Search results for: Dong Zhang

Authors: Xiaoqi Jia, Qing Zhu, Hao Zhang, Su Yang

Abstract:

A gender recognition system is able to tell the gender of the given person through a few of frontal facial images. An effective gender recognition approach enables to improve the performance of many other applications, including security monitoring, human-computer interaction, image or video retrieval and so on. In this paper, we present an effective method for gender classification task in frontal facial images based on deep belief networks (DBNs), which can pre-train model and improve accuracy a little bit. Our experiments have shown that the pre-training method with DBNs for gender classification task is feasible and achieves a little improvement of accuracy on FERET and CAS-PEAL-R1 facial datasets.

Keywords: gender recognition, beep belief net-works, semi-supervised learning, greedy-layer wise RBMs

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Authors: Lin Zhang

Abstract:

Neighborhood redevelopment is vital to improve residents’ living environment, and there has been a national neighborhood micro-redevelopment initiative in China since 2020, which is largely different from the previous large-scale demolition and reconstruction projects. Yet, few studies systematically examine the new interactions of multiple actors in this initiative. China’s neighborhood (micro-) redevelopment is a kind of governance network, and the complexity perspective could reflect the dynamic nature of multiple actors and their relationships in governance networks. In order to better understand the fundamental shifts of governance networks in China’s neighborhood micro-redevelopment, this paper adopted a theoretical framework of complexity in governance networks and analyzed the new governance networks of neighborhood micro-redevelopment projects in Haikou accordingly.

Keywords: neighborhood redevelopment, governance, networks, Haikou

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Authors: Caixia Kang, Takahiro Kuba, Aimin Hao, Yasushi Iseri, Chunjie Li, Zhenjia Zhang

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To improve the water quality of lakes and control algae blooms, The effects of Vallisneria asiatica which is one of aquatic plants spread over Lake Taihu. With different biomasses on the water quality and algae communities were researched. The results indicated that V. asiatica could control an excess of Microcystis spp. When the V. asiatica biomass was larger than 50g in the tank with 30L solution in the laboratory, Planktonic and epiphytic algae responded differently to V. asiatica. The presence of macrophyte V. asiatica in eutrophic waters has a positive effect on algae compositions because of different sensitivities of algae species to allelopathic substances released by macrophyte V. asiatica. That is, V. asiatica could inhibit the growth of Microcystis spp. effectively and was benefited to the diatom on the condition in the laboratory.

Keywords: algae bloom, algae community, Microcystis spp., Vallisneria asiatica

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Authors: Yuxuan Liu, Jianli Hao, Ruoyu Zhang, Lin Lin, Nelsen Andreco Muljadi, Yu Song, Guobin Gong

Abstract:

With the increased municipal waste of China, household waste management (HWM) has become a key issue for sustainable development. In this study, an online survey questionnaire was conducted with the aim of assessing the current attitudes and behaviors of the households in China towards waste separationand recycling practices. Related influential factors are also determined within the context of the theory of planned behavior and PEST analysis. The survey received a total of 551 valid respondents. Results showed that the sample has an overall positive attitudes and behavior toward participating in HWM, but only 16.3% of themregularly segregate their waste. Society and policy are also found to be the two most impactful factors.

Keywords: householde waste management, theory of planned behavior, attitude, behavior

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Authors: Huai-Feng Wang, Meng-Lin Lou, Ru-Lin Zhang

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One good analysis method in seismic response analysis is direct time integration, which widely adopts Rayleigh damping. An approach is presented for selection of Rayleigh damping coefficients to be used in seismic analyses to produce a response that is consistent with Modal damping response. In the presented approach, the expression of the error of peak response, acquired through complete quadratic combination method, and Rayleigh damping coefficients was set up and then the coefficients were produced by minimizing the error. Two finite element modes of soil layers, excited by 28 seismic waves, were used to demonstrate the feasibility and validity.

Keywords: Rayleigh damping, modal damping, damping coefficients, seismic response analysis

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Authors: Xupin Zhang, Maria Caterina Bramati, Enrest Fokoue

Abstract:

Understanding the career placement of graduates from the university is crucial for both the qualities of education and ultimate satisfaction of students. In this research, we adapt the capabilities of dynamic Bayesian networks to characterize and predict students’ job placement using data from various universities. We also provide elements of the estimation of the indicator (score) of the strength of the network. The research focuses on overall findings as well as specific student groups including international and STEM students and their insight on the career path and what changes need to be made. The derived Bayesian network has the potential to be used as a tool for simulating the career path for students and ultimately helps universities in both academic advising and career counseling.

