Search results for: Yit Jian Liang

Authors: Liang Wang, Beste F. Yuksel, David Guy Brizan

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A computational model of affect that can distinguish between spontaneous and posed smiles with no errors on a large, popular data set using deep learning techniques is presented in this paper. A Long Short-Term Memory (LSTM) classifier, a type of Recurrent Neural Network, is utilized and compared to human classification. Results showed that while human classification (mean of 0.7133) was above chance, the LSTM model was more accurate than human classification and other comparable state-of-the-art systems. Additionally, a high accuracy rate was maintained with small amounts of training videos (70 instances). The derivation of important features to further understand the success of our computational model were analyzed, and it was inferred that thousands of pairs of points within the eyes and mouth are important throughout all time segments in a smile. This suggests that distinguishing between a posed and spontaneous smile is a complex task, one which may account for the difficulty and lower accuracy of human classification compared to machine learning models.

Keywords: affective computing, affect detection, computer vision, deep learning, human-computer interaction, machine learning, posed smile detection, spontaneous smile detection

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Authors: Heng Yang, Tao Luo, Yakun Zhang, Kai Wang, Wei Qin, Liang Xie, Ye Yan, Erwei Yin

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Recent years have seen that audio-visual recognition has shown great potential in a strong noise environment. The existing method of audio-visual recognition has explored methods with ResNet and feature fusion. However, on the one hand, ResNet always occupies a large amount of memory resources, restricting the application in engineering. On the other hand, the feature merging also brings some interferences in a high noise environment. In order to solve the problems, we proposed an effective framework with bidirectional distillation. At first, in consideration of the good performance in extracting of features, we chose the light model, Efficientnet as our extractor of spatial features. Secondly, self-distillation was applied to learn more information from raw data. Finally, we proposed a bidirectional distillation in decision-level fusion. In more detail, our experimental results are based on a multi-model dataset from 24 volunteers. Eventually, the lipreading accuracy of our framework was increased by 2.3% compared with existing systems, and our framework made progress in audio-visual fusion in a high noise environment compared with the system of audio recognition without visual.

Keywords: lipreading, audio-visual, Efficientnet, distillation

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Authors: Bingjie Wang, Qianqian Qang, Nan Lu, Xiubing Liang, Baolong Shen

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Novel composites of HfNbTaTiZrV refractory high-entropy alloy (RHEA) reinforced with 0-5 vol.% Al₂O₃ particles have been synthesized by vacuum arc melting. The microstructure evolution, compressive mechanical properties at room and elevated temperatures, as well as strengthening mechanism of the composites, are analyzed. The HfNbTaTiZrV RHEA reinforced with 4 vol.% Al₂O₃ displays excellent phase stability at elevated temperatures. A superior compressive yield strength of 2700 MPa at room temperature, 1392 MPa at 800 °C, and 693 MPa at 1000 °C has been obtained for this composite. The improved yield strength results from multiple strengthening mechanisms caused by Al₂O₃ addition, including interstitial strengthening, grain boundary strengthening, and dispersion strengthening. Besides, the effects of interstitial strengthening increase with the temperature and is the main strengthening mechanism at elevated temperatures. These findings not only promote the development of oxide-reinforced RHEAs for challenging engineering applications but also provide guidelines for the design of light refractory materials with multiple strengthening mechanisms.

Keywords: Al₂O₃-reinforcement, HfNbTaTiZrV, refractory high-entropy alloy, interstitial strengthening

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Authors: Feng Ji Mervin Goh, Edmund Chee Jian Pua, Stuart Alexander Cook

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Dilated cardiomyopathy (DCM) is a common cause of heart failure. Genetic mutations account for 50% of DCM cases with TTN mutations being the most common, accounting for up to 25% of DCM cases. However, the genetic architecture underlying Asian DCM patients is unknown. We evaluated 68 patients (female= 17) with DCM who underwent follow-up at the National Heart Centre, Singapore from 2013 through 2014. Clinical data were obtained and analyzed retrospectively. Genomic DNA was subjected to next-generation targeted sequencing. Nextera Rapid Capture Enrichment was used to capture the exons of a panel of 169 cardiac genes. DNA libraries were sequenced as paired-end 150-bp reads on Illumina MiSeq. Raw sequence reads were processed and analysed using standard bioinformatics techniques. The average age of onset of DCM was 46.1±10.21 years old. The average left ventricular ejection fraction (LVEF), left ventricular diastolic internal diameter (LVIDd), left ventricular systolic internal diameter (LVIDs) were 26.1±11.2%, 6.20±0.83cm, and 5.23±0.92cm respectively. The frequencies of mutations in major DCM-associated genes were as follows TTN (5.88% vs published frequency of 20%), LMNA (4.41% vs 6%), MYH7 (5.88% vs 4%), MYH6 (5.88% vs 4%), and SCN5a (4.41% vs 3%). The average callability at 10 times coverage of each major gene were: TTN (99.7%), LMNA (87.1%), MYH7 (94.8%), MYH6 (95.5%), and SCN5a (94.3%). In conclusion, TTN mutations are not common in Singaporean DCM patients. The frequencies of other major DCM-associated genes are comparable to frequencies published in the current literature.

