Journal of the American Statistical Association: William S. Cleveland, Marylyn E. McGill and Robert McGill, “The shape parameter for a two variable graph” 83 (1988) 289–300

One-class classification (OCC) algorithms aim to build classification models when the negative class is either absent, poorly sampled or not well defined. This unique situation constrains the learning of efficient classifiers by defining class boundary just with the knowledge of positive class. The OCC problem has been considered and applied under many research themes, such as outlier/ novelty detection and concept learning. In this paper, we present a unified view of the general problem of OCC by presenting a taxonomy of study for OCC problems, which is based on the availability of training data, algorithms used and the application domains applied. We further delve into each of the categories of the proposed taxonomy and present a comprehensive literature review of the OCC algorithms, techniques and methodologies with a focus on their significance, limitations and applications. We conclude our paper by discussing some open research problems in the field of OCC and present our vision for future research.

/pdf/one-class-classification-taxonomy-of-study-and-review-of-57u6uqiu0x.pdf

One-class classification: taxonomy of study and review of techniques

Kinetic energy harvesting technologies for applications in land transportation: A comprehensive review

Sustainability has become an important initiative discussed and undertaken, not only by private buildings, but also by public buildings which both dealing with residential, office, commercial as well as hospital. Sustainable building is the practice of designing, constructing, operating, maintaining, and removing buildings in ways that conserve natural resources and reduce pollution. Rating systems provide effective framework for assessing building environmental performance and they measure a building's sustainability by applying a set of criteria organized in different categories. A good Green Building Rating System (GBRS) should cover key indicators reflecting a building's characteristics and keep their performance in balance. This paper proposed a knowledge-based expert system as a tool to assess the performance level of a green building based on assessment factors of green building rating systems. Analytic Hierarchy Process (AHP) and fuzzy logic is adopted in order to develop the knowledge-based expert system. The data for this research collected from the experts in the field via pair-wise and Likert-based questionnaires. Using AHP, the most important parameters of rating systems according to their weights selected to be incorporated in the Fuzzy Inferences System (FIS) of fuzzy logic model. The fuzzy rules (knowledge) discovered from the collected data for FIS to assess the performance level of the green buildings from the Environmental, Social and Economical perspectives denoted as SE2. The outcome of this research is accordingly a performance assessment tool that analyzes the effect of factors in developing the sustainable building.

A knowledge-based expert system for assessing the performance level of green buildings

One-class classification (OCC) algorithms aim to build classification models when the negative class is either absent, poorly sampled or not well defined. This unique situation constrains the learning of efficient classifiers by defining class boundary just with the knowledge of positive class. The OCC problem has been considered and applied under many research themes, such as outlier/novelty detection and concept learning. In this paper we present a unified view of the general problem of OCC by presenting a taxonomy of study for OCC problems, which is based on the availability of training data, algorithms used and the application domains applied. We further delve into each of the categories of the proposed taxonomy and present a comprehensive literature review of the OCC algorithms, techniques and methodologies with a focus on their significance, limitations and applications. We conclude our paper by discussing some open research problems in the field of OCC and present our vision for future research.

/pdf/one-class-classification-taxonomy-of-study-and-review-of-1pdpl7k7e7.pdf

One-Class Classification: Taxonomy of Study and Review of Techniques

Regenerative active suspension system with residual energy for in-wheel motor driven electric vehicle

A novel robust event‐triggered fault tolerant automatic steering control approach of autonomous land vehicles under in‐vehicle network delay

The current investigations primarily focus on using advanced suspensions to overcome the tradeoff design of ride comfort and handling performance for mining vehicles. It is generally realized by adjusting spring stiffness or damping parameters through active control methods. However, some drawbacks regarding control complexity and uncertain reliability are inevitable for these advanced suspensions. Herein, a novel passive hydraulically interconnected suspension (HIS) system is proposed to achieve an improved ride-handling compromise of mining vehicles. A lumped-mass vehicle model involved with a mechanical–hydraulic coupled system is developed by applying the free-body diagram method. The transfer matrix method is used to derive the impedance of the hydraulic system, and the impedance is integrated to form the equation of motions for a mechanical–hydraulic coupled system. The modal analysis method is employed to obtain the free vibration transmissibilities and force vibration responses under different road excitations. A series of frequency characteristic analyses are presented to evaluate the isolation vibration performance between the mining vehicles with the proposed HIS and the conventional suspension. The analysis results prove that the proposed HIS system can effectively suppress the pitch motion of sprung mass to guarantee the handling performance, and favorably provide soft bounce stiffness to improve the ride comfort. The distribution of dynamic forces between the front and rear wheels is more reasonable, and the vibration decay rate of sprung mass is increased effectively. This research proposes a new suspension design method that can achieve the enhanced cooperative control of bounce and pitch motion modes to improve the ride comfort and handling performance of mining vehicles as an effective passive suspension system.

/pdf/vibration-performance-analysis-of-a-mining-vehicle-with-ur7h8popyx.pdf

Vibration Performance Analysis of a Mining Vehicle with Bounce and Pitch Tuned Hydraulically Interconnected Suspension

A frequency-based modeling approach has been developed for the vehicle fitted with Hydraulically Interconnected Suspension (HIS) system. This frequency-based model has fewer degrees of freedom (DOF) than the reference time-based model. Several physical parameters of HIS system are selected to analytically investigate their effects on several indicators of vehicle roll, pitch and bounce modes, such as roll and pitch angular acceleration, vertical acceleration, and tire ground force. The HIS system parameters are also coordinately tuned and optimized to meet the ride comfort requirement. The full vehicle drop test is conducted for the experimental validation. The analytical results of the proposed model have a good agreement with the measurements.

/pdf/frequency-based-modeling-of-a-vehicle-fitted-with-roll-plane-50rkw9ek6k.pdf

Jie Zhang

Papers

Regenerative active suspension system with residual energy for in-wheel motor driven electric vehicle

A novel robust event‐triggered fault tolerant automatic steering control approach of autonomous land vehicles under in‐vehicle network delay

Vibration Performance Analysis of a Mining Vehicle with Bounce and Pitch Tuned Hydraulically Interconnected Suspension

Frequency-Based Modeling of a Vehicle Fitted With Roll-Plane Hydraulically Interconnected Suspension for Ride Comfort and Experimental Validation

Robust adaptive backstepping sliding mode control for motion mode decoupling of two‐axle vehicles with active kinetic dynamic suspension systems