Keywords: dynamic bayesian networks, indicator estimation, job placement, social networks

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Authors: Ruichong Zhang

Abstract:

This study proposes a recording-based approach to characterize and quantify earthquake-induced site nonlinearity, exemplified as soil nonlinearity and/or liquefaction. Alternative to Fourier spectral analysis (FSA), the paper introduces time-frequency analysis of earthquake ground motion recordings with the aid of so-called Hilbert-Huang transform (HHT), and offers justification for the HHT in addressing the nonlinear features shown in the recordings. With the use of the 2001 Nisqually earthquake recordings, this study shows that the proposed approach is effective in characterizing site nonlinearity and quantifying the influences in seismic ground responses.

Keywords: site nonlinearity, site amplification, site damping, Hilbert-Huang Transform (HHT), liquefaction, 2001 Nisqually Earthquake

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Authors: E. Ghasemi Ardi, K. J. Dong, A. B. Yu, R. Y. Yang

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In current work, a numerical model based on the discrete element method (DEM) was developed which provided information about particle dynamic and impact event condition inside a laboratory scale impact mill (Fritsch). It showed that each particle mostly experiences three impacts inside the mill. While the first impact frequently happens at front surface of the rotor’s rib, the frequent location of the second impact is side surfaces of the rotor’s rib. It was also showed that while the first impact happens at small impact angle mostly varying around 35º, the second impact happens at around 70º which is close to normal impact condition. Also analyzing impact energy revealed that varying mill speed from 6000 to 14000 rpm, the ratio of first impact’s average impact energy and minimum required energy to break particle (Wₘᵢₙ) increased from 0.30 to 0.85. Moreover, it was seen that second impact poses intense impact energy on particle which can be considered as the main cause of particle splitting. Finally, obtained information from DEM simulation along with obtained data from conducted experiments was implemented in semi-empirical equations in order to find selection and breakage functions. Then, using a back-calculation approach, those parameters were used to predict the PSDs of ground particles under different impact energies. Results were compared with experiment results and showed reasonable accuracy and prediction ability.

Keywords: single particle breakage, particle dynamic, population balance model, particle size distribution, discrete element method

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Authors: Dong-Hyun Kim, Wan-Ho Chung, Hak-Sung Kim

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In this work, non-destructive evaluation was conducted to measure the sheet resistance of silver nanowire coated film and find a damage of that film using terahertz (THz) wave. Pulse type THz instrument was used, and the measurement was performed under transmission and pitch-catch reflection modes with 30 degree of incidence angle. In the transmission mode, the intensity of the THz wave was gradually increased as the conductivity decreased. Meanwhile, the intensity of THz wave was decreased as the conductivity decreased in the pitch-catch reflection mode. To confirm the conductivity of the film, sheet resistance was measured by 4-point probe station. Interaction formula was drawn from a relation between the intensity and the sheet resistance. Through substituting sheet resistance to the formula and comparing the resultant value with measured maximum THz wave intensity, measurement of sheet resistance using THz wave was more suitable than that using 4-point probe station. In addition, the damage on the silver nanowire coated film was detected by applying the THz image system. Therefore, the reliability of the entire film can be also be ensured. In conclusion, real-time monitoring using the THz wave can be applied in the transparent electrodes with detecting the damaged area as well as measuring the sheet resistance.

Keywords: terahertz wave, sheet resistance, non-destructive evaluation, silver nanowire

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Authors: Yuan Zhang

Abstract:

Along with large population and great demands for urban development, Hong Kong serves as a typical high-density city with multiple altitudes, advanced three-dimensional traffic system, rich city open space, etc. This paper contributes to analyzing its complex urban form and evolution mechanism from three aspects of view, separately as time, space and buildings. Taking both horizontal and vertical dimension into consideration, this paper provides a perspective to explore the fascinating process of growing and space folding in the urban form of high-density city, also as a research reference for related high-density urban design.

