Unnecessary inferences in associative-commutative completion procedures

Theoretical results for identifying unnecessary inferences are discussed in the context of the use of a completion-procedure-based approach toward automated reasoning. The notion of a general superposition is introduced and it is proved that in a completion procedure, once a general superposition is considered, all its instances are unnecessary inferences and, thus, do not have to be considered. It is also shown that this result can be combined with another criterion, called the prime superposition criterion, proposed by Kapur, Musser, and Narendran, thus implying that prime and general superpositions are sufficient. These results should be applicable to other approaches toward automated reasoning, too. These criteria can be effectively implemented, and their implementation has resulted in automatically proving instances of Jacobson's theorem (also known as the ring commutativity problems) usingRRL (Rewrite Rule Laboratory), a theorem prover based on rewriting techniques and completion.A preliminary version of this paper appeared in a paper entitled Consider only general superpositions in completion procedures in theProceedings of the Third International Conference on Rewriting Techniques and Applications, Chapel Hill, NC, April, 1989, Lecture Notes in Computer Science, Vol. 355, Springer-Verlag, Berlin, pp. 513–527. Part of the work of Hantao Zhang was done at the Rensselaer Polytechnic Institute, New York, and he was partially supported by National Science Foundation Grant No. CCR-8408461; also affiliated with Institute of Programming and Logics at SUNY, Albany, NY, and RPI. Deepak Kapur was partially supported by National Science Foundation Grantr Nos. CCR-8408461 and CCR-8906678.     

An evolutionary lion optimization algorithm‐based image compression technique for biomedical applications

Recently, medical image compression becomes essential to effectively handle large amounts of medical data for storage and communication purposes. Vector quantization (VQ) is a popular image compression technique, and the commonly used VQ model is Linde–Buzo–Gray (LBG) that constructs a local optimal codebook to compress images. The codebook construction was considered as an optimization problem, and a bioinspired algorithm was employed to solve it. This article proposed a VQ codebook construction approach called the L2‐LBG method utilizing the Lion optimization algorithm (LOA) and Lempel Ziv Markov chain Algorithm (LZMA). Once LOA constructed the codebook, LZMA was applied to compress the index table and further increase the compression performance of the LOA. A set of experimentation has been carried out using the benchmark medical images, and a comparative analysis was conducted with Cuckoo Search‐based LBG (CS‐LBG), Firefly‐based LBG (FF‐LBG) and JPEG2000. The compression efficiency of the presented model was validated in terms of compression ratio (CR), compression factor (CF), bit rate, and peak signal to noise ratio (PSNR). The proposed L2‐LBG method obtained a higher CR of 0.3425375 and PSNR value of 52.62459 compared to CS‐LBG, FA‐LBG, and JPEG2000 methods. The experimental values revealed that the L2‐LBG process yielded effective compression performance with a better‐quality reconstructed image.     

Design optimization of supersonic jet pumps using high fidelity flow analysis

Supersonic jet pumps are simple devices with no moving parts, where a high velocity (primary) flow is used to pump a second fluid. In this paper, Computational Fluid Dynamics (CFD) is combined with an optimization framework in order to develop a tool for the rapid generation of jet pump designs. A key feature of the problem formulation is the transformation of the jet pump design parameters in terms of geometric ratios. This approach dramatically reduces the number of unrealistic designs covered by the Design of Experiments. Optimal Latin Hypercubes for surrogate model building and model validation points are constructed using a permutation genetic algorithm and design points are evaluated using CFD. Surrogate models of primary and entrained flow rates are built using a Moving Least Squares approach. A series of optimizations for various pump sizes are performed using a genetic algorithm and Sequential Quadratic Programming, with responses calculated from the surrogates. This approach results in a set of optimized designs, from which pumps for a wide range of flow rates can be interpolated.     

