A Multi-Criteria Approach to Decision Making in Broadband Technology Selection

A new European Union regulatory framework for the telecom sector has been under a process of transposition to national laws by its member states that should have been completed by the end of 2020, notwithstanding some delays. A core purpose of the regulatory framework is to guarantee that most citizens will have access to very fast Internet connections, capable of 100 Mbps download link speed, regardless of where they live. According to this new framework, in areas where the market does not deliver, governments are to launch public tenders for the deployment, maintenance, and operations of network infrastructure as well as services, and public funds should be used to support the deployment of these broadband networks in less densely populated areas. Needless to say, public tenders of this nature are subject to different criteria when it comes to candidate evaluation. In this paper, we present a decision model for the selection of operators to deploy and maintain broadband networks in scarcely populated areas, taking into consideration infrastructure costs, the technical quality offered by the solutions, and the credibility of the candidates. We suggest an integrated multi-stakeholder multi-criteria approach and demonstrate how it can be used in this complex area and find that in the example provided, taking a relevant set of criteria into the analysis, optical fibre networks hold much higher chances to be used in these public tenders compared to networks based on the broadly favoured 5G technology.

Research on online teaching platform system based on microservice architecture

The traditional online teaching adopts the single architecture to develop and implement the system, which facilitates the data sharing and testing of the system. However, due to the increasing complexity of the system's business functions, the system based on monolithic architecture has become increasingly complex, its scalability has deteriorated, and its concurrency performance has decreased. Based on these problems, this paper puts forward combining microservice architecture and online teaching platform, using microservice architecture independent deployment, concurrent performance characteristics such as high technology selection and flexible, the complex business function is divided into several small service module, solve the challenges faced by the traditional system, at the same time improve the efficiency of the use of online teaching platform and students' learning autonomy, The system function design, architecture design, safety design and so on are expounded to build an efficient and perfect online teaching platform.

Cloud decision support framework for treatment technology selection of health-care waste

With the attention of people to environmental and health issues, health-care waste (HCW) management has become one of the focus of researchers. The selection of appropriate HCW treatment technology is vital to the survival and development of human beings. In the assessment process of HCW disposal alternative, the evaluation information given by decision makers (DMs) often has uncertainty and ambiguity. The expression, transformation and integration of this information need to be further studied. We develop an applicable decision support framework of HCW treatment technology to provide reference for relevant staff. Firstly, the evaluation information of DMs is represented by interval 2-tuple linguistic term sets (ITLTs). To effectively express qualitative information, the cloud model theory is used to process the linguistic information, a novel concept of interval 2-tuple linguistic integrated cloud (ITLIC) is proposed, and the relevant operations, distance measure and possibility degree of ITLICs are defined. Moreover, a weighted Heronian mean (HM) operator based ITLIC is presented to fuse cloud information. Secondly, the HCW treatment technology decision support model based on the BWM and PROMETHEE is established. Finally, the proposed model is demonstrated through an empirical example, and the effectiveness and feasibility of the model is verified by comparison with extant methods.

Sustainable High-Tech Brick Production with Energy-Oriented Consumption: An Integrated Possibilistic Approach Based on Criteria Interdependencies

Brick making contributes significantly to the of supply materials for the building industry. The majority of brick production sectors, especially in developing countries, employ polluting and energy-inefficient technologies. Due to the increasing pressures on manufacturing firms to improve economic performance and growing environmental protection issues, sustainable and clean production is the main concern for brick makers. This paper considers the technological, economic, environmental, social, and energy-oriented criteria to select the optimal brick production technologies. Therefore, technology selection is viewed as a multi-criteria group decision-making (MCGDM) problem. This research proposes a novel hybrid fuzzy MCGDM (HFMCGDM) model to tackle the problem. In this respect, first of all, the modified triangular fuzzy pair-wise comparison (MTFPC) method is proposed to compute the local weights of criteria and sub-criteria. Then, a fuzzy DEMATEL (FDEMATEL) method is presented to calculate the interdependencies between and within the criteria. Moreover, the integration of MTFPC and FDEMATEL methods is applied to calculate the global criteria weights. Afterward, a novel method is proposed to determine the experts’ weight. Considering the last aggregation approach to diminish data loss, a new version of a fuzzy TOPSIS method is proposed to find the local and global priorities of the candidates. Then, a case study is given to demonstrate the applicability and superiority of the proposed methodology. To get a deeper view about considering kilns, energy and environmental performance of which has been investigated. Moreover, a comparative analysis is presented to illuminate the merits of the proposed methodology. Eventually, a sensitivity analysis is conducted to peruse the influence of criteria weights on ranking order.

Optimization of Industry 4.0 Implementation Selection Process towards Enhancement of a Manual Assembly Line

Last year’s developments are characterized by a dramatic drop in customer demand leading to stiff competition and more challenges that each enterprise needs to cope with in a globalized market. Production in low-mix/high-volume batches is replaced with low-volume/high-variety production, which demands excessive information flow throughout production facilities. To cope with the excessive information flow, this production paradigm requires the integration of new advanced technology within production that enables the transformation of production towards smart production, i.e., towards Industry 4.0. The procedure that helps the decision-makers to select the most appropriate I4.0 technology to integrate within the current assembly line considering the expected outcomes of KPIs are not significantly been the subject of the research in the literature. Therefore, this research proposes a conceptual procedure that focus on the current state of the individual assembly line and proposes the technology to implement. The proposed solution is aligned with the expected strategic goals of the company since procedure takes into consideration value from the end-user perspective, current production plans, scheduling, throughput, and other relevant manufacturing metrics. The validation of the method was conducted on a real assembly line. The results of the validation study emphasize the importance of the individual approach for each assembly line since the preferences of the user as well as his diversified needs and possibilities affect the optimal technology selection.

