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Der digitale Wandel hat in den letzten Jahrzehnten die Geisteswissenschaften transformiert. Jede Art von Tätigkeit in Forschung und Lehre hat zumindest einen digitalen Anteil und sei es, dass dieser nur in der Nutzung digitaler Informationsinfrastrukturen für die Recherche besteht. In den historisch arbeitenden Wissenschaften mag der Beharrungswille größer sein als in anderen Disziplinen, aber auch hier haben sich in den vergangenen Jahren zwei Tendenzen herauskristallisiert: Erstens nimmt die Arbeit mit digitalen Surrogaten analoger Quellen zu – und wird noch mehr an Bedeutung gewinnen, je mehr die Fächer mit digital geborenen Quellen arbeiten. Zweitens werden die historischen Fächer selbst zu Produzenten von Forschungsdaten. Der Beitrag zeichnet diese Veränderungen nach und zeigt exemplarisch aktuelle Verfahren, Workflows und deren Voraussetzungen. Für die Gedächtniseinrichtungen argumentiert er, dass diese die sich abzeichnende Entwicklung nicht nur nicht ignorieren dürfen, sondern dass sie bereits jetzt ein wichtiger Teil des digitalen Umbruchs sind, der sich durch eine Konvergenz von Datenkompetenzen, aber auch von Verfahren und Modellierungen über die Grenzen der Fächer hinweg auszeichnet. Abschließend reflektiert der Beitrag, auf welche Weise Gedächtniseinrichtungen den Anforderungen dieser Veränderung und neuer Gruppen von Nutzenden gerecht werden können und welche Herausforderungen auch epistemischer Art in den bestehenden Sammlungen ruhen. The digital turn has shaped the humanities in recent decades. Every kind of activity in research and teaching now has at least a digital component, even if this only implies using digital information infrastructures for research. In the historical scholarship, the will to persevere time honed approaches may be greater than in other disciplines, yet even here two trends have emerged in recent years: firstly, scholarship based on datafied surrogates of analogue sources is increasing–and will become even more important the more scholars work with digitally born sources. Secondly, the historical disciplines themselves are becoming producers of research data. This paper traces the transformation, illustrating current techniques, workflows, and their prerequisites arguing that memory institutions should not only not ignore the development, but that they form already an important part of the digital transformation. For memory institutions the digital turn is characterised by a convergence of data competencies as well as procedures and models across the traditional boundaries of the disciplines. Finally, the article reflects on how memory institutions can meet the requirements of this transformation and new groups of users and what challenges, of an epistemic nature as well, are inherent to the existing collections. [ABSTRACT FROM AUTHOR]

The realization of common prosperity is an essential requirement of socialism and an important feature of modernization with Chinese characteristics. New infrastructure development is a new engine for general and balanced economic growth in the digital economy era and plays an important role in achieving high-quality and inclusive economic growth. This study innovatively incorporated new infrastructure development into the theoretical analysis framework of common prosperity. Based on the data of 30 provincial-level samples from 2011 to 2020 and using the entropy weight method and coupled coordination model, this paper measured the level index of new infrastructure development and that of common prosperity. On this basis, the paper empirically examined the influence mechanism of new infrastructure development on common prosperity, the process of marketization, and the moderating role of rural human capital investment. The results showed that, overall, new infrastructure development significantly promoted common prosperity. Regionally, the new infrastructure development promoted the common prosperity of China' s southern region but had an obvious inhibitory effect on its northern region. Although new infrastructure was divided into different categories, fusion infrastructure, innovation infrastructure, and information infrastructure all promoted common prosperity to different degrees, but in terms of impact coefficient, fusion infrastructure, information infrastructure, and innovation infrastructure all declined in turn, as a matter of fact. The marketization process, rural health, education and training, and the migration of human capital investments all contributed to strengthening the role of new infrastructure development in promoting common prosperity. This study not only helps to clarify the theoretical correlation between new infrastructure development and common prosperity and enrich the sustainable or inclusive assessment framework of new infrastructure development from the perspective of common prosperity, but also helps to coordinate the goals and tasks of new infrastructure development and common prosperity for governments at all levels and relevant departments in practice and provides empirical evidence and policy implications. [ABSTRACT FROM AUTHOR]

Copyright of Hydrogeology & Engineering Geology / Shuiwendizhi Gongchengdizhi is the property of Hydrogeology & Engineering Geology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: The purpose of this paper is to highlight the drivers, barriers, benefits and risks affecting the integration of Internet of Things (IoT) into the e-government and to provide a future research agenda. Design/methodology/approach: Existing literature examining the relationships between e-government and IoT is scanned and evaluated by conceptualizing the IoT concept in the e-government perspective. Findings: The study shows that there are drivers to integrate IoT in e-government, such as ensuring the economy, efficiency and effectiveness of government operations, which would largely establish a relationship between the government and the citizens. Furthermore, there are barriers to such integration, given the lack of political will, the appropriate information technology infrastructure, the training of the stakeholders with a focus on the employee and the like. Originality/value: The integration of IoT in e-government is a novel and weakly explored concept, particularly in the light of new advances such as blockchain in the e-government, which requires further exploration and conceptualization, thereby achieving a shared/common vision and body of knowledge for its further successful and sustainable adoption – to the best of the authors' knowledge, the current study is one of these initial attempts. [ABSTRACT FROM AUTHOR]

Blockchain technology has attracted a lot of attention lately because it is seen as an all-purpose method for conducting online transactions between unidentified parties without the need for a centralized authority. Modern developers and businesspeople think it will disrupt or even change both the government and industry. In this setting, government-focused blockchains are becoming increasingly prevalent. Several recent studies highlighted use cases in the public sector for decentralized information infrastructures. Blockchain is expected to revolutionize or at least simplify many governmental functions. However, because blockchain use has yet to be widely adopted in government or industrial settings, the question arises: what are the technical hurdles impeding blockchain adoption? To that purpose, a systematic literature assessment of 29 academic articles investigating software engineering problems in blockchain technology for government applications has been done. The papers are initially inductively analyzed in order to illustrate and identify the issues frequently highlighted in academic literature. Furthermore, a theoretical framework is discussed by relying on models used in traditional software development, which is then followed by deductive analysis to map out the blockchain use cases and future trends connected to the difficulties. [ABSTRACT FROM AUTHOR]

