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Environmental protection supervision is an important manifestation of ecological accountability system reform. Taking the implementation of China's central environmental protection inspection (CEPI) policy as a quasi-natural experiment, this paper applies the time-varying difference-in-difference (DID) model to identify the impact of the CEPI policy on the likelihood of enterprises' environmental violations. The main conclusions include: (1) the implementation of CEPI policy is conducive to inhibiting environmental violations. After a series of robustness tests, including the parallel trend test, the placebo test, the exclusion of policy interference, and the replacement of explained variables, the result remains robust. In terms of dynamic perspective, there is a lag in the impact of CEPI policy on enterprises' environmental violations. (2) The effect of CEPI policy is more prominent on samples of large enterprises, enterprises with highly concentrated equity, enterprises that polluted heavily, enterprises owned by executives with a political background, and enterprises that are situated in regions with higher level of marketization and more developed information infrastructure. (3) The CEPI policy can restrain the environmental violations of enterprises by a dual mechanism of releasing punishment and deterrence signals from the external governance, and forcing enterprises to enhance environmental management system from the internal governance. [ABSTRACT FROM AUTHOR]

Currently, China has entered a stage of high-quality development due to innovations and improving capabilities of the cities. Being the most valuable urban brand, civilized cities are a symbol of the city's comprehensive ability. Their construction blueprint coincides with the realization of high-quality development. Therefore, exploring the relationship between civilized cities' construction and urban innovative development is a matter of great significance for improving national high-quality development policies and strengthening civilized cities' construction. This paper examined the data from 242 cities from 2003 to 2016, applying the multi-period difference-in-difference model to test the established hypothesis. The results indicate that the pilot policy for civilized cities has effectively improved the level of urban innovation. The results also validate that the title of the civilized city effectively promotes the urban innovation level by promoting the agglomeration of human capital, improving the level of informatization, and increasing investment in scientific as well as technological innovation. At the same time, there are significant differences in policy effectiveness for cities with different urban levels and geographical locations. The construction of future civilized cities should focus on attracting and cultivating high-quality talents, strengthening investment and support in information infrastructure construction, and scientific and technological innovation research and development to adapt to local conditions and resultantly achieve the improvement in urban innovation level. [ABSTRACT FROM AUTHOR]

While archival user studies have largely focused on humanities (and adjacent) scholars, this paper focuses on anthropologists engaged in scientific research. Based on qualitative results from an open-ended survey, we investigate how science-based anthropologists perceive and use archives in their work. We ask: How are science-based anthropologists and archaeologists reusing archival data in their research? What difficulties or barriers do they encounter in reusing archival data in scientific contexts? What attitudes or understandings about archival research are held by science-based anthropologists and archaeologists? Our findings primarily add to the body of literature about user experience in archives and more broadly to the emerging literature on archival data reuse. Major findings include (1) barriers and gatekeeping legacies that impact archival research and the ability of researchers to reuse data and (2) mixed perceptions about archives among researchers. We also discuss suggestions made by these communities of practice, and the ways that barriers to archival data reuse may stem from a lack of knowledge about core archival and information infrastructures among researcher communities. Together, this research showcases possible (re)uses of important primary source data in archives among scientific communities but highlights that barriers to access and misperceptions create a gap in exploiting that potential. We argue for a "re-imagining" of anthropological archives as relevant to contemporary communities and scientific pursuits toward a richer scientific research environment. [ABSTRACT FROM AUTHOR]

Satellite Internet-of-Things (IoT) is a critical part to build information infrastructure for environmental and ecological monitoring in remote areas where the cellular networks are uneasy to cover. When massive IoT terminals pour in the crowded satellite channels, how to enhance the spectrum utility of satellite band and guarantee the system capacity calls for full investigations. In this paper, a secure spectrum optimization scheme is proposed in satellite IoT by introducing blockchain to hamper malicious users to involve in the spectrum sharing. A market-oriented spectrum optimization strategy is designed to improve the satellite systems' benefits wherein the heterogeneous satellite channels are fully be considered and priced. In this circumstance, differentiated pricing is adopted to satisfy the various spectrum users' demands. When applying blockchain to secure the spectrum trading, the edge computing along with the mechanism of user reputation are devised to address the concerns of limited computation power for general IoT devices. Besides, the consensus algorithm of Delegated Proof of Stake is used to improve the computing efficiency so as to better fit in the application circumstance of satellite IoT. Numerical results are provided to evaluate the performances of our proposed solution on satellite channel pricing and system benefits. [ABSTRACT FROM AUTHOR]

Considering that one of the goals of the future network generations is to provide ubiquitous communication in the most diverse scenarios to achieve high connection coverage, it is foreseen that the use of unmanned aerial vehicles as flying base stations (UAV-BSs) can potentially extend the network and communication range. UAVs as flying base station can bring the potential to assist user devices and vehicles by carrying communication resources that can accommodate clients that were not previously planned by the ground infrastructure design due to flash crowd events, sudden natural disasters, or any other event that let to an overloaded environment. Allocating UAVs as flying base station still poses significant challenges in their deployment and the effectiveness of information transmission through UAVs as flying base station in the context of wireless communication since it is necessary to deal with both wireless communication capability and interference in the presence of terrestrial infrastructures already present. Besides, it is essential to understand how communication resources affect network performance. This paper studies the feasibility of using UAVs as flying base station in the assistance of wireless communication in a scenario where there is a sudden demand for data transmission due to possible congestion of local infrastructure. We show how the number of communication resources provided by the UAV-BS, the interference caused by the presence of multiple next generation node Bs (gNBs), and the UAV as flying base station positioning affect the network performance. We also highlight the need for a better next generation node B (gNB) and UAVs placement criteria since the received signal power prevents the user equipments (UEs) from using most of the available resources. [ABSTRACT FROM AUTHOR]

