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DOES TYPE OF CAPITAL MATTER FOR ECONOMIC GROWTH? A STUDY OF THE CHINESE ECONOMY

Laszlo Vasa Md Abdullah Al Mamun Jin Hu Md Kamal Hossain Jin Hu Md Abdullah Al Mamun Md Abdullah Al Mamun

Publication Name: Investment Management and Financial Innovations

Publication Date: 2025-01-01

Volume: 22

Issue: 1

Page Range: 469-480

Description:

The impact of different types of capital flows on China’s economic growth has been widely studied to determine whether the type of capital significantly affects the Chinese economy. The purpose of this study is to investigate the relationship between long-term capital flows and economic growth in China, considering factors such as Foreign Direct Investment (FDI), portfolio equity, portfolio bonds, and external debt. All secondary data were collected from the World Bank database. The paper also investigates which type of capital flow has the most significant relation with the economic growth of China. A quantitative approach was chosen for the study. Moreover, to overcome the bias output of ordinary least squares, this paper deployed a Two-Stage Least Squares (2SLS) estimation method. This study has found a relatively stable positive relationship between FDI and growth, where the coefficient of 0.9699 indicates that a 1% increase in FDI is associated with a 0.97% growth in Gross Domestic Product (GDP). Similar to FDI, portfolio equity has a positive impact on GDP growth, with a coefficient of 2.1419. In contrast, portfolio bond and debts have a negative coefficient of –1.7752 and –0.2831. These findings contribute to a deeper understanding of China’s development experience, particularly regarding the role of capital flow. The paper explores two key limitations that need to be explored in the future, i.e., the causal relation between each type of long-term capital flow and economic growth, and the impact of COVID-19 on the economic growth relationship.

Open Access: Yes

DOI: 10.21511/imfi.22(1).2025.35

Robotics, drones, and other autonomous systems in the seafood sector

Abdo Hassoun John G. Keogh Abderahman Rejeb Karim Rejeb

Publication Name: Seafood 4 0 Digital Physical and Biological Innovations from Sea to Table

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: 223-252

Description:

The seafood sector is essential for global food security and economic development; however, it encounters substantial challenges, including labor shortages, sustainability issues, and the necessity for enhanced efficiency. Advanced technologies such as robotics, drones, and autonomous systems are increasingly being integrated into multiple stages of the seafood value chain, encompassing harvesting and distribution, to address these challenges. These technologies provide solutions through the enhancement of operational efficiency, improvement of product quality, and promotion of sustainability. This chapter examines the automation of processing and packaging through robotics, the enhancement of aquaculture and fishery monitoring via drones, and the optimization of logistics and environmental management by autonomous systems. The chapter also highlights challenges associated with the adoption of these technologies, such as elevated costs, regulatory concerns, and the necessity for technical expertise. Several real-world use cases are presented to demonstrate the practical application and benefits of each technology. The chapter concludes with recommendations for future research, emphasizing the scalability of these technologies for smaller enterprises, their integration throughout the value chain, and their environmental and social implications. Addressing these areas enables the seafood sector to leverage technology more effectively for a sustainable and efficient future.

Open Access: Yes

DOI: 10.1016/B978-0-443-33750-5.00017-2

Correlation coefficients on normal wiggly dual hesitant fuzzy sets: an application in the selection of real estate agents

Dragan Pamucar Khizar Hayat Nadeem Ajaib Kamran Kausar

Publication Name: Peerj Computer Science

Publication Date: 2025-01-01

Volume: 11

Issue: Unknown

Page Range: Unknown

Description:

