault occurrences, all faults were diagnosed, precisely identifying the layer and the faulty component. The solution was then incorporated into the product manufactured in industrial scale.

Stabilization of a class of underactuated Euler Lagrange system using an approximate model

The energy shaping method, Controlled Lagrangian, is a well-known approach to stabilize the underactuated Euler Lagrange (EL) systems. In this approach, to construct a control rule, some nonlinear and nonhomogeneous partial differential equations (PDEs), which are called matching conditions, must be solved. In this paper, a method is proposed to obtain an approximate solution of these matching conditions for a class of underactuated EL systems. To develop this method, the potential energy matching condition is transformed to a set of linear PDEs using an approximation of inertia matrices. Hence, the assignable potential energy function and the controlled inertia matrix both are constructed as a common solution of these PDEs. Subsequently, the gyroscopic and dissipative forces are determined as the solution for kinetic energy matching condition. Conclusively, the control rule is constructed by adding energy shaping rule and additional dissipation injection to provide asymptotic stability. The stability analysis of the closed-loop system which used the control rule derived with the proposed method is also provided. To demonstrate the success of the proposed method, the stability problem of the inverted pendulum on a cart is considered.

An Inertial Iterative Algorithm to Find Common Solution of a Split Generalized Equilibrium and a Variational Inequality Problem in Hilbert Spaces

In this paper, we introduce and study an iterative algorithm via inertial and viscosity techniques to find a common solution of a split generalized equilibrium and a variational inequality problem in Hilbert spaces. Further, we prove that the sequence generated by the proposed theorem converges strongly to the common solution of our problem. Furthermore, we list some consequences of our established algorithm. Finally, we construct a numerical example to demonstrate the applicability of the theorem. We emphasize that the result accounted in the manuscript unifies and extends various results in this field of study.

A stochastic approach to handle resource constraints as knapsack problems in ensemble pruning

Ensemble-based methods are highly popular approaches that increase the accuracy of a decision by aggregating the opinions of individual voters. The common point is to maximize accuracy; however, a natural limitation occurs if incremental costs are also assigned to the individual voters. Consequently, we investigate creating ensembles under an additional constraint on the total cost of the members. This task can be formulated as a knapsack problem, where the energy is the ensemble accuracy formed by some aggregation rules. However, the generally applied aggregation rules lead to a nonseparable energy function, which takes the common solution tools—such as dynamic programming—out of action. We introduce a novel stochastic approach that considers the energy as the joint probability function of the member accuracies. This type of knowledge can be efficiently incorporated in a stochastic search process as a stopping rule, since we have the information on the expected accuracy or, alternatively, the probability of finding more accurate ensembles. Experimental analyses of the created ensembles of pattern classifiers and object detectors confirm the efficiency of our approach over other pruning ones. Moreover, we propose a novel stochastic search method that better fits the energy, which can be incorporated in other stochastic strategies as well.

The Non-Tightness of a Convex Relaxation to Rotation Recovery

We study the Perspective-n-Point (PNP) problem, which is fundamental in 3D vision, for the recovery of camera translation and rotation. A common solution applies polynomial sum-of-squares (SOS) relaxation techniques via semidefinite programming. Our main result is that the polynomials which should be optimized can be non-negative but not SOS, hence the resulting convex relaxation is not tight; specifically, we present an example of real-life configurations for which the convex relaxation in the Lasserre Hierarchy fails, in both the second and third levels. In addition to the theoretical contribution, the conclusion for practitioners is that this commonly-used approach can fail; our experiments suggest that using higher levels of the Lasserre Hierarchy reduces the probability of failure. The methods we use are mostly drawn from the area of polynomial optimization and convex relaxation; we also use some results from real algebraic geometry, as well as Matlab optimization packages for PNP.

A co-design study to develop supportive interventions to improve psychological and social adaptation among adults with new-onset type 1 diabetes in Denmark and the UK

ObjectiveTo develop supportive interventions for adults with new-onset type 1 diabetes (T1D) to facilitate positive adaptive strategies during their transition into a life with diabetes.DesignThe study used a co-design approach informed by Design Thinking to stimulate participants’ reflections on their experiences of current care and generate ideas for new supportive interventions. Visual illustrations were used to depict support needs and challenges. Initial discussions of these needs and challenges were facilitated by researchers and people with diabetes in workshops. Data comprising transcribed audio recordings of the workshop discussions and materials generated during the workshops were analysed thematically.SettingsSpecialised diabetes centres in Denmark and the United Kingdom.ParticipantsAdults with new-onset T1D (n=24) and healthcare professionals (HCPs) (n=56) participated in six parallel workshops followed by four joint workshops with adults (n=29) and HCPs (n=24) together.ResultsThe common solution prioritised by both adults with new-onset T1D and HCP participants was the development of an integrated model of care addressing the psychological and social elements of the diagnosis, alongside information on diabetes self-management. Participants also indicated a need to develop the organisation, provision and content of care, along with the skills HCPs need to optimally deliver that care. The co-designed interventions included three visual conversation tools that could be used flexibly in the care of adults with new-onset T1D to support physical, psychological and social adaptation to T1D.ConclusionThis co-design study has identified the care priorities for adults who develop T1D, along with some practical conversational tools that may help guide HCPs in attending to the disruptive experience of the diagnosis and support adults in adjusting into a life with diabetes.

E-learning virtual meeting applications: A comparative study from a cybersecurity perspective

During the coronavirus disease 2019 (COVID-19) pandemic outbreak, the lockdown of all activities including schools and universities became a normal habit, forcing educational institutes to find new ways to ensure the continuity of the learning process. E-learning is considered the best choice at this stage whereas using video conferencing or virtual meeting applications (VM) apps is the most common solution. In this research, security issues and possible cyber-attacks that may occur due to the use of the most popular VM apps used by educational institutes (i.e., Zoom, Microsoft Teams, and Google meet) are discussed. Moreover, the security features of these applications are briefly explained. Furthermore, a comprehensive comparison from a cybersecurity perspective between VM apps was made. The results show that Google Meet was the most secure against cyber-attacks, followed by the Microsoft Teams and finally the Zoom app.

Degradation of lignocelluloses in straw using AC-1, a thermophilic composite microbial system

In composting, the degradation of lignocellulose in straw is problematic due to its complex structures such as lignin. A common solution to this problem is the addition of exogenous inoculants. AC-1, a stable thermophilic microbial composite, was isolated from high temperature compost samples that can decompose lignocellulose at 50–70 °C. AC-1 had a best degradation efficiency of rice straw at 60 °C (78.92%), of hemicellulose, cellulose and lignin were 82.49%, 97.20% and 20.12%, respectively. It showed degrad-ability on both simple (filter paper, absorbent cotton) and complex (rice straw) cellulose materials. It produced acetic and formic acid during decomposition process and the pH had a trend of first downward then upward. High throughput sequencing revealed the main bacterial components of AC-1 were Tepidimicrobium, Haloplasma, norank-f-Limnochordaceae, Ruminiclostridium and Rhodothermus which provides major theoretical basis for further application of AC-1.