Keywords: evolution mechanism, high-density city, Hong Kong, urban form

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Authors: Hieu Van Dong, Giang Thi Huong Tran, Giap Van Nguyen, Tung Duy Dao, Vuong Nghia Bui, Le Thi My Huynh, Yohei Takeda, Haruko Ogawa, Kunitoshi Imai

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Chicken anemia virus (CAV) has a ubiquitous and worldwide distribution in chicken production. Our group previously reported high seroprevalence of CAV in chickens in northern Vietnam. In the present study, 330 tissue samples collected from commercial and breeder chicken farms in eleven provinces in northern Vietnam were tested for the CAV infection. We found that 157 out of 330 (47.58%) chickens were positive with CAV genes by real-time PCR method. Nine CAV strains obtained from the different location and time were forwarded to the full-length sequence of CAV VP1 gene. Phylogenetic analysis of the Vietnamese CAV vp1 gene indicated that the CAVs circulating in northern Vietnam were divided into three distinct genotypes, II, III, and V, but not clustered with the vaccine strains. Among the three genotypes, genotype III was the major one widely spread in Vietnam, and that included three sub-genotypes, IIIa, IIIb, and IIIc. The Vietnamese CAV strains were closely related to the Chinese, Taiwanese, and USA strains. All the CAV isolates had glutamine at amino acid position 394 in the VP1 gene, suggesting that they might be highly pathogenic strains. One strain was defined to be genotype V, which had not been reported for Vietnamese CAVs. Additional studies are required to further evaluate the pathogenicity of CAV strains circulating in Vietnam.

Keywords: chicken anemia virus, genotype, genetic characteristics, Vietnam

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Authors: Ki Ok Choi, Sung Ho Hong, Dong Suck Kim, Don Mook Choi

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Rack type warehouses are different from general buildings in the kinds, amount, and arrangement of stored goods, so the fire risk of rack type warehouses is different from those buildings. The fire pattern of rack type warehouses is different in combustion characteristic and storing condition of stored goods. The initial fire burning rate is different in the surface condition of materials, but the running time of fire is closely related with the kinds of stored materials and stored conditions. The stored goods of the warehouse are consisted of diverse combustibles, combustible liquid, and so on. Fire detection time may be delayed because the residents are less than office and commercial buildings. If fire detectors installed in rack type warehouses are inadaptable, the fire of the warehouse may be the great fire because of delaying of fire detection. In this paper, we studied what kinds of fire detectors are optimized in early detecting of rack type warehouse fire by real-scale fire tests. The fire detectors used in the tests are rate of rise type, fixed type, photo electric type, and aspirating type detectors. We considered optimum fire detecting method in rack type warehouses suggested by the response characteristic and comparative analysis of the fire detectors.

Keywords: fire detector, rack, response characteristic, warehouse

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Authors: Dong Jin Kang

Abstract:

Application of single board microcontrollers is an important skill even for non-electronic engineering major students. Arduino board is widely utilized in engineering classes of the Yeungnam University of South Korea. In those classes, students are subjected to learn how to use various sensor components related to motion, sound, light, and so on as well as physical quantities. Students are grouped into several teams, and each team consists of 4~5 students. Many students are not motivated enough to learn those skills. An extracurricular program was planned to improve this problem. The extracurricular program was held as an international boot camp where students from three different countries were invited to participate. 10 students groups were formed, and each team was consisted of students having different nationality. The camp was 4 days long and wrapped up with competitions. During the camp, every student was assigned to design and make a two wheel robot. The competition was carried out in two different areas; individual and group performances. As most skills dealt in the class are used to build the robot, students are much motivated to review the whole subjects of the class. All students were surveyed after the program. The survey shows that the skills studied in the class are greatly improved, and practically understood. Staying at the dormitory and teaming with international students are help students improve communication skills. Competition at the camp was found as a key element to inspire and attract students for voluntary participation.

