A Rawlsian algorithm for autonomous vehicles

Autonomous vehicles must be programmed with procedures for dealing with trolley-style dilemmas where actions result in harm to either pedestrians or passengers. This paper outlines a Rawlsian algorithm as an alternative to the Utilitarian solution. The algorithm will gather the vehicle’s estimation of probability of survival for each person in each action, then calculate which action a self-interested person would agree to if he or she were in an original bargaining position of fairness. I will employ Rawls’ assumption that the Maximin procedure is what self-interested agents would use from an original position, and then show how the Maximin procedure can be operationalized to produce unique outputs over probabilities of survival.     

Experimental study on transient behavior of semi-open two-phase thermosyphon

An experimental system was set up to measure the temperature, pressure, heat transfer rate and mass flow rate in a semi-open two-phase thermosyphon. The behaviors of a semi-open two-phase thermosyphon during startup, shutdown and lack of water were studied to get complete understanding of its thermal characteristics. The variation of wall temperature, heat-exchange condition and pressure fluctuations of semi-open two-phase thermosyphons showed that the startup of SOTPT needs about 60～70 min; the startup speed of SOTPT is determined by the startup speed of the condensation section; the average pressure in the heat pipe is equal to the environmental pressure usually; the shutdown of SOTPT needs about 30～50 min; a semi-open two-phase thermosyphon has good response to lack of water accident.     

Personal knowledge management: supporting individual knowledge worker performance

Based on an exploratory study of the work and learning processes of highly skilled and experienced knowledge workers, this paper explores an alternative perspective to knowledge management, one that focuses on how individual workers apply knowledge processes to support their day-to-day work activities – broadly characterized as problem solving – and learning practices. Developing the concept of Personal Knowledge Management, the paper presents an emergent model that links distinctive types of problem solving activities with specific cognitive, information, social and learning competencies, supported by an individual, social and organizational enablers.     

Learning to Rank

New general purpose ranking functions are discovered using genetic programming. The TREC WSJ collection was chosen as a training set. A baseline comparison function was chosen as the best of inner product, probability, cosine, and Okapi BM25. An elitist genetic algorithm with a population size 100 was run 13 times for 100 generations and the best performing algorithms chosen from these. The best learned functions, when evaluated against the best baseline function (BM25), demonstrate some significant performance differences, with improvements in mean average precision as high as 32% observed on one TREC collection not used in training. In no test is BM25 shown to significantly outperform the best learned function.     

A language model-based framework for multi-publisher content-based recommender systems

The rapid growth of the Web has increased the difficulty of finding the information that can address the users’ information needs. A number of recommendation approaches have been developed to tackle this problem. The increase in the number of data providers has necessitated the development of multi-publisher recommender systems; systems that include more than one item/data provider. In such environments, preserving the privacy of both publishers and subscribers is a key and challenging point. In this paper, we propose a multi-publisher framework for recommender systems based on a client–server architecture, which preserves the privacy of both data providers and subscribers. We develop our framework as a content-based filtering system using the statistical language modeling framework. We also introduce AUTO, a simple yet effective threshold optimization algorithm, to find a dissemination threshold for making acceptance and rejection decisions for new published documents. We further propose a language model sketching technique to reduce the network traffic between servers and clients in the proposed framework. Extensive experiments using the TREC-9 Filtering Track and the CLEF 2008-09 INFILE Track collections indicate the effectiveness of the proposed models in both single- and multi-publisher settings.