Search results for: Qing Wang
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1376

Search results for: Qing Wang

1256 Hot Deformation Behavior and Recrystallization of Inconel 718 Superalloy under Double Cone Compression

Authors: Wang Jianguo, Ding Xiao, Liu Dong, Wang Haiping, Yang Yanhui, Hu Yang

Abstract:

The hot deformation behavior of Inconel 718 alloy was studied by uniaxial compression tests under the deformation temperature of 940~1040℃ and strain rate of 0.001-10s⁻¹. The double cone compression (DCC) tests develop strains range from 30% to the 79% strain including all intermediate values of stains at different temperature (960~1040℃). DCC tests were simulated by finite element software which shown the strain and strain rates distribution. The result shows that the peak stress level of the alloy decreased with increasing deformation temperature and decreasing strain rate, which could be characterized by a Zener-Hollomon parameter in the hyperbolic-sine equation. The characterization method of hot processing window containing recrystallization volume fraction and average grain size was proposed for double cone compression test of uniform coarse grain, mixed crystal and uniform fine grain double conical specimen in hydraulic press and screw press. The results show that uniform microstructures can be obtained by low temperature with high deformation followed by high temperature with small deformation on the hydraulic press and low temperature, medium deformation, multi-pass on the screw press. The two methods were applied in industrial forgings process, and the forgings with uniform microstructure were obtained successfully.

Keywords: inconel 718 superalloy, hot processing windows, double cone compression, uniform microstructure

Procedia PDF Downloads 182
1255 Integrating Virtual Reality and Building Information Model-Based Quantity Takeoffs for Supporting Construction Management

Authors: Chin-Yu Lin, Kun-Chi Wang, Shih-Hsu Wang, Wei-Chih Wang

Abstract:

A construction superintendent needs to know not only the amount of quantities of cost items or materials completed to develop a daily report or calculate the daily progress (earned value) in each day, but also the amount of quantities of materials (e.g., reinforced steel and concrete) to be ordered (or moved into the jobsite) for performing the in-progress or ready-to-start construction activities (e.g., erection of reinforced steel and concrete pouring). These daily construction management tasks require great effort in extracting accurate quantities in a short time (usually must be completed right before getting off work every day). As a result, most superintendents can only provide these quantity data based on either what they see on the site (high inaccuracy) or the extraction of quantities from two-dimension (2D) construction drawings (high time consumption). Hence, the current practice of providing the amount of quantity data completed in each day needs improvement in terms of more accuracy and efficiency. Recently, a three-dimension (3D)-based building information model (BIM) technique has been widely applied to support construction quantity takeoffs (QTO) process. The capability of virtual reality (VR) allows to view a building from the first person's viewpoint. Thus, this study proposes an innovative system by integrating VR (using 'Unity') and BIM (using 'Revit') to extract quantities to support the above daily construction management tasks. The use of VR allows a system user to be present in a virtual building to more objectively assess the construction progress in the office. This VR- and BIM-based system is also facilitated by an integrated database (consisting of the information and data associated with the BIM model, QTO, and costs). In each day, a superintendent can work through a BIM-based virtual building to quickly identify (via a developed VR shooting function) the building components (or objects) that are in-progress or finished in the jobsite. And he then specifies a percentage (e.g., 20%, 50% or 100%) of completion of each identified building object based on his observation on the jobsite. Next, the system will generate the completed quantities that day by multiplying the specified percentage by the full quantities of the cost items (or materials) associated with the identified object. A building construction project located in northern Taiwan is used as a case study to test the benefits (i.e., accuracy and efficiency) of the proposed system in quantity extraction for supporting the development of daily reports and the orders of construction materials.

Keywords: building information model, construction management, quantity takeoffs, virtual reality

Procedia PDF Downloads 104
1254 Analysis of Accurate Direct-Estimation of the Maximum Power Point and Thermal Characteristics of High Concentration Photovoltaic Modules

Authors: Yan-Wen Wang, Chu-Yang Chou, Jen-Cheng Wang, Min-Sheng Liao, Hsuan-Hsiang Hsu, Cheng-Ying Chou, Chen-Kang Huang, Kun-Chang Kuo, Joe-Air Jiang

Abstract:

Performance-related parameters of high concentration photovoltaic (HCPV) modules (e.g. current and voltage) are required when estimating the maximum power point using numerical and approximation methods. The maximum power point on the characteristic curve for a photovoltaic module varies when temperature or solar radiation is different. It is also difficult to estimate the output performance and maximum power point (MPP) due to the special characteristics of HCPV modules. Based on the p-n junction semiconductor theory, a brand new and simple method is presented in this study to directly evaluate the MPP of HCPV modules. The MPP of HCPV modules can be determined from an irradiated I-V characteristic curve, because there is a non-linear relationship between the temperature of a solar cell and solar radiation. Numerical simulations and field tests are conducted to examine the characteristics of HCPV modules during maximum output power tracking. The performance of the presented method is evaluated by examining the dependence of temperature and irradiation intensity on the MPP characteristics of HCPV modules. These results show that the presented method allows HCPV modules to achieve their maximum power and perform power tracking under various operation conditions. A 0.1% error is found between the estimated and the real maximum power point.

Keywords: energy performance, high concentrated photovoltaic, maximum power point, p-n junction semiconductor

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1253 Convective Hot Air Drying of Different Varieties of Blanched Sweet Potato Slices

Authors: M. O. Oke, T. S. Workneh

Abstract:

Drying behaviour of blanched sweet potato in a cabinet dryer using different five air temperatures (40-80oC) and ten sweet potato varieties sliced to 5 mm thickness were investigated. The drying data were fitted to eight models. The Modified Henderson and Pabis model gave the best fit to the experimental moisture ratio data obtained during the drying of all the varieties while Newton (Lewis) and Wang and Singh models gave the least fit. The values of Deff obtained for Bophelo variety (1.27 x 10-9 to 1.77 x 10-9 m2/s) was the least while that of S191 (1.93 x 10-9 to 2.47 x 10-9 m2/s) was the highest which indicates that moisture diffusivity in sweet potato is affected by the genetic factor. Activation energy values ranged from 0.27-6.54 kJ/mol. The lower activation energy indicates that drying of sweet potato slices requires less energy and is hence a cost and energy saving method. The drying behavior of blanched sweet potato was investigated in a cabinet dryer. Drying time decreased considerably with increase in hot air temperature. Out of the eight models fitted, the Modified Henderson and Pabis model gave the best fit to the experimental moisture ratio data on all the varieties while Newton, Wang and Singh models gave the least. The lower activation energy (0.27-6.54 kJ/mol) obtained indicates that drying of sweet potato slices requires less energy and is hence a cost and energy saving method.

