Search results for: S. Alina Wang

Authors: Xinke Huang, Huan Wang, Lidong Guo, Changbin Ju, Runbiao Liu, Shanshan Meng, Yibo Wang, Honghua Xu

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Large-scale photovoltaic (PV) generation system connected to HVDC grid has many advantages compared to its counterpart of AC grid. DC connection can solve many problems that AC connection faces, such as the grid-connection and power transmission, and DC connection is the tendency. DC/DC converter as the most important device in the system has become one of the hot spots recently. The paper proposes a centralized DC/DC converter which uses Boost Full Bridge Isolated DC/DC Converter(BFBIC) topology and combination through input parallel output series(IPOS) method to improve power capacity and output voltage to match with the HVDC grid voltage. Meanwhile, it adopts input current sharing control strategy to realize input current and output voltage balance. A ±30kV/1MW system is modeled in MATLAB/SIMULINK, and a downscaled ±10kV/200kW DC/DC converter platform is built to verify the proposed topology and control strategy.

Keywords: photovoltaic generation, cascaded dc/dc converter, galvanic isolation, high-voltage, direct current (HVDC)

Procedia PDF Downloads 442

Authors: Yuling Cui, Danhao Deng, Chaowei Wang, Weidong Wang

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In recent years, unmanned aerial vehicles (UAVs) have been widely used in wireless communication, attracting more and more attention from researchers. UAVs can not only serve as a relay for auxiliary communication but also serve as an aerial base station for ground users (GUs). However, limited energy means that they cannot work all the time and cover a limited range of services. In this paper, we investigate 2D UAV trajectory design and power allocation in order to maximize the UAV's service time and downlink throughput. Based on deep reinforcement learning, we propose a depth deterministic strategy gradient algorithm for trajectory design and power distribution (TDPA-DDPG) to solve the energy-efficient and communication service quality problem. The simulation results show that TDPA-DDPG can extend the service time of UAV as much as possible, improve the communication service quality, and realize the maximization of downlink throughput, which is significantly improved compared with existing methods.

Keywords: UAV trajectory design, power allocation, energy efficient, downlink throughput, deep reinforcement learning, DDPG

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Authors: Dequn Teng, Tianshuo Yang, Mingrui Wang, Qiuyu Chen, Xiao Wang, Katie Atkinson

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Currently, many students are kind of at a loss in the university due to the complex environment within the campus, where every information within the campus is isolated with fewer interactions with each other. However, if the on-campus resources are gathered and combined with the artificial intelligence modelling techniques, there will be a bridge for not only students in understanding themselves, and the teachers will understand students in providing a much efficient approach in education. The objective of this paper is to provide a competency level analysis method, apparatus, electronic equipment, and storage medium. It uses a user’s target competency level analysis model from a plurality of predefined candidate competency level analysis models by obtaining a user’s promotion target parameters, promotion target parameters including at least one of the following parameters: target profession, target industry, and the target company, according to the promotion target parameters. According to the parameters, the model analyzes the user’s ability level, determines the user’s ability level, realizes the quantitative and personalized analysis of the user’s ability level, and helps the user to objectively position his ability level.

Keywords: artificial intelligence, model, university, education, recommendation system, evaluation, job hunting

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Authors: Maletsema Alina Mofokeng, Hussein Shimelis, Mark Laing, Pangirayi Tongoona

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Sorghum is one of the most important cereal crops grown for food, feed and bioenergy. Knowledge of genetic diversity is important for conservation of genetic resources and improvement of crop plants through breeding. The objective of this study was to assess the level of genetic diversity among sorghum genotypes using microsatellite markers. A total of 103 accessions of sorghum genotypes obtained from the Department of Agriculture, Forestry and Fisheries, the African Centre for Crop Improvement and Agricultural Research Council-Grain Crops Institute collections in South Africa were estimated using 30 microsatellite markers. For all the loci analysed, 306 polymorphic alleles were detected with a mean value of 6.4 per locus. The polymorphic information content had an average value of 0.50 with heterozygosity mean value of 0.55 suggesting an important genetic diversity within the sorghum genotypes used. The unweighted pair group method with arithmetic mean clustering based on Euclidian coefficients revealed two major distinct groups without allocating genotypes based on the source of collection or origin. The genotypes 4154.1.1.1, 2055.1.1.1, 4441.1.1.1, 4442.1.1.1, 4722.1.1.1, and 4606.1.1.1 were the most diverse. The sorghum genotypes with high genetic diversity could serve as important sources of novel alleles for breeding and strategic genetic conservation.

