scholarly journals Nonnegative Matrix Factorization-Based Spatial-Temporal Clustering for Multiple Sensor Data Streams

2014 ◽  
Vol 2014 ◽  
pp. 1-12
Author(s):  
Di-Hua Sun ◽  
Chun-Yan Sang
Keyword(s):  
Data Streams ◽  
Clustering Algorithm ◽  
Synthetic Data ◽  
Spatial Relationship ◽  
Nonnegative Matrix ◽  
Research Area ◽  
Sensor Data ◽  
Temporal Clustering ◽  
Multiple Sensor ◽  
Active Research

Cyber physical systems have grown exponentially and have been attracting a lot of attention over the last few years. To retrieve and mine the useful information from massive amounts of sensor data streams with spatial, temporal, and other multidimensional information has become an active research area. Moreover, recent research has shown that clusters of streams change with a comprehensive spatial-temporal viewpoint in real applications. In this paper, we propose a spatial-temporal clustering algorithm (STClu) based on nonnegative matrix trifactorization by utilizing time-series observational data streams and geospatial relationship for clustering multiple sensor data streams. Instead of directly clustering multiple data streams periodically, STClu incorporates the spatial relationship between two sensors in proximity and integrates the historical information into consideration. Furthermore, we develop an iterative updating optimization algorithm STClu. The effectiveness and efficiency of the algorithm STClu are both demonstrated in experiments on real and synthetic data sets. The results show that the proposed STClu algorithm outperforms existing methods for clustering sensor data streams.

scholarly journals Pocketable Labs for Everyone: Synchronized Multi-Sensor Data Streaming and Recording on Smartphones with the Lab Streaming Layer

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8135
Author(s):  
Sarah Blum ◽  
Daniel Hölle ◽  
Martin Georg Bleichner ◽  
Stefan Debener
Keyword(s):  
Data Streams ◽  
Time Series Data ◽  
Sensor Data ◽  
Series Data ◽  
Personal Health ◽  
Data Streaming ◽  
Sensor Signals ◽  
Multiple Sensor ◽  
Android Applications ◽  
Smartphone Sensor

The streaming and recording of smartphone sensor signals is desirable for mHealth, telemedicine, environmental monitoring and other applications. Time series data gathered in these fields typically benefit from the time-synchronized integration of different sensor signals. However, solutions required for this synchronization are mostly available for stationary setups. We hope to contribute to the important emerging field of portable data acquisition by presenting open-source Android applications both for the synchronized streaming (Send-a) and recording (Record-a) of multiple sensor data streams. We validate the applications in terms of functionality, flexibility and precision in fully mobile setups and in hybrid setups combining mobile and desktop hardware. Our results show that the fully mobile solution is equivalent to well-established desktop versions. With the streaming application Send-a and the recording application Record-a, purely smartphone-based setups for mobile research and personal health settings can be realized on off-the-shelf Android devices.

scholarly journals Constraint-based discriminative dimension selection for high-dimensional stream clustering

2018 ◽  
Vol 4 (3) ◽  
pp. 167
Author(s):  
Kitsana Waiyamai ◽  
Thanapat Kangkachit
Keyword(s):  
Data Streams ◽  
Clustering Algorithm ◽  
Expert Knowledge ◽  
Clustering Algorithms ◽  
Clustering Methods ◽  
Dynamic Constraints ◽  
Stream Clustering ◽  
Clustering Quality ◽  
Active Research ◽  
Clustering Data

Clustering data streams is one of active research topic in data mining. However, runtime of the existing stream clustering algorithms increases and their performance drop in the face of large number of dimensions. Complexity of the stream clustering methods is increased when perform on data with large number of dimensions. In order to reduce the clustering complexity, one possible solution consists in determining the appropriate subset of cluster dimensions via dimension projection. SED-Stream is an efficient clustering algorithm that supports high dimension data streams. The aim of this paper is to increase performance of SED-Stream in terms of both clustering quality and execution-time. In order to improve the clustering process, background or domain expert knowledge are integrated as “constraints” in SEDC-Stream. The new algorithm, SEDC-Stream, supports the evolving characteristics of the dynamic constraints which are activation, fading, outdating and prioritization. SEDC-Stream algorithm is able to reduce cluster splitting time, and place new incoming points to their suitable clusters. Compared to SED-Stream on the three real-world streams datasets, SEDC-Stream is able to generate a better clustering performance in terms of both purity and f-measure.

Document Image Quality Assessment with Relaying Reference to Determine Minimum Readable Resolution for Compression

2020 ◽  
Vol 2020 (9) ◽  
pp. 323-1-323-8
Author(s):  
Litao Hu ◽  
Zhenhua Hu ◽  
Peter Bauer ◽  
Todd J. Harris ◽  
Jan P. Allebach
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Research Area ◽  
Input Image ◽  
Quality Score ◽  
Document Image ◽  
Digital Cameras ◽  
Active Research ◽  
Traditional Approaches

Image quality assessment has been a very active research area in the field of image processing, and there have been numerous methods proposed. However, most of the existing methods focus on digital images that only or mainly contain pictures or photos taken by digital cameras. Traditional approaches evaluate an input image as a whole and try to estimate a quality score for the image, in order to give viewers an idea of how “good” the image looks. In this paper, we mainly focus on the quality evaluation of contents of symbols like texts, bar-codes, QR-codes, lines, and hand-writings in target images. Estimating a quality score for this kind of information can be based on whether or not it is readable by a human, or recognizable by a decoder. Moreover, we mainly study the viewing quality of the scanned document of a printed image. For this purpose, we propose a novel image quality assessment algorithm that is able to determine the readability of a scanned document or regions in a scanned document. Experimental results on some testing images demonstrate the effectiveness of our method.

