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Discusses development of an open architecture multi‐robot system that can be used for training engineers in the area of networked‐based multi‐robot programming.

The robots are operated under their original controllers connected together through a network of supervisory computers. A preemptive multi‐tasking real time operating system (RTOS) running on these computers is used to perform supervisory and cooperative tasks involving multiple robots. The software environment allows for controlling the motion of one or more robots and their interaction with other devices.

Robots can be networked to perform more elaborate tasks.

The environment is used to train undergraduate and graduate students on how to develop software for various robotic applications, including scheduling techniques, cooperative manipulation, collision avoidance, and emerging robotic applications.

There is a growing need to train and support educators to introduce or enhance aspects of sustainability into post-secondary curriculum. The authors provide an overview of integration of curricular sustainability development and education as well as related institutional leadership at the post-secondary level. Turning to educational development for sustainability education, the authors share tools and resources to support educators from any discipline, to introduce, integrate, and/or enhance sustainability in their course, program, or initiative. The authors found very few examples of workshops to post-secondary teachers. For one such example, the Sustainability Education Intensive, a three-day workshop that the authors designed and led at the University of British Columbia. The authors summarize the workshop aspects that two years of participants found helpful, and how workshop involvement affected them as sustainability educators. The authors encourage post-secondary institutions to provide support in the form of workshops, resources, and funding to help educators introduce or enhance aspects of sustainability into their courses and programs. Students are asking for this, and, as they are future leaders, it is important that educators address the numerous environmental, social and economic issues that demand attention.

This study sought to better understand how to support and plan for a collaborative effort that brought educators together from three universities in the United States and Pakistan. This project sough to foster collaborative relationships between the two countries by expanding knowledge, collaboration, and capacity in middle schools in the Punjab region of Pakistan with a particular focus on underrepresented students and middle grades STEM instruction.

This study was informed through the use of formative survey data gathered from the workshop participants throughout the course of the week. The researchers conducted pre and post surveys of 22 participants using Likert scale items.

This project provided insights regarding curriculum alignment, engaging communication, teacher-centered formative data. These findings offered insights on how to grow as reflective practitioners and researchers, and how to form a robust multi-national professional learning community.

The survey data were gathered from participants who willingly sought professional development in one region of Pakistan. The sample was small (four participating middle schools and one local university) and thus the findings cannot be necessarily generalized to a greater population.

This project provides practical insights of how teams can work together in regard to building a professional learning community. Teams can plan with intentionality, foster various modes of discussion, and empower both teachers and students to inquire, solve problems, and share their insights.

The STEM topics in this study are important across continents. Navigating time constraints and distance is feasible through communication, attention to objectives and clarity in goals, and a desire to learn outside of one’s usual comfort zones.

This project was unique in the time and space in which it was designed and implemented, yet it offers value in fostering ongoing collaboration through various modalities and in being intentional in the planning process.

The Russia–Ukraine war has disrupted the wheat supply worldwide. Given that wheat is one of the most important agri-food products in the world, it is necessary to pay attention to the wheat supply chain during the global crises. The use of resilience strategies is one of the solutions to face the supply chain disruptions. In addition, there is a possibility of multiple crises occurring in global societies simultaneously.

In this research, the resilience strategies of backup suppliers (BS) and inventory pre-prepositioning (IP) were discussed in order to cope with the wheat supply chain disruptions. Furthermore, the p-Robust Scenario-based Stochastic Programming (PRSSP) approach was used to optimize the wheat supply chain under conditions of disruptions from two perspectives, feasibility and optimality.

After implementing the problem of a real case in Iran, the results showed that the use of resilience strategy reduced costs by 9.33%. It was also found that if resilience strategies were used, system's flexibility and decision-making power increased. Besides, the results indicated that if resilience strategies were used and another crisis like the COVID-19 pandemic occurred, supply chain costs would increase less than when resilience strategies were not used.