Keywords: extracurricular program, robot, Arduino board, international camp, competition

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Authors: Seon Ho Kim, Minho Bang, Seok Min Choi, Young Moon Lee, Dong Kwan Kim, Hyung Hee Cho

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Gas turbines are heat engines that convert chemical energy into electrical energy through mechanical energy. Since their high energy density per unit volume and low pollutant emissions, gas turbines are classified as clean energy. In order to obtain better performance, the turbine inlet temperature of the current gas turbine is operated at about 1600℃, and thermal damage is a very serious problem. Especially, these thermal damages are more prominent in off-design conditions than in design conditions. In this study, the thermal damage characteristics of high temperature components of a gas turbine made of a single crystal material are studied numerically for the off-design operating conditions. The target gas turbine is configured as a reheat cycle and is operated in peak load operation mode, not normal operation. In particular, the target gas turbine features a lot of low-load operation. In this study, a commercial code, ANSYS 18.2, was used for analyzing the thermal-flow coupling problems. As a result, the flow separation phenomenon on the pressure side due to the flow reduction was remarkable at the off-design condition, and the high heat transfer coefficient at the upper end of the suction surface due to the tip leakage flow was appeared.

Keywords: gas turbine, single crystal blade, off-design, thermal analysis

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Authors: Ahmad FAROOQ, Xinfeng Zhang, Fahad Sabah, Raheem Sarwar

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In Traditional Chinese Medicine, tongue diagnosis is a vital inspection tool (TCM). In this study, we explore the potential of machine learning in tongue diagnosis. It begins with the cataloguing of the various classifications and characteristics of the human tongue. We infer 24 kinds of tongues from the material and coating of the tongue, and we identify 21 attributes of the tongue. The next step is to apply machine learning methods to the tongue dataset. We use the Weka machine learning platform to conduct the experiment for performance analysis. The 457 instances of the tongue dataset are used to test the performance of five different machine learning methods, including SVM, Random Forests, Decision Trees, and Naive Bayes. Based on accuracy and Area under the ROC Curve, the Support Vector Machine algorithm was shown to be the most effective for tongue diagnosis (AUC).

Keywords: medical imaging, image retrieval, machine learning, tongue

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Authors: Zhang Yu, Ding Yi

Abstract:

The discussion about elements of cultural heritage and their relevance among the ancient villages is comparably insufficient. The protection work is strongly influenced by touristic development and cultural gimmick, resulting in low protection efficiency and many omissions. Historical villages as the cultural settlement patterns bear a large number of heritage relics. They were regionally scattered with a clear characteristic of gathering. First of all, this study proposes the association and similarities of the forming mechanism between four historic cultural villages in Mian Mountain. Secondly, the study reveals that these villages own the strategic pass, underground passage, and the mountain barrier. Thirdly, based on the differentiated characteristics of villages’ space, the study discusses about the integrated conservation from three levels: the regional heritage conservation, the cultural line shaping, and the featured brand building.

Keywords: conservation, fortress, historical villages, Mian Moutain

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

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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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Authors: J. Zhang, K. Agyapong-Kodua

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Digital factory based on visual design and simulation has emerged as a mainstream to reduce digital development life cycle. Some basic industrial systems are being integrated via semantic modelling, and products (P) matching process (P)-resource (R) requirements are designed to fulfill current customer demands. Nevertheless, product design is still limited to fixed product models and known knowledge of product engineers. Therefore, this paper presents a rapid reconfiguration method based on semantic technologies with PPR ontologies to reuse known and unknown knowledge. In order to avoid the influence of big data, our system uses a cloud manufactory and distributed database to improve the efficiency of querying meeting PPR requirements.

Keywords: semantic technologies, factory system, digital factory, cloud manufactory

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Authors: Quoc Hung Le Pham

Abstract:

In the field of language study, classifier is an interesting research feature. In the world’s languages, some languages have classifier system, some do not. Mandarin Chinese and Vietnamese languages are a rich classifier system, however, because of the language system, the cognitive, cultural differences, so that the syntactic structure of classifier of them also dissimilar. When using Mandarin Chinese classifiers must collocate with nouns or verbs, in the lexical category it is not like nouns or verbs, belong to the open class. But some scholars believe that Mandarin Chinese measure words are similar to English and other Indo European languages. The word hanging on the structure and word formation (suffix), is a closed class. Compared to other languages, such as Chinese, Vietnamese, Thai and other Asian languages are still belonging to the classifier language’s second type, this type of language is classifier, it is in the majority of quantity must exist, and following deictic, anaphoric or quantity appearing together, not separation between its modified noun, also known as numeral classifier language. Main syntactic structure of Chinese classifiers are as follows: ‘quantity+measure+noun’, ‘pronoun+measure+noun’, ‘pronoun+quantity+measure+noun’, ‘prefix+quantity+measure +noun’, ‘quantity +adjective + measure +noun’, ‘ quantity (above 10 whole number), + duo (多)measure +noun’, ‘ quantity (around 10) + measure + duo (多) +noun’. Main syntactic structure of Vietnamese classifiers are: ‘quantity+measure+noun’, ‘ measure+noun+pronoun’, ‘quantity+measure+noun+pronoun’, ‘measure+noun+prefix+ quantity’, ‘quantity+measure+noun+adjective', ‘duo (多) +quanlity+measure+noun’, ‘quantity+measure+adjective+pronoun (quantity word could not be 1)’, ‘measure+adjective+pronoun’, ‘measure+pronoun’. In daily life, classifiers are commonly used, if Chinese learners failed to standardize this using catergory, because the negative impact might occur on their verbal communication. The richness of the Chinese classifier system contributes to the complexity in the study of the system by foreign learners, especially in the inter language of Vietnamese learners. As above mentioned, Vietnamese language also has a rich system of classifiers, however, the basic structure order of two languages are similar but both still have differences. These similarities and dissimilarities between Chinese and Vietnamese classifier systems contribute significantly to the common errors made by Vietnamese students while they acquire Chinese, which are distinct from the errors made by students from the other language background. This article from a comparative perspective of language, has an orientation towards Chinese and Vietnamese languages commonly used in classifiers semantics and structural form two aspects. This comparative study aims to identity Vietnamese students while learning Chinese classifiers may face some negative transference of mother language, beside that through the analysis of the classifiers questionnaire, find out the causes and patterns of the errors they made. As the preliminary analysis shows, Vietnamese students while learning Chinese classifiers made some errors such as: overuse classifier ‘ge’(个); misuse the other classifiers ‘*yi zhang ri ji’(yi pian ri ji), ‘*yi zuo fang zi’(yi jian fang zi), ‘*si zhang jin pai’(si mei jin pai); homonym words ‘dui, shuang, fu, tao’ (对、双、副、套), ‘ke, li’ (颗、粒).

Keywords: acquisition, classifiers, negative transfer, Vietnamse learners

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Authors: Giang Tran Thi Huong, Hieu Dong Van, Tung Dao Duy, Saadanov Iskender, Isakeev Mairambek, Tsutomu Omatsu, Yukie Katayama, Tetsuya Mizutani, Yuki Ozeki, Yohei Takeda, Haruko Ogawa, Kunitoshi Imai

Abstract:

Newcastle disease virus (NDV) is a contagious viral disease of the poultry industry and other birds throughout the world. At present, very little is known about molecular epidemiological data regarding the causes of ND outbreak in commercial poultry farms in Kyrgyzstan. In the current study, the NDV isolated from the one out of three samples from the unvaccinated flock was confirmed as NDV. Phylogenetic analysis indicated that this NDV strain is clustered in the Class II subgenotype VIId, and closely related to the Chinese NDV isolate. Phylogenetic analyses revealed that the isolated NDV strain has an origin different from the 4 NDV strains previously identified in Kyrgyzstan. According to the mean death time (MDT: 61.1 h) and a multibasic amino acid (aa) sequence at the F0 proteolytic cleavage site (¹¹²R-R-Q-K-R-F¹¹⁷), the NDV isolate was determined as mesogenic strain. Several mutations in the neutralizing epitopes (notably, ³⁴⁷E→K) and the global head were observed in the hemagglutinin-neuraminidase (HN) protein of the current isolate. The present study represents the molecular characterization of the coding gene region of NDV in Kyrgyzstan. Additionally, further study will be investigated on the antigenic characterization using monoclonal antibody.

