bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi-objective Optimization of Spectrum Sensing and Power Allocation Based on Improved Slime Mould Algorithm
Authors: Sun Jianan , Guo Bin , Hu Yanfei , Zhang Yiheng 
Published: July 2021

Abstract
In order to improve the throughput of sub-users of cognitive radio networks and reduce the interference to primary users, firstly, we consider the spectrum sensing time, decision threshold, and power allocation factors of joint sub-users, and construct the average network throughput and average interference as a multi-objective optimization problem, and secondly, propose a multi-objective optimization algorithm based on improved sticky bacterium algorithm (SMA) to model and solve this problem to obtain the best the sensing time, decision threshold and power. Finally, the proposed method is compared with the NSGA-II algorithm, and the simulation results show that the proposed method can effectively search for the optimal solutions of the spectrum sensing parameters to maximize the average network throughput and minimize the average interference.
A Comparative Study on the Influence of Artificial Intelligence Robot Distribution and Traditional Logistics Distribution Mode
Authors: Zhang Xiaolei 
Published: July 2021

Abstract
With the increasing level of intelligence of logistics enterprises in China, the mode of artificial intelligent logistics distribution has become a new strategy for the development of modern logistics industry. In the logistics industry of artificial intelligence, logistics robot has occupied the market and become the key link of logistics distribution. It is of great significance to study the distribution mode of artificial intelligence robot. With the development of our national economy and the improvement of people’s living standard, the demand for logistics service quality and distribution efficiency is higher and higher. At present, most enterprises in our country abandon the traditional manpower distribution operation mode. This paper expounds the basic concepts of “artificial intelligence” and “intelligent robot” through the literature research method and the research method of combining theory with practical cases, and obtains the cognition of the current technology of intelligent logistics by collecting, processing and sorting the relevant documents. The emergence of artificial intelligence makes large amount of data fast and accurate, while artificial intelligence robot makes logistics management system, object transportation, distribution and order quantity processing intelligent, and produces the integration of production, the production chain is greatly reduced, the communication between logistics enterprises and intelligent robots is closer, the corresponding cost can be greatly reduced, and the enterprise can manage and operate effectively.
Research on the hyper-heuristic of Sub-domain Elimination Strategies based on Firefly Algorithm
Authors: Sun Mingquan , Xing Bangsheng , Yang Daolong 
Published: July 2021

Abstract
In this study, a hyper-heuristic named Sub-domain Elimination Strategies based on Firefly Algorithm (SESFA) is proposed. First, a typical hyper-heuristic is usually using the high-level strategy selection or the combination of the low-level heuristics to obtain a new hyper-heuristic, each round of optimization process is carried out in the whole problem domain. However, SESFA evaluates the problem domain through the feedback information of the meta-heuristic at the lower level, eliminating the poor performance areas, and adjusting the underlying heuristic or adjusting the algorithm parameters to improve the overall optimization performance. Second, the problem domain segmentation function in SESFA can reduce the complexity of the objective function within a single sub-domain, which is conducive to improving the optimization efficiency of the underlying heuristic. Further, the problem domain segmentation function in SESFA also makes there is no direct correlation between different sub-domains, so different underlying heuristics can be adopted in different sub-domains, which is beneficial to the realization of parallel computing. Comparing SESFA with Firefly Algorithms with five standard test functions, the results show that SESFA has advantages in precision, stability and success rate.
An Algorithm for Target Tracking of the Car in Accident
Authors: Zhang Siyuan , Liu Yunqing , Dai Yile 
Published: July 2021

Abstract
At present, the target tracking algorithm for the video of the vehicle involved in the accident is not perfect, which causes the target to rotate and the target is blocked, and the tracking effect is not good. This paper uses a CamShift tracking algorithm that combines HLBP feature matching and unscented Kalman filtering. Firstly, the vehicle features are extracted through the algorithm to obtain more accurate features, thereby reducing the interference caused by the target rotation on the feature extraction. Secondly, the degree of occlusion of the target is judged by the Bhattacharyya distance, and finally the UKF algorithm is used to predict the target position. The vehicle efficiently solve the problem of poor tracking performance when the target is occluded. Experiments have proved that, in the actual application of tracking the accident vehicle, the algorithm can effectively reduce the influence of external factors on the tracking effect, and the tracking accuracy is greatly improved.
Research on Face Recognition Algorithm Based on Convolutional Nerve
Authors: Fang Yunqian 
Published: July 2021