In this study, the design of the wheat supply chain was discussed according to the wheat supply disruptions due to the Russia–Ukraine war and its implementation on a real case. In the following, various resilience strategies were used to cope with the wheat supply chain disruptions. Finally, the effect of the COVID-19 pandemic on the wheat supply chain in the conditions of disruptions caused by the Russia–Ukraine war was investigated.

Due to the importance of quality to customers, this study considers criteria of quality and profit and optimizes both in a multi-echelon cold chain of perishable agricultural products whose quality immediately begins to deteriorate after harvest. The two objectives of the proposed cold chain are to maximize profit and quality. Since postharvest quality loss in the supply chain depends on various decisions and factors, in addition to strategic decisions, the authors consider the temperature setting in refrigerated facilities and transportation vehicles due to the unfixed shelf life of the products which is related to the temperature found by Arrhenius formula.

The authors use bi-objective mixed-integer nonlinear programming to design a four-echelon supply chain. The authors integrate the supply chain echelons to detect the sources and factors of quality loss. The four echelons include supply, processing, storage and customer. The decisions, including facility location, assigning nodes of each echelon to corresponding nodes from the adjacent echelon, allocation of vehicles to transport the products from farms to wholesalers, processing selection, and temperature setting in refrigerated facilities, are made in an integrated way. Model verification and validation in the case study are done based on three perishable herbal plants.

The model obtains a 29% profit against a total cost of 71 and 93% of original quality of the crops is maintained, indicating a 7% quality loss. The final quality of 93% is the result of making a US$6m investment in the supply chain, including the procurement of high-quality raw materials; facility establishment; high-speed, high-capacity vehicles; location assignment; processing selection and refrigeration equipment in the storage and transportation systems, helping to maximize both the final quality of the products and the total profit.

The proposed supply chain model should help managers with modeling decisions, especially when it comes to cold chains for agricultural products. The model yields these results – optimal location-allocation decisions for the facilities to minimize distances between the network nodes, which save time and maintain the majority of the products’ original quality; choosing the most appropriate processing method, which reduces the perishability rate; providing high-capacity, high-speed vehicles in the logistics system, which minimizes transportation costs and maximizes the quality; and setting the right temperature in the refrigerated facilities, which mitigates the postharvest decay reaction rate of the products.

Comparison of the results of the present research with those of the traditional chain (obtained through experts) shows that since the designed chain increases the profit as well as the final quality, it has benefits for the main chain stakeholders, which are customers of agricultural products. This study model is expected to have a positive impact on the environment by placing strong emphasis on quality and preventing excessive waste generation and air pollution by imposing a financial penalty on extra demand production.

Since profit and quality of the final product are two important factors in all cultures and communities, the proposed supply chain model can be used in any food industry around the world. Applying the proposed model induces growth in local industries and promotes the culture of prioritizing quality in societies.

To the best of the authors’ knowledge, this is the first research on a bi-objective four-echelon (supply, processing, storage and customer) postharvest supply chain for agricultural products including that integrates transportation logistics and considers the deterioration rate of products as a time-dependent variable at different levels of decision-making.

This study focuses on a specific method of meat production that involves carcass purchase and meat production by packing facilities with a novel two-stage model that simultaneously considers location-routing and inventory-production operating decisions. The considered problem aims to reduce variable and fixed transportation and production costs, inventory holding cost and the cost of opening cold storage facilities.

The proposed model encompasses a two-stage model consisting of a single-echelon and a three-echelon many-to-many network with deterministic demand. The proposed model is a mixed-integer linear programming (MILP) model which was tested with the general algebraic modelling system (GAMS) software for a real-world case study in Iran. A sensitivity analysis was performed to examine the effect of retailers' holding capacity and supply capacity at carcass suppliers.

In this research, the number of products transferred at each level, the number of products held, the quantity of red meat produced, the required cold storage facilities and the required vehicles were optimally specified. The outcomes indicated a two percent (2%) decrease in cost per kg of red meat. Eventually, the outcomes of the first and second sensitivity analysis indicated that reduced retailers' holding capacity and supply capacity at carcass suppliers leads to higher total costs.