Methane Emission Estimation of Oil and Gas Sector: A Review of Measurement Technologies, Data Analysis Methods and Uncertainty Estimation

The emission estimation of the oil and gas sector, which involves field test measurements, data analysis, and uncertainty estimation, precedes effective emission mitigation actions. A systematic comparison and summary of these technologies and methods are necessary to instruct the technology selection and for uncertainty improvement, which is not found in existing literature. In this paper, we present a review of existing measuring technologies, matching data analysis methods, and newly developed probabilistic tools for uncertainty estimation and try to depict the process for emission estimation. Through a review, we find that objectives have a determinative effect on the selection of measurement technologies, matching data analysis methods, and uncertainty estimation methods. And from a systematic perspective, optical instruments may have greatly improved measurement accuracy and range, yet data analysis methods might be the main contributor of estimation uncertainty. We suggest that future studies on oil and gas methane emissions should focus on the analysis methods to narrow the uncertainty bond, and more research on uncertainty generation might also be required.

A review on future wastewater treatment technologies: micro-nanobubbles, hybrid electro-Fenton processes, photocatalytic fuel cells, and microbial fuel cell

The future prospect in wastewater treatment technologies mostly emphasizes processing efficiency and the economic benefits. Undeniably, the use of advanced oxidation processes (AOPs) in physical and chemical treatments has played a vital role in helping the technologies to remove the organic pollutants efficiently and reduce the energy consumption or even harvesting the electrons movements in the oxidation process to produce electrical energy. In the present paper, we reviewed several types of wastewater treatment technologies, namely micro-nanobubbles, hybrid electro-Fenton processes, photocatalytic fuel cells, and microbial fuel cell. The aims are to explore the interaction of hydroxyl radicals with pollutants using these wastewater technologies, including their removal efficiencies, optimal conditions, reactor setup, and energy generation. Despite these technologies recorded high removal efficiency of organic pollutants, the selection of the technologies is dependent on the characteristic of the wastewater and the daily production volume. Hence the review paper also provides comparisons between technologies as the guidance in technology selection.

Managing Energy Transition - Adapting Power to Gas Technology PTG - Project Management Review of Complexity, Technology and Integration Aspects

Managing climate change is a growing global concern. The Paris Agreement, the first ever legally binding global climate change agreement, enforced longer term actions for energy firms in terms of implementing newer means and technologies to reduce reliance on fossil fuel-based energy. In this regard, much attention is drawn to commercialized Power-To-Gas (PTG) - Hydrogen generated from renewable energy-based electrolysis can be introduced into natural gas utilities, thereby ensuring "Greener" natural gas mix. The integration of PTG plants and natural gas-fired power plants presents an attractive model to implement this. This paper analyzes the associated project management challenges, ranging from complexity issues to technology management and with a view on better integration and risk reduction. Power-to-Gas (PTG) is the process of converting surplus renewable energy into hydrogen gas through electrolysis. PTG plants and natural gas-fired power plants can form a closed loop between an electric power system and an interconnected multi-energy system, and this is believed to be a sustainable solution towards environment friendly energy systems. Power-to-Gas (PTG) technology is yet to mature in terms of its commercial viability. As such, traditional project management processes and methodologies also need to be reviewed and adapted to suit the economic and execution models needed for project success. The dimensions that will be analyzed in this paper include project integration management, project complexity management, technology management and risk management strategies. A model for Joint Venture management will also be proposed. PTG projects, as an effective means of transitioning to a ‘greener’ natural gas mix and the associated project life cycle process will be defined based on an integrated FEL (iFEL) model. Project risk management perspectives, its stakeholder influences and methods to mitigate risks towards better decision-making process shall be explored. This work proposes establishment of a dedicated, technically competent and scalable Global PMO to oversee the PTG projects’ prioritization, concept/technology selection, JV management, contracting strategies, formulation of a proactive management response system and overall value assurance.

Lessons Learned in the Delivery of Live Remote Group Weight Loss and Physical Activity Interventions for Older Adults

Social connection lies at the root of lasting health behavior change, and as such most effective interventions are built around social tools. Group leaders and peers provide education, and act as models of successful change and collaborators in addressing common barriers to behavioral adoption and maintenance. Unfortunately, many older adults do not have access to high quality group programs due to factors such as limited transport options, lack of local availability, or worries over personal safety. Importantly, developing effective, synchronous remote group programming is not as simple as delivering an in-person session via teleconference software. Instead, careful consideration must be paid to technology selection, fostering effective group communication, and developing confidence for use of remote intervention tools. This symposium provides key lessons learned from three group-based activity and weight loss interventions for older adults that focused on live, remote interaction. Jason Fanning will share lessons from the MORPH study, which paired remote group-mediated behavioral counseling with dietary weight loss and the accumulation of aerobic activity across the day. Christina Hugenschmidt will share her experiences adapting a group program involving improvisational dance or social gaming for remote delivery. Kushang Patel will present results from a mixed-methods study on the feasibility and acceptability of a remotely-delivered exercise program for older adults with knee osteoarthritis. Finally, Barbara Nicklas will place these experiences in the context of the development of exercise interventions for older adults over time, and highlighting vital next steps for ensuring more older adults have access to this important behavioral medicine.