Keywords: sweet potato slice, drying models, moisture ratio, moisture diffusivity, activation energy

Procedia PDF Downloads 484
1252 Effects of Dust Storm Events on Tuberculosis Incidence Rate in Northwest of China

Authors: Yun Wang, Ruoyu Wang, Tuo Chen, Guangxiu Liu, Guodong Chen, Wei Zhang

Abstract:

Tuberculosis (TB) is a major public health problem in China. China has the world's second largest tuberculosis epidemic (after India). Xinjiang almost has the highest annual attendance rate of TB in China, and the province is also famous because of its severe dust storms. The epidemic timing starts in February and ends in July, and the dust storm mainly distribute throughout the spring and early summer, which strongly indicate a close linkage between causative agent of TB and dust storm events. However, mechanisms responsible for the observed patterns are still not clearly indentified. By comparing the information on cases of TB from Centers for Disease Control of China annual reports with dust storm atmosphere datasets, we constructed the relationship between the large scale annual occurrence of TB in Xinjiang, a Northwest province of China, and dust storm occurrence. Regional atmospheric indexes of dust storm based on surface wind speed show a clear link between population dynamics of the disease and the climate disaster: the onset of epidemics and the dust storm defined by the atmospheric index share the same mean year. This study is the first that provides a clear demonstration of connections that exist between TB epidemics and dust storm events in China. The development of this study will undoubtedly help early warning for tuberculosis epidemic onset in China and help nationwide and international public health institutions and policy makers to better control TB disease in Norwest China.

Keywords: dust storm, tuberculosis, Xinjiang province, epidemic

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1251 Zoning and Planning Response to Low-Carbon Development Transition in the Chengdu-Chongqing City Clusters, China

Authors: Hanyu Wang, Guangdong Wang

Abstract:

County-level areas serve as vital spatial units for advancing new urbanization and implementing the principles of low-carbon development, representing critical regions where conflicts between the two are pronounced. Using the 142 county-level units in the Chengdu-Chongqing city clusters as a case study, a coupled coordination model is employed to investigate the coupled coordination relationship and its spatiotemporal evolution between county-level new urbanization and low-carbon development levels. Results indicate that (1) from 2005 to 2020, the overall levels of new urbanization and low-carbon development in the Chengdu-Chongqing city clusters showed an upward trend but with significant regional disparities. The new urbanization level exhibited a spatial differentiation pattern of "high in the suburban areas, low in the distant suburbs, and some counties standing out." The temporal change in low-carbon development levels was not pronounced, yet spatial disparities were notable. (2) The overall coupling coordination degree between new urbanization and low-carbon development is transitioning from barely coordinated to moderately coordinated. The lag in new urbanization levels serves as a primary factor constraining the coordinated development of most counties. (3) Based on the temporal evolution of development states, all county units can be categorized into four types: coordinated demonstration areas, synergistic improvement areas, low-carbon transformation areas, and development lag areas. The research findings offer crucial reference points for spatial planning and the formulation of low-carbon development policies.

Keywords: county units, coupling coordination, low-carbon development, new urbanization

Procedia PDF Downloads 49
1250 Climate Change Based Frontier Research in Landscape Architecture

Authors: Xiaoyan Wang, Zhongde Wang

Abstract:

The issue of climate change, which originated in the middle of the twentieth century, has become a focus of international political, academic, and non-governmental organizations and public attention. In order to address the problems caused by climate change, the Chinese government has proposed a dual-carbon target and taken some national measures, such as ecological priority and green low-carbon development. These goals and measures are highly aligned with the values of the landscape architecture industry. This is an opportunity for the architectural discipline and the landscape architecture industry, so it is very necessary to summarize and analyze the hotspots related to climate change in the field of building science in China, which can assist the landscape architecture industry and related organizations in formulating more rational professional goals and taking actions that contribute to the betterment of societal, environmental development. Through the study, it is found as follows: firstly, after 20 years of rapid development, the research on climate change in the major architectural disciplines has shown a trend of diversification of research perspectives, interdisciplinary cross-cutting, and broadening of content; secondly, the research contents of landscape architecture focuses on the strategies to adapt to climate change, such as selection of urban tree species, the urban green infrastructure space layout, and the resilient city. Finally, in the future, climate change-based landscape architecture research will make the content system more diversified, but at the same time, it is still necessary to further deepen the research on quantitative methodology and construct scale systematic planning and design methods.

Keywords: climate change, landscape architecture, knowledge mapping, cites-pace

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1249 Blockchain-Based Approach on Security Enhancement of Distributed System in Healthcare Sector

Authors: Loong Qing Zhe, Foo Jing Heng

Abstract:

A variety of data files are now available on the internet due to the advancement of technology across the globe today. As more and more data are being uploaded on the internet, people are becoming more concerned that their private data, particularly medical health records, are being compromised and sold to others for money. Hence, the accessibility and confidentiality of patients' medical records have to be protected through electronic means. Blockchain technology is introduced to offer patients security against adversaries or unauthorised parties. In the blockchain network, only authorised personnel or organisations that have been validated as nodes may share information and data. For any change within the network, including adding a new block or modifying existing information about the block, a majority of two-thirds of the vote is required to confirm its legitimacy. Additionally, a consortium permission blockchain will connect all the entities within the same community. Consequently, all medical data in the network can be safely shared with all authorised entities. Also, synchronization can be performed within the cloud since the data is real-time. This paper discusses an efficient method for storing and sharing electronic health records (EHRs). It also examines the framework of roles within the blockchain and proposes a new approach to maintain EHRs with keyword indexes to search for patients' medical records while ensuring data privacy.