Keywords: Genetic Diversity, Genotypes, Microsatellites, Sorghum

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Authors: Yan Yu, Wang Yu, Chen Xintong, Liu Yi, Zhang Yanzhong, Wang Yanji, Chen Xingyu, Zhang Miaocheng, Tong Yi

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Neuromorphic computing based on spiking neural networks (SNNs) has emerged as a promising avenue for building the next generation of intelligent computing systems. Owing to its high-density integration, low power, and outstanding nonlinearity, memristors have attracted emerging attention on achieving SNNs. However, fabricating a low-power and robust memristor-based spiking neuron without extra electrical components is still a challenge for brain-inspired systems. In this work, we demonstrate a TiO₂-based threshold switching (TS) memristor to emulate a leaky integrate-and-fire (LIF) neuron without auxiliary circuits, used to realize single layer fully connected (FC) SNNs. Moreover, our TiO₂-based resistive switching (RS) memristors realize spiking-time-dependent-plasticity (STDP), originating from the Ag diffusion-based filamentary mechanism. This work demonstrates that TiO2-based memristors may provide an efficient method to construct hardware neuromorphic computing systems.

Keywords: leaky integrate-and-fire, memristor, spiking neural networks, spiking-time-dependent-plasticity

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Authors: Xiangxu Chai, Bin Feng, Ping Li, Deyan Zhu, Liquan Wang, Guanzhong Wang, Yukun Jing

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In high power large-aperture laser systems, such as the inertial confinement fusion project, the Nd: glass laser (1053nm) is usually needed to be converted to ultraviolet (UV) light and the fourth harmonic generation (FHG) is one of the most favorite candidates to achieve UV light. Deuterated potassium dihydrogen phosphate (DKDP) crystal is an optimal choice for converting the Nd: glass radiation to the fourth harmonic laser by noncritical phase matching (NCPM). To reduce the damage probability of focusing lens, the DKDP crystal is suggested to be set before the focusing lens. And a converging beam enters the FHG crystal consequently. In this paper, we simulate the process of FHG in the scheme and the dependence of FHG efficiency on the lens’ F is derived. Besides, DKDP crystal with gradient deuterium is proposed to realize the NCPM FHG of the converging beam. At every position, the phase matching is achieved by adjusting the deuterium level, and the FHG efficiency increases as a result. The relation of the lens’ F with the deuterium gradient is investigated as well.

Keywords: fourth harmonic generation, laser induced damage, converging beam, DKDP crystal

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Authors: Mengying Wang, Xiaohui Wang, Chun Deng, Bei Liu, Changyu Sun, Guangjin Chen, Mahmoud El-Halwagi

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Significant amounts of natural gas hydrates (NGHs) are considered potential new sustainable energy resources in the future. However, common used methods for methane gas recovery from hydrate sediments require high investment but with low gas production efficiency, and may cause potential environment and security problems. Therefore, there is a need for effective gas production from hydrates. The natural gas hydrate production method by CO₂/H₂ replacement coupling steam methane reforming can improve the replacement effect and reduce the cost of gas separation. This paper develops a simulation model of the gas production process integrated with steam reforming and membrane separation. The process parameters (i.e., reactor temperature, pressure, H₂O/CH₄ ratio) and the composition of CO₂ and H₂ in the feed gas are analyzed. Energy analysis is also conducted. Two design scenarios with different composition of CO₂ and H₂ in the feed gas are proposed and evaluated to assess the energy efficiency of the novel system. Results show that when the composition of CO₂ in the feed gas is between 43 % and 72 %, there is a certain composition that can meet the requirement that the flow rate of recycled gas is equal to that of feed gas, so as to ensure that the subsequent production process does not need to add feed gas or discharge recycled gas. The energy efficiency of the CO₂ in feed gas at 43 % and 72 % is greater than 1, and the energy efficiency is relatively higher when the CO₂ mole fraction in feed gas is 72 %.

Keywords: Gas production, hydrate, process integration, steam reforming

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Authors: Xiao-lei Wang

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The Novel Concept Combination (NCC) refers to the unique ability of multilingual children to creatively merge and integrate different linguistic and cultural elements to form innovative and original concepts. Children raised with more than one language often exhibit this skill in their daily communication, such as creating innovative metaphors that enrich their communication, showcasing their creativity in conveying the essence of their messages. This paper explores NCC abilities in multilingual children by focusing on two male trilingual siblings exposed to Chinese, French, and English from birth. The siblings were observed for 19 years in their daily context. Seventy-six hours of video-recorded data were used for this study (38 hours for each participant). A coding scheme developed by Wang et al. was employed to code the recorded data. The results suggest that these multilingual siblings proportionally increased their NCC skills over the years, emerging at age 3 and peaking at age 15. The characteristic of their NCC lies in their capacity to not merely replicate linguistic elements of different languages but to recreate, reshape, and reconstruct novel ideas in communication, enriching their interactions. The paper also addresses the educational implications for educators and parents, emphasizing the importance of valuing these novel ideas in everyday environments to encourage NCC development. This, in turn, contributes to cognitive and social development.

