Network Management, Optimization and Security with Machine Learning Applications in Wireless Networks

Wireless communication networks are emerging fast with a lot of challenges and ambitions. Requirements that are expected to be delivered by modern wireless networks are complex, multi-dimensional, and sometimes contradicting. In this thesis, we investigate several types of emerging wireless networks and tackle some challenges of these various networks. We focus on three main challenges. Those are Resource Optimization, Network Management, and Cyber Security. We present multiple views of these three aspects and propose solutions to probable scenarios. The first challenge (Resource Optimization) is studied in Wireless Powered Communication Networks (WPCNs). WPCNs are considered a very promising approach towards sustainable, self-sufficient wireless sensor networks. We consider a WPCN with Non-Orthogonal Multiple Access (NOMA) and study two decoding schemes aiming for optimizing the performance with and without interference cancellation. This leads to solving convex and non-convex optimization problems. The second challenge (Network Management) is studied for cellular networks and handled using Machine Learning (ML). Two scenarios are considered. First, we target energy conservation. We propose an ML-based approach to turn Multiple Input Multiple Output (MIMO) technology on/off depending on certain criteria. Turning off MIMO can save considerable energy of the total site consumption. To control enabling and disabling MIMO, a Neural Network (NN) based approach is used. It learns some network features and decides whether the site can achieve satisfactory performance with MIMO off or not. In the second scenario, we take a deeper look into the cellular network aiming for more control over the network features. We propose a Reinforcement Learning-based approach to control three features of the network (relative CIOs, transmission power, and MIMO feature). The proposed approach delivers a stable state of the cellular network and enables the network to self-heal after any change or disturbance in the surroundings. In the third challenge (Cyber Security), we propose an NN-based approach with the target of detecting False Data Injection (FDI) in industrial data. FDI attacks corrupt sensor measurements to deceive the industrial platform. The proposed approach uses an Autoencoder (AE) for FDI detection. In addition, a Denoising AE (DAE) is used to clean the corrupted data for further processing

The Interplay between Computation and Communication

In this thesis, a comprehensive exploration into the integration of communication and learning within the massive Internet of Things (mIoT) is undertaken. Addressing one of the fundamental challenges of mIoT, where traditional channel estimation methods prove inefficient due to high device density and short packets; initially, a novel approach leveraging unsupervised machine learning for joint channel estimation and signal detection is proposed. This technique utilizes the Gaussian mixture model (GMM) clustering of received signals, thereby reducing the necessity for exhaustive channel estimation, decreasing the number of required pilot symbols, and enhancing symbol error rate (SER) performance. Building on this foundation, an innovative method is proposed that eliminates the need for pilot symbols entirely. By coupling GMM clustering with rotational invariant (RI) coding, the model maintains robust performance against the effects of channel rotation, thereby improving the efficiency of mIoT systems. This research delves further into integrating communication and learning in mIoT, specifically focusing on federated learning (FL) convergence under error-prone conditions. It carefully analyzes the impact of factors like block length, coding rate, and signal-to-noise ratio on FL's accuracy and convergence. A novel approach is proposed to address communication error challenges, where the base station (BS) uses memory to cache key parameters. Closing the thesis, an extensive simulation of a real-world mIoT system, integrating previously developed techniques, such as the innovative channel estimation method, RI coding, and the introduced FL model. It notably demonstrates that optimal learning outcomes can be achieved even without stringent communication reliability. Thus, this work not only achieves comparable or superior performance to traditional methods with fewer pilot symbols but also provides valuable insights for optimizing mIoT systems within the FL framework

Automated Deduction – CADE 28

This open access book constitutes the proceeding of the 28th International Conference on Automated Deduction, CADE 28, held virtually in July 2021. The 29 full papers and 7 system descriptions presented together with 2 invited papers were carefully reviewed and selected from 76 submissions. CADE is the major forum for the presentation of research in all aspects of automated deduction, including foundations, applications, implementations, and practical experience. The papers are organized in the following topics: Logical foundations; theory and principles; implementation and application; ATP and AI; and system descriptions

Women in Science 2012

The summer of 2012 saw the number of students seeking summer research experiences with a faculty mentor reaching record levels. In total, 179 students participated in the Summer Undergraduate Research Fellows (SURF) program, involving 59 faculty mentor-advisors, representing all of the Clark Science Center’s fourteen departments and programs.https://scholarworks.smith.edu/clark_womeninscience/1011/thumbnail.jp

Conflict Management

Many students reading the book will have previously taken Communication Psychology and will have read the companion OER, Psychology, Communication and the Canadian Workplace. If you did not take: Communication Psychology, you may find it helpful to look at this resource for a general introduction to many of the topics that we will be discussing in this book. The course learning objectives for this course are as follows: 1. Identify factors that contribute to conflict in the workplace. 2. Name factors that lead to positive professional identity and productive group dynamics. 3. Describe different conflict styles. 4. Discuss their own interpersonal competencies and areas in need of improvement regarding conflict management in the workplace. 5. Evaluate the strengths and weaknesses of conflict management styles and strategies. 6. Analyze hypothetical/case study conflict scenarios for the workplace. 7. Implement strategies to manage/resolve conflict in the workplace. 8. Analyze workplace conflict prevention and management policies. These learning objectives were formed in consultation with local employers and stakeholders in London, ON. Employers indicated that it was desirable for graduates entering the workforce to have more explicit training in conflict management. While employees do not usually need to be trained negotiators or legal experts, it is helpful for students to have the skills and knowledge to navigate both the mundane occurrences of conflict in the workplace (e.g., the coworker with a difficult personality) and more serious incidences of conflict at work (e.g., bullying, harassment, and violence). We will learn a bit about federal and provincial legislation, organizational policies and the formal conflict process. However, the focus will be on the individual, and how each one of us can play a role in making the workplace a safe and functional environment. Throughout the book, you will be encouraged to engage in critical self-assessment and case studies. These exercises will provide you with the opportunity to assess potential conflict situations, recognize your emotions, communicate assertively, and manage conflict with integrity and professionalis