Keywords: healthcare sectors, distributed system, blockchain, electronic health records (EHR)

Procedia PDF Downloads 164
1248 Research on Morning Commuting Behavior under Autonomous Vehicle Environment Based on Activity Method

Authors: Qing Dai, Zhengkui Lin, Jiajia Zhang, Yi Qu

Abstract:

Based on activity method, this paper focuses on morning commuting behavior when commuters travel with autonomous vehicles (AVs). Firstly, a net utility function of commuters is constructed by the activity utility of commuters at home, in car and at workplace, and the disutility of travel time cost and that of schedule delay cost. Then, this net utility function is applied to build an equilibrium model. Finally, under the assumption of constant marginal activity utility, the properties of equilibrium are analyzed. The results show that, in autonomous driving, the starting and ending time of morning peak and the number of commuters who arrive early and late at workplace are the same as those in manual driving. In automatic driving, however, the departure rate of arriving early at workplace is higher than that of manual driving, while the departure rate of arriving late is just the opposite. In addition, compared with manual driving, the departure time of arriving at workplace on time is earlier and the number of people queuing at the bottleneck is larger in automatic driving. However, the net utility of commuters and the total net utility of system in automatic driving are greater than those in manual driving.

Keywords: autonomous cars, bottleneck model, activity utility, user equilibrium

Procedia PDF Downloads 83
1247 Assessing the Impacts of Frugivorous Birds on Dispersal and Recruitment of Invasive Phytolacca Americana in an Urban Landscape

Authors: Ning Li, Yaner Yan, Yajun Qiao, Shu-qing An

Abstract:

Although seed dispersal is considered to be a key process determining the spatial structure and spread of invasive plant populations, few studies have explicitly addressed the link between dispersal vector behaviour, and seedling recruitment to gain insight into the process of exotic species invasion within a urban landscape. The present study tests the effects of native bird species on the dispersal and recruitment of invasive Phytolacca Americana in an urban garden. We found the invasive population of American pokeweed attracted both generalist species and specialist species to forage and disperse its seeds, with generalists Pycnonotus sinensis and Urocissa erythrorhyncha being by far the most important dispersers. Seedling numbers of P. Americana was strongly affected by perching behavior of bird dispersers. Moreover, two main disperser species, P. sinensis and U. erythrorhyncha govern a high quality dispersal service for P. Americana. Our results highlight the ability of invasive P. americana to recruit seed dispersal agents in urban habitats. However, if the newly recruited species could use the seedling safe site for perching shelter, the invasive plants will get a high regenerate rate in the invasive new habitats thus enhancing their invasive ability.

Keywords: frugivorous birds, phytolacca americana, seed dispersal, urban landscape

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1246 Application of the Electrical Resistivity Tomography and Tunnel Seismic Prediction 303 Methods for Detection Fracture Zones Ahead of Tunnel: A Case Study

Authors: Nima Dastanboo, Xiao-Qing Li, Hamed Gharibdoost

Abstract:

The purpose of this study is to investigate about the geological properties ahead of a tunnel face with using Electrical Resistivity Tomography ERT and Tunnel Seismic Prediction TSP303 methods. In deep tunnels with hydro-geological conditions, it is important to study the geological structures of the region before excavating tunnels. Otherwise, it would lead to unexpected accidents that impose serious damage to the project. For constructing Nosoud tunnel in west of Iran, the ERT and TSP303 methods are employed to predict the geological conditions dynamically during the excavation. In this paper, based on the engineering background of Nosoud tunnel, the important results of applying these methods are discussed. This work demonstrates seismic method and electrical tomography as two geophysical techniques that are able to detect a tunnel. The results of these two methods were being in agreement with each other but the results of TSP303 are more accurate and quality. In this case, the TSP 303 method was a useful tool for predicting unstable geological structures ahead of the tunnel face during excavation. Thus, using another geophysical method together with TSP303 could be helpful as a decision support in excavating, especially in complicated geological conditions.

Keywords: tunnel seismic prediction (TSP303), electrical resistivity tomography (ERT), seismic wave, velocity analysis, low-velocity zones

Procedia PDF Downloads 115
1245 Characterizing Surface Machining-Induced Local Deformation Using Electron Backscatter Diffraction

Authors: Wenqian Zhang, Xuelin Wang, Yujin Hu, Siyang Wang

Abstract:

The subsurface layer of a component plays a significant role in its service performance. Any surface mechanical process during fabrication can introduce a deformed layer near the surface, which can be related to the microstructure alteration and strain hardening, and affects the mechanical properties and corrosion resistance of the material. However, there exists a great difficulty in determining the subsurface deformation induced by surface machining. In this study, electron backscatter diffraction (EBSD) was used to study the deformed layer of surface milled 316 stainless steel. The microstructure change was displayed by the EBSD maps and characterized by misorientation variation. The results revealed that the surface milling resulted in heavily nonuniform deformations in the subsurface layer and even in individual grains. The direction of the predominant grain deformation was about 30-60 deg to the machined surface. Moreover, a local deformation rate (LDR) was proposed to quantitatively evaluate the local deformation degree. Both of the average and maximum LDRs were utilized to characterize the deformation trend along the depth direction. It was revealed that the LDR had a strong correlation with the development of grain and sub-grain boundaries. In this work, a scan step size of 1.2 μm was chosen for the EBSD measurement. A LDR higher than 18 deg/μm indicated a newly developed grain boundary, while a LDR ranged from 2.4 to 18 deg/μm implied the generation of a sub-grain boundary. And a lower LDR than 2.4 deg/μm could only introduce a slighter deformation and no sub-grain boundary was produced. According to the LDR analysis with the evolution of grain or sub grain boundaries, the deformed layer could be classified into four zones: grain broken layer, seriously deformed layer, slightly deformed layer and non-deformed layer.

