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1.Energy Dissipation During Impact of an Agglomerate Composed of Autoadhesive Elastic-Plastic Particles

Author:Liu, LF;Thornton, C;Shaw, SJ

Source:PROCEEDINGS OF THE 7TH INTERNATIONAL CONFERENCE ON DISCRETE ELEMENT METHODS,2017,Vol.188

Abstract:Discrete Element Method is used to simulate the impact of agglomerates consisting of autoadhesive, elastic-plastic primary particles. In order to explain the phenomenon that the elastic agglomerate fractures but the elastic-plastic agglomerate disintegrates adjacent to the impact site for the same impact velocity, we increase the impact velocity and lower the yield strength of the constituent particles of the agglomerate. We find that increasing the impact velocity can lead to the increased number of yielded contacts, and cause the elastic-plastic agglomerate to disintegrate faster. Mostly importantly, the energy dissipation process for the elastic-plastic agglomerate impact has been investigated together with the evolutions of the yielding contacts, and evolutions of velocity during impact.

2.Identifying the influential spreaders in multilayer interactions of online social networks

Author:Al-Garadi, MA;Varathan, KD;Ravana, SD;Ahmed, E;Chang, V

Source:JOURNAL OF INTELLIGENT & FUZZY SYSTEMS,2016,Vol.31

Abstract:Online social networks (OSNs) portray a multi-layer of interactions through which users become a friend, information is propagated, ideas are shared, and interaction is constructed within an OSN. Identifying the most influential spreaders in a network is a significant step towards improving the use of existing resources to speed up the spread of information for application such as viral marketing or hindering the spread of information for application like virus blocking and rumor restraint. Users communications facilitated by OSNs could confront the temporal and spatial limitations of traditional communications in an exceptional way, thereby presenting new layers of social interactions, which coincides and collaborates with current interaction layers to redefine the multiplex OSN. In this paper, the effects of different topological network structure on influential spreaders identification are investigated. The results analysis concluded that improving the accuracy of influential spreaders identification in OSNs is not only by improving identification algorithms but also by developing a network topology that represents the information diffusion well. Moreover, in this paper a topological representation for an OSN is proposed which takes into accounts both multilayers interactions as well as overlaying links as weight. The measurement results are found to be more reliable when the identification algorithms are applied to proposed topological representation compared when these algorithms are applied to single layer representations.

3.Minimize Reactive Power Losses of Dual Active Bridge Converters using Unified Dual Phase Shift Control

Author:Wen, HQ;Su, B

Source:JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY,2017,Vol.12

Abstract:This paper proposed an unified dual-phase-shift (UDPS) control for dual active bridge (DAB) converters in order to improve efficiency for a wide output power range. Different operating modes of UDPS are characterized with respect to the reactive current distribution. The proposed UDPS has the same output power capability with conventional phase-shift (CPS) method. Furthermore, its implementation is simple since only the change of the leading phase-shift direction is required for different operating power range. The proposed UDPS control can minimize both the inductor rms current and the circulating reactive current for various voltage conversion ratios and load conditions. The optimal phase-shift pairs for two bridges of DAB converter are derived with respect to the comprehensive reactive power loss model, including the reactive components delivered from the load and back to the source. Simulation and experimental results are illustrated and explained with details. The effectiveness of the proposed method is verified in terms of reactive power losses minimization and efficiency improvement.

4.Quantitative and rapid detection of microcystin-LR using time-resolved fluorescence immunochromatographic assay based on europium nanospheres

