SUBGOAL ORDERING AND GRANULARITY CONTROL FOR INCREMENTAL PLANNING

2007 ◽  
Vol 16 (04) ◽  
pp. 707-723 ◽  
Author(s):  
CHIH-WEI HSU ◽  
YIXIN CHEN ◽  
BENJAMIN W. WAH
Keyword(s):  
Grain Size ◽  
Study Strategies ◽  
Partial Orders ◽  
Experimental Results ◽  
Planning Problem ◽  
Solution Quality ◽  
Time Efficiency ◽  
Trade Offs ◽  
Incremental Planning

In this paper, we study strategies in incremental planning for ordering and grouping subproblems partitioned by the subgoals of a planning problem. To generate a rich set of partial orders for ordering subproblems, we propose an algorithm based on a relaxed plan that ignores the delete lists. The new algorithm considers both the initial and the goal states and can effectively order subgoals in such a way that greatly reduces the number of invalidations during incremental planning. We have also considered trade-offs between the granularity of the subgoal sets and the complexity of solving the overall planning problem. We propose an efficient strategy for dynamically adjusting the grain size in partitioning in order to minimize the total complexity. We further evaluate a redundant-ordering scheme that uses two different subgoal orders to improve the solution quality, without greatly sacrificing run-time efficiency. Experimental results on using Metric-FF, YAHSP, and LPG-TD-speed as the embedded planners in incremental planning show that our strategies are general for improving the time and quality of these planners across various benchmarks. Finally, we compare the performance of the three planners, the incremental versions using these planners as embedded planners, and SGPlan4.1.

scholarly journals Scientifically substantiated definition of quality optimum parameters for surface layer low-rigid shafts at centrifugal runningin

2016 ◽  
Vol 1 (6) ◽  
pp. 28-34
Author(s):  
С. Зайдес ◽  
S. Zaides ◽  
А. Горбунов ◽  
A. Gorbunov
Keyword(s):  
Grain Size ◽  
Surface Layer ◽  
Experimental Results ◽  
Cold Hardening ◽  
Layer Depth ◽  
Optimum Parameters ◽  
A Value ◽  
Basic Parameters ◽  
Definition Of

A surface layer and a cold-hardening depth as basic parameters ensuring quality of low-rigid shafts are analyzed. A value of an interference area depending on a grain size which is a criterion for the definition of strengthened layer depth is established. The experimental results on the definition of quality basic parameters for a surface layer at the strengthening for the depth of an interference area are shown.

scholarly journals Improving CNN-Based Pest Recognition with a Post-Hoc Explanation of XAI

2021 ◽  
Author(s):  
Ching-Ju Chen ◽  
Ling-Wei Chen ◽  
Chun-Hao Yang ◽  
Ya-Yu Huang ◽  
Yueh-Min Huang
Keyword(s):  
Data Processing ◽  
Model Identification ◽  
Experimental Results ◽  
Future Research ◽  
Visual Interpretation ◽  
Training Models ◽  
Trade Offs ◽  
Comparison Of The Results ◽  
Post Hoc

Abstract Deep learning is currently quite prevalent and is often used in image classification or object detection. This article adds emerging research on the use of explainable AI (XAI) in Tessaratoma papillosa pest identification and investigates the connotation and importance of XAI, interpretability classification standards, and neural network interpretation methods and compares the quality of interpretations between different approaches and various trade-offs. The experimental results include the data processing in the research, the establishment of training models, a comparison of the results and feature visualization methods, and the consequences of improving the training models. First, we analyzed the data processing methods of the dataset, trained the VGG16 model, and finally added a visual interpretation method to the model to visualize and explain the model identification results. The experimental results indicated that the best visual discrimination effect was obtained through eXplanation with Ranked Area Integrals (XRAI). In this study, XAI was used to obtain the factors contributing to incorrect predictions based on post-hoc explanations. Based on the inferenced result, we proposed an adjustment method for improving the model accuracy as a basis for future research to subsequently adjust and improve the model. It is hoped that the experimental results of this study can provide researchers in artificial intelligence useful information so that they can use XAI to acquire appropriate interpretations to correct recognition accuracy and drive the development of XAI.