Keywords: multilingual children, novel concept combination, multilingual creativity, linguistic richness

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Authors: W. Du, X. Wang, Jun Cao, H. F. Wang

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Due to the randomness and uncertainty of wind energy, modern power systems integrating large-scale wind generation will be significantly impacted in terms of system performance and technical challenges. System inertia with high wind penetration is decreasing when conventional thermal generators are gradually replaced by wind turbines, which do not naturally contribute to inertia response. The power imbalance caused by wind power or demand fluctuations leads to the instability of system frequency. Accordingly, the need to attach the supplementary virtual inertia control to wind farms (WFs) strongly arises. When multi-wind farms are connected to the grid simultaneously, the selection of which critical WFs to install the virtual inertia control is greatly important to enhance the stability of system frequency. By building the small signal model of wind power systems considering frequency regulation, the installation locations are identified by the geometric measures of the mode observability of WFs. In addition, this paper takes the impacts of grid topology and selection of feedback control signals into consideration. Finally, simulations are conducted on a multi-wind farms power system and the results demonstrate that the designed virtual inertia control method can effectively assist the frequency regulation.

Keywords: frequency regulation, virtual inertia control, installation locations, observability, wind farms

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Authors: Yuqiao Zhou

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The Sapir-Whorf hypothesis (SWH) emphasizes the effect produced by language on people’s minds. According to linguistic relativity, language has evolved over the course of human life on earth, and, in turn, the acquisition of language shapes learners’ thoughts. Despite much attention drawn by SWH, few scholars have attempted to analyse people’s thoughts via their literary works. And yet, the linguistic choices that create a narrative can enable us to examine its writer’s thoughts. Still, less work has been done on the impact of language on the minds of bilingual people. Internationalization has resulted in an increasing number of bilingual and multilingual individuals. In China, where more than one hundred languages are used for communication, most people are bilingual in Mandarin Chinese (the official language of China) and their own dialect. Taking as its corpus the ethnic minority myth of Ge Sa-er Wang by Alai and its English translation by Goldblatt and Lin, this paper aims to analyse the effects of culture on bilingual people’s minds. It will first analyse Alai’s thoughts on using the original version of Ge Sa-er Wang; next, it will examine the thoughts of the two translators by looking at translation choices made in the English version; finally, it will compare the cultural influences evident in the thoughts of Alai, and Goldblatt and Lin. Whereas Alai can speak two Sino-Tibetan languages – Mandarin Chinese and Tibetan – Goldblatt and Lin can speak two languages from different families – Mandarin Chinese (a Sino-Tibetan language) and English (an Indo-European language). The results reveal two systems of thought existing in the translators’ minds; Alai’s text, on the other hand, does not reveal a significant influence from North China, where Mandarin Chinese originated. The findings reveal the inconsistency of a second language’s influence on people’s minds. Notably, they suggest that the more different the two languages are, the greater the influence produced by the second language culture on people’s thoughts. It is hoped that this research will expand the scope of SWH as well as shed light on future translation studies on ethnic minority literature.

Keywords: Sapir-Whorf hypothesis, cultural translation, cultural-specific items, Ge Sa-er Wang, ethnic minority literature, Tibet

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Authors: Wenjuan Du, Jingtian Bi, Tong Wang, Haifeng Wang

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Grid connection of a large-scale wind farm affects power system small-signal angular stability in two aspects. Firstly, connection of the wind farm brings about the change of load flow and configuration of a power system. Secondly, the dynamic interaction is introduced by the wind farm with the synchronous generators (SGs) in the power system. This paper proposes a method to assess the two aspects of the effect of the wind farm on power system small-signal angular stability. The effect of the change of load flow/system configuration brought about by the wind farm can be examined separately by displacing wind farms with constant power sources, then the effect of the dynamic interaction of the wind farm with the SGs can be also computed individually. Thus, a clearer picture and better understanding on the power system small-signal angular stability as affected by grid connection of the large-scale wind farm are provided. In the paper, an example power system with grid connection of a wind farm is presented to demonstrate the proposed approach.

