bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis and Optimization of Low-Voltage and High-Current Matrix Current-Doubler Rectifiers Integrated Magnetic Components
Authors: Zhou Yingjian , Chen Wei
Published: December 2022

All parties favour the half-bridge current-doubling rectifier circuit due to its advantages: small output current pulsation, low switching voltage stress, and high anti-unbalance ability. Further integration of the secondary inductor and the transformer further reduces the size of the converter and dramatically improves the power density. This paper carefully analyzes the existing magnetic integration schemes. Combined with the characteristics of low-voltage and high-current DC converters, the secondary winding in this paper adopts the form of one turn to further reduce the loss so as to adapt to the secondary output of high current. The way the integrated magnetics are matrixed. The secondary side has a higher DC flux offset, and the magnetic core material adopts a magnetic powder core with high saturation magnetic density, which is equivalent to a distributed air gap, which significantly reduces the additional winding loss caused by the air gap diffusion magnetic flux cutting the winding. The winding loss, termination loss, core loss, and distribution parameters of single and matrix integrated magnetic components were compared and analyzed. Focus on optimization analysis. At the same time, it focuses on the influence of matrix on the DC bias and DC loss of the current-doubling rectifier core. At the same time, the leakage inductance and winding loss of the integrated magnetic components are comprehensively considered, and a compromise design is carried out further to improve the power density of the integrated magnetic components.
ST-AGNN: Spatial-Temporal Attention Graph Neural Network for Pedestrian Trajectory Prediction
Authors: Li Yonghong , Cui Jiayi , Zhao Zhiqiang , Li Laquan
Published: December 2022

Accurate and fast prediction of pedestrian trajectory is very important. However, the interaction between pedestrians is complex, pedestrians are affected not only by their own motion but also by the neighboring pedestrians. Some methods do not extract the pedestrian motion features completely. It is easy to ignore a few of important features of pedestrians. The Spatial-Temporal Attention Graph Convolutional Network (ST-AGNN) for pedestrian trajectory prediction is proposed in this paper. ST-AGNN model can extract the spatial interaction features of each time step and stack the spatial features to obtain the spatial-temporal features. It can predict the future trajectory by using Temporal Convolutional Network (TCN). We evaluate the average displacement error (ADE) and final displacement error (FDE) of the proposed method on ETH and UCY datasets. The experimental results show that the proposed method is effective in accuracy and efficiency.
Simulation and Analysis of Dynamic Characteristics of Tilt Rotor/Wing Coupling System
Authors: Sun Fengnan , Zhu Yan , Cheng Qiyou , Wang Siwen , Xing Longtao
Published: December 2022

Considering the coupling effects of elastic wing, elastic blade, rigid nacelle and connection points between systems, the mathematical model of the coupling system including wing/nacelle/tilting rotor is established. Based on the eigenvalue method, the overall modal changes of the rotor installed on the wing and the effects of speed and offset on the dynamic characteristics of the system are studied. The results show that the wing joint motion mainly affects the backward and forward modes of rotor flapping. Different rotor rotation speeds cause varying degrees of modal frequencies of wings in different flight modes, especially the wing flapping mode. The nacelle tilt angle causes significant changes in wing waving frequency, and other modes are basically unaffected. The shaft length mainly affects the wing shimmy and torsional mode in vertical flight, and the offset basically does not affect the wing modes in the forward flight stage.
CAE Optimization Analysis and Design of Injection Mold Cooling System for Digital Camera Battery Cover
Authors: Liang Guodong
Published: December 2022

Moldflow is used to analyze the injection molding of the product. According to the analysis results, the gate position, quantity, size, cooling system, and pressure holding parameters are effectively optimized, and the warpage deformation is effectively reduced. It can reduce the late modification caused by the unreasonable mold design, obtain the best molding parameters, shorten the production cycle of the product, and enhance the competitiveness of the enterprise. This paper optimizes the filling, cooling and molding parameters of the mold cooling system of the digital camera battery cover based on the Moldflow software, so that the warpage deformation can be effectively controlled.
A Deep Learning-Based Model for Classifying Malicious Network Traffic
Authors: Gu Liang , Di Ting , Zhou Xin
Published: December 2022

Network traffic, as a carrier of information transmission and interaction, portrays the behavior trajectory of users and functions as an important approach to detect network attacks and analyze network anomalies. To address the problems such as low recognition rate, high false alarm rate and inability to detect unknown traffic due to the difficulty of traffic feature extraction, over-reliance on manual experience and feature techniques in traditional network traffic analysis practice, this paper proposes a network traffic classification method that integrates mutual information and convolutional neural network, which, not relying too much on manual feature extraction, assigns weights to network features by mutual information and accomplishes the classification and analysis of malicious traffic based on convolutional neural network and short and long-term memory network. The experimental results show that the method can greatly improve the detection rate of malicious traffic with excellent robustness and generalization while reducing the artificial dependence.
Analysis of the Influence of Foundation Pit Excavation on Adjacent Metro Tunnel
Authors: Zhou Jian , Ye Shuaihua , Zeng Hao
Published: December 2022