Keywords: surface machining, EBSD, subsurface layer, local deformation

Procedia PDF Downloads 302
1244 The Asymmetric Proximal Support Vector Machine Based on Multitask Learning for Classification

Authors: Qing Wu, Fei-Yan Li, Heng-Chang Zhang

Abstract:

Multitask learning support vector machines (SVMs) have recently attracted increasing research attention. Given several related tasks, the single-task learning methods trains each task separately and ignore the inner cross-relationship among tasks. However, multitask learning can capture the correlation information among tasks and achieve better performance by training all tasks simultaneously. In addition, the asymmetric squared loss function can better improve the generalization ability of the models on the most asymmetric distributed data. In this paper, we first make two assumptions on the relatedness among tasks and propose two multitask learning proximal support vector machine algorithms, named MTL-a-PSVM and EMTL-a-PSVM, respectively. MTL-a-PSVM seeks a trade-off between the maximum expectile distance for each task model and the closeness of each task model to the general model. As an extension of the MTL-a-PSVM, EMTL-a-PSVM can select appropriate kernel functions for shared information and private information. Besides, two corresponding special cases named MTL-PSVM and EMTLPSVM are proposed by analyzing the asymmetric squared loss function, which can be easily implemented by solving linear systems. Experimental analysis of three classification datasets demonstrates the effectiveness and superiority of our proposed multitask learning algorithms.

Keywords: multitask learning, asymmetric squared loss, EMTL-a-PSVM, classification

Procedia PDF Downloads 84
1243 Nelder-Mead Parametric Optimization of Elastic Metamaterials with Artificial Neural Network Surrogate Model

Authors: Jiaqi Dong, Qing-Hua Qin, Yi Xiao

Abstract:

Some of the most fundamental challenges of elastic metamaterials (EMMs) optimization can be attributed to the high consumption of computational power resulted from finite element analysis (FEA) simulations that render the optimization process inefficient. Furthermore, due to the inherent mesh dependence of FEA, minuscule geometry features, which often emerge during the later stages of optimization, induce very fine elements, resulting in enormously high time consumption, particularly when repetitive solutions are needed for computing the objective function. In this study, a surrogate modelling algorithm is developed to reduce computational time in structural optimization of EMMs. The surrogate model is constructed based on a multilayer feedforward artificial neural network (ANN) architecture, trained with prepopulated eigenfrequency data prepopulated from FEA simulation and optimized through regime selection with genetic algorithm (GA) to improve its accuracy in predicting the location and width of the primary elastic band gap. With the optimized ANN surrogate at the core, a Nelder-Mead (NM) algorithm is established and its performance inspected in comparison to the FEA solution. The ANNNM model shows remarkable accuracy in predicting the band gap width and a reduction of time consumption by 47%.

Keywords: artificial neural network, machine learning, mechanical metamaterials, Nelder-Mead optimization

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1242 Early-Onset Asthma and Early Smoking Increase Risk of Bipolar Disorder in Adolescents and Young Adults

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

Abstract:

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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1241 Characteristic Composition and Sensory Contributions of Acidic Aroma in Mainstream Cigarette Smoke of Cherry-Red Tobacco

Authors: Tian Yangyang, Xu Zihe, Lu Junping, Yang Jizhou, Xu Yiqun, Wang Jiansong, Chen Chao, Yang Mengmeng, Guo Jianhua, Mu Wenjun, Wang Guiyao, Xue Chaoqun, Liang Taibo, Hu Liwei

Abstract:

Cherry-red tobacco is receiving constant attention from cigarette enterprises because of its special flavor. This study aims to explore the material basis for the formation of the characteristic flavor of cherry-red tobacco and to clarify the distribution characteristics of the acidic aroma component groups in its mainstream smoke. In order to reach the aims of current study, this study employs GC/MS to examine the differences of distribution characteristics in particulate matter of mainstream cigarette smoke between cherry-red and common tobacco, meanwhile the aroma activity values (OVA) was used to compare the contribution of acidic aroma of cherry-red tobacco. The results showed that: 1) Isovaleric acid, acetic acid and butyric acid were the key acidic components in the mainstream smoke of the samples, followed by 3-methylvaleric acid, 4-methylvaleric acid and n-valeric acid. 2)Analysis of the release of these key sour fragrance components showed that the acidic aroma of "YUN 85" mainstream smoke was stronger than the leaf group, cherry-red tobacco was the weakest. In addition, aging had the effect of reducing the acidic components of cherry-red tobacco and the addition of cherry-red tobacco had little effect on the acidic components of the original leaf group. 3) For 14 acidic aroma(OAV>1) in smoke of cherry-red tobacco, 3-methylpentanoic acid, 4-methylpentanoic acid, pentanoic acid, and isovaleric acid were very prominent in contributing to acidic aroma, while pyruvic acid, 2-methylbutyric acid, hydrogenated acid, and propionic acid were less contribution.

Keywords: cherry-red tobacco, acidic aroma, GC/MS, mainstream cigarette smoke, odor activity value

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1240 Experiments on Weakly-Supervised Learning on Imperfect Data

Authors: Yan Cheng, Yijun Shao, James Rudolph, Charlene R. Weir, Beth Sahlmann, Qing Zeng-Treitler

Abstract:

Supervised predictive models require labeled data for training purposes. Complete and accurate labeled data, i.e., a ‘gold standard’, is not always available, and imperfectly labeled data may need to serve as an alternative. An important question is if the accuracy of the labeled data creates a performance ceiling for the trained model. In this study, we trained several models to recognize the presence of delirium in clinical documents using data with annotations that are not completely accurate (i.e., weakly-supervised learning). In the external evaluation, the support vector machine model with a linear kernel performed best, achieving an area under the curve of 89.3% and accuracy of 88%, surpassing the 80% accuracy of the training sample. We then generated a set of simulated data and carried out a series of experiments which demonstrated that models trained on imperfect data can (but do not always) outperform the accuracy of the training data, e.g., the area under the curve for some models is higher than 80% when trained on the data with an error rate of 40%. Our experiments also showed that the error resistance of linear modeling is associated with larger sample size, error type, and linearity of the data (all p-values < 0.001). In conclusion, this study sheds light on the usefulness of imperfect data in clinical research via weakly-supervised learning.

