bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Data Extraction of Tibetan Dance Movements Based on Different Convolution Models
Authors: Zhang Lijun , Dong Jianmin , Ye Kai , Liu Jianxin
Published: August 2021

In order to strengthen the in-depth integration between culture and technology, and provide a certain theoretical basis for the improvement of the digital system of Tibetan dance and the innovation of Tibetan dance teaching, a new research method was proposed : based on high-definition Tibetan dance video data, we used OpenPose to extract the dancer's skeleton joint point data, and the five characteristics of Tibetan dance: "open", "tremor", "left", "round", "shun" and other characteristic movements were summarized. In the feature extraction stage, we tried different convolution methods to compare the extraction results. In the end, we extracted the dancer's bone point data more completely, deeply digitized the movement characteristics of Tibetan dance through digital technology. The experimental results show that the numerical feature rules of the five major characteristics are highly consistent with the dancer's performance analysis characteristics, which proves that the extraction and analysis method given is feasible.
Impulse Ground Pressure Prediction Based on Rough Set- Distance Discriminant Model
Authors: Ping Jian
Published: August 2021

In this paper, introduce the rough set theory, and the weight coefficient is calculated by analyzing the support degree and attribute importance of the evaluation object. Combine with the distance discriminant model, successfully construct the weighted distance discriminant model of rock burst, and determine the reasonable discriminant factors. Taking 15groups of data from Yantai Coal Mine as training samples, and establish the rough set distance discriminant model for rock burst prediction. The discriminant results of this model were compared with those obtained by Fisher analysis discriminant model (FDA), R-type factor Fisher discriminator method, etc. Through the comparison of the judgment results, prove the effectiveness of the through-distinction model in the field of mine water source discrimination. The results show that the through set distance discrimination model has the advantages of high prediction jurisdiction and strong rationality, and it is a new way suitable for mine water source discrimination.
Performance Analysis of FISSER Model in Rural-Urban Cognitive Radio Networks
Authors: Oki Olukayode , Olwal Thomas , Adigun Matthew
Published: August 2021

In the past few decades, Cognitive Radio network (CRN) has been regarded in the literature as the most promising technology for performing dynamic spectrum management. One of the major aspects of spectrum management is referred to as the spectrum-reconfiguration decision-making ability of CR users. Dynamic spectrum reconfiguration has previously been reported to improve the spectrum utilisation in CRN. In exploiting spectrum reconfiguration to improve spectrum utilisation, various approaches have been adopted to develop models. However, none of these research works has been evaluated in the urban and rural settlement context. In a CRN environment, the frequency availability is not static like that of traditional networks. There are resource-rich regions such as in rural areas, where many frequencies are available for the Secondary Users (SUs) and resource-poor regions such as urban areas, where there are only a few frequencies available for SUs. Hence, this paper proposed a novel Foraging Inspired Spectrum Selection and Reconfiguration (FISSER) model. The performance of the FISSER model has been analysed through computer simulations both in the rural and urban CRN, using high and low perceptual radii. A high perceptual radius has been shown in the literature to improve energy efficiency and data communication performance in ad hoc networks. However, the simulation results reported in this paper show that even though the high perceptual radius improves the nodes’ energy efficiency it does not achieve optimal data communication performance compared to when the nodes use a low perceptual radius. Also, the efficacy of FISSER model was tested by comparing it against the reinforcement learning model. Based on the obtained results, it was shown that the FISSER model achieved better results in both the network throughput and the channel switching time.
Sequential Emotion-Aware Recommendation: A Preliminary Study on Data Acquisition and Modeling
Authors: Chen Weihao , Zheng Lin , Jiang Dazhi
Published: August 2021

The rapid development of recommender systems makes researchers pay more and more attention to the utilization of users’ subjective factors. Among various subjective factors, emotion plays an important role that can truly reflect the temporal changes of users’ preferences. However, the acquisition of user emotion is difficult, and is obtained passively in many methods. Moreover, there are few datasets suitable for continuous emotion modeling in existing recommendation research. To address these shortcomings, this work collects and organizes a dataset of users watching movies containing their temporal emotional data, which is appropriate for recommendation tasks based on sequential emotions. In addition, we propose a sequential emotion-aware recommendation method suitable for continuous emotion modeling, which outperforms other advanced sequential modeling approaches on our dataset. The contribution of this work is to conduct preliminary study and exploration on the modeling of users’ sequential emotion, so that this research direction can be further developed in future. The Sequential EMotion-Aware Recommendation (SEMAR) dataset we collected is available at: https://github.com/LinZheng666/Sequential-Emotion-Dataset-for-Recommendation.
A Prediction Method Based on Extreme Gradient Boosting Tree Model and its Application
Authors: Lao Yongchang , Qi Fangzhong , Zhou Jiakai , Fang Xiaobao
Published: August 2021

