The novel algorithm of bus-cluster phenomenon

2016 ◽  
Author(s):  
Kai Yang ◽  
Wanggen Wan ◽  
Guoliang Chen
Keyword(s):  
The Novel ◽  
Cluster Phenomenon ◽  
Novel Algorithm

Novel Algorithmic Approach to Deciphering Rovash Inscriptions

2015 ◽  
pp. 7222-7233 ◽  
Author(s):  
Loránd Lehel Tóth ◽  
Raymond Pardede ◽  
Gábor Hosszú
Keyword(s):  
Experimental Results ◽  
The Novel ◽  
Statistical Probability ◽  
Algorithmic Approach ◽  
Topological Parameters ◽  
Novel Method ◽  
Novel Algorithm

The article presents a method to decipher Rovash inscriptions made by the Szekelys in the 15th-18th centuries. The difficulty of the deciphering work is that a large portion of the Rovash inscriptions contains incomplete words, calligraphic glyphs or grapheme errors. Based on the topological parameters of the undeciphered symbols registered in the database, the presented novel algorithm estimates the meaning of the inscriptions by the matching accuracies of the recognized graphemes and gives a statistical probability for deciphering. The developed algorithm was implemented in software, which also contains a built-in dictionary. Based on the dictionary, the novel method takes into account the context in identifying the meaning of the inscription. The proposed algorithm offers one or more words in a different random values as a result, from which users can select the relevant one. The article also presents experimental results, which demonstrate the efficiency of method.

scholarly journals Learning and Planning Based on Merged Experience from Multiple Situations for a Service Robot

2018 ◽  
Vol 8 (10) ◽  
pp. 1832
Author(s):  
Zhixian Chen ◽  
Baoliang Zhao ◽  
Shijia Zhao ◽  
Ying Hu ◽  
Jianwei Zhang
Keyword(s):  
Robot Learning ◽  
Physical Experiment ◽  
Planning Method ◽  
Service Robot ◽  
The Novel ◽  
Changing Environment ◽  
Task Knowledge ◽  
Learn Activity ◽  
Abstract Method ◽  
Novel Algorithm

For a service robot, learning appropriate behaviours to acquire task knowledge and deliberation in various situations is essential, but the existing methods do not support merging the plan-based activity experiences from multiple situations in the same task. In this paper, an abstract method is introduced to integrate the empirical activity schemas of multiple situations, and a novel algorithm is presented to learn activity schema with abstract methods. Furthermore, a novel planner called the schema-based optimized planner (SBOP) is developed based on the learned activity schema, in which actions merging optimization and partially backtracking techniques are adopted. A simulation with a PR2 robot and a physical experiment is conducted to validate the proposed method. The results show that the robot can generate a plan to recover from failure automatically using the novel learning and planning method, given that the experienced exception has been merged in the activity schema. Owing to the improved autonomy, the proposed SBOP exhibits increased efficiency in dealing with tasks containing loops and multiple activity schema instances. This research presents a novel solution of how to merge activity experiences from multiple situations and generate an intelligent and efficient plan that could adapt to a dynamically changing environment.

A Novel Neutrosophic Image Segmentation Based on Improved Fuzzy C-Means Algorithm (NIS-IFCM)

2019 ◽  
Vol 34 (05) ◽  
pp. 2055011
Author(s):  
Jing Zhao ◽  
Xiaoli Wang ◽  
Ming Li
Keyword(s):  
Computer Vision ◽  
Particle Swarm Optimization ◽  
Image Segmentation ◽  
Classical Problem ◽  
Local Optimum ◽  
The Novel ◽  
Swarm Optimization ◽  
Novel Method ◽  
Fuzzy C Means Algorithm ◽  
Novel Algorithm

Image segmentation is a classical problem in the field of computer vision. Fuzzy [Formula: see text]-means algorithm (FCM) is often used in image segmentation. However, when there is noise in the image, it easily falls into the local optimum, which results in poor image boundary segmentation effect. A novel method is proposed to solve this problem. In the proposed method, first, the image is transformed into a neutrosophic image. In order to improve the ability of global search, a combined FCM based on particle swarm optimization (PSO) is proposed. Finally, the proposed algorithm is applied to the neutrosophic image segmentation. The results of experiments show that the novel algorithm can eliminate image noise more effectively than the FCM algorithm, and make the boundary of the segmentation area clearer.

