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1.Investigation on mechanical characterizations of metal-coated lattice structure

Author:Wang, X. ; Yuan, F. ; Chen, M. ; He, J. ; Wang, P. ; Yu, Y. ; Li, J.

Source:Sustainable Buildings and Structures Building a Sustainable Tomorrow - Proceedings of the 2nd International Conference in Sustainable Buildings and Structures, ICSBS 2019,2020,Vol.

Abstract:Compared with traditional structures, lattice components produced by additive manufacturing have an outstanding mechanical performance with ultra-low density per unit. This lattice structure consisting of periodic unit cells can carry loads in tension or compression. In this study, the numerical simulation is used to explore the effect of the metal coating on the lattice units, and the experiment has been conducted to validate the mechanical properties of metal-coated lattice structure. The results of the simulation indicate that the coating technology can enhance the relative stiffness to density for lattice structures. Nevertheless, the experimental results exhibit the controversial conclusion, which was possibly caused by plating technologies for lattice with thin rods. © 2020 Taylor & Francis Group, London.

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

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


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.

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

Author:Williamson, G;Chen, Z


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.

4.Modeling and Verification of NCL Circuits Using PAT

Author:Ma, JM;Man, KL;Lim, EG;Zhang, N;Lei, CU;Guan, SU;Jeong, TT;Seon, JK

Source:CEIS 2011,2011,Vol.15

Abstract:NULL Conventional Logic (NCL) is a Delay-Insensitive (DI) clockless paradigm and is suitable for implementing asynchronous circuits. Efficient methods of analysis are required to specify and verify such DI systems. Based on Delay Insensitive sequential Process (DISP) specification, this paper demonstrates the application of formal methods by applying Process Analysis Toolkit (PAT) to model and verify the behavior of NCL circuits. A few useful constructs are successfully modeled and verified by using PAT. The flexibility and simplicity of the coding, simulation and verification shows that PAT is effective and applicable for NCL circuit design and verification. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [CEIS 2011]

5.Towards Better Forecasting by Fusing Near and Distant Future Visions

Author:Cheng, JZ;Huang, KZ;Zheng, ZB


Abstract:Multivariate time series forecasting is an important yet challenging problem in machine learning. Most existing approaches only forecast the series value of one future moment, ignoring the interactions between predictions of future moments with different temporal distance. Such a deficiency probably prevents the model from getting enough information about the future, thus limiting the forecasting accuracy. To address this problem, we propose Multi-Level Construal Neural Network (MLCNN), a novel multi-task deep learning framework. Inspired by the Construal Level Theory of psychology, this model aims to improve the predictive performance by fusing forecasting information (i.e., future visions) of different future time. We first use the Convolution Neural Network to extract multi-level abstract representations of the raw data for near and distant future predictions. We then model the interplay between multiple predictive tasks and fuse their future visions through a modified Encoder-Decoder architecture. Finally, we combine traditional Autoregression model with the neural network to solve the scale insensitive problem. Experiments on three real-world datasets show that our method achieves statistically significant improvements compared to the most state-of-the-art baseline methods, with average 4.59%% reduction on RMSE metric and average 6.87%% reduction on MAE metric.

6.Chromosome Classification with Convolutional Neural Network based Deep Learning

Author:Zhang, WB;Song, SF;Bai, TM;Zhao, YX;Ma, F;Su, JL;Yu, LM


Abstract:Karyotyping plays a crucial role in genetic disorder diagnosis. Currently Karyotyping requires considerable manual efforts, domain expertise and experience, and is very time consuming. Automating the karyotyping process has been an important and popular task. This study focuses on classification of chromosomes into 23 types, a step towards fully automatic karyotyping. This study proposes a convolutional neural network (CNN) based deep learning network to automatically classify chromosomes. The proposed method was trained and tested on a dataset containing 10304 chromosome images, and was further tested on a dataset containing 4830 chromosomes. The proposed method achieved an accuracy of 92.5%%, outperforming three other methods appeared in the literature. To investigate how applicable the proposed method is to the doctors, a metric named proportion of well classified karyotype was also designed. An result of 91.3%% was achieved on this metric, indicating that the proposed classification method could be used to aid doctors in genetic disorder diagnosis.

