Category Learning in Rhesus Monkeys: A Study of the Shepard, Hovland, and Jenkins (1961) Tasks.

In influential research, R. N. Shepard, C. I. Hovland, and H. M. Jenkins (1961) surveyed humans' categorization abilities using tasks based in rules, exclusive-or (XOR) relations, and exemplar memorization. Humans' performance was poorly predicted by cue-conditioning or stimulus-generalization theories, causing Shepard et al. to describe it in terms of hypothesis selection and rule application that were possibly supported by verbal mediation. The authors of the current article surveyed monkeys' categorization abilities similarly. Monkeys, like humans, found category tasks with a single relevant dimension the easiest and perceptually chaotic tasks requiring exemplar memorization the most difficult. Monkeys, unlike humans, found tasks based in XOR relations very difficult. The authors discuss the character and basis of the species difference in categorization and consider whether monkeys are the generalization-based cognitive system that humans are not. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Predicting Organizational Success within a Project-Based Joint Venture Alliance

Project-based joint ventures (a special type of alliance) are an often-used method to form competitive organizational structures in the global market; they allow participants to quickly assemble project-needed assets on a short-term basis without substantial investment. However, published discussions of joint ventures describe mixed success and focus on factors that affect the ventures after they are formed. This paper exposes factors, which may be observed at joint venture inception, that are predictive of organizational success within the joint venture. The survey research of U.S. architecture/engineering/construction (A/E/C) firms indicates that smaller partners in a joint venture experience more market growth and are more successful. Also, a firm with strength in legitimacy (client trust) is more likely to gain in short-term income but will likely suffer some long-term market loss in comparison to its less-legitimized partners. It is further concluded that culture match among partners plays a significant role in ensuring profitable joint venture returns.     

Optimal classification methods for mapping agricultural tillage practices

The classification of agricultural tillage systems has proven challenging in the past using traditional classification methods due to the similarity of spectral reflectance signatures of soils and senescent crop residues. In this study, five classification methods were examined to determine the most suitable classification algorithm for the identification of no-till (NT) and traditional tillage (TT) cropping methods: minimum distance (MD), Mahalanobis distance, Maximum Likelihood (ML), spectral angle mapping (SAM), and the cosine of the angle concept (CAC). A Landsat ETM+ image acquired over southern Michigan and northern Indiana was used to test these classification methods. Each classification method was validated with 293 ground truth sampling locations collected commensurate with the satellite overpass. Classification accuracy was then assessed using error matrix analysis, Kappa statistics, and tests for statistical significance. The results indicate that of the classification routines examined, the two spectral angle methods were superior to the others. The cosine of the angle concept algorithm outperformed all the other classification routines for tillage practice identification and mapping, yielding an overall accuracy of 97.2% (Kappa=0.959).     

Towards Pseudonymous e-Commerce

The lack of privacy is one of the main reasons that limits trust in e-commerce. Current e-commerce practice enforces a customer to disclose her identity to the e-shop and the use of credit cards makes it straightforward for an e-shop to know the real identity of its customers. Although there are some payment systems based on untraceable tokens, they are not as widely used as credit cards. Furthermore, even without buying anything, a customer is already disclosing some information about who or where she may be by just connecting to the e-shop's web server and leaving behind an IP-address. In this paper, we present novel components that enable secure pseudonymous e-commerce. On the one hand, these components allow a customer to browse through an e-shop, select goods, and pay the goods with her credit card such that neither the e-shop operator nor the credit card issuer nor an eavesdropper is able to get any information about the customer's identity. On the other hand, it is guaranteed that none of the involved parties is able to act dishonestly during the credit card payment. Such a system could greatly enhance trust in e-commerce since it overcomes the customers' privacy concerns.     