Keywords: heart failure, dilated cardiomyopathy, genetics, next-generation sequencing

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Authors: Wei Tian, Jie Liang, Hammad Naveed

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Beta-barrel membrane proteins are found in the outer membrane of gram-negative bacteria, mitochondria, and chloroplasts. They carry out diverse biological functions, including pore formation, membrane anchoring, enzyme activity, and bacterial virulence. In addition, beta-barrel membrane proteins increasingly serve as scaffolds for bacterial surface display and nanopore-based DNA sequencing. Due to difficulties in experimental structure determination, they are sparsely represented in the protein structure databank and computational methods can help to understand their biophysical principles. We have developed a novel computational method to predict the 3D structure of beta-barrel membrane proteins using evolutionary coupling (EC) constraints and a reduced state space. Combined with an empirical potential function, we can successfully predict strand register at > 80% accuracy for a set of 49 non-homologous proteins with known structures. This is a significant improvement from previous results using EC alone (44%) and using empirical potential function alone (73%). Our method is general and can be applied to genome-wide structural prediction.

Keywords: beta-barrel membrane proteins, structure prediction, evolutionary constraints, reduced state space

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Authors: Fu-Chien Hung, Chi‐Wen Liang

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Background: People who suffer from chronic fatigue syndrome (CFS) frequently complain about continuous tiredness, weakness or lack of strength, but without apparent organic etiology. The prevalence rate of the CFS is nearly from 3% to 20%, yet more than 80% go undiagnosed or misdiagnosed as depression. The biopsychosocial model has suggested the associations among the CFS, depressive syndrome, and stress. This study aimed to investigate the difference between individuals with the CFS and with the depressive syndrome on psychophysiological responses under stress. Method: There were 23 participants in the CFS group, 14 participants in the depression group, and 23 participants in the healthy control group. All of the participants first completed the measures of demographic data, CFS-related symptoms, daily life functioning, and depressive symptoms. The participants were then asked to perform a stressful cognitive task. The participants’ psychophysiological responses including the HR, BVP and SC were measured during the task. These indexes were used to assess the reactivity and recovery rates of the automatic nervous system. Results: The stress reactivity of the CFS and depression groups was not different from that of the healthy control group. However, the stress recovery rate of the CFS group was worse than that of the healthy control group. Conclusion: The results from this study suggest that the CFS is a syndrome which can be independent from the depressive syndrome, although the depressive syndrome may include fatigue syndrome.

Keywords: chronic fatigue syndrome, depression, stress response, misdiagnosis

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Authors: Fu-Chi Chuang, Yu-Liang, Chang, Wen-Der Wang

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Our environment has been contaminated by many artificial chemicals, such as plastics, pesticides. Many of them have hormone-like activity and are classified as 'environmental hormone (also named endocrine disruptors)'. These chemicals interfere with or mimic hormones have adverse effects that persist into adulthood. Environmental education is an important way to teach students to become engaged in real-world issues that transcend classroom walls. Elementary education is the first stage to perform environmental education and it is an important component to help students develop adequate environmental knowledge, attitudes, and behavior. However, elementary teachers' knowledge plays a critical role in this mission. Therefore, we use a questionnaire to survey the knowledge of environmental hormone of elementary school teachers and their learning motivation of the environmental hormone-regarding knowledge. We collected 218 questionnaires from Taiwanese elementary teachers and the results indicate around 73% of elementary teachers do not have enough knowledge about environmental hormones. Our results also reveal the in-service elementary teachers’ learning motivation of environmental hormones knowledge is positively enhanced once they realized their insufficient cognitive ability of environmental hormones. We believe our study will provide the powerful reference for Ministry of Education to set up the policy of environmental education to enrich all citizens sufficient knowledge of the effects of the environmental hormone on organisms, and further to enhance our correct environmental behaviors.

Keywords: elementary teacher, environmental hormones, learning motivation, questionnaire

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Authors: Anes Enakoa, Yawei Liang

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Question Answering (QA) system is one of the most important and demanding tasks in the field of Natural Language Processing (NLP). In QA systems, the answer generation task generates a list of candidate answers to the user's question, in which only one answer is correct. Answer selection is one of the main components of the QA, which is concerned with selecting the best answer choice from the candidate answers suggested by the system. However, the selection process can be very challenging especially in Arabic due to its particularities. To address this challenge, an approach is proposed to answer questions with multiple answer choices for Arabic QA systems based on Textual Entailment (TE) recognition. The developed approach employs a Support Vector Machine that considers lexical, semantic and syntactic features in order to recognize the entailment between the generated hypotheses (H) and the text (T). A set of experiments has been conducted for performance evaluation and the overall performance of the proposed method reached an accuracy of 67.5% with C@1 score of 80.46%. The obtained results are promising and demonstrate that the proposed method is effective for TE recognition task.