Relying on the deep foundation pit support engineering adjacent to the subway tunnel in Lanzhou, Two support schemes of double row piles and row piles + inner bracing are designed. Through the method of numerical simulation, the three-dimensional models including tunnel are established by using MIDAS-GTS-NX software, and then compared and analyzed from two aspects: the displacement of supporting structure, deformation and internal force of tunnel lining. The results show that: (1) For the double-row pile supporting structure, the maximum displacement and stress of the row pile appear near the midpoint of the side of the excavation side; for the row pile + internal bracing supporting structure, the maximum displacement and stress appear near the left position of the midpoint of the excavation side. (2) The maximum position of the tunnel displacement is different, and the displacement decreases gradually from the maximum position of the tunnel displacement to both sides of the tunnel. Through the comparative analysis, it can be known that the row pile + internal bracing structure is much better than the double-row pile supporting structure in controlling the deformation of foundation pit and adjacent tunnel.
Dynamic Analysis of Bifurcations for a Class of Fractional-Order Controlled Model with Damping
Authors: Deng Shuxian , Zhang Lina
Published: December 2022

In this paper, a class of damped fractional-order control systems is studied, and the dynamic characteristics of its bifurcations are analyzed. We use Riccati transform, inequality technique, H function and other methods to study nonlinear fractional-order control with damping terms. For the nonlinear neutral fractional-order control system, we analyze the dynamic behavior of the bifurcation of the system in the large-time state, and obtain the asymptotic properties in the large-time state. By designing damping conditions, local and global asymptotic behaviors are obtained, and the coupling strength of multiple nodes in a fractional dynamic control system is solved according to the obtained results. The internal coupling matrix and topology of the considered complex control model have symmetric and irreducible properties. Numerical simulation examples verify the validity of the obtained conclusions.
Estimating Hidden Parameters from a Dataset with Large Amount of Missing Data
Authors: Hu Yuzhong
Published: December 2022

Dealing with missing data is a fundamental problem in data science. In some rare cases, the large amount of missing data can be a big problem for any data analysing tasks. In this paper, we propose a method based on maximum likelihood estimation and expectation maximization to get estimation on the hidden parameter with large amount of missing data in the dataset. We perform the numerical experiments to validate the feasibility and stability of our method. We test the algorithm for different patterns of missing data, different amount of samples and different noise levels. The result indicates that the algorithm is effective in handling large amount of missing data if enough samples are provided.
A Recommender System for Healthy Food Choices Based on Integer Programming
Authors: Wang Shuai , Xia Kaiwen , Yang Yanxiong , Qiu Ruofeng , Qi Yunfei , Miao Qunfeng , Xie Wu , Liu Tao
Published: December 2022

With the change of life style, more and more people are eating out, and the dietary content is high in calories, fat and sugar, resulting in the increasing number of obesity in children, adolescents and adults, and the prevalence of chronic diseases continues to grow. Therefore, preventive health care has become the focus of health policy in the 21st century. The pursuit of health must start from the daily diet. This paper proposes an intelligent recipe recommendation model based on integer planning, which customize personalized balanced diet according to the limitations of food type and meal cost and other restrictions.
The Tunnel Fire Emergency Response Ontology Construction
Authors: Zhanga Wenyan , Zhang Huazhong , Hao Lin , He Yongming , Zhang Shijing
Published: December 2022

Tunnel fire emergency response is one of the most complex fire of all kinds of fire emergency response. Although the frequency of occurrence is small, once it occurs, it will seriously threaten the life and property safety of the surrounding people and road traffic. T-FERO ontology model for tunnel fire emergency response is constructed based on typical tunnel fire emergency response texts in China and abroad. We choose Protege as the realization tool of tunnel fire emergency ontology. Through the construction of upper ontology based on the guidance of domain experts, we built a quintuple including highway tunnel, tunnel auxiliary equipment, passing vehicles, safety passage and other elements, and then the constructed emergency ontology of tunnel fire emergency response stage is evaluated through a group of examples.
Numerical Calculation of Fluid-Solid-Thermal Coupling Based on Temperature Scanning Probe
Authors: Ren Jia , Cai Jing , Dong Lei , Wang Xiaohu
Published: December 2022

To introduce a scanning probe for measuring the surface temperature of aero-engine hot end components. Numerical simulation was used to simulate the cooling and purging conditions of the reflector of the temperature scanning probe at different stances, and the flow fluid and temperature field distribution in the probe were analyzed to evaluate the protective effect of the cooling air on the probe, thus guiding the design of the temperature scanning probe. Analyzes the four kinds of cooling conditions on the mirror cooling effect., the transient analysis under different conditions of 20s time basically reach thermal equilibrium, mirror different angles to probe head has a great influence on the flow field and temperature field, the largest mirror angle 45°, due to the effect of blocking of the reflector of cooling air flow is larger, mirrors the overall temperature is higher, with minimal in the mirror when the angle is 22.5°, the cooling condition is better. The results show that the maximum temperature of the reflector is close to the maximum allowable value when the cooling air flow rate is 0.005kg/s at room temperature, which indicates that the air flow rate should not be lower than that in practice.
Numerical Simulation of Dynamic Characteristics Based on Radiation Temperature Probe
Authors: Cai Jing , Ren Jia , Zhang Xuecong , Wang Xiaohu
Published: December 2022

