Details of a Researcher - Nakazawa, Jin

Papers - Nakazawa, Jin

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Protocol for an interventional study to reduce postpartum weight retention in obese mothers using the internet of things and a mobile application: a randomized controlled trial (SpringMom)

Kawasaki M., Mito A., Waguri M., Sato Y., Abe E., Shimada M., Fukuda S., Sasaki Y., Fujikawa K., Sugiyama T., Ota E., Nakazawa J., Okoshi T., Takimoto H., Honda Y., Inoue E., Hiramatsu Y., Arata N.

BMC Pregnancy and Childbirth (BMC Pregnancy and Childbirth) 21 ( 1 ) 2021.12

Background: Obese pregnant women are known to experience poorer pregnancy outcomes and are at higher risk of postnatal arteriosclerosis. Hence, weight control during and after pregnancy is important for reducing these risks. The objective of our planned randomized controlled trial is to evaluate whether the rate of change in body weight in obese women before pregnancy to 12 months postpartum would be lower with the use of an intervention consisting of Internet of Things (IoT) devices and mobile applications during pregnancy to 1 year postpartum compared to a non-intervention group. Methods: Women will be recruited during outpatient maternity checkups at four perinatal care institutions in Japan. We will recruit women at less than 30 weeks of gestation with a pre-pregnancy body mass index ≥ 25 kg/m2. The women will be randomly assigned to an intervention or non-intervention group. The intervention will involve using data (weight, body composition, activity, sleep) measured with IoT devices (weight and body composition monitor, activity, and sleep tracker), meal records, and photographs acquired using a mobile application to automatically generate advice, alongside the use of a mobile application to provide articles and videos related to obesity and pregnancy. The primary outcome will be the ratio of change in body weight (%) from pre-pregnancy to 12 months postpartum compared to before pregnancy. Discussion: This study will examine whether behavioral changes occurring during pregnancy, a period that provides a good opportunity to reexamine one's habits, lead to lifestyle improvements during the busy postpartum period. We aim to determine whether a lifestyle intervention that is initiated during pregnancy can suppress weight gain during pregnancy and encourage weight loss after delivery. Trial registration: UMIN: UMIN (University hospital Medical Information Network) 000,041,460. Resisted on 18th August 2020. https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000047278.

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Investigating the occurrence of selfie-based emotional contagion over social network

W Sasaki, Y Nishiyama, T Okoshi, J Nakazawa

Social Network Analysis and Mining 11 (1), 1-14 (Social Network Analysis and Mining) 11 ( 1 ) 8 - 8 2021.12

Research paper (scientific journal), Joint Work, ISSN 18695450

Happiness is obviously one of the most fundamental essence that affects many aspects of our lives. Past research found that happiness of one person affects that of other people. What occurs under this propagation of emotion is called “emotional contagion,” a phenomenon wherein through perception, people experience the same emotion expressed by someone when communicating with them. Although online communication is increasing due to growth of mobile computing, emotional contagion on online communication is not well studied yet. Particularly, it is not yet clear if emotional contagion among people occurs through selfie photographs posted on the social network media. We implemented “SmileWave,” the social networking system for investigating selfie-based emotional contagion. The key feature of SmileWave is detecting “smile degree” in user’s posting selfies and in reactive facial expressions when the user is viewing the posted photographs from others. Our in-the-wild user studies with 38 participants for 2 weeks revealed the occurrence of selfie-based emotional contagion over the social network, based on the results that the users’ smile degree improved (15% on average) when the user looked at posted selfie photographs.

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DEMO: Extracting Multiple Promotional Media Elements from Urban Spaces

Motoki Y., Nakayama M., Kondo S., Ishikawa E., Jinno S., Nakazawa J.

Proceedings - 2021 IEEE International Conference on Smart Computing, SMARTCOMP 2021 (Proceedings - 2021 IEEE International Conference on Smart Computing, SMARTCOMP 2021) 407 - 409 2021.08

ISSN 9781665412520

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Physical Activity Analysis of College Students During the COVID-19 Pandemic Using Smartphones

Y Nishiyama, Y Kakino, E Naka, Y Noda, S Hashiba, Y Yamada, W Sasaki, ...

arXiv preprint arXiv:2103.06515 abs/2103.06515 2021

Protocol for an interventional study to reduce postpartum weight retention in obese mothers using the internet of things and a mobile application: a randomized controlled trial …

M Kawasaki, A Mito, M Waguri, Y Sato, E Abe, M Shimada, S Fukuda, ...

