Hasil untuk "Commercial geography. Economic geography"

Rostand A. K. Fezeu, Lilian C. Freitas, Eman Ramadan et al.

Radio Access Network (RAN) sharing, which often also includes spectrum sharing, is a strategic cooperative agreement among two or more mobile operators, where one operator may use another's RAN infrastructure to provide mobile services to its users. By mutually sharing physical sites, radio elements, licensed spectrum and other parts of the RAN infrastructure, participating operators can significantly reduce the capital (and operational) expenditure in deploying and operating cellular networks, while accelerating coverage expansion -- thereby addressing the spectrum scarcity and infrastructure cost challenges in the 5G era and beyond. While the economic benefits of RAN sharing are well understood, the impact of such resource pooling on user-perceived performance remains underexplored, especially in real-world commercial deployments. We present, to the best of our knowledge, the first empirical measurement study of commercial 5G spectrum and RAN sharing. Our measurement study is unique in that, beyond identifying real-world instances of shared 5G spectrum and RAN deployment "in the wild", we also analyze users' perceived performance and its implication on Quality of Experience (QoE). Our study provides critical insights into resource management (i.e., pooling) and spectrum efficiency, offering a blueprint (and implications) for network evolution in 5G, 6G and beyond.

Emelia Ohene Afriyie, Michael Snowden, Ernest Christian Winful et al.

Abstract This study examined the influence of an entrepreneurship education learning approach on students’ self-efficacy, with a specific focus on the mediating roles played by entrepreneurial competence and satisfaction. Informed by a conceptual framework drawn from pertinent literature, data were collected through purposive sampling from a diverse cohort of students within technical universities. Employing the AMOS structural equation modelling (SEM) method, the analysis revealed a statistically significant positive relationship between the entrepreneurship learning approach and self-efficacy without mediating variables. However, the study observed no significant direct relationship in the presence of these mediating factors. This suggests that entrepreneurial competence and satisfaction fully mediated the impact of the learning approach on self-efficacy. It is important to note that the study’s findings are contextually bound to technical universities within a less developed economy, cautioning against generalising them to traditional universities. Nonetheless, the study underscored the pivotal role of entrepreneurship education, self-competence, and student satisfaction in bolstering students’ self-efficacy, serving as a potent catalyst for fostering entrepreneurial intentions. Consequently, the study advocated for integrating entrepreneurship learning approaches in Technical and Vocational Education and Training (TVET) institutions.

NEAMTU ADINA CLAUDIA, NEAMTU LIVIU

The article aims to reconfigure the marketing organizational structure in the context of the approach marketing on two levels: offline and online, in physical space and virtual space, in what we call an integrated marketing system. This approach must be systemic, in a complex and complete, correlated gear, in which each component, each element, has its own role but functions integratedly, in connection and correlation with all the other elements, interconnected, influencing each other. The marketing organizational structure must be reconfigured and adapted to growing complexity of the marketing system. Digital marketing is the umbrella term that includes all online marketing activities. Virtual marketing is a specialization of it, focused on virtual environments. The emergence of artificial intelligence - AI, has decisively marked this evolution, marketing acquiring unprecedented valences in the current world, which in some places belong to science fiction, imagination being surpassed by reality. AI is the intelligence of machines that imitates the cognitive functions that we associate with humans: learning and problem solving, the ability of a system to correctly interpret external data, to learn from such data and to use what it has learned to achieve its specific goals and tasks through flexible adaptation. Companies have a wide range of strategies and potential aspects on the Internet to consider when deciding how to best implement profit maximization strategies

Aleksandar Pramov

This paper addresses the prediction of commercial (brand) memorability as part of "Subtask 2: Commercial/Ad Memorability" within the "Memorability: Predicting movie and commercial memorability" task at the MediaEval 2025 workshop competition. We propose a multimodal fusion system with a Gemma-3 LLM backbone that integrates pre-computed visual (ViT) and textual (E5) features by multi-modal projections. The model is adapted using Low-Rank Adaptation (LoRA). A heavily-tuned ensemble of gradient boosted trees serves as a baseline. A key contribution is the use of LLM-generated rationale prompts, grounded in expert-derived aspects of memorability, to guide the fusion model. The results demonstrate that the LLM-based system exhibits greater robustness and generalization performance on the final test set, compared to the baseline. The paper's codebase can be found at https://github.com/dsgt-arc/mediaeval-2025-memorability

Guhan Sivakumar

This paper explores the application of Hidden Markov Models (HMM) and Long Short-Term Memory (LSTM) neural networks for economic forecasting, focusing on predicting CPI inflation rates. The study explores a new approach that integrates HMM-derived hidden states and means as additional features for LSTM modeling, aiming to enhance the interpretability and predictive performance of the models. The research begins with data collection and preprocessing, followed by the implementation of the HMM to identify hidden states representing distinct economic conditions. Subsequently, LSTM models are trained using the original and augmented data sets, allowing for comparative analysis and evaluation. The results demonstrate that incorporating HMM-derived data improves the predictive accuracy of LSTM models, particularly in capturing complex temporal patterns and mitigating the impact of volatile economic conditions. Additionally, the paper discusses the implementation of Integrated Gradients for model interpretability and provides insights into the economic dynamics reflected in the forecasting outcomes.