The paper introduced a kind of radiation temperature probe used for measuring aircraft engine components of hot end surface temperature, the probe passes through the external duct of the engine and enters the inner duct. The air coming from the fan in the external duct will have a dynamic impact force on the probe rod, causing deformation and vibration of the probe, and thus causing structural failure or reduced life on the probe. Moreover, the vibration of the engine running will be transmitted to the probe through engine, which may cause resonance and collision of the probe. Therefore, in order to verify the normal operation of the radiation temperature probe, the dynamic characteristics of the probe were analyzed by numerical simulation, and the overall structural strength and dynamic characteristics were evaluated. Through modal analysis, frequency response analysis, transient response analysis and physical field dynamics analysis results show that the dynamic strength is enough overall probe, within the scope of the engine speed frequency coverage, although there are a few order resonance frequency probe, but due to the structural strength, support and installation design is reasonable, won’t produce larger resonance.
Numerical Simulation of Performance of TLD Device with a Ribbed Baffle
Authors: Huang Zijuan , Chang Peiran , Duan Yongqiang , Li Guojun
Published: December 2022

Tuned liquid damper(TLD) has been widely used to suppress structural vibration, and its combination with elastic components has become a research hotspot. In this paper, a TLD structure with a ribbed baffle is proposed, and the vibration damping performance of the normal baffle and the ribbed baffle has been compared when using rigid material and elastic material, respectively. The partitioned solution of fluid-structure interaction method is used to numerically simulate the horizontal vibration attenuation process of five TLD devices, which proves the superiority of vibration damping performance of ribbed baffles when using elastic materials. The vorticity contour of the two structures with different baffles when using elastic materials is compared, which confirms the superiority of the vibration damping effect of the structure with ribbed baffle.
Simulation Research on Back Flushing Time of High Pressure Back Flushing Filter Station
Authors: Jia Chunqiang , Sun Bin , Li Han , Yu Ling
Published: December 2022

The hydraulic support system in fully mechanized face is huge and complex, working environment is special, so emulsified pollution is an outstanding problem, which influences the performance and efficiency of the hydraulic support system, high pressure back flushing filter station is an important emulsion cleaning equipment in the system. The pollution control model is constructed, pollution equilibrium equations are derived for high pressure emulsion back flushing filter station in ore. Flow division coefficient and back flushing efficiency are introduced for back flushing time simulation research, that indicate the parameters influence relation for back flushing time, at last accuracy and feasibility of the pollution control simulation model is discussed by the comparison analysis of experimental and simulation results, the higher the back flushing efficiency is, the higher the flow division coefficient is, the shorter the back flushing time is, and the higher the cost is, the back flushing model based on pollution control is effective that provides a theoretical criterion for the optimal design of high pressure back flushing filter station.
Approximation of Broad Learning System and Convolution Function Applied on Face Classification
Authors: Nan Dong , Li Zhengying , Diao Luhong
Published: December 2022

Broad Learning System (BLS) is a very fast and effective discriminative learning which is developed by C. L. P. Chen, Z. Liu and others. It avoids the shortcomings of complex model design and large amount of calculation in deep learning. This paper studies the approximation capability of BLS for continuous functions defined on a compact set. It is proved that if the activation function of the enhancement node of BLS is not polynomial, for any continuous function f(x)∈C(K) defined on the compact set K, there is limmq→ ∞,nk→ ∞‖f(x)-fw(x)‖22=0, that is ∀ ε>0, ∃nk ∈ N, mq∈N’, and parameter set w, so that ‖f(x)-fw(x)‖22<ε. A reconstructed model of BLS which is combined the CNN network with the BLS is applied to numerical experiments. The semi-supervised broad learning system(SS-BLS) and its algorithm are proposed. Then, SS-BLS and convolution function are combined to establish SS-CBLS, the numerical experiments of SS-CBLS on face classification are carried out by ORL and Yale face database respectively
Real Power Loss Reduction by Choosing Certain Parameters to Modernize – Grounded Algorithm
Authors: Lenin Kanagasabai
Published: December 2022

In this paper choosing certain parameters to Modernize – Grounded Algorithm (CCM) is sculpted for untying loss descendant problem. The procedure of modernizing populace associates in the projected CCM observes to double values. The chief norm is that certain associates of the populace might be in a condition wherever if lone standards of certain parameters alter, they determined to be in an improved location as a substitute of altering all of the parameters. Consequently, in the projected CCM, the quantity of parameters nominated for the modernization procedure is fixed in iterations. The next standard is to stop the algorithm populace modernize procedure from depend on precise associates. Depend on procedure modernization to explicit associates of the populace influence the procedure to congregate in the direction of the local optimal solution and avert precise perusing of the examination region to achieve the universal optimal solution. Stoutness of the Choosing certain parameters to Modernize – Grounded Algorithm (CCM) corroborated in IEEE 30 bus test system. Diminution of loss has been accomplished.
Evaluation and Optimization Method of Enterprise Data System Based on FAHP-CEEMDAN
Authors: Tao Heng , Wan Jialin , Zhao Kan , Zhou Wenting , Yao Chengzhi , Zhang Qinke
Published: December 2022