Despite the existence of studies addressing the historical development of digital platforms, none of them has yet drawn a coherent and comprehensive interpretation of the emergence of scientific digital platforms. The previous literature (i) focuses on specific scientific practices; (ii) does not reach far enough back into the past; (iii) does not cover all relevant groups of social actors; (iv) does not propose a taxonomy for scientific digital platforms; and (v) does not provide a definition for scientific digital platforms. We propose in this paper a long-term view (from 1990 onwards), allowing us to identify the participation of distinct groups of social actors—within State, Market and Science subsystems—in the process of science platformization. Dialoguing with the most up-to-date literature, we broaden our understanding of the ongoing process of platformization of the research life cycle, proposing a taxonomy and a definition for scientific digital platforms. The evidence provided throughout the paper unveils that (i) the changes (caused by platformization) in each of the phases of the research cycle are not at all linear and are not happening simultaneously; (ii) actors from different subsystem played important roles in the platformization of science; and, (iii) specific categories of platforms have consolidated themselves as infrastructures and certain scientific infrastructures have been platformed, although this varies by category. [ABSTRACT FROM AUTHOR]

Edge architectures provide local, decentralized services, enabling balancing network traffic and distributing hardware resources. Later, many new use cases can be implemented by combining the advantages of the edge computing concept with the services of 5G systems. One of the biggest beneficiaries of this could be the Vehicle-to-Cloud (V2C) technology, where it is necessary to efficiently process large amounts of data resulting from Vehicle-to-Everything communication (V2X) services. In specific use cases, this makes it possible to process sensor data collectively, enhanced by fusion, which promotes a more effective virtual representation of the real world. The effective implementation of these technologies is a complex task. One of the most important steps before tests on actual infrastructures with real vehicles is evaluating and validating edge cloud systems. We present a solution for this problem, the Cloud-in-the-Loop (CiL) simulation framework. It can orchestrate a real-size, telco-grade level, Kubernetes-based edge cloud infrastructure based on information gathered from a traffic simulator and performing fine-grained benchmarking and data collection. In addition to the performance analysis of the edge system, it also enables an in-depth examination of cloud-native applications serving complex automotive use cases. In this paper, we focus on presenting the developed framework and its capabilities by utilizing the system with implemented test applications, and give an example of testing QoS and QoE aspects of the edge cloud-based V2C concept. [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]

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]

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]

In Industry 4.0, smart manufacturing is facing its next stage, cybermanufacturing, founded upon advanced communication, computation, and control infrastructure. Cybermanufacturing will unleash the potential of multi-modal manufacturing data, and provide a new perspective called computation service, as a part of service-oriented architecture (SOA), where on-demand computation requests throughout manufacturing operations are seamlessly satisfied by data analytics and machine learning. However, the complexity of information technology infrastructure leads to fundamental challenges in modeling and analysis under cybermanufacturing, ranging from information-poor datasets to a lack of reproducibility of analytical studies. Nevertheless, existing reviews have focused on the overall architecture of cybermanufacturing/SOA or its technical components (e.g., communication protocol), rather than the potential bottleneck of computation service with respect to modeling and analysis. In this paper, we review the fundamental challenges with respect to modeling and analysis in cybermanufacturing. Then, we introduce the existing efforts in computation pipeline recommendation, which aims at identifying an optimal sequence of method options for data analytics/machine learning without time-consuming trial-and-error. We envision computation pipeline recommendation as a promising research field to address the fundamental challenges in cybermanufacturing. We also expect that computation pipeline recommendation can be a driving force to flexible and resilient manufacturing operations in the post-COVID-19 industry. [ABSTRACT FROM AUTHOR]

Due to the continuous evolution of adversary tactics, strategies, and processes, the contemporary digital universe is confronted with new obstacles in defending digital assets ranging from secret information to essential infrastructure. The advanced persistent threat (APT) is a new attack methodology used by modern adversaries in which the attacker employs sophisticated and highly evasive exploits and payloads to achieve long-term persistence and lateral movement to accomplish objectives such as high endurance data collection, disruption, or denial of critical infrastructure services. The payloads employed in these sorts of attacks are sophisticated and include advanced approaches for evading contemporary security solutions that depend heavily on signature and rule-based detection methods. Nowadays, individuals rely on behavior analysis combined with artificial intelligence approaches to determine given sample is malicious or not. This paper presents an innovative multi-dimensional hybrid Bayesian belief network model to classify the given sample as malicious or benign in the APT malware detection domain. It is a hybrid method of three analytical models: static analysis Bayesian belief network (SABBN), dynamic analysis Bayesian belief network (DABBN), and event analysis Bayesian belief network (EABBN) that covers the vast range of malware behavioral traits. The suggested framework detects APT Malware with 92.62 percent accuracy and a 0.0538 percent false-positive rate, which is excellent in an area where security solutions lack trustworthy mechanisms. [ABSTRACT FROM AUTHOR]

