Energy Storage Systems (ESSs) have recently been highlighted because of their many benefits such as load-shifting, frequency regulation, price arbitrage, renewables, and so on. Among those benefits, we aim at evaluating their economic value in frequency regulation application. However, unlike previous literature focusing on profits obtained from participating in the ancillary service market, our approach concentrates on the cost reduction from the perspective of a utility firm that has an obligation to pay energy fees to a power exchange. More specifically, we focus on the payments between the power exchange market and the utility firm as a major source of economic benefits. The evaluation is done by cost- benefit analysis (CBA) with a dataset of the Korean market while considering operational constraint costs as well as scheduled energy payments, and a simulation algorithm for the evaluation is provided. Our results show the potential for huge profits to be made by cost reduction. We believe that this research can provide a guideline for a utility firm considering investing in ESSs for frequency regulation application as a source of cost reduction.

Digital document communication between an enterprise and a customer is becoming a primary form of communication rather than the traditional physical document communication. A PDF document, the most popular document format, provides an identical document layout regardless of OS or device and has a content integrity verification feature with a digital signature. However, it has a bad user experience, such as low readability on a mobile device. On the other hand, an HTML document has a weakness in verifying the content integrity even though it is the primary document format and provides a good user experience on mobile devices. There are certified document services using blockchain technology, but it is still vulnerable to verifying content integrity. Furthermore, research on the document HTML has proposed the trusted document generation technique by HTML conformance and digital signature; however, this research does not provide content delivery verification, and there is a file size overhead. In this paper, we have developed the chained document HTML by defining HTML conformance, digital signature, and blockchain technology. First, the chained document HTML has to embed all resources and does not allow loading content on-demand. Second, the file is signed by a digital signature, and the signature value is added in the file header. Lastly, the metadata to verify the content integrity is inserted in a blockchain node. We have created the chained document HTML generation and verification experiment environment by Ethereum and Python. We have confirmed that the chained document HTML provides content and delivery integrity verification in the research. We expect the chained document HTML will be widely used in document communication between an enterprise and a customer, especially if the document has sensitive personal information that might have a legal dispute.

Regional governments and regional intergovernmental organizations play an increasingly important role in land use and transportation planning in many countries. In the U.S., regional organizations such as metropolitan planning organizations provide regional forums and institutions to coordinate actions of local government necessary to overcome collective action problems that result from the fragmentation of local authority. Their regional scope allows them to directly address collaboration problems or broker collaborative arrangements among local governments within their boundaries. Nevertheless, the scale of regional problems often extends beyond the boundaries of these regional entities. Thus, collaboration across regional governance organizations is necessary to address problems that have multi-regional impacts, such as large transportation projects. Extant research generally measures regional collaboration based on counts of collaboration actions undertaken, but this does not account for the fact that some are symbolic, while others require resources and commitment. Drawing insights from the institutional collective action framework, we advance an explanation for how regional organizations overcome collaboration risks to participate in collaborative solutions to regional and multi-regional problems. The analysis employs a unique national survey of metropolitan planning organizations (MPOs) and adds a novel application of item response theory (IRT) to capture differences in risk or difficulty among collaborative actions. The IRT results offer support for our ICA-based explanation of collaboration commitments. The implications of the findings for theory development and empirical study of RIGOs are discussed in conclusion.

Local government managers play a critical role in sustainability and climate adaptation planning, and in relation to land-use policy, but little is known about how managers’ hazard risk concerns influence the implementation of resilience policy or how this relationship may vary across different landscapes and types of hazards. Linking managers’ disaster concerns to their planning choices is particularly relevant to resilience planning for adaptation to climate change, since greenhouse gas emissions are global but the harms produced by climate change are local. Moreover, climate adaptation planning encompasses risks from multiple hazards. For a sample of cities in the state of Florida, USA, we report the findings of empirical analysis of the relationships between local government managers’ hazard-specific climate-related disaster concerns and their resilience-planning priorities for four types of hazards: river flooding, sea-level rise, storm surge and hurricane/tornado winds. Drawing on data from a survey of local disaster managers and policy data on the implementation of adaptation-planning actions, the link between managers’ concerns and plan implementation is identified and compared across communities and across types of hazards. The pooled logit regression results reveal that the differences observed among these hazards persist even after controlling for objective risks and relevant community characteristics. We discuss the nature of the differences across four hazards and explore the implications of the findings for the literature on land use and climate adaptation and for the education of local government managers.

The categories for call center conversation data are valuably used for reporting business results and marketing analysis. However, they typically lack clear patterns and suffer from severe imbalance in the number of instances across categories. The call center conversation categories used in this study are Payment, Exchange, Return, Delivery, Service, and After-sales service (AS), with a significant imbalance where Service accounts for 26% of the total data and AS only 2%. To address these challenges, this study proposes a model that ensembles meta-information generated through Named Entity Recognition (NER) with machine learning inference results. Utilizing KoBERT (Korean Bidirectional Encoder Representations from Transformers) as our base model, we employed Easy Data Augmentation (EDA) to augment data in categories with insufficient instances. Through the training of nine models, encompassing KoBERT category probability weights and a CatBoost (Categorical Boosting) model that ensembles meta-information derived from named entities, we ultimately improved the F1 score from the baseline of 0.9117 to 0.9331, demonstrating a solution that circumvents the need for expensive LLMs (Large Language Models) or high-performance GPUs (Graphic Process Units). This improvement is particularly significant considering that, when focusing solely on the category with a 2% data proportion, our model achieved an F1 score of 0.9509, representing a 4.6% increase over the baseline.