Keywords: information retrieval, machine learning, natural language processing, question answering, textual entailment

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Authors: Yang Yu, Jian Wang, Jiqiang Liu, Lei Han, Xudong He, Shaohua Lv

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As the increasing network attacks become more and more complex, network situation assessment based on log analysis cannot meet the requirements to ensure network security because of the low quality of logs and alerts. This paper addresses the lack of consideration of security attributes of hosts and attacks in the network. Identity and effectiveness of Distributed Denial of Service (DDoS) are hard to be proved in risk assessment based on alerts and flow matching. This paper proposes a multi-dimension threat situation assessment method based on network security attributes. First, the paper offers an improved Common Vulnerability Scoring System (CVSS) calculation, which includes confident risk, integrity risk, availability risk and a weighted risk. Second, the paper introduces deterioration rate of properties collected by sensors in hosts and network, which aimed at assessing the time and level of DDoS attacks. Third, the paper introduces distribution of asset value in security attributes considering features of attacks and network, which aimed at assessing and show the whole situation. Experiments demonstrate that the approach reflects effectiveness and level of DDoS attacks, and the result can show the primary threat in network and security requirement of network. Through comparison and analysis, the method reflects more in security requirement and security risk situation than traditional methods based on alert and flow analyzing.

Keywords: DDoS evaluation, improved CVSS, network security attribute, threat situation assessment

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Authors: Rong Liu, Kuiying Chen, Ju Chen, Jingrong Zhao, Ming Liang

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This article presents modeling studies of NiAl alloy under solid-particle erosion and liquid-drop erosion. In the solid particle erosion simulation, attention is paid to the oxide scale thickness variation on the alloy in high-temperature erosion environments. The erosion damage is assumed to be deformation wear and cutting wear mechanisms, incorporating the influence of the oxide scale on the eroded surface; thus the instantaneous oxide thickness is the result of synergetic effect of erosion and oxidation. For liquid-drop erosion, special interest is in investigating the effects of drop velocity and drop size on the damage of the target surface. The models of impact stress wave, mean depth of penetration, and maximum depth of erosion rate (Max DER) are employed to develop various maps for NiAl alloy, including target thickness vs. drop size (diameter), rate of mean depth of penetration (MDRP) vs. drop impact velocity, and damage threshold velocity (DTV) vs. drop size.

Keywords: liquid-drop erosion, NiAl alloy, oxide scale thickness, solid-particle erosion

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Authors: Xiang Li, Jian-Qiao Sun

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As the crucial component of city traffic network, intersections have significant impacts on urban traffic performance. Despite of the rapid development in transportation systems, increasing traffic volumes result in severe congestions especially at intersections in urban areas. Effective regulation of vehicle flows at intersections has always been an important issue in the traffic control system. This study presents a multi-objective optimization method at intersections with cellular automata to achieve better traffic performance. Vehicle conflicts and pedestrian interference are considered. Three categories of the traffic performance are studied including transportation efficiency, energy consumption and road safety. The left-turn signal type, signal timing and lane assignment are optimized for different traffic flows. The multi-objective optimization problem is solved with the cell mapping method. The optimization results show the conflicting nature of different traffic performance. The influence of different traffic variables on the intersection performance is investigated. It is observed that the proposed optimization method is effective in regulating the traffic at the intersection to meet multiple objectives. Transportation efficiency can be usually improved by the permissive left-turn signal, which sacrifices safety. Right-turn traffic suffers significantly when the right-turn lanes are shared with the through vehicles. The effect of vehicle flow on the intersection performance is significant. The display pattern of the optimization results can be changed remarkably by the traffic volume variation. Pedestrians have strong interference with the traffic system.

Keywords: cellular automata, intersection, multi-objective optimization, traffic system

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Authors: C. C. Liang

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MSN used to be the most popular application for communicating among social networks, but Facebook chat is now the most popular. Facebook and MSN have similar characteristics, including usefulness, ease-of-use, and a similar function, which is the exchanging of information with friends. Facebook outperforms MSN in both of these areas. However, the adoption of Facebook and abandonment of MSN have occurred for other reasons. Functions can be improved, but users’ willingness to use does not just depend on functionality. Flow status has been established to be crucial to users’ adoption of cyber applications and to affects users’ adoption of software applications. If users experience flow in using software application, they will enjoy using it frequently, and even change their preferred application from an old to this new one. However, no investigation has examined choice behavior related to switching from Facebook to MSN based on a consideration of flow experiences and functions. This investigation discusses the flow experiences and functions of social-networking applications. Flow experience is found to affect perceived ease of use and perceived usefulness; perceived ease of use influences information ex-change with friends, and perceived usefulness; information exchange influences perceived usefulness, but information exchange has no effect on flow experience.

