Flexible manufacturing systems (FMSs) have widely expanded in industry sectors all over the world. Scheduling is one of the problems that face the life cycle of FMSs. This paper introduces the simultaneous scheduling problem of automated guided vehicles (AGVs) and machines in FMSs. The study is based on discrete event simulation (DES) to solve that problem using benchmark data used by previous studies. The objective of this study is to determine the starting and completion times of each job to minimise the makespan. The results validate the robustness of the simulation model, especially for large-scale problems. Furthermore, they are compared against the other approaches and show consistency.

Flexible manufacturing systems (FMSs) have widely expanded in industry sectors all over the world. Scheduling is one of the problems that face the life cycle of FMSs. This paper introduces the simultaneous scheduling problem of automated guided vehicles (AGVs) and machines in FMSs. The study is based on discrete event simulation (DES) to solve that problem using benchmark data used by previous studies. The objective of this study is to determine the starting and completion times of each job to minimise the makespan. The results validate the robustness of the simulation model, especially for large-scale problems. Furthermore, they are compared against the other approaches and show consistency.

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Over the past few years, dynamic spectrum access has been gaining an increasing attention as a solution to the spectrum scarcity problem. In this paper, a primary user detection technique based on Maximum A Posteriori estimation is proposed for dynamic spectrum access networks. In the proposed technique, a set of secondary users acting as sensing nodes send their individual decisions about the existence of the primary user to a central fusion center. The fusion center uses the received data to form a codeword then, applies the maximum a posteriori estimation rule to make a final decision regarding the presence of the primary user. The proposed technique takes into consideration the accuracy of the local decisions provided by the secondary users when making a final decision. In this paper, we analyze the performance of the proposed scheme and derive closed-form expressions for the upper bounds of the false alarm and misdetection probabilities. The results show that the proposed technique outperforms other combining techniques in terms of its ability to detect the primary user and, accordingly, minimizes the harmful interference to the licensed network. Moreover, the proposed technique achieves better performance at a lower number of reporting secondary users which compensates for the complexity of the maximum a posteriori estimation.

Over the past few years, dynamic spectrum access has been gaining an increasing attention as a solution to the spectrum scarcity problem. In this paper, a primary user detection technique based on Maximum A Posteriori estimation is proposed for dynamic spectrum access networks. In the proposed technique, a set of secondary users acting as sensing nodes send their individual decisions about the existence of the primary user to a central fusion center. The fusion center uses the received data to form a codeword then, applies the maximum a posteriori estimation rule to make a final decision regarding the presence of the primary user. The proposed technique takes into consideration the accuracy of the local decisions provided by the secondary users when making a final decision. In this paper, we analyze the performance of the proposed scheme and derive closed-form expressions for the upper bounds of the false alarm and misdetection probabilities. The results show that the proposed technique outperforms other combining techniques in terms of its ability to detect the primary user and, accordingly, minimizes the harmful interference to the licensed network. Moreover, the proposed technique achieves better performance at a lower number of reporting secondary users which compensates for the complexity of the maximum a posteriori estimation.

Over the past few years, dynamic spectrum access has been gaining an increasing attention as a solution to the spectrum scarcity problem. In this paper, a primary user detection technique based on Maximum A Posteriori estimation is proposed for dynamic spectrum access networks. In the proposed technique, a set of secondary users acting as sensing nodes send their individual decisions about the existence of the primary user to a central fusion center. The fusion center uses the received data to form a codeword then, applies the maximum a posteriori estimation rule to make a final decision regarding the presence of the primary user. The proposed technique takes into consideration the accuracy of the local decisions provided by the secondary users when making a final decision. In this paper, we analyze the performance of the proposed scheme and derive closed-form expressions for the upper bounds of the false alarm and misdetection probabilities. The results show that the proposed technique outperforms other combining techniques in terms of its ability to detect the primary user and, accordingly, minimizes the harmful interference to the licensed network. Moreover, the proposed technique achieves better performance at a lower number of reporting secondary users which compensates for the complexity of the maximum a posteriori estimation.

Abstract: As a result of increased global concern about sustainability and climate change issues; developed Countries committed to finding techniques to conserve resources and achieve a balanced development. Achieving such goals requires more efficient and responsive urban management tools. Accustomed tools are ineffective to enabling cities to achieve such goals. Since 1990, global awareness has been directed towards using ICT in urban management. Creating a smart self-organizing system to manage and monitor cities' performance can accelerate improving of economic competitiveness, sustainability and quality of life. Egypt has an ambitious strategy: Egypt's 2030 vision for achieving sustainability and improving the quality of life. while, current urban management systems cannot accomplish such tasks. Therefore, this paper aimed to develop a conceptual model for a GIS-based urban management tool that enabling Egyptian cities to achieve Egypt's vision 2030. To achieve this goal the researcher relied on: 1) Recognizing the city's self-organizing system and identifying the role of geographic information systems in managing the urban transformation process and monitoring the city's performance; 2) Evaluating the capability of key performance indicators that were developed to measure the achievement of Egypt's 2030 vision. To achieve the first goal, a systematic literature review was conducted; while to achieve the second goal, KPIs of Egypt's 2030 vision were assessed with using strategic objectives/KPIs matrix as well as using comparative analysis with international evaluating systems. The contribution of this paper is twofold: 1 - Theoretical contribution that built the bridge between the theory of self-organizing system and the management of cities; 2- Practical contribution represented by: a) the conceptual model, which helps in understanding the components of the smart system for monitoring and evaluating the performance of cities, and the relationship between them; and b) The evolved list of KPIs that track the city's performance in the six domains of city (economy, environment, mobility, living, community, and governance), to ensure achieving desired goals of Egypt's 2030 vision.