This research proposes a novel multi-period location-inventory-routing problem for the red meat supply chain in an emerging economy with a heterogeneous vehicle fleet and logistics decisions. The proposed model is presented in two stages and four-echelon including carcass suppliers, packing facilities, cold storage facilities and retailers.

This paper critically analyzes the International Olympic Committee's 2000 global marketing campaign titled “Celebrate Humanity”. Released prior to the 2000 Summer Games, this campaign capitalized on recent cultural trends by focusing on multicultural inclusivity and the idea that sport could contribute to world peace. Using this campaign as our case study, we demonstrate the possibilities for both local consumption and interpretation of a global campaign within the specific cultural context of the United States.

The purpose of this paper is to investigate how the dc-link voltage for the converter of a wind generator should be selected, i.e. to determine the losses in the generator and the converter when using various dc-link voltage levels.

To presents the efficiency evaluation of 5 MW wind turbine generating systems, two 5 MW surface mounted permanent magnet synchronous generators (PMSG) with medium and low rated voltage is designed. A two-level transistor converter is considered for ac/dc conversion. Three different dc-link voltage levels are used. By using these voltage levels the PMSG is utilized in slightly different ways.

It is found that the system with the lower voltage machine has slightly higher annual energy efficiency compare to the higher voltage system. Furthermore, it is shown that the best choice for the dc-link voltage level is a voltage between the minimum voltage which gives the desired torque and the voltage which gives Maximum Torque Per Ampere.

A procedure as well as investigations with quantified results on how to find the highest complete drive system efficiency for a wind turbine application. Based on two given PMSG, the most energy-efficient dc-link voltage has been established.

Thermal analysis of electrical machines is usually performed by using numerical methods or lumped parameter thermal networks depending on the desired accuracy. The analytical prediction of temperature distribution based on the formal resolution of thermal partial differential equations (PDEs) by the harmonic modeling technique (or the Fourier method) is uncommon in electrical machines. Therefore, this paper aims to present a two-dimensional (2D) analytical model of steady-state temperature distribution for permanent-magnet (PM) synchronous machines (PMSM) operating in generator mode.

The proposed model is based on the multi-layer models with the convolution theorem (i.e. Cauchy’s product theorem) by using complex Fourier’s series and the separation of variables method. This technique takes into the different thermal conductivities of the machine parts. The heat sources are determined by calculating the different power losses in the PMSM with the finite-element method (FEM).

To validate the proposed analytical model, the analytical results are compared with those obtained by thermal FEM. The comparisons show good results of the proposed model.

A new 2D analytical model based on the PDE in steady-state for full prediction of temperature distribution in the PMSM takes into account the heat transfer by conduction, convection and radiation.

The main purpose of this paper is to propose a quasi-impedance source (QIS) converter fed switched reluctance motor (SRM) drive. The proposed converter topology is configured for DC link capacitance minimization and power factor (PF) correction.

A QIS converter is used as a front end converter to reduce the bulk capacitance requirement during current commutation and to decline the power ripple. To improve the PF with reduced total harmonic distortion at the input current, the PF current control loop is merged with the QIS converter control loop.

The overall SRM drive speed is regulated over a wide range by controlling the DC link voltage. The voltage regulation can be achieved by pulse width modulation of the QIS converter. Hence, the overall system efficiency has been improved by operating the proposed converter at a low switching frequency. Moreover, the proposed QIS converter uses an advanced repetitive controller to achieve voltage regulation and fewer ripples in torque.

The steady state and dynamic analyzes have been performed on the proposed drive topology. The performance of the proposed topology has been simulated through MATLAB/Simulink environment. A hardware prototype with a processor of Xilinx SPARTAN 6 field-programmable gate array has been used to validate the experimental response with the simulation results.