Keywords: power system small-signal angular stability, power system low-frequency oscillations, electromechanical oscillation modes, wind farms, double fed induction generator (DFIG)

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Authors: Xiang Jianhong, Wang Cong, Wang Linyu

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With the rise of medical IoT technologies, Wireless body area networks (WBANs) can collect fetal electrocardiogram (FECG) signals to support telemedicine analysis. The compressed sensing (CS)-based WBANs system can avoid the sampling of a large amount of redundant information and reduce the complexity and computing time of data processing, but the existing algorithms have poor signal compression and reconstruction performance. In this paper, a Joint block multi-orthogonal least squares (JBMOLS) algorithm is proposed. We apply the FECG signal to the Joint block sparse model (JBSM), and a comparative study of sparse transformation and measurement matrices is carried out. A FECG signal compression transmission mode based on Rbio5.5 wavelet, Bernoulli measurement matrix, and JBMOLS algorithm is proposed to improve the compression and reconstruction performance of FECG signal by CS-based WBANs. Experimental results show that the compression ratio (CR) required for accurate reconstruction of this transmission mode is increased by nearly 10%, and the runtime is saved by about 30%.

Keywords: telemedicine, fetal ECG, compressed sensing, joint sparse reconstruction, block sparse signal

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Authors: Hao Liu, Lihui Zheng, Chinedu J. Okere, Chao Wang, Xiangchun Wang, Peng Zhang

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The coalbed methane (CBM) extraction industry (an unconventional energy source) is yet to promulgated an established standard code of practice for the experimental evaluation of sensitivity damage of coal samples. The existing experimental process of previous researches mainly followed the industry standard for conventional oil and gas reservoirs (CIS). However, the existing evaluation method ignores certain critical differences between CBM reservoirs and conventional reservoirs, which could inevitably result in an inaccurate evaluation of sensitivity damage and, eventually, poor decisions regarding the formulation of formation damage prevention measures. In this study, we propose improved experimental guidelines for evaluating seepage sensitivity damage of CBM reservoirs by leveraging on the shortcomings of the existing methods. The proposed method was established via a theoretical analysis of the main drawbacks of the existing methods and validated through comparative experiments. The results show that the proposed evaluation technique provided reliable experimental results that can better reflect actual reservoir conditions and correctly guide future development of CBM reservoirs. This study is pioneering the research on the optimization of experimental parameters for efficient exploration and development of CBM reservoirs.

Keywords: coalbed methane, formation damage, permeability, unconventional energy source

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Authors: Fuyuan Ma, Ying Wang, Xin Wang

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Social networks have become breeding grounds for the rapid spread of rumors and malicious information, posing threats to societal stability and causing significant public harm. Existing research focuses on simulating the spread of information and its impact on users through propagation dynamics and applies methods such as greedy approximation strategies to approximate the optimal control solution at the global scale. However, the greedy strategy at the global scale may fall into locally optimal solutions, and the approximate simulation of information spread may accumulate more errors. Therefore, we propose a multi-scale control model for network group behavior, introducing individual and group scales on top of the greedy strategy’s global scale. At the individual scale, we calculate the propagation influence of nodes based on their structural attributes to alleviate the issue of local optimality. At the group scale, we conduct precise propagation simulations to avoid introducing cumulative errors from approximate calculations without increasing computational costs. Experimental results on three real-world datasets demonstrate the effectiveness of our proposed multi-scale model in controlling network group behavior.

Keywords: influence blocking maximization, competitive linear threshold model, social networks, network group behavior

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Authors: Huilei Wang, Yuanfeng Wang

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In the early period of China, economy developed rapidly at the cost of environment. Recently, it is generally recognized that the heavily polluted environment not only puts a brake on economic development but also paces negative impact on people’ health as well as probably next decades of generations. Accordingly, the latest Environmental Protection Law revised in 2014 makes a clear-cut division of environmental responsibility and regulates stricter penalties of breaching law. As the new environmental law is enforced gradually, environmental forensic is increasingly required in the process of ascertaining facts in judicial proceedings of environmental cases. Based on the outcomes of documentary analysis for all environmental cases judged on the basis of new environmental law, it is concluded that there still exists problems in present system of environmental forensic. Thus, this paper is aimed to make proposition on improving Chinese environmental forensic system, which involves: (i) promoting capability of environmental forensic system (EFS) to handle professional questions; (ii) develop price mechanism; (iii) multi-departments cooperate to establish unifying and complete EFS system;(iv) enhance the probative value of results of EFS. Such protocol for amending present regulation on environmental forensic is of significant importance because a quality report of environmental forensic will contributes to providing strong probative evidence of culprits’ activity of releasing contaminant into environment, degree of damages for victims and above all, causality between the behavior of public nuisance and damages.

