Virtual Track: Applications and Challenges of the RFID System on Roads

The RFID System on Roads (RSR), which includes RFID tags deployed on roads and RFID readers installed on vehicles, is an essential platform for future transportation systems. It can provide unique features that are missing from the current systems, including lane level position, road traffic control information, vehicle distance estimation, real time driving behavior analysis, and so on. Based on these features, several novel vehicular applications can be implemented, which can significantly improve the transportation safety and efficiency. Specifically, the proposed applications on RSR include Assisted Navigation Systems, Electrical Traffic Control, Unmanned Patrol Systems, Vehicle Distance Estimation, Parking Assistant System, Route Tracing and Access Control, Unmanned Ground Vehicles. We also investigate the corresponding engineering/system and research challenges for implementing RSR and its applications in this article

A game theoretic analysis on block withholding attacks using the zero-determinant strategy

In Bitcoin's incentive system that supports open mining pools, block withholding attacks incur huge security threats. In this paper, we investigate the mutual attacks among pools as this determines the macroscopic utility of the whole distributed system. Existing studies on pools' interactive attacks usually employ the conventional game theory, where the strategies of the players are considered pure and equal, neglecting the existence of powerful strategies and the corresponding favorable game results. In this study, we take advantage of the Zero-Determinant (ZD) strategy to analyze the block withholding attack between any two pools, where the ZD adopter has the unilateral control on the expected payoffs of its opponent and itself. In this case, we are faced with the following questions: who can adopt the ZD strategy? individually or simultaneously? what can the ZD player achieve? In order to answer these questions, we derive the conditions under which two pools can individually or simultaneously employ the ZD strategy and demonstrate the effectiveness. To the best of our knowledge, we are the first to use the ZD strategy to analyze the block withholding attack among pools

Fabrication error Indexed eXamples and Solutions: FIXS

The major goal of the Regional/National Bridge Fabrication Error Expert System research project is to develop a sharable and well reasoned bridge fabrication error repair database which can be used by several state: DOTs within a geographical,. region. This report focuses on the enhancement of the knowledge base and improvement of the system performance based on the initial work of Fabrication error Indexed examples and Solutions (FIXS). FIXS is a knowledge-based system in the domain of steel bridge fabrication errors using both rule-based reasoning and casebased reasoning. To expand the knowledge base to cover errors experienced by multiple DOTs and to improve the system effectiveness, 38 new cases were solicited from the North Central States Consortium and the Repair Database Task Group of the AASHTONSBA Steel Bridge Collaboration. The new cases, along with the existing 120 rule solutions and 112 case solutions in the knowledge base, were reviewed by the Task Group members. The sketches and instructions summarized from actual cases and the comments obtained from the Task Group members were implemented in the ,, software to provide graphical and instructive information for case solutions. In addition, generic problems and corrections were also collected and implemented in the software as a tutorial tool for common fabrication errors. To improve the accuracy of similar case retrieval, the case-based reasoning shell SCBR was revised by introducing continuous feature evaluation for numeric features, replacing the simple match approach in the first version of FIXS. The explanation facility was also improved

Social Big Data: Mining, Applications, and Beyond

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Explainable History Distillation by Marked Temporal Point Process

Explainability of machine learning models is mandatory when researchers introduce these commonly believed black boxes to real-world tasks, especially high-stakes ones. In this paper, we build a machine learning system to automatically generate explanations of happened events from history by \gls{ca} based on the \acrfull{tpp}. Specifically, we propose a new task called \acrfull{ehd}. This task requires a model to distill as few events as possible from observed history. The target is that the event distribution conditioned on left events predicts the observed future noticeably worse. We then regard distilled events as the explanation for the future. To efficiently solve \acrshort{ehd}, we rewrite the task into a \gls{01ip} and directly estimate the solution to the program by a model called \acrfull{model}. This work fills the gap between our task and existing works, which only spot the difference between factual and counterfactual worlds after applying a predefined modification to the environment. Experiment results on Retweet and StackOverflow datasets prove that \acrshort{model} significantly outperforms other \acrshort{ehd} baselines and can reveal the rationale underpinning real-world processes

The influence of minimum wage regulation on labor income share and overwork: evidence from China

Minimum Wage Regulation (MWR) can raise wage rate, but its relation with labor income share is in controversy. We explore the influence of raising wage rate on labor income share and overwork in China. Panel data regressions are taken mainly based on China’s Industrial Enterprise Database and the International Labor Organization Database. Our findings show that raising wage rate can increase labor income share without leading to overwork. Factors that may significantly increase overwork are a higher proportion of male workers, a larger income gap and a lower percapita income. We point out that the neoclassical explanation for labor income share is not persuasive. We support policies of raising wage rate and believe MWR is an effective measure to increase labor income share