scholarly journals Investigating the PageRank and sequence prediction based approaches for next page prediction

2021 ◽  
Vol 11 (3) ◽  
pp. 2229
Author(s):  
Nguyen Thon Da ◽  
Tan Hanh
Keyword(s):  
Standard Method ◽  
Research Area ◽  
Experimental Results ◽  
Sequence Database ◽  
Sequence Prediction ◽  
Time Performance ◽  
The Right

Discovering unseen patterns from web clickstream is an upcoming research area. One of the meaningful approaches for making predictions is using sequence prediction that is typically the improved compact prediction tree (CPT+). However, to increase this method's effectiveness, combining it with at least other methods is necessary. This work investigates such PageRank-based methods related to sequence prediction as All-K-Markov, DG, Markov 1st, CPT, CPT+. The experimental results proved that the integration of CPT+ and PageRank is the right solution for next page prediction in terms of accuracy, which is more than a standard method of approximately 0.0621%. Still, the size of the newly created sequence database is reduced up to 35%. Furthermore, our proposed solution has an accuracy that is much higher than other ones. It is intriguing for the next phase (testing one) to make the next page prediction in terms of time performance.

Wavelets as activation functions in Neural Networks

2021 ◽  
pp. 1-11
Author(s):  
Oscar Herrera ◽  
Belém Priego
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
High Performance ◽  
Research Area ◽  
Experimental Results ◽  
Activation Functions ◽  
Hyperbolic Tangent ◽  
Open Research ◽  
Bounded Functions

Traditionally, a few activation functions have been considered in neural networks, including bounded functions such as threshold, sigmoidal and hyperbolic-tangent, as well as unbounded ReLU, GELU, and Soft-plus, among other functions for deep learning, but the search for new activation functions still being an open research area. In this paper, wavelets are reconsidered as activation functions in neural networks and the performance of Gaussian family wavelets (first, second and third derivatives) are studied together with other functions available in Keras-Tensorflow. Experimental results show how the combination of these activation functions can improve the performance and supports the idea of extending the list of activation functions to wavelets which can be available in high performance platforms.

Research on Safety Vehicle Distance Recognition Based on Stereo Vision and DSP

2013 ◽  
Vol 333-335 ◽  
pp. 805-810 ◽  
Author(s):  
Rong Bao Chen ◽  
Ning Li ◽  
Hua Feng Xiao ◽  
Wei Hou
Keyword(s):  
Stereo Vision ◽  
Traffic Safety ◽  
Traffic Accidents ◽  
Intelligent Transportation ◽  
Research Area ◽  
Measurement Range ◽  
Vehicle Speed ◽  
Target Vehicle ◽  
Operation Rate ◽  
The Right

With the development of economy, there are an increasing number of cars as well as traffic accidents, thus intensifying the need to take measures to reduce traffic accidents and protect the safety of life and property. Vehicle distance is one of the most important indexes of traffic safety. The measurement of safety vehicle distance has become an increasingly hot research area of intelligent transportation. Through analyzing the basic principle of stereo vision and calibrating the parameters of the CCD sensors both inside and outside, this paper comes up with a method to measure the former vehicle distance based on stereo vision and DSP. Once the vehicle speed and distance form a non-security association, it will give a warning, and upload data or force speed-limiting. According to the different coordinates of the obtained images of the target vehicle from the left and the right sensor, this method can identify feature points, calculate distance to the target vehicle, and analyze the security of vehicle distance. The experimental results show that this method has wide measurement range, high measurement accuracy, and fast operation rate, thus it can meet the actual needs of the measurement of safe vehicle distance in intelligent transportation.

A Visual Saliency Detection Approach by Fusing Low-Level Priors With High-Level Priors

2019 ◽  
Vol 9 (3) ◽  
pp. 23-37
Author(s):  
Monika Singh ◽  
Anand Singh Singh Jalal ◽  
Ruchira Manke ◽  
Aamir Khan
Keyword(s):  
Minimum Distance ◽  
Saliency Detection ◽  
Visual Saliency ◽  
Research Area ◽  
Experimental Results ◽  
Low Level ◽  
Detection Approach ◽  
Art Methods ◽  
High Level ◽  
Visual Saliency Detection

Saliency detection has always been a challenging and interesting research area for researchers. The existing methodologies either focus on foreground regions or background regions of an image by computing low-level features. However, considering only low-level features did not produce worthy results. In this paper, low-level features, which are extracted using super pixels, are embodied with high-level priors. The background features are assumed as the low-level prior due to the similarity in the background areas and boundary of an image which are interconnected and have minimum distance in between them. High-level priors such as location, color, and semantic prior are incorporated with low-level prior to spotlight the salient area in the image. The experimental results illustrate that the proposed approach outperform the sate-of-the-art methods.

Fuzzy Clustering with Repulsive Prototypes

2010 ◽  
pp. 332-346
Author(s):  
Frank Rehm ◽  
Roland Winkler ◽  
Rudolf Kruse
Keyword(s):  
Data Analysis ◽  
Fuzzy Clustering ◽  
Experimental Results ◽  
Number Of Clusters ◽  
Fuzzy C Means ◽  
Analysis Process ◽  
Fuzzy C Means Clustering ◽  
The Right

A well known issue with prototype-based clustering is the user’s obligation to know the right number of clusters in a dataset in advance or to determine it as a part of the data analysis process. There are different approaches to cope with this non-trivial problem. This chapter follows the approach to address this problem as an integrated part of the clustering process. An extension to repulsive fuzzy c-means clustering is proposed equipping non-Euclidean prototypes with repulsive properties. Experimental results are presented that demonstrate the feasibility of the authors’ technique.

scholarly journals Evaluation of Bilateral Asymmetry in the Humerus of Human Skeletal Specimen