Decision makers (DMs) continually demonstrate shortcomings in their approaches to analyzing information through fuzzy systems; nevertheless, a model that integrates many dimensions of uncertainty is generally substantial. Normal wiggly dual hesitant fuzzy sets (NWDHFSs) incorporate a range of DMs' preferences for membership grades (MGs) and non-membership grades (NMGs). For complicated and multifaceted problems, one can apply the dynamic framework of NWDHFSs. To illustrate the relationship between NWDHFSs, correlation coefficients (CCs) on NWDHFSs, as well as weighted CCs on NWDHFSs, are presented in this work. These CCs are built up using means of values in hesitant fuzzy elements of NWDHFSs. Some fundamental axioms and thresholds of CCs on NWDHFSs are examined. A multi-criteria decision-making (MCDM) technique and associated algorithms based on these CCs are introduced. Because of the competitive real estate market, choosing a real estate agent is a challenging task for organizations. Through the consideration of a real estate case study, we select an appropriate real estate agent for a real estate firm utilizing proposed CCs on NWDHFSs. We examine the methodologies and outcomes of our approach to previous strategies.

Open Access: Yes

DOI: 10.7717/peerj-cs.3308

Developing Longitudinal Vehicle Dynamics Model of Electric Bicycles for Virtual Validation of Active Safety Systems †

Bence Nagy Denes Fodor

Publication Name: Engineering Proceedings

Publication Date: 2025-01-01

Volume: 113

Issue: 1

Page Range: Unknown

Description:

The increasing adoption of electric bicycles (e-bikes) has led to a growing need for advanced active safety systems, such as anti-lock braking systems (ABSs), to enhance rider safety. In recent years, both hydraulic and electromechanical ABSs were researched. To support the development and validation of these systems, this paper presents a longitudinal vehicle dynamics model of an electric bicycle. The model captures key physical interactions, including drivetrain, transmission, braking, and tire–road contact, to accurately simulate longitudinal motion. By leveraging this model, future studies can perform virtual validation of active safety components in a controlled and repeatable environment, reducing the dependency on costly and time-intensive physical testing. The proposed model lays the foundation for a model-based design approach, enabling early-stage performance assessment and optimization of safety-critical functions in electric bicycles.

Open Access: Yes

DOI: 10.3390/engproc2025113073

Exhaustive Generation of the Complete Multidimensional Pareto Front for Multi-Objective Process Network Synthesis

Botond Bertok Károly Kalauz Márton Frits

Publication Name: Chemical Engineering Transactions

Publication Date: 2025-01-01

Volume: 121

Issue: Unknown

Page Range: 157-162

Description:

In sustainable systems design, optimizing complex process networks often involves multiple conflicting objectives, such as minimizing cost, reducing environmental impact, and maximizing performance. Traditional single-objective optimization methods frequently fail to address this complexity, resulting in suboptimal and inflexible solutions. This study focuses on a comprehensive approach to multi-objective optimization for a single fixed process structure, where all integer decisions are predetermined through a prior process synthesis phase, such as the Solution Structure Generator algorithm from the P-graph framework. The remaining task involves optimizing continuous parameters—specifically, the operational volumes within the network—to generate the complete Pareto front, representing all non-dominated solutions. Each objective function is assumed to be a linear function of operational volumes, allowing for a scalable mathematical formulation. An algorithmic framework is developed to address the challenges associated with generating infinite-point Pareto fronts in high-dimensional spaces, incorporating genetic algorithms, machine learning models, and the P-graph methodology. This hybrid approach supports dynamic adaptation to changing data and improves computational efficiency. The methodology is demonstrated through a case study. The example highlights how balancing cost and environmental criteria using Pareto optimal solutions leads to more sustainable system designs. Ultimately, this work underscores the practical importance of generating and evaluating the complete set of Pareto optimal solutions in sustainable system design. Moving beyond a single optimal configuration, the proposed methodology offers robust decision support across diverse industrial applications, bridging the gap between theoretical optimality and real-world implementation.

Open Access: Yes

DOI: 10.3303/CET25121027

Model testing – decision-making on capacity expansion in family businesses. Evidence from Portugal

Márta Konczos Szombathelyi Inês Lisboa Kinga Nemes

Publication Name: Journal of International Studies

Publication Date: 2025-01-01

Volume: 18

Issue: 1

Page Range: 22-40

Description:

This paper aims to test and validate a model of internal factors influencing the capacity expansion decisions of family businesses, thereby helping these organizations better understand their decision-making processes. The identified internal factors include socio-emotional wealth, intergenerational cooperation, and a heterogeneous top management team. The study focuses on family businesses in the Portuguese food industry and employs both qualitative and quantitative methods. A structured online questionnaire, completed by 150 respondents, was analyzed using SPSS. Additionally, in-depth interviews were conducted to confirm the quantitative findings and provide a broader conceptual perspective. The results indicate that both qualitative and quantitative analyses support the proposed model.

