A note on the variance of rank-based selection strategies for genetic algorithms and genetic programming

This paper evaluates different forms of rank-based selection that are used with genetic algorithms and genetic programming. Many types of rank based selection have exactly the same expected value in terms of the sampling rate allocated to each member of the population. However, the variance associated with that sampling rate can vary depending on how selection is implemented. We examine two forms of tournament selection and compare these to linear rank-based selection using an explicit formula. Because selective pressure has a direct impact on population diversity, we also examine the interaction between selective pressure and different mutation strategies.     

Value of career-decision-making self-efficacy in predicting career-decision-making attitudes and skills.

233 undergraduates (162 women and 71 men) completed a demographics questionnaire and measures of career-decision-making (CDM) self-efficacy (K. M. Taylor and N. E. Betz, 1983), CDM attitudes (J. O. Crites, 1978), and CDM skills (D. E. Super et al, 1981). Results revealed that CDM self-efficacy was moderately and positively related to CDM attitudes and age of participants (p?     

Fast buffering for FPGA implementation of vision-based object recognition systems

Real-time frame rate is an important factor for practical deployment of computer vision systems. Field programmable gate array (FPGA) technology has been considered for many applications due to its parallel computing capability. FPGA implementations of computer vision algorithms normally involve buffering data on external memory devices, which could slow down the whole system. This paper proposes a buffering scheme suitable for implementing real-time vision-based systems on an FPGA that does not require external memory to buffer data. A stop sign detection system implemented on an FPGA employing the proposed buffering scheme is presented as an example system. This system is capable of processing over 200?fps at the frame size of 480?×?752 pixels.     

Static and Cyclic Fatigue of Alumina at High Temperatures: II, Failure Analysis

Failure mechanisms of an alumina, tested at 1200°C under static and various cyclic loading conditions, were examined. Slow crack growth of a single crack is the dominant mechanism for the failure in specimens under cyclic loading with a short duration of maximum stress at all applied stress levels, as well as at high applied loads for static loading and cyclic loading with a longer hold time at maximum stress. At low stress levels, failure of static loading and cyclic loading with a longer hold time at maximum stress might occur by formation and/or growth of multiple macrocracks. More importantly, for all the given loading conditions. The viscous glassy phase behind the crack tip could have a bridging effect on the crack surfaces. A simplified model for calculating effective stress intensity factor at the crack tip under static and various cyclic loading demonstrated a trend consistent with the stress–life data.     

Extraction of rice brain oil using supercritical carbon dioxide and propane

Extraction of rice bran lipids was performed using supercritical carbon dioxide (SC−CO₂) and liquid propane. To provide a basis for extraction efficiency, accelerated solvent extraction with hexane was performed at 100°C and 10.34 MPa. Extraction pressure was varied for propane and SC−CO₂ extractions. Also, the role of temperature in SC−CO₂ extraction efficiency was investigated at 45,65, and 85°C. For the SC−CO₂ experiments, extraction efficiencies were proportional to pressure and inversely proportional to temperature, and the maximal yield of oil achieved using SC−CO₂ was 0.222±0.013 kg of oil extracted per kg of rice bran for conditions of 45°C and 35 MPa. The maximal yield achieved with propane was 0.224±0.016 kg of oil per kg of rice bran at 0.76 MPa and ambient temperature. The maximum extraction efficiencies of both SC−CO₂ and propane were found to be significantly different from the hexane extraction baseline yield, which was 0.261±0.005 kg oil extracted per kg of rice bran. A simulated economic analysis was performed on the possibility of using SC−CO₂ and propane extraction technologies to remove oil from rice bran generated in Mississippi. Although the economic analysis was based on the maximal extraction efficiency for each technology, neither process resulted in a positive rate of return on investment.     

Transformations and losses of fertilizer nitrogen on no-till and conventional till soils

