Incremental Decision Rules Algorithm: A Probabilistic and Dynamic Approach to Decisional Data Stream Problems

Data science is currently one of the most promising fields used to support the decision-making process. Particularly, data streams can give these supportive systems an updated base of knowledge that allows experts to make decisions with updated models. Incremental Decision Rules Algorithm (IDRA) proposes a new incremental decision-rule method based on the classical ID3 approach to generating and updating a rule set. This algorithm is a novel approach designed to fit a Decision Support System (DSS) whose motivation is to give accurate responses in an affordable time for a decision situation. This work includes several experiments that compare IDRA with the classical static but optimized ID3 (CREA) and the adaptive method VFDR. A battery of scenarios with different error types and rates are proposed to compare these three algorithms. IDRA improves the accuracies of VFDR and CREA in most common cases for the simulated data streams used in this work. In particular, the proposed technique has proven to perform better in those scenarios with no error, low noise, or high-impact concept drifts.

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Adaptive Method for Modeling of Temporal Dependencies between Fields of Vision in Multi-Camera Surveillance Systems

Electronics ◽

10.3390/electronics10111303 ◽

2021 ◽

Vol 10 (11) ◽

pp. 1303

Author(s):

Karol Lisowski ◽

Andrzej Czyżewski

Keyword(s):

Statistical Data ◽

Input Parameter ◽

Gaussian Mixture ◽

Adaptive Method ◽

Transition Time ◽

Surveillance Systems ◽

Modified Particle Swarm Optimization ◽

Novel Approach ◽

Transition Times ◽

Temporal Dependencies

A method of modeling the time of object transition between given pairs of cameras based on the Gaussian Mixture Model (GMM) is proposed in this article. Temporal dependencies modeling is a part of object re-identification based on the multi-camera experimental framework. The previously utilized Expectation-Maximization (EM) approach, requiring setting the number of mixtures arbitrarily as an input parameter, was extended with the algorithm that automatically adapts the model to statistical data. The probabilistic model was obtained by matching to the histogram of transition times between a particular pair of cameras. The proposed matching procedure uses a modified particle swarm optimization (mPSO). A way of using models of transition time in object re-identification is also presented. Experiments with the proposed method of modeling the transition time were carried out, and a comparison between previous and novel approach results are also presented, revealing that added swarms approximate normalized histograms very effectively. Moreover, the proposed swarm-based algorithm allows for modelling the same statistical data with a lower number of summands in GMM.

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Computation of Parameters of a Form Grinding Wheel for Grinding of Shaving Cutter for Plunge Shaving of Topologically Modified Involute Pinion

Journal of Manufacturing Science and Engineering ◽

10.1115/1.2037087 ◽

2005 ◽

Vol 127 (4) ◽

pp. 819-828 ◽

Cited By ~ 10

Author(s):

Stephen P. Radzevich

Keyword(s):

Transmission Error ◽

Low Noise ◽

Tooth Surface ◽

Grinding Wheel ◽

Cnc Machine ◽

Surface Machining ◽

Form Grinding ◽

Novel Approach ◽

Light Trucks ◽

Part Surface

The paper is targeting on the finishing of precision gears for low-noise/noiseless transmission for cars and light trucks. Transmission error is the predominant cause of gear noise. The application of a topologically modified pinion results in reduction of transmission error up to two times. The required modification of the pinion tooth surface is provided on a plunge shaving operation with application of a shaving cutter of an appropriate design. A novel approach for computation of parameters of a form grinding wheel for grinding of the shaving cutter for plunge shaving of a precision involute pinion with topologically modified tooth surface is reported in the paper. The developed approach for computation of parameters of the form grinding wheel is focused on application of the shaving cutter grinder with a lack of CNC articulation. The problem under consideration is solved using the DG/K-based approach of part surface machining earlier developed by the author. (The DG/K-approach is based on fundamental results obtained in differential geometry of surfaces, and in kinematics of multi-parametric motion of a rigid body in E3 space (See Radzevich, S.P., Sculptured Surface Machining on Multi-Axis CNC Machine. Monograph, 1991, Vishcha Shkola Publishers, Kiev (in Russian). See also Radzevich, S.P., 2001, Fundamentals of Surface Machining. Monograph, Rastan, Kiev (in Russian).) An analytical solution to the problem is discussed in the paper. The solution has been used for developing software for the Mitsubishi ZA30CNC shaving cutter grinder for the needs of the automotive industry. Computer simulation reveals high accuracy of the ground shaving cutter.

