A new approach based on graph matching and evolutionary approach for sport scheduling problem

2020 ◽  
pp. 1-16
Author(s):  
Meriem Khelifa ◽  
Dalila Boughaci ◽  
Esma Aïmeur
Keyword(s):  
Graph Matching ◽  
State Of The Art ◽  
Travel Cost ◽  
Round Robin ◽  
New Approach ◽  
Traveling Tournament Problem ◽  
Significant Interest ◽  
National League ◽  
Better Than

The Traveling Tournament Problem (TTP) is concerned with finding a double round-robin tournament schedule that minimizes the total distances traveled by the teams. It has attracted significant interest recently since a favorable TTP schedule can result in significant savings for the league. This paper proposes an original evolutionary algorithm for TTP. We first propose a quick and effective constructive algorithm to construct a Double Round Robin Tournament (DRRT) schedule with low travel cost. We then describe an enhanced genetic algorithm with a new crossover operator to improve the travel cost of the generated schedules. A new heuristic for ordering efficiently the scheduled rounds is also proposed. The latter leads to significant enhancement in the quality of the schedules. The overall method is evaluated on publicly available standard benchmarks and compared with other techniques for TTP and UTTP (Unconstrained Traveling Tournament Problem). The computational experiment shows that the proposed approach could build very good solutions comparable to other state-of-the-art approaches or better than the current best solutions on UTTP. Further, our method provides new valuable solutions to some unsolved UTTP instances and outperforms prior methods for all US National League (NL) instances.

Neighborhood Evaluation in Recommender Systems Using the Realization Based Entropy Approach

2014 ◽  
Vol 1 (4) ◽  
pp. 34-50
Author(s):  
Roee Anuar ◽  
Yossi Bukchin ◽  
Oded Maimon ◽  
Lior Rokach
Keyword(s):  
Recommender Systems ◽  
Entropy Measure ◽  
Continuous Data ◽  
System Evaluation ◽  
Rating Data ◽  
New Approach ◽  
Selection Of ◽  
Classical Entropy ◽  
Better Than

The task of a recommender system evaluation has often been addressed in the literature, however there exists no consensus regarding the best metrics to assess its performance. This research deals with collaborative filtering recommendation systems, and proposes a new approach for evaluating the quality of neighbor selection. It theorizes that good recommendations emerge from good selection of neighbors. Hence, measuring the quality of the neighborhood may be used to predict the recommendation success. Since user neighborhoods in recommender systems are often sparse and differ in their rating range, this paper designs a novel measure to asses a neighborhood quality. First it builds the realization based entropy (RBE), which presents the classical entropy measure from a different angle. Next it modifies the RBE and propose the realization based distance entropy (RBDE), which considers also continuous data. Using the RBDE, it finally develops the consent entropy, which takes into account the absence of rating data. The paper compares the proposed approach with common approaches from the literature, using several recommendation evaluation metrics. It presents offline experiments using the Netflix database. The experimental results confirm that consent entropy performs better than commonly used metrics, particularly with high sparsity neighborhoods. This research is supported by The Israel Science Foundation, Grant #1362/10. This research is supported by NHECD EC, Grant #218639.

scholarly journals Learning to Make Inferences in a Semantic Parsing Task

2016 ◽  
Vol 4 ◽  
pp. 155-168
Author(s):  
Kyle Richardson ◽  
Jonas Kuhn
Keyword(s):  
State Of The Art ◽  
Background Knowledge ◽  
Semantic Representations ◽  
Semantic Parsing ◽  
New Approach ◽  
Textual Entailment ◽  
High Level

We introduce a new approach to training a semantic parser that uses textual entailment judgements as supervision. These judgements are based on high-level inferences about whether the meaning of one sentence follows from another. When applied to an existing semantic parsing task, they prove to be a useful tool for revealing semantic distinctions and background knowledge not captured in the target representations. This information is used to improve the quality of the semantic representations being learned and to acquire generic knowledge for reasoning. Experiments are done on the benchmark Sportscaster corpus (Chen and Mooney, 2008), and a novel RTE-inspired inference dataset is introduced. On this new dataset our method strongly outperforms several strong baselines. Separately, we obtain state-of-the-art results on the original Sportscaster semantic parsing task.

scholarly journals A Novel Mesh Quality Improvement Method for Boundary Elements

2012 ◽  
Vol 2012 ◽  
pp. 1-13
Author(s):  
Hou-lin Liu ◽  
Cui Dai ◽  
Liang Dong ◽  
Ming-gao Tan
Keyword(s):  
Topology Optimization ◽  
Weight Coefficient ◽  
Mesh Quality ◽  
Practical Application ◽  
New Approach ◽  
Discrete Surfaces ◽  
Improvement Method ◽  
Quality Improvement Method ◽  
Better Than

