Hospitality Management Instructor Attitudes towards COVID-Driven Compulsory Course-Virtualization: A Qualitative Descriptive Study

The purpose of this qualitative descriptive study was to explore how hospitality management instructors at a college of management in the Northeastern United States describe their attitudes towards the effects on instruction of the COVID-driven compulsory virtualization of their courses that occurred in Spring 2020. The Theory of Technology Acceptance, the Extended Theory of Technology Acceptance, and the Unified Theory of the Use and Acceptance of Technology jointly constituted this study’s theoretical foundations. Data collection was guided by three research questions, namely: (i) How do hospitality management instructors describe their attitudes towards the effects on teaching of the COVID-driven virtualization of instruction that occurred in Spring 2020? (ii) How do such instructors describe the setbacks created by said virtualization? (iii) How do such instructors describe the benefits of said virtualization? Data was acquired through 14 semistructured interviews and two semi-structured focus groups. Thematic analysis of the data yielded eight themes: (i) Virtual instruction was relatively convenient in some respects; (ii) Student-on-student interaction was limited; (iii) Instructor-student interaction was limited; (iv) Complex material was hard to teach; (v) Students disengaged; (vi) Virtual courses came to resemble correspondence courses; (vii) Courses involving labs and lab-like components could not be taught properly: (viii) Virtual instruction had more downsides than upsides. Conclusion: In order for the virtualization of hospitality management courses to succeed, the technology being used must allow the emotional dynamics that govern inperson instruction to govern virtual instruction

The Pandemic\u27s Impact on the Efficacy of Chaplaincy at the Baldwin State Prison

Chaplains usually provide pastoral care for inmates, staff members, and counseling for offenders and offenders’ families. Because of the pandemic, they have not provided adequate pastoral care and counseling in their respective facilities. The restrictions imposed by the pandemic have negatively impacted the chaplain’s ability to adequately provide pastoral care and counseling in most federal and state correctional institutions. The Department of Georgia Correctional facilities, particularly at the Baldwin State prison, has also experienced this decrease in pastoral care and counseling due to the pandemic. In the Georgia Department of Corrections, all visitations, including lawyers and clergy, have been suspended since March 2020. Due to these restrictions, the chaplain of the Baldwin State prison in Georgia cannot coordinate the various religious services representing the different religious groups housed in the facility. Secondly, the facility has seven dormitories that house one hundred and seven inmates (107) per dormitory, and the COVID-19 virus can spread exponentially due to this overcrowded condition. The pandemic has severely hindered the Baldwin State prison\u27s chaplain\u27s ability to provide this critical pastoral care and counseling for staff members and offenders. This body of research implications is discussed: the restrictions imposed by the pandemic and the overcrowded conditions at this facility have impeded the Baldwin State chaplain\u27s ability to adequately provide the pastoral care and counseling required for this facility during the COVID-19 pandemic. This lack of pastoral care and counseling results in moral issues and increased mental health challenges throughout the facility

Adversarial Machine Learning for the Protection of Legitimate Software

Obfuscation is the transforming a given program into one that is syntactically different but semantically equivalent. This new obfuscated program now has its code and/or data changed so that they are hidden and difficult for attackers to understand. Obfuscation is an important security tool and used to defend against reverse engineering. When applied to a program, different transformations can be observed to exhibit differing degrees of complexity and changes to the program. Recent work has shown, by studying these side effects, one can associate patterns with different transformations. By taking this into account and attempting to profile these unique side effects, it is possible to create a classifier using machine learning which can analyze transformed software and identifies what transformation was used to put it in its current state. This has the effect of weakening the security of obfuscating transformations used to protect legitimate software. In this research, we explore options to increase the robustness of obfuscation against attackers who utilize machine learning, particular those who use it to identify the type of obfuscation being employed. To accomplish this, we segment our research into three stages. For the first stage, we implement a suite of classifiers that are used to xiv identify the obfuscation used in samples. These establish a baseline for determining the effectiveness of our proposed defenses and make use of three varied feature sets. For the second stage, we explore methods to evade detection by the classifiers. To accomplish this, attacks setup using the principles of adversarial machine learning are carried out as evasion attacks. These attacks take an obfuscated program and make subtle changes to various aspects that will cause it to be mislabeled by the classifiers. The changes made to the programs affect features looked at by our classifiers, focusing mainly on the number and distribution of opcodes within the program. A constraint of these changes is that the program remains semantically unchanged. In addition, we explore a means of algorithmic dead code insertion in to achieve comparable results against a broader range of classifiers. In the third stage, we combine our attack strategies and evaluate the effect of our changes on the strength of obfuscating transformations. We also propose a framework to implement and automate these and other measures. We the following contributions: 1. An evaluation of the effectiveness of supervised learning models at labeling obfuscated transformations. We create these models using three unique feature sets: Code Images, Opcode N-grams, and Gadgets. 2. Demonstration of two approaches to algorithmic dummy code insertion designed to improve the stealth of obfuscating transformations against machine learning: Adversarial Obfuscation and Opcode Expansion 3. A unified version of our two defenses capable of achieving effectiveness against a broad range of classifiers, while also demonstrating its impact on obfuscation metrics

