Towards Climate Neutrality: A Comprehensive Overview of Sustainable Operations Management, Optimization, and Wastewater Treatment Strategies

Various studies have been conducted in the fields of sustainable operations management, optimization, and wastewater treatment, yielding unsubstantiated recovery. In the context of Europes climate neutrality vision, this paper reviews effective decarbonization strategies and proposes sustainable approaches to mitigate carbonization in various sectors such as building, energy, industry, and transportation. The study also explores the role of digitalization in decarbonization and reviews decarbonization policies that can direct governments action towards a climate-neutral society. The paper also presents a review of optimization approaches applied in the fields of science and technology, incorporating modern optimization techniques based on various peer-reviewed published research papers. It emphasizes non-conventional energy and distributed power generating systems along with the deregulated and regulated environment. Additionally, this paper critically reviews the performance and capability of micellar enhanced ultrafiltration (MEUF) process in the treatment of dye wastewater. The review presents evidence of simultaneous removal of co-existing pollutants and explores the feasibility and efficiency of biosurfactant in-stead of chemical surfactant. Lastly, the paper proposes a novel firm-regulator-consumer interaction framework to study operations decisions and interactive cooperation considering the interactions among three agents through a comprehensive literature review on sustainable operations management. The framework provides support for exploring future research opportunities

An Emergent Architecture for Scaling Decentralized Communication Systems (DCS)

With recent technological advancements now accelerating the mobile and wireless Internet solution space, a ubiquitous computing Internet is well within the research and industrial community's design reach - a decentralized system design, which is not solely driven by static physical models and sound engineering principals, but more dynamically, perhaps sub-optimally at initial deployment and socially-influenced in its evolution. To complement today's Internet system, this thesis proposes a Decentralized Communication System (DCS) architecture with the following characteristics: flat physical topologies with numerous compute oriented and communication intensive nodes in the network with many of these nodes operating in multiple functional roles; self-organizing virtual structures formed through alternative mobility scenarios and capable of serving ad hoc networking formations; emergent operations and control with limited dependency on centralized control and management administration. Today, decentralized systems are not commercially scalable or viable for broad adoption in the same way we have to come to rely on the Internet or telephony systems. The premise in this thesis is that DCS can reach high levels of resilience, usefulness, scale that the industry has come to experience with traditional centralized systems by exploiting the following properties: (i.) network density and topological diversity; (ii.) self-organization and emergent attributes; (iii.) cooperative and dynamic infrastructure; and (iv.) node role diversity. This thesis delivers key contributions towards advancing the current state of the art in decentralized systems. First, we present the vision and a conceptual framework for DCS. Second, the thesis demonstrates that such a framework and concept architecture is feasible by prototyping a DCS platform that exhibits the above properties or minimally, demonstrates that these properties are feasible through prototyped network services. Third, this work expands on an alternative approach to network clustering using hierarchical virtual clusters (HVC) to facilitate self-organizing network structures. With increasing network complexity, decentralized systems can generally lead to unreliable and irregular service quality, especially given unpredictable node mobility and traffic dynamics. The HVC framework is an architectural strategy to address organizational disorder associated with traditional decentralized systems. The proposed HVC architecture along with the associated promotional methodology organizes distributed control and management services by leveraging alternative organizational models (e.g., peer-to-peer (P2P), centralized or tiered) in hierarchical and virtual fashion. Through simulation and analytical modeling, we demonstrate HVC efficiencies in DCS structural scalability and resilience by comparing static and dynamic HVC node configurations against traditional physical configurations based on P2P, centralized or tiered structures. Next, an emergent management architecture for DCS exploiting HVC for self-organization, introduces emergence as an operational approach to scaling DCS services for state management and policy control. In this thesis, emergence scales in hierarchical fashion using virtual clustering to create multiple tiers of local and global separation for aggregation, distribution and network control. Emergence is an architectural objective, which HVC introduces into the proposed self-management design for scaling and stability purposes. Since HVC expands the clustering model hierarchically and virtually, a clusterhead (CH) node, positioned as a proxy for a specific cluster or grouped DCS nodes, can also operate in a micro-capacity as a peer member of an organized cluster in a higher tier. As the HVC promotional process continues through the hierarchy, each tier of the hierarchy exhibits emergent behavior. With HVC as the self-organizing structural framework, a multi-tiered, emergent architecture enables the decentralized management strategy to improve scaling objectives that traditionally challenge decentralized systems. The HVC organizational concept and the emergence properties align with and the view of the human brain's neocortex layering structure of sensory storage, prediction and intelligence. It is the position in this thesis, that for DCS to scale and maintain broad stability, network control and management must strive towards an emergent or natural approach. While today's models for network control and management have proven to lack scalability and responsiveness based on pure centralized models, it is unlikely that singular organizational models can withstand the operational complexities associated with DCS. In this work, we integrate emergence and learning-based methods in a cooperative computing manner towards realizing DCS self-management. However, unlike many existing work in these areas which break down with increased network complexity and dynamics, the proposed HVC framework is utilized to offset these issues through effective separation, aggregation and asynchronous processing of both distributed state and policy. Using modeling techniques, we demonstrate that such architecture is feasible and can improve the operational robustness of DCS. The modeling emphasis focuses on demonstrating the operational advantages of an HVC-based organizational strategy for emergent management services (i.e., reachability, availability or performance). By integrating the two approaches, the DCS architecture forms a scalable system to address the challenges associated with traditional decentralized systems. The hypothesis is that the emergent management system architecture will improve the operational scaling properties of DCS-based applications and services. Additionally, we demonstrate structural flexibility of HVC as an underlying service infrastructure to build and deploy DCS applications and layered services. The modeling results demonstrate that an HVC-based emergent management and control system operationally outperforms traditional structural organizational models. In summary, this thesis brings together the above contributions towards delivering a scalable, decentralized system for Internet mobile computing and communications