7.Multi-GHz Microstrip Transmission Lines Realised by Screen Printing on Flexible Substrates

Author:Shi, YZ;Jiang, ZZ;Lam, S;Leach, M;Wang, JC;Lim, EG


Abstract:This paper reports experimental work on 50 SI microstrip transmission lines implemented by screen-printing low-cost silver paste onto thin flexible polyethylene terephthalate (PET) substrates of varying thickness. The microstrip line designs are based on PET substrates with thicknesses of 1.4 mm, 0.7 mm and 0.5 mm, leading to conductive track widths of 3.8 mm, 1.7 mm and 1.2 mm respectively for a 50 SI line; these designs were then realised. The S-parameter measurements show that the insertion loss of the microstrip transmission lines on each substrate can be as low as 0.2 dB/cm, 0.17 dB/cm, and 0.14 dB/cm up to a frequency of 5 GHz in spite of the average quality of the silver paste used. The experimental results also show that the screen-printed transmission lines still work quite well in bent condition and wearable electronics application at GHz is possible.

8.A Systematic Analysis of Link Prediction in Complex Network

Author:Gul, H;Amin, A;Adnan, A;Huang, KZ

Source:IEEE ACCESS,2021,Vol.9

Abstract:Link mining is an important task in the field of data mining and has numerous applications in informal community. Suppose a real-world complex network, the responsibility of this function is to anticipate those links which are not occurred yet in the given real-world network. Holding the significance of LP, the link mining or expectation job has gotten generous consideration from scientists in differing exercise. In this manner, countless strategies for taking care of this issue have been proposed in the late decades. Various articles of link prediction are accessible, however, these are antiquated as multiples new methodologies introduced. In this paper, give a precise assessment of prevail link mining approaches. The investigation is through, it consists the soonest scoring-based approaches and reaches out to the latest strategies which confide on different link prediction strategies. We additionally order link prediction strategies because of their specialized methodology and discussion about the quality and weaknesses of various techniques. Additionally, we compared and expounded various top link prediction techniques. The experimental results of these techniques, over twelve data-sets are ordered here based on performance, RA, 0.7411 > AA, 0.7285 > PA, 0.7202 > Katz, 0.7141 > CN, 0.6951 > HP, 0.6924 > LHN, 0.6017 > PD, 0.3978.

9.Optimization for Train Speed Trajectory Based on Pontryagin's Maximum Principle

Author:Bao, K;Lu, SF;Xue, E;Tan, ZX


Abstract:Among different energy efficiency improvement technologies for railway transportation, the optimization of speed trajectory is a feasible method with low cost, since there is no need to upgrade the railway infrastructures. This paper proposes a simplified method to find speed trajectory and co-state variables. The method is based on Pontryagin's Maximum Principle (PMP) to minimize tractive energy. Hamiltonian and co-state equation are derived. The design of this paper is based on an ideal model which has no speed limit, gradient, and regenerative braking. Under the necessary condition of PMP, it can obtain acceleration, cruising, coasting, deceleration sections independently using a linear iteration, and then connect them to form full trajectory using the Linking Principle proposed in this paper. The train parameters are determined based on locomotive SS4. The results show that PMP can be applied on optimal train trajectory with minimum energy consumption.