Keywords: consumer behavior, social media, technology acceptance model, flow experience

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Authors: Chen-Yu Chen, Wei-Mon Yan, Chi-Nan Lai, Jian-Hao Su

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The proton exchange membrane fuel cell (PEMFC) becomes more important as an alternative energy source recently. Maintaining proper water content in the membrane is one of the key requirements for optimizing the PEMFC performance. The planar membrane humidifier has the advantages of simple structure, low cost, low-pressure drop, light weight, reliable performance and good gas separability. Thus, it is a common external humidifier for PEMFCs. In this work, a planar membrane humidifier for kW-scale PEMFCs is developed successfully. The heat and mass transfer of humidifier is discussed, and its performance is analyzed in term of dew point approach temperature (DPAT), water vapor transfer rate (WVTR) and water recovery ratio (WRR). The DPAT of the humidifier with the counter flow approach reaches about 6°C under inlet dry air of 50°C and 60% RH and inlet humid air of 70°C and 100% RH. The rate of pressure loss of the humidifier is 5.0×10² Pa/min at the torque of 7 N-m, which reaches the standard of commercial planar membrane humidifiers. From the tests, it is found that increasing the air flow rate increases the WVTR. However, the DPAT and the WRR are not improved by increasing the WVTR as the air flow rate is higher than the optimal value. In addition, increasing the inlet temperature or the humidity of dry air decreases the WVTR and the WRR. Nevertheless, the DPAT is improved at elevated inlet temperatures or humidities of dry air. Furthermore, the performance of the humidifier with the counter flow approach is better than that with the parallel flow approach. The DPAT difference between the two flow approaches reaches up to 8 °C.

Keywords: heat and mass transfer, humidifier performance, PEM fuel cell, planar membrane humidifier

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Authors: Jian Li

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The uncertainty quantification and inversion problems of subsurface oil-water phase flow usually require extensive repeated forward calculations for new runs with changed conditions. To reduce the computational time, various forms of surrogate models have been built. Related research shows that deep learning has emerged as an effective surrogate model, while most surrogate models with deep learning are purely data-driven, which always leads to poor robustness and abnormal results. To guarantee the model more consistent with the physical laws, a coupled theory-guided convolutional neural network (TgCNN) based surrogate model is built to facilitate computation efficiency under the premise of satisfactory accuracy. The model is a convolutional neural network based on multi-well reservoir simulation. The core notion of this proposed method is to bridge two separate blocks on top of an overall network. They underlie the TgCNN model in a coupled form, which reflects the coupling nature of pressure and water saturation in the two-phase flow equation. The model is driven by not only labeled data but also scientific theories, including governing equations, stochastic parameterization, boundary, and initial conditions, well conditions, and expert knowledge. The results show that the TgCNN-based surrogate model exhibits satisfactory accuracy and efficiency in subsurface oil-water phase flow under multi-well conditions.

Keywords: coupled theory-guided convolutional neural network, multi-well conditions, surrogate model, subsurface oil-water phase

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Authors: Ting-Yu Hsu, Shyu-Yu Wu, Shieh-Kung Huang, Hung-Wei Chiang, Kung-Chun Lu, Pei-Yang Lin, Kuo-Liang Wen

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Regional earthquake early warning (EEW) systems are not suitable for Taiwan, as most destructive seismic hazards arise due to in-land earthquakes. These likely cause the lead-time provided by regional EEW systems before a destructive earthquake wave arrives to become null. On the other hand, an on-site EEW system can provide more lead-time at a region closer to an epicenter, since only seismic information of the target site is required. Instead of leveraging the information of several stations, the on-site system extracts some P-wave features from the first few seconds of vertical ground acceleration of a single station and performs a prediction of the oncoming earthquake intensity at the same station according to these features. Since seismometers could be triggered by non-earthquake events such as a passing of a truck or other human activities, to reduce the likelihood of false alarms, a seismometer was installed at three different locations on the same site and the performance of the EEW system for these three sensor locations were discussed. The results show that the location on the ground of the first floor of a school building maybe a good choice, since the false alarms could be reduced and the cost for installation and maintenance is the lowest.

