Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

Exploring foundations for using simulations in IS research

Simulation has been adopted in many disciplines as a means for understanding the behavior of a system by imitating it through an artificial object that exhibits a nearly identical behavior. Although simulation approaches have been widely adopted for theory building in disciplines such as engineering, computer science, management, and social sciences, their potential in the IS field is often overlooked. The aim of this paper is to understand how different simulation approaches are used in IS research, thereby providing insights and methodological recommendations for future studies. A literature review of simulation studies published in top-tier IS journals leads to the definition of three classes of simulations, namely the self-organizing, the elementary, and the situated. A set of stylized facts is identified for characterizing the ways in which the premise, the inference, and the contribution are presented in IS simulation studies. As a result, this study provides guidance to future simulation researchers in designing and presenting findings

Final Report: Informal Worker Organizing as a Strategy for Improving Subcontracted Work in the Textile and Apparel Industries of Brazil, South Africa, India and China

[Excerpt] Recent tragedies in Bangladesh and Pakistan have led to greater public attention on the garment and textile industry. Hence, this study is timely and provides insights into the current working conditions, organizing efforts, and the changing organization and structure of the industry in question. Our central question in this study is the extent to which worker organization can improve monitoring and enforcement of labor standards in subcontracted and home-based work in the garment and textile sectors in Brazil, China, India, and South Africa. Existing research literature suggests that in at least some cases of informalized and casualized work, formation and mobilization of worker organizations can do much in this regard. The research has particularly pointed to the importance of innovative and alternative forms of organization that depart from standard trade union models—in line with the departure of whole sections of the world of work from standard forms of work organization. While suggestive, this literature has been dominated by cases of a single organization in a single country, or in some cases convenience samples of organizations from one or a range of countries. This report thus makes two distinctive contributions. First, it spotlights a set of specific sector-country combinations that have received limited attention at best in previous research. Second, it assembles a systematic comparison of organizing activities in a single sector (apparel and textile) across four countries with very different economies, institutional structures, and histories. This comparison points to some possibilities for generalization to a broader range of countries. At the same time, the study design, itself centered on case studies, builds in important limitations. The four countries in question range in size from large to very large, including the two largest countries in the world by population, China and India. The garment and textile sector, as the conjunction “and” signals, combines a variety of economic units and activities ranging from huge, highly automated textile mills producing standardized outputs to individual home-based seamstresses carrying out custom work. Narrowing the focus to subcontracted and home-based work limits this variety somewhat, but as we will see in all four countries, given the current pervasiveness of subcontracting in this industry, it is not a major narrowing. At the same time, the case study nature of the research, and its limited scale and duration, necessitates a focus on a small number of organizations in countries where organization is relatively advanced (India and South Africa), or on a single productive region in countries where organizations are still at an early, experimental stage (China and Brazil, though in the latter case we were able to supplement the in-depth regional study with a look at organization in a different region as well). The organizations and regions are chosen because of their importance as distinctive examples, and because in their entirety or in key aspects they have remained understudied in previous research. The resulting cases are valuable in their own right, but degree of generalizability across the full clothing and textile sector and the full countries in question is unknown

Trauma Training in Educational Settings: Developing a Universal Approach Training Manual

Children who have experienced trauma(s) may display a wide variety of symptoms, including withdrawal, behavioral challenges, difficulty with focus, learning disabilities, and social/emotional delays (Cole et al., 2005). Each of these challenges can present a barrier to learning. Therefore, in order to provide the highest quality support in the school setting, teachers and other school staff need to be educated and trained on the topic of trauma. Further, they need strategies and tools regarding how to best work with all of their students, including those who have, or may have, experienced trauma. The current study examined the available research, as well as a pilot program, in order to develop the Trauma-Informed Practices in Schools (TIPS) program manual for educators. Outcomes of the study included a program manual and supplemental materials needed to implement the program. Initial comments from reviewers, future directives, and limitations are also discussed

The University of Maine Historic Preservation Master Plan

Historic Preservation Plan for the University of Maine. The plan represents the efforts of University of Maine personnel, including administrators, Facilities Management staff, faculty and students; and consulting architects, historians, and landscape architects, working closely with the CPC (and through representation on the CPC, the CBAC) and the MHPC. The University’s Board of Visitors periodically reviewed the work of the planning team and offered enthusiastic support. The goals of the Historic Preservation Master Plan are to:• identify and document historic resources of the core campus of the University of Maine;• identify more recent buildings and landscapes of the University of Maine that have acquired or are expected to acquire significance in the future;• determine and document existing conditions of these resources;• recommend appropriate preservation treatmentsand uses for these resources;• publicize and protect these resources through designation under institutional, local, state and federal historic preservation processes;• put in place University policies and procedures that will assure adequate protection, maintenance, and appropriate use of these resources;• use University resources to educate the University community about the importance and value of campus historic resources;• protect the historic resources of the University in order to maintain strong ties between the institution and its alumni family; and• provide campus planners with specific and practical information to assist them with the day-to-day management of the physical plant and with long-range development decisions