Nikolaos Kalyviotis, Christopher D. F. Rogers, Geoffrey J. D. Hewings

Transport infrastructure systems operate in, and are shaped by, the specific context in which they are expected to perform and contribute to the system-of-systems that support civilised life; they must strive to be sustainable and resilient. However, transport, one of the economic infrastructures, is viewed narrowly in political circles as a vehicle for economic prosperity: political focus falls on the economic pillar of sustainability. One perennial challenge concerns the inclusion of social and environmental value into such performance judgements. A deep understanding of system interdependencies is essential when comparing input output tables (a top down approach) with cost benefit analysis (CBA, a bottom up approach). CBA works best when there is adequate information to calculate a monetary value for all economic, social, and environmental outcomes, whereas input output tables are most effective when environmental and social value are kept distinct from economic value and where the beneficial economic impacts extend across multiple sectors (CBA is inadequate in this regard). This research uses the World Input Output Database and principal component analysis to develop a model to capture this complex accounting process.In recognising how past interdependencies inform future development, this study s model provides new insights into indirect economic value creation within infrastructure systems.

Fayzah Alshammari, Yunpeng Luo, Qi Alfred Chen

Indoor Delivery Robots (IDRs) play a vital role in the upcoming fourth industrial revolution, autonomously navigating and transporting items within indoor environments. In this work, we thus aim to conduct the first security analysis of the IDR systems considering both cyber- and physical-layer attack surface and domain-specific attack goals across security, safety, and privacy. As initial results, we formulated a general IDR system architecture from 40 commercial IDR models and then performed an initial cyber-physical attack entry point identification. We also performed an experimental analysis of a real commercial IDR robot-side software and identified several vulnerabilities. We then discuss future steps.

Yanqiao Deng, Minda Ma, Nan Zhou et al.

National carbon peak track and optimized provincial carbon allocations are crucial for mitigating regional inequality within the commercial building sector during China's transition to carbon neutrality. This study proposes a top-down model to evaluate carbon trajectories in operational commercial buildings up to 2060. Through Monte Carlo simulation, scenario analysis is conducted to assess carbon peak values and the corresponding peaking year, thereby optimizing carbon allocation schemes both nationwide and provincially. The results reveal that (1) the nationwide carbon peak for commercial building operations is projected to reach 890 (+- 50) megatons of carbon dioxide (MtCO2) by 2028 (+- 3.7 years) in the case of the business-as-usual scenario, with a 7.87% probability of achieving the carbon peak under the decarbonization scenario. (2) Significant disparities will exist among provinces, with Shandong's carbon peak projected at 69.6 (+- 4.0) MtCO2 by 2029, approximately 11 times higher than Ningxia's peak of 6.0 (+- 0.3) MtCO2 by 2027. (3) Guided by the principle of maximizing the emission reduction potential, the optimal provincial allocation scheme reveals the top three provinces requiring the most significant reductions in the commercial sector: Xinjiang (5.6 MtCO2), Shandong (4.8 MtCO2), and Henan (4.7 MtCO2). Overall, this study offers optimized provincial carbon allocation strategies within the commercial building sector in China via dynamic scenario simulations, with the goal of hitting the carbon peak target and progressing toward a low-carbon future for the building sector.

Kenshi Yanagisawa, Reiko Furusho, Shiomi Nemoto et al.

The intensity spectra recovered from the spectroscopic photographic plates were compared with the CCD spectra, and we found the difference between the two was 2.5%.The measurements were taken using a commercial flatbed scanner instead of a microdensitometer. The results indicate that the following two statements are inaccurate: (1) Correct measurement of spectroscopic plates requires a microdensitometer, and a commercial flatbed scanner is insufficient; (2) The spectrophotometric accuracy of spectroscopic plate is approximately 10% accurate. These results will encourage the creation and publication of a digital archive of spectroscopic plates. This paper presents the measurement of spectroscopic plates, the method of recovering intensity spectra from photographic density spectra, the results of comparison with CCD spectra, and discusses the causes of the high accuracy spectra obtained with a commercial flatbed scanner.

