Special Issue
[Submission Due Date - 2023-10-30]
ICT technologies and convergence practices for Digital Transformation, DX
KIPS Transactions on Computer and Communication Systems
Description
Digital Transformation (DX) technology is leading innovation across society and creating a new ecosystem of industrial convergence. In particular, AI, data, cloud, edge computing, AIoT, and digital twin technologies are core technologies for digital transformation. Earlier digital transformation cases were simple digital transformation with single ICT technologies such as AI, cloud, and data, but now, various digital transformation is taking place in all areas such as smart city, digital finance, digital manufacturing, digital agriculture, and digital fishery by converging multiple ICT technologies in various industries. Therefore, this special issue solicits papers on AI, cloud, data, AIoT, and digital twin technologies that are being applied for digital transformation in various areas, as well as ICT applications and convergence technologies that are being applied for digital transformation in various areas. In addition, this special issue also solicits papers on the history of ICT technology changes in the past and present to mark the 30th anniversary of the Korea Information Processing Society.
Scope & Topics
• ICT Applications and Convergence Technologies for Digital Transformation
• AI-based digital transformation cases
• Digital transformation cases in various industries
• Other digital transformation-related research areas
• Cases of ICT technology change history
Submission Guideline
• Submission: Online Manuscript Submission and Review System - Select 'Special Issue Track' - Select 'AI Application Technology'
• Page Limit: 20 pages
• Format: Your submission is subject to the 'Manuscript Preparation' of 'Instruction for Authors' in the Journal homepage (http://ktsde.kips.or.kr)
• Review: Final decision will be made at the 1st round
• Sample Manuscript Format: You can download it in the KTSDE homepage (http://ktsde.kips.or.kr)
- Submission Fee: USD 100 or KRW 100,000
- Contact: Ms. Young-Suk Yun (02-2077-1414, Ext. 3)
Schedule
* The scheduled publication date may be adjusted depending on the circumstances of the publication of the paper.
Guest Editors
Prof. YongGeun Hong (Daejeon University, Korea)
[Submission Due Date - 2020-09-15]
DNA (Data, Network, AI) based Intelligent Information Technology
KIPS Transactions on Computer and Communication Systems
Description
DNA (Data, Network, AI) is a relatively new term and has recently become a hot topic which combines three of the hottest acronyms. Recently, DNA-based intelligent services and applications are actively developed with IoT Technology. IoT consists of interconnected things with built-in sensors and has the potential to generate or collect a vast amount of data. Collected data can be then analyzed and utilized with AI for problem solving or decision making for Intelligent ICT service. Without AI, IoT and Data would have limited value. AI can multiply the value of Data collected by IoT; conversely, IoT can promote the learning and intelligence of AI.
There are many challenges while deploying DNA and DNA based intelligent applications in practice. For instance, the edge computing issues for supporting the low latency of transmitting huge data in networks and achieving real-time responses with high-performance AI for analyzing the huge data. Security issue is another challenge to provide privacy and safety in terms of data protection in personality applications based IoT system. Machine learning is one of the possible technologies to be utilized in DNA system protection. Besides, there are many other issues related to the increasing DNA systems and DNA based applications.
Since the combination of Data, Network and AI, namely DNA, has various potential technology to be able to develop Intelligent application in the real world, this Special Issue aims to solicit the submission of original research articles with a focus on challenging issues in the field of DNA technologies and Intelligent applications based on DNA. Both theoretical and experimental contributions containing novel architectures, systems, algorithms, approaches, techniques, or applications with new insights and findings in the field of DNA are welcome.