In order to help enterprises obtain greater data analysis advantages and optimize enterprise data system, this paper proposes a data evaluation optimization model. The model uses the index weight analysis method, empirical mode decomposition algorithm by improving the collection, calculation of expert judgment weight of the signal as the data system of subjective evaluation weight value, and through the fuzzy measurement analysis method, the weight is compared with the weight of the actual data system of the enterprise, calculate the maturity of the system and reflect the current state of the data system, so as to analyze and optimize the data system and reflect the competitive advantage and data value of the enterprise The experimental results show that the data analysis model is objective and effective, which is of great help to enterprise data system optimization.
Research on the Protection and Inheritance of Intangible Cultural Heritage Based on Digital Technology
Authors: Guo Lifang , Wang Junqi
Published: December 2022

In the digital age, we should not only protect and preserve intangible cultural heritage, but also reinterpret them through new methods and means, and give them new meanings. Digital enforces the inheritance and innovation of intangible cultural heritage and breaks the realistic dilemma of “restatement and light dissemination”. We advocate the construction and improvement of three-dimensional digital platform of intangible cultural heritage, scientific protection, integration and display of intangible cultural heritage projects; Building a data platform interactive system to enhance public awareness and recognition of intangible cultural heritage; Design projects and competitions related to intangible cultural heritage projects, and carry out data-oriented cultural innovation activities.
Data Analysis for Lung Cancer: Fermatean Hesitant Fuzzy Sets Approach
Authors: Kirişci Murat
Published: December 2022

The Fermatean fuzzy set concept, which was developed by merging Fermatean fuzzy sets with hesitant fuzzy sets, may be utilized in practice to ease the solution of complex multi-criteria decision-making (MCDM) issues. The idea of a Fermatean hesitant fuzzy set is introduced first, followed by the operations associated with this concept. Aggregation operations based on Fermatean hesitant fuzzy sets are provided, and their fundamental features are investigated. A novel MCDM approach obtained using operators has been developed to choose the best choice in practice. Finally, the efficiency of the recommended strategies was demonstrated using a lung cancer case study.
Modified-FWO-Algorithm for Complex “White-Box” Thermal Kinetic Model: A Case Application on Amphotericin Residue Incineration
Authors: Cui Anshun , Liu Sensen , Ge Baoxin , Xu Chang , Cao Qi , Li Jie , Zhang Dalei , Qi Yuanfeng
Published: December 2022

A Modified-FWO-Algorithm was proposed to modify the drawbacks of the traditional FWO-Algorithm throughout the construction of incineration kinetics model for complex pollutants. And the implementation process of this algorithm was introduced via the construction of amphotericin residue incineration kinetic model. The results indicate that two stages emerged in TG/DTG analysis of amphotericin residue, and reactions related to those stages are both multi-step reaction. “White-Box” incineration kinetic model established on Modified-FWO-Algorithm possessed the lowest RMSE value was 0.43%. Data reproducibility of the model derived Modified-FWO-Algorithm was 24.54 times higher than established by FWO-Algorithm.
An Entity Relationship Extraction Model Based on BERT-BLSTM-CRF Algorithm for Cosmetics Domain
Authors: Zuo Min , Ge Wei , Dong Wei , Zhang QingChuan
Published: December 2022

In view of the lack of timeliness in the regulation of the cosmetics field, we establish a model for extracting the relationship between entities in the cosmetics field, assist the relevant departments in building an intelligent regulatory system, and rely on data to achieve scientific decision-making and effective regulation. In this paper, we use the BERT (Bidirectional Encoder Representations from Transformers) network model to train the word vectors, and combine the BLSTM (bidirectional long short-term memory) network with the fused positional attention mechanism to perform entity relationship extraction, and the extracted relationship features extracted by the BERT neural network are incorporated into the word dimension text vector, and then the entity pairs are extracted by the BLSTM with the fused positional attention mechanism, and finally the predicted labels are decoded by CRF (Conditional Random Field). The experimental results show that the BERT-BLSTM-CRF-based entity relationship extraction model in cosmetics domain constructed in this paper exhibits good feature extraction and classification performance.
Research on Simulation Experimental Platform Under New Power System
Authors: Li Qingsheng , Long Jiahuan , Li Zhen , Yang Shunji , Xu Ying
Published: December 2022

