Article
Business
Brett Watson, Matthew N. Reimer, Mouhcine Guettabi, Alan Haynie
Summary: The study found that commercial fishing activity in Alaska has a positive impact on the local economy, with each dollar increase in fisheries earnings leading to a $1.54 increase in total income. The results demonstrate the potential for commercial fishing to benefit local economies through direct, indirect, and induced effects into other sectors, highlighting the importance of local resource ownership for generating benefits.
JOURNAL OF ENVIRONMENTAL ECONOMICS AND MANAGEMENT
(2021)
Article
Computer Science, Artificial Intelligence
Andreas Theissler, Mark Thomas, Michael Burch, Felix Gerschner
Summary: This paper proposes a model-agnostic approach ConfusionVis for evaluating and selecting multi-class classifiers based on their confusion matrices. By incorporating human knowledge and analyzing the per-class errors and class confusions, the proposed approach enables a more efficient training process and yields better models for specific applications.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Business
Stefan Meyer, Paulo Santos, Chitpasong Kousonsavath
Summary: In this study, the effect of competing for a prize on the coordinated control of invasive species in the presence of externalities was evaluated through a field experiment. It was found that only monetary prizes were capable of promoting behavioral change, and intermediate size prizes led to reductions in storage losses. Moreover, spillovers were important, with non-participants benefiting almost as much as participants, and the avoided losses were significant enough to drive a reduction in market prices.
JOURNAL OF ENVIRONMENTAL ECONOMICS AND MANAGEMENT
(2022)
Article
Management
Frank van der Wouden, Hyejin Youn
Summary: New communication and transportation technologies have made the world smaller, but the death of distance is exaggerated in academic scholarship and knowledge development where knowledge spillovers are highly dependent on geographical distances. A study analyzing 17.6 million publications authored by 1.7 million scholars shows that scholars collaborating locally were 57% more likely to learn from knowledge spillovers than those collaborating non-locally in 1975. Factors such as career stage, institutional ranking, number of collaborators, and field of study influence the impact of geographical distance on knowledge spillovers.
Article
Automation & Control Systems
Christos Spandonidis, Panayiotis Theodoropoulos, Fotis Giannopoulos, Nektarios Galiatsatos, Areti Petsa
Summary: The ESTHISIS project aims to develop a low-cost and low-energy wireless sensor system for the immediate detection of leaks in metallic piping systems for the transport of liquid and gaseous petroleum products. Two leakage detection methodologies were presented in this study: a 2D-Convolutional Neural Network (CNN) model for supervised classification and a Long Short-Term Memory Autoencoder (LSTM AE) for unsupervised leakage detection. Field tests and evaluation in a real environment showed the effectiveness of the methods.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Business
Danae Manika, Paolo Antonetti, Savvas Papagiannidis, Xiaojing Guo
Summary: The study shows that pride triggered by purchasing environmentally-friendly technology can lead to positive spillover effects, such as reducing energy consumption through other means and recycling. Leveraging pride appeals in social businesses can enhance the impacts of pro-environmental technology adoption, benefitting both society and financial goals.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2021)
Article
Humanities, Multidisciplinary
Yuxuan Ma, Lei Wang, Di Hu, Yaoqing Ge, Junzhu Zuo, Tian Lan
Summary: Innovation is the key driver of regional economic development, and understanding the spatial patterns of regional innovation can provide insights into regional differences in innovation development. This study used patent data from Jiangsu province in China in 2019 to analyze the spatial patterns of technological innovation capability. The results showed that the technological innovation capability in Jiangsu province exhibited a core and belt distribution pattern, with Nanjing as the core and Suzhou, Wuxi, and Changzhou as a high innovation capacity belt in the southeast-northwest. The study also found variations in aggregation patterns and industrial development across different cities in the province.
HUMANITIES & SOCIAL SCIENCES COMMUNICATIONS
(2023)
Article
Mathematics
Ryul Kim, Young Hwan Choi
Summary: This research proposes a method that quantitatively evaluates the volume of leakage using deep learning technology and simultaneously detects the location of leakage through real-time monitoring. By using hydraulic data from a calibrated hydraulic model as training data and applying deep learning techniques, the study analyzes various scenarios regarding leakage volume and location to optimize leakage detection performance.
Article
Engineering, Multidisciplinary
Yong Shao, Congxin Chen, Zude Lu, Yun Zheng, Yapeng Zhang
Summary: This study proposes an intelligent leakage detection method for diaphragm wall joints based on FBG sensing signals. By analyzing the characteristics of the FBG wavelength curve and establishing intelligent detection models, the method is effective and efficient in identifying and locating leakage through diaphragm walls.
Article
Green & Sustainable Science & Technology
Ben Filewod, Geoff McCarney
Summary: With nature-based offsets becoming crucial for achieving short-term climate objectives, ensuring their effectiveness in reducing emissions is crucial. However, the interventions used for generating offsets can lead to unintentional carbon leakage and hinder mitigation efforts. This article argues that current practices for addressing leakage are ineffective and proposes an alternative approach based on a new conceptual framework. Additionally, three principles are outlined to enhance the credibility of nature-based offsets without compromising further investment in nature-based solutions.
Article
Business, Finance
Yueshan Li, Shoudong Chen, John W. Goodell, Dianmin Yue, Xutang Liu
Summary: The collapse of Silicon Valley Bank has called attention to the assessment of risks. This study proposes a new approach to estimate the systemic importance of different sectors by integrating both top-down and bottom-up information networks. Through the use of component-expected-shortfall and generalized error-variance-decomposition methodologies, this approach identifies systemically important sectors based on both interconnectedness and size. The study finds that the level of risk spillovers in sectors is not well correlated with their corresponding level of risk contribution, suggesting that focusing solely on connectedness between assets can distort risk estimation. These findings have significant implications for regulatory authorities in accurately identifying sector risks.
FINANCE RESEARCH LETTERS
(2023)
Article
Management
Paul Elhorst, Dries Faems
Summary: This study explores negative scoring spillovers in proposal evaluations, finding that proposals can influence each other in contests without strict evaluation sequences. The magnitude of these spillovers depends on the design of the innovation contest.
Article
Green & Sustainable Science & Technology
Jianqin Ma, Jiangshan Yang, Xiuping Hao, Bifeng Cui, Shuoguo Yang
Summary: This study utilizes machine learning to analyze the impact of dynamic changes in flow rate and soil moisture content on channel leakage loss in water transmission process and constructs a dynamic simulation model. The experimental results show that machine learning can improve the calculation accuracy of channel leakage loss.
Article
Computer Science, Information Systems
Jinghua Tan, Qing Li, Jun Wang, Junxiao Chen
Summary: Recent financial studies have shown the significant role of spillover effects of certain market factors in stock fluctuations. This study proposes a novel conditional heterogeneous graph neural network (FinHGNN) to capture multiple spillover effects in asset pricing. Experimental results demonstrate the advantages of the proposed framework over other algorithms on two real-world datasets.
INFORMATION SCIENCES
(2022)
Article
Engineering, Biomedical
Meghana R. Khare, Raviraj H. Havaldar
Summary: Lumbar spine illnesses, such as spondylolisthesis, have become more common and early detection is crucial. This study proposes a sequential approach using deep learning's DenseNet 201 to process and classify lumbar spine images for detecting anterior slippage. The method achieves high accuracy and outperforms other techniques.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