Improving the accuracy of financing risk prediction is of great significance to the healthy development of grid enterprises. Taking a provincial-level power grid company as the research object, the financing risk index system is constructed by considering multiple dimensions, and the monthly financing risk index RI of power grid enterprises from 2015-2018 is determined based on entropy weight and comprehensive index method, while the financing risk prediction model is constructed with the help of extreme gradient boosting tree model. The empirical results show that compared with support vector regression and BP neural network models, the financing risk prediction model constructed based on the extreme gradient boosting model has an excellent performance in terms of prediction accuracy and stability.
Computational Efficiency of Three Programming Languages in N-body Simulation
Authors: Pan Junnan , Li Zhongmu
Published: August 2021

The computational efficiency of FORTRAN, C and Python languages in N-body simulation is investigated. The potential of these languages to promote the research of N-body simulation is therefore shown by this paper. Our work utilizes Particle-Particle (PP) algorithm, which not only balances the accuracy and efficiency, but also simplifies the traditional numerical calculation. The experimental results show that the computational efficiency of the three is almost the same in the case of a small number of particles, but FORTRAN shows the highest computational efficiency in the case of a large number of particles. The efficiency of Python is the lowest among three languages. The result suggests that FORTRAN is the best choice for N-body simulation, and Python should be used after optimizing the algorithm or working on extreme high-performance computers.
Simulation Analysis of Cam Wear in Shedding Mechanism of Loom
Authors: Dai Xin , Li Jing
Published: August 2021

Aiming at the serious wear of the cam surface in the shedding mechanism of the loom weaving, which is likely to cause uneven movement of the heald frame, this paper proposes to add a layer of copper-plated carbon fiber composite material to the cam surface to improve the cam wear during the operation of the shedding mechanism. In finite element ABAQUS®, the cam is modeled, material properties and boundary loads are set, and ALE adaptive mesh technology and Umeshmotion subroutine are also used for wear analysis. The simulation results show that under the same conditions, the wear between the cam and the roller with a copper-plated carbon fiber layer is much smaller than the wear between the pure metal cam and the roller.
Influence of Fluid Effect on Virtual Simulation of Otolith Movement
Authors: Kong Lingyi , Wu Jun , Feng Mingjie , Liu Zhaobang , Yang Xiaoguo
Published: August 2021

More and more physics engines are used to simulate the dynamics between two rigid bodies. However, it is still unknown whether physics engine is suitable for computing the physical information of objects with fluid effect, such as the trajectory and collision dynamics of otolith in semicircular canal in benign paroxysmal postural vertigo (BPPV). The purpose of this study is to determine whether the fluid effect in Bullet physics engine has an impact on the movement data of otoliths in semicircular canal. Based on the experimental data obtained previously, we discuss the position and trajectory of the otolith when it falls in the Dix-Hallpike test. Root Mean Square Error (RMSE) is used to evaluate the static position of otolith under two conditions, and the RMSE is 0.716. We found that the initial position of otolith is affected by fluid effects, but the final static position and trajectory of otolith is similar (x=-5.838±0.294, y=19.348±0.143, z=-9.540±0.635). The experimental results show that the fluid effect does not affect the experimental results of the Dix-Hallpike test, and it has sufficient applicability for the evaluation of BPPV diagnostic methods.
The Comfort Simulation of Double-wheel Intelligent Vehicles Considering Human Bodys
Authors: Gao Zhendong , Chen Xin , Hou Jing , Lin Zhangxi , Lv Shunya , Hong Bin
Published: August 2021

In this paper, aiming at the self-developed double-wheel intelligent vehicle, a comfort simulation considering the human two-DOF (degree-of-freedom) model was conducted. Based on the analysis of the human body response to the vibration, the dynamic model of vehicle random vibration is used to establish a five-DOF human-seating-road ride dynamic model combined with MATLAB/Simulink software. Through the simulation of the road comfort test under the excitation of filtered white noise, the ride comfort analysis of the intelligent vehicle was realized.
Research on Detection Method for Welding Seam Defects in Ultrasonic TOFD Image Based on Mask R-CNN
Authors: Wang Yimin , Cao Yongbei , Ye Birun , Zhang Huidi , Fu Yadi
Published: August 2021

In this paper, the technology of ultrasonic TOFD was used in the welding seam inspection of construction steel structure. 162 ultrasonic TOFD scanning images including five kinds of common defects were obtained through field test. The five kinds of common welding defects include stoma, slag inclusion, lack of fusion, incomplete penetration and crackle. Combined with artificial intelligence image recognition technology, an automatic detection algorithm of welding seam defects in ultrasonic TOFD scanning images based on Mask R-CNN was developed. By comparing the effects of automatic location and classification of welding seam defects based on Mask R-CNN after the same number of iterative training under different parameter configurations, the results show that Mask R-CNN can automatically locate and classify welding seam defects and the recognition effect is the best when epoch is 667, steps_per_epoch is 15 and learning rate is 0.001. Under this parameter configuration, the recognition and classification of five kinds of common defects such as stoma, slag inclusion, lack of fusion, incomplete penetration and crackle are correct. The correct recognition confidence of all five kinds of defects can reach more than 0.9, and the location is precise.
Application of Fuzzy Extension Analytic Hierarchy Process in Location Selection of Logistics Center
Authors: Yu He , Wang Nana , Pan Jiaqi
Published: August 2021