According to the development trend of electric frontier field and the requirement for construction of new engineering, the construction and application of simulation experimental platform under new electric system are studied. The construction scheme of new engineering experimental platform of electric system, which takes the real-time simulator of electric information as the core, is put forward to connect all links of demand analysis, system design, mirror simulation and product definition, train and cultivate the students’ ability of project development, and organize the fragmented knowledge of multiple courses. The whole process of model building, off-line simulation, real-time simulation and semi physical simulation is studied based on the teaching case of smart micro-grid project. It is proved in the teaching practice that the platform can support the experimental teaching mode of new engineering, which is of great significance to cultivate students’ large engineering view, engineering thinking and innovative quality, and is a beneficial exploration for the construction of new electric engineering under the background of new power system.
A Multi-Objective Portfolio Model and Its Solution
Authors: Yang Jiale , Li Xiang , He Chunyan , Zhu Yuetong , Bao Anna
Published: December 2022

For the investment portfolio problem in the securities market, the log return rate function and the semi-absolute deviation risk function are used to obtain the expected return rate and risk of the securities, and the multi-target portfolio model comprehensively considering the investment return, risk and liquidity is established. A dimensional adjustment coefficient is weighted linear combined according to the investor preference coefficient, that is, the multi-target planning model is transformed into a single-target planning model. Finally, the effectiveness and rationality of the method are explained.
Food Enterprises’ Profit Growth Rate Prediction Based on LSTM from the Perspective of the Supply Chain
Authors: Zuo Min , Wang Yili , Yan Wenjing , Zhang Qingchuan
Published: December 2022

Food is the fundamental guarantee of people’s lives, and the food industry has always occupied an essential position in the national economy. Profit growth rate, as a measure of an enterprise’s development ability, can intuitively reflect the change in operating profit for food enterprises. The accurate prediction of profit growth rate can provide a decision-making reference for enterprises in planning business objectives in the next stage. However, many factors affect the profit variation of a company, and it is hard to make accurate predictions using traditional statistical economics forecasting methods. Since the Long-Short Term Memory (LSTM) model can capture nonlinear relationships in time series analysis, we propose an LSTM-based model to predict the profit growth rate of enterprises by using the operational data of four seasons ahead. Moreover, due to the COVID-19 pandemic, the impact of supply chain integrity on enterprise operations is increasing. We introduce the information of the supply chain owned by the enterprise to predict the profit growth rate of the enterprise. The result of our model exhibits high prediction accuracy, which indicates that our model could provide practical guidance for companies’ production and operation activities.
Structure Design and Simulation Analysis of Portable Movable-Type Chinese Teaching Aids
Authors: Wang Chao , Zhang Changyuan , Gao Fei , Lv Hang , Zhang Peng
Published: December 2022

With the improvement of China’s economy and international status, more and more people begin to study Chinese. Aiming at learning Chinese as a foreign language at HSK1-3 level, this paper puts forward a kind of interesting and efficient teaching aid for learning Chinese as a foreign language. According to the traditional movable type printing technology combined with computer recognition technology, the use of compressible movable type block structure is more operable and enhance the interest in learning. The movable type block recognition device on the learning board presents the shape, sound, meaning, example sentences and other information of the words on the electronic screen of the learning board through sensor recognition; at the same time, each layer is designed as a foldable scissors structure, which is easy to carry. The compression fatigue life of movable type block is analyzed by ANSYS, and the structure is stable and reliable in long-term use.
Research on On-Line Monitoring System of Strength of Tripod of Mining Belt Conveyor
Authors: Zheng Dong , Wang Xingru
Published: December 2022

Aiming at the reliability of the tripod under the operating conditions of the mining belt conveyor, an on-line monitoring system for the strength of the tripod of the mining belt conveyor was designed. The system mainly includes welding strain gauges, multi-channel static stress and strain testing instruments, 4G wireless routers and analysis platform software. The static stress and strain testing instrument transmits the collected data to the monitoring computer through the 4G wireless router, and the software analysis platform on the computer performs the corresponding data processing, presents the stress value of each position of the tripod, and realizes the real-time observation and reading of the data. The online monitoring system is simple in operation, low in cost and high in accuracy, and can perfectly realize real-time monitoring and early warning of the strength of the tripod, providing corresponding guarantees for the stable operation of the mining belt conveyor.
A Deep Learning-Based Entity-Relationship Extraction Method in the Field of Electric Power Public Opinion
Authors: Zhang Qiang , Song Bochuan , Lin Jiajun , Liu Tongyang , Li Chen , Lang Xuchao
Published: December 2022

Entity-relationship extraction can obtain key information elements from texts. Electricity opinion texts have the characteristics of complex entity relationships and less annotated data, so it is difficult to find entity information with mutual relationships from text data in the field of electricity opinion. To solve the above problems, we propose the ABAC (ALBERT-BiLSTM-ATT-CRF) model to extract entity relationships in electric power opinion texts. By using the pre-training model of ALBERT and combining the five-stroke sequence, radicals and pinyin of Chinese characters to extract features, and the features of these parts are fused to enhance the ability of extracting text feature vectors. The experimental results show that the accuracy of entity-relationship extraction has been significantly improved, which verifies the effectiveness of the model designed in this paper for entity-relationship extraction in the field of electric power public opinion.
Legendre Polynomial Approach for Multimodal Analysis of the Transverse-Type Rectangular Piezoelectric Transformer with Common Ground Electrodes
Authors: Randrianarivelo Joli , Ratolojanahary Faniry Emilson , Rguiti Mohamed , Falimiaramanana Derandraibe Jeannot
Published: December 2022