Constructing a quasi-natural experiment based on China's National Independent Innovation Demonstration Zone (NIDZ) pilot, this study applies the time-varying difference-in-differences (DID) model to estimate the impact of innovation-driven development on urban carbon emission reduction. We use panel data on 285 cities which covers 95.96% of Chinese cities during the period of 2003 to 2017. Compared with non-pilot cities, our results indicate that total carbon dioxide emissions and emission intensity of pilot cities decreased by 4.8% and 5.8%, respectively. The results suggest that the construction of NIDZs can significantly promote urban carbon emission reductions. Moreover, our mechanism tests indicate that this pilot policy can encourage technological innovation and optimize industrial structure, which in turn suppresses urban carbon dioxide emissions. Additionally, further analysis shows that the policy effect increases over years and is stronger in urban areas with higher levels of human capital, government finance, and information infrastructure. This study enriches the relevant research on carbon emission reduction. [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]

This article is a report of the IFIP AIMS 2016, which was held at Universität der Bundeswehr München, Germany from June 20 to June 23, 2016. AIMS 2016 focused on the theme “Management and Security in the Age of Hyperconnectivity”. The AIMS conference positions itself in the network management community as an educational venue for young researchers and Ph.D. students. The AIMS program included keynotes, technical sessions and Ph.D. Workshop sessions, but also hands-on labs and an educational panel for training young academics. The highlights on each of the parts of the AIMS 2016 program are summarized in this article. [ABSTRACT FROM AUTHOR]

Social media platform like Twitter is one of the primary sources for sharing real-time information at the time of events such as disasters, political events, etc. Detecting the resource tweets during a disaster is an essential task because tweets contain different types of information such as infrastructure damage, resources, opinions and sympathies of disaster events, etc. Tweets are posted related to Need and Availability of Resources (NAR) by humanitarian organizations and victims. Hence, reliable methodologies are required for detecting the NAR tweets during a disaster. The existing works don't focus well on NAR tweets detection and also had poor performance. Hence, this paper focus on detection of NAR tweets during a disaster. Existing works often use features and appropriate machine learning algorithms on several Natural Language Processing (NLP) tasks. Recently, there is a wide use of Convolutional Neural Networks (CNN) in text classification problems. However, it requires a large amount of manual labeled data. There is no such large labeled data is available for NAR tweets during a disaster. To overcome this problem, stacking of Convolutional Neural Networks with traditional feature based classifiers is proposed for detecting the NAR tweets. In our approach, we propose several informative features such as aid, need, food, packets, earthquake, etc. are used in the classifier and CNN. The learned features (output of CNN and classifier with informative features) are utilized in another classifier (meta-classifier) for detection of NAR tweets. The classifiers such as SVM, KNN, Decision tree, and Naive Bayes are used in the proposed model. From the experiments, we found that the usage of KNN (base classifier) and SVM (meta classifier) with the combination of CNN in the proposed model outperform the other algorithms. This paper uses 2015 and 2016 Nepal and Italy earthquake datasets for experimentation. The experimental results proved that the proposed model achieves the best accuracy compared to baseline methods. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics including the use of cloud computing in the wireless domain, information technology (IT) possibilities of cloud computing, and the combination of electronic commerce (e-commerce), cloud computing, and broadband infrastructure.

Vector geographic data are the fundamental achievements of national information infrastructure, and they play an important role in society's development. How to protect the copyright of vector geographic data has become a popular issue in the age of big data, and digital watermarking technology can be used to solve this problem. In this paper, a robust and blind watermarking algorithm for vector geographic data is proposed based on the technology of coordinate mapping and matching detection. First, the basic principle for resisting data translation based on quantization index modulation (QIM) and matching detection was analyzed. Second, a watermarking algorithm for vector geographic data was designed based on coordinate mapping, QIM and matching detection. Finally, we performed experiments to test the robustness and adaptability of the proposed algorithm. The experimental results show that the proposed watermarking algorithm is not only robust against the watermarking attacks of data compression, data adding, data deleting, data cropping, feature deleting and data translation but also against composite attack. The proposed algorithm is also suitable for small vector geographic datasets such as point-based data. [ABSTRACT FROM AUTHOR]

Vehicular ad hoc network (VANET) is expected one of promising network forms for intelligent transportation system which supports road safety applications, in-vehicle entertainment and arriving automatic driving. Establishing and maintaining stable connections in VANETs are challenging on account of the high mobility of vehicles, dynamic vehicle topology, and time-varying vehicle density. Clustering can provide scalability and reliability for VANETs by grouping vehicles with hierarchical structures. However, keeping cluster stable became a hard nut to crack due to high vehicle speed and unpredictable driving pattern. Recent rapid development of artificial intelligence (AI) provided an innovative solution for this situation. In this paper, a Naive Bayes Classifier based driving habit prediction scheme for stable clustering is proposed, briefly named NBP. According to driving speed and overtaking decisions, vehicles are classified into two alignments with different driving habit. Specifically, Naive Bayes classifier perform driving habit prediction through several relative independent factors, such as relative velocity, vehicle type, number of lanes traveled. The cluster head candidates will be chosen from alignment with mild driving pattern which will benefit for stable clusters. Combined with clustering design, the proposed method has been proven effective for stable clustering in VANET based on the real data of highways in California. [ABSTRACT FROM AUTHOR]