Ganapati Kumar Biswas

Financial inclusion is touted one of the principal drivers for economic growth for an economy. The study aims to explore the impact of financial inclusion on economic growth in Bangladesh. In my study, I used the number of loan accounts as the proxy for financial inclusion. Using time series data from spans from 2004-2021, the study revealed that there exists a long-run relationship between GDP, financial inclusion, and other macroeconomic variables in Bangladesh. The study also found that financial inclusion had a positive impact on economic growth of Bangladesh during the study period. Therefore, the policymakers and the central bank of Bangladesh as the apex authority of financial system should promote financial inclusion activities to achieve sustainable economic growth.

Eilam Shapira, Omer Madmon, Itamar Reinman et al.

Large Language Models (LLMs) show significant potential in economic and strategic interactions, where communication via natural language is often prevalent. This raises key questions: Do LLMs behave rationally? How do they perform compared to humans? Do they tend to reach an efficient and fair outcome? What is the role of natural language in strategic interaction? How do characteristics of the economic environment influence these dynamics? These questions become crucial concerning the economic and societal implications of integrating LLM-based agents into real-world data-driven systems, such as online retail platforms and recommender systems. To answer these questions, we introduce a benchmark for standardizing research on two-player, sequential, language-based games. Inspired by the economic literature, we define three base families of games with consistent parameterization, degrees of freedom and economic measures to evaluate agents' performance (self-gain), as well as the game outcome (efficiency and fairness). We develop an open-source framework for interaction simulation and analysis, and utilize it to collect a dataset of LLM vs. LLM interactions across numerous game configurations and an additional dataset of human vs. LLM interactions. Through extensive experimentation, we demonstrate how our framework and dataset can be used to: (i) compare the behavior of LLM-based agents in various economic contexts; (ii) evaluate agents in both individual and collective performance measures; and (iii) quantify the effect of the economic characteristics of the environments on the behavior of agents. Our results suggest that the market parameters, as well as the choice of the LLMs, tend to have complex and interdependent effects on the economic outcome, which calls for careful design and analysis of the language-based economic ecosystem.

Ayse D. Lokmanoglu, Carol K. Winkler, Kareem El Damanhoury et al.

With globalization's rise, economic interdependence's impacts have become a prominent factor affecting personal lives, as well as national and international dynamics. This study examines RT's public diplomacy efforts on its non-Russian Facebook accounts over the past five years to identify the prominence of economic topics across language accounts. Computational analysis, including word embeddings and statistical methods, investigates how offline economic indicators, like currency values and oil prices, correspond to RT's online economic content changes. The results demonstrate that RT uses message reinforcement associated economic topics as an audience targeting strategy and differentiates their use with changing currency and oil values.

Sergey Masaev

A review of economic approaches showed the lack of a universal method for assessing management decisions in the face of an increasing volume of analyzed data and changing parameters of the external environment. The method of integral indicators is proposed. Integral indicators are one of the modern methods for researching the behavior of an enterprise. It provides an assessment of the impact of the external environment. It shows the ability of the enterprise to adapt to new conditions. The dynamics of the correlation indicator shows the reaction of the enterprise to the impact of external factors. The purpose of the scientific work was achieved: the optimal control of the enterprise was carried out in the conditions of changing the parameters of the external environment For this, the model of the economic object and the method of its analysis are formalized. The structure of an economic object (enterprise) is given. The characteristics of the parameters of the external environment are given. The state of an economic object (enterprise) is modeled taking into account the influence of the external environment. With the help of the software package created by the author, six optimal options for control decisions have been analyzed. The state of an economic object has been modeled depending on the state of the external environment by 5,000 parameters. The research showed significant changes in the values of the correlation of the parameters of the system and the intensity of business processes when the conditions for the functioning of the system change. The optimal control of an economic object (enterprise) is selected according to the integral indicator.