This paper use fuzzy extension analytic method to solve the problem of location selection of logistics center. First, establish an evaluation system. There are three first-level indicators at the criterion level, which are social benefits, economic benefits, and infrastructure, and nine second-level indicators at the sub-criteria level. The extension analytic method is used to compare all the factors corresponding to the layer to the first factor and use the number of extension intervals to compare them in pairs, so as to construct a judgment matrix for the extension interval and find the weight vector. Further hierarchical ranking is performed. Secondly, the fuzzy comprehensive evaluation method is used to determine the factor set and evaluation set of influencing factors, and the evaluation matrix is established. The primary element is used to determine the evaluation model. First-level evaluation is performed on each logistics center to obtain a second-level evaluation matrix. The model comprehensively evaluates the two-level evaluation matrix, and then ranks the evaluation levels of each which introduces extension theory, considers human ambiguity, uses interval numbers instead of specific numbers to construct a judgment matrix. The example proves that the ranking is more practical and provides a theoretical basis for site selection.
TCPW-F: A Congestion Control Algorithm Based on Noise-aware in Wireless Networks
Authors: Zhao Fei , Jiang Yufei , Wang Yaming , Tang Junyong
Published: August 2021

Due to the wireless link with more noise packet loss and higher latency as compared with the wired link, conventional TCP Westwood (TCPW) variants over wireless channels perform unsatisfactorily when competing for the shared capacity of the bottleneck link with other variants. The shortcoming is these variants mistakenly interpret noise packet loss as a congestion signal. This leads to frequent delay jitter and long latency due to the inability to distinguish the type of packet loss, which reduces the transmission efficiency of the network. Therefore, we propose a novel TCP variant (TCPW-F) that distinguishes noise loss and congestion loss. By constructing the congestion factor F, the real-time available bandwidth can be calculated. When receiving congestion signals, it ignores the false of them induced by noise packet loss upon the wireless link but responds to true congestion according to backlog-constrained-based judgment. Therefore, TCPW-F is widely used in wireless networks with large noise interference. Numerical analysis and simulation results show that TCPW-F resists noise interference, and smooths the delay jitter per unit time. And the throughput of TCPW-F is significantly higher than other TCPW variants. TCPW-F improves the transmission performance in wireless networks.
A Heuristic Algorithm to Compute a Subgraph for TSP Based on Frequency Quadrilaterals
Authors: Deng Qirong , Wang Yong , Chen Liping
Published: August 2021

A heuristic algorithm was presented to compute certain subgraphs for symmetric traveling salesman problem using frequency quadrilaterals. If we choose a set of frequency quadrilaterals containing an edge to compute the frequency for it, the frequency of an edge contained within the optimal Hamiltonian cycle approaches an extreme value as the city number is big enough. A heuristic algorithm was designed to compute a frequency graph with randomly selected frequency quadrilaterals. A subgraph containing the optimal solution was computed according to a given frequency threshold. The experimental results illustrated that in certain instances for Euclidean TSP with scale above 1000, the number of edges in complete graph is reduced by more than 30 times. Moreover, the bigger the number of frequency quadrilaterals is used, the higher the frequency threshold is and the smaller the number of edges in the subgraphs is kept.
Product-assisted Optimization Method Based on Fault and Patent Knowledge Extraction
Authors: Liu Haiyan , Zhan Hongfei , Yu Junhe , Wang Rui
Published: August 2021

With the shortening of product life cycles, accelerating the efficiency of product optimization is crucial for companies. For this reason, a method for optimizing the design of auxiliary products with product maintenance data and patent information as the core is proposed. In this method, the text mining technology is used to extract the product maintenance knowledge hidden in the maintenance records, establish a product failure demand matrix to analyse the technical maturity of related fields. According to the patented technology efficacy information, a product knowledge service model for optimization design is established based on patent knowledge and product maintenance information. This model is constructed to provide technical personnel with product optimization knowledge services, which improves the efficiency of product failure optimization and the core competitiveness of the enterprise.
Method of Indoor Navigation and Safety Improvement by SE-Dense-DQN
Authors: Zhou Jie , Zheng Xin , Chen Mengting
Published: August 2021