Open Access: Yes

DOI: 10.14254/2071-8330.2025/18-1/2

Heartbeat Estimation from Subtle Body Vibrations via Inertial Sensing

Patrik Gabor Rozsa Szilvia Nagy

Publication Name: 60th International Scientific Conference on Information Communication and Energy Systems and Technologies Icest 2025 Proceedings

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

This paper presents a cost-conscious signal processing pipeline for detecting heartbeats from faint body vibrations using a single back-mounted inertial measurement unit (IMU). The system operates without ECG or PPG sensors, relying solely on accelerometer and gyroscope data. The pipeline is designed with the intent to run on lightweight edge-computing platforms, such as Raspberry Pi-class devices or even on a ESP32, while prioritizing energy efficiency and user-friendliness for extended battery-powered use. Preliminary validation against manually recorded heart rates demonstrates feasibility with limitations.

Open Access: Yes

DOI: 10.1109/ICEST66328.2025.11098443

Integrating footwear features into fatigue prediction models for marathon runners: A hybrid CNN-LSTM approach

Yaodong Gu Dong Sun Yang Song Zixiang Gao Xuanzhen Cen Zhenghui Lu Yufan Xu Chengyuan Zhu Chen Hu

Publication Name: Proceedings of the Institution of Mechanical Engineers Part P Journal of Sports Engineering and Technology

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Footwear design, especially the curvature of carbon plates, may influence fatigue perception, but few studies have integrated footwear features into fatigue prediction models. This study aimed to develop a hybrid CNN-LSTM model to predict runners’ fatigue states and evaluate the impact of footwear characteristics on fatigue perception. Twelve male marathon runners (age = 21.8 ± 1.3 years; body mass = 59.1 ± 4.1 kg; height = 168.9 ± 2.2 cm; and weekly mileage = 68.8 ± 5.5 km) participated. They wore two types of carbon-plated shoes (flat plate, FP, and curved plate (CP)) and ran at a steady pace (Borg score 13) until a Borg score of 16 or 85% of maximum heart rate was reached for 2 min. EMG signals and physiological data were collected during treadmill running. A hybrid CNN-LSTM model was trained with and without footwear features to predict fatigue states. The model with footwear features achieved 85% accuracy, compared to 69% without. Curved carbon plate (CP) shoes delayed semi-fatigue onset, indicating better initial support, but the time to full fatigue was similar for both shoe types. The CNN-LSTM model effectively predicted fatigue states, with significant improvement when footwear features were included. Footwear design, particularly carbon plate curvature, influenced fatigue perception.

Open Access: Yes

DOI: 10.1177/17543371251356133

ModRTU InjectX: A Command Injection Simulation Tool for Industrial Cybersecurity Research

Zoltán Dobrády Timót Hidvégi Szilvia Nagy

Publication Name: 60th International Scientific Conference on Information Communication and Energy Systems and Technologies Icest 2025 Proceedings

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

ModRTU_InjectX is a Python-based research tool with a graphical user interface, specifically designed for real-time monitoring, analysis, and command injection simulation within Modbus RTU industrial communication systems. The platform enables users to craft custom data packets and inject them into the serial communication channel using event-driven logic, effectively modelling realistic cyberattack scenarios. All communication is logged and can be exported in structured formats, making the system ideal for creating annotated datasets for training and validating machine learning-based intrusion detection systems. The tool supports parallel injection block configurations, evaluates attack effectiveness, and provides detailed statistical summaries. ModRTU_InjectX serves as a valuable contribution to the research infrastructure for industrial cybersecurity.

Open Access: Yes

DOI: 10.1109/ICEST66328.2025.11098380