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Found 6515 publications

A logic model for inference chains in expert systems

Publication Name: International Conference on Artificial Intelligence and Pattern Recognition 2007 Aipr 2007

Publication Date: 2007-12-01

Volume: Unknown

Issue: Unknown

Page Range: 243-248

Description:

This paper deals with the calculations performed in the reasoning process of rule-based expert systems, where inference chains are applied. It presents a logic model for representing the rules and the rule base of a given system. Also, the fact base of the same expert system is involved in the logic model. The proposed equivalent representation manifests itself in a logic network. After that, a four-valued logic algebra is introduced. This algebra is used for the calculations where forward chaining is carried out. Next, the notion of line-value justification is described. This operation is applied in the backward chaining process, also on the base of the previously introduced four-valued logic. The paper describes two exact algorithms which serve for the forward and backward chaining processes. These algorithms make it possible to be implemented by a computer program, resulting in an efficient inference engine of an expert system. The achieved result enhances the reliability and usability of the intelligent software systems which is extremely important in embedded environments.

Open Access: Yes

DOI: DOI not available

Body Mass and Aerobic Capacity are Robust Predictors of the 2000m Ergometer Rowing Performance: A Laboratory Study

Publication Name: International Journal of Kinesiology and Sports Science

Publication Date: 2025-01-01

Volume: 13

Issue: 2

Page Range: 78-85

Description:

Purpose: Predicting performance in sports competitions is a popular topic in research. However, only a few studies exist in rowing sports, which suggest that some anthropometric and performance indices might predict performance in various situations. Methods: This work expands past research by examining the effects of five anthropometric measures, such as body mass index (BMI), height, weight, fat, and muscle, and three performance indicators, such as aerobic capacity, maximum speed, and force, while also considering the training history of 38 elite rowers (Mage = 16.89 ± 1.85, range 14.7 to 22.6 years, 61% males) participating in a national championship. Results: Apart from BMI, all measures correlated statistically significantly with the 2000m rowing time. A bootstrapped forward multiple regression yielded the best model with only two predictors (R2 =.995), aerobic capacity and body mass, accounting for 99.5% variance in the 2000m rowing time. Conclusions: While the results support previous findings, such robust prediction has not been reported in the literature. We conjecture that the differences from other past works rest with the high-pressure 2000m performance preceding a national championship. If these findings could be replicated, their practical implication is substantial in preparatory training for rowing contests.

Open Access: Yes

DOI: 10.7575/aiac.ijkss.v.13n.2p.78

Localization in a Head-Related Transfer Function-based virtual audio synthesis using additional high-pass and low-pass filtering of sound sources

Publication Name: Acoustical Science and Technology

Publication Date: 2007-08-02

Volume: 28

Issue: 4

Page Range: 244-250

Description:

Listening tests were carried out for investigating the localization judgments of untrained subjects through equalized headphones and with HRTF synthesis. The investigation was made on the basis of the former 'Graphical User Interface for Blind Persons' project in order to determine the possibilities of a 2D virtual sound screen and headphone playback. 50 untrained subjects evaluated a virtual audio display in front of the listener using different horizontal and vertical resolutions on a 2D surface. A listening test using white and filtered noise signals was followed by a special investigation using simple high-pass and low-pass filtering of the original sound in order to increase correct vertical localization judgments. The simulation uses high-pass filtering for higher elevations and low-pass filtering for lower elevations in a 5 × 2 and a 3 × 3 spatial resolution. Results of the listening test will be presented and the efficiency of the filtering in correct localization judgments will be discussed. © 2007 The Acoustical Society of Japan.

Open Access: Yes

DOI: 10.1250/ast.28.244

A virtual screening framework based on the binding site selectivity for small molecule drug discovery

Publication Name: Computers and Chemical Engineering

Publication Date: 2024-05-01

Volume: 184

Issue: Unknown

Page Range: Unknown

Description:

Structure-based virtual screening of binding of candidate drug molecules is a topic of increasing interest in the discovery of small molecule drugs. As the same drug molecule may bind to different binding sites on a target protein, the binding site selectivity that is related to the binding tendency of candidate drug molecules to different binding sites after reaching the target protein need to be considered in sufficient details. In this work, a systematic and computer-aided virtual screening framework based on the binding site selectivity to screen candidate drug molecules in terms of their ability to bind on selected sites is presented. The framework integrates two machine learning (ML)-based models to predict the binding potential and binding selectivity to specific binding sites that are important for virtual screening of drug molecules. The details of the ML-based models together with the work-flow of the computer-aided virtual screening methods and the efficient and consistent integration of related drug design tools are presented. The applicability of this virtual screening framework is illustrated through a case study involving the screening for drug molecules as inhibitors to block the binding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to angiotensin converting enzyme 2 (ACE2), which is the target protein. The case study results point to identification of new candidate inhibitors with better binding site selectivity than two known potential inhibitors, Nilotinib and SSAA09E2.