Copyright of Raumforschung und Raumordnung is the property of Oekom Verlag GmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Railway Signalling & Communication Engineering is the property of Railway Signalling & Communication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Learning Analytics (LA) and tools for intelligent analysis of data accumulated in the information systems used in higher education institutions (HEIs) allow quality experts to increase the effectiveness of processes for monitoring, quality assurance and evaluation of training. The paper presents LA model and a correspondent software tool designed for the needs of quality experts in Bulgarian higher education institutions. The tool allows them to monitor and improve the learning process. However, the experiments presented here show that the tool can also significantly assist in the preparation of selfassessment reports for internal and external quality assessment in HE. Research and experiments with the model and the LA tool under consideration are conducted on the basis of the information infrastructure of a typical Bulgarian university - University of Plovdiv "Paisii Hilendarski". [ABSTRACT FROM AUTHOR]

Data and information are considered today as the "new oil" or the "new gold" in almost all aspects of life and economic domains, such as industry, healthcare, education, entertainment and more. The so‐called 4th Industrial Revolution1 is based on the digital transformation derived from the Big Data revolution, through the capability of storing huge amounts of data and performing very sophisticated analytics. In this paper, we present opportunities for Systems Engineering (SE) to evolve towards a data ‐driven and evidence ‐based discipline, thereby making better systems and engineering decisions. We discuss how systems engineers can apply data‐driven characteristics through systems engineering processes and programs. The classical Model‐Based Systems Engineering (MBSE) approaches are presented here as powerful tools to collect, generate, and analyze data on systems under development. In addition, the "Digital Twin" concept is presented here in the context of system design. We highlight the challenges for systems engineering to become an evidence‐based discipline. Moreover, we empha‐size research and development in systems engineering processes using statistical techniques in the design and analysis of systems testing, and Model‐Based Systems Engineering (SE) as a source for evidence‐based engineering decisions. The success of data driven SE in organizations depends on the information and data analytics infrastructure in these organizations. An information quality frame‐work is proposed for evaluating organizational information infrastructure. In addition, it is proposed to assess the data analytics maturity level in organizations. The level of data analytics is the basis for planning implementation programs of data‐driven and evidence‐based systems engineering. The paper concludes with a case study based on a real‐life complex project, and lessons learned for ef‐fective data analytics implementation. [ABSTRACT FROM AUTHOR]

Japan is currently facing serious issues associated with an aging society and negative population growth. Urban structures, remnants of economic prosperity, are now hindrances to sustainable urban development, driving municipalities to seek efficient methods to manage this growth. Japanese municipalities continuously conduct surveys to collect data for urban planning purposes. However, lack of standardization and poor visualization tools prevent coordination and consensus-building among stakeholders during the planning process. The "i-Urban Revitalization" (i-UR) is an information infrastructure promoted by the Japanese government expected to enable municipalities to analyze and visualize their goals related to that process.This paper presents the implementation of i-UR. One approach employed for data standardization is to develop a CityGML Application Domain Extension (ADE) for urban planning that covers detailed attributes of city objects and mechanisms for global representation and analysis necessary for urban planning. The effectiveness of this ADE is being evaluated through data implementation and visualization experiments conducted in three municipalities in Japan. A prototype for the proposed "AR Consensus-formation system" is being developed for further utilization of the ADE. In addition, Ideathon events are being held to develop human resources in municipalities to promote urban revitalization and facilitate i-UR use. The ADE and i-UR tools described in this paper are expected to evolve based on feedback from users and experimental results. [ABSTRACT FROM AUTHOR]

This paper investigates the executive modalities and implications of digital platforms for business process management to rethink and redesign the operational processes in the inter-organizational relationship systems among public and private players in seaports. The research question is: how can digital platforms based on the information technology infrastructure rethink and redefine the business processes in seaport organizations? A multiple case study methodology, comparing two Italian port experiences which adopt digital platforms (TPCS and GAIA), evidences several benefits, including the reduction of time schedules and paper documents in the operational processes in relation to sustainability policy. Consequently, the performance of the whole business process increases; more generally, the sea-land supply chain improves its performance and its inter-organizational relationships. This paper aims to fill the existent research gap by providing a broad analysis of the phenomenon and empirical evidence. [ABSTRACT FROM AUTHOR]

The environmental problems caused by global warming have made low-carbon development a focus of attention worldwide. At the same time, the digital economy based on the Internet, big data, cloud computing, and other new technologies have become an important force in driving the country's economic development. Can the digital economy contribute to low-carbon development while driving the computing infrastructure? This paper selects 210 sample data points from 15 RCEP countries from 2005 to 2018 and uses OLS robust standard error regression to study the impact of the digital economy on carbon emissions and its mechanism of action. It is found that there is a significant inverted U-shaped relationship between the digital economy and carbon emissions, while the dual effects of the digital economy and the level of information infrastructure have a suppressive effect on carbon emissions. Based on the above research results, the following insights are proposed: strengthen the dual development of the digital economy and information infrastructure in RECP countries; enhance the research and development of digital economy products; and improve technological support capabilities. [ABSTRACT FROM AUTHOR]

