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Optimal Routing and Scheduling in E-commerce Logistics using Crowdsourcing Strategies
No full textA Master of Science thesis in Engineering Systems Management by Eman Mohamed entitled, "Optimal Routing and Scheduling in E-commerce Logistics using Crowdsourcing Strategies," submitted in July 2017. Thesis advisor is Dr Malick Ndiaye. Soft and hard copy available.The internet penetration has transformed the way people shop and has enlarged online shopping popularity. From 2014 to 2016, electronic commerce has increased by 50% and the forecast predicts a three fold increase by 2020. This growth creates various challenges for logistics providers when it comes to home deliveries. Researches showed that the last mile delivery accounts for 13% to 75% of logistics costs and is currently regarded as the most problematic and most polluting section of the entire supply chain. Till now, there is no straight forward solution but technology is paving the way to optimize this part of the logistical process. At the same time, the popularity of mobile applications is an opportunity for companies as they create valuable connections between companies and customers. This research aims to benefit from these connections to finish the last leg of delivery through the use of crowdsourcing. The idea is to use a pool of citizens to deliver products from several lockers distributed around thecity to consumers' doorsteps. Deliveries occur during a set time window for each customer taking into consideration drivers' capacity and availability time. The problem as described is proven to be NP-Hard, thus its solution should be verified using exactand heuristic-based techniques for large size instances. We propose two Integer Linear programming (ILP) formulations with the objective of minimizing the total reward paid to crowd-workers through optimum assignment of parcels to drivers and optimum routing for each driver. The proposed models are first solved using Lingo software and their run time compared. Furthermore, a Variable Neighborhood Search (VNS) algorithm that uses a Variable Neighborhood Descent (VND) in its local search phase is developed using C++ programming language to solve large-size problems in a reasonable time. The proposed algorithm returned exact and near-optimal solutions within few seconds depending on the problem's size and all results were obtained within an average of 20 seconds. A sensitivity analysis is conducted by varying the main model parameters to determine inputs' their impact on the problem. Although there was a clear correlation between some parameters and the total delivery cost, some other experiments were inconclusive.College of EngineeringDepartment of Industrial EngineeringMaster of Science in Engineering Systems Management (MSESM
Al Jissir: Abu Dhabi
No full textAn Urban Planning Research Workshop II (UPL 682) project by Ali Ahmed, Atousa Aslaminezhad, and Fajer Alenezi entitled, "Al Jissir: Abu Dhabi", submitted in Spring 2017. Project supervisor is Prof. Rafael Pizarro
Sensor-Based Signer Independent Continuous Arabic Sign Language Recognition
No full textA Master of Science thesis in Mechatronics Engineering by Mohamed Hassan entitled, "Sensor-Based Signer Independent Continuous Arabic Sign Language Recognition," submitted in May 2017. Thesis advisor is Dr. Khaled Assaleh and thesis co-advisor is Dr. Tamer Shanableh. Soft and hard copy available.The deaf community relies on sign language as the primary means of communication. For the millions of people around the world who suffer from hearing loss, interaction with hearing people is quite difficult. The main objective of Sign language recognition (SLR) is the development of automatic SLR systems to facilitate communication with the deaf community. SLR as a whole is considered a relatively new area. Arabic SLR (ArSLR) specifically did not receive much attention until recent years. This work presents a comprehensive comparison between two different recognition techniques for continuous ArSLR, namely a Modified k-Nearest Neighbor (MKNN) which is suitable for sequential data and Hidden Markov Models (HMMs) techniques based on two different toolkits. Additionally, in this thesis, two new ArSL datasets composed of 40 Arabic sentences are collected using Polhemus G4 motion tracker and a camera. An existing glove-based dataset is employed in this work as well. The three datasets are made publicly available to the research community. The advantages and disadvantages of each data acquisition approach and classification technique are discussed in this thesis. In the experimental results chapter, it has been shown that data acquisition using only the motion tracker results in accurate sentence recognition similar to that generated by the glove-based acquisition system. The modified KNN solution is inferior to HMMs in terms of the computational time required for classification. Moreover, the performance of Polhemus G4 and RASR on multiple users is examined and promising results have been achieved.College of EngineeringMultidisciplinary ProgramsMaster of Science in Mechatronics Engineering (MSMTR
Incremental and Heuristic Algorithms for Deriving Adaptive Distinguishing Test Cases for Nondeterministic Finite State Machines
