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In recent years, evidence has accumulated that there are four distinct states of consciousness under normal conditions; in addition to the three commonly experienced states of wakefulness, sleep, and dreaming, there is a fourth state achieved by various Eastern meditation techniques. A model of man is discussed that could account for these states. This model, inspired by the concepts of cybernetics, holds that man's behavior and experience can be accounted for by feedback‐control processes and that these processes are hierarchically organized. This paper first attempts to demonstrate that the existence of four distinct states of consciousness is consistent with a general cybernetic view of man. Then, a specific information‐flow model of the mind, developed by Powers, is introduced and it is shown that with some revision this model well accounts for the four states.

In recent years, a new view of man has begun to emerge. This view, inspired by the concepts of cybernetics, holds that man's behavior and experience can be accounted for by feedback‐control processes and that these processes are hierarchically organized. In this paper, the ideas of three authors who have best expressed this new view, Arthur Koestler, Ervin Laszlo and William Powers, are summarized and compared. The conclusion is reached that, despite differences in detail, the three authors articulate remarkably consistent theories of the nature of man.

This chapter explores how the recognition of opportunities regarding developing technology and entering a new market is influenced by the systemic effect of social forces. These include institutions, social networks and the entrepreneur’s cognitive frames. This study adopts a longitudinal perspective by capturing and analysing the phenomenon in two moments: first, when the businesses started to operate domestically and second, when they began to internationalise. The cases of five Brazilian technology firms are analysed. The findings reveal the systemic and mutually reinforcing effect of these social forces on the recognition of opportunities. The entrepreneurs’ cognitive frames were particularly vital in recognising opportunities to enter the Brazilian market. The institutional support provided by universities along with government mechanisms and entrepreneurs’ social networks were essential to accrue experiential and non-experiential knowledge of international markets, therefore contributing to the recognition of international opportunities. The temporal perspective employed in this research assists the understanding of how historical events shape entrepreneurs’ capabilities to recognise and change company discourse to pursue the recognition of international opportunities. The results provide guidelines for researchers, practitioners and policy-makers, particularly in the emerging economies in Latin America, to support the growth and flourishing of entrepreneurial ventures through pursuing international opportunities.

The growing trends in the usage of hand held devices necessitate the need to design them with low power consumption and less area design. Besides, information security is gaining enormous importance in information transmission and data storage technology. In addition, today’s technology world is connected, communicated and controlled via the Internet of Things (IoT). In many applications, the most standard and widely used cryptography algorithm for providing security is Advanced Encryption Standard (AES). This paper aims to design an efficient model of AES cryptography for low power and less area.

First, the main issues related to less area and low power consumption in the AES encryption core are addressed. To implement optimized AES core, the authors proposed optimized multiplicative inverse, affine transforms and Xtime multipliers functions, which are the core function of AES’s core. In addition, to achieve the high throughput, it uses the multistage pipeline and resource reuse architectures for SBox and Mixcolumn of AES.

The results of optimized AES architecture have revealed that the multistage pipe line and resource sharing are optimal design model in Field Programmable Gate Array (FPGA) implementation. It could provide high security with low power and area for IoT and wireless sensors networks.

This proposed optimized modified architecture has been implemented in FPGA to calculate the power, area and delay parameters. This multistage pipeline and resource sharing have promised to minimize the area and power.

This paper seeks to advance research and strategies that lead to a heightened awareness of the need to protect data from disclosure, to guarantee the authenticity of data and messages, and to protect systems from network‐based attacks.

The paper introduces the necessary mathematics of cryptography: integer and modular arithmetic, linear congruence, Euclidean and extended Euclidean algorithm, Fermat's theorem, and Elliptic curve.

The results indicate that encryption has expanded beyond confidentiality concerns to include techniques for message integrity checking, sender/receiver identity authentication, digital signatures, interactive proofs, and secure computation.

The results of this research show that all forms of e‐commerce activities such as online credit card processing, purchasing stocks, and banking data processing, if compromised, would lead to businesses losing billions of dollars in lost revenues as well as losing confidence in e‐commerce. In the last few years, it had been reported that organizations that store and maintain customers' private and confidential records were compromised on many occasions by hackers breaking into the data networks and stealing the records from the storage media.

