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The Internet of Things has recently been a popular topic of study for developing smart homes and smart cities. Most IoT applications are very sensitive to delays, and IoT sensors provide a constant stream of data. The cloud-based IoT services that were first employed suffer from increased latency and inefficient resource use. Fog computing is used to address these issues by moving cloud services closer to the edge in a small-scale, dispersed fashion. Fog computing is quickly gaining popularity as an effective paradigm for providing customers with real-time processing, platforms, and software services. Real-time applications may be supported at a reduced operating cost using an integrated fog-cloud environment that minimizes resources and reduces delays. Load balancing is a critical problem in fog computing because it ensures that the dynamic load is distributed evenly across all fog nodes, avoiding the situation where some nodes are overloaded while others are underloaded. Numerous algorithms have been proposed to accomplish this goal. In this paper, a framework was proposed that contains three subsystems named user subsystem, cloud subsystem, and fog subsystem. The goal of the proposed framework is to decrease bandwidth costs while providing load balancing at the same time. To optimize the use of all the resources in the fog sub-system, a Fog-Cluster-Based Load-Balancing approach along with a refresh period was proposed. The simulation results show that “Fog-Cluster-Based Load Balancing” decreases energy consumption, the number of Virtual Machines (VMs) migrations, and the number of shutdown hosts compared with existing algorithms for the proposed framework.

While global attention to zero-energy building (ZEB) has surged as a sustainable countermeasure to high-energy consumption, a congruent expansion in research remains conspicuously absent. Addressing this lacuna, our study harnesses public research and development grant data to decipher evolving trajectories within ZEB research. Distinctively departing from conventional methodologies, we employ state-of-the-art natural language processing (NLP) artificial intelligence models to meticulously analyze grant textual content pertinent to ZEB. Our findings illuminate an expansive spectrum of ZEB-related research, with a pronounced focus on the holistic continuum of energy supply, demand, distribution, and actualization within architectural confines. Theoretically, this work delineates key avenues ripe for future empirical exploration, fostering a robust academic foundation for subsequent ZEB inquiries. Practically, the insights derived bear significant implications for practitioners, informing optimal implementation strategies, and offering policymakers coherent roadmaps for sustainable urban development. Collectively, this study affords a panoramic perspective on contemporary ZEB research contours, enhancing both scholarly comprehension and practical enactment in this pivotal domain.

This study examines how the registration of certain agricultural regions affects the sales of vegetables classified as traditional. We focused on the sales trends of traditional vegetables from the Noto region, one of the first designated sites of Globally Important Agricultural Heritage Systems (GIAHS). We compared the sales of recognized traditional vegetables to those of similar traditional vegetables from nearby areas and vegetables labeled with the same place names as the traditional vegetables but without elements of traditionality in branding. The study analyzed the sale and relevant trends of four categories of vegetable: Kaga vegetables, vegetables labeled “Kaga”, Noto vegetables, and vegetables labeled “Noto”. We further analyzed the trends by applying Convention Theory to understand the underpinning “orders of worth” in the purchase and sale of the items. Both Noto vegetables and place-labeled vegetables increased in overall sales since GIAHS registration in 2011. The recent increases in sales volume and number of items, however, were largely due to the production of lettuce, a crop from a vegetable factory. By applying Convention Theory, we identified that in the agriculture of the region, industrial farming impacted even the GIAHS registered site. Thus, careful collection and analysis of evidence is necessary to evaluate the effects of GIAHS registration and draft an action plan for further evidence-based policy making.

With information technology (IT) now showing advanced capabilities, many new services are being introduced to consumers of smartphones through the various available app stores. Moreover, the recent proliferation of such services related to information and communications technology has seen a momentous rise. Despite this trend, the ever-changing landscape of mobile IT services is creating a serious problem for businesses who are already experiencing fierce market conditions. Thus, in order to maintain the sustainability of an enterprise, it is necessary to make an adequate analysis of the success and failure factors of IT services in order to create a sustained competitive advantage. Considering 22 real IT service cases based on two platform models (merchant model and two-sided model) and through surveys submitted to 11 experienced entrepreneurs in IT services, we conducted a t-test analysis in order to first assess the success and failure factors of the IT service cases. Next, we performed a logistic regression analysis in order to find underlying relationships of our hypothesized model. The results showed that the participants identified 141 success and 101 failure factors in total with the t-tests, confirming that the distinction between success and failure of each IT service assessed was significant. Next, the results from the logistic regression showed which relationships were the best on the basis of the given platform model. Overall, this study was able to identify the main factors that have an influence on the success and failure of IT services based on two identified platform models. In doing so, this paper can help to inform future IT service entrepreneurs and researchers involved in developing new apps based on IT services by providing a guide to what factors need to be considered before going to market.