To optimize the accessibility algorithm and quantify the potential relationship between human development index and traffic comprehensive accessibility system, this paper analyzed the spatial distribution pattern of urban accessibility and human development index of highway, railway, and aviation transportation systems using data on highway, railway, and aviation schedules based on GIS spatial analysis method. Furthermore, the coupling degree between human development index and accessibility and its influence mechanism on the city level in China were explored based on the super-efficiency data envelopment analysis model. Results showed as follows: (1) Spatial distribution of human development index from high to low was gradually changing from east to west. The spatial distribution of urban accessibility of the three traffic systems had an evident "Hu Huanyong Line" effect. (2) The coordination degree of urban accessibility and human development index spread in a ladder mode. High coordination of cities in North and East China and the central Yangtze River region forms the spatial distribution of urban development circles connecting an urban development belt. (3) Railway connectivity and control value were highly sensitive to human development index in cities where serious imbalance between accessibility and human development index. Highway connectivity and control value were highly sensitive to human development index in cities where high coordination between accessibility and human development index. The results would provide scientific references for spatial planning of transportation, economic, and social development of cities and coordinated development of urban agglomeration in China. [ABSTRACT FROM AUTHOR]

Block chain is a decentralized core architecture, which is widely used in emerging digital encryption currencies. It has attracted much attention and has been researched with the gradual acceptance of bitcoin. Block chaining technology has the characteristics of centralization, block data, no tampering and trust, so it is sought after by enterprises, especially financial institutions. This paper expounds the core technology principle of block chain technology, discusses the application of block chain technology, the existing regulatory problems and security problems, so as to provide some help for the related research of block chain technology. Intrusion detection is an important way to protect the security of information systems. It has become the focus of security research in recent years. This paper introduces the history and current situation of intrusion detection system, expounds the classification of intrusion detection system and the framework of general intrusion detection, and discusses all kinds of intrusion detection technology in detail. Intrusion detection technology is a kind of security technology to protect network resources from hacker attack. IDS is a useful supplement to the firewall, which can help the network system to quickly detect attacks and improve the integrity of the information security infrastructure. In this paper, intrusion detection technology is applied to block chain information security model, and the results show that proposed model has higher detection efficiency and fault tolerance. [ABSTRACT FROM AUTHOR]

Trust is the key element of commerce, both for traditional models and — more recently — for eCommerce. Unlike its traditional counterpart, eCommerce relies on trust being created and maintained with the help of digital devices and services. Convergence brings significant changes to the way people interact through digital media by offering ubiquitous and seamless communication. This has a significant impact on the way trust is established and maintained, with consequent impact upon eCommerce. This paper identifies a number of the most important challenges to trust in eCommerce as well as trust-related aspects of key enablers of eCommerce. From this perspective, the paper studies an impact of convergence on trust within eCommerce to identify several positive relationships. [ABSTRACT FROM AUTHOR]

Cloud computing has provided new dimensions and opportunities to telecom providers to enhance their ability in creating new revenue streams, reduce operational costs and increase customer satisfaction. In recent years, the progression of evolving cloud computing systems is huge. Conversely, it also encountered a lot of new challenges to the institutions utilizing cloud systems. It is critical to evaluate the change in organizational risk profile before deciding the level of cloud adoption. The conventional risk assessment framework of telecom providers may be unsuitable for cloud computing owing to the difficulties in the configuration. This paper aims to propose a system to quantify the influences of cloud adoption in telecom risk profile. This study also provides a comparison of overall risk profile change between clouds enabled infrastructure, traditional on-premises information technology solutions, and a combination of both in the telecom sector. The result encourages the selective adoption of the hybrid cloud model which demonstrated a relatively low organizational risk score. This work contributes to cloud computing business research by providing a holistic risk comparison model which reflects the distinctiveness of telecom service provider's assets and capabilities. [ABSTRACT FROM AUTHOR]

This paper discusses the development of an enterprise domain model in an environment where part of the domain knowledge is vague and not yet formalised in company-wide business rules. The domain model was developed for a young company starting in the telecommunications sector. The company relied on a number of stand-alone business support systems and sought for a manner to integrate them. There was opted for the development of an enterprise-wide domain model that had to serve as an integration layer to coordinate the stand-alone applications. A specific feature of the company was that it could build up its information infrastructure form scratch, so that many aspects of its business were still in the process of being defined. The paper will highlight parts of the Enterprise Model where there was a need for co-designing business rules together with the domain model. A result of this whole effort was that the company got more insight into important domain knowledge and developed a common understanding across functional areas of the way of doing business. [ABSTRACT FROM AUTHOR]

Various computing environments are constantly emerging which are using different technology platforms and security mechanisms from each other. The development of network technology makes cross-domain access between various systems necessary, which requires seamless information sharing and data exchange between systems, thus eliminating the phenomenon of information islands. With its unique consensus mechanism and compatible encryption algorithms, it has gradually attracted attention in various fields. Many people believe that blockchain technology is a revolution in Internet technology in the future, which is a huge innovation in information infrastructure technology as well. In order to ensure a high QoS of the data grid, the system needs to overcome many unstable factors of the network and the grid nodes. Resource (capability) reservation, copy deployment, buffer mechanism, parallel data transfer, and data storage and recovery are the main means to solve such problems. Above all, this paper proposed a QoS optimization system for complex data cross-domain request based on neural blockchain structure. Experimental results show that the proposed method has higher robustness and efficiency. [ABSTRACT FROM AUTHOR]

