Natural languege processing

Natural Language Processing (NLP) Track Session, topics for the session include, but are not limited to:

    • Cognitive aspects of natural language processing
    • Corpus and Language Resources
    • Corpus-based language modeling
    • Dialog Systems
    • Information Retrieval
    • Language and Ontology Unifying
    • Language Engineering
    • Language Learning
    • Language processing in internet applications
    • Languages for Disability
    • Linguistic models of language
    • Linguistic Resources
    • Machine Translation
    • NLP Applications
    • NLP-based knowledge science
    • Ontology Engineering
    • Phonetics, phonology and morphology
    • Pragmatics and discourse
    • Semantics, syntax and lexicon
    • Speech Recognition and Synthesis
    • Tools and resources for NLP

Robotics, IoT and Embedded System

High performance embedded computing has recently become more and more present in devices used in everyday life. A wide variety of applications require building up powerful yet cheap embedded devices. In this context, embedded software has turned out to be more and more complex, posing new challenging issues. Design of embedded systems must take into account a wide variety of constraints: performance, code size, power consumption, presence of real-time tasks, robustness, maintainability, security, and possibly scalability. Novel robotics applications is one of a good example in high performance embedded system that can driven by research, industry and society call for the development of systems of ever increasing complexity: systems with sliding autonomy. Software development for autonomous robots and to boost a smooth shifting of results from simulated to real-world applications is needed.

Data Analytics and Machine Learning

Decision-making is a crucial, yet challenging mission in enterprise management. It is still made based on a reactive approach rather than on facts and proactive approaches. This is often due to unknown correlation between data and goals, conflicting goals and weak defined strategy. Enterprise success depends on fast and well-defined decisions taken by relevant policy makers and business actors in their specific area. Open business intelligent systems can be seen as a collection of decision support technologies and tools for enterprises to enable knowledge workers such as executives, managers, and analysts to make better and faster decisions. With the emergence of big data, it possible to explore new opportunities that will revolutionize business intelligence. These include data warehouse based decision support, Hadoop (development environment), sensor data, social media, machine learning and crowd sourcing. The aim of this workshop is provide a forum to review open business intelligent systems as an open innovation strategy and address their importance in revolutionizing knowledge processing in economics and business sustainability. Topics for the workshop include, but are not limited to:

    • Artificial Intelligence tools & Applications
    • Big Data Mining and Analytics
    • Machine learning
    • Neural Networks
    • Probabilistic Reasoning
    • Evolutionary Computing
    • Pattern recognition
    • Heuristic Planning Strategies and Tools
    • Data Mining and Machine Learning Tools
    • Reactive Distributed AI
    • Hybrid Intelligent Systems
    • Intelligent System Architectures
    • Network Intelligence
    • Multimedia & Cognitive Informatics
    • Pervasive Computing and Ambient Intelligence
    • Semantic Web Techniques and Technologies
    • Web Intelligence Applications & Search
    • Deep Learning
    • Business Intelligent
    • Information Technology Management

Signal, Image and Speech Processing

The signal, image and speech processing (SIS) will focus on basic concepts, methodologies, and successful adoption of signal, image and speech processing and artificial intelligent technology. The conference will use technical papers, challenge papers, invited talks, and panel discussions to explore issues, methods, and lessons learned in the development and deployment of signal, image and speech processing, and AI applications; and to promote an interchange of ideas between basic and applied signal, image and speech processing.

The adoption of signal, image and speech processing and artificial intelligent technology, and in particular of its most challenging components like information and intelligent which can constitute the basic building blocks for a variety of applications within the signal, image and speech processing world. The combination of the emerging information technologies such as information retrieval, computer vision, expert systems, chat bot, social network analysis, and big Data Analyticss lets us transform everyday information into smart knowledge applications.

This track will bring all signal, image and speech processing issues from a diverse group of people working on real world systems for commercial, industrial and academic applications. People from different background will share idea and experience by presenting the study and results leading to intelligent innovation, knowledge and applications.