Keywords: earthquake early warning, on-site, seismometer location, support vector machine

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Authors: Cheng-Cao Sun, Shu-Jun Li, Cuili Yang, Yongyong Xi, Liang Wang, Feng Zhang, De-Jia Li

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Hsa-miRNA-326 (miR-326) has recently been discovered having anticancer efficacy in different organs. However, the role of miR-326 on non-small cell lung cancer (NSCLC) is still ambiguous. In this study, we investigated the role of miR-326 on the development of NSCLC. The results indicated that miR-326 was significantly down-regulated in primary tumor tissues and very low levels were found in NSCLC cell lines. Ectopic expression of miR-326 in NSCLC cell lines significantly suppressed cell growth as evidenced by cell viability assay, colony formation assay and BrdU staining, through inhibition of cyclin D1, cyclin D2, CDK4, and up-regulation of p57(Kip2) and p21(Waf1/Cip1). In addition, miR-326 induced apoptosis, as indicated by concomitantly with up-regulation of key apoptosis protein cleaved caspase-3, and down-regulation of anti-apoptosis protein Bcl2. Moreover, miR-326 inhibited cellular migration and invasiveness through inhibition of matrix metalloproteinases (MMP)-7 and MMP-9. Further, oncogene CCND1 was revealed to be a putative target of miR-326, which was inversely correlated with miR-326 expression in NSCLC. Taken together, our results demonstrated that miR-326 played a pivotal role on NSCLC through inhibiting cell proliferation, migration, invasion, and promoting apoptosis by targeting oncogenic CCND1.

Keywords: hsa-miRNA-326 (miR-326), cyclin D1, non-small cell lung cancer (NSCLC), proliferation, apoptosis

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Authors: Chih-Hung Liang, Jung-Jung Chen, Shen-Shih Chiang

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Obesity is defined as abnormal or excessive fat accumulation that presents a risk to health, which are major risk factors for a number of chronic diseases, including diabetes, cardiovascular diseases and cancer. Cordyceps militaris (CM) is a well-known traditional medicine in Asian countries and a rich source of biologically active components. Black rice (Oryza sativa L.) is a special cultivar of rice that contains rich anthocyanins and regarded as a health-promoting food in China and other Eastern. The aim of this study was to investigate the anti-obesity effect of Cordyceps militaris fermented black rice (CB) on HFD-induced BALB/c mice model. The results indicated that administration of low and high dosage of CB powder significantly reduced the body weights (7.38% and 7.78%), body fat ratio (2.37% and 2.78%), aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels compared to the HF group (p<0.05). Histopathological analysis showed that the score of fatty liver in HF group (5.0) was significantly higher than CB groups (2.1 and 3.6) (p<0.05). In conclusion, Cordyceps militaris fermented black rice can reduce the body weight via inhibition of the fat accumulation in liver and body and possess the anti-obesity potency.

Keywords: Cordyceps militaris, black rice, obesity, HFD-induced mice

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Authors: Ying-Ming Su

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Fujian earthen building which was known as a classic for ecological buildings was listed on the world heritage in 2008 (UNESCO) in China. Its design strategy can be applied to modern architecture planning and design. This study chose two different cases (Round Atrium: Er-Yi Building, Double Round Atrium: Zhen-Chen Building) of earthen building in Fu-Jian to compare the ventilation effects of different atrium forms. We adopt field measurements and computational fluid dynamics (CFD) simulation of temperature, humidity, and wind environment to identify the relationship between external environment and atrium about comfort and to confirm the relationship about atrium H/W (height/width). Results indicate that, through the atrium convection effect, it makes the natural wind guides to each space surrounded and keeps indoor comfort. It illustrates that the smaller the ratio of the H/W which is the relationship between the height and the width of an atrium is, the greater the wind speed generated within the street valley. Moreover, the wind speed is very close to the reference wind speed. This field measurement verifies that the value of H/W has great influence of solar radiation heat and sunshine shadows. The ventilation efficiency is: Er-Yi Building (H/W =0.2778) > Zhen-Chen Building (H/W=0.3670). Comparing the cases with the same shape but with different H/W, through the different size patios, airflow revolves in the atriums and can be brought into each interior space. The atrium settings meet the need of building ventilation, and can adjust the humidity and temperature within the buildings. It also creates good ventilation effect.

Keywords: traditional folk houses, atrium, tulou, ventilation, building microclimate

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Authors: Haoyang Liang, Dandong Ge

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With the rapid development of Chinese cities, traffic congestion has become more and more serious. At the same time, there are many closed old residential area in Chinese cities, which seriously affect the connectivity of urban roads and reduce the density of urban road networks. After reopening the restricted old residential area, the internal roads in the original residential area were transformed into urban roads, which was of great help to alleviate traffic congestion. This paper uses the spatial syntactic theory to analyze the urban road network and compares the roads with the integration and connectivity degree to evaluate whether the opening of the roads in the residential areas can improve the urban traffic. Based on the road network system within the first loop road in Kunming, the Space Syntax evaluation model is established for status analysis. And comparative analysis method will be used to compare the change of the model before and after the road openness of the old urban residential district within the first-ring road in Kunming. Then it will pick out the areas which indicate a significant difference for the small dimensions model analysis. According to the analyzed results and traffic situation, the evaluation of road openness in the old urban residential district will be proposed to improve the urban residential districts.

