Thermal Evolution of Planetesimals and Protoplanets in the Terrestrial Planet Region: Code Optimization and Implementation on a Distributed Grid using NetSolve

A code for asteroidal heat transfer and growth is optimized for performance. The Gauss elimination routine for the solver is replaced by a sparse matrix routine. Finite element matrix assembly operations are rewritten to reduce operations involving 3D arrays to 1D. Advantage is taken of the sparse matrix structure of finite element matrices in reducing 2D arrays to 1D. The number of vector touches are reduced to the extent possible, by carrying over statements from one iteration to the next. The number of do loops are reduced by merging several do loops into one. The optimization reduced the CPU time taken to run the code from 297 sec to 0.88 sec for a matrix size of 100, an improvement of 99.70%. More importantly, the algorithm was reduced from a O(n3) operation to a O(n) operation. Thus, the percent time difference between the optimized and unoptimized versions is greater at larger matrix sizes. At matrix sizes of 100, the number of floating point operations were reduced from 2.39 E+09 to 2.99E+07, an improvement of 98.75% and the performance was increased by about 4 times, from 8.06 MFLOPS/s to 33.92 MFLOPS/s. Because of inefficiency in memory allocation, the maximum matrix size for the unoptimized code was limited to 200. This was increased to 5,000,000 for the optimized code. A version of the code was implemented on NetSolve and added to the list of problems on netsolve.cs.utk.edu. Two sample movies were generated using OpenGL to explain the scientific significance of the code. With the implementation of the optimized code, applications to address scientific problems can now be envisioned that were previously thought to be prohibitive in terms of computer time

A Study of Convergence of the PMARC Matrices Applicable to WICS Calculations

This report discusses some analytical procedures to enhance the real time solutions of PMARC matrices applicable to the Wall Interference Correction Scheme (WICS) currently being implemented at the 12 foot Pressure Tunnel. WICS calculations involve solving large linear systems in a reasonably speedy manner necessitating exploring further improvement in solution time. This paper therefore presents some of the associated theory of the solution of linear systems. Then it discusses a geometrical interpretation of the residual correction schemes. Finally some results of the current investigation are presented

Two-stream Multi-dimensional Convolutional Network for Real-time Violence Detection

The increasing number of surveillance cameras and security concerns have made automatic violent activity detection from surveillance footage an active area for research. Modern deep learning methods have achieved good accuracy in violence detection and proved to be successful because of their applicability in intelligent surveillance systems. However, the models are computationally expensive and large in size because of their inefficient methods for feature extraction. This work presents a novel architecture for violence detection called Two-stream Multi-dimensional Convolutional Network (2s-MDCN), which uses RGB frames and optical flow to detect violence. Our proposed method extracts temporal and spatial information independently by 1D, 2D, and 3D convolutions. Despite combining multi-dimensional convolutional networks, our models are lightweight and efficient due to reduced channel capacity, yet they learn to extract meaningful spatial and temporal information. Additionally, combining RGB frames and optical flow yields 2.2% more accuracy than a single RGB stream. Regardless of having less complexity, our models obtained state-of-the-art accuracy of 89.7% on the largest violence detection benchmark dataset.Comment: 8 pages, 6 figure

Modulation of fluorophore environment in host membranes of varying charge

The net electrical charge of the biological membrane represents an important parameter in the organization, dynamics and function of the membrane. In this paper, we have characterized the change in the microenvironment experienced by a membrane-bound fluorescent probe when the charge of the phospholipids constituting the host membrane is changed from zwitterionic to cationic with minimal change in the chemical structure of the host lipid. In particular, we have explored the difference in the microenvironment experienced by the fluorescent probe 2-(9-anthroyloxy)stearic acid (2-AS) in model membranes of zwitterionic 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) and cationic 1-palmitoyl-2-oleoyl-sn-glycero-3-ethylphosphocholine (EPOPC) which are otherwise chemically similar, using the wavelength-selective fluorescence approach and other fluorescence parameters. Our results show that the microenvironment experienced by a membrane probe such as 2-AS is different in POPC and EPOPC membranes, as reported by red edge excitation shift (REES) and other fluorescence parameters. The difference in environment encountered by the probe in the two cases could possibly be due to variation in hydration in the two membranes owing to different charges

Optimal path and gait generations simultaneously of a six-legged robot using a GA-Fuzzy approach

This paper describes a new method for generating optimal path and gait simultaneously of a six-legged robot using a combined GA-fuzzy approach. The problem of combined path and gait generations involves three steps, namely determination of vehicle's trajectory, foothold selection and design of a sequence of leg movements. It is a complicated task and no single traditional approach is found to be successful in handling this problem. Moreover, the traditional approaches do not consider optimization issues, yet they are computationally expensive. Thus, the generated path and gaits may not be optimal in any sense. To solve such problems optimally, there is still a need for the development of an efficient and computationally faster algorithm. In the proposed genetic-fuzzy approach, optimal path and gaits are generated by using fuzzy logic controllers (FLCs) and genetic algorithms (GAs) are used to find optimized FLCs. The optimization is done off-line on a number of training scenarios and optimal FLCs are found. The hexapod can then use these GA-tuned FLCs to navigate in test-case scenarios

Design of a genetic-fuzzy system for planning optimal path and gait simultaneously of a six-legged robot

This paper describes a genetic-fuzzy system used for generating optimal path and gait simultaneously of a six-legged robot. No single traditional approach is found to be successful in handling this complicated task. Moreover, the conventional methods are computationally expensive and the generated path and gaits may not be optimal in any sense. Thus, there is still a need for the development of an efficient and computationally faster algorithm for solving this problem. In the proposed algorithm, optimal path and gaits are generated by fuzzy logic controllers (FLCs) and optimized FLCs are found by genetic algorithms (GAs). Design of an optimized FLC (only rule base optimization) involves the problem of dealing with discrete variables and GA is an efficient tool for this purpose. The actual optimization is done off-line and the hexapod can use these GA-tuned FLCs to navigate in real-world scenarios, in an optimal sense