Since the increasing requirement of indoor navigation with the assurance of safety, Deep Learning was been used in this area by numerous scholars. In order to help unmanned aerial vehicle navigate in various environment without prior experience, this paper proposed the method of Deep Q Learning with the Squeeze-and-Excitation Networks and Dense blocks. The structure of the Q-Network also amended with the information of LIDAR processed by Long Short-Term Memory to make sure the accuracy. The structure of the network shows in figure 6. The experiment conducted in simulated environment. Experimental results indicated that this method excelled in efficiency and accuracy than other classic Deep Q Networks like classic Deep Q Network and Double Deep Q Network. The results displaying in figure 8 and figure 9 shows unmanned aerial vehicle can arrive at target place more accurately than other networks.
Design of a Reconfigurable Information Collection and Identification System for Packages Storage and Checkout
Authors: Shi Yangao , Qian Guoming , Shen Jianghao
Published: August 2021

With the continuous and rapid development of e-commerce, the requirements of logistics informatization are also increasing. At present, the barcode collection and identification device used in the operation of packages storage and checkout is generally based on ASIC chip, which is not fast enough. Therefore, this paper proposes a reconfigurable information acquisition and identification system, which is applied to the operation of package storage and delivery. This system uses FPGA + ARM architecture to realize the functions of identifying, storing and uploading the barcode information on the outer surface of the package to the host computer through UDP protocol. Because the parallel operation structure of FPGA is used to design the barcode image processing accelerator circuit, the data processing capacity of the soft core processor is reduced, and the recognition speed of the system is improved as a whole. The test shows that this system is faster and more accurate than the package barcode information recognition device based on ASIC technology.
Design of Barcode Recognition System Based on YOLOV5
Authors: Zhu Xia
Published: August 2021

In this paper, based on the research focus of the current logistics field, a deep learning based express single-side bar code extraction algorithm is designed. This algorithm can recognize the original image and read out the information of the package. The algorithm is divided into two parts: bar code localization algorithm and bar code recognition algorithm. To avoid high delay, we use the YOLOV5S network to complete the barcode localization algorithm. First, the YOLOV5S algorithm is used to frame out the barcode, and the bounding Box is cut off. Then, OpenCV's method is used to obtain the deflection Angle of the image. Finally, affine transformation is used to correct the images with deflection. The bar code recognition algorithm is to use ZBAR algorithm to decode the bar code and output the decoded content in the form of string, and finally realize the location and recognition of the bar code on the single side of the express. Finally, through the test of the data set, it can be seen from the experimental results that this paper has accomplished the goal well.
A New Filled Function for Non-smooth Global Optimization and Its Applications
Authors: Wang Weixiang , Sun Guanglei , Shang Youlin
Published: August 2021

This paper aims to discover a global optima for non-smooth optimal issues by designing a novel filled function, which, regarded as a bridge delivering one minimizer to another minimizer, contains only one parameter for easy adjustment. Theoretically, the natures of the considered filled function are conducted as well as a new algorithm is presented. Finally, certain experimental calculations are presented to illustrate the performance of the constructed algorithm.
Synthesis of Adequate Mathematical Descriptions of Dynamic Systems for the Purposes of Forecasting, Control and Diagnostics
Authors: Menshikov Yuri
Published: August 2021

The article proposes to use adequate mathematical descriptions of dynamical systems which in some cases allow making a reasonable forecast of the behaviour of real processes, control of motion and diagnostics in deterministically statement. Two criteria for the adequacy are used (quantitative and qualitative types). The possibilities of adequate mathematical descriptions are investigated if both criteria are met. Several algorithms of synthesis of such descriptions are proposed.
Uniqueness of Solutions for the Initial Value Problem of a Simple Type Riccati Equation with Variable Fractional Order
Authors: Chen Lisha , Lin Shiyou , Li Boyang
Published: August 2021

In recent years, researches on the fractional Riccati equation have attracted extensive attention, and many achievements have emerged. However, most of the current works are carried out on the basis of constant fractional order. Here we study the Cauchy problem of one simple type Riccati equation with variable fractional order. By using Gronwall-Bellman inequality and other mathematical tools, we will prove the uniqueness of solutions of this problem.
A Generalized Distance-Based Total Uncertainty Measure in Complex Evidence Theory
Authors: Huang Xiumei , Zhang Yuanping , Yang Ming , Hao Yunzhi
Published: August 2021

In this paper, a generalized total uncertainty (GTU) measure method is presented directly under the complex evidence theory framework, rather than under the probability framework. GTU is defined based on the distance between the belief interval of each singleton and the most uncertain case, which is normalized by the normalization factor. We proved the properties of GTU. There is an average evidence that represents the average acceptable environment for data from sensors. According to the GTU difference of each data and the average evidence, data from different sensors are given different weights. Each weight represents the trustworthiness of each sensor data in the fusion process, and giving a low weight to abnormal data can avoid false conclusions. The practicability and rationality of the method are verified by numerical examples and applications.
Solution of Dynamic Games of Fractional Order by the Method of Grids
Authors: Mamatov Mashrabjon
Published: August 2021