A Legendre polynomial approach (PA) is proposed to forecast a thin film of transverse-type rectangular piezoelectric transformer (PT) performance with common ground electrodes located on its whole bottom surface, fabricated from a PZT5A (lead zirconate titanate) ceramic material. Based on the automatic incorporation of boundary conditions into the equations of motion and the development on a basis of orthonormal polynomials of the fields, formulations calculated analytically are simulated numerically. Then, series and parallel resonance frequencies, profiles of the mechanical displacement and the electrical potential are obtained for the PT. Our results are validated through a comparison with the three-dimensional Finite Element Method (FEM) ones. Furthermore, the mechanical tethers positions are located at the PT’s junctions.
Research on Multi-Target Detection and Tracking Algorithm Based on Improved YOLOv5
Authors: Zhou Qian , Sun Fuxin , Zhang Junyou
Published: December 2022

A detection and tracking algorithm based on improved YOLOv5 is proposed for the poor recognition and tracking of obscured targets and small-sized targets. The K-means ++ algorithm is used to cluster to obtain new anchor values; the CIOU-NMS is introduced to improve the missed detection problem when the target is obscured; the CBAM is proposed to be embedded into the Backbone and Neck part to improve the feature extraction capability of the algorithm for small targets. DeepSORT is chosen as the multi-target tracker to plot the motion trajectory of the target in real time. The experimental results show that the improved algorithm has a 2.1% improvement in detection accuracy and a detection speed of 32.32/s, satisfying real-time efficient detection with better tracking.
Numerical Study of the Propagating Properties of a Laser-Generated Surface Acoustic Wave Interacting with a Bracket Structure
Authors: Li Ziming
Published: December 2022

Shield tunneling machines are widely used around the world for construction in tunnels, railways, and subways. The bracket of a shield tunneling machine, which is welded to the cutterhead, is prone to suffer maximum stress due to its bad operating environment. This paper introduces a laser-generated surface acoustic wave for non-destructive detection. A numerical model is constructed to analyze the interaction between a laser-generated surface acoustic wave and a bracket structure. The results show that the laser-generated acoustic wave with a longitudinal wave, a shear wave, and a Rayleigh wave can propagate along the surface of the bracket structure. When the wave encounters the junction of the welding and the horizontal surface, it generates a reflected wave, a transmitted wave, and a mode converted wave. This propagating phenomenon can be used for the defect detection of a bracket in the future.
Evaluation of Motivation Factors of Social Work Organizations with Neuro-Fuzzy Inference System
Authors: Qi Li , Zhao Lanlan , Fu Yue , Liu Zhi , Li Xingchun
Published: December 2022

The incentive mechanism in social institutions is not perfect, and the loss of employees is serious. However, inspiring employees is quite a complex task. According to the internal contract theory in modern human resource management, incentive strategies based on work value orientation can avoid role confusion and conflict of interest caused by value mismatch. In order to solve the above problems, the employee incentive mechanism under the work value orientation is studied, and the model is established using a neuro-fuzzy inference system to realize the quantitative analysis and performance of motivation factors under the work value orientation. The neuro-fuzzy inference system autonomously extracts fuzzy rules from the original data, sets the membership function parameters, and the fuzzy inference system completes the fuzzy information processing and judgment and decision-making functions. It can consider the impact of the combination of different incentive factors on the performance of social workers. And can achieve rapid quantitative evaluation of job performance.
An Empirical Study on the Knowledge Structure and Hotspot Mapping of Reverse Innovation Based on VOSviewer Software and Big Data
Authors: Li Hongyan
Published: December 2022

From the aspects of annual publications, journals and cited literatures, this paper uses content analysis and bibliometric analysis to study the papers on reverse innovation collected in Web of Scienc database from 2008 to 2020. Based on VOSviewer software and Big data, this paper research data processing and data visualization aiming at reverse innovation, summarizes the development status of reverse innovation research in foreign countries, and puts forward suggestions for further development of reverse innovation research in Chinese management research from two aspects of multi-factor scenario application and main role switch.
Research on Dynamic Path Planning of Theme Park Based on Improved Genetic Algorithm
Authors: Zhang Jialin , Qu Xingke , Li Lei , Zhang Yueyang
Published: December 2022

