Modeling the behavior of the 4/5ths rule for determining adverse impact: Reasons for caution.

The Equal Employment Opportunity Commission's 4/5ths rule has been used for over 20 years in applied psychology and employment law. The rule signals that there is adverse impact when the protected group selection ratio is less than 80% of the highest scoring group's selection ratio. We conducted several simulations and found, consistent with some previous management science literature, that the 4/5ths rule often resulted in false-positive readings of adverse impact even when there were no underlying (population) standardized group differences between subgroups. We then incorporated tests of statistical significance and found that adding such tests to the 4/5ths rule eliminated many false-positive indications of adverse impact. We also examined simulated selection systems based on meta-analytic values from the selection literature. The frequency of adverse impact signals from the 4/5ths rule increased markedly relative to simulations with no subgroup population differences. Adding statistical tests mitigated the number of indications of adverse impact to some extent. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Re-illuminating single images using Albedo estimation

Predicting the appearance of a scene under novel lighting conditions is of growing interest at the convergence of vision, graphics and virtual reality. In this paper, we develop a method for appearance prediction from a single image using the apparatus of shape from shading (SFS). We re-visit the reflectance estimation process first proposed by Blake (Graphics Image Process. 32 (1985) 314), and develop a novel approach to parameter selection within the Blake method based on the quality of images which can be produced by re-illuminating the recovered needle-map. Combining Blake's method with recent advances in SFS is demonstrated to yield significant improvements in the appearance prediction of real images under varying lighting conditions.     

MIMO Channel Characterization for Short Range Fixed Wireless Propagation Environments

This paper reports results from wideband MIMO measurements performed in short range fixed wireless environments at 5.2 GHz. The objective is to provide MIMO channel characterization results for the measured environments and contribute to the limited available similar studies. Two kinds of propagation scenarios are investigated, rooftop to rooftop and street to rooftop, at three different sites always under LOS propagation conditions. The analysis of measurement data is performed in the context of non physical modeling, providing insight into the statistics of the measured channels. In particular, the slow time varying nature of the channel is studied and the narrow Doppler spectrum shape is approximated. Furthermore, frequency correlation results are obtained and the typical delay dispersion measures are extracted. Then, the antenna correlation is studied and the error of the Kronecker product approximation is evaluated. Finally, capacity results are provided and the channel measurements are characterized in terms of spatial multiplexing quality and multipath richness through condition number analysis. Nikolaos D. Skentos received his Diploma in Electrical and Computer Engineering from the National Technical University of Athens (NTUA), Greece in October 2000. Since January 2001 he has been a research associate at the Mobile Radio Communications Laboratory at the NTUA, and he is currently working towards the Ph.D. degree. His research interests include channel measurements, MIMO channel characterization, MIMO algorithms and space time processing. He has been active in the IST STINGRAY project, the COST 273 Action and the ACE Network of Excellence. He is also a member of the National Technical Chamber of Greece since 2001. Athanasios G. Kanatas received the Diploma in Electrical Engineering from the National Technical University of Athens, Greece, in 1991, the M.Sc. degree in Satellite Communication Engineering from the University of Surrey, Surrey, UK in 1992, and the Ph.D. degree in Mobile Satellite Communications from the National Technical University of Athens, Greece in February 1997. From 1993 to 1994 he was with National Documentation Center of National Research Institute. In 1995 he joined SPACETEC Ltd. where he was Technical Project Manager for VISA/EMEA VSAT Project in Greece. In 1996 he joined the Mobile Radio Communications Laboratory as a research associate. From 1999 to 2002 he was with the Institute of Communication & Computer Systems. In 2000 he became a member of the Board of Directors of OTESAT S.A. He is an Assistant Professor in the Department of Technology Education and Digital Systems at University of Piraeus. His current research interests include channel characterization and estimation, simulation and modeling for mobile, mobile satellite, and future wireless communication systems. He has been a Senior Member of IEEE since 2002, and is also a member of the Technical Chamber of Greece. In 1999 he was elected Chairman of the Communications Society of the Greek IEEE Section. Panagiotis I. Dallas was born 1967 in Thessaloniki, Greece. He obtained his diploma and Ph.D. degree from the Electrical and Computer Engineering Department of Aristotle University of Thessaloniki, Greece, in 1990 and 1997, respectively. Since 1998 he joined with INTRACOM where he currently is Section Manager of Advanced Communications Technologies branch of Emerging Technologies & Markets department, leading the next generation of broadband wireless access systems for internal and EU projects. He runs the relevant standardization activities (IEEE 802.16 and ETSI/BRAN HIPERMAN) in INTRACOM and he represents the company in WiMAX forum. Finally, he has over 30 publications in international journals and conferences. Philip Constantinou received the Diploma in Physics from the National University of Athens in 1972, the Master of Applied Science in Electrical Engineering from the University of Ottawa, Ontario, Canada in 1976, and the Ph.D. degree in Electrical Engineering in 1983 from Carleton University, Ottawa, Ontario, Canada. From 1976 to 1979 he was with Telesat Canada as a Communications System Engineer. In 1980 he joined the Ministry of Communications in Ottawa, Canada where he was engaged in the area of Mobile Communication. From 1984 to 1989 he was with the National Research Center Demokritos in Athens, Greece where he was involved in several research projects in the area of Mobile Communications. In 1989 he joined the National Technical University of Athens where he is currently a Professor and Director of the Mobile Radio Communications Laboratory. His current research interests include Personal Communications, Mobile Satellite Communications, and Interference Problems on Digital Communications Systems.     

