Nontrivial Rules Research Articles

The Process of Identifying Automobile Joint Failures during the Operation Phase: Data Analytics Based on Association Rules

The increasing complexity of vehicle design, the use of new engine types and fuels, and the increasing intelligence of automobiles are making it increasingly difficult to ensure trouble-free operation. Finding faulty parts quickly and accurately is becoming increasingly difficult, as the diagnostic process requires analyzing a great amount of information. Therefore, we propose an approach based on association rules, a machine learning technique, to simplify the defect detection process. To facilitate its use in a real repair company environment, we have developed a web service that allows a repairman to simultaneously identify nodes with a high probability of failure. We have described the structure and working principles of the developed web service, as well as the procedure for its application, which resulted in the discovery of several useful non-trivial rules. We have presented several rules resulting from the use of this interactive tool, which allow repairers to detect possible defects in the relevant components, during the diagnostic process, quickly and easily. These rules are also well supported and can be used by procurement departments to make tactical decisions when selecting the most promising suppliers and manufacturers. The methodology developed allows the evaluation of the effectiveness of changes in the design and technology for the manufacture and operation of individual vehicle components, analyzing the change in the composition of parts combinations over time.

Understanding of social behaviour in human collective motions with non-trivial rule of control

The coordination and movement of people in large crowds, during sports games or when socialising, seems readily explicable. Sometimes this occurs according to specific rules or instructions such as in a sport or game, at other times the motivations for movement may be more focused around an individual's needs or fears. Over the last decade, the computational ability to identify and track a given individual in video footage has increased. The conventional methods of how data is gathered and interpreted in biology rely on fitting statistical results to particular models or hypotheses. However, data from tracking movements in social groups or team sports are so complex as they cannot easily analyse the vast amounts of information and highly varied patterns. The author is an expert in human behaviour and machine learning who is based at the Graduate School of Informatics at Nagoya University. His challenge is to bridge the gap between rule-based theoretical modelling and data-driven modelling. He is employing machine learning techniques to attempt to solve this problem, as a visiting scientist in RIKEN Center for Advanced Intelligence Project.

Committee Scoring Rules

Committee scoring voting rules are multiwinner analogues of positional scoring rules, which constitute an important subclass of single-winner voting rules. We identify several natural subclasses of committee scoring rules, namely, weakly separable, representation-focused, top- k -counting, OWA-based, and decomposable rules. We characterize SNTV, Bloc, and k -Approval Chamberlin--Courant as the only nontrivial rules in pairwise intersections of these classes. We provide some axiomatic characterizations for these classes, where monotonicity properties appear to be especially useful. The class of decomposable rules is new to the literature. We show that it strictly contains the class of OWA-based rules and describe some of the applications of decomposable rules.

What Do Multiwinner Voting Rules Do? An Experiment Over the Two-Dimensional Euclidean Domain

We visualize aggregate outputs of popular multiwinner voting rules — SNTV, STV, Bloc, k-Borda, Monroe, Chamberlin–Courant, and PAV — for elections generated according to the two-dimensional Euclidean model. We consider three applications of multiwinner voting, namely, parliamentary elections, portfolio/movie selection, and shortlisting, and use our results to understand which of our rules seem to be best suited for each application. In particular, we show that STV (one of the few nontrivial rules used in real high-stake elections) exhibits excellent performance, whereas the Bloc rule (also often used in practice) performs poorly.

SQL-based discovery of exact and approximate functional dependencies

Students in a typical database course are introduced to theoretical design from a functional dependency standpoint. Functional dependencies are rules of the form X→Y, where X and Y are attributes of a relation r(R). Those rules express the potential one-to-one, and many-to-one relationships among the atributes of R. Unfortunately finding the non-trivial rules X→Y from an existing arbitrary relation is a hard problem. We present an extension of the SQL-based algorithm of Bell and Brockhausen [1] to explore a relation and find its exact and approximate functional dependencies. We use the g3 measure of Kivinen and Mannila to express the degree of approximation of a dependency. This application could be used either as an example or a project in an advanced database course.

Is Corporate Law Trivial?: A Political and Economic Analysis

On its face, state corporate law contains a mix of mandatory and default rules. I develop the triviality that the appearance of a mandatory core to state corporate law is a mirage, and that state corporate law is trivial, in the sense that it lets companies -- managers and investors together -- establish any set of governance rules they would reasonably want. Rules that appear mandatory may be trivial for four reasons. First, some mandatory rules would be universally adopted if people thought about them (market mimicking rules). Second, some rules can be avoided by advance planning, including choice of capital structure and state of incorporation. Third, some mandatory rules are unimportant -- they cover situations that occur rarely or matter little. Finally, as circumstances change, some rules that used to be market mimicking, avoidable, or unimportant may matter, but precisely because these rules matter, they will soon be changed. The political forces that led to the trivialization of corporate law will see to that. Many apparently mandatory corporate law rules are trivial in one of these senses. Moreover, proving that nontrivial rules exist is hard. It is not trivial to disprove the extreme null hypothesis that all of state corporate law is trivial.