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Samuel S. Dare ◽  
Godfery Masilili ◽  
Kintu Mugagga ◽  
Peter E. Ekanem
Keyword(s):  
Research Area ◽  
Important Research ◽  
Biomedical Sciences ◽  
Bilateral Asymmetry ◽  
Makerere University ◽  
Geographical Regions ◽  
Humeral Torsion ◽  
Important Research Area ◽  
The Right ◽  
Geographical Locations

Several studies have established a relationship between morphological and behavioral asymmetry making investigations of bilateral bone asymmetry an attractive and important research area. The purpose of this study was to investigate bilateral asymmetry patterns of skeletal specimen from five geographical locations (Rwanda, Burundi, Congo, Kenya, and Uganda) at Galloway Osteological Collection, Department of Anatomy, School of Biomedical Sciences, Makerere University College of Health Sciences. The angle of torsion and retroversion, mid-shaft circumference, length, and weight of 232 pairs of humeri were determined. A Torsiometer was used to measure the angle of torsion in degrees according to Krahl and Evans 1945, a tape was used to measure the mid-shaft circumference at the level of the apex of the deltoid V, and the length in cm was determined. An osteometric board was used to measure the length of the humerus in centimeters. A weighing balance was used to measure the weight of the humerus in grams. The analysis of humeral asymmetry with respect to parameters of the human skeletal specimen at the Galloway Osteological Collection Mulago revealed bilateral asymmetrical status observed in the angle of torsion, length, weight, and mid-shaft circumference. Our result mostly showed lateralization to the right in all the parameters investigated except the torsion angle which is to the left. Our investigation revealed that humeral torsion is inversely proportional to weight, length, and mid-shaft circumference of the humerus. This study established the existence of bilateral asymmetries in the humeri of all the geographical regions investigated with more asymmetry observed in the male compared with the female.

Web Form Entrance Detection and Automatic Form Filling

2013 ◽  
Vol 380-384 ◽  
pp. 2712-2715
Author(s):  
Wen Qian Shang
Keyword(s):  
Research Area ◽  
Deep Web ◽  
Experimental Results ◽  
Web Pages ◽  
Information Mining ◽  
Form Analysis ◽  
Entire Process ◽  
Web Information

At present, deep web information mining is a considerably potential research area. How to get this massive and valuable information hidden after the database is need to be studied further. So this paper presents an approach that includes web pages analysis, getting forms, form analysis, automatic form filling, automatic form submission and acquiring returning pages. The aim is to let the computer automatically complete this process. The experimental results show the feasibility of this method. It can automatically complete the entire process.

The Algorithm of Sense Disambiguation Based on Bayesian Model

2013 ◽  
Vol 427-429 ◽  
pp. 1879-1882
Author(s):  
Chun Xiang Zhang ◽  
Xue Yao Gao ◽  
Zhi Mao Lu
Keyword(s):  
Pattern Recognition ◽  
Bayesian Model ◽  
Ambiguous Word ◽  
Experimental Results ◽  
Accuracy Rate ◽  
Part Of Speech ◽  
Sense Disambiguation ◽  
The Right

Sense disambiguation is an important problem in pattern recognition. In this paper, a new algorithm of sense disambiguation is proposed, in which part-of-speech tags of the left word and the right word around the ambiguous word are extracted as discriminative features. At the same time, the bayesian model is selected as the sense disambiguation classifier and it is built based on discriminative features. The architecture of sense classification is given. The new algorithm is trained on sense-annotated corpus. Then it is used to determine its sense category. Experimental results show that the accuracy rate of disambiguation arrives at 60%.

A Parallel Algorithm for Mining Non-Redundant Recurrent Rules from a Sequence Database

2019 ◽  
Vol 23 (5) ◽  
pp. 956-961
Author(s):  
Seung-Yong Yoon ◽  
◽  
Hirohisa Seki
Keyword(s):  
Parallel Algorithm ◽  
Processing Time ◽  
Experimental Results ◽  
Task Parallelism ◽  
Sequence Database ◽  
Computation Cost ◽  
Software Specification ◽  
Specification And Verification

We propose a parallel algorithm for mining non-redundant recurrent rules from a sequence database. Recurrent rules, proposed by Lo et al. [1], can express “Whenever a series of precedent events occurs, eventually a series of consequent events occurs,” and they have shown the usefulness of recurrent rules in various domains, including software specification and verification. Although some algorithms such as NR3 have been proposed, mining non-redundant recurrent rules still requires considerable processing time. To reduce the computation cost, we present a parallel approach to mining non-redundant recurrent rules, which fully utilizes the task-parallelism in NR3. We also give some experimental results, which show the effectiveness of our proposed method.

Strength of Composite Laminated Bolted Joint Subjected to a Clamping Force

2006 ◽  
Vol 326-328 ◽  
pp. 1777-1780
Author(s):  
Jin Ho Choi ◽  
Young Hwan Lee ◽  
Jin Hwe Kweon ◽  
Woo Seong Che
Keyword(s):  
Composite Structures ◽  
Research Area ◽  
Experimental Results ◽  
Clamping Force ◽  
Bolted Joint ◽  
Important Research ◽  
Index Method ◽  
Area Index ◽  
Composite Joint ◽  
Important Research Area

As these composites have become more popular, composite joint design has become a very important research area, as these joints are often the weakest parts of composite structures. In this paper, the strength of a composite laminated bolted joint being subjected to a clamping force was tested and predicted using the FAI (Failure Area Index) method. The strengths of composite joints subjected to clamping forces on different geometric shapes and dimensions were predicted using the FAI method, and the results were compared with experimental results. From the tests and analyses, the strength of a given composite laminated bolted joint subjected to a clamping force could be predicted within 22.5% via the FAI method.

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