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In this chapter, the authors interrogate the structures, natures, processes, and variables that shape globalized collegiate desegregation. The authors pay attention to the history of segregation in South African culture, then proceed to current efforts to dismantle and rebuild the country’s educational enterprise. Drawing parallels with segregation policy in the United States, the authors argue that both nations may draw from global lessons about systemic global anti-Black oppression and its structural forms (e.g., apartheid, inequities in higher education). More specifically, the authors ground arguments in an analysis of the linguistic hegemony that continues to inculcate the college-aspiring students of South Africa. Understanding fundamental desegregation characteristics of racial hegemonic nations (e.g., United States) vis-à-vis racial and linguistic hegemonic nations (e.g., South Africa) is imperative to increase understanding of democratization of educational systems throughout the world.

The purpose of the study is to develop a cloud supporting model for green computing. In today's contemporary world, information technology (IT) plays a significant role. Because of the rapid growth of the IT business and the high level of greenhouse gas emissions, salient data centers are increasingly considering green IT techniques to reduce their environmental impacts. Both developing and underdeveloped countries are widely adopting green infrastructure and services over the cloud because of its cost-effectiveness, scalability and guaranteed high uptime. Several studies have investigated the fact that cloud computing provides beyond green information and communication technology (ICT) services and solutions. Therefore, anything offered over clouds also needs to be green to reduce the adverse influence on the environment.

This paper examines the rationale for the use of green ICT in higher education and finds crucial success variables for the implementation of green ICT on the basis of an analysis of chosen educational organizations and interviews with key academic experts from the Universities of Ethiopia, in general, and BuleHora University, in particular.

Finally, this paper described the design and development of a green cloud selection supporting model for green ICTs in higher educational institutions that helps cloud service customers choose the most green cloud-based ICT products as well as services.

This study may be a significant source of new information for green ICT design and implementation in higher education institutions to preserve the environment and its impact on human life.

Using the most recent dataset from 2013–2014 to 2017–2018, the study examines the efficiency of 75 coal-fired power plants in the Indian thermal power sector. The authors obtained robust estimates of efficiency scores by employing Seiford and Zhu’s (2002) DEA-based classification invariance technique to account for CO₂ emissions as an undesirable output. Meta-frontier analysis and the Tobit regression are used to compute technology heterogeneity across power plants belonging to public and private groups and investigate the factors driving carbon-adjusted efficiency, respectively. The results reveal that, on average, the efficiency of power plants during the study period is 78.26%, showing significant room for reduction in CO₂ emissions alongside augmentation in electricity generation. Private plants are more efficient than public ones, and relative performance inefficiency is the primary source of inefficiency in the thermal power sector. Regression analysis indicates that domestic-equipped plants perform with lesser levels of efficiency, and plants with more units are more inefficient than plants with fewer units. Carbon productivity significantly improves efficiency since fewer fossil fuels with high carbon will generate more electricity.

The effect of throughflow and Coriolis force on convective instabilities in micropolar fluid layer heated from below for free‐free, isothermal and micro‐rotation free boundaries is investigated. Calculations are made using a lower order Galerkin approximation to solve the eigenvalue problem for stationary instability. It is observed that both stabilizing and destabilizing factors due to constant vertical throughflow can be enhanced by rotation.

Service-oriented architecture is an emerging software architecture, in which web service (WS) plays a crucial role. In this architecture, the task of WS composition and verification is required when handling complex requirement of services from users. When the number of WS becomes very huge in practice, the complexity of the composition and verification is also correspondingly high. In this paper, the authors aim to propose a logic-based clustering approach to solve this problem by separating the original repository of WS into clusters. Moreover, they also propose a so-called quality-controlled clustering approach to ensure the quality of generated clusters in a reasonable execution time.

The approach represents WSs as logical formulas on which the authors conduct the clustering task. They also combine two most popular clustering approaches of hierarchical agglomerative clustering (HAC) and k-means to ensure the quality of generated clusters.

This logic-based clustering approach really helps to increase the performance of the WS composition and verification significantly. Furthermore, the logic-based approach helps us to maintain the soundness and completeness of the composition solution. Eventually, the quality-controlled strategy can ensure the quality of generated clusters in low complexity time.

The work discussed in this paper is just implemented as a research tool known as WSCOVER. More work is needed to make it a practical and usable system for real life applications.

In this paper, the authors propose a logic-based paradigm to represent and cluster WSs. Moreover, they also propose an approach of quality-controlled clustering which combines and takes advantages of two most popular clustering approaches of HAC and k-means.

The Black Belt of the Deep South with rural areas in the states of Alabama, Georgia, and Mississippi has historically faced challenges that come with rural isolation, limited industry and financial services, poor healthcare options, and lack of educational opportunities. In the early 1990s, some institutions of higher education, including Historically Black Colleges and Universities, sought to increase educational opportunities for African Americans living in these areas. This chapter provides a historic case study of a doctoral education program that was founded to increase the number of education leaders, especially African Americans with advanced degrees, who would work in Alabama. As a historic case study, it provides a general overview of the founding of the program including mission and vision, a retrospective of the types of opportunities provided to doctoral students, and reflections on ways in which the program has improved the students' professional practices from both faculty and students. One component of this retrospective is to trace those students living in and working in the Alabama Black Belt. A key understanding undergirding the importance of this work is that as school administrators educational knowledge levels increase, so does the personal knowledge base that they can contribute to the communities in which they live and work. In this way, the educational reach of the doctor of education program leads to improvements in the larger Alabama Black Belt through both community and P-12 school interactions.