Keywords: China, environmental cases, environmental forensic system, proposition

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Authors: Li Yu, Chenlu Jiao, Hongrun Xin, Yan Wang, Kaiyang Wang

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In order to study the impact of various factors on the housing price, we propose to build different prediction models based on deep learning to determine the existing data of the real estate in order to more accurately predict the housing price or its changing trend in the future. Considering that the factors which affect the housing price vary widely, the proposed prediction models include two categories. The first one is based on multiple characteristic factors of the real estate. We built Convolution Neural Network (CNN) prediction model and Long Short-Term Memory (LSTM) neural network prediction model based on deep learning, and logical regression model was implemented to make a comparison between these three models. Another prediction model is time series model. Based on deep learning, we proposed an LSTM-1 model purely regard to time series, then implementing and comparing the LSTM model and the Auto-Regressive and Moving Average (ARMA) model. In this paper, comprehensive study of the second-hand housing price in Beijing has been conducted from three aspects: crawling and analyzing, housing price predicting, and the result comparing. Ultimately the best model program was produced, which is of great significance to evaluation and prediction of the housing price in the real estate industry.

Keywords: deep learning, convolutional neural network, LSTM, housing prediction

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Authors: Xinke Huang, Huan Wang, Lidong Guo, Changbin Ju, Runbiao Liu, Guoen Cao, Yibo Wang, Honghua Xu

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Grid connected photovoltaic (PV) power system is to be developed in the direction of large-scale, clustering. Large-scale PV generation systems connected to HVDC grid have many advantages compared to its counterpart of AC grid, and DC connection is the tendency. DC/DC converter as the most important device in the system, has become one of the hot spots recently. The paper proposes a Quasi Z-Source(QZS) based Boost Full Bridge Isolated DC/DC Converter(BFBIC) topology as a basis power module and combination through input parallel output series(IPOS) method to improve power capacity and output voltage to match with the HVDC grid. The topology has both traditional voltage source and current source advantages, it permit the H-bridge short through and open circuit, which adopt utility duty cycle control and achieved input current and output voltage balancing through input current sharing control strategy. A ±10kV/200kW system model is built in MATLAB/SIMULINK to verify the proposed topology and control strategy.

Keywords: PV Generation System, Cascaded DC/DC converter, HVDC, Quasi Z Source Converter

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Authors: Jing Wang, Yong Wang

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For organizational development, employee well-being is critical and has been influenced deeply by character strengths. Therefore, investigating the relationship between character strengths and employee well-being and its inner mechanism is crucial. In this study, we explored the features of Chinese employees' character strengths, studied the relationship between character strengths and employees' subjective well-being, work well-being and psychological well-being respectively, and examined the mediating effect of work-family relationship (both enrichment and conflict). An online survey was conducted. The results showed that: (1) The top five character strengths of Chinese employees were gratitude, citizenship, kindness, appreciation of beauty and excellence, justice, while the bottom five ones were creativity, authenticity, bravery, spirituality, open-mindedness. (2) Subjective well-being was significantly correlated to courage, humanity, transcendence and justice. Work well-being was significantly correlated to wisdom, courage, humanity, justice and transcendence. Psychological well-being was significantly correlated to all the above five character strengths and temperance. (3) Wisdom and humanity influenced Chinese employees’ subjective well-being through work-family enrichment. Justice enhanced psychological well-being via work-family enrichment; meanwhile, it also played a positive role in subjective well-being, work well-being, and psychological well-being by decreasing the family-work conflict. At the end of this paper, some theoretical and practical contributions to organizational management were further discussed.

Keywords: character strengths, work-family conflict, work-family enrichment, employee well-being, work well-being

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Authors: Haohao Wang

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The purpose of this paper is to find elimination ideals via Grobner basis. We first introduce the concept of Grobner bases, and then, we provide computational algorithms to applications for curves and surfaces.

Keywords: curves, surfaces, Grobner basis, elimination

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Authors: Elena Tkachenko, Vladimir Kokh, Alina Osipenko, Vladislav Surkov

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The modern period of development of Russian economy is fraught with a number of problems related to limitations in the use of traditional planning and financial management tools. Restrictions in the use of foreign software when performing an order of the Russian Government, on the one hand, and sanctions limiting the support of the major ERP and MRP II systems in the Russian Federation, on the other hand, entail the necessity to appeal to the basics of developing budgeting and analysis systems for industrial enterprises. Thus, cost calculation theory becomes the theoretical foundation for the development of industrial cost management systems. Based on the foregoing, it would be fair to make an assumption that the development of a working managerial accounting model on an industrial enterprise using an automated enterprise resource management system should rest upon the concept of the inevitability of alterations of business processes. On the other hand, optimized business processes make the architecture of financial analytics more transparent and permit the use of all the benefits of data cubes. The metrics and indicator slices provide online assessment of the state of key business processes at a given moment of time, which improves the quality of managerial decisions considerably. Therefore, the bilateral sanctions situation boosted the development of corporate business analytics and took industrial companies to the next level of understanding of business processes.

