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The Cyclic Innovation Model is applied to a new process for the production of fine chemicals and pharmaceuticals using a combination of ionic liquids and supercritical carbon dioxide. This multi-value innovation combines economic growth with environmental concerns and social value. The most important obstacles in the implementation of this new technology are the successful life cycle management of current production plants, the linearity of current innovation thinking, and a perceived high risk of adoption.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

In this chapter, a general introduction on artificial intelligence (AI) is given as well as an overview of the advances of AI in different engineering disciplines, including its effectiveness in driving the United Nations Sustainable Development Goals (UN SDGs). This chapter begins with some fundamental definitions and concepts on AI and machine learning (ML) followed by a classification of the different categories of ML algorithms. After that, a general overview of the impact which different engineering disciplines such as Civil, Chemical, Mechanical, Electrical and Telecommunications Engineering have on the UN SDGs is given. The application of AI and ML to enhance the processes in these different engineering disciplines is also briefly explained. This chapter concludes with a brief description of the UN SDGs and how AI can positively impact the attainment of these goals by the target year of 2030.

Adsorption parameters (e.g. Langmuir constant, mass transfer coefficient and Thomas rate constant) are involved in the design of aqueous-media adsorption treatment units. However, the classic approach to estimating such parameters is perceived to be imprecise. Herein, the essential features and performances of the ant colony, bee colony and elephant herd optimisation approaches are introduced to the experimental chemist and chemical engineer engaged in adsorption research for aqueous systems. Key research and development directions, believed to harness these algorithms for real-scale water treatment (which falls within the wide-ranging coverage of the Sustainable Development Goal 6 (SDG 6) ‘Clean Water and Sanitation for All’), are also proposed. The ant colony, bee colony and elephant herd optimisations have higher precision and accuracy, and are particularly efficient in finding the global optimum solution. It is hoped that the discussions can stimulate both the experimental chemist and chemical engineer to delineate the progress achieved so far and collaborate further to devise strategies for integrating these intelligent optimisations in the design and operation of real multicomponent multi-complexity adsorption systems for water purification.

We examine the evolution of vertical specialization in three industries: chemicals, computers, and semiconductors. Vertical specialization is the restructuring of industry-wide value chains, such that different stages are controlled by different firms, rather than being vertically integrated within the boundaries of individual firms. In some cases, vertical specialization may span international boundaries and is associated with complex international production networks. After decades of vertical specialization, firms in the chemical industry are re-integrating stages of the value chain. By contrast, the semiconductor and computer industries have experienced significant vertical specialization during the past ten years. We examine how and why these contrasting trends in vertical specialization have co-evolved with industry maturation and decline, and underscore the importance and role of both industry factors and business strategies necessary for industries to become more specialized. We also consider the effects of vertical specialization on the sources of innovation and the geographic redistribution of production and other activities. We conclude that the evolution of vertical specialization in these three industries has both reflected and influenced the strategies of leading firms, while also displays industry-specific characteristics that are rooted in different technological and market characteristics.

Strengthening the nation’s technological workforce, competing and expanding its relevance in the global economy, and maintaining personal as well as homeland security will be highly dependent on the quantity, quality, and diversity of the next generations of scientists, engineers, technologists, and mathematicians. Production of a diverse generation of human resources with relevant, competitive skills is critical. However, so too is the need to raise an enlightened citizenry with cross-cultural experience and cultural awareness competency, with a broad worldview and global perspectives. These requirements are critical to understanding the challenges and opportunities of scholarly activity in a pluralistic global environment and positioning ourselves to capitalize upon them. Scholars with cross-cultural experience and competency are empowered to adapt and work collaboratively, nationally and globally, with scholars of different races, geopolitical, socioeconomic, and cultural backgrounds. Development of effective strategies to transform science, technology, engineering, and mathematics (STEM) departments for inclusion and to broaden the participation in STEM across cultures, socioeconomic standing, race, and gender in higher education has been a dominant topic of pedagogical interest of national priority in the last several decades. However, success in these endeavors is achievable only through systemic change and a cultural shift to address the underlying root causes of socioeconomic disparity, gender, and racial disparities and a paucity of cultural awareness among all educational stakeholders. STEM departments can only be truly transformed for inclusion through the development of sensitive, creative, and student-engaging curricula and targeted recruitment and retention of underrepresented minorities in STEM. Formation of well-coordinated alliances spanning educational sectors, governmental and non-governmental organizations, and community engagement and outreach are also critical to promoting inclusive and broad participation in STEM education.

The first section of the chapter gives an introduction to various challenges, obstacles, and hindrances that prevent a successful transformation of K–12 science education as well as STEM departments in higher education for inclusion. The second section discusses historical perspectives of the University of Arkansas-Fort Smith (UAFS) – the institutional profile, missions, and visions of UAFS as a regional university. Policies and strategies for addressing the socioeconomic disparity, faculty gender, and racial disparities and cultural competency awareness at UAFS are also highlighted in this section. Other approaches including targeted efforts to recruit and retain underrepresented minority students, provision of financial assistance for students from low-income families, and a creative “Math-up” curriculum innovation to promote inclusive and broad participation in STEM at UAFS are highlighted in the latter section of the chapter. Formation of alliances between UAFS, local K–12 school districts, and governmental and non-governmental agencies to promote broad participation in STEM at UAFS are discussed. The last section of the chapter provides recommendations for adaptation and sustainability of strategies and efforts aimed at transforming national STEM departments for inclusion.