Query indexing with containment-encoded intervals for efficient stream processing

Many continual range queries can be issued against data streams. To efficiently evaluate continual queries against a stream, a main memory-based query index with a small storage cost and a fast search time is needed, especially if the stream is rapid. In this paper, we study a CEI-based query index that meets both criteria for efficient processing of continual interval queries. This new query index is an indirect indexing approach. It centres around a set of predefined virtual containment-encoded intervals, or CEIs. The CEIs are used to first decompose query intervals and then perform efficient search operations. The CEIs are defined and labeled such that containment relationships among them are encoded in their IDs. The containment encoding makes decomposition and search operations efficient; from the encoding of the smallest CEI containing a data point, the encodings of other containing CEIs can be easily derived. Closed-form formulae for the bounds of the average index storage cost are derived. Simulations are conducted to evaluate the effectiveness of the CEI-based query index and to compare it with alternative approaches. The results show that the CEI-based query index significantly outperforms existing approaches in terms of both storage cost and search time. Kun-Lung Wu received the B.S. degree in electrical engineering from the National Taiwan University, Taipei, Taiwan, the M.S. and Ph.D. degrees in computer science from the University of Illinois at Urbana–Champaign. He is with the IBM Thomas J. Watson Research Center, currently a member of the Software Tools and Techniques Group. His current research interests include data streams, continual queries, mobile computing, Internet technologies and applications, database systems and distributed and parallel computing. He has published extensively and holds various patents in these areas. Dr. Wu is a Senior Member of the IEEE Computer Society and a member of the ACM. He was an Associate Editor for the IEEE Transactions on Knowledge and Data Engineering, 2000–2004. He was the general chair for the 3rd International Workshop on e-Commerce and Web-Based Information Systems (WECWIS 2001). He has served as an organising and program committee member on various conferences. He has received various IBM awards, including IBM Corporate Environmental Affair Excellence Award, Research Division Award and Invention Achievement Awards. He received a best paper award from IEEE EEE 2004. He is an IBM Master Inventor. Shyh-Kwei Chen received the B.S. degree in computer science and information engineering from National Taiwan University, Taipei, Taiwan, in 1983, the M.S. degree in computer science from the University of Minnesota, Minneapolis, in 1987, and the Ph.D. degree in computer science from University of Illinois at Urbana–Champaign, in 1994. Dr. Chen has been with the IBM Thomas J. Watson Research Center, Yorktown Heights, New York since October 1994, where he is currently a research staff member. His current research interests include XML, electronic commerce, business performance management, data engineering and compilers. He is a member of the ACM, the IEEE and the IEEE Computer Society. Philip S. Yu received the B.S. degree in electrical engineering from National Taiwan University, the M.S. and Ph.D. degrees in electrical engineering from Stanford University, and the M.B.A. degree from New York University. He is with the IBM Thomas J. Watson Research Center and is currently manager of the Software Tools and Techniques group. His research interests include data mining, Internet applications and technologies, database systems, multimedia systems, parallel and distributed processing and performance modelling. Dr. Yu has published more than 400 papers in refereed journals and conferences. He holds or has applied for more than 250 US patents. Dr. Yu is a Fellow of the ACM and a Fellow of the IEEE. He is an associate editor of ACM Transactions on Internet