scholarly journals A Roadmap to Gradually Compare and Benchmark Description Logic Calculi

10.29007/tgc4 ◽  
2019 ◽  
Author(s):  
Fred Freitas
Keyword(s):  
Asymptotic Analysis ◽  
Description Logic ◽  
Basic Research ◽  
Detailed Comparison ◽  
Optimization Techniques ◽  
Cutting Edge ◽  
Memory Usage ◽  
Inference Methods

DL reasoners were developed with cutting-edge performance, implementing plenty of specific optimization techniques over tableaux-based methods, which took over the field. However, promising methods may have been neglected in such a scenario, in which the tough competition is often focused on gains through optimizations. Therefore, perhaps there is still room available for “basic research” on DL reasoning. The purpose of this work is to stimulate research on trying out DL calculi other than tableaux. Such endeavors should be carried out by making a careful, detailed comparison between tableaux and other inference methods in a systematic way: first starting with simpler languages (like ALC) without any optimizations. Then gradually including optimizations and comparing them; and continuing these interactive steps: enhancing language expressivity, including optimizations, and testing until reaching the most expressive DL fragments such as SROIQ. The comparison can also be done by in terms memory usage and algorithm asymptotic analysis, with worst and average cases, etc. The rationale is identifying whether there are fragments which are more suitable to certain inference methods, as well as which aspects or constructs (e.g., the costliest combinations, which usually involve inverses, nominals, equalities, etc) are sensitive to which calculus.

Optimization of Cutting Edge Truncation Depth for Ultrasonically Assisted Grinding to Finish Mirror Surface

2009 ◽  
Vol 76-78 ◽  
pp. 88-93 ◽  
Author(s):  
Keisuke Hara ◽  
Hiromi Isobe ◽  
Akira Kyusojin
Keyword(s):  
Ground Surface ◽  
Optimization Techniques ◽  
Cutting Edge ◽  
Mirror Surface ◽  
Skilled Workers ◽  
Ultrasonic Oscillation ◽  
Oscillation Effect ◽  
Grinding Conditions ◽  
Grinding Technique ◽  
Face Grinding

High precision mold grinding technique to obtain mirror surface is required which realizes minimization or omission of final polishing by skilled workers. In the previous reports, ultrasonic diamond grinding experiments were carried out to confirm ultrasonic oscillation effect for die steel face grinding. Smooth and glossy surfaces were obtained successfully and little abrasive worn out was found. In the above techniques require cutting edge truncation because the cutting edge shape of a tool affects the ground surface resulting from transcription of cutting edge. This paper describes optimization techniques for the cutting edge truncation of diamond electroplated tools which are used in ultrasonically assisted grinding. Experiments were carried out to confirm truncation effects on the ground surface and grinding force. It was confirmed that roughness was proportional to inverse of thrust force. Minimum roughness in grinding conditions were estimated from the proportional diagrams. The minimum roughness shows limit of roughness on an each grinding condition.

scholarly journals Optimised ExpTime Tableaux for𝒮ℋℐ𝒩over Finite Residuated Lattices

2014 ◽  
Vol 2014 ◽  
pp. 1-15
Author(s):  
Jian Huang ◽  
Xinye Zhao ◽  
Jianxing Gong
Keyword(s):  
Experimental Evaluation ◽  
Decision Procedure ◽  
Description Logic ◽  
Optimization Technique ◽  
Residuated Lattices ◽  
Optimization Techniques ◽  
Satisfiability Problem ◽  
Reasoning Algorithm ◽  
De Morgan Lattice

This study proposes to adopt a novel tableau reasoning algorithm for the description logic𝒮ℋℐ𝒩with semantics based on a finite residuated De Morgan lattice. The syntax, semantics, and logical properties of this logic are given, and a sound, complete, and terminating tableaux algorithm for deciding fuzzy ABox consistency and concept satisfiability problem with respect to TBox is presented. Moreover, based on extended and/or completion-forest with a series of sound optimization technique for checking satisfiability with respect to a TBox in the logic, a new optimized ExpTime (complexity-optimal) tableau decision procedure is presented here. The experimental evaluation indicates that the optimization techniques we considered result in improved efficiency significantly.

Proposal of Contour Line Model for High-Speed End Milling Simulation

2020 ◽  
Vol 14 (1) ◽  
pp. 38-45 ◽  
Author(s):  
Isamu Nishida ◽  
◽  
Keiichi Shirase
Keyword(s):  
Cutting Force ◽  
Cross Sections ◽  
High Speed ◽  
End Milling ◽  
Cutting Edge ◽  
Contour Line ◽  
Memory Usage ◽  
Line Model ◽  
Milling Simulation ◽  
Contour Lines

A contour line model for end milling simulation, which realizes high-speed arithmetic processing by reducing memory usage, is proposed. In this model, a 3-dimensional shape can be expressed by superimposing the contour lines of the cross-sections obtained by dividing the workpiece along any axial direction. Therefore, the memory usage is reduced compared to a Z-map model or a voxel model as the interior information of the object can be eliminated. The contour line model can also be applied to complicated shapes having overhangs. Furthermore, cutting volume can be calculated from the interference area enclosed by two contour lines of the workpiece and the tool cross-sections. The workpiece shape can be changed by eliminating the interference area. In the contour line model, cutting force can also be predicted with an instantaneous rigid force model using the uncut chip thickness for each cutting edge from the positional relationship between the interference area and the cutting edge. To validate the proposed model, cutting experiments were conducted, which confirmed that the predicted machining shape had good agreement with the actual machined shape. Furthermore, it was confirmed that the cutting force can be predicted accurately.