A Person-Centered Design Framework for Serious Games for Dementia

2020 ◽  
Vol 64 (1) ◽  
pp. 18-22
Author(s):  
Bella Yigong Zhang ◽  
Mark Chignell
Keyword(s):  
Theoretical Basis ◽  
Serious Games ◽  
Aging Population ◽  
Research Area ◽  
Design Framework ◽  
Strategic Design ◽  
Health And Wellbeing ◽  
Initial Design ◽  
Active Research ◽  
Active Research Area

With the rapidly aging population and the rising number of people living with dementia (PLWD), there is an urgent need for programming and activities that can promote the health and wellbeing of PLWD. Due to staffing and budgetary constraints, there is considerable interest in using technology to support this effort. Serious games for dementia have become a very active research area. However, much of the work is being done without a strong theoretical basis. We incorporate a Montessori approach with highly tactile interactions. We have developed a person-centered design framework for serious games for dementia with initial design recommendations. This framework has the potential to facilitate future strategic design and development in the field of serious games for dementia.

scholarly journals An Overview on the Rheology, Mechanical Properties, Durability, 3D Printing, and Microstructural Performance of Nanomaterials in Cementitious Composites

Materials ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 2950
Author(s):  
Hongwei Song ◽  
Xinle Li
Keyword(s):  
Mechanical Properties ◽  
3D Printing ◽  
Three Dimensional ◽  
Cementitious Materials ◽  
Research Area ◽  
Cementitious Composites ◽  
Split Tensile Strength ◽  
Contour Crafting ◽  
Wide Range ◽  
Active Research

The most active research area is nanotechnology in cementitious composites, which has a wide range of applications and has achieved popularity over the last three decades. Nanoparticles (NPs) have emerged as possible materials to be used in the field of civil engineering. Previous research has concentrated on evaluating the effect of different NPs in cementitious materials to alter material characteristics. In order to provide a broad understanding of how nanomaterials (NMs) can be used, this paper critically evaluates previous research on the influence of rheology, mechanical properties, durability, 3D printing, and microstructural performance on cementitious materials. The flow properties of fresh cementitious composites can be measured using rheology and slump. Mechanical properties such as compressive, flexural, and split tensile strength reveal hardened properties. The necessary tests for determining a NM’s durability in concrete are shrinkage, pore structure and porosity, and permeability. The advent of modern 3D printing technologies is suitable for structural printing, such as contour crafting and binder jetting. Three-dimensional (3D) printing has opened up new avenues for the building and construction industry to become more digital. Regardless of the material science, a range of problems must be tackled, including developing smart cementitious composites suitable for 3D structural printing. According to the scanning electron microscopy results, the addition of NMs to cementitious materials results in a denser and improved microstructure with more hydration products. This paper provides valuable information and details about the rheology, mechanical properties, durability, 3D printing, and microstructural performance of cementitious materials with NMs and encourages further research.

Factor-Bounded Nonnegative Matrix Factorization

2021 ◽  
Vol 15 (6) ◽  
pp. 1-18
Author(s):  
Kai Liu ◽  
Xiangyu Li ◽  
Zhihui Zhu ◽  
Lodewijk Brand ◽  
Hua Wang
Keyword(s):  
Matrix Factorization ◽  
Clustering Algorithm ◽  
Nonnegative Matrix Factorization ◽  
Nonnegative Matrix ◽  
Optimization Methods ◽  
Auxiliary Function ◽  
Image Clustering ◽  
Real World Datasets ◽  
The Relationship ◽  
Matrix Factors

Nonnegative Matrix Factorization (NMF) is broadly used to determine class membership in a variety of clustering applications. From movie recommendations and image clustering to visual feature extractions, NMF has applications to solve a large number of knowledge discovery and data mining problems. Traditional optimization methods, such as the Multiplicative Updating Algorithm (MUA), solves the NMF problem by utilizing an auxiliary function to ensure that the objective monotonically decreases. Although the objective in MUA converges, there exists no proof to show that the learned matrix factors converge as well. Without this rigorous analysis, the clustering performance and stability of the NMF algorithms cannot be guaranteed. To address this knowledge gap, in this article, we study the factor-bounded NMF problem and provide a solution algorithm with proven convergence by rigorous mathematical analysis, which ensures that both the objective and matrix factors converge. In addition, we show the relationship between MUA and our solution followed by an analysis of the convergence of MUA. Experiments on both toy data and real-world datasets validate the correctness of our proposed method and its utility as an effective clustering algorithm.

Advances in Water Treatment Application of Sepiolite Mineral Materials

2013 ◽  
Vol 710 ◽  
pp. 217-220 ◽  
Author(s):  
Fei Wang ◽  
Lei Feng ◽  
Meng Ran Tang ◽  
Ji Yuan Li ◽  
Qing Guo Tang
Keyword(s):  
Water Treatment ◽  
Size Effect ◽  
Large Scale ◽  
Surface Effect ◽  
Development Trend ◽  
High Energy ◽  
Research Area ◽  
Group Mineral ◽  
Active Research ◽  
Treatment Application

Synthetic nanomaterials have the disadvantages of large-scale investment, high energy consumption, complex production process and heavy environmental load. Mineral nanomaterials such as sepiolite group mineral nanomaterials are characterized by small size effect, quantum size effect and surface effect. Water treatment application of sepiolite group mineral nanomaterials has become an active research area and showed good development and application prospects. Based on the above reasons, this paper systematically summarizes the water treatment application of sepiolite group mineral nanomaterials, and development trend related to water treatment application of sepiolite group mineral nanomaterials were also proposed.

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