In this article, we have studied the game problem of the equation of motion, which is described with partial derivatives of fractional order in a multidimensional domain. The time derivative is defined as the partial Riemann - Liouville fractional derivatives. To solve this problem, the grid method is applied for an equation with fractional derivatives. The convergence of the scheme is established and the error estimates are obtained in terms of the sampling step. Sufficient conditions are found close to each other for the completion of the pursuit. A method of controlling the pursuing player is constructed according to the feedback principle, which guarantees the desired result even in the situation of the most unfavorable controls of the fleeing player. In each of the above cases, a numerical method is constructed to find the price of the game in suitable classes of strategies and to construct the corresponding control laws. The discretization schemes for a differential game described by equations of fractional order in a multidimensional domain are constructed and studied.
Algorithm Development for Generation of Powder Particles for Use in Numerical Simulations of Powder Bed Fusion Additive Manufacturing Processes
Authors: Kelley Garrett M. , Ramulu Mamidala
Published: August 2021

This article presents an algorithm development methodology for incorporating the effects of powder quality into numerical simulations of powder bed fusion technologies. The framework leverages x-ray microtomography measurements of samples representative of changes in powder quality with powder reuse. Individual particles are labelled and analysed by postprocessing the three-dimensional data. Included in this data is the particle surface normal and point cloud information which can be used to reconstruct the particle using Poisson Surface Reconstruction in Open3D. This reconstruction can then be exported as a Standard Tessellation Language (STL) file that can be incorporated into discrete element method solvers such as YADE or finite element frameworks such as MOOSE. In this sense, libraries of particles can be generated and used in simulations. To demonstrate the applicability of this method, a publicly available NIST dataset is leveraged. In lieu of experimental data, a second method using Computer-Generated Imagery (CGI) software, Blender, is also presented. The methods are able to replicate powder features, such as satellites and surface irregularity, that are functions of both powder manufacturing methods as well as powder reuse cycles. These particle irregularities have important implications on part quality and manufacturing cost.
Numerical Analysis of Free Dust Diffusion Law in Large Section Construction Tunnel
Authors: Qiao Liwei , Sang Conghui , Yuan Wenchao
Published: August 2021

The Youzhushan tunnel (large section double-track railway tunnel) is used as the research background, the concentration distribution of the free dust diffusion trajectory after blasting in the working face was numerically simulated by using the finite element computational fluid dynamics software Ansys-CFD. The simulation results were compared with the field measured data, and the results are basically consistent. The results show that the lining trolley is the main equipment to hinder the dust diffusion, the free dust on both sides of the lining trolley has a clear boundary, and the high concentration of free dust has not been well diffused. A vortex area appears near the entrance of the adit level, which forces the free dust from the tunnel to do vortex circulation. The dust removal rate of parallel guide is about 66.5% after 800 seconds of ventilation and about 76.6% after 2400 seconds of ventilation. The drainage effect of parallel guide is more obvious when the dust concentration in the tunnel is lower.
Estimating Latent Factors Based on Statistical Data Analysis
Authors: Xu Guoqing , Yang Guoxiao
Published: August 2021

In recent years, statistical methods have been widely used to estimate latent risk factors that affect the prices of financial assets. This paper develops new estimators for asset pricing factors by introducing dependence measure--distance covariance, that can identify nonlinear dependence. We combined distance covariance with Principal Component Analysis (PCA) and Risk-Premium PCA (RPPCA) and made contrast analysis based on Chinese market data. RPPCA, as a new method, shows strong applicability and detects factors with high Sharpe-ratio efficiently. Moreover, distance covariance produces better performance than covariance in PCA as a factor estimator, which illustrates the superiority of the distance covariance. Finally, the most striking results revealed by the study is that RPPCA including distance covariance of residuals outperforms others with a smaller pricing error and a significantly large Sharpe-ratio.
Handwritten Digit Recognition Based On Spiking-Vovnet and Extended Application
Authors: Guo Yonghui , Li Yuntao , Zhang Yu , Li Yonggang , He Yonghua
Published: August 2021

Spike Neural Network (SNN) can provide an efficient reasoning process. In this paper, by modifying the Vovnet network to use IF neurons to replace the traditional Vovnet RELU neurons, testing on the open handwritten digit mnist data set, and comparing the Vovnet network structure of CNN and SNN for comparative experiments, it is found that the Spiking-Vovnet network is guaranteed and traditional Under the premise of the accuracy of the Vovnet network, the speed has been greatly improved, and at the same time, the resource consumption is reduced. In order to expand the application, in the synthetic aperture radar (SAR) image target detection, the Spiking-Vovnet network is used as the FCOS ship target detection feature extraction network. For promote the prise degree of detection, the variability convolutional neural network is lead into design a SAR ship Feature extraction network for ship target detection.
The design and performance of CUBES — a CubeSat X-ray detector
Authors: Kushwah R. , Stana T.A. , Pearce M.
Published: August 2021