This paper adopts knowledge mapping combined with a deep neural network algorithm to conduct in-depth research and analysis on the current situation and development of the industrial economy and designs a visual analysis model of economic development based on knowledge mapping combined with a deep neural network algorithm. Cultivate the concept of coordinated development and legal system of the subject, improve the awareness of network security and integrity self-discipline of the subject, improve the level of network hardware equipment manufacturing, improve the level of network platform construction, build a network security technology prevention system, improve the repair system of network information alienation, set up a specialized agency setting for the coordinated development of network ecology and industrial economy, and increase the capital investment in network infrastructure and network information technology research and development. A framework of breadth and depth recommendation ranking based on a knowledge graph is proposed and implemented. This paper provides a visual analysis method to sort and classify multivariate data. The method first determines users' preferences through their interactive operations, calculates the weights of each attribute according to the users' preference model, then uses the obtained attribute weight sets to sort the whole data set, and finally completes the category classification according to the sorting results and the users' markings on some data. The visual display allows users to intuitively perform data sorting and classification operations and quickly understand the characteristics and category features of the data. The framework achieves modeling and integration of knowledge graph neighborhood information from breadth dimension and depth dimension to realize personalized recommendation sorting and improves the F1 metrics by 8.59%, 14.36%, and 15.22% on the public datasets Amazon-book, Yelp2018, and ILast-FM compared with the previous optimal model. [ABSTRACT FROM AUTHOR]

Smart infrastructure is positioned as central to the liveability and viability of rural and regional towns in Australia. The Australian Government's Smart Cities Plan and Regional Connectivity Program includes Smart Investment in regional areas and the New South Wales Government has prioritised connectivity and telecommunications infrastructural development through the Regional Digital Connectivity program. And yet regional and rural communities are typically excluded from the evidence base for smart technologies and services. Local Aboriginal Land Councils are also important stakeholders in managing the digital processes associated with information and infrastructure moving across different Countries. This paper draws on data from the 'It just works!': Regional and rural consumer understandings of smart technologies in North West New South Wales project, including over 130 survey responses and interviews with shire councillors, land councillors, and consumers on smart development and Internet infrastructure in the region. In the areas surveyed, smart regional policy is variously emerging, non‐existent, or assembled from existing policy domains and regulation involving the Internet, telecommunications, regional development, First Nations, and local government. We argue that regional and rural understandings of growth and development are experienced through the infrastructuring processes of Internet quality, availability, and speed. [ABSTRACT FROM AUTHOR]

Over the past 20 years, drive-by monitoring, using data from sensors in passing vehicles, has become increasingly popular due to its low cost and high efficiency at a network level. Despite significant advances, the dynamics of vehicles remains one of the main challenges to overcome before accurately identifying critical information about the infrastructure being crossed, bridges or road pavements. This paper introduces a novel approach to estimating bridge profiles (i.e. road surface profiles on the bridges) and vehicle properties using a fleet of passing vehicles. In this method, bridge profiles are first calculated using the innovative Inverse Newmark-beta integration method, and the cross-entropy optimization algorithm is employed to solve the problem. Numerical results demonstrate that the proposed approach is highly effective in extracting bridge profiles and predicting vehicle properties, even in scenarios with significant levels of measurement noise. [ABSTRACT FROM AUTHOR]

In the field of multimodal sentiment analysis, it is an important research task to fully extract modal features and perform efficient fusion. In response to the problems of insufficient semantic information and poor cross-modal fusion effect of traditional sentiment classification models, this paper proposes a composite hierarchical feature fusion method combined with prior knowledge. Firstly, the ALBERT (A Lite BERT) model and the improved ResNet model are constructed for feature extraction of text and image, respectively, and high-dimensional feature vectors are obtained. Secondly, to solve the problem of insufficient semantic information expression in cross-scene, a prior knowledge enhancement model is proposed to enrich the data characteristics of each modality. Finally, to solve the problem of poor cross-modal fusion effect, a composite hierarchical fusion model is proposed, which combines the temporal convolutional network and the attention mechanism to fuse the sequence features of each modality information and realizes the information interaction between different modalities. Experiments on MVSA-Single and MVSA-Multi datasets show that the proposed model is superior to a series of comparison models and has good adaptability in new scenarios. [ABSTRACT FROM AUTHOR]

The problem of detecting communities in real-world networks has been extensively studied in the past, but most of the existing approaches work on single-domain networks , i.e. they consider only one type of relationship between nodes. Single-domain networks may contain noisy edges and they may lack some important information. Thus, some authors have proposed to consider the multiple relationships that connect the nodes of a network, thus obtaining multi-domain networks. However, most community detection approaches are limited to multi-layer networks , i.e. networks generated from the superposition of several single-domain networks (called layers) that are regarded as independent of each other. In addition to being computationally expensive, multi-layer approaches might yield inaccurate results because they ignore potential dependencies between layers. This paper proposes a multi-domain discrete-time quantum walks (MDQW) model for multi-domain networks. First, the walking space of network nodes in multi-domain network is constructed. Second, the quantum permutation circuit of the coin state is designed based on the coded particle state. Then, using different coin states, the shift operator performs several quantum walks on the particles. Finally, the corresponding update rule is selected to move the node according to the measurement result of the quantum state. With continuous update iteration, the shift operator automatically optimizes the discovered community structure. We experimentally compared our MDQW method with four state-of-the-art competitors on five real datasets. We used the normalized mutual information (NMI) to compare clustering quality, and we report an increase in NMI of up to 3.51 of our MDQW method in comparison with the second-best performing competitor. The MDQW method is much faster than its competitors, allowing us to conclude that MDQW is a useful tool in the analysis of large real-life multi-domain networks. Finally, we illustrate the usefulness of our approach on two real-world case studies. [ABSTRACT FROM AUTHOR]

Data sharing and service reuse in the health sector pose significant privacy and security challenges. The European Commission recognizes health data as a unique and cost-effective resource for research, while the OECD emphasizes the need for privacy-protecting data governance systems. In this paper, we propose a novel approach to health data access in a hospital environment, leveraging homomorphic encryption to ensure privacy and secure sharing of medical data among healthcare entities. Our framework establishes a secure environment that enforces GDPR adoption. We present an Information Sharing Infrastructure (ISI) framework that seamlessly integrates artificial intelligence (AI) capabilities for data analysis. Through our implementation, we demonstrate the ease of applying AI algorithms to treated health data within the ISI environment. Evaluating machine learning models, we achieve high accuracies of 96.88% with logistic regression and 97.62% with random forest. To address privacy concerns, our framework incorporates Data Sharing Agreements (DSAs). Data producers and consumers (prosumers) have the flexibility to express their prefearences for sharing and analytics operations. Data-centric policy enforcement mechanisms ensure compliance and privacy preservation. In summary, our comprehensive framework combines homomorphic encryption, secure data sharing, and AI-driven analytics. By fostering collaboration and knowledge creation in a secure environment, our approach contributes to the advancement of medical research and improves healthcare outcomes. A real case application was implemented between Portuguese hospitals and universities for this data sharing. [ABSTRACT FROM AUTHOR]