10.Towards efficiently migrating virtual networks in cloud-based data centers

Author:Zhang, SM;Sun, G;Chang, V


Abstract:With the expansion of cloud computing, virtual network (VN) migration becomes the very perspective technology for saving energy, ensuring Service Level Agreements or improving the survivability of virtual networks in cloud networks. At present, the majority of research on the VN migration, however, are for saving energy or improving resource utilizations, and few of them for the entire virtual network migration for guaranteeing QoS or improving the survivability of virtual networks. Since the regional failure, network maintenance or QoS violation, the service provider generally needs to migrate the VN for guaranteeing the QoS or improving the survivability of virtual networks. In the paper, we research the live migration problem of the virtual network to optimize the virtual network migration performance. To efficient migrate virtual network, we present an effective VN migration method, VNM. To control the cost of migration or migration traffic, based on the VNM algorithm, we present an effective VN migration method with migration traffic control, VNM-MTC. We use two networks as substrate networks to simulate the performances of our presented algorithms. From the experiment, we can see that the total VN reconfiguration cost, total VN redeployment cost, total VN migration cost and blocking ratio of our presented algorithms are better than that of the contrast algorithm.

11.Determine the Permittivity of the Plastic Materials

Author:Lim, EG;Wang, Z;Leach, MP;Gray, D;Man, KL;Zhang, N


Abstract:Microwave dielectric measurements are difficult to make, each method involves a compromise between accuracy, experimental simplicity, and complexity of the analysis. It is with these ideas in mind that we present a technique in which a waveguide is completely filled with the dielectric of interest to determine the dielectric constant for plastic materials (e.g. Rexolite, Lacqrene and PTFE). Good agreements between measured and manufacturer material specifications have been obtained.

12.Modern Service Design Thinking on Traditional Culture-Based Services: A Case Study of the Service Businesses in Suzhou Old Town Areas

Author:Shen, X;Lo, CH


Abstract:This paper presents a case study that utilizes modern service design thinking techniques to investigate culture-based service businesses. The study is carried out in two heritage sites in Suzhou, which itself is a historical city located in the south of Yangtze River in China. Ethnographic methods are used to explore and collect the data. Service design thinking principles and methods are then applied to analyze the observed service businesses and identify common thematic issues and design opportunities. Service prototyping techniques are also used to review and rearrange a customer's journeys in the services. The result shows that modern design thinking concepts such as the user-centered approach can provide fundamental transformations to those services. It also illustrates a more cross-cultural development with the cross-cultural encounter between the modern design techniques and the traditional culture-based services.

13.An Investigation of Material Perception in Virtual Environments

Author:Niu, MT;Lo, CH


Abstract:Material representation has always been an important part of visual effects in industrial design. And the judgment and recognition of product material often remain on the rendering effect drawings of the 2D display. However, it cannot fully intuitive performed, even sometimes cannot identify the specific material composition. As a device to simulate the real environment, VR strengthens people's immersive experience by its 3D sense of space. The purpose of this study is to explore whether the material perception in VR is different from that in traditional 2D mode, and to determine whether VR can be used as a tool for users' material perception in the future. The study found that VR provides the users with stereoscopic visual effects not seen on a 2D display. This feature seems to deepen the perception of material, which may facilitate the design of industrial products, furniture design, automotive interior and so on.

14.Compressing Deep Networks by Neuron Agglomerative Clustering

Author:Wang, LN;Liu, WX;Liu, X;Zhong, GQ;Roy, PP;Dong, JY;Huang, KZ


Abstract:In recent years, deep learning models have achieved remarkable successes in various applications, such as pattern recognition, computer vision, and signal processing. However, high-performance deep architectures are often accompanied by a large storage space and long computational time, which make it difficult to fully exploit many deep neural networks (DNNs), especially in scenarios in which computing resources are limited. In this paper, to tackle this problem, we introduce a method for compressing the structure and parameters of DNNs based on neuron agglomerative clustering (NAC). Specifically, we utilize the agglomerative clustering algorithm to find similar neurons, while these similar neurons and the connections linked to them are then agglomerated together. Using NAC, the number of parameters and the storage space of DNNs are greatly reduced, without the support of an extra library or hardware. Extensive experiments demonstrate that NAC is very effective for the neuron agglomeration of both the fully connected and convolutional layers, which are common building blocks of DNNs, delivering similar or even higher network accuracy. Specifically, on the benchmark CIFAR-10 and CIFAR-100 datasets, using NAC to compress the parameters of the original VGGNet by 92.96%% and 81.10%%, respectively, the compact network obtained still outperforms the original networks.