Virtualization and shared Infrastructure data storage for IT in Kosovo institutions

This capstone project addressed the need to strengthen the centralization and security of the electronic data from various national institutions in Kosovo. Most of the electronic data in Kosovo Institutions are separated in so many server rooms in different institutions and different locations. The Republic of Kosovo institutions have different systems of data stored in different physical spaces. Most of these data should be exchangeable in different systems and different data bases. The country lacks physical security in the current system of data security and professional staff for maintaining such data (databases, applications, and other electronic data). The budget of Kosovo is making higher and unnecessary expenditure in the field of information and technology. This project would be a good alternative in order to reduce budgetary expenditure of Kosovo ... The outcome of this project provides recommendations in order to achieve the goals of the project. The three main recommendations of the project are centralization, virtualization and business continuity

A multi-agent system framework for dialogue games in the group decision-making context

Dialogue games have been applied to various contexts in computer science and artificial intelligence, particularly to define interactions between autonomous software agents. However, in order to implement dialogue games, the developers need to deal with other important details besides what is presented in the model’s definition. This is a complex work, mostly when it is expected that the agents’ interactions correctly represent a human group behavior. In this work, we present a multi-agent system framework specifically designed to facilitate the implementation of dialogue games under the context of group decision-making in which agents interact as the humans do in face-to-face meetings. The proposed framework, named MAS4GDM, encapsulates the JADE framework and provides a layer that allows developers to easily implement their dialogue models without being concerned with some complex implementation details, such as: the communication model, the agents’ life cycle, among others. We ran an experimental evaluation and verified that the proposed framework allows to implement dialogue models in an easier way and abstract the developers from important implementation details that can compromise the application’s success.This work was supported by the GrouPlanner Project (POCI-01-0145-FEDER-29178) and by National Funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within the Projects UID/CEC/00319/2013 and UID/EEA/00760/2013

Exploring Views on Data Centre Power Consumption and Server Virtualization

The primary purpose of this Thesis is to explore views on Green IT/Computing and how it relates to Server Virtualization, in particular for Data Centre IT environments. Our secondary purpose is to explore other important aspects of Server Virtualization, in the same context. The primary research question was to determine if Data Centre (DC) power consumption reduction is related to, or perceived as, a success factor for implementing and deploying server virtualization for consolidation purposes, and if not, what other decision areas affect Server Virtualization and power consumption reduction, respectively. The conclusions from our research are that there is a difference of opinion regarding how to factor power consumption reduction from server equipment, both from promoters and deployers. However, it was a common view that power consumption reduction was usually achieved, but not necessarily considered, and thus not evaluated, as a success factor, nor that actual power consumption was measured or monitored after server virtualization deployment. We found that other factors seemed more important, such as lower cost through higher physical machine utilization, simplified high availability and disaster recovery capabilities

Complex systems virtualization in the current’s economical context

How can we dramatically improve the efficiency and availability of resources and applications in our organization? Today, the answer is very simple: virtualization. Reducing your capital and IT operational costs by virtualizing your IT infrastructure in a „virtual infrastructure” while increasing the efficiency,utilization and flexibility of your existing assets. Go beyond server consolidation and deploy a standard virtualization platform to automate your entire IT infrastructure. Virtualization IT infrastructure delivers resources, applications and even servers when and where they are needed. Use the power of virtualization to better manage IT capacity, provide better service levels, and streamline IT processes. Respond to market dynamics faster and more efficiently than ever before with an automated virtualization platform

Drivers and challenges of circular business models : Comparative case study in textile industry

