【计算机类】CCF推荐期刊专刊约稿信息7条

全文截稿: 2017-09-20

影响因子: 1.388

期刊难度: ★★★

CCF分类: C类

网址: http://www.tandfonline.com/toc/tbit20/current

From the well-defined scientific and application domain described as Information and Communication Technologies we focus on some of the most evolutionary technologies of the last years namely Learning Analytics and Cognitive Computing. These technologies and methodologies are in the focus of this special issue aiming to foster a scientific debate for the new era of Higher Education, where academic institutions would have to develop strategies for the adoption of technologies in the daily educational process beyond limitations and barriers promoting advanced decision making capabilities.  

Learning Analytics and applications have received growing attention in recent years from various perspectives. The thriving numbers of Big Data creation in Higher Education have captured the attention of Higher Education, computer engineering and business researchers that, in the past years, have been trying to decipher the phenomenon of Higher Education Performance and Innovation, its relation to already-conducted research, and its implications for new research opportunities that effect innovations in teaching and higher education dynamics.

The current applications of Learning Analytics in Higher Education worldwide present a very interesting picture. Several medium/big scale information systems provide a variety of services to all the stakeholders in Higher Education institutions including students, professors, managers and professionals.  A key strategic shift in the focus of education is evident, from a core-knowledge oriented education to a collaborative-dynamic evolving paradigm. It seems that we are in a crossroad where the traditional classroom based model of Higher Education must be critically enriched with technology enabled added value components. Toward this direction, it is critical to reveal hidden pattern in educational data, to develop, understand and measure key performance indicators and to promote sophisticated decision making

These widely-accepted Learning Analytics systems endeavors demonstrate that a wide range of decision making capabilities are available and present a viable and robust alternative to traditional strategies to Higher Education.  In parallel several surveys in Higher Education directly link the response to students’ inefficiencies to the use of advanced analytics in Higher Education.  

The objective of the special issue is to communicate and disseminate recent higher education, computer engineering, social, behavioral and business research and success stories that demonstrate the power of Learning Analytics to improve the Quality of Higher Education and the Decision making capabilities. The purpose of the special issue is to demonstrate state-of-the art approaches of Learning Analytics and to show how new, advanced, educational models and adoption strategies can expand the sustainability frontiers in advanced applied computer engineering and knowledge management towards Smart Education and knowledge society vision.

Consequently, manuscripts are sought that touch on these aspects and extend technical and domain knowledge in the global economy and Higher Education. This special issue is intended to initiate a dialog between the educational, social, computing, business, human, and technical views of the field that effect the Higher Education environment through the adoption of novel Learning Analytics solutions. Novel Higher Education approaches and sound technological learning analytics solutions will be expected.

全文截稿: 2017-09-30

影响因子: 8.085

期刊难度: ★★★★★

CCF分类: A类

网址: http://www.comsoc.org/jsac

The architectures of mobile networks (both core and radio access networks), fixed networks, and service delivery platforms are subject to an unprecedented techno-economic transformation. This trend, often referred to as Network Softwarization within an ever-growing community of researchers in both academia and industry, will yield significant benefits in terms of reducing expenditure and operational costs of next generation (5G and beyond) networks.

The key enablers are Network Function Virtualization, Software-Defined Networking, and Cloud, Fog, and (mobile/multi-access) Edge Computing. These technologies are still at their infancy. They introduce significant technical challenges that the research community is tackling. When they are integrated to enable fully programmable, flexible, service/vertical-tailored, and automated end-to-end networks (i.e., network slices), the challenges become more significant. The technical challenges pertain to the overall process, network slice instantiation and maintenance, slicing over multi-domains (i.e., both administrative and technology), orchestration and allocation of shared and isolated resources (i.e., computing and storage capacity, virtualized network functions, networking resources, and physical radio resources), and communication interfaces amongst different network slices along with supporting algorithms and mechanisms. The concept of network softwarization is expected to serve diverse services and verticals, including,  but not limited to, Tactile Internet of Things, Pervasive Robotics, Self-driving, Immersive communications, Industry 4.0, and Augmented Reality.