BMC pregnancy and childbirth 21 (1), 1-14 2021

WellComp 2021: Fourth International Workshop on Computing for Well-Being

T Okoshi, J Nakazawa, JG Ko, F Kawsar, S Pirttikangas

Adjunct Proceedings of the 2021 ACM International Joint Conference on … (UbiComp/ISWC 2021 - Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers) 108 - 111 2021

ISSN 9781450384612

With the advancements in ubiquitous computing, ubicomp technology has deeply spread into our daily lives, including office work, home and house-keeping, health management, transportation, or even urban living environments. Furthermore, beyond the initial metrics commonly applied in computing, such as "efficiency"and "productivity", the benefits that people (users) benefit on a well-being perspective based on such ubiquitous technology has been greatly emphasized in the recent years. Through the second "WellComp"(Computing for Well-being) workshop, we will intensively discuss about the contribution of ubiquitous computing towards users' well-being that covers both physical, mental, and social wellness (and their combinations), from the viewpoints of various different layers of computing. Having strong international organization members in various ubicomp research domains, WellComp 2021 will bring together researchers and practitioners from the academia and industry to explore versatile topics related to well-being and ubiquitous computing.

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Making Cities Smarter with Regional IoT and the Force of Information

Y Chen, J Nakazawa

Journal of The Institute of Electrical Engineers of Japan 141 (1), 11-14 2021

Extracting Multiple Promotional Media Elements from Urban Spaces

Y Motoki, M Nakayama, S Kondo, E Ishikawa, S Jinno, J Nakazawa

2021 IEEE International Conference on Smart Computing (SMARTCOMP), 407-409 2021

Combining Blockchains, Smart Contracts, and Complex Sensors Management Platform for Hyper-Connected SmartCities: An IoT Data Marketplace Use Case

G Palaiokrassas, P Skoufis, O Voutyras, T Kawasaki, M Gallissot, ...

Computers 10 (10), 133 (Computers) 10 ( 10 ) 2021

In this paper, we demonstrate the multiple points of innovation when combining blockchain technology with Internet of Things (IoT) and security frameworks. The deployment and use of IoT device networks in smart city environments has produced an enormous amount of data. The fact that those data are possessed by multiple sources that use independent systems for data collection, storage, and use impedes the exploitation of their value. Blockchains, as distributed ledgers, can be used for addressing the development of a universal system for data collection and distribution. Smart contracts can be used to automate all the processes of such a network, while at the same time, blockchain and the InterPlanetary File System (IPFS) protect sensitive data through anonymity and distributed storage. An innovative and open IoT blockchain market of applications, data, and services is proposed that: (i) provides the framework upon which objects and people can exchange value in form of virtual currencies, for assets (data and services) received; (ii) defines the motivation incentives according to social and business context for humans and smart objects to interact. The specific marketplace is piloted through a cross-border trial between Santander and Fujisawa, in the context of the M-Sec project, validating thus the interoperability, efficiency, and data protection principles.

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A Comparative Study of CIPN Symptom Estimation Methods Based on Machine Learning

S Hamanaka, W Sasaki, T Okoshi, J Nakazawa, K Yagasaki, H Komatsu

ISSN 9781450384612

Chemotherapy-induced peripheral neuropathy (CIPN) is a common side effect of anticancer medicines that causes muscular weakness and falls in cancer patients. Therefore, we compared the methods for identifying and estimating the factors that cause symptoms in CIPN based on factor analysis and four different machine learning algorithms. The results of factor analysis showed that the latent factors causing CIPN can be classified into three categories: "Morning body condition", "Pain in the legs"and "Dizziness". We chose models for machine learning based on the premise of multi-task learning and built numerous machine learning models to estimate various CIPN symptoms. According to the results of the comparison studies, TabNet has the best generalization performance.

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A Methodology for Generating Systems Architectural Glimpse Statements Using the 5W1H Maxim

O Voutyras, AH Bokhari, A Tsuge, G Palaiokrassas, T Kawasaki, ...

