arXiv subjects

Bin Hao

Publications and source records attributed to Bin Hao.

3 recordsLinked to original sources

arXiv2023

Production of Martian fiber by in-situ resource utilization strategy

Many countries and commercial organizations have shown great interest in constructing Martian base. In-situ resource utilization (ISRU) provides a cost-effective way to achieve this ambitious goal. In this paper, we proposed to use Martian soil simulant to produce fiber to satisfy material requirement for the construction of Martian base. The composition, melting behavior and fiber forming process of soil simulant was studied, and continuous fiber with a maximum strength of 1320 MPa was obtained on a spinning facility. The findings of this study demonstrate the feasibility of ISRU to prepare Martian fiber from the soil on the Mars, offering a new way to get key materials for the construction of Martian base.

physics.pop-ph↗

arXiv2021

A Large-Scale Rich Context Query and Recommendation Dataset in Online Knowledge-Sharing

Data plays a vital role in machine learning studies. In the research of recommendation, both user behaviors and side information are helpful to model users. So, large-scale real scenario datasets with abundant user behaviors will contribute a lot. However, it is not easy to get such datasets as most of them are only hold and protected by companies. In this paper, a new large-scale dataset collected from a knowledge-sharing platform is presented, which is composed of around 100M interactions collected within 10 days, 798K users, 165K questions, 554K answers, 240K authors, 70K topics, and more than 501K user query keywords. There are also descriptions of users, answers, questions, authors, and topics, which are anonymous. Note that each user's latest query keywords have not been included in previous open datasets, which reveal users' explicit information needs. We characterize the dataset and demonstrate its potential applications for recommendation study. Multiple experiments show the dataset can be used to evaluate algorithms in general top-N recommendation, sequential recommendation, and context-aware recommendation. This dataset can also be used to integrate search and recommendation and recommendation with negative feedback. Besides, tasks beyond recommendation, such as user gender prediction, most valuable answerer identification, and high-quality answer recognition, can also use this dataset. To the best of our knowledge, this is the largest real-world interaction dataset for personalized recommendation.

cs.IR↗

arXiv2019

Trick or Heat? Manipulating Critical Temperature-Based Control Systems Using Rectification Attacks

Temperature sensing and control systems are widely used in the closed-loop control of critical processes such as maintaining the thermal stability of patients, or in alarm systems for detecting temperature-related hazards. However, the security of these systems has yet to be completely explored, leaving potential attack surfaces that can be exploited to take control over critical systems. In this paper we investigate the reliability of temperature-based control systems from a security and safety perspective. We show how unexpected consequences and safety risks can be induced by physical-level attacks on analog temperature sensing components. For instance, we demonstrate that an adversary could remotely manipulate the temperature sensor measurements of an infant incubator to cause potential safety issues, without tampering with the victim system or triggering automatic temperature alarms. This attack exploits the unintended rectification effect that can be induced in operational and instrumentation amplifiers to control the sensor output, tricking the internal control loop of the victim system to heat up or cool down. Furthermore, we show how the exploit of this hardware-level vulnerability could affect different classes of analog sensors that share similar signal conditioning processes. Our experimental results indicate that conventional defenses commonly deployed in these systems are not sufficient to mitigate the threat, so we propose a prototype design of a low-cost anomaly detector for critical applications to ensure the integrity of temperature sensor signals.

cs.CR↗