Keywords: weakly-supervised learning, support vector machine, prediction, delirium, simulation

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1239 Proton Nuclear Magnetic Resonance Based Metabolomics and 13C Isotopic Ratio Evaluation to Differentiate Conventional and Organic Soy Sauce

Authors: Ghulam Mustafa Kamal, Xiaohua Wang, Bin Yuan, Abdullah Ijaz Hussain, Jie Wang, Shahzad Ali Shahid Chatha, Xu Zhang, Maili Liu

Abstract:

Organic food products are becoming increasingly popular in recent years, as consumers have turned more health conscious and environmentally aware. A lot of consumers have understood that the organic foods are healthier than conventionally produced food stuffs. Price difference between conventional and organic foods is very high. So, it is very common to cheat the consumers by mislabeling and adulteration. Our study describes the 1H NMR based approach to characterize and differentiate soy sauce prepared from organically and conventionally grown raw materials (wheat and soybean). Commercial soy sauce samples fermented from organic and conventional raw materials were purchased from local markets. Principal component analysis showed clear separation among organic and conventional soy sauce samples. Orthogonal partial least squares discriminant analysis showed a significant (p < 0.01) separation among two types of soy sauce yielding leucine, isoleucine, ethanol, glutamate, lactate, acetate, β-glucose, sucrose, choline, valine, phenylalanine and tyrosine as important metabolites contributing towards this separation. Abundance ratio of 13C to 12C was also evaluated by 1H NMR spectroscopy which showed an increased ratio of 13C isotope in organic soy sauce samples indicating the organically grown wheat and soybean used for the preparation of organic soy sauce. Results of the study can be helpful to the end users to select the soy sauce of their choice. This information could also pave the way to further trace and authenticate the raw materials used in production of soy sauce.

Keywords: 1H NMR, multivariate analysis, organic, conventional, 13C isotopic ratio, soy sauce

Procedia PDF Downloads 236
1238 Public Preferences for Lung Cancer Screening in China: A Discrete Choice Experiment

Authors: Zixuan Zhao, Lingbin Du, Le Wang, Youqing Wang, Yi Yang, Jingjun Chen, Hengjin Dong

Abstract:

Objectives: Few results from public attitudes for lung cancer screening are available both in China and abroad. This study aimed to identify preferred lung cancer screening modalities in a Chinese population and predict uptake rates of different modalities. Materials and Methods: A discrete choice experiment questionnaire was administered to 392 Chinese individuals aged 50–74 years who were at high risk for lung cancer. Each choice set had two lung screening options and an option to opt-out, and respondents were asked to choose the most preferred one. Both mixed logit analysis and stepwise logistic analysis were conducted to explore whether preferences were related to respondent characteristics and identify which kinds of respondents were more likely to opt out of any screening. Results: On mixed logit analysis, attributes that were predictive of choice at 1% level of statistical significance included the screening interval, screening venue, and out-of-pocket costs. The preferred screening modality seemed to be screening by low-dose computed tomography (LDCT) + blood test once a year in a general hospital at a cost of RMB 50; this could increase the uptake rate by 0.40 compared to the baseline setting. On stepwise logistic regression, those with no endowment insurance were more likely to opt out; those who were older and housewives/househusbands, and those with a health check habit and with commercial endowment insurance were less likely to opt out from a screening programme. Conclusions: There was considerable variance between real risk and self-perceived risk of lung cancer among respondents, and further research is required in this area. Lung cancer screening uptake can be increased by offering various screening modalities, so as to help policymakers further design the screening modality.

Keywords: lung cancer, screening, China., discrete choice experiment

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1237 Development of Membrane Reactor for Auto Thermal Reforming of Dimethyl Ether for Hydrogen Production

Authors: Tie-Qing Zhang, Seunghun Jung, Young-Bae Kim

Abstract:

This research is devoted to developing a membrane reactor to flexibly meet the hydrogen demand of onboard fuel cells, which is an important part of green energy development. Among many renewable chemical products, dimethyl ether (DME) has the advantages of low reaction temperature (400 °C in this study), high hydrogen atom content, low toxicity, and easy preparation. Autothermal reforming, on the other hand, has a high hydrogen recovery rate and exhibits thermal neutrality during the reaction process, so the additional heat source in the hydrogen production process can be omitted. Therefore, the DME auto thermal reforming process was adopted in this study. To control the temperature of the reaction catalyst bed and hydrogen production rate, a Model Predictive Control (MPC) scheme was designed. Taking the above two variables as the control objectives, stable operation of the reformer can be achieved by controlling the flow rates of DME, steam, and high-purity air in real-time. To prevent catalyst poisoning in the fuel cell, the hydrogen needs to be purified to reduce the carbon monoxide content to below 50 ppm. Therefore, a Pd-Ag hydrogen semi-permeable membrane with a thickness of 3-5 μm was inserted into the auto thermal reactor, and the permeation efficiency of hydrogen was improved by steam purging on the permeation side. Finally, hydrogen with a purity of 99.99 was obtained.

Keywords: hydrogen production, auto thermal reforming, membrane, fuel cell

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1236 Application of Particle Swarm Optimization to Thermal Sensor Placement for Smart Grid

Authors: Hung-Shuo Wu, Huan-Chieh Chiu, Xiang-Yao Zheng, Yu-Cheng Yang, Chien-Hao Wang, Jen-Cheng Wang, Chwan-Lu Tseng, Joe-Air Jiang

Abstract:

Dynamic Thermal Rating (DTR) provides crucial information by estimating the ampacity of transmission lines to improve power dispatching efficiency. To perform the DTR, it is necessary to install on-line thermal sensors to monitor conductor temperature and weather variables. A simple and intuitive strategy is to allocate a thermal sensor to every span of transmission lines, but the cost of sensors might be too high to bear. To deal with the cost issue, a thermal sensor placement problem must be solved. This research proposes and implements a hybrid algorithm which combines proper orthogonal decomposition (POD) with particle swarm optimization (PSO) methods. The proposed hybrid algorithm solves a multi-objective optimization problem that concludes the minimum number of sensors and the minimum error on conductor temperature, and the optimal sensor placement is determined simultaneously. The data of 345 kV transmission lines and the hourly weather data from the Taiwan Power Company and Central Weather Bureau (CWB), respectively, are used by the proposed method. The simulated results indicate that the number of sensors could be reduced using the optimal placement method proposed by the study and an acceptable error on conductor temperature could be achieved. This study provides power companies with a reliable reference for efficiently monitoring and managing their power grids.