Keywords: Space Syntax, Kunming, urban renovation, traffic jam

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Authors: Chengcao Sun, Shujun Li, Cuili Yang, Yongyong Xi, Liang Wang, Feng Zhang, Dejia Li

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Recently, the long non-coding RNA (lncRNA) NEAT1 has been identified as an oncogenic gene in multiple cancer types and elevated expression of NEAT1 was tightly linked to tumorigenesis and cancer progression. However, the molecular basis for this observation has not been characterized in progression of non-small cell lung cancer (NSCLC). In our studies, we identified NEAT1 was highly expressed in NSCLC patients and was a novel regulator of NSCLC progression. Patients whose tumors had high NEAT1 expression had a shorter overall survival than patients whose tumors had low NEAT1 expression. Further, NEAT1 significantly accelerates NSCLC cell growth and metastasis in vitro and tumor growth in vivo. Additionally, by using bioinformatics study and RNA pull down combined with luciferase reporter assays, we demonstrated that NEAT1 functioned as a competing endogenous RNA (ceRNA) for has-miR-377-3p, antagonized its functions and led to the de-repression of its endogenous targets E2F3, which was a core oncogene in promoting NSCLC progression. Taken together, these observations imply that the NEAT1 modulated the expression of E2F3 gene by acting as a competing endogenous RNA, which may build up the missing link between the regulatory miRNA network and NSCLC progression.

Keywords: long non-coding RNA NEAT1, hsa-miRNA-377-3p, E2F3, non-small cell lung cancer, tumorigenesis

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Authors: Changchun Liang, Xiaodong Zhang, Xin Liu, Pengfei Sun

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Space intelligent robotic systems are expected to play an increasingly important role in the future. The robotic on-orbital service, whose key is the tracking and capturing technology, becomes research hot in recent years. In this paper, the authors propose a vision servo control system for target capturing. Robotic manipulator will be an intelligent robotic system with large-scale movement, functional agility, and autonomous ability, and it can be operated by astronauts in the space station or be controlled by the ground operator in the remote operation mode. To realize the autonomous movement and capture mission of SRM, a kind of autonomous programming strategy based on multi-camera vision fusion is designed and the selection principle of object visual position and orientation measurement information is defined for the better precision. Distributed control system hierarchy is designed and reliability is considering to guarantee the abilities of control system. At last, a ground experiment system is set up based on the concept of robotic control system. With that, the autonomous target capturing experiments are conducted. The experiment results validate the proposed algorithm, and demonstrates that the control system can fulfill the needs of function, real-time and reliability.

Keywords: control system, on-orbital service, space robot, vision servo

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Authors: Terry Liang Khin Teo, Sun Woh Lye, Kai Lun Brendon Goh

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As applied to dynamic monitoring situations, the prevailing approach to situation awareness (SA) assumes that the relevant areas of interest (AOI) be perceived before that information can be processed further to affect decision-making and, thereafter, action. It is not entirely clear whether this is the case. This study seeks to investigate the monitoring of dynamic objects through matching eye fixations with the relevant AOIs in boundary-crossing scenarios. By this definition, a match is where a fixation is registered on the AOI. While many factors may affect monitoring characteristics, traffic simulations were designed in this study to explore two factors, namely: the number of inbounds/outbound traffic transfers and the number of entry and/or exit points in a radar monitoring sector. These two factors were graded into five levels of difficulty ranging from low to high traffic flow numbers. Combined permutation in terms of levels of difficulty of these two factors yielded a total of thirty scenarios. Through this, results showed that changes in the traffic flow numbers on transfer resulted in greater variations having match limits ranging from 29%-100%, as compared to the number of sector entry/exit points of range limit from 80%-100%. The subsequent analysis is able to determine the type and combination of traffic scenarios where imperfect matching is likely to occur.

Keywords: air traffic simulation, eye-tracking, visual monitoring, focus attention

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Authors: Han Bai, Lemei Yu, Tong Zhang, Doudou Xie, Liang Zhao

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The brightness changes at highway tunnel entrance and exit have an effect on the physical and psychological conditions of drivers. It is more conducive for examining driving safety with quantitative analysis of the physical and psychological characteristics of drivers to determine the speed limit sign locations at the tunnel entrance and exit sections. In this study, the physical and psychological effects of tunnels on traffic sign recognition of drivers are analyzed; subsequently, experiments with the assistant of Eyelink-II Type eye movement monitoring system are conducted in the typical tunnels in Ji-Qing freeway and Xi-Zha freeway, to collect the data of eye movement indexes “Fixation Duration” and “Eyeball Rotating Speed”, which typically represent drivers' mental load and visual characteristics. On this basis, the paper establishes a visual recognition model for the speed limit signs at the highway tunnel entrances and exits. In combination with related standards and regulations, it further presents the recommended values for locating speed limit signs under different tunnel conditions. A case application on Panlong tunnel in Ji-Qing freeway is given to generate the helpful improvement suggestions.