Triggering economic growth is a requirement to promote human welfare and realize sustainable development in many developing countries. However, place-based policies' impact on economic growth is debatable, and its underlying mechanism is unknown. China's Old Revolutionary Development Program (ORDP) is a large-scale and novel type of place-based policy targeted at undeveloped regions in China. We evaluate the effect of ORDP on economic growth by employing a time-varying difference-in-differences model and further explore the potential mechanisms and heterogeneity effects. VIIRS/DNB nightlight data is used to measure economic growth. We find that ORDP can significantly promote economic growth by 4.0% and the result is still robust after several tests. Mechanism analysis shows that ORDP can improve economic growth through government intervention, industrial structure optimization, and information infrastructure construction. Heterogeneity analysis indicates that the ORDP performs better on economic growth in central Chinese cities and high-economy cities. At the same time, our paper provides three practical suggestions for stimulating economic growth in ORDP, which can be enlightening for other developing countries. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to determine whether there is a correlation between mobilization costs and project schedule performance of highway projects. In addition to this, the study will also determine if the mobilization costs are helping small or large highway projects in terms of improving the schedule performance. Design/methodology/approach: The data of 206 highway projects were collected from the Department of Transportation of two states with the help of questionnaire survey. The cost, schedule and mobilization costs data were collected. The performance metrics related to construction schedule growth and construction intensity were developed in order to test the research hypotheses: mobilization costs will increase the schedule performance of highway projects. The data were also divided into two groups based on project cost and analyzed to check whether the mobilization costs impact the schedule performance of these highway projects. Spearman's correlation test was conducted to determine the correlation between dependent and independent variables. In addition, a Mann–Whitney test was conducted to determine the difference in medians of construction schedule growth and the construction intensity of these two groups of projects. Findings: One major study finding was that there was no strong linear correlation between the mobilization cost percentage and the construction schedule growth and construction intensity of highway projects. However, the study found the projects that have 9% or more mobilization costs had significantly better schedule growth compared to the projects that have less than 9% mobilization costs. When data were analyzed based on the project size, it was found that this pattern was seen only in large projects costing equal to or more than $5 million. Practical implications: This study's findings have very crucial practical implications to state DOTs contract engineers. This study shows that the highway contract engineers need to provide the right amount of mobilization costs to complete their projects on and before schedule. If the correct amount of mobilization costs is not provided to the contractors, the impact of these mobilization costs on reducing the schedule growth will be negligible. The findings of this study will assist public agency decision makers to complete their projects on or before time by including the mobilization costs provision in the contract. The state DOTs can improve their schedule performance by providing enough financial help to the contractors so that they can improve their cash flows and complete projects successfully within the given timeframe. Originality/value: This paper contributes to the existing body of knowledge by validating the impact of mobilization costs on the schedule performance of highway projects. There has been no empirical study conducted prior to this to identify the role of mobilization costs on reducing the schedule growth of highway projects. [ABSTRACT FROM AUTHOR]

Copyright of Journal of South China University of Technology (Natural Science Edition) is the property of South China University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper analyzes the essence of the conceptual approach to the intellectual digital innovation economy, which will be formed based on the normal development of the digital economy. It is noted that most researchers of the economy of the modern era use many different concepts such as knowledge, digital, Internet, post-industrial, virtual, network, information, electronic, intellectual, etc. in their works. Scientific approaches to the study of the development problems of the intellectual economy formed in the new era are classified. As a result of summarizing existing scientific works, a new approach to the system of economic relations using modern innovative information technologies, the intellectual information environment efficiently developed with ICT, and the newly formed intellectual digital innovation economy are proposed. With the help of digital technologies, priority directions for developing information infrastructure, and Global digital space, including new business models, have been proposed. By using the concept of Industry 4.0 and "smart structures" as the driving force of the digital transformation of industrial development, taking advantage of the use of the "cyber-physical system" as a unified complex of information resources, systems, and physical processes and the Internet of Things, cloud, Big Data, artificial intelligence technologies, new recommendations on the formation of the economy were given. [ABSTRACT FROM AUTHOR]

This paper examines the impact of highway construction on the size distribution of manufacturing firms using Chinese firm and highway network data. I construct instrumental variables using historical and counterfactual road approaches to identify the causal effects of highway construction. I find that highway construction can increase firm size dispersion and market concentration. Areas near highways have a higher number of firms, more outsourcing activities, and more large firms; while areas further from highways have a higher share of new entry firms. [ABSTRACT FROM AUTHOR]

Conventional highway design approaches have primarily focused on the use of guidelines in the design of highways. These design guidelines provide nominal safety where conservative percentile values of the design inputs are used to account for the uncertainty associated with the inputs. Reliability-based analysis (RBA) been one of the elements of reliability, availability, maintainability, and safety (RAMS) has been identified as an effective method to account for the uncertainty in the design input and to assess the risk related to a particular design. RBA approaches have effectively been used for certain purposes in other disciplines. In highway geometric design literature, these methods were also investigated and showed promise. Given the compelling importance of RBA in highway design, this paper provides a systematic analysis and evaluation of RBA applications for ten highway geometric elements: stopping sight distance, passing sight distance, intersection sight distance, horizontal curve design, vertical curve design, number of freeway lanes, highway grade length, truck escape ramp, and design guide calibration. The review consists of four parts: the concept of RAMS, background on reliability theories, applications in highway geometric design, and guidelines for the use of reliability analysis. The literature review revealed that the application of reliability-based analysis in highway geometric design leads to significant improvements in traffic safety. It is our hope that this paper will serve as a source of information on RBA for highway designers and practitioners, promoting its development and application in highway geometric design. [ABSTRACT FROM AUTHOR]

Summarizes the content of the special issue of "Computational Intelligence" journal related to various aspects of the application of agents to support electronic business (e-business). Impact of electronic commerce on traditional business processes; Issues that limit the use of Web for commercial purposes; Requirements in relation to the infrastructure for e-business; Role of agent technologies in doing business over the Internet.