CUBES is a X-ray detector payload which will be installed on the KTH 3U CubeSat mission, MIST.
The detector comprises cerium-doped Gd3Al2Ga3O12 (GAGG) scintillators read out with silicon photomultipliers through a Citiroc Application-Specific Integrated Circuit. The detector operates in the energy range
∼35–800 keV. The aim of the CUBES mission is to provide experience in the operation of these relatively new technologies in a high-inclination low earth orbit, thereby providing confidence for component selection in more complex satellite missions. The design of the CUBES detector is described, and results from performance characterisation tests carried out on a prototype of CUBES, called Proto-CUBES, are reported. Proto-CUBES was flown on a stratospheric balloon platform from Timmins, Canada, in August 2019. During the ∼12 hour long flight, the performance of Proto-CUBES was studied in the near-space environment. As well as measuring the X-ray counts spectra at different atmospheric depths, a 511 keV line from positron annihilation was observed.
Computer modelling of R.C. shear walls-comparative analyses at different values of the reduction coefficient. Internal forces values
Authors: Tsvetkov S
Published: August 2021

The report shows a continuation of analyses of reinforced concrete shear walls solved by horizontal forces [14]. In certain places in the walls the stiffnesses are reduced, thus comparing the obtained results between the groups of models. Solutions for wall and mixed structural systems are shown. The decisions were made with specialized Tower software based on work by the Finite Element Method. Interesting conclusions can be seen for the level between the rigid basement and the first floor. Decreases in bending moments and increases in shear forces are observed. Motivation – quick analysis of walls subjected to the action of horizontal forces (hand analysis, without program system); the goals-proving the idea of the influence of the supports from the basement levels; the methodology-solutions with specialized software-only for a certain speed in the decisions. The solutions have characteristic geometry and loads and can be easily parameterized with correction factors.
Effect of cooling on power generated by photovoltaic panels
Authors: Hudișteanu S V , Cherecheș N C , Popovici C G , Verdeș M , Ciocan V , Balan M C , Țurcanu F E , Scurtu I C
Published: August 2021

The paper presents a numerical analysis of the operation of photovoltaic (PV) panels integrated in fixed position on the roofs or facades of the buildings. Knowing that the efficiency of photovoltaic panels is temperature-dependent, and due to fixed PV panel position, the possibility of the improving the conversion is analysed from the point of view of the temperature of the PV cells. The model is simulated using TRNSYS software and the main functioning parameters assessed are the operating temperature of the cells, open circuit voltage, maximum power generated and conversion efficiency. The solution proposed for cooling consists in using water heat exchangers attached to the backside of the photovoltaic panel. The results highlight the direct dependence of the photovoltaic efficiency with the temperature of the panel for different positions in the same geographical location. The energy gain during the cooling interval is about 26.9 Wh/m2 (vertical), 81.9 Wh/m2 (inclined) and 81.7 Wh/m2 (horizontal), which represents an increase of 5.8%, 9.3% and 9.2% respectively, compared to the normal operating conditions.
Experimental statistical models for the study of cement-concrete for road pavements
Authors: Chintea L , Mishutin A , Grynyova I , Zavoloka M
Published: August 2021

The article presents the calculation and statistical analysis of the experimental statistical (ES) model of the several samples of concrete and reinforced concrete for road pavements. For the analysis, the Program (dialogue) Complex COMPEX was used, which was developed at the Odessa State Academy of Civil Engineering and Architecture by scientists of the scientific school of prof. V.A. Voznesensky. In the research of the structure and properties of rigid road pavements concrete with an optimal plan, a 4-factor experiment was carried out, in which the following factors of concrete composition were varied: X1- the amount of Portland cement PC II / A-Sh-500, from 400 to 500 kg / m3; X2- the amount of polypropylene fiber from 0 to 2 kg / m3; X3- the amount of Metakaolin, from 0 to 30 kg / m3; X4- the amount of complex action additive (polycarboxylate type) Coral ExpertSuid-5, from 0.6 to 1% of the cement mass. An increase in the amount of Coral ExpertSuid-5 additive from 0.6 to 0.8% of the cement mass is noticeable, by 10…12%, and decreases the W/C ratio of mixture. An increase in the amount of this additive of complex action to 1% causes a further, but less noticeable, decrease in W/C ratio.
Asphalt mixtures for bituminous coatings with BF slag filler
Authors: Nanea D R
Published: August 2021

Asphalt mixtures, as a construction material intended to produce bituminous coatings, consists of a homogenous mixture made from natural aggregates and bitumen. Replacing one of the natural rocks, the filler with artificial filler, a metallurgical industry waste material, will determine a saving of material and financial resources. This can be used as an actual method of environmental protection by conserving the relief, protecting localities from noise produced in stone quarries and reusing a waste material. The processing of granular blast furnace slag from the Liberty Galati plant by grinding it exceptionally fine, into filler and their subsequent use in the preparation of asphalt mixtures, leads to obtaining favourable results on two of the most used currently in the country, AC16 surf50/70 and AC 22.4 bin50/70.