Computers 10 (10), 131 (Computers) 10 ( 10 ) 2021

Attempts to facilitate and streamline systems architecting have resulted in a great number of reusable principles, practices, mechanisms, frameworks, and tools. Such a practice is the use of architectural viewpoints and views. However, as systems change, these practices should also evolve. The increasing scale and complexity of systems resulting from an ever-growing pool of human needs and breakthroughs may lead, in some cases, to an increased gap between the abstraction activities attempting to capture the whole of a system, and the instantiation activities that produce concrete and detailed descriptions of a system’s architecture. To address this issue, this article introduces a new notion, that of architectural glimpse statements, fundamental questions acting as the building blocks for architectural views and products. This notion can help architects ask the right questions in the right manner to create fundamental statements, the elaboration on which can lead directly to concrete architectural products. Working on top of standardized and common approaches, the article introduces a language for the creation of architectural glimpse statements using the 5W1H maxim. Based on this language, a tool and guidelines are also provided to facilitate the usage of glimpses. Finally, the overall methodology is demonstrated in two case studies.

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Search Wandering Score: Predicting Timings of Online Shopping based on Wandering in User’s Web Search Queries

K Tsubouchi, W Sasaki, T Okoshi, J Nakazawa

2020 IEEE International Conference on Big Data (Big Data), 1681-1688 (Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020) 1681 - 1688 2020.12

Joint Work, ISSN 9781728162515

Many researchers and companies have engaged in estimating users' interests so that an online shopping system can tell what he/she wants now. This paper tackles the next challenge in online shopping, i.e., predicting the times that users go shopping online. To predict the timing of online shopping, we focus on wandering behavior in web search activities and propose a search wandering score (SWS). Online shopping behavior can be categorized into three states: wandering shop-ping, focused shopping, and others. Wandering shopping is a state in which users make purchases in high SWS situations; focused shopping is a state in which users buy things in low SWS situations. Unlike previous studies, our work is based on an analysis of large-scale data containing shopping and search logs produced by approximately 200,000 users of a real web portal site for over a year. The results of an extensive evaluation show that our methodology can predict user's future shopping behavior types with 86% accuracy. This research is the first step towards understanding the relationship between users' mental states and their online shopping behavior.

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A mobility-aware pub/sub architecture for short-lived data in smart cities: Poster abstract

Kawasaki T, Okoshi T, Nakazawa J

SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems (SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems) 645 - 646 2020.11

Research paper (international conference proceedings), Joint Work, ISSN 9781450375900

With an increase in the number of IoT devices, the amount of data transferred between the devices and applications is becoming huge. To ensure that these data are properly used, a new IoT data transfer system is needed to better control the timing and the content of the data to transmit. One of the promising means for such a large-scale city-data transfer is the publish/subscribe messaging model, which can separate data senders and receivers so that they can run independently. However, existing pub/sub systems cannot cope well with the mobility of senders and receivers, thereby limiting its applicability to real-world uses. In concrete, they don't consider Time-to-live (TTL) of data. Users can use the data anytime and within TTL of it. IoT platforms can improve controlling data transmission by used to this characteristic. In this paper, we focus on the Time-to-Live of data (data-TTL). Our system can control data transmission by using data-TTL and combine with the user's movement information. We have constructed a system, that is capable of control data transmission for mobility aware.

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Behavification: bypassing human's attentional and cognitive systems for automated behavior change

T Okoshi, W Sasaki, J Nakazawa

Adjunct Proceedings of the 2020 ACM International Joint Conference on … (UbiComp/ISWC 2020 Adjunct - Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers) 692 - 695 2020.09

Research paper (international conference proceedings), Joint Work, ISSN 9781450380768

To achieve behavior change in our lives for several specific goals towards better well-being, various types intervention systems have been proposed. However, because of humans' bounded rationality, such explicit information provision for the users do not always reach their attention, thus fails the needed information for the behavior change. This paper propose new concepts "behavification"with which information system bypasses the user's cognitive, attentional and perceptive system by not notifying him/her and modifies the system behavior to directly influence the user's behavior under user's explicit advance permission. Through a series of group discussion and survey sessions with 19 participants, we investigated how the potential behavification users see its appropriateness to different application categories, killer application scenarios, and design guidelines and rationales for a behavification system to support such scenarios. We found total 58 application scenarios and propose 3 guidelines "advance user permission", "multi-modality"and "integration with real-world action/actuation".