Abstract
Facial expression can truly reflect people’s inner activities, human emotions can be fully reflected through the expression, facial expression recognition in the field of artificial intelligence has important research significance, in daily life also has its application value. At present, facial expression recognition technology has become a very promising frontier technology, but also the current research focus in the field of computer vision.
In this paper, facial expression recognition based on convolution neural network is studied. The concrete work has the following several parts: For the part of face detection, this paper introduces the common methods of knowledge-based rules, feature-based, template-based matching, and statistical model-based, and V-J detector is used for face detection in this paper. In the part of expression recognition, we study the recognition of happiness, sadness, anger, depression, fear and surprise by convolution neural network. This paper uses keras to build a deep learning framework. The neural network consists of volume base layer, pool layer, activation layer and full connection layer. The classifier uses softmax. Using the image data in the standard database as input, after the processing of each layer in the neural network, and finally outputting the probability corresponding to six expressions through softmax, it is generally believed that the expression with the highest probability is the facial expression in the input image.
Application Research of VR Technology in Product Design
Authors: Min Song 
Published: July 2021

Abstract
At present, VR technology has been widely used in R&D and manufacturing of product design projects because of its many advantages. How to further improve the application effect of VR technology in product design practice projects has become one of the research hotspots in the design field in recent years. Based on this, this paper explores the application of VR technology in product design. Firstly, it introduces the basic situation of VR technology. Then, taking the design of leisure and entertainment products in public facilities as an example, it discusses the basic application process of VR technology. Finally, it looks forward to the future development of VR technology based on the shortcomings of VR technology in product design.
An Empirical Study of Online Terminology Translation Retrieval:Using Search Engines as a Tool
Authors: Wang Zheng 
Published: July 2021

Abstract
Online search engines and other computer-aided tools are playing an increasingly important role in technical translation, especially in the translation of out-of-vocabulary new terms. Dictionaries, at times, prove to be of little help to term translation where out-of-vocabulary terms rely on polysemy for heuristic effects. This paper explores the role of online search engines in terminology translation by analyzing the effectiveness of four terminology translation extraction methods which utilize online search engines as search tools, thereby generating suggestions on how to use search result for reference. An experiment with some new terms was conducted to examine the effectiveness of each method. This study revealed that template-based term translation extraction and dictionary-based translation extraction have the highest accuracy rate of 86% and 89% respectively while semantic prediction search method is the most flexible method with the highest retrieval rate of 95% although its results are not always accurate. Therefore, a verification model was proposed, which utilizes quantitative-and-qualitative context analysis to verify the accuracy of translation results obtained from a search engine.
Research on Intelligent Fault Diagnosis of Servo Hydraulic Drawing Cushion
Authors: Yu Zikou , Duan Yongyong , Wu Zongling , Wang Yuhang 
Published: July 2021

Abstract
The drawing cushion of press line in the press workshop of the whole car factory has been extensively upgraded from air cushion to hydraulic drawing cushion. The hydraulic drawing cushion is more accurate than the drawing force of the air cushion, however, the hydraulic drawing cushion is a complex of mechanical, hydraulic, Motion Control and detection technology, and coupled with the press, which makes the fault diagnosis of the hydraulic drawing cushion more difficult. This paper mainly introduces the problems of the coordination among the three systems of mechanical, hydraulic and electronic control of Rexroth Company’s servo-hydraulic drawing cushion and its intelligent fault diagnosis method.
A Target Detection and Evaluation Method for Safety Protection Equipment
Authors: Qiu Jianzhong , Wu Jun , Wan Guoyong , Huang Pengcheng , Zhou Tingting 
Published: July 2021

Abstract
The existing safety detection methods are not sufficient to achieve real-time accurate detection, and cannot perform real-time safety assessment. Taking the construction site as an example, this paper proposes a safety equipment wear detection method based on the joint constraint of linear distance and angle, and proposes the idea of establishing a knowledge database of safety protection equipment wear behavior, and proposes a safety factor evaluation model. In this paper, convolutional neural networks are used to identify the construction personnel and safety equipment in two basic poses, and the linear distance and deflection angle of the regional center point coordinates are used to jointly determine the wearing status of the safety equipment. The generated result matches the safety information knowledge base to obtain the final test results. We obtained the real-time safety factor of the construction personnel by correlating the detection results with the actual scene. Finally, the method used in the article is summarized and prospected.
Segmentation of Pulmonary Nodules Based on BBClstm Unet
Authors: Wang Xi , Li Mingqiu , Yang Ji 
Published: July 2021