Many countries have devoted increasing attention to information infrastructures. However, a gap in digitalization exists among different government agencies, causing unequal opportunities for accessing infrastructures, information, and communication technologies. This paper, based on Gowin's Vee structure, is an empirical study of the digital divide in the context of local governments in Taiwan. A model for identifying and measuring aforementioned digital divide is constructed in this paper. We first refer to the grounded theory to draft a framework for measuring the digital divide in local governments. Then, through the use of a questionnaire distributed to experts implemented alongside the analytic hierarchy process (AHP), we generate five dimensions (including ICT infrastructure, human resources, external environment, internals of organization, and information) and 42 measures. Finally, we measure the actual levels of the digital divide in local governments with the resulting digital divide evaluation model. This paper aims to generate results that can serve as a reference for government agencies (at all levels) in the formulation of their digitalization strategies. Moreover, the digital divide evaluation model constructed in this study goes beyond existing measures and may serve as a reference for academics in the examination of methods to narrow the digital divide in various levels of governmental bodies. Taken together, the features of integration, comprehensiveness, and wide applicability of this proposed model can be considered the theoretical contributions to digital divide and local government hierarchy research. [ABSTRACT FROM AUTHOR]

It is important to obtain analytical expressions of the maximum throughput in IEEE 802.11 Distributed Coordination Function multi-hop networks. In the previous works, the analytical expressions of the maximum throughput for one-way string multi-hop networks taking into account the signal capture effect were obtained. In other researches, the analytical expressions of the maximum throughput for one-way string multi-hop networks were also obtained, which are, however, valid only for short-frame communications. There is no analytical expression for maximum throughput, which is valid for long-frame communications. This paper presents an analytical expression of the maximum throughput for long-frame communications. For the long-frame-communication analysis, we make different assumptions from those in the previous-analyses. In the short-frame-communication analyses, it is assumed that all nodes always have frames. In the long-frame-communication analysis, however, it should be assumed that every equal to or more than three nodes in a string-topology network have frames. The comprehension of this behavior is the most important progression in this paper. The assumptions and the analytical expression are validated by the simulation results. [ABSTRACT FROM AUTHOR]

This article contains the report on AIMS 2010, which was held June 23-25, 2010 at the Department of Informatics (IFI), University of Zürich, Switzerland and which was driven by the theme 'Mechanisms for Autonomous Management of Networks and Services'. Furthermore, the report also synopsizes ISSNSM 2010, which was run June 21-23, 2010 at the same location and which offered a practical summer school on selected topics in network and service management. [ABSTRACT FROM AUTHOR]

There are two problem areas of the current Internet to be solved in Future Internet scenarios—security and putting the user back in control despite the move to the Internet of things. With this in mind, we address problems associated with the diversifying of the Internet towards an Internet of things, and with increased ways to be reachable, whether the user wants it or not, in the digital world. The paper presents two approaches to cope with the problem: The Identinet and a concept designated by the digital shadow. The paper presents an architecture based on these concepts. [ABSTRACT FROM AUTHOR]

Various industries are developing information infrastructures to improve the efficiency and quality of work. Little research attention has been paid to how workers might resist the development of a new infrastructure beyond the point of technology use. In industries in which government agencies have taken a top-down, policy-driven approach to developing infrastructures, though, coordinated, distributed resistance—or organized resistance—is likely to play a role in implementation outcomes because policies limit the flexibility of organizations and workers in adopting and using infrastructure technologies. This paper presents the results of a qualitative study of the United States government's multi-billion dollar electronic medical record (EMR) infrastructure program aimed to support data collection and sharing within and between healthcare organizations. It describes how healthcare professionals manifested their resistance through professional organizations at the political level via organized resistance. [ABSTRACT FROM AUTHOR]

Given the possibilities provided by smart grids in terms of communication infrastructure and information acquisition, there are new options on how to use the signals coming from meters to locate short circuits that occur in the system. This paper presents a framework for fault location in radial distribution systems based on machine learning algorithms and a multistage approach. A methodology in order to segment the system for proper identification of the outage region is presented. Studies are carried out involving the variation of the fault impedance, the fault incidence angle and the number and position of the meters. The IEEE 34-bus bar distribution feeder was considered for the tests. The results so far are promising, attesting and validating the presented methodology. [ABSTRACT FROM AUTHOR]

Based on expectancy valence theory, people's behavior is affected by their self-perception and the external environment. In rural China, policy instruments as robust external environment factors have a strong effect on waste separation behavior (WSB). The purpose of the paper is to explore the influencing mechanism of policy instruments (infrastructure and information) on perceived value (perceived benefit and perceived cost) and waste separation behaviors. The data were collected from 689 rural households of Shaanxi province in China, and analyzed by using structural equation model (SEM). According to the results, the mediation effect proves that policy instruments not only can affect WSB directly but also can affect it indirectly through the perceived value. Specifically, information and infrastructure influence the perceived benefit positively and the perceived cost negatively, and information and infrastructure have an indirect effect on WSB through the mediation effect of the perceived cost. Second, policy instruments have a stronger effect on rural people's waste separation behavior than perceived value. Specifically, infrastructure has the most important impact on waste separation behavior, followed by information and then perceived cost. Third, the perceived cost is significantly negatively related to WSB, and perceived benefit has a positive effect but is statistically insignificant. It has a practical implication for the government. Providing sufficient infrastructure and launching effective information activities could improve the perceived benefit including biospheric, egoistic, social-altruistic, and reputation; and reduce the perceived cost of time, physical, learning, and money, which could then induce rural households to engage in WSB. [ABSTRACT FROM AUTHOR]