Author:Zhang, Y;Ding, XL;Guo, MM;Han, TT;Huang, ZJ;Shang, HT;Huang, B

Source:ANALYTICAL METHODS,2017,Vol.9

Abstract:In the present study, a novel time-resolved fluorescence immunochromatographic assay was established for the rapid quantitative detection of microcystin-leucine arginine (MC-LR). In this method, the europium nanoshpere labelled with anti-MC-LR antibodies was used as the luminescent tracer, dissolved in the running buffer and then added with the sample solution on the pad. MC-LR-BSA and goat anti-mouse antibody were dispensed on the nitrocellulose membrane for the test and the control line, respectively. The optimal parameters were 0.05 g L-1 MC-LR-BSA, 1 : 100 colloidal europium-antibody conjugate, and 10 min reaction time. The linear working range for MC-LR was 0.1-5 mu g L-1 with an IC50 of 0.78 mu g L-1 and a sensitivity of 0.035 mu g L-1. The low cross-reactivity was observed with MC-YR and MC-LF. The assay accuracy was confirmed by the HPLC method with a correlation coefficient of 0.99. When the variable coefficients were 4.4%% and 5.4%%, the average recoveries of tap and lake water were 94.6%% and 102.8%%, respectively. The time-resolved fluorescence immunochromatographic assay provides a sensitive, simple, and speedy performance for MC-LR quantitative determination and has a potential use for water sample screening.

5.On the theoretical distribution of the wind farm power when there is a correlation between wind speed and wind turbine availability

Author:Kan, C;Devrim, Y;Eryilmaz, S

Source:RELIABILITY ENGINEERING & SYSTEM SAFETY,2020,Vol.203

Abstract:It is important to elicit information about the potential power output of a wind turbine and a wind farm consisting of specified number of wind turbines before installation of the turbines. Such information can be used to estimate the potential power output of the wind farm which will be built in a specific region. The output power of a wind turbine is affected by two factors: wind speed and turbine availability. As shown in the literature, the correlation between wind speed and wind turbine availability has an impact on the output of a wind farm. Thus, the probability distribution of the power produced by the farm depending on the wind speed distribution and turbine availability can be effectively used for planning and risk management. In this paper, the theoretical distribution of the wind farm power is derived by considering the dependence between turbine availability and the wind speed. The theoretical results are illustrated for real wind turbine reliability and wind speed data.

6.An Empirical Research on the Investment Strategy of Stock Market based on Deep Reinforcement Learning model

Author:Li, Yuming ; Ni, Pin ; Chang, Victor

Source:COMPLEXIS 2019 - Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk,2019,Vol.

Abstract:The stock market plays a major role in the entire financial market. How to obtain effective trading signals in the stock market is a topic that stock market has long been discussing. This paper first reviews the Deep Reinforcement Learning theory and model, validates the validity of the model through empirical data, and compares the benefits of the three classical Deep Reinforcement Learning models. From the perspective of the automated stock market investment transaction decision-making mechanism, Deep Reinforcement Learning model has made a useful reference for the construction of investor automation investment model, the construction of stock market investment strategy, the application of artificial intelligence in the field of financial investment and the improvement of investor strategy yield. © 2019 International Conference on Complexity, Future Information Systems and Risk.

7.2,2-Dicyanovinyl-end-capped oligothiophenes as electron acceptor in solution processed bulk-heterojunction organic solar cells

Author:Wu, J;Ma, Y;Wu, N;Lin, Y;Lin, J;Wang, L;Ma, CQ

Source:ORGANIC ELECTRONICS,2015,Vol.23

Abstract:Three 2,2-dicyanovinyl (DCV) end-capped A-pi-D-pi-A type oligothiophenes (DCV-OTs) containing dithieno[3,2-b: 2',3'-d] silole (DTSi), cyclopenta[1,2-b: 3,4-b'] dithiophene (DTCP) or dithieno[3,2-b: 2',3'-d] pyrrole (DTPy) unit as the central donor part, mono-thiophene as the pi-conjugation bridge were synthesized. The absorption spectroscopies, cyclic voltammetry of these compounds were characterized. Results showed that all these compounds have intensive absorption band over 500-680 nm with a LUMO energy level around -3.80 eV, which is slightly higher than that of [6,6] phenyl-C-61-butyric acid methyl ester (PC61BM, E-LUMO = -4.01 eV), but lower than that of poly(3-hexylthiophene) (P3HT, ELUMO = -2.91 eV). Solution processed bulk heterojunction "all-thiophene'' solar cells using P3HT as electron donor and the above mentioned oligothiophenes as electron acceptor were fabricated and tested. The highest power conversion efficiency (PCE) of 1.31%% was achieved for DTSi-cored compound DTSi(THDCV) 2, whereas PTB7: DTSi(THDCV) 2 based device showed slightly higher PCE of 1.56%%. Electron mobilities of these three compounds were measured to be around 10 (5) cm(2) V (1) s (1) by space charge limited current method, which is much lower than that of PC61BM, and was considered as one of the reason for the low photovoltaic performance. (C) 2015 Elsevier B.V. All rights reserved.