A Suite of Tools for Debugging Distributed Autonomous Systems

This paper describes a set of tools that enables developers to log and analyze the run-time behavior of distributed control systems. A feature of the tools is that they can be applied to distributed systems. The logging tools enable developers to instrument C or C++ programs so that data indicating state changes can be logged automatically in a variety of formats. In particular, run-time data from distributed systems can be synchronized into a single relational database. Tools are also provided for visualizing the logged data. Analysis to verify correct program behavior is done using a new interval logic that is described in this paper. The logic enables system engineers to express temporal specifications for the autonomous control program that are then checked against the logged data. The data logging, visualization, and interval logic analysis tools are all fully implemented. Results are given from a NASA distributed autonomous control system application.     

Identity fraud: the stealth threat to UK plc

Identity (ID) fraud is one of the fastest growing criminal trends in the UK and costs the British economy around £1.3 billion per year according to the Home Office. It is not just financial loss that victims suffer: it can take up to 300 hours of effort to regain their credibility with banks and credit reference agencies.     

Working Together Apart? Building a Knowledge‐Sharing Culture for Global Virtual Teams

A new impetus for greater knowledge‐sharing among team members needs to be emphasized due to the emergence of a significant new form of working known as ‘global virtual teams’. As information and communication technologies permeate every aspect of organizational life and impact the way teams communicate, work and structure relationships, global virtual teams require innovative communication and learning capabilities for different team members to effectively work together across cultural, organizational and geographical boundaries. Whereas information technology‐facilitated communication processes rely on technologically advanced systems to succeed, the ability to create a knowledge‐sharing culture within a global virtual team rests on the existence (and maintenance) of intra‐team respect, mutual trust, reciprocity and positive individual and group relationships. Thus, some of the inherent questions we address in our paper are: (1) what are the cross‐cultural challenges faced by global virtual teams?; (2) how do organizations develop a knowledge sharing culture to promote effective organizational learning among culturally‐diverse team members? and; (3) what are some of the practices that can help maximize the performance of global virtual teams? We conclude by examining ways that global virtual teams can be more effectively managed in order to reach their potential in this new interconnected world and put forward suggestions for further research.     

A combination model for orientation field of fingerprints

Orientation field is a global feature of fingerprints that is very important in automatic fingerprint identification systems (AFIS). Establishing an accurate and concise model for orientation fields will not only improve the performance of orientation estimation, but also make it feasible to apply orientation information in the matching process. In this paper, a novel model for the orientation field of fingerprints is proposed. We use a polynomial model to approximate the orientation field globally and a point-charge model at each singular point to improve the approximation locally. These two models are combined together by a weight function. Experimental results are provided to illustrate the fact that this combination model is more accurate and robust with respect to noise compared with the previous works. The application of the model is discussed at the end.     

Remote sensing of vegetation and land-cover change in Arctic Tundra Ecosystems

The objective of this paper is to review research conducted over the past decade on the application of multi-temporal remote sensing for monitoring changes of Arctic tundra lands. Emphasis is placed on results from the National Science Foundation Land-Air-Ice Interactions (LAII) program and on optical remote sensing techniques. Case studies demonstrate that ground-level sensors on stationary or moving track platforms and wide-swath imaging sensors on polar orbiting satellites are particularly useful for capturing optical remote sensing data at sufficient frequency to study tundra vegetation dynamics and changes for the cloud prone Arctic. Less frequent imaging with high spatial resolution instruments on aircraft and lower orbiting satellites enable more detailed analyses of land cover change and calibration/validation of coarser resolution observations.The strongest signals of ecosystem change detected thus far appear to correspond to expansion of tundra shrubs and changes in the amount and extent of thaw lakes and ponds. Changes in shrub cover and extent have been documented by modern repeat imaging that matches archived historical aerial photography. NOAA Advanced Very High Resolution Radiometer (AVHRR) time series provide a 20-year record for determining changes in greenness that relates to photosynthetic activity, net primary production, and growing season length. The strong contrast between land materials and surface waters enables changes in lake and pond extent to be readily measured and monitored.