These values will provide an image on the behaviour resistance and their deformability under traffic. A high-water absorption can indicate a porous mixture and favours the penetration of water into the layer, water that can change its volume during freezing-thawing and can lead to cracks in the bitumen film, stripping, dislocation of pieces in the layer. A high creep can indicate a mixture which will deform under traffic, will form slopes, or will favour the phenomenon of exudation.

High stability may indicate a rigid mixture and under traffic does not have an elastic conduct, which can lead to cracks in the road surface.

Framing of the results and the appreciation of this conduct of asphalt mixture made with bf slag filler compared to a standard, leads us to the finding that the mixture is accurate and will withstand environmental factors.
Analytical methods for selection of demolition technology
Authors: Popov O , Chystiakov A , Petrovsky A
Published: August 2021

Demolition of buildings and structures, or their structural elements, is primarily aimed in designing stage – for the reconstruction or renovation of a building or complex of buildings, updating the appearance, design or philosophical meaning of an object. Therefore, demolition must be approached no less responsibly than the construction itself. The article deals with data on the economic feasibility of a correct approach to demolition, which allows the maximum extraction of raw materials from construction waste for further construction. The article provides a brief overview of the technologies for demolition structures to select the optimal and most effective. For the best use of the existing knowledge on this subject, and as a result – obtaining the greatest economic benefit, it is proposed to classify demolition technologies, their description and recommendations for use. For this, it was proposed to create a certain database that can, in an interactive form, help to choose the optimal technology for demolition a building or a separate structure.
Defining an existing prefabrication workflow to identify measures for increased labour time utilization rates
Authors: Cribbs J , Root S
Published: August 2021

This paper analyses the current operations and labour utilization rates for a project team engaged in the prefabrication of exterior wall panels, in an existing manufacturing facility in Tempe, Arizona. A current state process is defined for the BIM-to-install process of each exterior insulation and finish system (EIFS) wall panel. Through analysis of the current state, it is found that only 17% of time was spent directly modelling components meant for prefabrication. The remaining 83% of time engaged in modelling is subject to optimization. Based on these findings, a discussion is presented regarding in place scheduling procedures, model and data management protocols, and field to shop verification/validation measures impacting modelling activities. Finally, a presentation of a series of future workflow interventions intended to improve labour utilization rates for modelling and shop personnel while enabling the internal shop ideal for “mass customization through prefabrication” is provided.
FEM analysis of a floor structural system made of thin-walled cold-formed steel profiles
Authors: Țăranu G , Toma I-O
Published: August 2021

The paper presents the results of a nonlinear FEM analysis of a floor system made of plane truss beams. The steel profiles are made of U-shaped thin walled cold-formed stell. Experimental data were used to model the stiffness of the joints. To observe the structural behaviour of the floor system, nonlinear constraints were defined as a parabolic function considering previous experimental data.
Numerical studies on steel-concrete composite structures
Authors: Urian G , Haupt-Karp A
Published: August 2021

The paper focuses on the seismic performances of steel-concrete composite structures made with fully encased steel-concrete composite columns and steel beams. An important objective is to study the influence of the structural steel ratio on the behaviour of composite columns. To meet the proposed objectives, a numerical study was developed on composite structures. Some comments, design recommendations and an economical study conclude the paper.
Self-stressed steel-reinforced concrete floor slab stress-strain state numerical analysis taking into account the concreting stages
Authors: Semko O V , Hasenko A V
Published: August 2021

In steel-reinforced concrete floor slabs, structurally ensuring the joint operation of monolithic reinforced concrete slab and steel crossbars, a successful combination of its components positive qualities is realized at a high level: compression forces are perceived by monolithic slab, and tensile forces by steel beams. Reinforced concrete slabs in such structures have a relatively equal weight with a payload on interfloor slabs for public buildings. Having effectively developed the sequence of concreting the slab through the span in two stages, it is possible to create pre-stressing in the floor steel crossbars, located in the spans of the second concreting stage, and in monolithic reinforced concrete slab of the first concreting stage. In this sense, the term “self-stressed” is used in this work. By creating pre-stresses in the steel crossbars of the floor, it is possible to reduce their cross-section or to increase their span and to achieve savings in metal costs on the building frame. Pre-stressing of the monolithic reinforced concrete slab of the first concreting stage in the opposite to operational bending form, will increase crack resistance of the specified sites of a monolithic overlapping and will give the chance to reduce its reinforcement.
Propagation properties of spin wave in Co2FeAl Heusler alloy ultrathin films
Authors: Singh Suraj , Gupta Nanhe Kumar , Hait Soumyarup , Chaudhary Sujeet , Tybell Thomas , Wahlström Erik
Published: August 2021