Keywords: driver psychological load, eye movement index, speed limit sign location, tunnel entrance and exit

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Authors: Meng-Huan Wu, Wei-Er Wang, Tsu-Nai Wang, Wei-Jian Hsu, Vincent Chin-Hung Chen

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Objective: Studies have reported a strong link between asthma and bipolar disorder. We conducted a 17-year community-based large cohort study to examine the relationship between asthma, early smoking initiation, and bipolar disorder during adolescence and early adulthood. Methods: A total of 162,766 participants aged 11–16 years were categorized into asthma and non-asthma groups at baseline and compared within the observation period. Covariates during late childhood or adolescence included parental education, cigarette smoking by family members of participants, and participant’s gender, age, alcohol consumption, smoking, and exercise habits. Data for urbanicity, prednisone use, allergic comorbidity, and Charlson comorbidity index were acquired from the National Health Insurance Research Database. The Cox proportional-hazards model was used to evaluate the association between asthma and bipolar disorder. Results: Our findings revealed that asthma increased the risk of bipolar disorder after adjustment for key confounders in the Cox proportional hazard regression model (adjusted HR: 1.31, 95% CI: 1.12-1.53). Hospitalizations or visits to the emergency department for asthma exhibited a dose–response effect on bipolar disorder (adjusted HR: 1.59, 95% CI: 1.22-2.06). Patients with asthma with onset before 20 years of age who smoked during late childhood or adolescence had the greatest risk for bipolar disorder (adjusted HR: 3.10, 95% CI: 1.29-7.44). Conclusions: Patients newly diagnosed with asthma had a 1.3 times higher risk of developing bipolar disorder. Smoking during late childhood or adolescence increases the risk of developing bipolar disorder in patients with asthma.

Keywords: adolescence, asthma, smoking, bipolar disorder, early adulthood

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Authors: Li Guoyou, Zhang Tao, Ji Wenzhan, Huo Liang, Lin Xiqiang, Zhang Nan

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The three dimensional (3D) printing technology has undergone rapid development in the last few years and it is possible to print engineering structures. 3D printing buildings use wastes from constructions, industries and mine tailings as “ink”, and mix it with property improved materials, such as cement, fiber etc. This paper presents a study of the Thermodynamic performance of 3D printed walls using cement and steel slag powder. Analyses the thermal simulation regarding 3D printed walls and solid brick wall by the way of the hot-box methods and the infrared technology, and the results were contrasted with theoretical calculation. The results show that the excellent thermodynamic performance of 3D printed concrete wall made it suitable as the partial materials for self-thermal insulation walls in residential buildings. The thermodynamic performance of 3D printed concrete walls depended on the density of materials, distribution of holes, and the filling materials. Decreasing the density of materials, increasing the number of holes or replacing the filling materials with foamed concrete could improve its thermodynamic performance significantly. The average of heat transfer coefficient and thermal inertia index of 3D printed steel slag powder concrete wall all better than the traditional solid brick wall with a thickness of 240mm.

Keywords: concrete, 3D printed walls, thermodynamic performance, steel slag powder

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Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

Abstract:

The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluate the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: convolutional neural network, electronic medical record, feature representation, lexical semantics, semantic decision

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Authors: Lijuan Wang, Junsheng Huo, Jing Sun, Wenxian Li, Jian Huang, Lin Ling, Yiping Zhou, Chengyu Huang, Jifang Hu

Abstract:

Backgrounds and Objective: This study aimed to evaluate the impact of highly nutrient-dense complementary food supplement-Yingyangbao, at the time of 3 months after Wenchuan earthquake, on the anemia of young children in a county in Sichuan province. Methods: The young children aged 6-23 months in the county were fed one sachet Yingyangbao per day. Yingyangbao were distributed for 15 months for free. The children entering 6 months age would be included. The length, weight and hemoglobin of the children aged 6-29 months were assessed at baseline (n=257) and Yingyangbao intervention for 6 (n=218) and 15 months (n=253) by cluster sampling. Growth status has not been described in the paper. The analysis was conducted based on 6-11, 12-17, 18-23 and 24-29 months. Results: It showed that the hemoglobin concentration in each group among the 4 groups increased by 4.9, 6.4, 8.0, 9.5 g/L after 6 months and 12.7, 11.4, 16.7, 15.7 g/L after 15 months compared to the baseline, respectively. The total anemia prevalence in each group was significantly lower after 6 and 15 months than the baseline (P<0.001), except the 6-11 months group after 6 months because of fewer Yingyangbao consumption. Total moderate anemia rate decreased from 18.3% to 5.5% after 6 months, and kept decreasing to 0.8% after another 9 months. The hemoglobin concentration was significantly correlated with the amount of Yingyangbao consumption(P<0.001) The anemia rate was significantly different based on the Yingyangbao compliance (P<0.001). Conclusion: It was concluded that Yingyangbao which contains quality protein, vitamins and micronutrients intervened 15 months could be effective for the improvement of anemia of young children. The study provides the support that the application of the complementary food supplements to reduce the anemia of young children in the emergency of natural disaster.