15.Compliance Current Effect on Switching Behavior of Hafnium Oxide based RRAM

Author:Qi, YF;Zhao, C;Fang, YX;Lu, QF;Liu, CG;Yang, L;Zhao, CZ


Abstract:In this study, we compared the basic switching behaviors of HfO2, Al2O3 and HfAlOx (Hf:Al=9:1) based RRAM with Ti top electrode by setting various compliance currents (1mA, 5mA, 10mA, 15mA). The resistance ratio of HfO2 based RRAM (20 -> 320) increases with compliance current whereas it drops not obviously for Al2O3 based RRAM (85 -> 54). HfAlOx (Hf:Al=9:1)) based one has the best resistance ratio (300-440) and resistance stability. All low resistance state (LRS) resistance values of three samples are around 100 Omega with large compliance current while there is a difference in HRS resistance which causes the ratio difference accordingly. The dominant mechanism of resistive switching is the formation and rupture of the conductive filament composed of oxygen vacancies. The appropriate compliance current selection and doping technology to high-k materials should be considered in further study.

16.Unveiling the dynamics in RNA epigenetic regulations

Author:Meng, J;Cui, XD;Liu, H;Zhang, L;Zhang, SW;Rao, MK;Chen, YD;Huang, YF


Abstract:Despite the prevalent studies of DNA/Chromatin related epigenetics, such as, histone modifications and DNA methylation, RNA epigenetics did not receive deserved attention due to the lack of high throughput approach for profiling epitranscriptome. Recently, a new affinity-based sequencing approach MeRIPseq was developed and applied to survey the global mRNA N6-methyladenosine (m(6)A) in mammalian cells. As a marriage of ChIPseq and RNAseq, MeRIPseq has the potential to study, for the first time, the transcriptome-wide distribution of different types of post-transcriptional RNA modifications. Yet, this technology introduced new computational challenges that have not been adequately addressed. We have previously developed a MATLAB-based package 'exomePeak' for detection of RNA methylation sites from MeRIPseq data. Here, we extend the features of exomePeak by including a novel computational framework that enables differential analysis to unveil the dynamics in RNA epigenetic regulations. The novel differential analysis monitors the percentage of modified RNA molecules among the total transcribed RNAs, which directly reflects the impact of RNA epigenetic regulations. In contrast, current available software packages developed for sequencing-based differential analysis such as DESeq or edgeR monitors the changes in the absolute amount of molecules, and, if applied to MeRIPseq data, might be dominated by transcriptional gene differential expression. The algorithm is implemented as an R-package 'exomePeak' and freely available. It takes directly the aligned BAM files as input, statistically supports biological replicates, corrects PCR artifacts, and outputs exome-based results in BED format, which is compatible with all major genome browsers for convenient visualization and manipulation. Examples are also provided to depict how exomePeak R-package is integrated with exiting tools for MeRIPseq based peak calling and differential analysis. Particularly, the rationales behind each processing step as well as the specific method used, the best practice, and possible alternative strategies are briefly discussed. The algorithm was applied to the human HepG2 cell MeRIPseq data sets and detects more than 16000 RNA m(6)A sites, many of which are differentially methylated under ultraviolet radiation. The challenges and potentials of MeRIPseq in epitranscriptome studies are discussed in the end.