Aiming at the current queuing problem in large theme parks and the insufficient utilization of facilities, a dynamic virtual queuing model is proposed, which can recommend the most time-saving tour route for visitors based on each visitor’s interest points and combined with the real-time dynamic changes of crowd flow in each facility. An improved data structure is proposed to transform the Dynamic Travelling Salesman Problem into Travelling Salesman Problem; the traditional genetic algorithm is also improved by proposing the Optimal Replication Method to optimally adjust the population before the selection operation, and the Parent-Child Competition Method is introduced in crossover and mutation to guarantee that the evolutionary process always proceeds in a beneficial direction. The improved data structure greatly improves the efficiency of the algorithm; the improved genetic algorithm can achieve convergence faster and find a better tour route in a faster time, thus improving the visitor experience.
Modeling the Dynamics of the Decomposed Ulva Prolifera Biotoxicity with Luminous Bacteria Method
Authors: Zhou Ruijia , Yu Qingyun , Li Juan , Wang Chunhui , Wen Ruobing , Xu Zhaodong , Zhao Shen
Published: December 2022

The “green tide” occurred frequently, however, their biotoxicity information is relatively scarce. In this study, we used luminescent bacteria test based on Vibrio fischeri (NRRL b-11177) to detect the biotoxicity of Enteromorpha prolifera in decomposition process. We added different biomasses of Enteromorpha prolifera to the same volume of seawater to simulate decomposition process. The biotoxicity was detected regularly. The comparative analysis showed that luminescent bacteria had high sensitivity to the biotoxicity in Enteromorpha prolifera decomposition. And the change of biotoxicity was closely related to the biomass of Enteromorpha prolifera. The more Enteromorpha prolifera added, the sample showed greater biotoxicity, got the grade III earlier and continued longer. Group E (32g/L) reached grade III on the 9th day of the experiment, and the number of days of grade III accounted for 95%. The decomposition of high concentration Enteromorpha prolifera produced obvious biotoxicity, and subsided slowly. Therefore, the area where “green tide” occured should cleanup in time to prevent the damage of the local ecological environment.
New Possibility Soft Sets with Gender Equality Application in Early Childhood Children
Authors: Kirişci Murat , Bardak Musa , Topaç Nihat
Published: December 2022

In this study, we introduce the theory of possibility Fermatean fuzzy soft set and describe various associated operations, such as complement, union, intersection, AND, and OR. Then, for dealing with decision issues, a similarity measure is devised to compare two possiblity Fermatean fuzzy soft sets. Finally, a practical example with respect to gender equality in early childhood children is given to demonstrate the applicability of this similarity measure in decision-making situations.
Reduced Order Modelling and Control of Induction Motor with Chaos-Based Gorilla Troop Optimizers (CBGTO)
Authors: Ganguli Souvik
Published: December 2022

This paper proposes 50 new chaos-based gorilla troop optimizers (CBGTO). It is possible to change two regulating parameters in the parent algorithm by using various one-dimensional chaotic maps. Along with these two controlling variables, one of the random variables is also changed in order. Ten well-known and widely used chaotic maps are used to create chaotic algorithms. An induction motor model of order five is used to evaluate the performance of the suggested method. In addition, the same approach is used to build an intelligent PID controller. By using the delta operator, the induction motor model is made simpler. The applicability of the findings is confirmed by statistical analyses of the optimised values, in this example, the integral of time-weighted absolute error (ITAE). Results for the test system under consideration, a 50 hp induction motor, are remarkably positive. Additional parameter changes could be done in the future to boost the functionality of the gorilla troop optimizer (GTO). The PID controller is put into action using a framework for approximate model matching. The novel methods outperform the existing standard and state-of-the-art methods in terms of convergence speed and accuracy.
Impact of photodynamic therapy on the marginal adaptation of Biodentine used as root-end filling material
Authors: Dimitrova Ivanka , Kouzmanova Yaneta
Published: December 2022

BACKGROUND: The marginal adaptation of root-end filling materials and the effective antibacterial control in a surgical site are crucial for the successful outcome of endodontic surgery. OBJECTIVE: This study aimed to evaluate the effect of retrograde application of photodynamic therapy on the marginal adaptation of Biodentine used as a root-end filling material. METHODS: Twenty single-rooted anterior teeth were selected, instrumented and obturated with gutta-percha and AH Plus. The apical 3 mm of the roots were resected and root-end cavities were prepared with an ultrasonic retro-tip. The teeth were randomly divided into two groups (n = 10). In the first group, photodynamic therapy (PDT) was applied in the retrograde cavity prior to the root-end filling. In the second group retro cavity was filled without PDT. All specimens were obturated with Biodentine and afterwards sectioned longitudinally. The gap width at the material-dentin interface was measured using a scanning electron microscope. The results were statistically analyzed. RESULTS: The produced gap width by Biodentine/PDT was 3.85 μm versus 2.68 μm in the Biodentine control group with significant differences in-between. CONCLUSION: Under the conditions of this study, PDT has a negative effect on the marginal adaptation of Biodentine used as root-end filling material.
Linking Appellate Judgments to Tribunal Judgments – Benchmarking Different ML Techniques
Authors: Condevaux Charles , Mathis Bruno , Mahmoudi Sid Ali , Mussard Stéphane , Zambrano Guillaume
Published: December 2022