Keywords: cost culculation, ERP, OLAP, modern Russian economy

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Authors: Otilia Ruxandra Vasile, Ecaterina Andronescu, Cristina Daniela Ghitulica, Bogdan Stefan Vasile, Roxana Trusca, Eugeniu Vasile, Alina Maria Holban, Carmen Mariana Chifiriuc, Florin Iordache, Horia Maniu

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Engineered powders offer great promise in several applications, but little information is known about cytotoxicity effects. The aim of the current study was the synthesis and cytotoxicity examination of silver powders using pyrosol method at temperatures of 600°C, 650°C and 700°C, respectively sol-gel method and calcinations at 500°C, 600°C, 700°C and 800°C. We have chosen to synthesize and examine silver particles cytotoxicity due to its use in biological applications. The synthesized Ag powders were characterized from the structural, compositional and morphological point of view by using XRD, SEM, and TEM with SAED. In order to determine the influence of the synthesis route on Ag particles cytotoxicity, different sizes of micro and nanosilver synthesized powders were evaluated for their potential toxicity. For the study of their cytotoxicity, cell cycle and apoptosis have been done analysis through flow cytometry on human colon carcinoma cells and mesenchymal stem cells and through the MTT assay, while the viability and the morphological changes of the cells have been evaluated by using cloning studies. The results showed that the synthesized silver nanoparticles have displayed significant cytotoxicity effects on cell cultures. Our synthesized silver powders were found to present toxicity in a synthesis route and time-dependent manners for pyrosol synthesized nanoparticles; whereas a lower cytotoxicity has been measured after cells were treated with silver nanoparticles synthesized through sol-gel method.

Keywords: Ag, cytotoxicity, pyrosol method, sol-gel method

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Authors: Wang Zhiwei, Wang Weiwu

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The process of urbanization in China has entered a critical period of transformation from urban expansion and construction to delicate urban design, thus forming a new direction in the field of urban design. So far, catalyst theory has become a prominent guiding strategy in urban planning and design. In this paper, under the background of urban renewal, catalyst theory is taken as the guiding ideology to explore the method of urban design in shouxian county. Firstly, this study briefly introduces and analyzes the catalyst theory. Through field investigation, it is found that the city has a large number of idle Spaces, such as abandoned factories and schools. In the design, the idle Spaces in the county town are utilized and interlinked in space, and functional interaction is carried out from the pattern of the county town. On the one hand, the results showed that the catalyst theory can enhance the vitality of the linear street space with a small amount of monomer construction. On the other hand, the city can also increase the cultural and economic sites of the city without damaging the historical relics and the sense of alterations of the ancient city, to improve the quality of life and quality of life of citizens. The city micro-transformation represented by catalyst theory can help ancient cities like shouxian to realize the activation of the old city and realize the gradual development.

Keywords: catalytic theory, urban design, China's ancient city, Renaissance

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Authors: Ishaq Ahmad, Zhaomin Li, Liu Chengwen, Song yan Li, Wang Lei, Zhoujie Wang, Zheng Lei

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Because nanoparticles have the potential to improve foam stability, only a small amount of surfactant or polymer is required to control gas mobility in the reservoir. Numerous researches have revealed that this specific application is in use. The goal is to improve foam formation and foam stability. As a result, the foam stability and foam ability of black rice husk ash were investigated. By injecting N₂ gases into a core flood condition, black rice husk ash was used to produce stable foam. The properties of black rice husk ash were investigated using a variety of characterization techniques. The black rice husk ash was mixed with the best-performing anionic foaming surfactants at various concentrations (ppm). Sodium dodecyl benzene sulphonate was the anionic surfactant used (SDBS). In this article, the N₂ gas- black rice husk ash (BRHA) with high Silica content is shown to be beneficial for foam stability and foam ability. For the test, a 30 cm sand pack was prepared. For the experiment, N₂ gas cylinders and SDBS surfactant liquid cylinders were used. Two N₂ gas experiments were carried out: one without a sand pack and one with a sand pack and oil addition. The black rice husk and SDBS surfactant concentration was 0.5 percent. The high silica content of black rice husk ash has the potential to improve foam stability in sand pack conditions, which is beneficial. On N₂ foam, there is an increase in black rice husk ash particles, which may play an important role in oil recovery.