J. Yadav, P. Tomar, Y. Singh et al.

Abstract Avian mycoplasmosis mainly caused by Mycoplasma gallisepticum and M. synoviae is an economically important disease of poultry industry. It causes huge economic losses in terms of decrease in weight gain, feed conversion efficiency, egg production, hatchability; increase in embryo mortality, carcass condemnation, prophylaxis and treatment cost in broiler, layer and breeder flocks. The disease is caused by four major pathogenic mycoplasmas viz., M. gallisepticum (MG), M. synoviae (MS), M. meleagradis (MM) and M. iowae (MI). The MG and MS are World Organization for Animal Health listed respiratory pathogens. MG causes chronic respiratory disease in chicken and infectious sinusitis in turkey; however, MS causes synovitis and airsacculitis in birds. The infection is transmitted both horizontally and vertically. Prevention and control measures of avian mycoplasmosis mainly comprises of biosecurity, treatment and vaccination. For vaccination of birds, inactivated bacterins, live attenuated and/or recombinant live poxvirus vaccines are commercially available against MG and MS infection. The present systematic review summarizes the different epidemiological studies carried out on MG and MS infection in poultry in different geographical locations of India and abroad over the last decade (2010–2020), economic impact, diagnosis and prevention and control.

Ting Liang, Tongtong Zhang, Xipeng Lin et al.

Liquid air energy storage (LAES) uses air as both the storage medium and working fluid, and it falls into the broad category of thermo-mechanical energy storage technologies. The LAES technology offers several advantages including high energy density and scalability, cost-competitiveness and non-geographical constraints, and hence has attracted a growing interest in recent years. As a result, several reviews have been published on the topic. However, these reviews covered little in the following aspects of LAES: dynamic simulation and optimisation, key components for LAES, LAES applications through integration, and unified economic and cost models for LAES. This article provides a comprehensive review on the LAES technology and fills the above gaps. Apart from applications in electrical grids such as peak-shaving, load shifting, and dealing with intermittency of renewable generation, the review also shows a diverse range of other LAES applications through integration, including waste heat and cold energy recovery and utilisation, multi-energy vector service provision, and sector coupling for chemical production and carbon capture. The review also leads to the recommendation of several areas for future research and development, including dynamic characteristics of whole LAES system integrated with renewables and end users; thermo-economic and dynamic optimization of stand-alone LAES and integrated systems; and experimental study on commercial systems.

KADDOUR KHIR, RANIA DAT

This paper focuses on one of the components of the working capital requirements, the receivables item, an essential asset in the optimization of working capital requirements. Our research objective is to analyze the efficiency of the receivables management at the french pharmaceutical company Sanofi, as well as its role in optimizing the working capital requirement. Fort that, we used the software SPSS to analyse the correlation of the working capital requirements of Sanofi with its components.

Pol Jané-Soneira, Albertus J. Malan, Ionela Prodan et al.

In this paper, we introduce the novel concept of economic ports, allowing modular and distributed optimal operation of networked microgrids. Firstly, we design a novel price-based controller for optimal operation of a single microgrid and show asymptotic stability. Secondly, we define novel physical and economic interconnection ports for the microgrid and study the dissipativity properties of these ports. Lastly, we propose an interconnection scheme for microgrids via the economic ports. This interconnection scheme requires only an exchange of the local prices and allows a globally economic optimal operation of networked microgrids at steady state, while guaranteeing asymptotic stability of the networked microgrids via the passivity properties of economic ports. The methods are demonstrated through various academic examples.

Duncan Earl, K Karunaratne, Jason Schaake et al.

We present the architecture and near-term use cases for a first-generation commercial quantum network. We define the foundational hardware and software elements required to operate and manage the network. Finally, we discuss the configuration of this network for near-term consumer applications and propose how the network can support the broader technical goals of the quantum information science community.

A. Kravets, V. Bogachev, I. Egorova et al.

Abstract A multicriteria approach with temporal indicators in optimizing the distribution of cargo flows in multimodal transport and technological system is presented. Based on the infrastructure indicators of the considered part of the railway landfill and the economic and geographical volumes of cargo accumulation, a mathematical model of the transport process is developed, expressed as a nonlinear integer programming problem. For various combinations of several objective functions, which are temporary indicators of the transportation process, an algorithm of optimal distribution of cargo flows for the considered loading stations and unloading stations is developed. Computational procedures for finding the Pareto optimal distribution of cargo flows are implemented in the environment of a computer mathematics system, which can be Free Ware. The distribution of grain cargo flows, which, as well known, are especially relevant from a commercial point of view for Russian exports, was chosen as a specific object for implementing the developed optimization approach.

CARINA-ELENA STEGĂROIU, AMELIA-GEORGIANA BONCEA, CONSTANŢA ENEA

The current pandemic context has led to the rapid transition of all online teaching activities, and the security of all activities has become vulnerable, largely due to limited awareness by students and teachers, creating a security breach through the emergence of channels. more accessible to cybercriminals. The infrastructure and educational platforms made available to students are low in terms of cyber security. The task of ensuring a safe education process for all parties involved in the process is, on the one hand, the state, which should anticipate major security risks, set standards and best practices to guide the actors in the educational process in one direction. with low risks.