Nowadays, ample industries are fascinated to look for high strength and light weight materials for the development of robust parts. Because of light weight and high stiffness to weight ratio; usage of aluminum parts is growing rapidly, especially in automotive engineering. Process improvement of Al alloys and their grain structure refinement is the current area of interest in casting companies. In this research work, an investigation has been carried out to enhance the process improvement of die casting by optimization of various significant parameters and their refinement of grains by the effect of Nb-C novel grain refiner.

L27 orthogonal array (OA) has been considered to optimize the preferred casting input parameters such as molten metal temperature (°C), die temperature (°C), injection pressure (bar), Al-3.5Nb-1.5 C novel grain refiner and Ni alloying additions as key process parameters in order to increase the quality and efficiency of Al-9Si-3Cu aluminum alloy die casting by reducing the porosity formation.

It was observed that the porosity values have significantly decreased from 0.88% to 0.25% particularly at 0.1 wt.% of new grain refiner and 0.5 wt. % of Al-6Ni master alloy. As per the ANOVA results, it was observed that Al-3.5FeNb-1.5 C grain refiner (F value 2609.22), Al-6Ni alloying addition (F value 1329.13), molten metal temperature (F value 1002.43) and, injection pressure (F value 448.06) are the factors that significantly affects the porosity, whereas die temperature was found to be insignificant. The results show that new grain refiner is one the most significant factor among the other selected parameters. The contribution of the new grain refiner to the variation of mean casting porosity is around 57.74%. confidence interval (CI) has also been estimated as 0.013 for 95% consistency level to validate the predicted range of optimum casting porosity of aforesaid alloy.

To the best of the authors' knowledge, no study has been conducted in the past to investigate the combined effect of these die casting parameters and composition factors for the development of Al-Si robust cast parts. The paper represents original research and provides new information for the fabrication of die casting parts.

The purpose of this paper is to introduce four new organic dyes based on naphthalimide for dye-sensitized solar cells (DSSCs).

Four new dyes based on naphthalimide with substitutions of amine and acetylamine in position C4 were designed in conjugation with substituted carbazole as donor–acceptor (D-A) architecture. The absorption and emission characteristics of the prepared dyes were evaluated in H₂O, DMF and their mixture (DMF:H₂O = 1:1). The feasibility of electron transfer in the DSSCs structure and energy levels were evaluated using electrochemical and density functional theory, which confirm the use of dyes in the DSSCs structure. The DSSCs were prepared using an individual strategy and their optical properties were investigated under the light of AM 1.5.

The prepared dyes exhibit orange color with strong emission at λem = 530–570 nm due to charge transfer with a positive solvatochromic effect. The efficiency of DSSCs based on Dye1-4 1 is: 3.69%, 3.71%, 4.69% and 4.76%. Therefore, the power efficiency increases by about 29 % in the presence of acetylamine group.

The design of new structures of organic dyes should be accompanied by the development of optical and electrical properties. In other words, in addition to the continuous production of electrons, efficient dyes must also be resistant to light to increase the life of the device.

Organic dyes play a key role in the production of electrons in the DSSCs structure. The engineering of these structures and the introduction of widely used but low cost types can play an important role in the development of clean energy production.

The application of organic dyes based on naphthalimide was evaluated in the DSSCs structure and its photovoltaic properties were investigated.

The cross-docking strategy has a significant influence on supply chain and logistics efficiency. This paper aims to investigate the most suitable and efficient way to schedule the transfer of logistics activities and present a meta-heuristic method of the truck scheduling problem in cross-docking logistics. A truck scheduling problem with products time window is investigated with objectives of minimizing the total product transshipment time and earliness and tardiness cost of outbound trucks.

This research proposed a meta-heuristic method for the truck scheduling problem with products time window. To solve the problem, a lower bound of the problem is built through a novel two-stage Lagrangian relaxation problem and on account of the NP-hard nature of the truck scheduling problem, the novel red deer algorithm with the mechanism of the heuristic oscillating local search algorithm, as well as adaptive memory programming was proposed to overcome the inferior capability of the original red deer algorithm in the aspect of local search and run time.

Theory analysis and simulation experiments on an industrial case of a cross-docking center with a product’s time window are conducted in this paper. Satisfactory results show that the performance of the red deer algorithm is enhanced due to the mechanism of heuristic oscillating local search algorithm and adaptive memory programming and the proposed method efficiently solves the real-world size case of truck scheduling problems in cross-docking with product time window.

The consideration of products time window has very realistic significance in different logistics applications such as cold-chain logistics and pharmaceutical supply chain. Furthermore, the novel adaptive memory red deer algorithm could be modified and applied to other complex optimization scheduling problems such as scheduling problems considering energy-efficiency or other logistics strategies.

For the first time in the truck scheduling problem with the cross-docking strategy, the product’s time window is considered. Furthermore, a mathematical model with objectives of minimizing the total product transshipment time and earliness and tardiness cost of outbound trucks is developed. To solve the proposed problem, a novel adaptive memory red deer algorithm with the mechanism of heuristic oscillating local search algorithm was proposed to overcome the inferior capability of genetic algorithm in the aspect of local search and run time.