On finite time stability with guaranteed cost control of uncertain linear systems

summary:This paper deals with the design of a robust state feedback control law for a class of uncertain linear time varying systems. Uncertainties are assumed to be time varying, in one-block norm bounded form. The proposed state feedback control law guarantees finite time stability and satisfies a given bound for an integral quadratic cost function. The contribution of this paper is to provide a sufficient condition in terms of differential linear matrix inequalities for the existence and the construction of the proposed robust control law. In particular, the construction of the feedback control law is brought back to a feasibility problem which can be solved inside the convex optimization framework. The effectiveness of the proposed approach is shown by means of the results obtained on a numerical and a physical example

Biological Monitoring of Blood Naphthalene Levels as a Marker of Occupational Exposure to PAHs among Auto-Mechanics and Spray Painters in Rawalpindi

<p>Abstract</p> <p>Background</p> <p>Routine exposure to chemical contaminants in workplace is a cause for concern over potential health risks to workers. In Pakistan, reports on occupational exposure and related health risks are almost non-existent, which reflects the scarce availability of survey data and criteria for determining whether an unsafe exposure has occurred. The current study was designed to evaluate blood naphthalene (NAPH) levels as an indicator of exposure to polycyclic aromatic hydrocarbons (PAHs) among automobile workshop mechanics (MCs) and car-spray painters (PNs). We further determined the relationship between blood NAPH levels and personal behavioural, job related parameters and various environmental factors that may further be associated with elevated risks of occupational exposures to PAHs.</p> <p>Methods</p> <p>Sixty blood samples (n = 20 for each group i.e. MC, PN and control group) were collected to compare their blood NAPH levels among exposed (MCs and PNs) and un-exposed (control) groups. Samples were analyzed using high pressure liquid chromatography (HPLC). Data regarding demographic aspects of the subjects and their socioeconomic features were collected using a questionnaire. Subjects were also asked to report environmental hygiene conditions of their occupational environment.</p> <p>Results</p> <p>We identified automobile work areas as potential sites for PAHs exposure, which was reflected by higher blood NAPH levels among MCs. Blood NAPH levels ranged from 53.7 to 1980.6 μgL^-1and 54.1 to 892.9 μgL^-1among MCs and PNs respectively. Comparison within each group showed that smoking enhanced exposure risks several fold and both active and passive smoking were among personal parameters that were significantly correlated with log-transformed blood NAPH levels. For exposed groups, work hours and work experience were job related parameters that showed strong associations with the increase in blood NAPH levels. Poor workplace hygiene and ventilation were recognized as most significant predictors related to differences among workplaces that may enhance the extent of exposure to chemical contaminants.</p> <p>Conclusions</p> <p>It appeared that chemical exposure at the workplace may be influenced by multiple environmental factors, but poor workplace hygiene and duration of exposure (long work hours) were the most important factors. Smoking and negligence of workers regarding self protection were among some of the important personal behaviours than can be addressed with better training. There is also a need to improve workplaces hygiene and to rationalize work hours to minimize health risks. Since smoking was an important confounding factor that supplemented most of the actual occupational exposure, a study based on non-smoker subjects is needed to separate out the effects of smoking and other confounding factors that may obscure measurements of actual extent of occupational exposure.</p

R2S100K: Road-Region Segmentation Dataset For Semi-Supervised Autonomous Driving in the Wild

Semantic understanding of roadways is a key enabling factor for safe autonomous driving. However, existing autonomous driving datasets provide well-structured urban roads while ignoring unstructured roadways containing distress, potholes, water puddles, and various kinds of road patches i.e., earthen, gravel etc. To this end, we introduce Road Region Segmentation dataset (R2S100K) -- a large-scale dataset and benchmark for training and evaluation of road segmentation in aforementioned challenging unstructured roadways. R2S100K comprises 100K images extracted from a large and diverse set of video sequences covering more than 1000 KM of roadways. Out of these 100K privacy respecting images, 14,000 images have fine pixel-labeling of road regions, with 86,000 unlabeled images that can be leveraged through semi-supervised learning methods. Alongside, we present an Efficient Data Sampling (EDS) based self-training framework to improve learning by leveraging unlabeled data. Our experimental results demonstrate that the proposed method significantly improves learning methods in generalizability and reduces the labeling cost for semantic segmentation tasks. Our benchmark will be publicly available to facilitate future research at https://r2s100k.github.io/

The genetics associated with Primary Congenital Glaucoma

Glaucoma is a progressive optic neuropathy; increased intraocular pressure (IOP) is a modifiable risk factor for primary congenital glaucoma (PCG). Increase IOP causes retinal and optic nerve compression and leads to gradual and irreversible loss of eyesight if left untreated. It is the second most leading cause of blindness. PCG mainly affects children up to the age of three years, and symptoms include epiphora, photalgia, swollen eyes, opaque corneas, blepharospasm, rupture in the retina and ocular nerve damage due to IOP. Early detection, management, and treatment are the keys to preventing vision loss from glaucoma. Many mutations have been discovered in Cytochrome P450 1B1 (CYP1B1) gene to be responsible for causing PCG, and there are still a lot of mutations to be discovered. In this review, we will discuss the genetic aspects of PCG and the most frequent mutations responsible for PCG in Pakistani children. PCG can be handled by decreasing IOP either by medication or by surgery. Genetic counselling plays a significant role in the establishment of proper management of PCG.Keywords: Primary Congenital Glaucoma; IOP; Cyp1b1; Mutation