A Political Economy Model of a Research University

2009 ◽  
pp. 132-143
Author(s):  
K. Sonin ◽  
I. Khovanskaya
Keyword(s):  
Organizational Structure ◽  
Information Structure ◽  
Research University ◽  
Hiring Decisions ◽  
Voting Rules ◽  
Economy Model ◽  
Trade Offs ◽  
Political Economic ◽  
Optimal Incentives

Hiring decisions are typically made by committees members of which have different capacity to estimate the quality of candidates. Organizational structure and voting rules in the committees determine the incentives and strategies of applicants; thus, construction of a modern university requires a political structure that provides committee members and applicants with optimal incentives. The existing political-economic model of informative voting typically lacks any degree of variance in the organizational structure, while political-economic models of organization typically assume a parsimonious information structure. In this paper, we propose a simple framework to analyze trade-offs in optimal subdivision of universities into departments and subdepartments, and allocation of political power.

Hybrid features prediction model of movie quality using Multi-machine learning techniques for effective business resource planning

2021 ◽  
Vol 40 (5) ◽  
pp. 9361-9382 ◽  
Author(s):  
Naeem Iqbal ◽  
Rashid Ahmad ◽  
Faisal Jamil ◽  
Do-Hyeun Kim
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Resource Planning ◽  
Experimental Results ◽  
Quality Prediction ◽  
Classification Models ◽  
Hybrid Features ◽  
Social Media Data ◽  
Media Data

Quality prediction plays an essential role in the business outcome of the product. Due to the business interest of the concept, it has extensively been studied in the last few years. Advancement in machine learning (ML) techniques and with the advent of robust and sophisticated ML algorithms, it is required to analyze the factors influencing the success of the movies. This paper presents a hybrid features prediction model based on pre-released and social media data features using multiple ML techniques to predict the quality of the pre-released movies for effective business resource planning. This study aims to integrate pre-released and social media data features to form a hybrid features-based movie quality prediction (MQP) model. The proposed model comprises of two different experimental models; (i) predict movies quality using the original set of features and (ii) develop a subset of features based on principle component analysis technique to predict movies success class. This work employ and implement different ML-based classification models, such as Decision Tree (DT), Support Vector Machines with the linear and quadratic kernel (L-SVM and Q-SVM), Logistic Regression (LR), Bagged Tree (BT) and Boosted Tree (BOT), to predict the quality of the movies. Different performance measures are utilized to evaluate the performance of the proposed ML-based classification models, such as Accuracy (AC), Precision (PR), Recall (RE), and F-Measure (FM). The experimental results reveal that BT and BOT classifiers performed accurately and produced high accuracy compared to other classifiers, such as DT, LR, LSVM, and Q-SVM. The BT and BOT classifiers achieved an accuracy of 90.1% and 89.7%, which shows an efficiency of the proposed MQP model compared to other state-of-art- techniques. The proposed work is also compared with existing prediction models, and experimental results indicate that the proposed MQP model performed slightly better compared to other models. The experimental results will help the movies industry to formulate business resources effectively, such as investment, number of screens, and release date planning, etc.

scholarly journals Characterizing Color Quality, Damage to Artwork, and Light Intensity of Multi-Primary LEDs for Museums

Heritage ◽  
2021 ◽  
Vol 4 (1) ◽  
pp. 188-197
Author(s):  
Dorukalp Durmus
Keyword(s):  
Energy Efficiency ◽  
Appearance Model ◽  
Light Sources ◽  
Great Flexibility ◽  
Oil Paintings ◽  
Damage Reduction ◽  
Output Variability ◽  
Color Quality ◽  
Trade Offs

Light causes damage when it is absorbed by sensitive artwork, such as oil paintings. However, light is needed to initiate vision and display artwork. The dilemma between visibility and damage, coupled with the inverse relationship between color quality and energy efficiency, poses a challenge for curators, conservators, and lighting designers in identifying optimal light sources. Multi-primary LEDs can provide great flexibility in terms of color quality, damage reduction, and energy efficiency for artwork illumination. However, there are no established metrics that quantify the output variability or highlight the trade-offs between different metrics. Here, various metrics related to museum lighting (damage, the color quality of paintings, illuminance, luminous efficacy of radiation) are analyzed using a voxelated 3-D volume. The continuous data in each dimension of the 3-D volume are converted to discrete data by identifying a significant minimum value (unit voxel). Resulting discretized 3-D volumes display the trade-offs between selected measures. It is possible to quantify the volume of the graph by summing unique voxels, which enables comparison of the performance of different light sources. The proposed representation model can be used for individual pigments or paintings with numerous pigments. The proposed method can be the foundation of a damage appearance model (DAM).