The aim of this research is to advance knowledge of circular business models and the drivers and challenges related to the implementation of these models. Textile industry is the world`s second most polluting industry and the current linear “take-make-waste” model of this industry cannot continue. Circular economy and circular business models are solutions for the current unsustainable linear economic model. Circular economy bases on the idea of restorative and regenerative production and consumption systems. The aim of these systems is to keep materials and products as their highest utility for as long as possible. Despite the growing popularity of circular economy, it is still a poorly understood concept and the implementation of circular business model is even more uncertain. Thus, this thesis explores circular business models in textile industry as well as the factors which strengthen or hamper the implementation of a circular business model. This study is conducted as a comparative case study that reflects the circular business models of developing and established textile companies. The empirical research was conducted through four semi-structured interviews with Finnish textile companies. Furthermore, this research follows a deductive approach as the research continues from theory to empirical testing. The findings of this research explain different circular business models and the drivers and challenges related to the specific circular business model. The research results show what business actions each company operated to create a circular business model. Furthermore, this research analyzes the differences and similarities between developing and established textile companies. Circular business models of case companies varied with each other, but the main drivers and challenges were similar. The main drivers related to circular economy were social and cultural issues whereas the main challenges related to circular economy were the lack of technological development. The outcomes of this study will support textile companies to analyze different options of implementing circular economy and the things which will either strengthen or hamper the implementation

Towards a Cyber-Physical Manufacturing Cloud through Operable Digital Twins and Virtual Production Lines

In last decade, the paradigm of Cyber-Physical Systems (CPS) has integrated industrial manufacturing systems with Cloud Computing technologies for Cloud Manufacturing. Up to 2015, there were many CPS-based manufacturing systems that collected real-time machining data to perform remote monitoring, prognostics and health management, and predictive maintenance. However, these CPS-integrated and network ready machines were not directly connected to the elements of Cloud Manufacturing and required human-in-the-loop. Addressing this gap, we introduced a new paradigm of Cyber-Physical Manufacturing Cloud (CPMC) that bridges a gap between physical machines and virtual space in 2017. CPMC virtualizes machine tools in cloud through web services for direct monitoring and operations through Internet. Fundamentally, CPMC differs with contemporary modern manufacturing paradigms. For instance, CPMC virtualizes machining tools in cloud using remote services and establish direct Internet-based communication, which is overlooked in existing Cloud Manufacturing systems. Another contemporary, namely cyber-physical production systems enable networked access to machining tools. Nevertheless, CPMC virtualizes manufacturing resources in cloud and monitor and operate them over the Internet. This dissertation defines the fundamental concepts of CPMC and expands its horizon in different aspects of cloud-based virtual manufacturing such as Digital Twins and Virtual Production Lines. Digital Twin (DT) is another evolving concept since 2002 that creates as-is replicas of machining tools in cyber space. Up to 2018, many researchers proposed state-of-the-art DTs, which only focused on monitoring production lifecycle management through simulations and data driven analytics. But they overlooked executing manufacturing processes through DTs from virtual space. This dissertation identifies that DTs can be made more productive if they engage directly in direct execution of manufacturing operations besides monitoring. Towards this novel approach, this dissertation proposes a new operable DT model of CPMC that inherits the features of direct monitoring and operations from cloud. This research envisages and opens the door for future manufacturing systems where resources are developed as cloud-based DTs for remote and distributed manufacturing. Proposed concepts and visions of DTs have spawned the following fundamental researches. This dissertation proposes a novel concept of DT based Virtual Production Lines (VPL) in CPMC in 2019. It presents a design of a service-oriented architecture of DTs that virtualizes physical manufacturing resources in CPMC. Proposed DT architecture offers a more compact and integral service-oriented virtual representations of manufacturing resources. To re-configure a VPL, one requirement is to establish DT-to-DT collaborations in manufacturing clouds, which replicates to concurrent resource-to-resource collaborations in shop floors. Satisfying the above requirements, this research designs a novel framework to easily re-configure, monitor and operate VPLs using DTs of CPMC. CPMC publishes individual web services for machining tools, which is a traditional approach in the domain of service computing. But this approach overcrowds service registry databases. This dissertation introduces a novel fundamental service publication and discovery approach in 2020, OpenDT, which publishes DTs with collections of services. Experimental results show easier discovery and remote access of DTs while re-configuring VPLs. Proposed researches in this dissertation have received numerous citations both from industry and academia, clearly proving impacts of research contributions

California State University, San Bernardino managing cloud computing resources with CloudStack using KVM hypervisor

The purpose of this project is to present a detailed description of the Enterprise Cloud Computing implementation of CloudStack using KVM. It will explain the purpose and features of the system, the interfaces of the system, what the system will do, and the constraints or limitations implementing CloudStack with the hardware available for this study