Technology. He is a member of the IEEE Data Engineering steering committee and is also on the steering committee of IEEE Conference on Data Mining. He was the Editor-in-Chief of IEEE Transactions on Knowledge and Data Engineering (2001–2004), an editor and advisory board member of IEEE Transactions on Knowledge and Data Engineering and also a guest coeditor of the special issue on mining of databases. He had also served as an associate editor of Knowledge and Information Systems. In addition to serving as program committee member on various conferences, he was the program cochair of the 11th International Conference on Data Engineering, the 6th Pacific Area Conference on Knowledge Discovery and Data Mining, and the 9th ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, and the program chair of the 2nd International Workshop on Research Issues on Data Engineering: Transaction and Query Processing, the PAKDD Workshop on Knowledge Discovery from Advanced Databases and the 2nd International Workshop on Advanced Issues of E-Commerce and Web-based Information Systems. He served as the general chair of the 14th International Conference on Data Engineering and the general cochair of the 2nd IEEE International Conference on Data Mining. He has received several IBM honours, including two IBM Outstanding Innovation Awards, an Outstanding Technical Achievement Award, two Research Division Awards and the 81st Plateau of Invention Achievement Awards. He received an Outstanding Contributions Award from IEEE International Conference on Data Mining in 2003 and also an IEEE Region 1 Award for “promoting and perpetuating numerous new electrical engineering concepts” in 1999. Dr. Yu is an IBM Master Inventor and was recognised as one of the IBM's 10 top leading inventors in 1999.     

Landscape visualizations: Applications and requirements of 3D visualization software for environmental planning

This paper presents the findings of an investigation into the role and use of landscape visualization software for landscape and environmental planning in Germany. It examines the challenges and requirements of 3D visualization technology and its potential for application in landscape and environmental planning. Relevant literature and comparable surveys are reviewed in order to determine the current state of affairs, and the general and international relevance of the results is assessed.In 2000, a survey of user requirements for 3D landscape simulation software, including the demand for specific features, was conducted within the framework of a feasibility study for a visualization tool. As part of the German-wide survey, comprehensive questionnaires were sent to 1044 respondents from a pool of private landscape planning consultancies, freelance landscape architects, and public planning and environmental authorities.The survey showed that 3D landscape visualization has a positive image in Germany, both among user and non-user groups of visualization tools. Twenty-eight percent of private consultancies and freelance landscape architects, as well as 7% of public authorities, stated that they already used 3D simulation software. Those respondents who did not use 3D simulation software cited insufficient computer equipment, lack of technical expertise of planners and cost-related aspects as reasons for not yet having adopted the technology. “Ease of learning” and “interoperability” are deemed to be the most important features of 3D simulation software, whereas factors such as “high interactivity”, “representability of ecological processes” and “photo-realism” are, surprisingly, regarded as much less important.Users of 3D visualization software are particularly concerned by insufficient representation of plants and habitats in simulations. Looking to the future, the vast majority of respondents (91%) expect increased benefits for landscape planning from 3D visualization software, are convinced of the advantages of the technology, and are eager to integrate 3D landscape visualizations into their working practices.     

