Fourth International Conference on Digital Data Processing (DDP 2024)
Yeshiva University. New York. US
September 30-October 01, 2024
(www.socio.org.uk/ddp)
(IEEE Xplore indexed)

As technology advances in different sub-domains of computing, data-driven models are becoming increasingly important. The data-dependent world now faces many challenges in terms of data accuracy and data privacy. High-impact advancements include machine learning, artificial intelligence, deep learning and many more. Data is growing exponentially in terms of diversity and complexity. One organization or industry processes over a few million transactions per hour and stores hundreds of billions of data. We live in a world with a great need for more efficient data analysis and processing. Data analytics can reveal hidden patterns, complex relationships, internal information relations, and even segmentation. Data applications have opened up new possibilities in every aspect of our lives. Studying data and its structure, dynamics, and modern data technologies is ongoing. There is a great deal of literature and research on data management, but it does not address the data processing needs. Many studies focus on developing models and systems for analyzing large datasets.

Data analysis leads to application domains that have a systematic impact on decisions. The knowledge gained from the data analysis enables the generation of critical information for multiple domains. In this conference, we review and discuss the latest trends in data management, the opportunities and challenges, and how they have affected organizations' ability to develop effective business and technology strategies and stay up-to-date in data technology. We also highlight current open research directions in data analytics that need further attention.

The proposed conference will discuss topics not limited to

Data applications in various domains and activities
Data in cloud
Real-world data processing
Data inaccuracy and reliability issues
Data Ecosystem
Business Analytics
New data analytics techniques
Physical and management challenges
Synthetic data
Data synthesis
Crowdsourcing and Sensing
Data modelling
Deep learning techniques
Data fusion
Descriptive analytics, Diagnostic analytics, Predictive Analytics, and Prescriptive analytics
Machine learning impact on data processing
Network optimization
Data in Biomedical Engineering
Data in Materials science and mechanics
Data handling and applications in domains
Wireless Networking Data Management
Data of Electronic & Embedded Systems
Multi-media Systems Data
Artificial Intelligence Models and Systems Data
E-Computing Data
Renewable Energies Data

General Chair

Honggang Wang, Yeshiva University, USA

Program Chairs

Youshan Zhang, Yeshiva University, USA
Ezendu Ariwa, Warwick University, UK
Simon Fong, University of Macau, Macau

Program Co-chairs

Martin Loperz, University of Vigo, Spain

Keynote Speakers

1. Xiaofan (Fred) Jiang, Columbia University
2. Edwin Chihchuan Kan, Cornell University

Publications

All accepted and presented papers will be submitted to IEEE Xplore for publication and indexing.

Modified versions of the papers will appear in the following journals.

Journal of Digital Information Management
International Journal of Computational Linguistics
Information Services & Use

Important Dates

Submission of Workshop Proposals: April 10, 2024
Submission of Papers: July 15, 2024
Notification of Acceptance/Rejection: August 15, 2024
Camera-ready: September 15, 2024
Registration: September 15, 2024
Conference Dates: September 30- October 01, 2024

Paper submission

Papers should follow the IEEE template. Submissions at http://socio.org.uk/ddp/paper-submission/

Contact: stm@socio.org.uk

Martes, 17 de septiembre – presencial. Pre-Congreso ARGENCON 2024.

El IEEE Computational Intelligence Society Argentina junto al Games Technical Committee llevarán a cabo el martes 17 de septiembre la undécima edición del Torneo Regional de Inteligencia Computacional como actividad previa de ARGENCON 2024, el Congreso Bienal premium de la Sección Argentina del IEEE.

El TRIC presentará conferencias, talleres y otras actividades relacionadas a los tópicos mencionados con la participación de profesionales, investigadores, docentes y estudiantes. Te invitamos a presentar tus investigaciones y trabajos. También podés asistir como oyente a las actividades y relacionarte con personas con tu mismo interés.

El TRIC es el evento más antiguo de IEEE CIS Argentina, iniciado en el año 2002, con más de 700 asistentes y 60 premios entregados. El torneo considera los trabajos en el track de:

• Inteligencia Computacional
• Videojuegos
• Edutainment
• Gamificación
• Juegos Serios

Y reconoce los méritos y/u originalidad de los trabajos presentados con certificados y premios.

El TRIC es abierto y gratuito para todo público y este año se realizará en forma presencial el martes 17/09 en la sede de la Universidad Tecnológica Nacional de San Nicolás (Provincia de Buenos Aires) de 4 pm a 7 pm aproximadamente (hora de Argentina).

Acompañan Universidad Abierta Interamericana, Universidad de Palermo, Universidad de la Cuenca del Plata, Universidad FASTA, Red Internacional de Desarrollo de Videojuegos, CIS Labs, Centro de Altos Estudios en Tecnologías Informáticas (CAETI), Academia Nacional de Ciencias de Buenos Aires (ANCBA), Sociedad Científica Argentina, Escuela de Game Design Latinoamérica, Brinca Academia de Videojuegos, MIMEC (Cluster de Industrias Creativas de Monterrey) Instituto de Innovación para el Desarrollo de la industria de los Videojuegos.

LLAMADO A ENVÍO DE TRABAJOS
Para más detalles, visite el enlace del IEEE Biennial Congress of Argentina
(ARGENCON): https://attend.ieee.org/argencon-2024/articulos/

Más información : https://r9.ieee.org/ar-cis-gaming/tric-xi-torneo-regional-de-inteligencia-computacional-2024/

Biological data are collected from a variety of sources, including humans, animals, and viruses. Research on these data has emerged in many fields, such as genetics, proteomics, and healthcare applications, to name a few. Presently, thanks to the development of computer technology, extracting useful data from raw biological data and deciphering intricate biological data have become more feasible through the application of machine learning techniques.

The purpose of this Special Issue is to publish recent developments in machine learning applications for biological data. We invite researchers to submit their research articles and reviews to this Special Issue. Example topics include (but are not limited to) the following, which relate machine learning applications to biological data:

• Use of machine learning algorithms for investigating biological systems;
• New machine learning algorithms;
• Genetics/genomics;
• Proteomics;
• Medical image analysis and diagnosis;
• Drug discovery/development;
• Healthcare applications.

Keywords: machine learning; artificial intelligence; biological data; genetics; genomics; proteomics; bioimage; drug discovery

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

The deadline for manuscript submissions: 30 June 2024 (can be extended)

More details about the Special Issue can be found here.