8.BEYOND CODES AND PIXELS

Author:Fischer, T;De Biswas, K;Ham, JJ;Naka, R;Huang, WX

Source:PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON COMPUTER-AIDED ARCHITECTURAL DESIGN RESEARCH IN ASIA (CAADRIA 2012): BEYOND CODES AND PIXELS,2012,Vol.

9.Key management and key distribution for secure group communication in mobile and cloud network

Author:Vijayakumar, P;Chang, V;Deborah, LJ;Kshatriya, BSR

Source:FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE,2018,Vol.84

Abstract:With the computing systems becoming more and more pervasive and ubiquitous due to the invention of cloud computing and mobile phone based applications, secure data transmission is the pressing need for a real time perspective of the technologies. Examples of the need for secure key management and distribution environments include secure transmission of health related SMS, telecare medicine provisioning for critical applications such as heart disorders, secure agriculture monitoring, data transmission in surveillance scenarios, secure military networks, etc. In the context of key exchange for secure group communication, the computational complexities need to be addressed in particular due to the advent of resource constrained mobile phones, sensors and other embedded devices. This special issue introduces some of the novel approaches for enabling secure group communication in the contexts related to cloud and mobile computing. (C) 2018 Published by Elsevier B.V.

10.Dual algorithm for truncated fractional variation based image denoising

Author:Liang, HX;Zhang, JL

Source:INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS,2020,Vol.97

Abstract:Fractional-order derivative is attracting more and more attention of researchers in image processing because of its better property in restoring more texture than the total variation. To improve the performance of fractional-order variation model in image restoration, a truncated fractional-order variation model was proposed in Chan and Liang [Truncated fractional-order variation model for image restoration, J. Oper. Res. Soc. China]. In this paper, we propose a dual approach to solve this truncated fractional-order variation model on noise removal. The proposed algorithm is based on the dual approach proposed by Chambolle [An algorithm for total variation minimisation and applications, J. Math Imaging Vis. 20 (2004), pp. 89-97]. Conversely, the Chambolle's dual approach can be treated as a special case of the proposed algorithm with fractional order . The work of this paper modifies the result in Zhang et al. [Adaptive fractional-order multi-scale method for image denoising, J. Math. Imaging Vis. 43(1) (2012), pp. 39-49. Springer Netherlands 0924-9907, Computer Science, pp. 1-11, 2011], where the convergence is not analysed. Based on the truncation, the convergence of the proposed dual method can be analysed and the convergence criteria can be provided. In addition, the accuracy of the reconstruction is improved after the truncation is taken.

11.A multi-objective optimization model for bike-sharing    

Author:Shan, Yu ; Xie, Dejun ; Zhang, Rui

Source:ACM International Conference Proceeding Series,2019,Vol.

Abstract:The study proposes a multi-objective optimization model for bike-sharing industry by monitoring, with high accuracy, the user demand and providing the suitable number of bikes at selected stations. One of the key factors for designing an optimized bike sharing system is to balance the demand of pick-ups (drop-offs) around a given station and the number of available bikes (vacant lockers) in the station throughout the day. The model optimizes the location of bicycle stations and the number of parking slots that each station should have by taking account of the main contributing factors including the total budget of the bike sharing system, the popularity of riding in the city, and the expected proximity of the stations. A case study using the bike-sharing in New York was conducted to test theeffectiveness of themodel. © 2019 Association for Computing Machinery.

12.Dopamine Surface Modification of Trititanate Nanotubes: Proposed In-Situ Structure Models.

Author:Liu, Ruochen; Fu, Xuejian; Wang, Congyi; Dawson, Graham

Source:Chemistry (Weinheim an der Bergstrasse, Germany),2016,Vol.22

Abstract:Two models for self-assembled dopamine on the surface of trititanate nanotubes are proposed: individual monomer units linked by π-π stacking of the aromatic regions and mono-attached units interacting through hydrogen bonds. This was investigated with solid state NMR spectroscopy studies and powder X-ray diffraction.