scholarly journals Tracking intermediate performance of vigilant attention using multiple eye metrics

SLEEP ◽  
2020 ◽  
Vol 43 (3) ◽  
Author(s):  
Takashi Abe ◽  
Kazuo Mishima ◽  
Shingo Kitamura ◽  
Akiko Hida ◽  
Yuichi Inoue ◽  
...  
Keyword(s):  
Sleep Deprivation ◽  
Human Error ◽  
Reaction Times ◽  
Simultaneous Recording ◽  
Time On Task ◽  
The Novel ◽  
Eyelid Closure ◽  
Psychomotor Vigilance Test ◽  
Falling Asleep ◽  
Novel Algorithm

Abstract Vigilance deficits account for a substantial number of accidents and errors. Current techniques to detect vigilance impairment measure only the most severe level evident in eyelid closure and falling asleep, which is often too late to avoid an accident or error. The present study sought to identify ocular biometrics of intermediate impairment of vigilance and develop a new technique that could detect a range of deficits in vigilant attention (VA). Sixteen healthy adults performed well-validated Psychomotor Vigilance Test (PVT) for tracking vigilance attention while undergoing simultaneous recording of eye metrics every 2 hours during 38 hours of continuous wakefulness. A novel marker was found that measured VA when the eyes were open—the prevalence of microsaccades. Notably, the prevalence of microsaccades decreased in response to sleep deprivation and time-on-task. In addition, a novel algorithm for detecting multilevel VA was developed, which estimated performance on the PVT by integrating the novel marker with other eye-related indices. The novel algorithm also tracked changes in intermediate level of VA (specific reaction times in the PVT, i.e. 300–500 ms) during prolonged time-on-task and sleep deprivation, which had not been tracked previously by conventional techniques. The implication of the findings is that this novel algorithm, named “eye-metrical estimation version of the PVT: PVT-E,” can be used to reduce human-error-related accidents caused by vigilance impairment even when its level is intermediate.

Accurate determination of DNA in agarose gels using the novel algorithm GelScann(1.0)

1995 ◽  
Vol 11 (2) ◽  
pp. 187-194
Author(s):  
Michael L. Metzker ◽  
Kyle M. Allain ◽  
Richard A. Gibbs
Keyword(s):  
Accurate Determination ◽  
The Novel ◽  
Agarose Gels ◽  
Novel Algorithm

Dynamic Controller Based on Ying Learning Algorithm for Medical Temperature System

2011 ◽  
Vol 187 ◽  
pp. 371-376
Author(s):  
Ping Zhang ◽  
Xiao Hong Hao ◽  
Heng Jie Li
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Fuzzy Neural Network ◽  
Learning Algorithm ◽  
Fuzzy Neural Networks ◽  
The Novel ◽  
Fuzzy Neural ◽  
Learning Set ◽  
And Training ◽  
Novel Algorithm

In order to avoid the over fitting and training and solve the knowledge extraction problem in fuzzy neural networks system. Ying Learning Dynamic Fuzzy Neural Network (YL-DFNN) algorithm is proposed. The Learning Set based on K-VNN is constituted from message. Then the framework of is designed and its stability is proved. Finally, Simulation indicates that the novel algorithm is fast, compact, and capable in generalization.

scholarly journals Feedback control of the forearm movement of tetraplegic patient based on microsoft kinect and multi-pad electrodes

2013 ◽  
Vol 21 (1) ◽  
pp. 7-11 ◽  
Author(s):  
Matija Strbac ◽  
Nebojsa Malesevic ◽  
Radoje Cobeljic ◽  
Laszlo Schwirtlich
Keyword(s):  
Sensory Feedback ◽  
Closed Loop ◽  
Microsoft Kinect ◽  
Hand Position ◽  
Closed Loop Control ◽  
The Novel ◽  
Upper Arm ◽  
Loop Control ◽  
Novel Algorithm ◽  
Stimulation Of

