A digital computer simulation of high-altitude parachute response to wind gradients

Digital computer rigid body simulation of impervious hemisphere and disk-gap-band parachute systems response to high altitude wind shea

Hebbian learning in recurrent neural networks for natural language processing

This research project examines Hebbian learning in recurrent neural networks for natural language processing and attempts to interpret language at the level of a two and one half year old child. In this project five neural networks were built to interpret natural language: a Simple Recurrent Network with Hebbian Learning, a Jordan network with Hebbian learning and one hidden layer, a Jordannetwork with Hebbian learning and no hidden layers, a Simple Recurrent Network back propagation learning, and a nonrecurrent neural network with backpropagation learning. It is known that Hebbian learning works well when the input vectors are orthogonal, but, as this project shows, it does not perform well in recurrent neural networks for natural language processing when the input vectors for the individual words are approximately orthogonal. This project shows that,given approximately orthogonal vectors to represent each word in the vocabulary the input vectors for a given command are not approximately orthogonal and the internal representations that the neural network builds are similar for different commands. As the data shows, the Hebbian learning neural networks were unable to perform the natural language interpretation task while the back propagation neural networks were much more successful. Therefore, Hebbian learning does not work well in recurrent neural networks for natural language processing even when the input vectors for the individual words are approximately orthogonal

A Spectroscopic Survey of the Fields of 28 Strong Gravitational Lenses: The Group Catalog

With a large, unique spectroscopic survey in the fields of 28 galaxy-scale strong gravitational lenses, we identify groups of galaxies in the 26 adequately-sampled fields. Using a group finding algorithm, we find 210 groups with at least five member galaxies; the median number of members is eight. Our sample spans redshifts of 0.04 $\le z_{grp} \le$ 0.76 with a median of 0.31, including 174 groups with $0.1 < z_{grp} < 0.6$. Groups have radial velocity dispersions of 60 $\le \sigma_{grp} \le$ 1200 km s$^{-1}$ with a median of 350 km s$^{-1}$. We also discover a supergroup in field B0712+472 at $z =$ 0.29 consisting of three main groups. We recover groups similar to $\sim$ 85% of those previously reported in these fields within our redshift range of sensitivity and find 187 new groups with at least five members. The properties of our group catalog, specifically 1) the distribution of $\sigma_{grp}$, 2) the fraction of all sample galaxies that are group members, and 3) the fraction of groups with significant substructure, are consistent with those for other catalogs. The distribution of group virial masses agrees well with theoretical expectations. Of the lens galaxies, 12 of 26 (46%) (B1422+231, B1600+434, B2114+022, FBQS J0951+2635, HE0435-1223, HST J14113+5211, MG0751+2716, MGJ1654+1346, PG 1115+080, Q ER 0047-2808, RXJ1131-1231, and WFI J2033-4723) are members of groups with at least five galaxies, and one more (B0712+472) belongs to an additional, visually identified group candidate. There are groups not associated with the lens that still are likely to affect the lens model; in six of 25 (24%) fields (excluding the supergroup), there is at least one massive ($\sigma_{grp} \ge$ 500 km s$^{-1}$) group or group candidate projected within 2$^{\prime}$ of the lens.Comment: 87 pages, 8 figures, a version of this was published in Ap

Research Notes, February 1965

This is issue 2: Glacier Park Chalet Visits; An Introduction to Wilderness Experiencehttps://scholarworks.umt.edu/montana_forestry_notes/1001/thumbnail.jp

Evaluation of Technical Quality Circle Team Performance

Quality circle team performance of a major energy company was analyzed for tangible savings for the years 1988 and 1989, to determine if quality circles in the technical/professional environment are not as effective as quality circles in the non-technical areas. The performance of 244 teams was analyzed in these two years. Cost and savings data were evaluated using a number of different measures. Questionnaires were used to obtain attitudinal data in evaluating intangible benefits over the three year period 1983 through 1985. This survey data was designed to measure and evaluate changes in communications, teamwork, attitudes, morale, and job satisfaction resulting from employee involvement in quality circle teams. During the years 1988 and 1989, the Technical quality circle team tangible savings exceeded that of the Non-technical teams. It would appear that the work environment of the Technical employee exposes him to greater potential savings than the Nontechnical employee. The Non-technical response to the surveys were slightly more positive than the Technical member response indicating that his intangible benefits were slightly greater. This finding would be consistent with the concept that many of the attributes of the circle team already exist in the technical/professional work environment, and as a result, the intangible benefits of participating in a quality circle program are not as great to the Technical employee when compared to the Non-technical employee.Business Administratio