13.An atomic finite element model for biodegradable polymers. Part 1. Formulation of the finite elements

Author:Gleadall, A;Pan, JZ;Ding, LF;Kruft, MA;Curco, D

Source:JOURNAL OF THE MECHANICAL BEHAVIOR OF BIOMEDICAL MATERIALS,2015,Vol.51

Abstract:Molecular dynamics (MD) simulations are widely used to analyse materials at the atomic scale. However, MD has high computational demands, which may inhibit its use for simulations of structures involving large numbers of atoms such as amorphous polymer structures. An atomic-scale finite element method (AFEM) is presented in this study with significantly lower computational demands than MD. Due to the reduced computational demands, AFEM is suitable for the analysis of Young's modulus of amorphous polymer structures. This is of particular interest when studying the degradation of bioresorbable polymers, which is the topic of an accompanying paper. AFEM is derived from the inter-atomic potential energy functions of an MD force field. The nonlinear MD functions were adapted to enable static linear analysis. Finite element formulations were derived to represent interatomic potential energy functions between two, three and four atoms. Validation of the AFEM was conducted through its application to atomic structures for crystalline and amorphous poly(lactide). (C) 2015 Elsevier Ltd. All rights reserved.

14.Critically paintable, choosable or colorable graphs

Author:Riasat, A;Schauz, U

Source:DISCRETE MATHEMATICS,2012,Vol.312

Abstract:We extend results about critically k-colorable graphs to choosability and paintability (list colorability and on-line list colorability). Using a strong version of Brooks' Theorem, we generalize Gallai's Theorem about the structure of the low-degree subgraph of critically k-colorable graphs, and introduce a more adequate lowest-degree subgraph. We prove lower bounds for the edge density of critical graphs, and generalize Heawood's Map-Coloring Theorem about graphs on higher surfaces to paintability. We also show that on a fixed given surface, there are only finitely many critically k-paintable/k-choosable/k-colorable graphs, if k >= 6. In this situation, we can determine in polynomial time k-paintability, k-choosability and k-colorability, by giving a polynomial time coloring strategy for "Mrs. Correct". Our generalizations of k-choosability theorems also concern the treatment of non-constant list sizes (non-constant k). Finally, we use a Ramsey-type lemma to deduce all 2-paintable, 2-choosable, critically 3-paintable and critically 3-choosable graphs, with respect to vertex deletion and to edge deletion. (C) 2012 Elsevier B.V. All rights reserved.

15.Three-Dimensional Local Energy-Based Shape Histogram (3D-LESH): A Novel Feature Extraction Technique

Author:Wajid, SK;Hussain, A;Huang, KZ

Source:EXPERT SYSTEMS WITH APPLICATIONS,2018,Vol.112

Abstract:In this paper, we present a novel feature extraction technique, termed Three-Dimensional Local Energy-Based Shape Histogram (3D-LESH), and exploit it to detect breast cancer in volumetric medical images. The technique is incorporated as part of an intelligent expert system that can aid medical practitioners making diagnostic decisions. Analysis of volumetric images, slice by slice, is cumbersome and inefficient. Hence, 3D-LESH is designed to compute a histogram-based feature set from a local energy map, calculated using a phase congruency (PC) measure of volumetric Magnetic Resonance Imaging (MRI) scans in 3D space. 3D-LESH features are invariant to contrast intensity variations within different slices of the MRI scan and are thus suitable for medical image analysis. The contribution of this article is manifold. First, we formulate a novel 3D-LESH feature extraction technique for 3D medical images to analyse volumetric images. Further, the proposed 3D-LESH algorithmic, for the first time, applied to medical MRI images. The final contribution is the design of an intelligent clinical decision support system (CDSS) as a multi-stage approach, combining novel 3D-LESH feature extraction with machine learning classifiers, to detect cancer from breast MRI scans. The proposed system applies contrast-limited adaptive histogram equalisation (CLAHE) to the MRI images before extracting 3D-LESH features. Furthermore, a selected subset of these features is fed into a machine-learning classifier, namely, a support vector machine (SVM), an extreme learning machine (ELM) or an echo state network (ESN) classifier, to detect abnormalities and distinguish between different stages of abnormality. We demonstrate the performance of the proposed technique by its application to benchmark breast cancer MRI images. The results indicate high-performance accuracy of the proposed system (98%%+/- 0.0050, with an area under a receiver operating charactertistic curve value of 0.9900 +/- 0.0050) with multiple classifiers. When compared with the state-of-the-art wavelet-based feature extraction technique, statistical analysis provides conclusive evidence of the significance of our proposed 3D-LESH algorithm. (C) 2017 The Authors. Published by Elsevier Ltd.