No full textA Master of Science thesis in Computer Engineering by Ayat Saleh entitled, "Incremental and Heuristic Algorithms for Deriving Adaptive Distinguishing Test Cases for Nondeterministic Finite State Machines," submitted in September 2017. Thesis advisor is Dr. Khaled El-Fakih. Soft and hard copy available.Many methods are proposed for the construction of distinguishing test cases (DTCs) based on a specification given in the form of a Finite State Machine (FSM). In FSM-based testing, we have a black-box FSM Implementation Under Test (IUT) about which we lack some information, and we want to conclude this information by using the applied input sequences of DTCs to the IUT, then by observing the output responses to the applied input sequences final conclusions about the IUTare drawn. A DTC is adaptive if the next input of a DTC is selected based on the previously observed outputs. In this thesis, we propose an incremental approach, called Inc, for the construction of an adaptive DTC for a given set of states of a nondeterministic FSM. In addition, two heuristics are proposed for the derivation of adaptive DTCs. The first heuristic, called H, uses depth first search for a given fixed height while appropriately utilizing hashing to speed up the search for a DTC. The second heuristic, called Hc, is similar to the first; however, it uses a cost function for ordering the inputs to be considered while conducting the search. Comprehensive experiments are conducted, using both real and randomly generated FSMs, to assess the existence of DTCs and compare the performance of the proposed approaches. According to these experiments, in terms of execution time, Inc usually outperforms an existing non-incremental algorithm, called A, when a DTC does not exist. However, in contrary to the H and Hc methods, both A and Inc do not scale well for large size FSMs. Both H and Hc have comparable execution time; however, for large size FSMs, in terms of quality of obtained solutions (length of obtained DTC), usually Hc outperforms H.College of EngineeringDepartment of Computer Science and EngineeringMaster of Science in Computer Engineering (MSCoE
Centralized Control Scheme for Energy Management in Smart Microgrids
No full textA Master of Science thesis in Electrical Engineering by Wla Elshafye Malik Elamin entitled, "Centralized Control Scheme for Energy Management in Smart Microgrids," submitted in April 2017. Thesis advisor is Dr. Mostafa Shaaban. Soft and hard copy available.The development in smart grid technologies will authorize consumers to participate in the decision making of their electricity consumption. This participation in decision making is the called demand side management (DSM). DSM allows the customers to optimally manage their loads and hence reduce their energy bills and overall consumption. This work proposes a new real-time energy management system (EMS) for smart microgrids (MGs) including DSM with several distributed energy resources (DER) technologies, such as photovoltaic panels, dispatchable distributed generation (DG), capacitor banks, and battery energy storage systems (BESS). The developed EMS consists of three main units that are controlled by the centralized MG controller (MGC). The aim of the MGC is to optimally schedule the grid and customers' assets to benefit both the grid operators and the customers. The MGC utilizes the rolling horizon concept to manage real-time information and to provide the plug-and-play option for all controllable devices such as controllable loads and DER. The three units managed by the MGC are the data collection and storage unit, the forecasting unit and the optimization unit. The optimization unit receives the current and forecasted information from the other units; then, it develops the optimal scheduling decisions for all controllable devices with the target of reducing the overall operating costs while meeting the customers' requirements. The MG can either operate in grid-connected mode or in islanded mode of operation. In this work, both modes are considered. Simulation results on a typical MG system of the proposed approach are compared to the results of the traditional day-ahead approach. The proposed approach results show same savings as the day-ahead approach. However, unlike the day-ahead approach, the proposed approach is more robust to disturbances and fast changes of PV panels' output. Moreover, the proposed approach can accommodate changes in customers' preferences and new connected equipment in a timely manner.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
Closing the loop: Empirical evidence for a positive feedback model of IT business value creation
No full textResearchers have established that information technology (IT) can improve firms' productivity. Whether improved productivity leads to additional investment in IT, however, remains largely uninvestigated. In this paper, we consider whether the relationship between productivity and subsequent IT investment might be positive, negative, or ad hoc, and hypothesize that this relationship is positive. We analyze seven years of panel data from 1,223 healthcare firms and present empirical evidence supporting our hypothesis. When our finding is combined with extant research, it becomes reasonable to propose that unidirectional causality does not fully describe the process of IT business value creation. Instead, we argue that existing static models of IT business value with unidirectional causality can be recast as dynamic models that explicitly incorporate multiple time periods and a positive feedback relationship to more accurately capture the complexity of this process. The creation of IT business value can thus be understood as a positive feedback model where productivity in a given time period leads to IT investment in a future time period, where IT investment builds the stock of IT inputs, and where those IT inputs then impact productivity, beginning the cycle anew
A Smart Home Energy Management System Using IoT and Big Data Analytics Approach
