CcS 2020 is organized by:
Research Center for Community Centric Systems

Technical Sponsor:


Technical Supporter:



Advisory Committee:

Toshio Fukuda
Meijo University, Japan
Yutaka Hata
University of Hyogo, Japan
Levente Kovács
Obuda University, Hungary
Honghai Liu
University of Portsmouth, UK
Ahmad Lotfi
Nottingham Trent University, UK
Chu-Kiong Loo
University of Malaya, Malaysia
Junichi Yamamoto
Keio University, Japan
Indra Adji Sulistijono
Politeknik Elektronika Negeri Surabaya, Indonesia

Organizing Committee:

General Chair:
Naoyuki Kubota
Tokyo Metropolitan University, Japan

General Co-chairs:
Toru Yamaguchi
Tokyo Metropolitan University, Japan
Sunu Wibirama
Universitas Gadjah Mada, Indonesia
Byung-Jae Choi
Daegu University, Korea

Program Chair:
Yasufumi Takama
Tokyo Metropolitan University, Japan

Program Co-chairs:
Naoyuki Takesue
Tokyo Metropolitan University, Japan
Syoji Kobashi
University of Hyogo
Jing Li
Nanchang University, China

Special Sessions Chair:
Zhaojie Ju
University of Portsmouth, UK

Special Sessions Co-Chairs:
Takenori Obo
Tokyo Polytechnic University, Japan
Politeknik Negeri Semarang, Indonesia

Award Committee Chair:
Chang-Shing Lee
National University of Tainan, Taiwan

Award Committee Co-Chairs:
Jinseok Woo
Tokyo University of Technology, Japan

Workshop Chair:
Kazuyoshi Wada
Tokyo Metropolitan University, Japan

Workshop Co-chairs:
Janos Botzheim
Budapest University of Technology and Economics, Hungary
Emmett Kerr
Ulster University, UK

Publication Chair:
Takahiro Takeda
Daiichi Institute of Technology, Japan

Publication Co-Chairs:
WeiHong Chin
Tokyo Metropolitan University, Japan

Publicity Chair:
Takeo Ainoya
Tokyo Metropolitan University, Japan

Publicity Co-Chairs:
Simon Egerton
La Trobe University, Australia
Lieu-Hen Chen
National ChiNan University, Taiwan

Financial Chair:
Eri Sato-Shimokawara
Tokyo Metropolitan University, Japan
Yasunari Fujimoto
Tokyo Metropolitan University, Japan

Invited Talks of CcS 2020

1. Fertility Treatment Assist by Information Technology
2. EventGo! Exploring Event Dynamics from Social-Media Posts
3. Medis247

Speaker: Yutaka Hata


Title: Fertility Treatment Assist by Information Technology

Date: 23 September 2020
Time: 9:40 - 10:40

Currently, there are a lot of active studies in the medical and healthcare field using information technology and artificial intelligence (AI). In this talk, I will focus on the fusion research of AI and reproductive medicine, and discuss the usefulness. I will talk about the following topics. (1) Detection of thick seminiferous tubules in the testicles: In micro-TESE surgery is performed using a microscope, and the seminiferous tubules that produce sperm are removed, and the sperm is collected from the removed seminiferous tubules. This sperm collection surgery for patients with non-obstructive azoospermia requires incision of the testes. This damage needs to be minimized, and this cost must be saved. Therefore, it is required for both surgeons and patients to non-invasively detect the presence of sperm in the testes before this operation. In this study, we detect the seminiferous tubules with a diameter of 250-300 micrometer that can recover sperm using ultrasound technique. However, currently used ultrasonic waves of about 8 MHz cannot find a fine tube of this diameter by the low resolution. Thus, we found a characteristic that the peak frequency of the ultrasonic reflected wave is proportional to the reciprocal of the diameter, and estimated the diameter of the seminiferous tubule present in the testicle based on fuzzy inference. (2) Supporting of ovum collection surgery: At the time of surgery to collect ova, an ultrasonic system is generally used. However, the follicles watched by the ultrasound system do not always contain ovum, and there are follicles that do not contain ovum is called vacuole. It is not possible in terms of resolution to confirm the vacuoles with ultrasound images before their removal, and the presence or absence of ovum is only known after collection. Therefore, we developed detection software of vacuoles using AI. (3) Determining the insertion position of sperm that does not cause rupture on the ovum: In micro-insemination, a sperm is directly injected into an ovum collected from a woman using a pipette. When injecting sperm, the oval cell membrane is usually sufficiently extended with a pipette, and then rupture is performed by piezo pulse. However, rupture may occur during the development of the membrane, in which case the insemination rate is reduced. Therefore, we quantitatively evaluate the effect of puncture position on ruptured membrane from ovum images during micro-insemination, and develop a system that can perform puncture based on the evaluation. (4) Analysis of peristalsis of the uterus: The uterus performs a movement called uterine peristalsis to transport sperm. It is known that the direction and frequency of uterine peristalsis change according to the menstrual cycle. We developed a system to evaluate peristalsis of the uterus by Cine-MRI analysis, and an evaluation system of peristaltic movement frequency by the clinical ultrasonic image analysis. Finally, I would like to consider the future role of AI in the medical and health fields.