Authors are solicited to contribute to this session by submitting papers that illustrate research results, projects, surveying works, and industrial experiences that describe significant advances in signal, image and speech processing, intelligent computing and business applications of information systems. Topics for the session include, but are not limited to:

    • AI in image and speech processing
    • Computer vision and virtual reality
    • Content-based image retrieval
    • Content-based indexing, search and retrieval
    • Document recognition
    • Evolution and fuzzy computation
    • Hardware implementation for signal processing
    • Image and video coding and compression
    • Image filtering, restoration, and enhancement
    • Image segmentation
    • Intelligent system and application
    • Multiple filtering and filter banks
    • Object and face detection
    • Pattern analysis and recognition
    • Super-resolution imaging
    • Time-frequency signal analysis
    • Video analysis and event recognition
    • Video compression and streaming
    • Visualization
    • Web intelligence application and search

Smart industrial Technologies

One science-related technology by applying technology to various tasks in the industry. In addition, including management quality control plant layout, industrial technician. There is knowledge in both smart technology and management will be able to work well with engineering science. Topics for the workshop include, but are not limited to:

    • Smart Home and Smart Building
    • Smart Material
    • Smart Transportation and Infrastructure
    • Smart Grid
    • Smart City and Technology Application
    • Smart Energy and Efficient-Networks
    • Autonomous Vehicles
    • Big Data, Machine Learning and Artificial intelligence for Industry Management
    • Condition Monitoring and Control for Intelligence Manufacturing
    • Smart Management for Industry
    • Smart and Technology in Tourism
    • Smart and Technology in Education
    • Learning Innovation Technology
    • Basic Research for Smart Industry
    • Relate topic in Smart Technology and Engineering
    • Energy Storage Technology

AI and Iot: Design and Applications

Design and implementation of AI + IoT applications, including sensor signal processing, energy conversion, speech processing, image processing, network computing, and distributed computing. Design and realization of embedded processors for AIoT applications, including FPGA, ASIC, DSP, and soft-core processors. Software platform for AIoT applications, including middleware for Things and gateway, AIoT-ready cloud infrastructure. AI algorithms related to AIoT applications, including Neural Networks, Bayesian Models, Pattern Recognition, Deep Learning, Biologically Inspired Neural Networks, and Semantic Web. Emerging technologies for next-generation AIoT computing systems and other related topics such as ICT hardware and software, ICT Policy/Strategy, and Mathematical Foundations of AI and Intelligent Computational methods. 

Management Technology

Service Science
• Management and Engineering
• Operations
• Logistics and Supply Chain Management
• Optimization
• Probabilistic and Statistical Model
• Economics
• Occupational Safety and Health Management
• Ergonomics
• Human Resource and Organization Management
• Environmental Management 

Security of IoT

Internet of Things (IoT) devices are becoming more common in our everyday lives as the backbone of interconnected smart homes, smart hospitals, smart cities, smart wearables, and other smart environments. The Internet of Things (IoT) makes use of embedded technologies with sensors and communication capabilities. These devices can broadcast their presence to other items and communicate with them utilizing a wide range of protocols and technologies. The usage of IoT brings benefits in terms of usability, efficiency, and cost savings, but it also increasingly poses security dangers and presents difficulties for digital forensics. These elements must be prioritized, as evidenced by the exponential growth of IoT botnets like Dark Nexus. Researchers and practitioners from the security and forensics sectors will be gathered at this session to discuss IoT-related issues and potential solutions.

    • Adversarial attacks for Artificial Intelligence in IoT
    • Cryptography protocols and algorithms for IoT
    • Data analysis of IoT for forensic investigation
    • Privacy and trust in IoT
    • Security and forensic aspects in cyber physical IoT systems
    • Security applications and management of IoT
    • Threat models and attack strategies for IoT
    • Challenger related to IoT forensics and security
    • Cybercrimes exploiting IoT