In order to improve the boundary mesh quality while maintaining the essential characteristics of discrete surfaces, a new approach combining optimization-based smoothing and topology optimization is developed. The smoothing objective function is modified, in which two functions denoting boundary and interior quality, respectively, and a weight coefficient controlling boundary quality are taken into account. In addition, the existing smoothing algorithm can improve the mesh quality only by repositioning vertices of the interior mesh. Without destroying boundary conformity, bad elements with all their vertices on the boundary cannot be eliminated. Then, topology optimization is employed, and those elements are converted into other types of elements whose quality can be improved by smoothing. The practical application shows that the worst elements can be eliminated and, with the increase of weight coefficient, the average quality of boundary mesh can also be improved. Results obtained with the combined approach are compared with some common approach. It is clearly shown that it performs better than the existing approach.

Fusion of Underwater Image Enhancement and Restoration

2019 ◽  
Vol 34 (03) ◽  
pp. 2054007 ◽  
Author(s):  
Rajni Sethi ◽  
Sreedevi Indu
Keyword(s):  
Image Enhancement ◽  
State Of The Art ◽  
Input Image ◽  
Laplacian Pyramid ◽  
Novel Technique ◽  
Underwater Image ◽  
Single Input ◽  
Color Cast ◽  
Better Than

Optical properties of water distort the quality of underwater images. Underwater images are characterized by poor contrast, color cast, noise and haze. These images need to be pre-processed so as to get some information. In this paper, a novel technique named Fusion of Underwater Image Enhancement and Restoration (FUIER) has been proposed which enhances as well as restores underwater images with a target to act on all major issues in underwater images, i.e. color cast removal, contrast enhancement and dehazing. It generates two versions of the single input image and these two versions are fused using Laplacian pyramid-based fusion to get the enhanced image. The proposed method works efficiently for all types of underwater images captured in different conditions (turbidity, depth, salinity, etc.). Results obtained using the proposed method are better than those for state-of-the-art methods.

scholarly journals GaN-Based Materials for Blue Emitting Device Structures Grown in Multiwafer Planetary® Reactors

1998 ◽  
Vol 3 ◽  
Author(s):  
O. Schoen ◽  
D. Schmitz ◽  
M. Heuken ◽  
Holger Juergensen ◽  
M. D. Bremser
Keyword(s):  
State Of The Art ◽  
Laser Action ◽  
Optically Pumped ◽  
Free Electrons ◽  
Optically Pumped Laser ◽  
Wavelength Standard ◽  
Device Structures ◽  
Layer Resistance ◽  
Better Than

Using optimised growth processes for an AIX 2000 HT Planetary® Reactor a high material quality and high potential device yield are demonstrated. Doping levels for GaN single layers from 1·1020 cm−3 free electrons to semi-insulating to 1·1018 cm−3 free holes with state-of-the-art layer resistance uniformities especially for n-type layers are shown. Both AlGaN and GaInN with composition homogeneities of better than 1 nm photoluminescence peak-wavelength standard deviation are displayed. Finally, examination of optically pumped laser action in simple double-hetero structures is quoted to prove the quality of the material.

Simulating SST Teleconnections to Africa: What is the State of the Art?

2013 ◽  
Vol 26 (15) ◽  
pp. 5397-5418 ◽  
Author(s):  
David P. Rowell
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Coupled Model ◽  
The State ◽  
Sub Saharan Africa ◽  
Intercomparison Project ◽  
Rainfall Anomalies ◽  
Sub Saharan ◽  
Better Than

Abstract This study provides an overview of the state of the art of modeling SST teleconnections to Africa and begins to investigate the sources of error. Data are obtained from the Coupled Model Intercomparison Project (CMIP) archives, phases 3 and 5 (CMIP3 and CMIP5), using the “20C3M” and “historical” coupled model experiments. A systematic approach is adopted, with the scope narrowed to six large-scale regions of sub-Saharan Africa within which seasonal rainfall anomalies are reasonably coherent, along with six SST modes known to affect these regions. No significant nonstationarity of the strength of these 6 × 6 teleconnections is found in observations. The capability of models to represent each teleconnection is then assessed (whereby half the teleconnections have observed SST–rainfall correlations that differ significantly from zero). A few of these teleconnections are found to be relatively easy to model, while a few more pose substantial challenges to models and many others exhibit a wide variety of model skill. Furthermore, some models perform consistently better than others, with the best able to at least adequately simulate 80%–85% of the 36 teleconnections. No improvement is found between CMIP3 and CMIP5. Analysis of atmosphere-only simulations suggests that the coupled model teleconnection errors may arise primarily from errors in their SST climatology and variability, although errors in the atmospheric component of teleconnections also play a role. Last, no straightforward relationship is found between the quality of a model's teleconnection to Africa and its SST or rainfall biases or its resolution. Perhaps not surprisingly, the causes of these errors are complex, and will require considerable further investigation.