Plaster of Paris activated supersulfated slag cement

Hydration and strength behavior of supersulfated cement produced by activating a granulated Indian blastfurnace slag by plaster of Paris has been investigated. It is shown that plaster of Paris is a better activator than the conventional hard burnt gypsum (anhydrite) at least for a class of blastfurnace slags which are ordinarily considered less than ideal for this purpose. The setting characteristics of the plaster of Paris activated slag were controlled by small additions of a set retarder which does not adversely affect the strength properties of the cement. X-ray analysis and DTA have been used to identify the hydration products, interpret the strength data, and to compare the plaster of Paris activated cement with anhydrite activated slag cement.     

Thermal decomposition and pore structure of pure and doped stannic oxide gel

The surface properties of a stannic oxide gel and its thermal dehydration products obtained both in vacuo and in the presence of air in the temperature range 100–600°C have been examined by N₂ adsorption. Phase and structural changes have been followed by differential thermal analysis and X-ray diffractometry. Complete pore structure analysis showed that samples dehydrated at or below 250°C were microporous. Above 250°C the pores were found to widen with increase of temperature, the widening occurring concurrently with the crystallisation process. Doping with cations of lower valency (Li⁺ and Al³⁺) than the host cation (Sn⁴⁺) had little effect on the pore structure and specific surface area for the low temperature samples (≤250°), whereas at higher temperatures, e.g. 600°C, it increased the specific area remarkably. The dope ions produce oxygen vacancies and hinder or retard sintering in SnO₂.     

Cellular automaton-based algorithms for the dispersion of mobile wireless sensor networks

Due to the advent of sensor technology and its applications, mobile wireless sensor networks (MWSNs) have gained a significant amount of research interest. In a typical MWSN, sensors can move within the network. We develop a set of probabilistic and deterministic cellular automaton (CA)-based algorithms for motion planning problems in MWSNs. First, we consider a scenario where a group of sensors are deployed and they need to disperse in order to maximise the area covered by the network. In this variant of the problem we do not explicitly consider that the sensors should maintain the connectivity of the network while they move. Second, we consider a scenario where the sensors are initially randomly distributed and they need to disperse autonomously to both maximise the coverage of the network and maintain its connectivity. We carry out extensive simulations of both deterministic and randomised variants of the algorithms. For the first variant of the problem we compare our algorithms with one previous algorithm and find that our algorithm yields better network coverage than the earlier algorithm. We also find that probabilistic algorithms have better overall performance for the second variant. CA algorithms rely only on local information about the network and, hence, they can be used in practice for MWSN problems. On the other hand, locality of the algorithm implies that maintaining connectivity becomes a non-trivial problem.     

An investigation on wear behavior of UHMWPE/carbide composites at elevated temperatures

Ultra-high molecular weight polyethylene (UHMWPE) is extensively used in frictional applications due to its advanced wear resistance. This advanced polymer is reinforced with hard particulate fillers for further developments against wear conditions. Since elevated temperatures prevail in the service conditions, wear behavior of UHMWPE composites is an important issue for the engineering applications. In the present work, UHMWPE-based composites including silicon carbide (SiC) fillers were fabricated in a compression molding chamber. In the specimen preparation stage, molding pressure, filler amount, and filler particle size were varied to investigate the influence of these variables. Upon deciding the optimum parameters from the wear tests conducted at room temperature, the wear experiments were repeated for the optimum specimen at elevated temperatures, such as 40 and 60°C. According to the results, the wear behavior of the SiC/UHMWPE composites is heavily changed by the effect of elevated temperature. Adhesive effect is pronounced at elevated temperatures while the wear characteristics possess the abrasive effect in the sliding path. In addition, the composites exhibit an accelerated material loss as temperature increases during the frictional system.     

Deciding the Word Problem for Ground and Strongly Shallow Identities w.r.t. Extensional Symbols

Journal of Automated Reasoning - The word problem for a finite set of ground identities is known to be decidable in polynomial time using congruence closure, and this is also the case if some of...