A Similarity Measure for GPU Kernel Subgraph Matching

Accelerator architectures specialize in executing SIMD (single instruction, multiple data) in lockstep. Because the majority of CUDA applications are parallelized loops, control flow information can provide an in-depth characterization of a kernel. CUDAflow is a tool that statically separates CUDA binaries into basic block regions and dynamically measures instruction and basic block frequencies. CUDAflow captures this information in a control flow graph (CFG) and performs subgraph matching across various kernel's CFGs to gain insights to an application's resource requirements, based on the shape and traversal of the graph, instruction operations executed and registers allocated, among other information. The utility of CUDAflow is demonstrated with SHOC and Rodinia application case studies on a variety of GPU architectures, revealing novel thread divergence characteristics that facilitates end users, autotuners and compilers in generating high performing code

Convolutional GRU Network for Seasonal Prediction of the El Ni\~no-Southern Oscillation

Predicting sea surface temperature (SST) within the El Ni\~no-Southern Oscillation (ENSO) region has been extensively studied due to its significant influence on global temperature and precipitation patterns. Statistical models such as linear inverse model (LIM), analog forecasting (AF), and recurrent neural network (RNN) have been widely used for ENSO prediction, offering flexibility and relatively low computational expense compared to large dynamic models. However, these models have limitations in capturing spatial patterns in SST variability or relying on linear dynamics. Here we present a modified Convolutional Gated Recurrent Unit (ConvGRU) network for the ENSO region spatio-temporal sequence prediction problem, along with the Ni\~no 3.4 index prediction as a down stream task. The proposed ConvGRU network, with an encoder-decoder sequence-to-sequence structure, takes historical SST maps of the Pacific region as input and generates future SST maps for subsequent months within the ENSO region. To evaluate the performance of the ConvGRU network, we trained and tested it using data from multiple large climate models. The results demonstrate that the ConvGRU network significantly improves the predictability of the Ni\~no 3.4 index compared to LIM, AF, and RNN. This improvement is evidenced by extended useful prediction range, higher Pearson correlation, and lower root-mean-square error. The proposed model holds promise for improving our understanding and predicting capabilities of the ENSO phenomenon and can be broadly applicable to other weather and climate prediction scenarios with spatial patterns and teleconnections.Comment: 13 pages, 7 figure

C−X (X = N, O) Cross-Coupling Reactions Catalyzed by Copper-Pincer Bis(N-Heterocyclic Carbene) Complexes

Over the last two decades, N-heterocyclic carbene (NHC)–copper catalysts have received considerable attention in organic synthesis. Despite the popularity of copper complexes containing monodentate NHC ligands and recent development of poly(NHC) platforms, their application in C–C and C–heteroatom cross-coupling reactions has been limited. Recently, we reported an air-assisted Sonogashira-type cross-coupling catalyzed by well-defined cationic copper-pincer bis(NHC) complexes. Herein, we report the application of these complexes in Ullmann-type C–X (X = N, O) coupling of azoles and phenols with aryl halides in a relatively short reaction time. In contrast to other well-defined copper(I) catalysts that require an inert atmosphere for an efficient C–X coupling, the employed Cu(I)-pincer bis(NHC) complexes provide good to excellent yields in air. The air-assisted reactivity, unlike that in the Sonogashira reaction, is also affected by the base employed and the reaction time. With Cs2CO3 and K2CO3, the oxygen-generated catalyst is more reactive than the catalyst formed under argon in a short reaction time (12 h). However, the difference in reactivity is compromised after a 24 h reaction with K2CO3. The efficient pincer Cu-NHC/O2/Cs2CO3 system provides great to excellent cross-coupling yields for electronically diverse aryl iodides and imidazole derivatives. The catalyst scope is controlled by a balance between nucleophilicity, coordinating ability, and the steric hindrance of aryl halides and N-/O-nucleophiles