COMM 11 Fundamentals of Interpersonal Communication textbook

A survey of interpersonal communication

An analysis of the distinction between voluntary and involuntary behaviour in psychology

Psychology, as a separate scientific discipline, was derived from philosophy and physiology and, in part, adopted their concepts and language. Initially psychology perceived its subject matter to be volition, among other mental constructs. In response to internal tensions, involving methodology, more intense interest was given to the study of behaviour. Behaviouristic psychology proposed the abolition of mental constructs, and sought to interpret behaviour in mechanistic terms. Two powerful methods were developed to study behaviour objectively; the classical and instrumental conditioning procedures. The use of the two conditioning procedures generated much controversy concerning the classification of behaviour as well as the necessary and sufficient conditions for learning.However, the behavioural taxonomy generated by its scientific study has been inadequately formulated and there have been fundamental confusions about the concept of behaviour itself. These confusions have been highlighted by the recent experimental data from two important areas of research in the experimental study of learning; (i) autoshaping (ii) the operant conditioning of autonomic responses. These data challenge the widely held view that all behaviour may be classified, after Skinner, as operants or respondents.ConventionaL psychological wisdom has conflated the concepts of 'voluntary' and 'involuntary' with the concepts of 'operant' and 'respondent', respectively. 'Respondents' by definition have specifiable antecedents, whereas 'operants' do not. The inability to note specific antecedents to instrumental behaviour is reflected in the original studies using animals by Thorndike. Instrumental (operant) behaviour was seen as 'impulsive', 'emitted' or 'spontaneous' - terms which have traditionally been associated with voluntary behaviour. Inadvertently, under the influence of Skinner, the vitalistic connotations of the operant were hidden from view and protected from criticism. Concomitant with these developments, the role of the central nervous system in the production and control of movement is being re-interpreted by neurophysiologists. In this field mentalistic and vitalistic accounts of behaviour have emerged at the highest levels. Although physical accounts of behaviour do not have logical priority over mental accounts, the former have the advantage of being more open to direct experimental investigation. The apparent paradox of a so-called mechanistic, physicalistic psychology and physiology accounting for behaviour in terms of vitalistic and mentalistic concepts prompted this analysis of the distinction between voluntary and involuntary behaviour.An historical approach is adopted which draws on both primary and secondary sources in psychology, physiology, philosophy and medicine. References to voluntary and involuntary processes from the early Greeks to the present day, are summarized and their relationship with the broader intellectual issues is broached. The distinction between voluntary and involuntary behaviours arose early in western intellectual history and the concept of 'voluntary behaviour' was discussed, largely within the context of moral responsibility. At various times the mentalistic concepts of soul, mind and free-will were proposed as its source.The idea that voluntary movement issued from the 'free-will' received its greatest support from Christian theology. Ecclesiastical monopoly of educated thought ensured that this interpretation of behaviour was firmly established in the institutions of western culture. With the rise of western science, the language of this view and its connotations intruded into the language of the disciplines of modern philosophy and physiology, among others. The term 'voluntary', referring to behaviour, has undergone numerous and subtle changes in meaning, and the separation of voluntary and involuntary behaviour parallels several other important conceptual dichotomies. Two of these are the'mind-body problem' and the 'mechanism vs vitalism' debate. Contemporary literature in the fields of psychology, physiology and philosophy reflects the fact that these conceptual issues have not been resolved, as once was thought; but are active points of debate.Psychology is presently changing its understanding of behaviour, and today the voluntary-involuntary distinction may be maintained by the operational definition of a voluntary response being an 'instructed response'. Instructed responses as voluntary responses have been extensively used in both experimental and clinical studies of behaviour. This operational definition, in contrast to others, has brought the voluntary response under direct experimental scrutiny and deprived it of its 'uncaused' attribute. Its use has produced much needed empirical data concerning the metric parameters of movement.No one method of study or theoretical model is likely to explain behaviour in the·near future, and such an explanation will not be derived from experimental evidence alone. It is suggested that future interpretations of behaviour will use concepts derived from such technical fields as engineering and cybernetics as well as from psychology and physiology. Perhaps no current conceptual analysis can give us even partial insight into the future development of self-regulating machines; the future development of such machines, however may shed light onto our current concepts

Efficient Passive Clustering and Gateways selection MANETs

Passive clustering does not employ control packets to collect topological information in ad hoc networks. In our proposal, we avoid making frequent changes in cluster architecture due to repeated election and re-election of cluster heads and gateways. Our primary objective has been to make Passive Clustering more practical by employing optimal number of gateways and reduce the number of rebroadcast packets