Keywords: Kyrgyzstan, Newcastle disease, genotype, genome characterization

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Authors: Fei Gao, Xinyang Dong, Yisu Ge, Shufang Lu, Libo Weng

Abstract:

Vehicle color recognition plays an important role in traffic accident investigation. However, due to the influence of illumination, weather, and noise, vehicle color recognition still faces challenges. In this paper, a vehicle color classification network based on spatial cluster loss and channel attention mechanism (SCNet) is proposed for vehicle color recognition. A channel attention module is applied to extract the features of vehicle color representative regions and reduce the weight of nonrepresentative color regions in the channel. The proposed loss function, called spatial clustering loss (SC-loss), consists of two channel-specific components, such as a concentration component and a diversity component. The concentration component forces all feature channels belonging to the same class to be concentrated through the channel cluster. The diversity components impose additional constraints on the channels through the mean distance coefficient, making them mutually exclusive in spatial dimensions. In the comparison experiments, the proposed method can achieve state-of-the-art performance on the public datasets, VCD, and VeRi, which are 96.1% and 96.2%, respectively. In addition, the ablation experiment further proves that SC-loss can effectively improve the accuracy of vehicle color recognition.

Keywords: feature extraction, convolutional neural networks, intelligent transportation, vehicle color recognition

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Authors: Hee Sun (Sunny) Choi, Gerhard Bruyns, Wang Zhang, Sky Cheng, Saijal Sharma

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The main focus of this paper is to propose a comprehensive framework for the cognitive measurement and modelling of the built environment. This will involve exploring and measuring neural mechanisms. The aim is to create a foundation for further studies in this field that are consistent and rigorous. Additionally, this framework will facilitate collaboration with cognitive neuroscientists by establishing a shared conceptual basis. The goal of this research is to develop a human-centric approach for urban design that is scientific and measurable, producing a set of urban design guidelines that incorporate cognitive measurement and modelling. By doing so, the broader intention is to design urban spaces that prioritize human needs and well-being, making them more liveable.

Keywords: vertical urbanism, human centric design, spatial cognition and psychology, vertical urban design guidelines

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Authors: Jiahau Guo, Yihe Zhang

Abstract:

This paper proposes solutions for pricing options on stocks paying discrete dividends in markets with daily price limits. We first extend the intraday density function of Guo and Chang (2020) to a multi-day one and use the framework of Haug et al. (2003) to value European options on stocks paying discrete dividends. Next, we adopt the fast Fourier transform (FFT) to derive accurate and efficient formulae for American options and further employ the three-point Richardson extrapolation to accelerate the computation. Finally, the accuracy of our proposed methods is verified by simulations.

Keywords: daily price limit, discrete dividend, early exercise, fast Fourier transform, multi-day density function, Richardson extrapolation

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Authors: Weiming Hu, Xu Li, Xiaonan Li, Zhong Xu, Li Yuan, Xuan Dong

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Maneuver decision-making plays a critical role in high-performance intelligent driving. This paper proposes a risk assessment-based decision-making network (RADMN) to address the problem of driving strategy for the commercial vehicle. RADMN integrates two networks, aiming at identifying the risk degree of collision and rollover and providing decisions to ensure the effectiveness and reliability of driving strategy. In the risk assessment module, risk degrees of the backward collision, forward collision and rollover are quantified for hazard recognition. In the decision module, a deep reinforcement learning based on multi-objective optimization (DRL-MOO) algorithm is designed, which comprehensively considers the risk degree and motion states of each traffic participant. To evaluate the performance of the proposed framework, Prescan/Simulink joint simulation was conducted in highway scenarios. Experimental results validate the effectiveness and reliability of the proposed RADMN. The output driving strategy can guarantee the safety and provide key technical support for the realization of autonomous driving of commercial vehicles.

Keywords: decision-making strategy, risk assessment, multi-objective optimization, commercial vehicle

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Authors: Sara Kamalisiahroudi, Jun Huang, Zhe Li, Jianbo Zhang

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Two types of commercial cylindrical lithium ion batteries (Panasonic 3.4 Ah NCR-18650B and Samsung 2.9 Ah INR-18650), were investigated experimentally. The capacities of these samples were individually measured using constant current-constant voltage (CC-CV) method at different ambient temperatures (-10 ℃, 0 ℃, 25 ℃). Their internal resistance was determined by electrochemical impedance spectroscopy (EIS) and pulse discharge methods. The cells with different configurations of parallel connection NCR-NCR, INR-INR and NCR-INR were charged/discharged at the aforementioned ambient temperatures. The results showed that the difference of internal resistance between cells much more evident at low temperatures. Furthermore, the parallel connection of NCR-NCR exhibits the most uniform temperature distribution in cells at -10 ℃, this feature is quite favorable for the safety of the battery pack.