WEB-GIS BASED BRIDGE INFORMATION DATABASE VISUALIZATION ANALYTICS AND DISTRIBUTED SENSING FRAMEWORK

The national bridge system plays very important role in society operations ensuring mobilities that can sustain social and economic growth. Recent increasingly growing concerns about the safety of existing bridges are shared by highway agencies at all levels of government, including federal, state and municipal. To provide a user-friendly and effective environment and services for accessing and analyzing the National Bridge Inventory (NBI) database, a powerful bridge data management system needs be developed to assist the bridge managers or professionals to manage and maintain effectively and efficiently the national bridge system. The objective of this research is to develop a Web-GIS (geographic information system) based bridge information database visualization analytics and distributed sensing framework for nation-wide bridge system management. This is accomplished by integrating modern technologies including GIS, Internet, database, remote sensing, visualization, and smartphone technologies. The objectives of this study include: 1) establishment of a system framework for effective use of current available bridge condition data and volunteering sensing data; 2) development of visualization and visual analytic applications appropriate for bridge information; 3) development of user-defined criteria query for decision-making support; and 4) development of a remote sensing database to aid engineers and other professionals in accessing, retrieving and manipulating information from the bridge database. The citizen-based sensors for bridge monitoring utilize voluntary information-sharing from individuals as a monitoring technique. The Web-GIS based Bridge Management System (BMS) framework developed in this research allows centralized data collection and data visualization analytics at any place and any time. It is intended as a critical step towards rapid bridge diagnostics using an integrated sensing data approach. Current bridge management is predominantly at state level. Furthermore, by adopting the “citizen sensor” concept, public data can be added into the bridge database as additional information for bridge management. The outcome of this research is a framework called: “Bridge-WGI.” The six critical modules formed the core of the framework, which are: 1) bridge database systems; 2) general bridge information visualization; 3) bridge information analytical visualization; 4) user-defined criteria query; 5) citizen sensing application in bridge monitoring; and 6) remote sensing database application. The Bridge-WGI framework demonstrates the capabilities of Web-based BMS can be accomplished via the integration of several technologies. These capabilities include: 1) application of volunteering sensing; 2) flexible accessibility via Internet; 3) several advanced visualization of bridge data; 4) bridge data integration; and 5) online user- defined query for decision making support

Trust models in ubiquitous computing

We recapture some of the arguments for trust-based technologies in ubiquitous computing, followed by a brief survey of some of the models of trust that have been introduced in this respect. Based on this, we argue for the need of more formal and foundational trust models

Assessing Communities of Practice in health policy : A conceptual framework as a first step towards empirical research

Peer reviewe

Qualitative Case Studies in Operations Management: Trends, Research Outcomes, And Future Research Implications

Our study examines the state of qualitative case studies in operations management. Five main operations management journals are included for their impact on the field. They are in alphabetical order: Decision Sciences, International Journal of Operations and Production Management, Journal of Operations Management, Management Science, and Production and Operations Management. The qualitative case studies chosen were published between 1992 and 2007. With an increasing trend toward using more qualitative case studies, there have been meaningful and significant contributions to the field of operations management, especially in the area of theory building. However, in many of the qualitative case studies we reviewed, sufficient details in research design, data collection, and data analysis were missing. For instance, there are studies that do not offer sampling logic or a description of the analysis through which research out-comes are drawn. Further, research protocols for doing inductive case studies are much better developed compared to the research protocols for doing deductive case studies. Consequently, there is a lack of consistency in the way the case method has been applied. As qualitative researchers, we offer suggestions on how we can improve on what we have done and elevate the level of rigor and consistency