Abstract
To solve the problem of insufficient segmentation accuracy caused by the failure of UNET model to make full use of the weight relationship and semantic information between coding layers in lung nodule image segmentation, a lung nodule segmentation method based on BBClstm-Unet is proposed. In this method, parallel attention module is used to complete the information coding of a larger range of pulmonary nodules image and reset the weight of sampling correlation channel information. Bconvlstm structure is used to combine feature mapping, and forward and backward output sampling are fused to obtain the final segmentation result. At the same time, hybrid loss function is used to alleviate the class imbalance problem. The experimental results show that the average dice value of BBClstm-Unet network on luna16 data set reaches 90.83%, which is better than the original UNET network.
Driver Fatigue Detection Based on Parallel Neural Network
Authors: Yang Ji , Li Mingqiu , Wang Xi , Lu Jiafeng 
Published: July 2021

Abstract
Aiming at the problem that the existing fatigue driving detection methods cannot make full use of eye features and semantic information, a driver eye fatigue detection method based on parallel neural network is proposed. This method detects human faces through a multi-task cascaded convolutional network, determines the driver’s eye area according to the face ratio relationship, uses the parallel structure of the convolutional neural network and the residual network to recognize the eye state opening and closing, and according to PERCLOS the criterion is to judge the fatigue state. The experimental results show that the method has a high accuracy rate and can effectively detect the fatigue driving state.
Primary Frequency Regulation of Intelligent Building-type Virtual Power Plant
Authors: Cui Yong , Xiao Fei , Gu Jun , Wang Weihong , Cao Liang , Zhan Gui , Yin Shuangrui , Chen Minyu , Ai Qian 
Published: July 2021

Abstract
In order to cope with the impact of intelligent building-type virtual power plant on system frequency, this paper proposes a primary frequency control strategy. Firstly, a typical demand-side resource model of intelligent building-type virtual power plant is established, which considers the travel uncertainty of electric vehicles and resident’s comfort preference. Secondly, the control parameters of electric vehicles and air-conditioning loads are designed respectively, and a control strategy based on variable coefficient droop control is proposed. Finally, a simulation example verifies the effectiveness of the primary frequency regulation strategy, which can effectively reduce system frequency fluctuations while ensuring user demand.
Betting on the best case: higher end warming is underrepresented in research
Authors: Jehn Florian U , Schneider Marie , Wang Jason R , Kemp Luke , Breuer Lutz 
Published: July 2021

Abstract
We compare the probability of different warming rates to their mentions in IPCC reports through text mining. We find that there is a substantial mismatch between likely warming rates and research coverage. 1.5 °C and 2 °C scenarios are substantially overrepresented. More likely higher end warming scenarios of 3 °C and above, despite potential catastrophic impacts, are severely neglected.
Reducing CO2emissions by targeting the world’s hyper-polluting power plants*
Authors: Grant Don , Zelinka David , Mitova Stefania 
Published: July 2021

AbstractCombusting fossil fuels to produce electricity is the single largest contributor to sector-level, anthropogenic carbon pollution. Because sector-wide policies are often too unwieldy to implement, however, some researchers have recommended reducing electricity-based CO2emissions by targeting the most extreme emitters of each nation’s electricity industry. Here, we use a unique international data source to measure national disproportionalities in power plant CO2emissions and estimate the fraction of each country’s electricity-based CO2emissions that would be reduced if its most profligate polluters lowered their emission intensities, switched to gas fuels, and incorporated carbon capture and storage systems. We find that countries’ disproportionalities vary greatly and have mostly grown over time. We also find that 17%–49% of the world’s CO2emissions from electricity generation could be eliminated depending on the intensity standards, fuels, or carbon capture technologies adopted by hyper-emitting plants. This suggests that policies aimed at improving the environmental performance of ‘super polluters’ are effective strategies for transitioning to decarbonized energy systems.
A mapping between the spin and fermion algebra
Authors: Meier Felix , Waltner Daniel , Braun Petr , Guhr Thomas 
Published: July 2021