In the 1870s, microscopy societies began to proliferate in the United States. Most of these societies attracted microscopists from surrounding cities, but the American Postal Microscopical Club, modelled on the British Postal Microscopical Society, used the postal system to connect microscopists scattered across the country. Club members exchanged microscope slides and notes following a chain-letter system. The main objective of the club was to teach its members how to make permanent slides. Preparation and mounting methods required technical skill, which was, as even club members had to admit, difficult to learn without personal instruction. Yet members developed ways to share craft knowledge through the post. Drawing on the private notes of a member and published reports on the slides circulated, this paper challenges the widespread assumption that the generation of craft knowledge depended on the co-location of artisans. It argues that microscopists' knowledge of preparation methods was intertwined with their skill in building and navigating information infrastructures, and that by tracing these infrastructures we gain a better understanding of how craft knowledge travelled in the late nineteenth century. [ABSTRACT FROM AUTHOR]

This article analyses how a pair of nineteenth century commodity exchanges—in Chicago and New Orleans—shaped the sociotechnical infrastructures underlying two key types of market information—price quotations and crop statistics. Specifically, the paper investigates why these exchanges saw divergent outcomes, each successfully developing one information infrastructure but not the other. Prior scholarship has understood infrastructural development as the result of idiosyncratic, social structural alignments in actors' resources and desires. This paper, by contrast, examines how such structural elements interacted with practical resources available to exchanges based on their roles within infrastructures. Findings demonstrate that the exchanges gained influence in proportion to their discretion over an infrastructure's everyday operations and the market routines these enabled. This 'infrastructural power', or lack thereof, interacted with social structural resources in two distinct forms— 'feedback' in New Orleans and 'sacrifice' in Chicago—providing or denying each exchange the ability to shape infrastructures to its advantage. These findings suggest that analysts should pay closer attention to market dynamics as they relate to 'infrastructure in action'. [ABSTRACT FROM AUTHOR]

This editorial comes in three parts: encouragement to delve into the start of long-distance telecommunications in Australia; some remarks on telecommunications as infrastructure; and a brief introduction to the papers in this issue. [ABSTRACT FROM AUTHOR]

Tourism has become an information-intensive business that heavily relies on ICT to provide information and conduct transactions for consumers of touristic products and services. Thus, ICT infrastructure would play a major role in the development of the tourism sector. This paper aims to investigate the threshold effect of ICT infrastructure on tourism sector development in top10 African tourism destinations including ; Botswana, Egypt, Kenya, Morocco, Namibia, Rwanda, South Africa, Tanzania, Tunisia, Uganda. To do so, a double panel threshold regression model utilized over the period 2004 to 2017. The empirical results revealed a new perspective that there is a double-threshold effect of ICT infrastructure on the development of tourism sector, indicating a nonlinear effect of ICT infrastructure on the development of tourism sector in top 10 African tourism destinations. More specifically, the empirical results reveal that ICT infrastructure weakly and positively derives the number of intentional tourism arrivals and international tourist receipts when the level of ICT infrastructure is less or equal to the first threshold, while it strongly and positively derives the number of intentional tourism arrivals and international tourist when the level of ICT infrastructure is less or equal to the first and second thresholds. Thus, this paper provides important implications for policy makers, in that maximizing the benefits from information technology in developing tourism sector can be achieved when its level between certain critical threshold values. [ABSTRACT FROM AUTHOR]

This paper investigates the potential link between changes in NASA's Black Marble VIIRS/NPP Gap-Filled Lunar BRDF-Adjusted Nighttime Lights Daily L3 Global 500 m Linear Lat Lon Grid (VNP46A2) nighttime lights product (NTL) and human dynamics, particularly population counts and changes at a variety of spatial and temporal scales. We conducted analyses in four case studies at varying resolutions to explore the relationship of NTL data for population studies, including demographic research, disaster mitigation and adaptation planning, and infrastructure development. The analyses were conducted using different administrative geographies, including a refugee camp, a subnational region, and a country. We compared changes in population counts, density, migration, and displacement against changes in daily, weekly, monthly, and annual NTL values. Our case study results demonstrate that out-migration does not always lead to a decrease in NTL. We found that rural population decline did not correspond to a decrease in NTL. Despite significant out-migration in many rural areas NTL remained largely unchanged. NTL provided essential information on infrastructure damage in the short-term aftermath of this disaster; however, NTL alone was not correlated to the location of displaced individuals. Through news reports, we were able to corroborate the NTL changes to downtimes of the electrical systems. Monthly NTL averages were highly correlated to population counts, but a pixel-level analysis showed that the changes in NTL were primarily attributed to economic diversification. In summary, NTL is the product of several factors including demographic, environmental, economic, and political forces that shape electricity infrastructure, and we suggest that NTL data must first be parameterized with ancillary ground-level information in order to be effectively applied to population models. [ABSTRACT FROM AUTHOR]