Inter-city highway plays an important role in modern urban life and generates sensory data with spatio-temporal characteristics. Its current situation and future trends are valuable for vehicles guidance and transportation security management. As a domain routine analysis, daily detection of traffic hotspots faces challenges in efficiency and precision, because huge data deteriorates processing latency and many correlative factors cannot be fully considered. In this paper, an ensemble-learning based method for potential traffic hotspots detection is proposed. Considering time, space, meteorology, and calendar conditions, daily traffic volume is modeled on heterogeneous data, and trends predictive error can be reduced through gradient boosting regression technology. Using real-world data from one Chinese provincial highway, extensive experiments and case studies show our methods with second-level executive latency with a distinct improvement in predictive precision. [ABSTRACT FROM AUTHOR]

In this era of ubiquitous networks that become increasingly vulnerable to disruptions, network reliability has emerged as a critical issue in their design and operation. Businesses and individuals become ever more dependent on networks and demand reliable delivery of critical services every time. This paper finds Pareto optimal locations for a single facility on an existing tree network that maximizes service availability to customers by considering both the average and the lowest level of service delivery with respect to all customers. Examples are the location of decision entities on information infrastructures, servers or databases on computer networks, control systems on telecommunication networks, critical information on social networks, supply centers on supply chain networks, and location of emergency response facilities to intentional or natural disasters. Model properties are identified in decision and objective space and used to develop an efficient algorithm for finding the efficient and the non-dominated sets. Numerical examples are provided to illustrate the algorithm and to show special conditions for the efficient and non-dominated sets to be continuous. [ABSTRACT FROM AUTHOR]

The “Internet,” as a global self-regulated and interconnected network of institutions driven by educational and subsequently commercial priorities, has evolved into an element within a broader “global information society.” Industry, treated benevolently by market-led governments, has created co- or self-regulatory institutions or compacts, but as consumers have eagerly embraced the broadband Internet the scheme of governance must embrace respect for the social and economic rights and responsibilities of consumers at national, European and global levels. This paper shows how existing divisions between public-sector, private-sector, and civil-society institutions and responsibilities have rapidly become eroded and it portrays the emerging agenda for “multistakeholder governance.” The involvement of the consumer on a more legitimised and consensual level than is permitted under industry-led regulation is as yet a novel approach, but this paper draws on case studies which demonstrate the salience of these issues to consumers as citizens, and it concludes by preparing an agenda for Information and Communications Technology (ICT) companies to adopt more sophisticated patterns of participatory co- and self-regulation. [ABSTRACT FROM AUTHOR]

In most content-based image retrieval systems, the color information is extensively used for its simplicity and generality. Due to its compactness in characterizing the global information, a uniform quantization of colors, or a histogram, has been the most commonly used color descriptor. However, a cluster-based representation, or a signature, has been proven to bemore compact and theoretically sound than a histogram for increasing the discriminatory power and reducing the gap between human perception and computer-aided retrieval system. Despite of these advantages, only few papers have broached dissimilarity measure based on the cluster-based nonuniform quantization of colors. In this paper, we extract the perceptual representation of an original color image, a statistical signature by modifying general color signature, which consists of a set of points with statistical volume. Also we present a novel dissimilarity measure for a statistical signature called Perceptually Modified Hausdorff Distance (PMHD) that is based on the Hausdorff distance. In the result, the proposed retrieval system views an image as a statistical signature, and uses the PMHD as the metric between statistical signatures. The precision versus recall results show that the proposed dissimilarity measure generally outperforms all other dissimilarity measures on an unmodified commercial image database. [ABSTRACT FROM AUTHOR]

Cloud data center providers benefit from software-defined infrastructure once it promotes flexibility, automation, and scalability. The new paradigm of software-defined infrastructure helps facing current management challenges of a large-scale infrastructure, and guarantying service level agreements with established availability levels. Assessing the availability of a data center remains a complex task as it requires gathering information of a complex infrastructure and generating accurate models to estimate its availability. This paper covers this gap by proposing a methodology to automatically acquire data center hardware configuration to assess, through models, its availability. The proposed methodology leverages the emerging standardized Redfish API and relevant modeling frameworks. Through such approach, we analyzed the availability benefits of migrating from a conventional data center infrastructure (named Performance Optimization Data center (POD) with redundant servers) to a next-generation virtual Performance Optimized Data center (named virtual POD (vPOD) composed of a pool of disaggregated hardware resources). Results show that vPOD improves availability compared to conventional data center configurations. [ABSTRACT FROM AUTHOR]

Abstract  BT’s planned new architecture defines the technological direction and structure of its future service infrastructure. It provides the template for all service developments and is the key enabler to BT meeting its service vision. This paper summarises the architecture, exploring the key features which will drive the development of BT’s future networks, intelligence and systems. [ABSTRACT FROM AUTHOR]