No full textIncreasing cost and demand of energy has led many organizations to find smart ways for monitoring, controlling and saving energy. A smart Energy Management System (EMS) can contribute towards cutting the costs while still meeting energy demand. The emerging technologies of Internet of Things (IoT) and Big Data can be utilized to better manage energy consumption in residential, commercial, and industrial sectors. This paper presents an Energy Management System (EMS) for smart homes. In this system, each home device is interfaced with a data acquisition module that is an IoT object with a unique IP address resulting in a large mesh wireless network of devices. The data acquisition System on Chip (SoC) module collects energy consumption data from each device of each smart home and transmits the data to a centralized server for further processing and analysis. This information from all residential areas accumulates in the utility's server as Big Data. The proposed EMS utilizes off-the-shelf Business Intelligence (BI) and Big Data analytics software packages to better manage energy consumption and to meet consumer demand. Since air conditioning contributes to 60% of electricity consumption in Arab Gulf countries, HVAC (Heating, Ventilation and Air Conditioning) Units have been taken as a case study to validate the proposed system. A prototype was built and tested in the lab to mimic small residential area HVAC systems1
Connecting Water Resources across Political Borders: A Pearl River Delta Special Ecological Area
No full textSituated between several interdependent political and economic zones of southern China's Pearl River Delta, the Pearl River Delta Special Ecological Area (PRD SEA) project explores the possibility that regional administrative boundaries could be softened and redrawn along ecological boundaries. With the advent of global sea level rise and its impact on the fragile fresh water ecology and huge population of the Pearl River Delta, the project proposes novel ways to share fresh water and wastewater across political zones to better administer and profit from the distribution of water resources. Climate change, urbanization, and pollution from industrial and agricultural development threaten the steady supply of fresh water to the Pearl River Delta and its cities, while population growth in the region only increases demand. At the same time, Hong Kong, Macau and Shenzhen's increasing economic, political and cultural interdependency presents the possibility to tackle these challenges holistically. Layering a regional water resource infrastructure onto existing and new industrial, residential, agricultural and transportation armatures would transcend borders and create new economic markets through ecologically sustainable practices
Designing constructed wetlands for reclamation of pretreated wastewater and stormwater
No full textWastewater reclamation is getting greater attention as an alternative to conventional approaches to wastewater treatment and water supply due to increasing water stress coupled with more stringent water quality limitation for discharge of treated wastewater. Among the few technologies adopted in the field for wastewater reclamation, constructed wetlands have been used to reclaim both primary and secondary treated wastewater in regions with arid and humid climates. This paper summarizes the widely adopted guidelines that need to be considered when designing constructed wetlands for wastewater reclamation, discusses the capacity of wetland treatment systems for water reuse while assessing the status of full-scale constructed wetlands designed for wastewater reclamation, and develops contaminant loading charts as a design tool based on the performance of existing full-scale constructed wetlands deployed for wastewater reclamation. It is evident that constructed wetland systems provide a viable means to treat wastewater to the levels required for low-quality reuses such as restricted irrigation and impoundment. It is challenging for constructed wetlands to consistently meet microbiological guidelines for high-quality reuses such as unrestricted agricultural and urban reuses. Wastewater reclaimed through constructed wetlands is used mainly for agricultural and landscape irrigation, groundwater recharge, indirect potable reuse, and environmental reuse. Surface area and hydraulic loading rate of constructed wetlands to be deployed for wastewater reclamation can be estimated with contaminant loading charts derived from monitoring data of existing full-scale operations
Business in War Zones: How Companies Promote Peace in Iraq
No full textThe private sector is vital to building and sustaining peace. These efforts are often recognized as “Business for Peace” or “Peace through Commerce.” Academic research on Business for Peace is almost twenty years old and tends to be theoretical. This paper is the first to present qualitative findings on businesses operating in an active violent conflict such as the case of Iraq. Companies in Iraq operate under the constant threat of violence and yet many still try to enhance peace through operations. We interviewed more than 40 participants who were business owners, managers, government officials, and international policymakers who were active in the Iraqi theater. We discuss our findings that relate to the perception of company activities as peace enhancing into four categories: capacity building, rule of law, social cohesion, and local engagement. Our findings support the existing business and peace categories of rule of law and social cohesion. Our findings also suggest that current theory may be missing capacity building and local engagement as important business activities to promote peace. We conclude by noting the limitations of the paper and the need for more qualitative research