With the growing popularity of autonomous electric vehicles (AEVs), optimizing their path-planning and charging strategy has become a critical research area. However, the dynamic nature of transport networks presents a significant challenge when ensuring their efficient operation. The use of vehicle-to-everything (V2X) communication in vehicular ad hoc networks (VANETs) has been proposed to tackle this challenge. However, establishing efficient communication and optimizing dynamic paths with charging selection remain complex problems. In this paper, we propose a joint push–pull communication mode to obtain real-time traffic conditions and charging infrastructure information (i.e., charging stations and energy segments). We also analyze the selection of relay vehicles in multi-hop communication routing, considering factors such as link stability, vehicle distance, and reputation values. Furthermore, we formulate a dynamic optimization problem based on real-time information to minimize travel and charging costs. Our proposed algorithm enables AEVs to obtain charging services from charging stations and conduct dynamic wireless charging via energy segments. We present a dynamic real-time A* algorithm to solve the path-optimization problem and a dynamic real-time charging selection algorithm based on dynamic path optimization when the state of charge is lower than the charging threshold. Extensive simulations demonstrate that the proposed joint push-pull communication mode can provide vehicles the up-to-date information and the developed optimization algorithms effectively reduce travel and charging costs. [ABSTRACT FROM AUTHOR]

The advancements in communication speeds have enabled the centralized financial market to be faster and more complex than ever. The speed of the order execution has become exponentially faster when compared to the early days of electronic markets. Though the transaction speed has increased, the underlying architecture or models behind the markets have remained the same. These models come with their own disadvantages. The disadvantages are usually faced by non-institutional or small traders. The bigger players, such as financial institutions, have an advantage over smaller players because of factors such as information asymmetry and access to better infrastructure, which give them an advantage in terms of the speed of execution. This makes the centralized stock market an uneven playing field. This paper discusses the limitations of centralized financial markets, particularly the disadvantage faced by non-institutional or small traders due to information asymmetry and better infrastructure access by financial institutions. The authors propose the usage of blockchain technology and the data highway protocol to create a decentralized stock exchange that can potentially eliminate these disadvantages. The data highway protocol is used to generate new blocks with a flexible finality condition that allows for the consensus mechanism to configure security thresholds more freely. The proposed framework is compared with existing frameworks to confirm its effectiveness and identify areas that require improvement. The evaluation of the proposed approach showed that the improved highway protocol boosted the transaction rate compared to the other two mechanisms (PoS and PoW). Specifically, the transaction rate of the proposed model was found to be 2.2 times higher than that of PoS and 12 times higher than that of the PoW consensus model. [ABSTRACT FROM AUTHOR]

This paper investigates the frequent claim that planning is a 'barrier' to developing digital networks (mobile telephony and broadband), causing 'delay' and deficits in rural network coverage. It draws on planning applications data and expert interviews gathered in Wales. It found only a relatively small proportion of infrastructure applications failing to gain consent but that developers did perceive planning uncertainty and constraints to adversely affect network roll out. However, economics rather than planning has been the central factor limiting rural network coverage. More fundamentally, framing planning as a 'barrier' to infrastructure delivery ignores how planning mediates between alternative technological pathways. [ABSTRACT FROM AUTHOR]

Vehicle trajectory prediction is an important decision-making and planning basis for autonomous driving systems that enables them to drive safely and efficiently. To accurately predict vehicle trajectories, the complex representations and dynamic interactions among the elements in a traffic scene are abstracted and modelled. This paper presents vehicle–road relationships net, a deep learning network that extracts features from vehicle–road relationships and models the effects of traffic environments on vehicles. The introduction of geographic highway information and the calculation of spatiotemporal distances with a reference not only unify heterogeneous vehicle–road relationship representations into a time series vector but also reduce the requirement for sensing transient changes in the surrounding area. A hierarchical long short-term memory network extracts environmental features from two perspectives—social interactions and road constraints—and predicts the future trajectories of vehicles by their manoeuvre categories. Accordingly, vehicle–road relationships net fully exploits the contributions of historical trajectories and integrates the effects of road constraints to achieve performance that is comparable to or better than that of state-of-the-art methods on the next-generation simulation dataset. [ABSTRACT FROM AUTHOR]

The application of Building Information Modeling (BIM) in infrastructure and structural projects, known as Integrated Structural and Infrastructure Modeling (ISIM), has gained attention in recent years due to its potential to revolutionize the construction industry. By providing a digital representation of the built environment, BIM allows for improved collaboration and communication between project stakeholders, leading to enhanced project outcomes. The ISIM approach is centered on the creation of a digital twin, a three-dimensional model of the infrastructure or structure, which serves as a virtual replica of the physical asset. This digital twin provides a platform for analysis, decision-making, and management throughout the project lifecycle, from design and construction to operation and maintenance. One of the key benefits of the ISIM approach is the ability to optimize the construction process, reducing costs, and improving efficiency. The digital twin allows for the identification of potential issues in the design phase, enabling them to be addressed before construction begins. The model can also be used to simulate different scenarios, providing insights into the most effective construction methods, sequencing, and scheduling. Additionally, the use of ISIM can facilitate collaboration and communication among project stakeholders, including architects, engineers, contractors, and owners. The digital twin provides a shared platform for all stakeholders to access and contribute to, allowing for real-time feedback and decision-making. This increased collaboration can lead to reduced errors, improved quality, and enhanced project outcomes. In this paper the authors propose the example of the Meier bridge in Alessandria starting from the 2D drawings to create the 3D model and link it to the external context using Autodesk Infraworks software. A virtual reality implementation has been considered as useful tool to improve the maintenance management. [ABSTRACT FROM AUTHOR]

Preventive maintenance practices have been proven to reduce maintenance costs in many industries. In the mining industry, preventive maintenance is the main form of maintenance, especially for mobile equipment. With the increase of sensor data and the installation of wireless infrastructure within underground mines, predictive maintenance practices are beginning to be applied to the mining equipment maintenance process. However, for the transition from preventive to predictive maintenance to succeed, researchers must first understand the maintenance process implemented in mines. In this paper, we conducted interviews with 15 maintenance experts from 7 mining sites (6 gold, 1 diamond) across East-Canada to investigate the maintenance planning process currently implemented in Canadian mines. We documented experts' feedback on the process, their expectations regarding the introduction of predictive maintenance in mining, and the usability of existing computerized maintenance management software (CMMS). From our results, we compiled a summary of actual maintenance practices and showed how they differ from theoretical practices. Finally, we list the Key Performance Indicators (KPIs) relevant for maintenance planning and user requirements to improve the usability of CMMS. [ABSTRACT FROM AUTHOR]

