This paper promotes the concept of smart and connected communities SCC, which is evolving from the concept of smart cities. SCC are envisioned to address synergistically the needs of remembering the ...past (preservation and revitalization), the needs of living in the present (livability), and the needs of planning for the future (attainability). Therefore, the vision of SCC is to improve livability, preservation, revitalization, and attainability of a community. The goal of building SCC for a community is to live in the present, plan for the future, and remember the past. We argue that Internet of Things (IoT) has the potential to provide a ubiquitous network of connected devices and smart sensors for SCC, and big data analytics has the potential to enable the move from IoT to real-time control desired for SCC. We highlight mobile crowdsensing and cyber-physical cloud computing as two most important IoT technologies in promoting SCC. As a case study, we present TreSight, which integrates IoT and big data analytics for smart tourism and sustainable cultural heritage in the city of Trento, Italy.
Nowadays, various online education platforms (such as MOOCs, Coursera, XuetangX and so on) not only provide a broad Internet environment for sharing multimedia learning resources, but also bring a ...series of challenges in digital rights management, such as the infringement of digital copyrights of multimedia learning resources, the insecurity of digital education certificates, and the low degree of openness of multimedia learning resources. To sovle these issues, we propose a blockchain-enabled digital rights management system, which includes an entirely new network architecture for sharing and managing multimedia resources of online education on the basis of the combination of the public and private blockchains, as well as three specific smart contract schemes for the realization of the recording of multimedia digital rights, the secure storage and the unmediated verification of digital certificates, respectively. The proposed blockchain-enabled digital rights management system has been demonstrated as a promising candidate solution to the blockchain-based multimedia data protection in an online education environment.
Data Security and Privacy in Cloud Computing Sun, Yunchuan; Zhang, Junsheng; Xiong, Yongping ...
International Journal of Distributed Sensor Networks,
01/2014, Volume:
10, Issue:
7
Book Review, Journal Article
Peer reviewed
Open access
Data security has consistently been a major issue in information technology. In the cloud
computing environment, it becomes particularly serious because the data is located in
different places even ...in all the globe. Data security and privacy protection are the two
main factors of user's concerns about the cloud technology. Though many techniques on the
topics in cloud computing have been investigated in both academics and industries, data
security and privacy protection are becoming more important for the future development of
cloud computing technology in government, industry, and business. Data security and
privacy protection issues are relevant to both hardware and software in the cloud
architecture. This study is to review different security techniques and challenges from
both software and hardware aspects for protecting data in the cloud and aims at enhancing
the data security and privacy protection for the trustworthy cloud environment. In this
paper, we make a comparative research analysis of the existing research work regarding the
data security and privacy protection techniques used in the cloud computing.
Massive scientific and technical literature has recorded the developments of science and technology and contains plentiful knowledge. Researchers have to read scientific literature such as papers, ...patents, and reports to know the latest developments in time. However, it is difficult for researchers to read all the newly published and relevant literature. So there is an urgent need for scientific literature summarization systems to provide brief and important dynamic information that researchers are interested in. This paper proposes an approach to generate automatic summarization based on 5W1H event structure. Sentences in the literature are classified and selected for different elements of events by relevance, and then the importance of each candidate sentence is calculated. Top-
k
relevant and important sentences are selected to formulate event-based summarization. Comparing with existing summarization results or abstracts given by authors, experiment results of our approach contain more detailed information with the the 5W1H event structure, which is more convenient for researchers to search and browse the brief description of scientific and technical information distributed in massive scientific literature.
Data management and information processing play the key roles in developing the Internet of Things (IoT). The requirements of a well-defined data model for IoT involve in six aspects: semantic ...supporting, active data extracting and explaining, flexibility and extensibility, enabling to manage massive and heterogeneous data, supporting formal organization, and solid mathematic-based theory. This paper aims to exploring an extensible and active semantic information organization model for IoT to meet the above requirements, and the primary idea is “Object-cored organizing data, event-based explaining data, and knowledge-based using data.” The proposed model involves two layers: the object layer and the event layer, and both of them are discussed in detail including conceptions, schema definitions, and the rule-based knowledge representation. Semantic reasoning can be supported by the knowledge base which involves in a set of reasoning rules on semantic relations among objects or among events correspondingly.
