Výsledky vyhledávání - "Arai, Ismail"

Report

Bus Ridership Prediction with Time Section, Weather, and Ridership Trend Aware Multiple LSTM

Autor: Yamamura, Tatsuya, Arai, Ismail, Kakiuchi, Masatoshi, Endo, Arata, Fujikawa, Kazutoshi

Public transportation has been essential in people's lives in recent years. Bus ridership is a factor in people's choice to board the bus. Therefore, from the perspective of improving service quality, it is important to inform passengers who have not

Externí odkaz: http://arxiv.org/abs/2304.08233

Zobrazit plný text záznamu

Report

Feasibility Study of Magnetism-based Indoor Positioning Methods in an Incineration Plant

Autor: Okumura, Rei, Arai, Ismail, Yutaro, Atarashi, Kaoru, Kawabata, Fujikawa, Kazutoshi

In an incineration plant, remote operation from a centralized control room is now possible, but inspection and cleaning of equipment still require a worker to visit the site. When the plant owner reduces the number of workers due to operation costs,

Externí odkaz: http://arxiv.org/abs/2203.12952

Zobrazit plný text záznamu

Report

The Effect of COVID-19 on the Transit System in Two Regions: Japan and USA

Autor: Arai, Ismail, El-Tawab, Samy, Salman, Ahmad, Elnoshokaty, Ahmed

The communication revolution that happened in the last ten years has increased the use of technology in the transportation world. Intelligent Transportation Systems wish to predict how many buses are needed in a transit system. With the pandemic effe

Externí odkaz: http://arxiv.org/abs/2112.01198

Zobrazit plný text záznamu

Report

Leveraging IoT and Weather Conditions to Estimate the Riders Waiting for the Bus Transit on Campus

Autor: Arai, Ismail, Elnoshokaty, Ahmed, El-Tawab, Samy

The communication technology revolution in this era has increased the use of smartphones in the world of transportation. In this paper, we propose to leverage IoT device data, capturing passengers' smartphones' Wi-Fi data in conjunction with weather

Externí odkaz: http://arxiv.org/abs/2102.01364

Zobrazit plný text záznamu

Report

DataLoc+: A Data Augmentation Technique for Machine Learning in Room-Level Indoor Localization

Autor: Hilal, Amr E, Arai, Ismail, El-Tawab, Samy

Indoor localization has been a hot area of research over the past two decades. Since its advent, it has been steadily utilizing the emerging technologies to improve accuracy, and machine learning has been at the heart of that. Machine learning has be

Externí odkaz: http://arxiv.org/abs/2101.10833

Zobrazit plný text záznamu

Report

Divider: Delay-Time Based Sender Identification in Automotive Networks

Autor: Ohira, Shuji, Desta, Araya Kibrom, Kitagawa, Tomoya, Arai, Ismail, Fujikawa, Kazutoshi

Controller Area Network (CAN) is one of the in-vehicle network protocols that is used to communicate among Electronic Control Units (ECUs) and has been de-facto standard. CAN is simple and has several vulnerabilities such as unable to distinguish spo

Externí odkaz: http://arxiv.org/abs/2008.10941

Zobrazit plný text záznamu