A Holistic Approach for Resource-aware Adaptive Data Stream Mining

Mining data streams is a field of increasing interest due to the importance of its applications and dissemination of data stream sources. Most of the streaming techniques developed so far have not addressed the need for resource-aware computing in data stream analysis. The fact that streaming information is often generated or received onboard resource-constrained computational devices such as sensor nodes and mobile devices motivates the need for resource-awareness in data stream processing systems. In this paper, we propose a generic framework that enables resource-awareness in streaming computation using algorithm granularity settings in order to change the resource consumption patterns periodically. This generic framework is applied to a novel threshold-based micro-clustering algorithm to test its validity and feasibility. We have termed this algorithm as RA-Cluster. RA-Custer is the first data stream clustering algorithm that can adapt to the changing availability of different resources. The experimental results show the applicability of the framework and the algorithm in terms of resource-awareness and accuracy.     

Customization of a Commercially Available Prep Scale SFC System to Provide Enhanced Capabilities

Preparative Scale Supercritical Fluid Chromatography is emerging as a powerful alternative to HPLC for the purification and separation of complex chemical reaction mixtures. Advantages include greatly reduced solvent usage (and thus lower cost and environmental impact), higher throughput, and in some cases higher resolution. While there are commercially available prep SFC instruments, none currently offer all the features desired by many medicinal chemists engaged in the drug discovery process. These include: the ability to collect an unlimited number of fractions per sample with high recovery and negligible carryover, fully automated capacity to collect several hundred fractions, and the ability to collect fractions into the same disposable test tubes and racks which are already employed in HPLC. This article describes the customization of a preparatory scale SFC system purchased from Berger Instruments, Inc., Newark, DE. (a subsidiary Mettler-Toledo International, Inc., of Greifensee, Switzerland) in order to provide these capabilities.     

Face posture estimation using eigen analysis on an IBR (image based rendered) database

In this paper, we present a novel representation of the human face for estimating the orientation of the human head in a two dimensional intensity image. The method combines the use of the much familiar eigenvalue based dissimilarity measure with image based rendering. There are two main components of the algorithm described here: the offline hierarchical image database generation and organization, and the online pose estimation stage. The synthetic images of the subject's face are automatically generated offline, for a large set of pose parameter values, using an affine coordinate based image reprojection technique. The resulting database is formally called as the IBR (or image based rendered) database. This is followed by the hierarchical organization of the database, which is driven by the eigenvalue based dissimilarity measure between any two synthetic image pair. This hierarchically organized database is a detailed, yet structured, representation of the subject's face. During the pose estimation of a subject in an image, the eigenvalue based measure is invoked again to search the synthetic (IBR) image closest to the real image. This approach provides a relatively easy first step to narrow down the search space for complex feature detection and tracking algorithms in potential applications like virtual reality and video-teleconferencing applications.     

The Relaxed Online Maximum Margin Algorithm

We describe a new incremental algorithm for training linear threshold functions: the Relaxed Online Maximum Margin Algorithm, or ROMMA. ROMMA can be viewed as an approximation to the algorithm that repeatedly chooses the hyperplane that classifies previously seen examples correctly with the maximum margin. It is known that such a maximum-margin hypothesis can be computed by minimizing the length of the weight vector subject to a number of linear constraints. ROMMA works by maintaining a relatively simple relaxation of these constraints that can be efficiently updated. We prove a mistake bound for ROMMA that is the same as that proved for the perceptron algorithm. Our analysis implies that the maximum-margin algorithm also satisfies this mistake bound; this is the first worst-case performance guarantee for this algorithm. We describe some experiments using ROMMA and a variant that updates its hypothesis more aggressively as batch algorithms to recognize handwritten digits. The computational complexity and simplicity of these algorithms is similar to that of perceptron algorithm, but their generalization is much better. We show that a batch algorithm based on aggressive ROMMA converges to the fixed threshold SVM hypothesis.