Wearable devices measuring some physical or physiological quantity of an individual have already become a part of daily life for many people. While such simple devices output mainly the statistical ...values of measured quantities or count events, demands in sport are more stringent. Quantities of interest must be measured in a wider range, with a greater precision, and with a higher sampling frequency. We present a short introduction to motor learning in sport and its needs for technology back-up. We present properties and limitations of various sensors used for sport activity signal acquisition, means of communication, and properties and limitations of communication channels. We shed some light on the analysis of various aspects of sport activity signal and data processing. We present timing, spatial, and computational power constraints of processing. Attention is given also to the state of the art data processing techniques such as machine learning and data mining. We also put into context some technological trends and challenges in sport, such as the Internet of Things, fog and cloud computing, smart sport equipment, and real-time biofeedback systems and applications.
In prior investigations, a correlation was established between patient outcomes in locally advanced non-small cell lung cancer (LA-NSCLC) following thoracic irradiation and parameters, such as ...pre/post-treatment neutrophil-to-lymphocyte ratio (NLR) and NLR change (ΔNLR). However, these parameters could potentially be influenced by radiation-related variables, such as gross tumor volume (GTV). The primary aim of this study was to elucidate the factors impacting post-treatment NLR and ΔNLR and to further assess their prognostic relevance. In this retrospective study, a cohort of 188 LA-NSCLC patients who underwent thoracic radiation between 2012 and 2017 was assessed. The calculation of pre/post-treatment NLR involved the use of absolute neutrophil and lymphocyte counts. ΔNLR was defined as the difference between post- and pre-treatment NLR values. To assess the relationships between various variables and overall survival (OS), local progression-free survival (LPFS), and distant metastasis-free survival (DMFS), the Kaplan-Meier technique and Cox proportional hazards regression were employed. Additionally, Spearman's rank correlation analysis was carried out to investigate correlations between the variables. The analysis revealed that both post-treatment NLR (r = 0.315, P < 0.001) and ΔNLR (r = 0.156, P = 0.032) were associated with GTV. However, OS, LPFS, and DMFS were not independently correlated with pre/post-treatment NLR. ΔNLR, on the other hand, exhibited independent associations with OS and DMFS (HR = 1.054, P = 0.020, and P = 0.046, respectively). Elevated ΔNLR values were linked to poorer OS (P = 0.023) and DMFS (P = 0.018) in the Kaplan-Meier analysis. Furthermore, when stratifying by GTV, a higher ΔNLR remained to be associated with worse OS and DMFS (P = 0.047 and P = 0.035, respectively) in the GTV ≤ 67.41 cm
group, and in the GTV > 67.41 cm
group (P = 0.028 and P = 0.042, respectively), highlighting ΔNLR as the sole independent predictive factor for survival and metastasis, irrespective of GTV.
SMEs in China always face financing constraints and hardly obtain bank loans under unsound financing system due to the information asymmetry, while thousands of SMEs have contributed greatly to ...Chinese economic development in the last decades. Credit reporting has been verified to be an effective way to lower information asymmetry. However, existed credit reporting systems for SMEs can not meet the development of SMEs and provide enough information to the financial institutions in China. This paper introduces an active and dynamic credit reporting framework based on Big data and Blockchain for SMEs. The framework is composed of five modules, including credit data acquisition, authentication, evaluation, reporting, and interaction. And it features in capturing diversified data online, conducting evaluation and analysis in real time, generating online credit reports for users automatically, and providing an effective way for different entities to interact. A case study from a real credit evaluation company is also proposed finally to show the proposed framework.
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