This study analyzes the changes in energy consumption of the Korean manufacturing sector using the index decomposition analysis (IDA) method. To capture the production effect based on actual physical activities, we applied the activity revaluation (AR) approach in the analysis. We also developed energy consumption data in terms of primary energy supply to consider conversion loss in the energy sector to avoid any distortions in the intensity effect. The analysis covers every manufacturing subsector in Korea over the period between 2006 and 2018. Combining two distinctive approaches from the previous literature, the AR approach and primary energy-based analysis gives us helpful findings for a climate policy. First, the overall activity effect estimated from the physical output indicator is lower than that from the monetary output indicator. The monetary indicator shows that the share of energy-intensive industries decreases, whereas the physical indicator shows the opposite. Second, in terms of energy efficiency, the intensity effect is estimated as an increasing factor of energy use, whereas inversed results are shown when we use the monetary indicator. Lastly, unlike the previous studies, the AR approach results indicate that Korean manufacturing sectors have been shifting toward an energy-intensive, so it is hard to anticipate positive intensity effects, which means decreasing energy consumption factor, for a while. These results support why analyzing the driving forces of energy consumption through the AR approach and primary energy base is highly recommended.

Direct mineral carbonation (MC) is used to mitigate carbon dioxide (CO2) emissions. This method has the great advantages of reducing the amount of industrial residues and creating valuable materials by incorporating CO2. Waste gypsum, industrial waste including flue gas desulfurization (FGD) gypsum (25.27–53.40 wt% of CaO), and phosphogypsum (30.50–39.06 wt% of CaO) can be used for direct MC (conversion rate up to 96%). Mineral carbonation converts waste gypsum into calcium carbonate (CaCO3), which can be recycled during desulfurization. Furthermore, ammonium sulfate ((NH4)2SO4), which is used as a fertilizer, can be prepared as a by-product when the carbonation reaction is performed using ammonia (NH3) as a base. In this study, recent progress in the carbonation kinetics and preparation of CaCO3 using FGD gypsum and phosphogypsum with NH3 was investigated. Temperature, CO2 partial pressure, CO2 flow rate, and NH3 concentration were reviewed as factors affecting carbonation kinetics and efficiency. The factors influencing the polymorphs of the prepared CaCO3 were also reviewed and summarized. A state-of-the-art bench-scale plant study was also proposed. In addition, economic feasibility was investigated based on a bench-scale study to analyze the future applicability of this technology.

This study explored whether Montana agricultural stakeholders’ perceptions and observations of climate change vary according to four socio-ecological variables: income, political view, agricultural occupation, and production region. A survey including 27 questions was developed into five sections: (1) agricultural background information; (2) perceptions about climate change; (3) observed changes in climate-related variables; (4) adaptation practices and strategies; and (5) demographic information. The survey included Likert-scored responses and multiple-choice questions, and was completed by 452 participants, including conventional and organic farmers and ranchers, extension agents, crop consultants, and researchers. The results indicate that while a notable fraction of agricultural stakeholders are alarmed about climate change and optimistic about the human capacity to reduce climate change, the degree of concern and optimism significantly varies depending on the stakeholder’s political views, production region, and agricultural occupation group. We found that observations of changes in climate, perceptions about climate change, and potential risks to agricultural production are driven mainly by political views. Both perceptions and observations drive the choice of adaptation and mitigation practices. It is thus essential to understand farmers’ socio-ecological characteristics when designing agricultural outreach programs in order to reduce barriers for the adoption of climate-resilient agriculture.