Scope & Topics
• DNA technology for CPS (Cyber-Physical Systems) and CPSS (Cyber-Physical-Social Systems)
• Cloud, fog and edge computing for intelligent service
• Machine learning and deep learning for intelligent service based on DNA
• 5G technology enabled DNA
• Intelligent vehicle service based on DNA
• Security and privacy in DNA
• Artificial Intelligence (AI) algorithms for DNA
• Intelligence Internet of Things (IoT) technologies for DNA
• DNA based innovative applications and Intelligent services
Submission Guideline
• Page Limit: 20 pages
• Format: Your submission is subject to the 'Manuscript Preparation' of 'Instruction for Authors' in the Journal homepage (http://ktccs.kips.or.kr)
• Review: Final decision will be made at the 1st round
• Sample Manuscript Format: You can download it in the KTCCS homepage (http://ktccs.kips.or.kr)
• Contact: Ms. Yong-Sook Yoon (02-2077-1414, Ext. 3)
Schedule
Guest Editors
Prof. Joosang Youn (Dong-Eui University)
[Submission Due Date - 2019-01-20 ]
Machine Learning in IoT and Edge Computing
KIPS Transactions on Computer and Communication Systems
Description
The Internet of Things (IoT) advances and promotes a variety of wired and wireless technologies through embedded devices, smart objects, and smartphones. The integration of IoT along with Wireless Sensor Networks (WSN) based on new Bluetooth standards, such as Bluetooth Low Energy (BLE) 4.0 and ZigBee, unlocks new IoT applications and services in the future generation of networks. IoT devices generate a massive volume of data continuously. In general, cloud systems are used to store and compute such a large volume of IoT sensor data. This creates even more challenges in data storage and the integration between IoT devices. In order to overcome this problem, edge computing technology moves the collection, process, and analysis of data into the point of origin, rather than to a cloud-based data center, and it enables data processing and analytics as well as knowledge generation to occur in the vicinity of the source of the data. Thus, edge computing technology is becoming a significant platform for enabling consumer-centric IoT services and applications that demand real-world applications. In the meantime, machine learning is a branch of artificial intelligence (AI) that focuses on enabling machines to learn for themselves without the need for human intervention or to be explicitly programmed to do so. Machine learning on IoT devices allows for learning models directly on the devices themselves, removing the need to externalize data in any way. Machine learning algorithms have a capability to process and analyze a kind of streaming data generated at the edge of the network and IoT devices. This special issue focuses on challenges and problems in machine learning algorithms for processing, learning and discovering knowledge from IoT devices and edge computing technology.
Scope
Submission Guideline
Schedule
Guest Editors
Prof. Kyungbaek Kim (Chonnam National University)
[Submission Due Date - 2016-10-30 ]
Android Security
KIPS Transactions on Computer and Communication Systems
Description
We plan to publish a new special issue. We are soliciting high quality manuscripts presenting original contributions for its special issue, and the manuscripts should be submitted by our online submission and review system. When submitting a new manuscript, please select 'Special Issue' track and then select 'Android Security' special issue, too.
Scope
Topics of interest include, but are not limited to:
- - Android system security
- - Android app security
- - Android hardware security
- - Android cryptography
- - Applying machine learning to android security
- - Android security in IoT Environment
- - Other android security study
Submission Guideline
- Submission: Online Manuscript Submission and Review System - Select 'Special Issue Track' - Select 'Android Security'
- Page Limit: 20 pages following the 'Manuscript Preparation' of 'Instruction for Authors'
- Format: Your submission is subject to the 'Manuscript Preparation' of 'Instruction for Authors'
- Review: Final decision will be made at the 1st round without revision process
- Sample Manuscript Format: Society homepage (http://www.kips.or.kr -> Notifications/Events)
- Submission Fee: 100,000 (KRW)
- Contact: Ms. Yong-Sook Yoon (02-2077-1414, Ext. 3)
Schedule
- Expected Publication Date: Vol.5, No.12, Dec. 2016
Guest Editors
Seoul Women's University
Indexing
All publications of KTCCS is indexed in DOI, EBSCO, Google Scholar, Crossref, and CrossCheck.
KTCCS is also selected as the Journal for Accreditation by NRF (National Research Foundation of Korea).