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WellComp 2020: third international workshop on computing for well-being

T Okoshi, J Nakazawa, JG Ko, F Kawsar, S Pirttikangas

Research paper (international conference proceedings), Joint Work, ISSN 9781450380768

With the advancements in ubiquitous computing, ubicomp technology has deeply spread into our daily lives, including office work, home and house-keeping, health management, transportation, or even urban living environments. Furthermore, beyond the initial metric of computing, such as "efficiency"and "productivity", the benefits that people (users) benefit on a well-being perspective based on such ubiquitous technology has been greatly paid attention in the recent years. In our third "WellComp"(Computing for Well-being) workshop, we intensively discuss about the contribution of ubiquitous computing towards users' well-being that covers physical, mental, and social wellness (and their combinations), from the viewpoints of various different layers of computing. After big success of two previous workshops WellComp 2018 and 2019, with strong international organization members in various ubicomp research domains, WellComp 2020 will bring together researchers and practitioners from the academia and industry to explore versatile topics related to well-being and ubiquitous computing.

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Using iOS for inconspicuous data collection: A real-world assessment

Y Nishiyama, D Ferreira, W Sasaki, T Okoshi, J Nakazawa, AK Dey, ...

Research paper (international conference proceedings), Joint Work, ISSN 9781450380768

Mobile Crowd Sensing (MCS) is a method for collecting multiple sensor data from distributed mobile devices for understanding social and behavioral phenomena. The method requires collecting the sensor data 24/7, ideally inconspicuously to minimize bias. Although several MCS tools for collecting the sensor data from an off-the-shelf smartphone are proposed and evaluated under controlled conditions as a benchmark, the performance in a practical sensing study condition is scarce, especially on iOS. In this paper, we assess the data collection quality of AWARE iOS, installed on off-the-shelf iOS smartphones with 9 participants for a week. Our analysis shows that more than 97% of sensor data, provided by hardware sensors (i.e., accelerometer, location, and pedometer sensor), is successfully collected in real-world conditions, unless a user explicitly quits our data collection application.

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Estimating symptoms caused by CIPN using mobile and wearable devices

W Sasaki, R Ozawa, T Okoshi, J Nakazawa, K Yagasaki, H Komatsu

Research paper (international conference proceedings), Joint Work, ISSN 9781450380768

Chemotherapy-induced peripheral neuropathy (CIPN) is a common side effect of anticancer drugs that causes muscle weakness in the cancer patients, causing them to fall. Therefore, we constructed "FD-AWARE", a system to understand the users' fall context and users' CIPN symptoms as the first step in preventing these falls. This system can collect the various sensor data from the iPhone and the Apple Watch, self-reported fall information data, self-reported user status data of CIPN symptoms, and their physical condition. We conducted a 2-week in-the-wild experiment with 8 patients who were actually suffering from CIPN. We constructed the machine learning models for estimating the users' status of CIPN symptoms and successfully achieved high accuracy of performance for several estimating models.

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SmileCityReport: Emotion-aware Participatory Sensing for Smart Cities with Double-sided Photo Shooting

W Sasaki, Y Eigen, A Medela, A Litke, VC Núnez, T Okoshi, J Nakazawa

2020 IEEE International Conference on Pervasive Computing and Communications … (2020 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2020) 1 - 6 2020.03

Research paper (international conference proceedings), Joint Work, ISSN 9781728147161

Collection of information of the events taking place in local neighborhoods along with the emotional statuses of the people involved can enable us to realize an 'affective smart city map', with which, for example, the local authority can review the measures adopted for the local areas and whether their these measure have actually contributed to the quality of life (QoL) and well-being of the people. To realize such an information system having easy-deployability, real-time and secure protection of user's sensitive data, we propose SmileCityReport, a smartphone app-based participatory sensing that can easily capture both the city events and the reporter's emotion-related status based on a novel technique that uses two cameras simultaneously. For our evaluation, we evaluated 15 users over one week and confirmed that the proposed methodology contributes to more activity and (estimated) more positive emotional status of the users, and also that the emotion-related facial expression values constitute valuable data that can be publicly shared.

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SenSys '20: The 18th ACM Conference on Embedded Networked Sensor Systems, Virtual Event, Japan, November 16-19, 2020

Jin Nakazawa, Polly Huang

SenSys 2020

ISSN 978-1-4503-7590-0

Multi-layered Security Technologies to Ensure Hyper Connected Smart Cities with Blockchain, BigData, Cloud and IoT

J Nakazawa, AM TST

IEICE Technical Report; IEICE Tech. Rep. 2020

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