Keywords: dynamic thermal rating, proper orthogonal decomposition, particle swarm optimization, sensor placement, smart grid

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1235 Historical Analysis of the Landscape Changes and the Eco-Environment Effects on the Coastal Zone of Bohai Bay, China

Authors: Juan Zhou, Lusan Liu, Yanzhong Zhu, Kuixuan Lin, Wenqian Cai, Yu Wang, Xing Wang

Abstract:

During the past few decades, there has been an increase in the number of coastal land reclamation projects for residential, commercial and industrial purposes in more and more coastal cities of China, which led to the destruction of the wetlands and loss of the sensitive marine habitats. Meanwhile, the influences and nature of these projects attract widespread public and academic concern. For identifying the trend of landscape (esp. Coastal reclamation) and ecological environment changes, understanding of which interacted, and offering a general science for the development of regional plans. In the paper, a case study was carried out in Bohai Bay area, based on the analysis of remote sensing data. Land use maps were created for 1954, 1970, 1981, 1990, 2000 and 2010. Landscape metrics were calculated and illustrated that the degree of reclamation changes was linked to the hydrodynamic environment and macrobenthos community. The results indicated that the worst of the loss of initial areas occurred during 1954-1970, with 65.6% lost mostly to salt field; to 2010, Coastal reclamation area increased more than 200km² as artificial landscape. The numerical simulation of tidal current field in 2003 and 2010 respectively showed that the flow velocity in offshore became faster (from 2-5 cm/s to 10-20 cm/s), and the flow direction seem to go astray. These significant changes of coastline were not conducive to the spread of pollutants and degradation. Additionally, the dominant macrobenthos analysis from 1958 to 2012 showed that Musculus senhousei (Benson, 1842) spread very fast and had been the predominant species in the recent years, which was a disturbance tolerant species.

Keywords: Bohai Bay, coastal reclamation, landscape change, spatial patterns

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1234 Research on the Optimization of the Facility Layout of Efficient Cafeterias for Troops

Authors: Qing Zhang, Jiachen Nie, Yujia Wen, Guanyuan Kou, Peng Yu, Kun Xia, Qin Yang, Li Ding

Abstract:

BACKGROUND: A facility layout problem (FLP) is an NP-complete (non-deterministic polynomial) problem, which is hard to obtain an exact optimal solution. FLP has been widely studied in various limited spaces and workflows. For example, cafeterias with many types of equipment for troops cause chaotic processes when dining. OBJECTIVE: This article tried to optimize the layout of troops’ cafeteria and to improve the overall efficiency of the dining process. METHODS: First, the original cafeteria layout design scheme was analyzed from an ergonomic perspective and two new design schemes were generated. Next, three facility layout models were designed, and further simulation was applied to compare the total time and density of troops between each scheme. Last, an experiment of the dining process with video observation and analysis verified the simulation results. RESULTS: In a simulation, the dining time under the second new layout is shortened by 2.25% and 1.89% (p<0.0001, p=0.0001) compared with the other two layouts, while troops-flow density and interference both greatly reduced in the two new layouts. In the experiment, process completing time and the number of interference reduced as well, which verified corresponding simulation results. CONCLUSIONS: Our two new layout schemes are tested to be optimal by a series of simulation and space experiments. In future research, similar approaches could be applied when taking layout-design algorithm calculation into consideration.

Keywords: layout optimization, dining efficiency, troops’ cafeteria, anylogic simulation, field experiment

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1233 In Ovo Injection of N-Carbamylglutamate Improves Growth Performance, Muscle Fiber Development, and Meat Quality in Broiler Chickens

Authors: Wang Yuan-hao, Habtamu Ayalew, Jing Wang, Shugeng Wu, Kai Qiu, Guanghai Qi, Haijun Zhang

Abstract:

N-carbamylglutamate (NCG) has emerged as a promising candidate for regulating endogenous arginine synthesis, thereby promoting desirable growth, carcass traits, and muscle development in broilers. Thus, this study aimed to investigate the effects of NCG in ovo feeding on the growth performance, growth hormones, and meat quality of Ross 308 breeder broilers. A total of 1680 embryo eggs were equally allocated into three treatment groups: non punctured control (NC), saline-injected control (SC; 100μL/egg), and N-carbamylglutamate injected group (NCG; 2 mg/egg). The treatment solution was injected into the amniotic cavity of the embryo at 17.5 days of incubation (DOI). For the subsequent 42 days of post hatch experimental sampling, a total of 360 broiler chicks with 6 replications per treatment and 15 chicks per replication were used. Chickens in the NCG group showed significantly higher (P<0.05) body weight gain (BWG) and final body weight (FBW) at both 21 and 42 days after hatch (DAH), while feed conversion efficiency (FCE) was significantly improved (P<0.05) at 42 DAH. The weight and percentage of drums at 21 DAH and the weight and percentage of breast muscle at 42 DAH were significantly higher (P<0.05) in the NCG group. In addition, insulin (INS), growth hormone (GH), and testosterone (T) levels were significantly higher (P<0.05) in the NCG groups at 21 and 42 DAH. Furthermore, triiodothyronine (T3) and tetraiodothyronine (T4) levels were significantly higher (P<0.05) in the NCG treatment group. Interestingly, meat color values were also significantly higher (P<0.05) in the NCG group at 24 hrs postmortem. Collectively, these findings show that 2 mg NCG in ovo injection improves the growth performance and meat quality of broilers; even the effects extend into the market age of the chickens.