Complex networks have now become integral parts of modern information infrastructures. This paper proposes a user-centric method for detecting anomalies in heterogeneous information networks, in which nodes and/or edges might be from different types. In the proposed anomaly detection method, users interact directly with the system and anomalous entities can be detected through queries. Our approach is based on tensor decomposition and clustering methods. We also propose a network generation model to construct synthetic heterogeneous information network to test the performance of the proposed method. The proposed anomaly detection method is compared with state-of-the-art methods in both synthetic and real-world networks. Experimental results show that the proposed tensor-based method considerably outperforms the existing anomaly detection methods. [ABSTRACT FROM AUTHOR]

This paper examines the enactment of the Information Infrastructure for the management of migrants in Italy. The recent migration crisis required e-government tools to deal with the management of migrants in Italy, and this paper critically explores how the relevant Italian Authorities put in place a purpose-built government solution, the Information Infrastructure, to better manage and allocate migrants in the Italian Territory. This work closely focuses on the functionalities enacted in the Information Infrastructure, and critically analyses its main characteristics and interoperability. This research derives from a case study which enables the phenomenon to be explored from multiple sources and angles. The findings are explored through the lens of the assemblage framework, which helps to uncover the real nature of this Information Infrastructure, identifying it as an assemblage, a heterogeneous composite which results from the encounter of technology with a spectrum of socio-technical dimensions. Looking at this Information Infrastructure as an assemblage will help to unveil the role of mediation between the various interests and dimensions in the making of the assemblage. In particular, we will argue that the interplay of dimensions has led to an Information Infrastructure that is suboptimal and imperfect by contrast with the original plans because some dimensions fail to recognize the effects of the others. Moreover, we aim to demonstrate that the attempts to design an assemblage that is fully controllable a priori failed because an assemblage is always in-the-making and needs to be continuously cultivated by its actors. [ABSTRACT FROM AUTHOR]

This paper aims to examine and document the current state of practice of model‐based systems engineering (MBSE), and how organizations look toward the future. The paper is based on a survey of how MBSE has been applied and factors that influenced the perceived benefits and results. The survey was designed to evaluate the maturity and status of the implementation of MBSE (also called model‐centric systems engineering), within industry, academia, and governments. The approach to the survey development is described along with the survey results. The study indicates that one of the main hurdles to introducing a model‐based approach is the lack of clear and adopted organizational structures and an understanding of required conditions and needs at a management level. The survey also indicates that 50–75% of the respondents noted some improvement or a significant improvement across almost all systems engineering tasks. [ABSTRACT FROM AUTHOR]

Newly emerged applications in vehicular networks demand high throughput to transfer large amount of data through both Vehicle-to-Vehicle and Vehicle-to-Infrastructure links. One solution which recently draws researchers attention to itself for improving the throughput in this type of network is to deploy some Road-Side-Units (RSUs) in the streets with storage capability and store the data closer to the end users. Consequently, vehicles are able to download their inquired contents from these local RSUs instead of the base station. This will decrease the network traffic of the base station and also the average delay each vehicle has to wait to receive his requested files. The main issue to implement this distributed approach in this type of environment compared to other types of networks is that the fast moving vehicles make the topology of the network highly dynamic. Also due to limited storage capacity of the caches in the RSUs, we should decide on how to distribute the contents in the RSUs to maximize the number of locally satisfied vehicles. In this paper, we address the cache content placement problem in vehicular networks and model it using a game theoretic approach. We show that the proposed game model is a special case of generalized covering games. Considering the hit ratio of the caches as the performance metric in our model, we propose a method to distributively optimize this metric using the RSU's local information. In addition, we propose a combinatorial approach to find efficient file placements in the RSUs using Markov approximation. Empirical evaluations on realistic trace-based simulations show an improvement of 7.5% in the average hit ratio of the proposed method compared to other well-known cache content placement approaches. Newly emerged applications in vehicular networks demand high throughput to transfer large amount of data through both Vehicle-to-Vehicle and Vehicle-to-Infrastructure links. To improve the network throughput, we deploy some Road-Side-Units (RSUs) in the streets with storage capability and store the data closer to the end users. Consequently, vehicles are able to download their inquired contents from these local RSUs instead of the base station. The main issue to implement this distributed approach is that the fast moving vehicles make the topology of the network highly dynamic. Also due to limited storage capacity of the caches in the RSUs, we should decide on how to distribute the contents in the RSUs to maximize the number of locally satisfied vehicles. In this paper, we address the cache content placement problem in vehicular networks and model it using game theoretic approach and Combinatorial approach. We show that the proposed game model is a special case of generalized covering games. Considering the hit ratio of the caches as the performance metric in our model, we propose a method to distributively optimize this metric using the RSU's local information. In addition, we propose a Combinatorial approach to find efficient file placements in the RSUs using Markov approximation. Empirical evaluations on realistic trace-based simulations show an improvement of 7.5% in the average hit ratio of the proposed method compared to other well-known cache content placement approaches. [ABSTRACT FROM AUTHOR]

Inter-city transportation plays an important role in modern cities, and has accumulated massive spatio-temporal data from various sensors by IoT (Internet of things) technologies. Travel characteristics and future trends of highway behind data are valuable for traffic guidance and personalized service. As a routine domain analysis, trend discovery for highway drivers faces challenges in processing efficiency and predictive accuracy. Insufficient profiles of those drivers are available directly, sensible executive latency on huge data is hard to guarantee, and inadequate features among spatio-temporal correlations hinder the analytical accuracy. In this paper, a travel-characteristic based method is proposed to discover the potential trend of payment identity for highway drivers. Considering time, space, subjective preference and objective property, travel characteristics are modeled on monthly data from highway toll stations, through which predictive errors can be reduced by gradient boosting classification. With real-world data of one Chinese provincial highway network, extensive experiments and case studies show that our method has second-level executive latency with more than 85% F1-score for trend discovery. [ABSTRACT FROM AUTHOR]