We report an investigation of spin wave propagation in ion beam sputtered Co2FeAl Heusler alloy thin film on Si(100) substrate. The spin wave transmission spectra measured at fixed frequencies by sweeping the external applied magnetic field were used to estimate technologically relevant spin wave propagation parameters. The spin wave group velocity was found at 6.1 km s−1 with an attenuation length larger than 7 μm. The Gilbert damping parameter was estimated to be 0.019. The frequency dependency of the group velocity decreased with increasing frequency and the attenuation length increased at low frequencies while started to decrease at larger frequencies. The amplitude of non-reciprocity also decreased with increasing frequency. The propagation parameters presented were also independently verified by time-resolved propagating spin wave spectroscopy.
ezGeno: an automatic model selection package for genomic data analysis
Authors: Lin Jun-Liang , Hsieh Tsung-Ting , Tung Yi-An , Chen Xuan-Jun , Hsiao Yu-Chun , Yang Chia-Lin , Liu Tyng-Luh , Chen Chien-Yu
Published: August 2021

Motivation

To facilitate the process of tailor-making a deep neural network for exploring the dynamics of genomic DNA, we have developed a hands-on package called ezGeno. ezGeno automates the search process of various parameters and network structures and can be applied to any kind of 1D genomic data. Combinations of multiple abovementioned 1D features are also applicable.

Results

For the task of predicting TF binding using genomic sequences as the input, ezGeno can consistently return the best performing set of parameters and network structure, as well as highlight the important segments within the original sequences. For the task of predicting tissue-specific enhancer activity using both sequence and DNase feature data as the input, ezGeno also regularly outperforms the hand-designed models. Furthermore, we demonstrate that ezGeno is superior in efficiency and accuracy compared to the one-layer DeepBind model and AutoKeras, an open-source AutoML package.

Availability and implementation

The ezGeno package can be freely accessed at https://github.com/ailabstw/ezGeno.

Supplementary information

Supplementary data are available at Bioinformatics online.
Evidence of intergenerational transmission of diethylstilbestrol health effects: hindsight and insight
Authors: Titus Linda
Published: August 2021

This review summarizes key findings from the US National Cancer Institute (NCI) diethylstilbestrol (DES) Combined Cohort Study with a focus on the results of the NCI Third Generation Study, a cohort of DES-exposed and -unexposed granddaughters. Findings to date from the Third Generation Study are discussed in the context of other research efforts and case reports, suggesting an intergenerational heritability of DES-related effects. The DES story serves as a model for the influence of endocrine disrupting chemicals on human health. It also serves as a warning of the special hazards of pregnancy exposures, and more broadly, of the potential for invisible health consequences arising from new or changing exposures.
Reparations: To What End? Developing the State’s Positive Duties to Address Socio-economic Harms in Post-conflict Settings through the European Court of Human Rights
Authors: Torres Felix E
Published: August 2021

Despite being conceived as a framework to protect civil and political rights in peacetime, the European Convention on Human Rights is currently being applied in states affected by armed conflicts with challenging socio-economic demands. This article outlines the European Court of Human Rights’ current approach for the protection of human rights in conflict-related scenarios and critically examines its suitability to cope with the socio-economic challenges that arise in post-conflict settings. With recourse to legal theory and moral thought, it explores an alternative avenue to coherently frame the Court’s practice to overcome certain problematic distributive outcomes that derive from the prevailing approach. The suggested alternative is a regime of positive duties intended to ensure an adequate standard of living after widespread violence.
Epistasis for head morphology in Drosophila melanogaster
Authors: Özsoy Ergi D , Yılmaz Murat , Patlar Bahar , Emecen Güzin , Durmaz Esra , Magwire Michael M , Zhou Shanshan , Huang Wen , Anholt Robert R H , Mackay Trudy F C
Published: August 2021

Epistasis—gene–gene interaction—is common for mutations with large phenotypic effects in humans and model organisms. Epistasis impacts quantitative genetic models of speciation, response to natural and artificial selection, genetic mapping, and personalized medicine. However, the existence and magnitude of epistasis between alleles with small quantitative phenotypic effects are controversial and difficult to assess. Here, we use the Drosophila melanogaster Genetic Reference Panel of sequenced inbred lines to evaluate the magnitude of naturally occurring epistasis modifying the effects of mutations in jing and inv, two transcription factors that have subtle quantitative effects on head morphology as homozygotes. We find significant epistasis for both mutations and performed single marker genome-wide association analyses to map candidate modifier variants and loci affecting head morphology. A subset of these loci was significantly enriched for a known genetic interaction network, and mutations of the candidate epistatic modifier loci also affect head morphology.