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Automating Terrain Texturing in Real-Time Using a Rule-Based Approach

International Journal of Virtual Reality ◽

10.20870/ijvr.2010.9.4.2787 ◽

2010 ◽

Vol 9 (4) ◽

pp. 21-28

Author(s):

John Ferraris ◽

Christos Gatzidis ◽

Feng Tian

Keyword(s):

Real Time ◽

Rule Based ◽

Novel Approach ◽

Great Performance ◽

Rule Set ◽

Complex Features ◽

Rule Based Approach

This publication proposes a novel approach to automatically colour and texture a given terrain mesh in real time. Through the use of weighting rules, a simple syntax allows for the generation of texture and colour values based on the elevation and angle of a given vertex. It is through this combination of elevation and angle that complex features such as ridges, hills and mountains can be described, with the mesh coloured and textured accordingly. The implementation of the approach is done entirely on the GPU using 2D lookup textures, delivering a great performance increase over typical approaches that pass colour and weighting information in the fragment shader. In fact, the rule set is abstracted enough to be used in conjunction with any colouring/texturing approach that uses weighting values to dictate which surfaces are depicted on the mesh

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Introduction to the Special Issue: Applications of Internet of Things

Symmetry ◽

10.3390/sym10090374 ◽

2018 ◽

Vol 10 (9) ◽

pp. 374 ◽

Cited By ~ 1

Author(s):

Chi-Hua Chen ◽

Eyhab Al-Masri ◽

Feng-Jang Hwang ◽

Despo Ktoridou ◽

Kuen-Rong Lo

Keyword(s):

Internet Of Things ◽

Smart Home ◽

Data Science ◽

Cooperative Spectrum Sensing ◽

Smart Homes ◽

Recognition System ◽

Special Issue ◽

Smart Transportation ◽

User Classification ◽

Novel Approach

This editorial introduces the special issue, entitled “Applications of Internet of Things”, of Symmetry. The topics covered in this issue fall under four main parts: (I) communication techniques and applications, (II) data science techniques and applications, (III) smart transportation, and (IV) smart homes. Four papers on sensing techniques and applications are included as follows: (1) “Reliability of improved cooperative communication over wireless sensor networks”, by Chen et al.; (2) “User classification in crowdsourcing-based cooperative spectrum sensing”, by Zhai and Wang; (3) “IoT’s tiny steps towards 5G: Telco’s perspective”, by Cero et al.; and (4) “An Internet of things area coverage analyzer (ITHACA) for complex topographical scenarios”, by Parada et al. One paper on data science techniques and applications is as follows: “Internet of things: a scientometric review”, by Ruiz-Rosero et al. Two papers on smart transportation are as follows: (1) “An Internet of things approach for extracting featured data using an AIS database: an application based on the viewpoint of connected ships”, by He et al.; and (2) “The development of key technologies in applications of vessels connected to the Internet”, by Tian et al. Two papers on smart home are as follows: (1) “A novel approach based on time cluster for activity recognition of daily living in smart homes”, by Liu et al.; and (2) “IoT-based image recognition system for smart home-delivered meal services”, by Tseng et al.

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A Novel Approach to the Design of a Linearized Widely Tunable Very Low Power and Low Noise Differential Transconductor

Lecture Notes in Computer Science - Integrated Circuit and System Design. Power and Timing Modeling, Optimization and Simulation ◽

10.1007/11556930_73 ◽

2005 ◽

pp. 714-723

Author(s):

M. N. Hamid Reza Sadr

Keyword(s):

Low Power ◽

Low Noise ◽

Novel Approach

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The Nature of Intelligent Analytics

Advances in Data Mining and Database Management - Intelligent Analytics With Advanced Multi-Industry Applications ◽

10.4018/978-1-7998-4963-6.ch001 ◽

2021 ◽

pp. 1-21

Author(s):

Zhaohao Sun ◽

Andrew Stranieri

Keyword(s):

Artificial Intelligence ◽

Big Data ◽

Research And Development ◽

Business Intelligence ◽

Data Analytics ◽

Data Science ◽

Big Data Analytics ◽

Business Analytics ◽

Novel Approach ◽

Advanced Analytics

Intelligent analytics is an emerging paradigm in the age of big data, analytics, and artificial intelligence (AI). This chapter explores the nature of intelligent analytics. More specifically, this chapter identifies the foundations, cores, and applications of intelligent big data analytics based on the investigation into the state-of-the-art scholars' publications and market analysis of advanced analytics. Then it presents a workflow-based approach to big data analytics and technological foundations for intelligent big data analytics through examining intelligent big data analytics as an integration of AI and big data analytics. The chapter also presents a novel approach to extend intelligent big data analytics to intelligent analytics. The proposed approach in this chapter might facilitate research and development of intelligent analytics, big data analytics, business analytics, business intelligence, AI, and data science.