scholarly journals A Novel AMR-WB Speech Steganography Based on Diameter-Neighbor Codebook Partition

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Junhui He ◽  
Junxi Chen ◽  
Shichang Xiao ◽  
Xiaoyu Huang ◽  
Shaohua Tang
Keyword(s):  
State Of The Art ◽  
Experimental Results ◽  
Covert Communication ◽  
Embedding Capacity ◽  
The Real ◽  
Speech Codec ◽  
Speech Steganography ◽  
Statistical Steganalysis ◽  
Better Than

Steganography is a means of covert communication without revealing the occurrence and the real purpose of communication. The adaptive multirate wideband (AMR-WB) is a widely adapted format in mobile handsets and is also the recommended speech codec for VoLTE. In this paper, a novel AMR-WB speech steganography is proposed based on diameter-neighbor codebook partition algorithm. Different embedding capacity may be achieved by adjusting the iterative parameters during codebook division. The experimental results prove that the presented AMR-WB steganography may provide higher and flexible embedding capacity without inducing perceptible distortion compared with the state-of-the-art methods. With 48 iterations of cluster merging, twice the embedding capacity of complementary-neighbor-vertices-based embedding method may be obtained with a decrease of only around 2% in speech quality and much the same undetectability. Moreover, both the quality of stego speech and the security regarding statistical steganalysis are better than the recent speech steganography based on neighbor-index-division codebook partition.

FluidC+: A novel community detection algorithm based on fluid propagation

2019 ◽  
Vol 30 (04) ◽  
pp. 1950021
Author(s):  
Jinfang Sheng ◽  
Kai Wang ◽  
Zejun Sun ◽  
Jie Hu ◽  
Bin Wang ◽  
...  
Keyword(s):  
Community Detection ◽  
Real World ◽  
Seed Set ◽  
State Of The Art ◽  
Ground Truth ◽  
Detection Algorithm ◽  
Original Algorithm ◽  
Community Detection Algorithm ◽  
Better Than

In recent years, community detection has gradually become a hot topic in the complex network data mining field. The research of community detection is helpful not only to understand network topology structure but also to explore network hiding function. In this paper, we improve FluidC which is a novel community detection algorithm based on fluid propagation, by ameliorating the quality of seed set based on positive feedback and determining the node update order. We first summarize the shortcomings of FluidC and analyze the reasons result in these drawbacks. Then, we took some effective measures to overcome them and proposed an efficient community detection algorithm, called FluidC+. Finally, experiments on the generated network and real-world network show that our method not only greatly improves the performance of the original algorithm FluidC but also is better than many state-of-the-art algorithms, especially in the performance on real-world network with ground truth.

scholarly journals Low-Light Image Enhancement Based on Multi-Path Interaction

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 4986
Author(s):  
Bai Zhao ◽  
Xiaolin Gong ◽  
Jian Wang ◽  
Lingchao Zhao
Keyword(s):  
Color Image ◽  
State Of The Art ◽  
Interaction Network ◽  
Feature Representation ◽  
Uniform Illumination ◽  
Feature Maps ◽  
Low Light ◽  
Low Contrast ◽  
Better Than

Due to the non-uniform illumination conditions, images captured by sensors often suffer from uneven brightness, low contrast and noise. In order to improve the quality of the image, in this paper, a multi-path interaction network is proposed to enhance the R, G, B channels, and then the three channels are combined into the color image and further adjusted in detail. In the multi-path interaction network, the feature maps in several encoding–decoding subnetworks are used to exchange information across paths, while a high-resolution path is retained to enrich the feature representation. Meanwhile, in order to avoid the possible unnatural results caused by the separation of the R, G, B channels, the output of the multi-path interaction network is corrected in detail to obtain the final enhancement results. Experimental results show that the proposed method can effectively improve the visual quality of low-light images, and the performance is better than the state-of-the-art methods.

Visual enhancement of brain cancer MRI using multiscale dyadic filter and Hilbert transformation

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Ankit Vidyarthi
Keyword(s):  
Decision Making ◽  
Medical Images ◽  
Spectral Information ◽  
Mr Images ◽  
Mr Image ◽  
New Approach ◽  
Visual Enhancement ◽  
Signal Image ◽  
Better Than

AbstractThe quality of the medical image plays a major role in decision making by the radiologists. There exists a visual differentiation between the normal scene color images and medical images. Due to the low illumination and unavailability of the color parameter, medical images require more attention by radiologists for decision making. In this paper a new approach is proposed that enhances the quality of the Magnetic Resonance (MR) images. Proposed approach uses the spectral information present in form of Amplitude and Frequency within the MR image slices for an enhancement. The extracted enhanced spectral information gives better visualization as compared with original signal image generated from MR scanner. The quantitative analysis of the proposed approach suggests that the new method is far better than the traditional state-of-art image enhancement methods.

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