The expansion of information technology infrastructure is encountered with Advanced Persistent Threats (APTs), which can launch data destruction, disclosure, modification, and/or Denial of Service attacks by drawing upon vulnerabilities of software and hardware. Moving Target Defense (MTD) is a promising risk mitigation technique that replies to APTs via implementing randomisation and dynamic strategies on compromised assets. However, some MTD techniques adopt the blind random mutation, which causes greater performance overhead and worse defense utility. In this paper, we formulate the cyber-attack and defense as a dynamic partially observable Markov process based on dynamic Bayesian inference. Then we develop an Inference-Based Adaptive Attack Tolerance (IBAAT) system , which includes two stages. In the first stage, a forward–backward algorithm with a time window is employed to perform a security risk assessment. To select the defense strategy, in the second stage, the attack and defense process is modelled as a two-player general-sum Markov game and the optimal defense strategy is acquired by quantitative analysis based on the first stage. The evaluation shows that the proposed algorithm has about 10% security utility improvement compared to the state-of-the-art. [ABSTRACT FROM AUTHOR]

In this paper we provide a brief description of the various ways in which the international business faculty can gain access to databases, reports and other resources on the Internet. The objective of this paper is to provide a low cost, efficient way of retrieving data which can be used for international business research. This paper will be important to international business researchers (both academicians and practitioners) and students. By helping build the infrastructure for accessing information for research, this paper indirectly contributes to existing research. [ABSTRACT FROM AUTHOR]

Information technology infrastructure (ITI) has gone through an exponential change due to the rapid evolution of digital technologies during the past few years. It is therefore relevant to identify the factors that push organizations towards the adoption of new technologies. This paper considers a specific case study of the higher education institutions (HEI) to present (i) the motivational factors that push HEIs toward the adoption of new technologies, and (ii) the key challenges HEIs face in the adoption of these technologies. The data was gathered after conducting 17 open-ended interviews with practitioners working at HEIs in Finland and Pakistan. Data analysis identified 10 motivational factors and 41 challenges faced by HEI in the adoption of the latest technologies. Furthermore, the data was further classified to identify broad themes and categories representing the challenges and motivation factors. [ABSTRACT FROM AUTHOR]

Oil and gas (O&G) organizations are progressively being digitalized in order to facilitate substantial information flow to remain competitive in the information age. This critical sector is spearheading the establishment of technical security measures to mitigate information security risks, yet employee behavioral influence remains an ongoing challenge in assuring information security. Existing studies of this domain primarily focus on employee behavior reshaping through multiple psychological theories. However, these studies ignore how these critical infrastructures implement information security. Most such infrastructures follow the International Society of Automation (ISA)-95 levels of automation and implement information security controls in line with these levels. This research paper proposed a theoretical framework to enhance information security policy compliance (ISPC) at level 4 to level 2 automation level in O&G organizations. To support the hypotheses, data were collected from 13 Malaysian O&G organizations. A total of 254 O&G employees participated in the survey and the structural equation modeling technique was used for data analysis. The study confirmed that ISA-95-based organizational governance factors and social bonding could enhance ISPC in O&G organizations. However, risk assessment and involvement factors have shown less support to the notion. For information systems practitioners, this study has shown how to enhance ISPC in O&G organizations through ISA-95-based organizational governance and social bonding. [ABSTRACT FROM AUTHOR]

Analyzing traffic accident data is crucial for pinpointing contributing factors, forecasting accident patterns, and informing effective safety measures. This insight leads to enhanced road safety, decreased fatalities, and better resource allocation in transportation planning. Severe weather conditions, including rain, fog, and sandstorms, can significantly reduce the visibility of highways and increase the risk of traffic accidents. The paper proposes a deep mining algorithm for road traffic accident data under adverse weather conditions. Firstly, collect traffic accident data under adverse weather conditions and complete attribute reduction, denoising, and normalization processing. Then, by improving the decision tree algorithm, the attribute selection criteria of the decision tree algorithm were enhanced; Finally, the improved decision tree algorithm is applied to achieve deep mining of traffic accident data. The experimental results show that proposed algorithm has an accuracy rate of over 95.3%, an accuracy rate of over 94.3%, a recall rate of over 92.7%, and a stable F1 value of around 0.8, demonstrating excellent performance. The provided deep mining algorithm for traffic accident data can provide more scientific and accurate decision support for traffic management departments. [ABSTRACT FROM AUTHOR]

In tunnel construction with tunnel boring machines (TBMs), accurate prediction of the remaining useful life (RUL) of disc cutters is critical for timely maintenance and replacement to avoid delays and cost overruns. This paper introduces a novel hybrid model, integrating fundamental and data-driven approaches, to enhance wear prediction of TBM disc cutters and enable accurate RUL estimation. The fundamental model is improved by incorporating composite wear mechanisms and load estimation techniques, showcasing superior prediction accuracy compared to single-mechanism models. Additionally, the hybrid model innovatively incorporates a data-driven supplementary residual term into the improved fundamental model, leading to a high-performance wear prediction model. Using actual field data from a highway tunnel project in Shenzhen, the performance of the hybrid model is rigorously tested and compared with pure fundamental and data-driven models. The hybrid model outperforms the other models, achieving the highest accuracy in predicting TBM disc cutter wear (mean absolute error (MAE) = 0.53, root mean square error (RMSE) = 0.64). Furthermore, this study thoroughly analyzes the hybrid model's generalization capability, revealing significant impacts of geological conditions on prediction accuracy. The model's generalization capability is also improved by expanding and updating the data sets. The RUL estimation results provided by the hybrid model are straightforward and effective, making it a valuable tool by which construction staff can monitor TBM disc cutters. [ABSTRACT FROM AUTHOR]