We invite high-quality submissions to the IEEE JSAC series on network softwarization and enablers. The first issue of the series will be published in April 2018, followed by a number of other issues to be scheduled in the period of 2018 – 2020. We are seeking papers which have not been published before and are not currently under review by any journal. The scope of this series is papers in the general arena of network softwarization, specifically on, but not limited to, the following topics:
- RAN slicing
- Mobile core networks and their slicing
- Fixed network slicing
- Slice programmability, modeling, composition algorithms and deployment
- System/service orchestration and management
- Network function decomposition
- Network function virtualization
- Service function chaining
- Resource sharing, isolation, and federation
- Software defined networking
- Cloud computing technologies
- Virtualization techniques
- (mobile/multi-access) edge and fog computing
- MEC-, SDN-, NFV-based network service enhancement
- Service, slice, and infrastructure monitoring
- Performance, interoperability, and scalability issues
- Security, trust, and privacy issues in virtualized environments
- Best practices from experimental testbeds, trials and deployment
- Verticals, new value chains and business models

全文截稿: 2017-09-30

影响因子: 0.0

期刊难度: ★★★

CCF分类: C类

网址: http://www.inderscience.com/jhome.php?jcode=ijics

Cyber security is quickly and constantly evolving due to the nature of security risks. Cyber security is the body of technologies, processes and practices designed to protect networks, computers, programs and data from attack, damage or unauthorised access. It involves the protection of information assets by addressing threats to information processed, stored, and transported by internetworked information systems.

The objective of this special issue will be to bring together research contributions on the design, specification, and implementation of architectures, protocols, and algorithms for current and future cyber security issues and solutions.

Suitable topics include, but are not limited to, the following:

- New paradigms in cyber security
- Emerging attack methods
- Digital forensics and privacy issues in cloud computing
- Cyber monitoring approaches
- Big data security strategy
- Big data security issues in social networks
- Security and fault tolerance for embedded or ubiquitous systems
- Critical issues and solutions of cyber security in tele-health
- Cyber security in mobile embedded systems
- Cyber security assessment
- Data analytics for cyber resilience
- Organisational security (government, commercial)
- Resilient smart cities
- Resilient internet of things (RIOT)
- Cyber-cities and cyber-environments
- Critical infrastructure security
- Backup and recovery for systems of systems
- Disaster planning and management from cyber perspective
- Integrated and smarter sensors
- Cloud computing security
- Big-data security
- Advanced persistent threats
- Network traffic analysis and trace-back
- Cyberspace operations
- Incident response
- Privacy in pervasive sensing and social media
- The security of online transactions
- Cyber-defence
- Authentication and access control
- Privacy-preserving Data Analysis

全文截稿: 2017-09-30

影响因子: 0.0

期刊难度: ★★★

CCF分类: C类

网址: http://www.tandfonline.com/pricing/journal/ugit20#.V5YLiUuF6Ul

Data analytics involves a systematic study of collection, aggregation, organization, processing, and analysis of data. With explosive growth in big data worldwide, organizations are looking for ways to leverage analytics tools, technologies, and applications from a global perspective to gather insights for improved decision making. The new actionable insights gained are expected to support achieving organizational and community goals at a global scale such as innovation, idea generation, problem solving, decision making, negotiation, and execution. Data analytics requires deep understanding of formulating problems valuable for collaborative goals, engineering effective solutions to business problems, and ways to communicate findings effectively across roles ranging from business managers, to users or customers.

Businesses and organizations can enhance their performance or competitiveness by investigating how data analytics can facilitate collaboration both within and across organizations.  For example, businesses are trying to understand how data analytics can help engage customers and improve operation efficiency and how it can leverage social media to support corporate knowledge management.  Another example is collaborative generation of ideas and solutions through crowdsourcing and online communities (such as dominodatalab.com). Access to heterogeneous, voluminous, and unverified data presents both new opportunities and challenges for data analysis and applications. Identifying and building the right talent is a critical component of an organization’s analytics capability. Organizations also face new ethical, legal, and regulatory challenges with analytics management and governance.

This special issue will present global issues in the context of data analytics and applications and a forum for academic researchers, policy makers and practitioners.  Theoretical and methodological papers from multiple disciplines such as information systems, marketing, management, organizational behavior, and cultural studies are welcome. Consistent with the focus of JGITM, all submitted papers must address global issues associated within the theme of the special issue.