Keywords: N-carbamylglutamate, broiler, in ovo injection, growth performance, meat quality

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1232 The Complex Relationship Between IQ and Attention Deficit Hyperactivity Disorder Symptoms: Insights From Behaviors, Cognition, and Brain in 5,138 Children With Attention Deficit Hyperactivity Disorder

Authors: Ningning Liu, Gaoding Jia, Yinshan Wang, Haimei Li, Xinian Zuo, Yufeng Wang, Lu Liu, Qiujin Qian

Abstract:

Background: There has been speculation that a high IQ may not necessarily provide protection against attention deficit hyperactivity disorder (ADHD), and there may be a U-shaped correlation between IQ and ADHD symptoms. However, this speculation has not been validated in the ADHD population in any study so far. Method: We conducted a study with 5,138 children who have been professionally diagnosed with ADHD and have a wide range of IQ levels. General Linear Models were used to determine the optimal model between IQ and ADHD core symptoms with sex and age as covariates. The ADHD symptoms we looked at included the total scores (TO), inattention (IA) and hyperactivity/impulsivity (HI). Wechsler Intelligence scale were used to assess IQ [Full-Scale IQ (FSIQ), Verbal IQ (VIQ), and Performance IQ (PIQ)]. Furthermore, we examined the correlation between IQ and the execution function [Behavior Rating Inventory of Executive Function (BRIEF)], as well as between IQ and brain surface area, to determine if the associations between IQ and ADHD symptoms are reflected in executive functions and brain structure. Results: Consistent with previous research, the results indicated that FSIQ and VIQ both showed a linear negative correlation with the TO and IA scores of ADHD. However, PIQ showed an inverted U-shaped relationship with the TO and HI scores of ADHD, with 103 as the peak point. These findings were also partially reflected in the relationship between IQ and executive functions, as well as IQ and brain surface area. Conclusion: To sum up, the relationship between IQ and ADHD symptoms is not straightforward. Our study confirms long-standing academic hypotheses and finds that PIQ exhibits an inverted U-shaped relationship with ADHD symptoms. This study enhances our understanding of symptoms and behaviors of ADHD with varying IQ characteristics and provides some evidence for targeted clinical intervention.

Keywords: ADHD, IQ, execution function, brain imaging

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1231 LaMn₁₋ₓNiₓO₃ Perovskites as Oxygen Carriers for Chemical Looping Partial Oxidation of Methane

Authors: Xianglei Yin, Shen Wang, Baoyi Wang, Laihong Shen

Abstract:

Chemical looping partial oxidation of methane (CLPOM) is a novel technology to produce high-quality syngas with an auto-thermic process and low equipment investment. The development of oxygen carriers is important for the improvement of the CLPOM performance. In this work, the effect of the nickel-substitution proportion on the performance of LaMn₁₋ᵧNiᵧO₃₊δ perovskites for CLPOM was studied in the aspect of reactivity, syngas selectivity, resistance towards carbon deposition and thermal stability in cyclic redox process. The LaMn₁₋ₓNiₓO₃ perovskite oxides with x = 0, 0.1, 0.2 were prepared by the sol-gel method. The performance of LaMn₁₋ᵧNiᵧO₃₊δ perovskites for CLPOM was investigated through the characterization of XRD, H₂-TPR, XPS, and fixed-bed experiments. The characterization and test results suggest that the doping of nickel enhances the generation rate of syngas, leading to high syngas yield, methane conversion, and syngas selectivity. This is attributed to the that the introduction of nickel provides active sites to promote the methane activation on the surface and causes the addition of oxygen vacancies to accelerate the migration of oxygen anion in the bulk of oxygen carrier particles. On the other hand, the introduction of nickel causes carbon deposition to occur earlier. The best substitution proportion of nickel is y=0.1 and LaMn₀.₉Ni₀.₁O₃₊δ could produce high-quality syngas with a yield of 3.54 mmol·g⁻¹, methane conversion of 80.7%, and CO selectivity of 84.8% at 850℃. In addition, the LaMn₀.₉Ni₀.₁O₃₊δ oxygen carrier exhibits superior and stable performance in the cyclic redox process.

Keywords: chemical looping partial oxidation of methane, LaMnO₃₊δ, Ni doping, syngas, carbon deposition

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1230 Study on the Mechanism of CO₂-Viscoelastic Fluid Synergistic Oil Displacement in Tight Sandstone Reservoirs

Authors: Long Long Chen, Xinwei Liao, Shanfa Tang, Shaojing Jiang, Ruijia Tang, Rui Wang, Shu Yun Feng, Si Yao Wang

Abstract:

Tight oil reservoirs have poor physical properties, insufficient formation energy, and low natural productivity; it is necessary to effectively improve their crude oil recovery. CO₂ flooding is an important technical means to enhance oil recovery and achieve effective CO₂ storage in tight oil reservoirs, but its heterogeneity is strong, which makes CO₂ flooding prone to gas channeling and poor recovery. Aiming at the problem of gas injection channeling, combined with the excellent performance of low interfacial tension viscoelastic fluid (GOBTK), the research on CO₂-low interfacial tension viscoelastic fluid synergistic oil displacement in tight reservoirs was carried out, and the synergy of CO₂ and low interfacial tension viscoelastic fluid was discussed. Oil displacement mechanism. Experiments show that GOBTK has good injectability in tight oil reservoirs (Kg=0.141~0.793mD); CO₂-0.4% GOBTK synergistic flooding can improve the recovery factor of low permeability layers (31.41%) under heterogeneous (gradient difference of 10) conditions the) effect is better than that of CO₂ flooding (0.56%) and 0.4% GOBT-water flooding (20.99%); CO₂-GOBT synergistic oil displacement mechanism includes: 1) The formation of CO₂ foam increases the flow resistance of viscoelastic fluid, forcing the displacement fluid to flow 2) GOBTK can emulsify and disperse residual oil into small oil droplets, and smoothly pass through narrow pores to produce; 3) CO₂ dissolved in GOBTK synergistically enhances the water wettability of the core, and the use of viscosity Elastomeric fluid injection and stripping of residual oil; 4) CO₂-GOBTK synergy superimposes multiple mechanisms, effectively improving the swept volume and oil washing efficiency of the injected fluid to the reservoir.

