Fixture aids soldering of electronic components on circuit board

Spring clamp fixture holds small electronic components in a desired position while they are being soldered on a circuit board. The spring clamp is clipped on the edge of the circuit board and an adjustable spring-steel boom holds components against the board. The felt pad at the end of the boom is replaced with different attachments for other holding tasks

A visual workspace for constructing hybrid MDS algorithms and coordinating multiple views

Data can be distinguished according to volume, variable types and distribution, and each of these characteristics imposes constraints upon the choice of applicable algorithms for their visualisation. This has led to an abundance of often disparate algorithmic techniques. Previous work has shown that a hybrid algorithmic approach can be successful in addressing the impact of data volume on the feasibility of multidimensional scaling (MDS). This paper presents a system and framework in which a user can easily explore algorithms as well as their hybrid conjunctions and the data flowing through them. Visual programming and a novel algorithmic architecture let the user semi-automatically define data flows and the co-ordination of multiple views of algorithmic and visualisation components. We propose that our approach has two main benefits: significant improvements in run times of MDS algorithms can be achieved, and intermediate views of the data and the visualisation program structure can provide greater insight and control over the visualisation process

A virtual workspace for hybrid multidimensional scaling algorithms

In visualising multidimensional data, it is well known that different types of algorithms to process them. Data sets might be distinguished according to volume, variable types and distribution, and each of these characteristics imposes constraints upon the choice of applicable algorithms for their visualization. Previous work has shown that a hybrid algorithmic approach can be successful in addressing the impact of data volume on the feasibility of multidimensional scaling (MDS). This suggests that hybrid combinations of appropriate algorithms might also successfully address other characteristics of data. This paper presents a system and framework in which a user can easily explore hybrid algorithms and the data flowing through them. Visual programming and a novel algorithmic architecture let the user semi-automatically define data flows and the co-ordination of multiple views

Can Markets Learn to Avoid Bubbles?

One of the most striking results in experimental economics is the ease with which market bubbles form in a laboratory setting and the difficulty of preventing them. This article re-examines bubble experiments in light of the results of an earlier series of market experiments that examine how learning occurs in markets characterized by an asymmetry of information between buyers and sellers, such as found in Akerlof’s lemons model and Spence’s signaling model and extends the arguments put forth in the author’s book, Paving Wall Street: Experimental Economics and the Quest for the Perfect Market. Markets with asymmetric information are incomplete because they lack markets for specific levels of product quality. Such markets either lump all qualities together (lemons) or using external indications of quality to separate them (signaling). Similarly, the markets used in bubble experiments are incomplete in that they are lacking a complete set of forward or futures markets, depriving traders of the information supplied by the prices in those markets. Preliminary experimental results suggest that the addition of a single forward market can sometimes mitigate bubble formation and this article suggests more extensive research in this direction is warranted. Market bubbles outside of the laboratory usually are found in markets in with forward and futures markets that are either legally restricted or otherwise limited. Experimentation in markets with asymmetric information also indicates that the ability of subjects to learn how to send and receive signals can be enhanced by changing the way that market information is presented to them. We explore how this result might be used to help asset markets learn to avoid bubbles.Market bubbles, learning and adaptation, behavioral finance, signaling, asymmetric information

Measuring the True Cost of Active Management by Mutual Funds

Recent years have seen a dramatic shift from mutual funds into hedge funds even though hedge funds charge management fees that have been decried as outrageous. While expectations of superior returns may be responsible for this shift, this article shows that mutual funds are more expensive than commonly believed. Mutual funds appear to provide investment services for relatively low fees because they bundle passive and active funds management together in a way that understates the true cost of active management. In particular, funds engaging in “closet” or “shadow” indexing charge their investors for active management while providing them with little more than an indexed investment. Even the average mutual fund, which ostensibly provides only active management, will have over 90% of the variance in its returns explained by its benchmark index. This article derives a method for allocating fund expenses between active and passive management and constructs a simple formula for finding the cost of active management. Computing this “active expense ratio” requires only a fund’s published expense ratio, its R-squared relative to a benchmark index, and the expense ratio for a competitive fund that tracks that index. At the end of 2004, the mean active expense ratio for the large-cap equity mutual funds tracked by Morningstar was 7%, over six times their published expense ratio of 1.15%. More broadly, funds in the Morningstar universe had a mean active expense ratio of 5.2%, while the largest funds averaged a percent or two less.mutual fund expenses, cost allocation, active expense ratio, active alpha, portable alpha

Linear-Time Algorithms for Finding Tucker Submatrices and Lekkerkerker-Boland Subgraphs

Lekkerkerker and Boland characterized the minimal forbidden induced subgraphs for the class of interval graphs. We give a linear-time algorithm to find one in any graph that is not an interval graph. Tucker characterized the minimal forbidden submatrices of binary matrices that do not have the consecutive-ones property. We give a linear-time algorithm to find one in any binary matrix that does not have the consecutive-ones property.Comment: A preliminary version of this work appeared in WG13: 39th International Workshop on Graph-Theoretic Concepts in Computer Scienc

A problem in optimal search and stop

Problem in optimal search and sto