Decentralized multi-item auctions offer great opportunities for integrating fragmented online auction markets into larger markets with more efficient outcomes. This paper extends the theory of multi-item ascending auctions of substitutes by considering any finite positive bid increment and allowing the bidders to bid asyn-chronously instead of bidding in a round-robin fashion. We consider a setup where the bidders’ utilities over multiple items are additive and bound the maximum inefficiency in the allocation when the bidders follow a simple greedy strategy. We also obtain the limits within which the prices of individual items can vary from one outcome to another. For the special case of single unit bidder demand, we also bound the maximum surplus which a bidder can extract by unilaterally switching to some other strategy. The paper suggests an upper bound for the minimum required bid increment which would be necessary for competitive price discovery and truthful bidding in a practical online implementation. [ABSTRACT FROM AUTHOR]

Recent scholarship in archival studies has employed ‘non-traditional’ modes of analysis to theorize the nature of the record and recordkeeping in organizational contexts. In that tradition, this paper discusses the author's use of ethnographic methodology to study recordkeeping in one academic research laboratory. The paper explores how ethnography contributes to our understanding of the laboratory as a recordkeeping organization and the intersections of scientific practice and the kinds of records scientists create and use. The paper calls for more analysis of recordkeeping as an information infrastructure and inquiry into the nature of the record in other kinds of knowledge production environments. [ABSTRACT FROM AUTHOR]

The construction of information infrastructure as well as the transformation and upgrading of the industrial structure are among the major challenges for the Chinese economy. Therefore, it is of great significance to explore how information infrastructure affects the upgrading of industrial structure. Based on the panel data of 31 provinces in China from 2013 to 2020, mediating effect model and non-parametric percentile bootstrap method are used to carry out empirical research, by creating an information infrastructure construction level and industrial structure upgrading indicators. The results show that, in addition to the direct effect of information infrastructure on industrial structure upgrading, information infrastructure can also work indirectly through three paths: (1) information infrastructure acts on industrial structure upgrading by enhancing urbanization level; (2) information infrastructure affects industrial structure upgrading by boosting technological innovation; (3) information infrastructure first enhances urbanization level, then acts on technological innovation, and finally promotes industrial structure upgrading. In addition, the intermediary effect of technological innovation is stronger than urbanization. In general, this study acknowledges that urbanization and technological innovation are partial mediators in the process of information infrastructure affecting industrial structure upgrading, notwithstanding other potential impact pathways being studied further. [ABSTRACT FROM AUTHOR]

This paper investigates some of the issues which will determine the viability of the World Wide Web as an infrastructure for cooperative work. In fact, taking a weak definition of collaboration, the Web is already a very successful collaborative environment. In addition, it is already being used as the basis for experimental and commercial groupware. The paper takes this as a starting point and uses analytic methods developed in the field of Computer Supported Cooperative Work to investigate the reasons for the Web‘s present success, its strengths and weaknesses as a platform for CSCW, and prospects for future development. [ABSTRACT FROM AUTHOR]

Fog and Cloud computing are ubiquitous computing paradigms based on the concepts of utility and grid computing. Cloud service providers permit flexible and dynamic access to virtualized computing resources on pay-per-use basis to the end users. The users having mobile device will like to process maximum number of applications locally by defining fog layer to provide infrastructure for storage and processing of applications. In case demands for resources are not being satisfied by fog layer of mobile device then job is transferred to cloud for processing. Due to large number of jobs and limited resources, fog is prone to deadlock at very large scale. Therefore, Quality of Service (QoS) and reliability are important aspects for heterogeneous fog and cloud framework. In this paper, Social Network Analysis (SNA) technique is used to detect deadlock for resources in fog layer of mobile device. A new concept of free space fog is proposed which helps to remove deadlock by collecting available free resource from all allocated jobs. A set of rules are proposed for a deadlock manager to increase the utilization of resources in fog layer and decrease the response time of request in case deadlock is detected by the system. Two different clouds (public cloud and virtual private cloud) apart from fog layer and free space fog are used to manage deadlock effectively. Selection among them is being done by assigning priorities to the requests and providing resources accordingly from fog and cloud. Therefore, QoS as well as reliability to users can be provided using proposed framework. Cloudsim is used to evaluate resource utilization using Resource Pool Manager (RPM). The results show the effectiveness of proposed technique. [ABSTRACT FROM AUTHOR]

The analysis of mobile phone data can help carriers to improve the way they deal with unusual workloads imposed by large-scale events. This paper analyzes human mobility and the resulting dynamics in the network workload caused by three different types of large-scale events: a major soccer match, a rock concert, and a New Year’s Eve celebration, which took place in a large Brazilian city. Our analysis is based on the characterization of records of mobile phone calls made around the time and place of each event. That is, human mobility and network workload are analyzed in terms of the number of mobile phone calls, their inter-arrival and inter-departure times, and their durations. We use heat maps to visually analyze the spatio-temporal dynamics of the movement patterns of the participants of the large-scale event. The results obtained can be helpful to improve the understanding of human mobility caused by large-scale events. Such results could also provide valuable insights for network managers into effective capacity management and planning strategies. We also present PrediTraf, an application built to help the cellphone carriers plan their infrastructure on large-scale events. [ABSTRACT FROM AUTHOR]