Possible contributions may include, but are not limited to, the following topics:
- Global challenges and opportunities in data analytics
- Cross-country comparison of talent issues in the context of data analytics
- Collaboration across organizations for social impact through analytics
- Collection, aggregation, and organization of global data for analytics
- Cross country comparison of data analytics use to improve health/lifestyle
- Data analytics for collaborative work (decision making, problem solving, negotiation, and creativity/innovation) in a global organization
- Data science and analytics for inter-organizational collaboration
- Cross country comparison of crowdsourcing analytics
- Global security and privacy issues in data analytics and applications
- Culture-related human factors in data analytics and applications
- Comparative case studies on data analytics and applications
- Analysis of global online social networks
- Governance issues in the context of data analytics in global organizations

全文截稿: 2017-09-30

影响因子: 0.711

期刊难度: ★★★★

CCF分类: B类

网址: http://comjnl.oxfordjournals.org/

Socially Aware Networking (SAN) is a modern paradigm that can be applied over many forms of human-centric wireless networks such as mobile ad hoc networks, delay-tolerant networks, and cognitive radio networks. In the SAN paradigm, the social features and mobility patterns of nodes are exploited to design efficient and effective networking protocols. In common, social network analysis techniques (such as node centrality, similarity, and community structure) are employed to explore the nodes’ attributes and behavior, discover relationships among them, and study their implications.

Nevertheless, designing an SAN paradigm entails several major challenges due to the lack of standard architectures, analysis methods, and evaluation metrics. On one hand, new social network applications require having access to the nodes’ various social and contextual information, and thus modern data sensing and modeling technologies should be developed. On the other hand, sharing such information is a matter of concern for users and effective safety mechanisms should be established to protect them against various damages. Meanwhile, rational mobile nodes might not be willing to cooperate with others due to the resource constraints or social objectives. Hence, realistic human altruism models should be explored to realize the interaction models among nodes and analyze the impact of their cooperation on the performance of networking protocols. Thus, it is necessary to redesign the standards and protocols for the SAN paradigm. This special issue aims to solicit high quality technical articles proposing novel system architectures, design models, and communication protocols in the area of the SAN paradigm with cutting-edge analysis and experimental results.

The topics of interest include, but are not limited to:
- New protocols, architectures, and services for SAN
- Operating system and middleware support for SAN
- Applications, simulations, and performance analysis for SAN
- Data sensing, learning, and computing in SAN
- Big data mining and analysis for SAN
- Analysis of human mobility and dynamics in SAN
- Social network analysis techniques in SAN
- Opportunistic communications and computing in SAN
- Exploring social cloud networks and computing for SAN
- Data forwarding and sharing in SAN
- Game theoretic applications in SAN
- Cooperative models and incentive mechanisms in SAN
- Security, privacy, and trust in SAN

全文截稿: 2017-10-01

影响因子: 0.85

期刊难度: ★★★★

CCF分类: B类

网址: http://todaes.acm.org/

As more low-power and internet-connected gadgets and sensors are integrated into our lives, there are issues remaining on optimal system design of these systems. In particular, performance, reliability, and security are key parameters. Furthermore with emerging research areas such as autonomous cars, advanced manufacturing, smart cities and building, usage of Internet of Things (IoT) devices is expected to skyrocket. This special issue focuses on design and optimization aspects of IoT’s. We believe these areas will also likely be key to advancements in the IoT arena.

We are inviting you to submit your original work to this special issue. The submissions should be related to the topics suggested below. The submissions will be subject to a two stage blind review by eminent researches in this research field. End goals of the special issue are to improve understanding about system performance, reliability, and security of IoT systems and propose novel solutions to these.

Topics for the Special Issue
– Design automation, test, and verification-aspects of internet of things,
– System architecture for internet of things,
– Performance optimization for internet of things,
– Reliability characterization and improvement for internet of things
– Security aspects of internet of things,
– Technology architecture for internet of things,
– Programming the internet of things,
– Applications of internet of things.

全文截稿: 2017-10-15

影响因子: 8.222

期刊难度: ★★★★★

CCF分类: A类

网址: http://www.springer.com/journal/11263/about

The field of Computational Photography and Imaging seeks to create novel photographic functionalities and experiences that go beyond what is possible with traditional cameras, by using a combination of unconventional optics and novel algorithms. In the last decade, computational photography and imaging has emerged as a vibrant field, both in academic research and industrial development. Examples of computational cameras and algorithms that have transitioned into the consumer domain include: 360-degree cameras (Ricoh, Google Jump), light-field cameras (Lytro), depth cameras (Kinect), navigating large photo collections (Photo Tourism), time-lapse ego-centric cameras (Microsoft Hyperlapse), high dynamic range cameras (Red, Blackmagic Design, iPhone), panoramic imaging, and image enhancement software (Photoshop).

In this special issue, authors are invited to submit novel full-paper submissions on various aspect of computational photography and imaging. This includes modifying the design of a traditional camera by introducing programmable optical elements and light sources, as well as developing algorithms that take information captured by conventional or modified cameras, and create a visual experience that goes beyond the capabilities of traditional systems.

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