We present a novel system for control of elbow movements by electrical stimulation of the biceps and triceps in tetraplegic patients. The operation of the system uses the novel algorithm and applies closed loop control. Movement of the arm is generated via multi-pad electrodes developed by Tecnalia Serbia, Ltd. by the stimulator that allows asynchronous activation of individual pads. The electrodes are positioned over the innervation of the biceps and triceps muscles on the upper arm. This layout allows distributed activation; thereby, selective and low fatiguing activation of paralyzed muscles. The sensory feedback comes from the image acquired by the Microsoft Kinect system and the depth stream analysis is performed in real time by the computer running in the MatLab environment. The image based feedback allows control of the hand position at the target by cocontraction of the antagonists. The control adjusts the stimulation intensity and results with the tracking of the desired movement. The algorithm was proven to operate efficiently in a tetraplegic patient.

scholarly journals Algorithms for Instance Retrieval and Realization in Fuzzy Ontologies

Mathematics ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 154 ◽  
Author(s):  
Ignacio Huitzil ◽  
Jorge Bernad ◽  
Fernando Bobillo
Keyword(s):  
Artificial Intelligence ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Description Logics ◽  
The Novel ◽  
Realization Problem ◽  
Previous Algorithm ◽  
Fuzzy Description ◽  
Novel Algorithm ◽  
Instance Retrieval

Fuzzy description logics, the formalism behind fuzzy ontologies, are an important mathematical method with applications in many artificial intelligence scenarios. This paper proposes the first specific algorithms to solve two reasoning tasks with respect to a fuzzy ontology: the instance retrieval and the realization problem. Our algorithms are based on a reduction of the number of optimization problems to solve by merging some of them. Our experimental evaluation shows that the novel algorithm to solve the instance retrieval outperforms the previous algorithm, and that in practice it is common to be able to solve a single optimization problem.

scholarly journals RetSynth: determining all optimal and sub-optimal synthetic pathways that facilitate synthesis of target compounds in chassis organisms

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Leanne S. Whitmore ◽  
Bernard Nguyen ◽  
Ali Pinar ◽  
Anthe George ◽  
Corey M. Hudson
Keyword(s):  
Efficient Production ◽  
The Novel ◽  
Ranking Criteria ◽  
Complex Process ◽  
Target Yield ◽  
Balance Analysis ◽  
Target Production ◽  
Biological Solutions ◽  
Novel Algorithm

Abstract Background The efficient biological production of industrially and economically important compounds is a challenging problem. Brute-force determination of the optimal pathways to efficient production of a target chemical in a chassis organism is computationally intractable. Many current methods provide a single solution to this problem, but fail to provide all optimal pathways, optional sub-optimal solutions or hybrid biological/non-biological solutions. Results Here we present RetSynth, software with a novel algorithm for determining all optimal biological pathways given a starting biological chassis and target chemical. By dynamically selecting constraints, the number of potential pathways scales by the number of fully independent pathways and not by the number of overall reactions or size of the metabolic network. This feature allows all optimal pathways to be determined for a large number of chemicals and for a large corpus of potential chassis organisms. Additionally, this software contains other features including the ability to collect data from metabolic repositories, perform flux balance analysis, and to view optimal pathways identified by our algorithm using a built-in visualization module. This software also identifies sub-optimal pathways and allows incorporation of non-biological chemical reactions, which may be performed after metabolic production of precursor molecules. Conclusions The novel algorithm designed for RetSynth streamlines an arduous and complex process in metabolic engineering. Our stand-alone software allows the identification of candidate optimal and additional sub-optimal pathways, and provides the user with necessary ranking criteria such as target yield to decide which route to select for target production. Furthermore, the ability to incorporate non-biological reactions into the final steps allows determination of pathways to production for targets that cannot be solely produced biologically. With this comprehensive suite of features RetSynth exceeds any open-source software or webservice currently available for identifying optimal pathways for target production.

Sign in / Sign up

Export Citation Format

Share Document