Speaker Biography:
Yutaka Hata Professor in the Graduate School of Simulation Studies, University of Hyogo, Japan. He received the B.E. degree (Electronics) in 1984, the M.E. degree (Electrical Engineering and Electronics) in 1986 and the Ph.D. (Doctor of Engineering) in 1989 all from Himeji Institute of Technology, Japan. He is currently a Professor in the Graduate School of Simulation Studies, University of Hyogo, Japan. He is also a Guest Professor in World Premier International Research Center, Immunology Frontier Research Center, Osaka University, Japan. He spent one year in BISC Group, University of California at Berkeley from 1995 to 1996 as a visiting scholar. His research interests are in medical imaging, Bio-signal processing, human health monitoring, and fuzzy system. He received 21 awards such as the Franklin V. Taylor Best Paper Award (IEEE SMC 2009), World Automation Congress Lifetime Achievement Award (2008), Biomedical Wellness Award (SPIE Defense, Security, and Sensing 2010) and Hyogo Scientific Excellence Award (Hyogo Prefecture, 2019). He is editors including IEEE Trans on SMC-Systems. He is an IEEE Fellow.

Speaker: Chia-Hui Chang


Title: EventGo! Exploring Event Dynamics from Social-Media Posts

Date: 23 September 2020
Time: 10:50 - 11:50

One way to explore a city is to know what people do on their leisure. Looking for local events and promotions is a common need for most people during travel or moving to a new city. However, delivering such messages to the right people is still a challenge for small businesses that do not sell tickets on high-end websites. Instead, most events are usually distributed by posting on social networking sites like Facebook. To fulfill such information need, we consider information technologies to extract events from 230K Facebook fan pages to build an event database and provide a social event search service. The technologies includes web scraping and web data extraction as well as natural language processing techniques for event names and venues recognition. We show how to speed up training data preparation through locality sensitive hashing (LSH) on seed lists based on distant supervision as well as how to improve the training data quality via double-tier automatic labeling. In addition to the demonstration of event search service provided by EventGo, we also disclose statistics in the events extracted from Facebook Fan Pages and Facebook events, showing the change in the ad market.

Speaker Biography:
Dr. Chia-Hui Chang is a full Professor at National Central University, Taiwan. Dr. Chang obtained her Ph.D. in Computer Science and Information Engineering from National Taiwan University, Taiwan in 1999. Her research interests focus on Information Extraction, Web Intelligence, Data Mining, Machine Learning and System Integration. Dr. Chang has published more than 80 papers at refereed conferences and journals including WWW, PAKDD, TKDE, IEEE Intelligent Systems, etc. She served as area co-chairs for ACL 2017, NAACL 2018 and PC members for ICDE, CIKM, PAKDD, AAAI, ICTIR, etc. She is currently the president of Taiwan Association for Artificial Intelligence (TAAI) and the president of the Association for Computational Linguistics and Chinese Language Processing (ACLCLP).

Speaker: Beno K Pradekso


Title: Medis247

Date: 23 September 2020
Time: 13:00 - 14:00

HGrid is a Hadoop data engineering tool made by solusi247 for Map Reduce, Spark and Storm frameworks which has been built since 2011 to help programmers building server-side data processing applications by automatically generate codes based on visually designed workflow. The biggest challenge to build this tool was to make most of the functions, modules, libraries and even workflow schemes (nearly) compatible between frameworks and to make a multipurpose single Integrated Development Environment (IDE) for Big Data availlable in the desktop and on the cloud. The development of the HGrid library starts with the collection of functions needed, how they can be implemented in each framework and how the codes can be generated. HGrid generated codes were also benchmarked against some commercially availlable tools to ensure good performance. HGrid is also designed to be visual, robust and user friendly although it still need to be improved in user experience part. It is also designed for average programmers and analysts. Data engineering libraries has been continuosly developed to ease application development with target near zero programming at the programmers side. HGrid has been used largely at the telco operators in Indonesia, in the largest banks, government institutions, hospitals and military to build complex applications such as Data Lake, Mediation Device, Media Analytics and many others.

Speaker Biography:
Beno K Pradekso is an entrepreneur with a background in electrical engineering from TU Delft, the Netherlands. He had worked for Sisindosat Lintas Buana (Indonesian Company), SEQUENT Computer Systems (Portland, Oregon) and IBM before establishing SOLUSI247. While working on SEQUENT and IBM, Beno worked a lot on databases such as Oracle, Ingres, Informix and also the Symmetrical Multiprocessing (SMP) and non Uniform Memory Access (NUMA) architecture-based mini computers used in business. Armed with this experience in 2000 he founded SOLUSI247 which focuses on mission and business critical applications, especially in the telecommunications industry. The need to process huge and fast data made him and his team build their own GRID Engine in 2003 and were used by almost all Telco operators in Indonesia. This system was then replaced by Hadoop in 2011 which he proposed himself because it has scalability, reliability, performance and better system management. In 2014 Beno and his team believed that Hadoop would be used for a long period of time and had great benefits as a data processing engine and storage system, he encouraged the formation of the Big Data association and Data scientists in Indonesia, which until now were increasingly active and well-known. In addition to building the HGrid, Beno and his team also built a Hadoop distribution called YAVA, HGrid-Analytics for machine learning and Artificial Intelligence and several ready for use applications such as media analytics, document management systems and EHR-based HL7v4 FHIR based integrated PACS for the health care industry. All these systems were built with HGrid and YAVA. Currently Beno and his team are involved in the Indonesian government research project for National Big Data and Artificial Intelligence. While leading the solution247, the company won several awards from APICTA, LIPI, RistekDikti Government of Indonesia and also produced intellectual properties.