This paper tackles one of the most critical problems of securing data networks. Security problems arise among other things to resource and workload sharing; complexity of interconnected networks; authentication of users; fast expandability of networks; threats to networks such as wiretapping and violations of the seven pillars of security: authentication, authorization, privacy, integrity, non‐repudiation, availability, and audit.

Expert Cloud as a new class of Cloud computing systems enables its users to request the skill, knowledge and expertise of people by employing internet infrastructures and Cloud computing concepts without any information of their location. Job scheduling is one of the most important issue in Expert Cloud and impacts on its efficiency and customer satisfaction. The purpose of this paper is to propose an applicable method based on genetic algorithm for job scheduling in Expert Cloud.

Because of the nature of the scheduling issue as a NP-Hard problem and the success of genetic algorithm in optimization and NP-Hard problems, the authors used a genetic algorithm to schedule the jobs on human resources in Expert Cloud. In this method, chromosome or candidate solutions are represented by a vector; fitness function is calculated based on response time; one point crossover and swap mutation are also used.

The results indicate that the proposed method can schedule the received jobs in appropriate time with high accuracy in comparison to common methods (First Come First Served, Shortest Process Next and Highest Response Ratio Next). Also the proposed method has better performance in term of total execution time, service+wait time, failure rate and Human Resource utilization rate in comparison to common methods.

In this paper the job scheduling issue in Expert Cloud is pointed out and the approach to resolve the problem is applied into a practical example.

The progressive computerization of business processes and widespread availability of computer networking make it possible to dramatically increase the frequency of periodic audits by redesigning the auditing architecture around Continuous Online Auditing (COA). Continuous auditing is viewed here as a type of auditing that produces audit results simultaneously with, or a short period of time after, the occurrence of relevant events. It is arguable that continuous auditing can be implemented only as an online system, i.e., a system that is permanently connected through computer networking to both auditees and auditors. This article proposes a research agenda for the emerging field of COA. First, the history, institutional background, feasibility of and some experiences in COA are briefly reviewed. Thereafter, a number of research issues relating to the architecture of COA, factors affecting the use of COA, and the major consequences of COA are presented. Finally, a selected number of research issues are highlighted as priorities for future research in COA.

Currently, a much-debated issue concerns the social and political significance of the emergence of the precariat, a social class consisting of people for whom uncertainty and unpredictability of life circumstances and employment relations make it impossible to plan for the future, forcing them to live on a day-to-day basis (Standing, 2011). However, it remains unclear how the precariat may be defined and operationalized. On the one hand, treating non-standard employment arrangements (fixed-term contracts, temporary agency work, etc.) as a basis for identifying precarious jobs is likely to be misleading, as research has shown non-standard employment to be heterogeneous with respect to working conditions and chances for achieving stabilization. On the other hand, subjective perceptions of security may also be misleading as indicators of precarity, as they are compounded by psychological coping mechanisms and perceptions of reference group status. This analysis attempts to disentangle the complex relationships between non-standard employment and perceived insecurity in order to provide grounds for a more adequate conceptualization and measurement of job precarity. Specifically, I assess the extent to which the relationship between worker contractual status and perceived job, labor market, and employment insecurity is conditional on various characteristics of workers, their jobs, and their households, taking into account the country-level economic and institutional context. The analysis is based on multi-level regression models using data from the 2010 European Working Conditions Survey.

This chapter will explore the impact virtual learning had on students and their social and emotional development as a result of the COVID-19 pandemic. The authors’ guiding question(s) for this chapter will be: How has social and emotional growth been considered as part of the missing piece to virtual learning? How are social and emotional learning opportunities addressed to achieve maximum student success and development as future leaders in a global society? What lessons have been learned during the pandemic regarding virtual teaching that can help develop more robust curriculum/learning choices for supporting students’ social and emotional well-being? Using research on digital learning and student and teacher interviews, the authors will gather data to report on the positives and opportunities for growth from the impact of the pandemic and virtual learning. The authors discuss implications of this work.