17.Fuzzy expert system-based framework for flood management in Saudi Arabia

Author:Amin, S;Hijji, M;Iqbal, R;Harrop, W;Chang, V


Abstract:This paper presents a fuzzy expert system-based framework for flood management in Saudi Arabia that helps the civil defense (CD) authority in both preparing their flood management capabilities and responding to scalable levels of flood risk. One of the most important type of flood management capabilities is training capabilities, the adequacy of training capabilities of emergency responders is a critical factor that influences on flood risk management, even considering other types of capabilities such as equipment and infrastructure. However, due to the lack of adequate training capabilities in place to address dynamic change of flood risk and vulnerabilities in some areas, emergency readiness for floods has been critically affected and resulted in ineffective response and mutual aid. Here, the study aimed to aid decision-makers in the Saudi CD Authority to reduce inappropriate readiness of training capabilities in some critical zones and maintain the levels of readiness using a proposed fuzzy expert system-based framework, which is named the capability evaluation and readiness (CER) framework. The developed CER framework includes a new fuzzy expert system, which is named the intelligent capability evaluation and readiness (ICER) system. CER framework uses three key elements for readiness evaluation and addressing needs related to training capabilities; the records of the provided training and exercises; the targeted standard and policy of readiness and mutual aid; and risk assessment of each zone and existing hazard and vulnerability (HV) factors within a zone. The results of evaluation by interviews indicted high agreement on effectiveness and productivity of the CER framework, however, it is recommended that additional stakeholders are included in order to have comprehensive information regarding others HV factors. In addition, questionnaires shown that more than 60%% of the respondents believe that the ICER system is an effective tool for flood response, however, regarding the readiness of the training capabilities, more that 17%% of the respondents believe that the ICER system is not effective tool to improving the readiness of the training capabilities.

18.When to Refinance Mortgage Loans in a Stochastic Interest Rate Environment

Author:Gan, SW;Zheng, J;Feng, XX;Xie, DJ


Abstract:Refinancing refers to the replacement of an existing debt obligation with another debt obligation to take the advantage of a lower interest rate. This paper reflects our ongoing work to find a desirable refinancing time for mortgage borrowers to minimize the total payments in a dynamic interest rate environment. To simulate the alternative financial service that the market may offer, it is assumed that the future interest rate follows a stochastic model with mean-reverting property, which is essentially the only required market condition to implement our method. To make it more applicable to the real financial practice, two balance settlement schemes are considered and compared. Numerical simulations with varying samplings lead to several interesting characteristics pertaining to the optimal mortgage refinancing period. Our method is robust and user friendly, thus is useful for financial institutions and individual property investors.

19.Efficient Path Planning Methods for UAVs Inspecting Power Lines

Author:Rafanavicius, V;Cimmperman, P;Taluntis, V;Man, KL;Volkvicius, G;Jurkynas, M;Bezaras, J


Abstract:Power line inspection is one of the most difficult and time consuming steps in power line maintenance. Even for a sizeable group of workers it takes months to inspect all of them, especially when they are not visible from the road and must be inspected on foot or with an aerial vehicle. That problem is even more prominent when the inspection must be done as fast as possible when the power cuts out in certain regions after natural disaster. To save time and reduce expenditure Unmanned Aerial Vehicles (UAV) could be used to film the power lines and automatically find problems (e.g. a broken cable or a tree branch too close to the a line). Our research focuses on planning the route for the survey.

20.Extension of Talenti's Inequality and Maximum Values Relative to Rearrangement Classes

Author:Emamizadeh, B;Liu, YC;Porru, G


Abstract:The article starts by revisiting and extending the Talenti's inequality where the sharpness of the extended inequality is also addressed. The process leading to the extension comprises two steps. First, an observation that the Talenti's inequality indeed can be formulated in terms of a rearrangement class. Second, proving that the inequality holds even when the rearrangement class is replaced by a much bigger (modulo trivial cases) set namely an appropriate closure of the class. The article then continues to introduce and explore a related maximization problem, associated to the classical Poisson equation, where the admissible set is the class of rearrangements of a given function. The article briefly explains the physical interest in this optimization problem. The existence of optimal solutions is proved and the optimality conditions they satisfy are explicitly derived. The particular case where the rearrangement class is built out of a characteristic function is also discussed.
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