Spartan Daily, September 9, 1985

Volume 85, Issue 7https://scholarworks.sjsu.edu/spartandaily/7328/thumbnail.jp

Methods and techniques for analyzing human factors facets on drivers

Mención Internacional en el título de doctorWith millions of cars moving daily, driving is the most performed activity worldwide. Unfortunately, according to the World Health Organization (WHO), every year, around 1.35 million people worldwide die from road traffic accidents and, in addition, between 20 and 50 million people are injured, placing road traffic accidents as the second leading cause of death among people between the ages of 5 and 29. According to WHO, human errors, such as speeding, driving under the influence of drugs, fatigue, or distractions at the wheel, are the underlying cause of most road accidents. Global reports on road safety such as "Road safety in the European Union. Trends, statistics, and main challenges" prepared by the European Commission in 2018 presented a statistical analysis that related road accident mortality rates and periods segmented by hours and days of the week. This report revealed that the highest incidence of mortality occurs regularly in the afternoons during working days, coinciding with the period when the volume of traffic increases and when any human error is much more likely to cause a traffic accident. Accordingly, mitigating human errors in driving is a challenge, and there is currently a growing trend in the proposal for technological solutions intended to integrate driver information into advanced driving systems to improve driver performance and ergonomics. The study of human factors in the field of driving is a multidisciplinary field in which several areas of knowledge converge, among which stand out psychology, physiology, instrumentation, signal treatment, machine learning, the integration of information and communication technologies (ICTs), and the design of human-machine communication interfaces. The main objective of this thesis is to exploit knowledge related to the different facets of human factors in the field of driving. Specific objectives include identifying tasks related to driving, the detection of unfavorable cognitive states in the driver, such as stress, and, transversely, the proposal for an architecture for the integration and coordination of driver monitoring systems with other active safety systems. It should be noted that the specific objectives address the critical aspects in each of the issues to be addressed. Identifying driving-related tasks is one of the primary aspects of the conceptual framework of driver modeling. Identifying maneuvers that a driver performs requires training beforehand a model with examples of each maneuver to be identified. To this end, a methodology was established to form a data set in which a relationship is established between the handling of the driving controls (steering wheel, pedals, gear lever, and turn indicators) and a series of adequately identified maneuvers. This methodology consisted of designing different driving scenarios in a realistic driving simulator for each type of maneuver, including stop, overtaking, turns, and specific maneuvers such as U-turn and three-point turn. From the perspective of detecting unfavorable cognitive states in the driver, stress can damage cognitive faculties, causing failures in the decision-making process. Physiological signals such as measurements derived from the heart rhythm or the change of electrical properties of the skin are reliable indicators when assessing whether a person is going through an episode of acute stress. However, the detection of stress patterns is still an open problem. Despite advances in sensor design for the non-invasive collection of physiological signals, certain factors prevent reaching models capable of detecting stress patterns in any subject. This thesis addresses two aspects of stress detection: the collection of physiological values during stress elicitation through laboratory techniques such as the Stroop effect and driving tests; and the detection of stress by designing a process flow based on unsupervised learning techniques, delving into the problems associated with the variability of intra- and inter-individual physiological measures that prevent the achievement of generalist models. Finally, in addition to developing models that address the different aspects of monitoring, the orchestration of monitoring systems and active safety systems is a transversal and essential aspect in improving safety, ergonomics, and driving experience. Both from the perspective of integration into test platforms and integration into final systems, the problem of deploying multiple active safety systems lies in the adoption of monolithic models where the system-specific functionality is run in isolation, without considering aspects such as cooperation and interoperability with other safety systems. This thesis addresses the problem of the development of more complex systems where monitoring systems condition the operability of multiple active safety systems. To this end, a mediation architecture is proposed to coordinate the reception and delivery of data flows generated by the various systems involved, including external sensors (lasers, external cameras), cabin sensors (cameras, smartwatches), detection models, deliberative models, delivery systems and machine-human communication interfaces. Ontology-based data modeling plays a crucial role in structuring all this information and consolidating the semantic representation of the driving scene, thus allowing the development of models based on data fusion.I would like to thank the Ministry of Economy and Competitiveness for granting me the predoctoral fellowship BES-2016-078143 corresponding to the project TRA2015-63708-R, which provided me the opportunity of conducting all my Ph. D activities, including completing an international internship.Programa de Doctorado en Ciencia y Tecnología Informática por la Universidad Carlos III de MadridPresidente: José María Armingol Moreno.- Secretario: Felipe Jiménez Alonso.- Vocal: Luis Mart