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Growing Neural Forest-Based Color Quantization Applied to RGB Images

International Journal of Computer Vision and Image Processing ◽

10.4018/ijcvip.2017070102 ◽

2017 ◽

Vol 7 (3) ◽

pp. 13-25

Author(s):

Jesús Benito-Picazo ◽

Ezequiel López-Rubio ◽

Enrique Domínguez

Keyword(s):

Data Streams ◽

Image Data ◽

Color Quantization ◽

Perceptual Distortion ◽

Self Organized ◽

Novel Approach ◽

Image Quantization ◽

Rgb Images ◽

Storage Technologies ◽

Future Work

Although last improvements in both physical storage technologies and image handling techniques have eased image managing processes, the large amount of information handled nowadays constantly demands more efficient ways to store and transmit image data streams. Among other alternatives for such purpose, the authors find color quantization, which consists of color indexing for minimal perceptual distortion image compression. In this context, artificial intelligence-based algorithms and more specifically, Artificial Neural Networks, have been consolidated as a powerful tool for unsupervised tasks, and therefore, for color quantization purposes. In this work, a novel approach to color quantization is presented based on the Growing Neural Forest (GNF), which is a Growing Neural Gas (GNG) variation where a set of trees is learnt instead of a general graph. Experimental results support the use of GNF for image quantization tasks where it overcomes other self-organized models including SOM, GHSOM and GNG. Future work will include more datasets and different competitive models to compare to.

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Building an integrated enhanced virtual research environment metadata catalogue

The Electronic Library ◽

10.1108/el-09-2018-0183 ◽

2019 ◽

Vol 37 (6) ◽

pp. 929-951 ◽

Cited By ~ 2

Author(s):

Laurent Remy ◽

Dragan Ivanović ◽

Maria Theodoridou ◽

Athina Kritsotaki ◽

Paul Martin ◽

...

Keyword(s):

Data Model ◽

Data Science ◽

Science Research ◽

Dublin Core ◽

Content Type ◽

Knowledge Based ◽

Novel Approach ◽

Virtual Research Environment ◽

Definition Of ◽

Practical Implications

Purpose The purpose of this paper is to boost multidisciplinary research by the building of an integrated catalogue or research assets metadata. Such an integrated catalogue should enable researchers to solve problems or analyse phenomena that require a view across several scientific domains. Design/methodology/approach There are two main approaches for integrating metadata catalogues provided by different e-science research infrastructures (e-RIs): centralised and distributed. The authors decided to implement a central metadata catalogue that describes, provides access to and records actions on the assets of a number of e-RIs participating in the system. The authors chose the CERIF data model for description of assets available via the integrated catalogue. Analysis of popular metadata formats used in e-RIs has been conducted, and mappings between popular formats and the CERIF data model have been defined using an XML-based tool for description and automatic execution of mappings. Findings An integrated catalogue of research assets metadata has been created. Metadata from e-RIs supporting Dublin Core, ISO 19139, DCAT-AP, EPOS-DCAT-AP, OIL-E and CKAN formats can be integrated into the catalogue. Metadata are stored in CERIF RDF in the integrated catalogue. A web portal for searching this catalogue has been implemented. Research limitations/implications Only five formats are supported at this moment. However, description of mappings between other source formats and the target CERIF format can be defined in the future using the 3M tool, an XML-based tool for describing X3ML mappings that can then be automatically executed on XML metadata records. The approach and best practices described in this paper can thus be applied in future mappings between other metadata formats. Practical implications The integrated catalogue is a part of the eVRE prototype, which is a result of the VRE4EIC H2020 project. Social implications The integrated catalogue should boost the performance of multi-disciplinary research; thus it has the potential to enhance the practice of data science and so contribute to an increasingly knowledge-based society. Originality/value A novel approach for creation of the integrated catalogue has been defined and implemented. The approach includes definition of mappings between various formats. Defined mappings are effective and shareable.

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