Keywords: black rice husk ash nanoparticle, surfactant, N₂ foam, sand pack

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Authors: Yuguang Wang, Chuanjun Wang

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At present, many coastal areas around the world suffer from seawater intrusion. Seawater intrusion is the superimposed result of two factors which are nature and human social economical activities in particular area. In recent years, due to excessive exploitation of groundwater, the seawater intrusion phenomenon aggravate in coastal zone of the Bohai and Huanghai seas in our country. Moreover, with sea-level rising, the original hydrodynamic equilibrium between saltwater and freshwater has been damaged to a certain extent, and it will further aggravate seawater intrusion in the land plains. In addition, overexploitation of groundwater declined groundwater level and increase saltwater intrusion in coastal areas. Therefore, in view of the sensitivity and vulnerability of the impact of sea-level rise in the future, the risk of sea-level rise in coastal zone should be considered, reasonable exploitation, utilization and management of coastal zone’s groundwater should be formulated. The response mechanism of sea-level rise should be studied to prevent and reduce the harm of seawater intrusion, which has important theoretical and realistic significances. In this paper, through the long-term monitoring of groundwater level and conductibility in the transition region of seawater intrusion for the sand coast area, realtimely master the situation of seawater intrusion. Combined with the seasonal exploitation station of groundwater and sea level variation, early alert the seawater intrusion to prevent and reduce the harm of seawater intrusion.

Keywords: groundwater level, sea level, seawater intrusion, sand coast

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Authors: Adrian Ionut Nicoara, Denisa Ionela Ene, Alina Maria Holban, Cristina Busuioc

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At present, the development of materials with biomedical applications is a domain of interest that will produce a full series of benefits in engineering and medicine. In this sense, it is required to use a natural material, and this paper is focused on the development of a composite material based on bacterial cellulose – hydroxyapatite and silver nanoparticles with applications in hard tissue. Bacterial cellulose own features like biocompatibility, non-toxicity character and flexibility. Moreover, the bacterial cellulose can be conjugated with different forms of active silver to possess antimicrobial activity. Hydroxyapatite is well known that can mimic at a significant level the activity of the initial bone. The material was synthesized by using an ultrasound probe and finally characterized by several methods. Thereby, the morphological properties were analyzed by using Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM). Because the synthesized material has medical application in restore the tissue and to fight against microbial invasion, the samples were tested from the biological point of view by evaluating the biodegradability in phosphate-buffered saline (PBS) and simulated body fluid (SBF) and moreover the antimicrobial effect was performed on Gram-positive bacterium Staphylococcus aureus, Gram-negative bacterium Escherichia coli, and fungi Candida albicans. The results reveal that the obtained material has specific characteristics for bone regeneration.

Keywords: bacterial cellulose, biomaterials, hydroxyapatite, scaffolds materials

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Authors: Haiyan Wang, Dongyun Wang, Yongyong Yan, Richard T. Jaspers, Gang Wu

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Mesenchymal stem cell and 3D printing-based bone tissue engineering present a promising technique to repair large-volume bone defects. Its success is highly dependent on cell attachment, spreading, osteogenic differentiation, and in vivo survival of stem cells on 3D-printed scaffolds. In this study, human salivary histatin-1 (Hst1) was utilized to enhance the interactions between human adipose-derived stem cells (hASCs) and 3D-printed β-tricalcium phosphate (β-TCP) bioceramic scaffolds. Fluorescent images showed that Hst1 significantly enhanced the adhesion of hASCs to both bioinert glass and 3D-printed β-TCP scaffold. In addition, Hst1 was associated with significantly higher proliferation and osteogenic differentiation of hASCs on 3D-printed β-TCP scaffolds. Moreover, coating 3D-printed β-TCP scaffolds with histatin significantly promotes the survival of hASCs in vivo. The ERK and p38 but not JNK signaling was found to be involved in the superior adhesion of hASCs to β-TCP scaffolds with the aid of Hst1. In conclusion, Hst1 could significantly promote the adhesion, spreading, osteogenic differentiation, and in vivo survival of hASCs on 3D-printed β-TCP scaffolds, bearing a promising application in stem cell/3D printing-based constructs for bone tissue engineering.

Keywords: 3d printing, adipose-derived stem cells, bone tissue engineering, histatin-1, osteogenesis

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Authors: Alina P. Colling, Robert G. Hekkenberg

Abstract:

Recent years have seen extensive technological advancement in truck platooning, as reflected in the literature. Its main benefits are the improvement of traffic stability and the reduction of air drag, resulting in less fuel consumption, in comparison to using individual trucks. Platooning is now being adapted to the waterborne transport sector in the NOVIMAR project through the development of a Vessel Train (VT) concept. The main focus of VT’s, as opposed to the truck platoons, is the decrease in manning on board, ultimately working towards autonomous vessel operations. This crew reduction can prove to be an important selling point in achieving economic competitiveness of the waterborne approach when compared to alternative modes of transport. This paper discusses the expected benefits and drawbacks of the VT concept, in terms of the technical logistic performance and generalized costs. More specifically, VT’s can provide flexibility in destination choices for shippers but also add complexity when performing special manoeuvres in VT formation. In order to quantify the cost and performances, a model is developed and simulations are carried out for various case studies. These compare the application of VT’s in the short sea and inland water transport, with specific sailing regimes and technologies installed on board to allow different levels of autonomy. The results enable the identification of the most important boundary conditions for the successful operation of the waterborne platooning concept. These findings serve as a framework for future business applications of the VT.