Open Access: Yes

DOI: 10.1016/j.compchemeng.2024.108626

Resource savings, recycling and utilization, and energy transition: Introduction

Publication Name: Geoscience Frontiers

Publication Date: 2024-05-01

Volume: 15

Issue: 3

Page Range: Unknown

Description:

No description provided

Open Access: Yes

DOI: 10.1016/j.gsf.2024.101797

Dissipative dynamics in the free massive boson limit of the sine-Gordon model

Publication Name: Scipost Physics Core

Publication Date: 2022-01-01

Volume: 5

Issue: 1

Page Range: Unknown

Description:

We study the dissipative dynamics of one-dimensional fermions, described in terms of the sine-Gordon model in its free massive boson or semi-classical limit, while keeping track of forward scattering processes. The system is prepared in the gapped ground state, and then coupled to environment through local currents within the Lindblad formalism. The heating dynamics of the system is followed using bosonization. The single particle density matrix exhibits correlations between the left and right moving particles. While the density matrix of right movers and left movers is translationally invariant, the left-right sector is not, corresponding to a translational symmetry breaking charge density wave state. Asymptotically, the single particle density matrix decays exponentially with exponent proportional to -γt|x|∆2 where γ and ∆ are the dissipative coupling and the gap, respectively. The charge density wave order parameter decays exponentially in time with an interaction independent decay rate. The second Rényi entropy grows linearly with time and is essentially insensitive to the presence of the gap.

Open Access: Yes

DOI: 10.21468/SciPostPhysCore.5.1.004

On combination of wavelet transformation and stabilized KH interpolation for fuzzy inferences based on high dimensional sampled functions

Publication Name: Studies in Computational Intelligence

Publication Date: 2018-01-01

Volume: 758

Issue: Unknown

Page Range: 31-42

Description:

A new approach for inference based on treating sampled functions is presented. Sampled functions can be transformed into only a few points by wavelet analysis, thus the complete function is represented by these several discrete points. The finiteness of the teaching samples and the resulting sparse rule bases can be handled by fuzzy rule interpolation methods, like KH interpolation. Using SHDSL transmission performance prediction as an example, the simplification of inference problems based on large, sampled vectors by wavelet transformation and fuzzy rule interpolation applied on these vectors are introduced in this paper.

Open Access: Yes

DOI: 10.1007/978-3-319-74681-4_3

Approximation of the stiffness of laminate stacks of electric motors subjected to cyclic loads

Publication Name: Materialpruefung Materials Testing

Publication Date: 2023-08-01

Volume: 65

Issue: 8

Page Range: 1202-1208

Description:

Electric motors in automotive applications are subjected to high thermal and structural loads, while having strict requirements regarding dimensions, mass, and costs. The design of such motors requires sophisticated simulation models. The laminate stack in the rotor of such a motor is made of steel sheets and behaves transversally isotropic: the radial stiffness is equivalent to steel, and in the axial direction, it has a highly progressive nonlinear stiffness characteristic. The loading and unloading stiffness curves change from cycle to cycle when subjected to repetitive loads. In this paper, the usage of a single approximating curve to describe the longitudinal stiffness of the laminate stack is proposed. This approximation can be used in FEM models to reproduce the structural nonlinear behavior of such a laminate stack using a simpler approach than implementing the full loading and unloading curves in a material model, at a price of negligible loss of precision.

Open Access: Yes

DOI: 10.1515/mt-2022-0382

Understanding the Mechanisms of Fe Deficiency in the Rhizosphere to Promote Plant Resilience

Publication Name: Plants

Publication Date: 2023-05-01

Volume: 12

Issue: 10

Page Range: Unknown

Description:

One of the most significant constraints on agricultural productivity is the low availability of iron (Fe) in soil, which is directly related to biological, physical, and chemical activities in the rhizosphere. The rhizosphere has a high iron requirement due to plant absorption and microorganism density. Plant roots and microbes in the rhizosphere play a significant role in promoting plant iron (Fe) uptake, which impacts plant development and physiology by influencing nutritional, biochemical, and soil components. The concentration of iron accessible to these live organisms in most cultivated soil is quite low due to its solubility being limited by stable oxyhydroxide, hydroxide, and oxides. The dissolution and solubility rates of iron are also significantly affected by soil pH, microbial population, organic matter content, redox processes, and particle size of the soil. In Fe-limiting situations, plants and soil microbes have used active strategies such as acidification, chelation, and reduction, which have an important role to play in enhancing soil iron availability to plants. In response to iron deficiency, plant and soil organisms produce organic (carbohydrates, amino acids, organic acids, phytosiderophores, microbial siderophores, and phenolics) and inorganic (protons) chemicals in the rhizosphere to improve the solubility of poorly accessible Fe pools. The investigation of iron-mediated associations among plants and microorganisms influences plant development and health, providing a distinctive prospect to further our understanding of rhizosphere ecology and iron dynamics. This review clarifies current knowledge of the intricate dynamics of iron with the end goal of presenting an overview of the rhizosphere mechanisms that are involved in the uptake of iron by plants and microorganisms.

Open Access: Yes

DOI: 10.3390/plants12101945