A field study was conducted in 1982 to measure the effect of no-till (NT) and conventional till (CT) systems on N transformation after surface and subsurface applications of N fertilizers. Urea, urea-ammonium nitrate (UAN) solution, (NH₄)₂SO₄ (AS), and CA(NO₃)₂ were applied to NT and CT plots (5.95 m²) at a rate of 448 kg N ha^–1. A comparison of fertilizer N recovered in soils receiving incorporated or surface applied N was used to estimate NH₃ volatilization while denitrification was estimated from fertilizer N recovered in the presence and absence of nitrapyrin with incorporated N. Immobilization was assessed in microplots (0.37 m²) after surface application of (¹⁵NH₄)₂SO₄ to NT and CT systems at a rate of 220 kg N ha^–1.The results indicate little difference between NT and CT systems on urea hydrolysis rates and immobilization of surface applied fertilizer N. Approximately 50% and 10% of the surface applied N was recovered in the inorganic and organic fractions, respectively, on both tillage systems. The N not recovered was likely lost from plot areas through soil runoff. Incorporation of UAN, urea and AS resulted in 20 to 40% greater inorganic N recovery than from surface application. Nitrification rates were greater under the NT than the CT system. The similarities in concentration in the various N pools observed between the two tillage systems may be partially due to the short length of time that NT was imposed in this field study (<1 year) since other researchers using established tillage systems (>5 y) indicate that NT tends to promote decreased efficiency of fertilizer N.     

Evaluation of the coupled multielectrode array sensor as a real-time corrosion monitor

Coupled multielectrode array sensors made of carbon steel and stainless steels were evaluated and compared with electrochemical noise (EN) sensors. Good correlations between sensor signals and solution corrosivity were observed for all multielectrode array sensors. Some correlation between the average pit index and solution corrosivity was observed for the carbon steel EN sensors, but not for the stainless steel EN sensors. The time-average noise resistances from the stainless steel EN sensors correlate well with solution corrosivity. There were, however, large random fluctuations and drifting for all EN signals, which make the EN sensors unreliable as real-time monitors.     

Development of a high pressure automated lag time apparatus for experimental studies and statistical analyses of nucleation and growth of gas hydrates

Nucleation in a supercooled or a supersaturated medium is a stochastic event, and hence statistical analyses are required for the understanding and prediction of such events. The development of reliable statistical methods for quantifying nucleation probability is highly desirable for applications where control of nucleation is required. The nucleation of gas hydrates in supercooled conditions is one such application. We describe the design and development of a high pressure automated lag time apparatus (HP-ALTA) for the statistical study of gas hydrate nucleation and growth at elevated gas pressures. The apparatus allows a small volume (≈150 μl) of water to be cooled at a controlled rate in a pressurized gas atmosphere, and the temperature of gas hydrate nucleation, T(f), to be detected. The instrument then raises the sample temperature under controlled conditions to facilitate dissociation of the gas hydrate before repeating the cooling-nucleation cycle again. This process of forming and dissociating gas hydrates can be automatically repeated for a statistically significant (>100) number of nucleation events. The HP-ALTA can be operated in two modes, one for the detection of hydrate in the bulk of the sample, under a stirring action, and the other for the detection of the formation of hydrate films across the water-gas interface of a quiescent sample. The technique can be applied to the study of several parameters, such as gas pressure, cooling rate and gas composition, on the gas hydrate nucleation probability distribution for supercooled water samples.     

A Unified Variational Volume Registration Method Based on Automatically Learned Brain Structures

We introduce a new volumetric registration technique that effectively combines active surfaces with the finite element method. The method simultaneously aligns multi-label automatic structural segmentation results, which can be obtained by the application of existing segmentation software, to produce an anatomically accurate 3D registration. This registration is obtained by the minimization of a single energy functional. Just like registering raw images, obtaining a 3D registration this way still requires solving a fundamentally ill-posed problem. We explain through academic examples as well as an MRI dataset with manual anatomical labels, which are hidden from the registration method, how the quality of a registration method can be measured and the advantages our approach offers.     

Learning to transform time series with a few examples

We describe a semi-supervised regression algorithm that learns to transform one time series into another time series given examples of the transformation. This algorithm is applied to tracking, where a time series of observations from sensors is transformed to a time series describing the pose of a target. Instead of defining and implementing such transformations for each tracking task separately, our algorithm learns a memoryless transformation of time series from a few example input-output mappings. The algorithm searches for a smooth function that fits the training examples and, when applied to the input time series, produces a time series that evolves according to assumed dynamics. The learning procedure is fast and lends itself to a closed-form solution. It is closely related to nonlinear system identification and manifold learning techniques. We demonstrate our algorithm on the tasks of tracking RFID tags from signal strength measurements, recovering the pose of rigid objects, deformable bodies, and articulated bodies from video sequences. For these tasks, this algorithm requires significantly fewer examples compared to fully-supervised regression algorithms or semi-supervised learning algorithms that do not take the dynamics of the output time series into account.