Keywords: young children, anemia, nutrition intervention, complementary food supplements, Yingyangbao

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Authors: Sophia Hayes, Kenny L. Liang, Sahil Sharma, Austin Shema, Mahmoud Bader, Mohamed Elbarkouky

Abstract:

Despite being one of the most significant economic contributors of the country, Canada’s construction industry is lagging behind other sectors when it comes to labor productivity improvements. The construction industry is very collaborative as a general contractor, will hire trade contractors to perform most of a project’s work; meaning low productivity from one contractor can have a domino effect on the shared success of a project. To address this issue and encourage trade contractors to improve their productivity tracking methods, an investigative study was done on the productivity views and tracking methods of various trade contractors. Additionally, an in-depth review was done on four standard tracking methods used in the construction industry: cost codes, benchmarking, the job productivity measurement (JPM) standard, and WorkFace Planning (WFP). The four tracking methods were used as a baseline in comparing the trade contractors’ responses, determining gaps within their current tracking methods, and for making improvement recommendations. 15 interviews were conducted with different trades to analyze how contractors value productivity. The results of these analyses indicated that there seem to be gaps within the construction industry when it comes to an understanding of the purpose and value in productivity tracking. The trade contractors also shared their current productivity tracking systems; which were then compared to the four standard tracking methods used in the construction industry. Gaps were identified in their various tracking methods and using a framework; recommendations were made based on the type of trade on how to improve how they track productivity.

Keywords: labor productivity, productivity tracking methods, trade contractors, construction

Procedia PDF Downloads 166

Authors: Hang Meng, Wen-Bin Liu, Bi Xiao, Kai-Jun Ma, Jian-Hui Xie, Geng Fei, Tian-Ye Zhang, Lu-Yi Xu, Dong-Chuan Zhang

Abstract:

The victims in water are often found in the coastal region, along river region or the region with lakes. In China, the examination for the bodies of victims in the water is conducted by forensic doctors working in the public security bureau. Because the enter water time for most of the victims are not clear, and often lack of monitor images and other information, so to find out the corpse enter water time for victims is very difficult. After the corpse of the victim enters the water, it sinks first, then corruption gas produces, which can make the density of the corpse to be less than water, and thus rise again. So the factor that determines the corpse floating time is temperature. On the basis of the temperature data obtained in Shanghai region of China (Shanghai is a north subtropical marine monsoon climate, with an average annual temperature of about 17.1℃. The hottest month is July, the average monthly temperature is 28.6℃, and the coldest month is January, the average monthly temperature is 4.8℃). This study selected about 100 cases with definite corpse enter water time and corpse floating time, analyzed the cases and obtained the empirical law of the corpse floating time. For example, in the Shanghai region, on June 15th and October 15th, the corpse floating time is about 1.5 days. In early December, the bodies who entered the water will go up around January 1st of the following year, and the bodies who enter water in late December will float in March of next year. The results of this study can be used to roughly estimate the water enter time of the victims in Shanghai. Forensic doctors around the world can also draw on the results of this study to infer the time when the corpses of the victims in the water go up.

Keywords: corpse enter water time, corpse floating time, drowning, forensic pathology, victims in the water

Procedia PDF Downloads 171

Authors: Dawoon Choi, Jian Li, Yunhyun Cho

Abstract:

Axial Flux Permanent Magnet (AFPM) machines have been widely used in various applications due to their important merits, such as compact structure, high efficiency and high torque density. This paper presents one of the most important characteristics in the design process of the AFPM device, which is a recent issue. To design AFPM machine, the predicting electromagnetic forces between the permanent magnets and stator is important. Because of the magnitude of electromagnetic force affects many characteristics such as machine size, noise, vibration, and quality of output power. Theoretically, this force is canceled by the equilibrium of force when it is in the middle of the gap, but it is inevitable to deviate due to manufacturing problems in actual machine. Such as large scale wind generator, because of the huge attractive force between rotor and stator disks, this is more serious in getting large power applications such as large. This paper represents the characteristics of Double-Stator Inner –Rotor AFPM machines when it has rotor eccentricity. And, unbalanced air-gap and inclined air-gap condition which is caused by rotor offset and tilt in a double-stator single inner-rotor AFPM machine are each studied in electromagnetic and mechanical aspects. The output voltage and cogging torque under un-normal air-gap condition of AF machines are firstly calculated using a combined analytical and numerical methods, followed by a structure analysis to study the effect to mechanical stress, deformation and bending forces on bearings. Results and conclusions given in this paper are instructive for the successful development of AFPM machines.

Keywords: axial flux permanent magnet machine, inclined air gap, unbalanced air gap, rotor eccentricity

Procedia PDF Downloads 194