16.Robust Localisation of Pedestrians with Cast Shadows Using Homology in A Monocular View

Author:Xu, M;Jia, TY;Lu, L;Smith, JS

Source:PROCEEDINGS 2012 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC),2012,Vol.

Abstract:In this paper an object detection algorithm is proposed, which is robust in the presence of cast shadows and is based on geometric projections. The novelty of the work lies in the use of homology mapping of the foreground regions between different parallel planes within a monocular view, unlike some existing algorithms which depend on the use of multiple cameras. The results on an open video dataset are provided.

17.The effects of the bioanode on the microbial community and element profile in paddy soil

Author:Williamson, G;Chen, Z

Source:ENVIRONMENTAL ARSENIC IN A CHANGING WORLD (AS2018),2018,Vol.

Abstract:In paddy soil the reductive dissolution of iron oxide and the availability of organic matter plays an important role in arsenic release under anaerobic conditions. Microbial fuel cells have been shown to reduce organic matter (OM) content and the rate in which this occurs strongly relate to the external resistance applied. In this study we investigated the effects of bioanode operating at different external resistance on the paddy soil microbial community and iron and arsenic concentration. The results show that MFC can be used to reduce soil pore water iron and arsenic concentration and the extent in which this occurs depend on the external resistance applied. The MFC is able to mitigate arsenic release by decreasing organic matter availability. Furthermore, our finding shows that external resistance had a significant influence on the bacterial community composition that develop on the bioanode however only had minimal effect on the community of the bulk soil. These findings suggest that the sMFC can influence the iron and arsenic concentration by reducing OM content and the microbial community that develop in the bioanode vicinity.

18.Automatic Building and Floor Classification using Two Consecutive Multi-layer Perceptron

Author:Cha, J;Lee, S;Kim, KS

Source:2018 18TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS),2018,Vol.2018-October

Abstract:Key issues of indoor localization is taking full advantages and overcoming its disadvantages. indoor localization based on Wi-Fi fingerprinting attracts researchers' attentions since it does not require new infrastructure and devices. Many devices such as smart phones and laptops, which have a function to capture Wi-Fi signals, can be used for Wi-Fi fingerprinting. However, due to unreliable Wi-Fi signals, there are still difficulty to achieve high positioning accuracy. The unreliable signal disturbs devices to find their locations. As a result, getting localization with devices sometimes makes a wrong decision in building classification. It is useless for people to find a destination floor if they are in different building. In this paper, we propose two consecutive multi-layer perceptrons to get more precise localization. With sumple structure, we get better performance and show precise decision results in building classification, which is critical in Wi-Fi fingerprinting. We use UJIndoorLoc dataset which is open dataset.

19.MidSens'09 - International Workshop on Middleware Tools, Services and Run-Time Support for Sensor Networks, Co-located with the 10th ACM/IFIP/USENIX International Middleware Conference Preface

Author:Michiels, Sam ; Hughes, Danny

Source:MidSens'09 - International Workshop on Middleware Tools, Services and Run-Time Support for Sensor Networks, Co-located with the 10th ACM/IFIP/USENIX International Middleware Conference,2009,Vol.

20.Big data analytics for sustainability

Author:Lv, ZH;Iqbal, R;Chang, V

Source:FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE,2018,Vol.86

Abstract:Sustainability is a paradigm for thinking about the future in which environmental, societal and economic considerations are equitable in the pursuit of an improved lifestyle. Most of the economies are developing with breakneck velocities and are becoming epicenters of unsustainable global growth. Immense utilization of natural resources, waste generation and ecological irresponsibility are the reasons for such a dire situation. Big data analytics is clearly on a penetrative path across all arenas that rely on technology. (C) 2018 Published by Elsevier B.V.
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