Keywords: batteries in parallel connection, internal resistance, low temperature, temperature difference, current distribution

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Authors: Hyun-Soo Seol, In-Gun Kim, Hyun Seok Hong, Dong-Woo Kang, Ju Lee

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Rotor of Spoke-Type PMSM is divided into permanent magnet and rotor core. Moreover, rotor core is composed of pole-piece, Bridge and rib. Piece between the permanent magnet N and S poles is pole-piece. Bridge and rib hold pole-piece. In the case of pole-piece and bridge, it is essential structure of Spoke-Type PMSM. However, Rib can be selected by the designer depending on the operating conditions and constraints. If rib is present in the rotor, rib which acts in the leak path generates a leakage flux. Although the leakage flux reduces the torque in low speed, it expands speed range in high speed. So, there is a relationship of trade off. Viewed from the standpoint of permanent magnet demagnetization, since the magnetic flux by the stator winding leaks to the rib, it is an advantage. In addition, rib affects the safety factor of the rotor. For application required high speed operation, since the securing the safety factor of the rotor is important, rib structure is advantageous. On the other hand, in the case of the application that does not require high speed operation, it is desirable to increase the output power by designing without rib. In this paper, Effects on rib structure is analyzed in detail and this paper provides designer with information about rotor design of spoke-type PMSM according to rib structure.

Keywords: spoke-Type PMSM, rotor shape, rib, operation range

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Authors: Mengxiao Li, Johnson Zhang

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Currently, topology optimization technique is widely used to define the layout design of structures that are presented as truss-like topologies. However, due to the difficulty in combining optimization technique with more realistic material models where their nonlinear properties should be considered, the achieved optimized topologies are commonly unable to apply straight towards the practical design problems. This study presented an optimization procedure of composite structures where different elastic stiffness, yield criteria, and hardening models are assumed for the candidate materials. From the results, it can be concluded that a more explicit modeling has the significant influence on the resulting topologies. Also, the isotropic or kinematic hardening is important for elastoplastic structural optimization design. The capability of the proposed optimization procedure is shown through several cases.

Keywords: topology optimization, material composition, nonlinear modeling, hardening rules

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Authors: Guanghua Zhang, Fubao Wang, Weijun Duan

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Convolution neural network (CNN) has attracted more and more attention on recent years. Especially in the field of computer vision and image classification. However, unsupervised learning with CNN has received less attention than supervised learning. In this work, we use a new powerful tool which is deep convolutional generative adversarial networks (DCGANs) to generate images from Sloan Digital Sky Survey. Training by various star and galaxy images, it shows that both the generator and the discriminator are good for unsupervised learning. In this paper, we also took several experiments to choose the best value for hyper-parameters and which could help to stabilize the training process and promise a good quality of the output.

Keywords: convolution neural network, discriminator, generator, unsupervised learning

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Authors: Zhengyang Ma, Zhiyao Li, Jiayi Zhang

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This article examines the prospect theory’s arguments about decision-making through two case studies, the First Gulf War and Russia’s annexation of Crimea. The article uses the methods of comparative case analysis and process tracing to investigate the prospect theory’s fundamental arguments. Through evidence derived from existing primary and secondary sources, this paper argues that both former U.S. President Bush and Russian President Putin viewed their situations as a domain of loss and made risky decisions to prevent further deterioration, which attests the arguments of the prospect theory. After the two case studies, this article also discusses how the prospect theory could be used in analyzing the decision-making process that led to the current Russia-Ukraine War.

Keywords: the prospect theory, international relations, the first gulf war, the crimea crisis

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Authors: Dezhi Li, Peng Cui, Bo Zhang, Tengyuan Chang

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In order to solve the housing problem for the low-income families, the construction of affordable housing is booming in China. However, due to various reasons, the service facilities and systems in the indemnificatory residential community meet many problems. This article established a Satisfaction Evaluation System of the Fundamental Public Services for Large-scale Indemnificatory Residential Community based on the national standards and local criteria and developed evaluation methods and processes. At last, in the case of Huagang project in Nanjing, the satisfaction of basic public service is calculated according to a survey of local residents.

Keywords: indemnificatory residential community, public services, satisfaction evaluation, structural equation modeling

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