Internet infrastructure is going to be re-designed as a core network layer, shifting from hosts to contents. To this end, content centric networking (CCN) as one of the most effective architectures has been proposed with significant features of in-network caching to open new possibilities for energy efficiency in content dissemination. However in energy-efficient CCN, less popular contents are cached near the origin server, and therefore in delay sensitive applications with less popularity, it leads to dropping delayed chunks, increasing energy waste, and degrading the quality of service (QoS). In the present paper, the energy consumption in CCN while being aware of QoS consideration in terms of imposed delay is minimized. The minimization is performed through integer linear programming by considering most of the energy consuming components. However, since this problem is NP-hard, a quantized Hopfield neural network with an augmented Lagrange multiplier method (MEDCCN-QHN) is proposed to derive the solution. The numerical results show that the MEDCCN-QHN achieves to better delay profile compared to the optimal energy-efficient algorithm, and near-optimal energy consumption. Moreover, the method is fast due to its parallel execution capability. [ABSTRACT FROM AUTHOR]

Scalability refers to the capability of a system or network being expanded or upgraded easily to satisfy ever-increasing growing demand, the development of smart grid is anticipated to be highly desirable in realizing the scalability. In this paper, scalability of smart infrastructure system composed of smart power electricity, smart information as well as smart communication was emphasized, which may provide basis and foundation for all other systems. All scalability aspects in smart grid was taken into consideration and particular focus was directed on the three major parts of smart infrastructure system. Finally, issues regarding to future challenges and opportunities of scalability architectures together with protocols and algorithms in smart grid were also addressed. [ABSTRACT FROM AUTHOR]

The virtualization of both servers and substrate networks is a promising technique that will enable the future Internet architecture to support a variety of cloud computing services and architectures. The problem of efficiently mapping a virtual infrastructure (VI) over a wide-area optical network is a key problem in provisioning Infrastructure (and Network) as a Service over multiple datacenters. In this paper, we study the problem of cost efficient VI mapping and propose a novel approach called the virtual infrastructure mapping algorithm (VIMA) that jointly considers node mapping and link mapping. Such a close coordination between the link and node mapping stages increases the efficiency of the VIMA algorithm. We compare the performance of our VIMA algorithm with other VI mapping algorithms such as NSVIM, vnmFlib and R-ViNE under various performance metrics using simulation. Our simulation results and analysis show that the VIMA algorithm outperforms the other algorithms in terms of VI mapping costs and path length of VI links. [ABSTRACT FROM AUTHOR]

Operators of wireless infrastructures should maintain their users 'always-best-connected'. This concept means that applications should be offered to users at the best possible Quality of Service (QoS) level, taking into account profile, context and policy information. The profiles provide the user requirements and preferences, the terminal capabilities, and the application requirements. The policies provide the objectives, constraints imposed by various stakeholders, for instance the network operator (NO). The context of operation designates relevant applications, available networks and their QoS capabilities. The 'always-best-connectivity' concept can be achieved by directing user terminals to the most appropriate networks of the heterogeneous infrastructure of the NO. In this respect, advanced terminal management functionality is required. This paper presents management mechanisms for utility-based cognitive network selections. The utility is used for expressing the user desire for a QoS level. Cognition mechanisms are applied for learning the QoS capabilities of candidate networks, and therefore increasing the reliability and seamlessness of the network selections. Extensive results are provided, which show the behaviour of the scheme in terms of network selections made, and computational effort required for the acquisition of the knowledge. [ABSTRACT FROM AUTHOR]

The advantages of using the multiple rates for wireless communications have been revealed in the recent years. To determine the appropriate rate and to make routing decision more precise, the communication nodes need the information from lower layer. Therefore, in this paper, a high throughput routing protocol using lower layer information for Multi-rate Ad-hoc Networks is proposed. We introduce a new routing metric named 'Route Assessment Index' (RAI). The route with maximum RAI value is preferred to achieve the high throughput route, and to avoid the link bottleneck for reducing the packet drop rate. The chosen route also has a small number of hops. The routing protocol works in distributed manner, and correctness of the proposal is proven. The simulation results show that our new metric provides an accurate and efficient method for assessing and selecting the best route in Multi-rate Ad-hoc Networks. [ABSTRACT FROM AUTHOR]

This paper addresses the collaborative development of information infrastructure for supporting data-rich scientific collaboration. Studying infrastructure development empirically not only in terms of spatial issues but also, and equally importantly, temporal ones, we illustrate how the long-term matters. Our case is about the collaborative development of a metadata standard for an ecological research domain. It is a complex example where standards are recognized as one element of infrastructure and standard-making efforts include integration of semantic work and software tools development. With a focus on the temporal scales of short-term and long-term, we analyze the practices and views of the main parties involved in the development of the standard. Our contributions are three-fold: 1) extension of the notion of infrastructure to more explicitly include the temporal dimension; 2) identification of two distinct temporal orientations in information infrastructure development work, namely 'project time' and 'infrastructure time', and 3) association of related development orientations, particularly 'continuing design' as a development orientation that recognizes 'infrastructure time'. We conclude by highlighting the need to enrich understandings of temporality in CSCW, particularly towards longer time scales and more diversified temporal hybrids in collaborative infrastructure development. This work draws attention to the manifold ramifications that 'infrastructure time', as an example of more extended temporal scales, suggests for CSCW and e-Research infrastructures. [ABSTRACT FROM AUTHOR]