Efficient Algorithms for Mining Frequent Patterns from Sparse and Dense Databases

2015 ◽  
Vol 24 (2) ◽  
pp. 181-197
Author(s):  
Lan Vu ◽  
Gita Alaghband
Keyword(s):  
Execution Time ◽  
Pattern Mining ◽  
Frequent Pattern Mining ◽  
Optimization Techniques ◽  
Frequent Pattern ◽  
Frequent Patterns ◽  
Memory Usage ◽  
New Approach ◽  
Support Threshold ◽  
Best Fit

AbstractIn this article, we present a new approach for frequent pattern mining (FPM) that runs fast for both sparse and dense databases. Two algorithms, FEM and DFEM, based on our approach are also introduced. FEM applies a fixed threshold as the condition for switching between the two mining strategies; meanwhile, DFEM adopts this threshold dynamically at runtime to best fit the characteristics of the database during the mining process, especially when minimum support threshold is low. Additionally, we present optimization techniques for the proposed algorithms to speed the mining process, reduce the memory usage, and optimize the I/O cost. We also analyze in depth the performance of FEM and DFEM and compare them with several existing algorithms. The experimental results show that FEM and DFEM achieve a significant improvement in execution time and consume less memory than many popular FPM algorithms including the well-known Apriori, FP-growth, and Eclat.

scholarly journals HRI Malta 2017—Cutting Edge Research in Homeopathy: HRI's Third International Research Conference in Malta

Homeopathy ◽  
2017 ◽  
Vol 107 (01) ◽  
pp. 050-054
Author(s):  
Angelina Mosley ◽  
E. Roberts ◽  
Hazel Partington ◽  
Katharina Gaertner ◽  
Peter Fisher ◽  
...  
Keyword(s):  
Conference Report ◽  
Basic Research ◽  
Research Community ◽  
Cutting Edge ◽  
Diverse Range ◽  
Scientific Advisory Committee ◽  
The Third ◽  
Veterinary Research ◽  
Oral Presentations ◽  
Memorable Event

AbstractThe third international conference on “Cutting Edge Research in Homeopathy” organised by the Homeopathy Research Institute (HRI) was held on the inspiring and historic island of Malta from 9th to 11th of June, 2017. One hundred and two abstracts underwent peer review by the HRI Scientific Advisory Committee and external experts to produce the programme of 36 oral presentations and 37 posters, presented by researchers from 19 countries. The 2.5-day programme covered a diverse range of topics, including quantitative and qualitative clinical research, basic research, veterinary research, and provings. These intensive plenary and parallel sessions were interspersed with multiple opportunities for delegates to discuss and exchange ideas, in particular through interactive panel discussions and a pre-conference workshop. The continuing commitment of the homeopathy research community to generate high-quality studies in this rapidly evolving field was clear. In this conference report, we present highlights from this memorable event.

A Metastasis Suppressor Pt-Dendrimer Nanozyme for the Alleviation of Glioblastoma

2021 ◽  
Author(s):  
Jong Min An ◽  
Youngwon Ju ◽  
Jeong Hee Kim ◽  
Hyein Lee ◽  
Yuna Jung ◽  
...  
Keyword(s):  
Translational Medicine ◽  
Basic Research ◽  
Cutting Edge ◽  
Metastasis Suppressor ◽  
Biological Applications ◽  
Enzymatic Characteristics ◽  
Natural Enzyme

Nanozymes are nanostructure-based materials which mimic the enzymatic characteristics of natural enzyme. Biological applications of nanozymes have been highlighted in basic research, industry, and translational medicine as a new cutting-edge...

scholarly journals Cone Semantics for Logics with Negation

2020 ◽  
Author(s):  
Özgür Lütfü Özçep ◽  
Mena Leemhuis ◽  
Diedrich Wolter
Keyword(s):  
Machine Learning ◽  
Knowledge Representation ◽  
Vector Space ◽  
Description Logic ◽  
Geometric Model ◽  
Optimization Techniques ◽  
Conic Optimization ◽  
Classical Sense ◽  
Cone Model ◽  
Representation Techniques

This paper presents an embedding of ontologies expressed in the ALC description logic into a real-valued vector space, comprising restricted existential and universal quantifiers, as well as concept negation and concept disjunction. Our main result states that an ALC ontology is satisfiable in the classical sense iff it is satisfiable by a partial faithful geometric model based on cones. The line of work to which we contribute aims to integrate knowledge representation techniques and machine learning. The new cone-model of ALC proposed in this work gives rise to conic optimization techniques for machine learning, extending previous approaches by its ability to model full ALC.

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