Special Issue on Machine Learning Enabled Technologies for Sustainable Computing
摘要截稿:
全文截稿: 2019-03-01
影响因子: 2.798
期刊难度:
CCF分类: 无
中科院JCR分区:
• 大类 : 计算机科学 - 4区
• 小类 : 计算机:硬件 - 4区
• 小类 : 计算机:信息系统 - 4区
Overview
In the present era machine learning (ML) based technologies have been revolutionizing and reshaping the global world with high sustainability to get them up to mark healthcare platform. Besides, sustainable autonomous and self-driven methods are getting closer attention from every corner to supplement the medical world with the modern trends and practices. Sustainable computing-based techniques are the key role players in most of the areas including industry, healthcare, and games among others. These applications need high visibility, productivity and innovative technologies for the betterment of each sector. Furthermore, the emerging role of the sustainable computing applications has dignified the importance and role of the various sectors especially, medical healthcare which is the cornerstone of today’s aging society. The computer-assisted living is one of the examples in the medical world to diagnose and examine the critical features of the common and elderly citizens effectively. On the one hand this domain has caught the attention, and on the other hand, there is a lack of proper interaction between humans to computers and computer to sustainable computer systems with strong and retainable capabilities. Thus, to obtain the longer and green environment self-adaptive and effective monitoring methods are the cornerstones of today’s aspiring need. Emerging sustainable computing enabled applications with the involvement of machine learning methods not only have facilitated every corner of the world but also opened the doors with various directions to promote every desired landscape. Machine learning is the prominent and inspiring ingredient with high strength in numerous areas for example, sustainable industrial and home automation, image processing, efficient and sustainable diagnosis in medical healthcare, etc. Due to a broader scope, it has been integrated with every moment of human needs where sustainable computing based emerging technologies and trends are playing the major role in developing the entire world.
The key purpose of this special issue is to integrate the academic and industrial thoughts by adopting the machine learning based sustainable and emerging computing applications to promote every sector for the betterment of the society.
Mainstreams are given below with a broader scope but not limited to, the following:
· Sustainable Computing based applications in healthcare domain
- Power-aware and battery-efficient sustainable communication systems
- Wireless power transfer based sustainable systems
- Sustainable Bluetooth low energy and LoRa
· Machine learning and deep learning for sustainable computing bio-informatic systems
- Q-learning based sustainable cloud-computing platform for pervasive healthcare
- Sustainable architectures and algorithms for Telemonitoring
- Sustainable and adaptive Internet of medical things
· Neural Network and Re-enforcement based sustainable frameworks/architectures and algorithms for the medical internet of things
- Fuzzy-based sustainable and QoS-aware body sensor networks
- Sustainable and Energy Harvesting based medical applications
- 5G-aware sustainable and battery friendly approaches
- Green and sustainable biomedical systems
· Self-adaptive and resource-aware sustainable healthcare technologies
- Secure and sustainable mobile healthcare platform
- QoS/QoE management and monitoring in the sustainable mobile healthcare
· Blockchain-based frameworks and strategies for sustainable Ambient living
- System-level optimization, cross-layer coordination
- Sustainable computing based decentralized systems for healthcare
- Secure and sustainable architectures and approaches for elderly healthcare
· Big data analytics in sustainable computing-based technologies.
- Sustainable computing-based data mining algorithms and frameworks
· Graphical summarization and visualization techniques for sustainable system
- Sustainable human computer interaction platform