Keywords: autonomous vessels, NOVIMAR, vessel trains, waterborne platooning

Procedia PDF Downloads 223

Authors: Jingting Luo, Yong Wang, Ying Wang

Abstract:

Pedestrian detection in image or video data is a very important and challenging task in security surveillance. The difficulty of this task is to locate and detect pedestrians of different scales in complex scenes accurately. To solve these problems, a deep neural network (RT-YOLOv3) is proposed to realize real-time pedestrian detection at different scales in security monitoring. RT-YOLOv3 improves the traditional YOLOv3 algorithm. Firstly, the deep residual network is added to extract vehicle features. Then six convolutional neural networks with different scales are designed and fused with the corresponding scale feature maps in the residual network to form the final feature pyramid to perform pedestrian detection tasks. This method can better characterize pedestrians. In order to further improve the accuracy and generalization ability of the model, a hybrid pedestrian data set training method is used to extract pedestrian data from the VOC data set and train with the INRIA pedestrian data set. Experiments show that the proposed RT-YOLOv3 method achieves 93.57% accuracy of mAP (mean average precision) and 46.52f/s (number of frames per second). In terms of accuracy, RT-YOLOv3 performs better than Fast R-CNN, Faster R-CNN, YOLO, SSD, YOLOv2, and YOLOv3. This method reduces the missed detection rate and false detection rate, improves the positioning accuracy, and meets the requirements of real-time detection of pedestrian objects.

Keywords: pedestrian detection, feature detection, convolutional neural network, real-time detection, YOLOv3

Procedia PDF Downloads 141

Authors: Maletsema Alina Mofokeng, Nemera Shargie

Abstract:

Sorghum is one of the most important cereal crops grown as a source of calories for many people in tropics and sub-tropics of the world. Proper characterisation and evaluation of crop germplasm is an important component for effective management of genetic resources and their utilisation in the improvement of the crop through plant breeding. The objective of the study was to estimate the genetic diversity present in sorghum accessions grown in South Africa using agro-morphological traits and some nutritional contents. The experiment was carried out in Potchefstroom. Data were subjected to correlations, principal components analysis, and hierarchical clustering using GenStat statistical software. There were highly significance differences among the accessions based on agro-morphological and nutritional quality traits. Grain yield was highly positively correlated with panicle weight. Plant height was highly significantly correlated with internode length, leaf length, leaf number, stem diameter, the number of nodes and starch content. The Principal component analysis revealed three most important PCs with a total variation of 78.6%. The protein content ranged from 7.7 to 14.7%, and starch ranged from 58.52 to 80.44%. The accessions that had high protein and starch content were AS16cyc and MP4277. There was vast genetic diversity observed among the accessions assessed that can be used by plant breeders to improve yield and nutritional traits.

Keywords: accessions, genetic diversity, nutritional quality, sorghum

Procedia PDF Downloads 263

Authors: Xiaoqing Wang, Junfeng Wang, Xiaolan Zhu

Abstract:

Android operating system has been recognized by most application developers because of its good open-source and compatibility, which enriches the categories of applications greatly. However, it has become the target of malware attackers due to the lack of strict security supervision mechanisms, which leads to the rapid growth of malware, thus bringing serious safety hazards to users. Therefore, it is critical to detect Android malware effectively. Generally, the permissions declared in the AndroidManifest.xml can reflect the function and behavior of the application to a large extent. Since current Android system has not any restrictions to the number of permissions that an application can request, developers tend to apply more than actually needed permissions in order to ensure the successful running of the application, which results in the abuse of permissions. However, some traditional detection methods only consider the requested permissions and ignore whether it is actually used, which leads to incorrect identification of some malwares. Therefore, a machine learning detection method based on the actually used permissions combination and API calls was put forward in this paper. Meanwhile, several experiments are conducted to evaluate our methodology. The result shows that it can detect unknown malware effectively with higher true positive rate and accuracy while maintaining a low false positive rate. Consequently, the AdaboostM1 (J48) classification algorithm based on information gain feature selection algorithm has the best detection result, which can achieve an accuracy of 99.8%, a true positive rate of 99.6% and a lowest false positive rate of 0.

Keywords: android, API Calls, machine learning, permissions combination

Procedia PDF Downloads 329