scholarly journals Public Administration and Governance for the SDGs: Navigating between Change and Stability

2021 ◽  
Vol 13 (11) ◽  
pp. 5914
Author(s):  
Louis Meuleman
Keyword(s):  
Public Administration ◽  
Policy Development ◽  
Governance Reform ◽  
Policy Coherence ◽  
Sector Reform ◽  
Eu Member States ◽  
Trade Offs ◽  
Strategic Policy ◽  
Research And Policy

This article highlights four key reform challenges regarding the quality of public administration and governance (PAG), aimed at increasing ‘SDG-readiness’ at all levels of administration, in a nexus characterized by complexity, volatility, pluriformity and uncertainty. Based on others’ research into how EU Member States institutionalize the implementation of the SDGs, a critical review of SDG-governance approaches, as well as a review paper on the management of the SDGs, it is concluded that that four priority areas could guide research and policy development to accelerate implementation of the 2030 Agenda. Firstly, to recognize that creating an effective public administration and governance is an important strategic policy area. Secondly, to begin with mission-oriented public administration and governance reform for SDG implementation, replacing the efficiency-driven public sector reform of the past decades. Thirdly, to apply culturally sensitive metagovernance to design, define and manage trade-offs and achieving synergies between SDGs and their targets. Fourthly, to start concerted efforts to improve policy coherence with a mindset beyond political, institutional, and mental ‘silos’.

scholarly journals X-ray diffraction analysis of kaolin M1 and M2 via the Williamson–Hall and Warren–Averbach methods

2021 ◽  
pp. 174751982098472
Author(s):  
Lalmi Khier ◽  
Lakel Abdelghani ◽  
Belahssen Okba ◽  
Djamel Maouche ◽  
Lakel Said
Keyword(s):  
Grain Size ◽  
High Temperature ◽  
Low Temperature ◽  
Diffraction Analysis ◽  
Mechanical Resistance ◽  
X Ray Diffraction ◽  
Integral Breadth ◽  
X Ray ◽  
Mullite Phase

Kaolin M1 and M2 studied by X-ray diffraction focus on the mullite phase, which is the main phase present in both products. The Williamson–Hall and Warren–Averbach methods for determining the crystallite size and microstrains of integral breadth β are calculated by the FullProf program. The integral breadth ( β) is a mixture resulting from the microstrains and size effect, so this should be taken into account during the calculation. The Williamson–Hall chart determines whether the sample is affected by grain size or microstrain. It appears very clearly that the principal phase of the various sintered kaolins, mullite, is free from internal microstrains. It is the case of the mixtures fritted at low temperature (1200 °C) during 1 h and also the case of the mixtures of the type chamotte cooks with 1350 °C during very long times (several weeks). This result is very significant as it gives an element of explanation to a very significant quality of mullite: its mechanical resistance during uses at high temperature remains.

scholarly journals Identification of the State of Electrical Appliances with the Use of a Pulse Signal Generator

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 673
Author(s):  
Augustyn Wójcik ◽  
Piotr Bilski ◽  
Robert Łukaszewski ◽  
Krzysztof Dowalla ◽  
Ryszard Kowalik
Keyword(s):  
Measurement System ◽  
Cross Correlation ◽  
Pulse Signal ◽  
Signal Generator ◽  
Experimental Results ◽  
The Novel ◽  
End User ◽  
Standard Classification ◽  
Electrical Appliance

The paper presents the novel HF-GEN method for determining the characteristics of Electrical Appliance (EA) operating in the end-user environment. The method includes a measurement system that uses a pulse signal generator to improve the quality of EA identification. Its structure and the principles of operation are presented. A method for determining the characteristics of the current signals’ transients using the cross-correlation is described. Its result is the appliance signature with a set of features characterizing its state of operation. The quality of the obtained signature is evaluated in the standard classification task with the aim of identifying the particular appliance’s state based on the analysis of features by three independent algorithms. Experimental results for 15 EAs categories show the usefulness of the proposed approach.

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