The typical judicial pathway is made of a judgment by a tribunal followed by a decision of an appellate court. However, the link between both documents is sometimes difficult to establish because of missing, incorrect or badly formatted references, pseudonymization, or poor drafting specific to each jurisdiction. This paper first shows that it is possible to link court decisions related to the same case although they are from different jurisdictions using manual rules. The use of deep learning afterwards significantly reduces the error rate in this task. The experiments are conducted between the Commercial Court of Paris and Appellate Courts.
Toward Automatically Identifying Legally Relevant Factors
Authors: Gray Morgan , Savelka Jaromir , Oliver Wesley , Ashley Kevin
Published: December 2022

In making legal decisions, courts apply relevant law to facts. While the law typically changes slowly over time, facts vary from case to case. Nevertheless, underlying patterns of fact may emerge. This research focuses on underlying fact patterns commonly present in cases where motorists are stopped for a traffic violation and subsequently detained while a police officer conducts a canine sniff of the vehicle for drugs. We present a set of underlying patterns of fact, that is, factors of suspicion, that police and courts apply in determining reasonable suspicion. We demonstrate how these fact patterns can be identified and annotated in legal cases and how these annotations can be employed to fine-tune a transformer model to identify the factors in previously unseen legal opinions.
Investigating Strategies for Clause Recommendation
Authors: Joshi Sagar , Balaji Sumanth , Thomas Jerrin , Garimella Aparna , Varma Vasudeva
Published: December 2022

Clause recommendation is the problem of recommending a clause to a legal contract, given the context of the contract in question and the clause type to which the clause should belong. With not much prior work being done toward the generation of legal contracts, this problem was proposed as a first step toward the bigger problem of contract generation. As an open-ended text generation problem, the distinguishing characteristics of this problem lie in the nature of legal language as a sublanguage and the considerable similarity of textual content within the clauses of a specific type. This similarity aspect in legal clauses drives us to investigate the importance of similar contracts’ representation for recommending clauses. In our work, we experiment with generating clauses for 15 commonly occurring clause types in contracts expanding upon the previous work on this problem and analyzing clause recommendations in varying settings using information derived from similar contracts.
A Compression and Simulation-Based Approach to Fraud Discovery
Authors: Fratrič Peter , Sileno Giovanni , van Engers Tom , Klous Sander
Published: December 2022

With the uptake of digital services in public and private sectors, the formalization of laws is attracting increasing attention. Yet, non-compliant fraudulent behaviours (money laundering, tax evasion, etc.)—practical realizations of violations of law—remain very difficult to formalize, as one does not know the exact formal rules that define such violations. The present work introduces a methodological framework aiming to discover non-compliance through compressed representations of behaviour, considering a fraudulent agent that explores via simulation the space of possible non-compliant behaviours in a given social domain. The framework is founded on a combination of utility maximization and active learning. We illustrate its application on a simple social domain. The results are promising, and seemingly reduce the gap on fundamental questions in AI and Law, although this comes at the cost of developing complex models of the simulation environment, and sophisticated reasoning models of the fraudulent agent.
Autosuggestion of Relevant Cases and Statutes
Authors: Pandian Saran , Joshi Shubham
Published: December 2022

In this paper, we describe a method to help legal practitioners in citing the relevant case laws and statute laws for the specified legal issue. In this method, we consider the cited case and statute law as single tokens where we try to find the relevant tokens based on the words around these tokens. We observed that context-based representations outperformed lexical-based representations and distributional representations. Also, we observed that the method works better for statute law retrieval compared to case law retrieval.
Extracting References from German Legal Texts Using Named Entity Recognition1
Authors: Peikert Silvio , Birle Celia , Al Qundus Jamal , Vu Le Duyen Sandra , Paschke Adrian
Published: December 2022

Information extraction tasks are particularly challenging in specific contexts such as the legal domain. In this paper, Named Entity Recognition is used to make legal texts more accessible to domain experts and laymen. This paper focuses on extracting law references and citations of court decisions, which occur in various syntactic formats. To investigate this task a reference data set is constructed from a large collection of German court decisions and different NER-techniques are compared. Pattern matching, probabilistic sequence labeling (CRF), Deep Learning (BiLSTM) and transfer learning using a pretrained language model (BERT) are applied to extract references to laws and court decisions. The results show that the BERT based approach achieves F1 scores around 0.98 for both tasks and outperforms methods from prior work, which achieve F1 scores of 0.89 (CRF for law references) respectively 0.82 (CRF for court decisions) on the same data set.
An End-to-End Pipeline from Law Text to Logical Formulas
Authors: Ranta Aarne , Listenmaa Inari , Soh Jerrold , Wong Meng Weng
Published: December 2022

We propose a pipeline for converting natural English law texts into logical formulas via a series of structural representations. Text texts are first parsed using a formal grammar derived from light-weight annotations. An intermediate representation called assembly logic is then used for logical interpretation and supports translations to different back-end logics and visualisations. The approach, while rule-based and explainable, is also robust: it can deliver useful results from day one, but allows subsequent refinements and variations.