Keywords: tight oil reservoir, CO₂ flooding, low interfacial tension viscoelastic fluid flooding, synergistic oil displacement, EOR mechanism

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1229 Alternative General Formula to Estimate and Test Influences of Early Diagnosis on Cancer Survival

Authors: Li Yin, Xiaoqin Wang

Abstract:

Background and purpose: Cancer diagnosis is part of a complex stochastic process, in which patients' personal and social characteristics influence the choice of diagnosing methods, diagnosing methods, in turn, influence the initial assessment of cancer stage, the initial assessment, in turn, influences the choice of treating methods, and treating methods in turn influence cancer outcomes such as cancer survival. To evaluate diagnosing methods, one needs to estimate and test the causal effect of a regime of cancer diagnosis and treatments. Recently, Wang and Yin (Annals of statistics, 2020) derived a new general formula, which expresses these causal effects in terms of the point effects of treatments in single-point causal inference. As a result, it is possible to estimate and test these causal effects via point effects. The purpose of the work is to estimate and test causal effects under various regimes of cancer diagnosis and treatments via point effects. Challenges and solutions: The cancer stage has influences from earlier diagnosis as well as on subsequent treatments. As a consequence, it is highly difficult to estimate and test the causal effects via standard parameters, that is, the conditional survival given all stationary covariates, diagnosing methods, cancer stage and prognosis factors, treating methods. Instead of standard parameters, we use the point effects of cancer diagnosis and treatments to estimate and test causal effects under various regimes of cancer diagnosis and treatments. We are able to use familiar methods in the framework of single-point causal inference to accomplish the task. Achievements: we have applied this method to stomach cancer survival from a clinical study in Sweden. We have studied causal effects under various regimes, including the optimal regime of diagnosis and treatments and the effect moderation of the causal effect by age and gender.

Keywords: cancer diagnosis, causal effect, point effect, G-formula, sequential causal effect

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1228 Qusai-Solid-State Electrochromic Device Based on PolyMethyl Methacrylate (PMMA)/Succinonitrile Gel Polymer Electrolyte

Authors: Jen-Yuan Wang, Min-Chuan Wang, Der-Jun Jan

Abstract:

Polymer electrolytes can be classified into four major categories, solid polymer electrolytes (SPEs), gel polymer electrolytes (GPEs), polyelectrolytes and composite polymer electrolytes. SPEs suffer from low ionic conductivity at room temperature. The main problems for GPEs are the poor thermal stability and mechanical properties. In this study, a GPE containing PMMA and succinonitrile is prepared to solve the problems mentioned above, and applied to the assembly of a quasi-solid-state electrochromic device (ECD). In the polymer electrolyte, poly(methyl methacrylate) (PMMA) is the polymer matrix and propylene carbonate (PC) is used as the plasticizer. To enhance the mechanical properties of this GPE, succinonitrile (SN) is introduced as the additive. For the electrochromic materials, tungsten oxide (WO3) is used as the cathodic coloring film, which is fabricated by pulsed dc magnetron reactive sputtering. For the anodic coloring material, Prussian blue nanoparticles (PBNPs) are synthesized and coated on the transparent Sn-doped indium oxide (ITO) glass. The thickness of ITO, WO3 and PB film is 110, 170 and 200 nm, respectively. The size of the ECD is 5×5 cm2. The effect of the introduction of SN into the GPEs is discussed by observing the electrochromic behaviors of the WO3-PB ECD. Besides, the composition ratio of PC to SN is also investigated by measuring the ionic conductivity. The optimized ratio of PC to SN is 4:1, and the ionic conductivity under this condition is 6.34x10-5 S∙cm-1, which is higher than that of PMMA/PC (1.35x10-6 S∙cm-1) and PMMA/EC/PC (4.52x10-6 S∙cm-1). This quasi-solid-state ECD fabricated with the PMMA/SN based GPE shows an optical contrast of ca. 53% at 690 nm. The optical transmittance of the ECD can be reversibly modulated from 72% (bleached) to 19% (darkened), by applying potentials of 1.5 and -2.2 V, respectively. During the durability test, the optical contrast of this ECD remains 44.5% after 2400 cycles, which is 83% of the original one.

Keywords: electrochromism, tungsten oxide, prussian blue, poly(methyl methacrylate), succinonitrile

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1227 Solving LWE by Pregressive Pumps and Its Optimization

Authors: Leizhang Wang, Baocang Wang

Abstract:

General Sieve Kernel (G6K) is considered as currently the fastest algorithm for the shortest vector problem (SVP) and record holder of open SVP challenge. We study the lattice basis quality improvement effects of the Workout proposed in G6K, which is composed of a series of pumps to solve SVP. Firstly, we use a low-dimensional pump output basis to propose a predictor to predict the quality of high-dimensional Pumps output basis. Both theoretical analysis and experimental tests are performed to illustrate that it is more computationally expensive to solve the LWE problems by using a G6K default SVP solving strategy (Workout) than these lattice reduction algorithms (e.g. BKZ 2.0, Progressive BKZ, Pump, and Jump BKZ) with sieving as their SVP oracle. Secondly, the default Workout in G6K is optimized to achieve a stronger reduction and lower computational cost. Thirdly, we combine the optimized Workout and the Pump output basis quality predictor to further reduce the computational cost by optimizing LWE instances selection strategy. In fact, we can solve the TU LWE challenge (n = 65, q = 4225, = 0:005) 13.6 times faster than the G6K default Workout. Fourthly, we consider a combined two-stage (Preprocessing by BKZ- and a big Pump) LWE solving strategy. Both stages use dimension for free technology to give new theoretical security estimations of several LWE-based cryptographic schemes. The security estimations show that the securities of these schemes with the conservative Newhope’s core-SVP model are somewhat overestimated. In addition, in the case of LAC scheme, LWE instances selection strategy can be optimized to further improve the LWE-solving efficiency even by 15% and 57%. Finally, some experiments are implemented to examine the effects of our strategies on the Normal Form LWE problems, and the results demonstrate that the combined strategy is four times faster than that of Newhope.

Keywords: LWE, G6K, pump estimator, LWE instances selection strategy, dimension for free

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