Towards secure private and trustworthy human-centric embedded machine learning: An emotion-aware facial recognition case study

The use of artificial intelligence (AI) at the edge is transforming every aspect of the lives of human beings from scheduling daily activities to personalized shopping recommendations. Since the success of AI is to be measured ultimately in terms of how it benefits human beings, and that the data driving the deep learning-based edge AI algorithms are intricately and intimately tied to humans, it is important to look at these AI technologies through a human-centric lens. However, despite the significant impact of AI design on human interests, the security and trustworthiness of edge AI applications are not foolproof and ethicalneither foolproof nor ethical; Moreover, social norms are often ignored duringin the design, implementation, and deployment of edge AI systems. In this paper, we make the following two contributions: Firstly, we analyze the application of edge AI through a human-centric perspective. More specifically, we present a pipeline to develop human-centric embedded machine learning (HC-EML) applications leveraging a generic human-centric AI (HCAI) framework. Alongside, we also analyzediscuss the privacy, trustworthiness, robustness, and security aspects of HC-EML applications with an insider look at their challenges and possible solutions along the way. Secondly, to illustrate the gravity of these issues, we present a case study on the task of human facial emotion recognition (FER) based on AffectNet dataset, where we analyze the effects of widely used input quantization on the security, robustness, fairness, and trustworthiness of an EML model. We find that input quantization partially degrades the efficacy of adversarial and backdoor attacks at the cost of a slight decrease in accuracy over clean inputs. By analyzing the explanations generated by SHAP, we identify that the decision of a FER model is largely influenced by features such as eyes, alar crease, lips, and jaws. Additionally, we note that input quantization is notably biased against the dark skin faces, and hypothesize that low-contrast features of dark skin faces may be responsible for the observed trends. We conclude with precautionary remarks and guidelines for future researchers. 2022 The Author(s)This publication was made possible by NPRP grant # [13S-0206-200273] from the Qatar National Research Fund (a member of Qatar Foundation). Open Access funding provided by the Qatar National Library The statements made herein are solely the responsibility of the authors.Scopu

Application of value stream mapping (VSM) in gear manufacturing process: A case study

Since the end of 20th century, Lean Manufacturing has been recognized as an important approach in competitive industrial environments to improving productivity by reducing process cycle time. To remain competitive in the market, organizations are compelled to find new domains for improvements in order to reduce production lead time and to smooth the flow of processes. The current research aims at designing efficient future VSM to improve productivity by reducing process cycle time and waste in a gear manufacturing process in an automotive industry. The approach was based on mapping the current state of the process to identify the non-value-added activities and also for opportunities for improvement in value added activities. Kaizen events are the main metrics for improvement in the current process by integrating it with the future value stream map. This study concluded that the designed future value stream map helps effectively in identifying the wasteful activities i.e. distance travelled and inventory at different workstations. VSM integrated with Kaizen proves itself a useful approach in achieving continuous process improvement

The Role Of EI In Effective Leadership, In The Context Of Saudi Arab: A Systematic Review

Background: The field of Emotional Intelligence (EI) is a growing field reflecting its effectiveness in different professions and institutes. There is little evidence available to seek a comprehensive role of EI in effective leadership. This study explores the role of EI in effective leadership. Aim: The aim of this study is to investigate how the component of EI plays an effective role in leadership, in the context of Saudi Arab. Method: For the purpose, a systematic approach was employed to identify and select relevant studies from key databases. Inclusion and exclusion criteria ensured the consideration of studies published within 05 years that examined the role of EI for effective leadership. Data extraction and analysis were conducted to synthesize findings from 11 selected studies. Results: In total 130 articles were explored and only 03 were found very relevant and 28 somewhat relevant based on inclusion criteria. Findings revealed that EI play a key role in any field specifically in effective leadership and leadership skills including empathy, self-management, and self-awareness. However, limitations including selection bias were acknowledged. Conclusion: The study concludes that EI can enhance the leadership role and can bring very significant advancement in the field of leadership. Since, there was no studies found that studied exclusively EI in relation with effective leadership

On finite time stability with guaranteed cost control of uncertain linear systems

summary:This paper deals with the design of a robust state feedback control law for a class of uncertain linear time varying systems. Uncertainties are assumed to be time varying, in one-block norm bounded form. The proposed state feedback control law guarantees finite time stability and satisfies a given bound for an integral quadratic cost function. The contribution of this paper is to provide a sufficient condition in terms of differential linear matrix inequalities for the existence and the construction of the proposed robust control law. In particular, the construction of the feedback control law is brought back to a feasibility problem which can be solved inside the convex optimization framework. The effectiveness of the proposed approach is shown by means of the results obtained on a numerical and a physical example

Remote Fault-Tolerant Control for Industrial Smart Surveillance System

We design a remote fault-tolerant control for an industrial surveillance system. The designed controller simultaneously tolerates the effects of local faults of a node, the propagated undesired effects of neighboring connected nodes, and the effects of network-induced uncertainties from a remote location. The uncertain network-induced time delays of communication links from the sensor to the controller and from the controller to the actuator are modeled using two separate Markov chains and packet dropouts using the Bernoulli process. Based on linear matrix inequalities, we derive sufficient conditions for output feedback-based control law, such that the controller does not directly depend on output, for stochastic stability of the system. The simulation study shows the effectiveness of the proposed approach