Abstract
We derive a formalism to express the spin algebra

s
u

(

2

)

in a spin s representation in terms of the algebra of L fermionic operators that obey the canonical anti-commutation relations. We also give the reverse direction of expressing the fermionic operators as polynomials in the spin operators of a single spin. We extend here to further spin values the previous investigations by Dobrov (2003 J. Phys. A: Math. Gen.
36 L503) who in turn clarified on an inconsistency within a similar formalism in the works of Batista and Ortiz (2001 Phys. Rev. Lett.
86 1082). We then consider a system of L fermion flavors and apply our mapping in order to express it in terms of the spin algebra. Furthermore we investigate a possibility to simplify certain Hamiltonian operators by means of the mapping.
Removing invasive conifers - considerations, complexity and costs
Authors: Edwards Peter , Sprague Rowan , Stahlmann-Brown Philip 
Published: July 2021

Abstract
Invasive conifers are a significant problem in countries such as New Zealand, requiting a substantial investment to bring them under control. One of the critical elements of controlling invasive conifers is operational planning—determining where to control them, which trees to control, what methods to use, and the estimated cost. However, it is challenging to determine accurate costs due to the complexity of multiple site- and tree-related factors. In New Zealand, control costs are highly variable because understanding of costs per method are outdated and the complexities involved are not well elucidated. This paper explores why and how control costs vary to better predict costs in the future. To explore the factors that influence cost, we ran an online workshop that generally followed a nominal group process with several experienced project managers and contractors involved in invasive conifer control. To effectively estimate the cost of control, contractors and project managers must first understand how various site and tree-related factors influence the choice of control method. Contractors and project managers then determine how the factors influence cost. These results come at an important time in the management of invasive conifers in New Zealand and elsewhere. Control operations are increasing and expanding, requiring accurate estimates of costs to plan future operations. The findings will also be useful for training new staff and updating guidelines on invasive conifer control.
‘What matters to you?’ Health outcome prioritisation in treatment decision-making for older patients
Authors: Festen Suzanne , van Twisk Yvette Z , van Munster Barbara C , de Graeff Pauline 
Published: July 2021

Abstract

Background
for shared decision-making, it is important to discuss of the patients’ priorities in order to align treatment decisions with these priorities.

Objective
to assess the most important health outcome for older patients on the verge of making a treatment decision, using the Outcome Prioritization Tool (OPT). Secondary objectives were the feasibility of the OPT and patient variables associated with prioritising different health outcomes.

Design
retrospective cohort study.

Setting and subjects
at the University Medical Hospital Groningen, the Netherlands, 350 patients were included who visited the geriatric outpatient clinic during the work-up regarding a complex treatment decision (such as cancer treatment or heart valve replacement).

Methods
during geriatric assessment, patients prioritised between four health outcomes, using the OPT.

Results
median age was 78.5 years, 172 (49.1%) were referred regarding a treatment decision for a malignant disease. Cognitive impairment was present in 23.6%. Most patients (55.2%) prioritised maintaining independence as their most important goal, followed by extending life in 21.1%. Only cognitive impairment was significantly associated with prioritising extending life as the most important health outcome. For 107 patients (30.6%), the OPT was not feasible; these patients more often had malnutrition and assisted living.

Conclusions
the main health outcome of older patients on the verge of making a treatment decision was maintaining independence, followed by extending life. Patients with cognitive impairment more often prioritised extending life. The OPT was feasible as a decision aid for most patients. For optimal shared decision-making, it is crucial to take patient preferences into account.
Estimation of Airborne Vapor Concentrations of Oil Dispersants COREXIT™ EC9527A and EC9500A, Volatile Components Associated with the Deepwater Horizon Oil Spill Response and Clean-up Operations
Authors: Stenzel Mark R , Arnold Susan F , Ramachandran Gurumurthy , Kwok Richard K , Engel Lawrence S , Sandler Dale P , Stewart Patricia A 
Published: July 2021

Abstract
The Deepwater Horizon (DWH) drilling unit explosion above the Macondo oil well on 20 April 2010 caused the release of approximately 4.9 million barrels (779 million L) of oil into the Gulf of Mexico. As part of a larger spill response and clean-up effort, approximately 1.84 million gallons (6.81 million L) of chemical dispersants COREXIT™ EC9500A and COREXIT™ EC9527A were applied to the resultant oil slicks through spraying on the water surface by plane and by vessel and through injection at the release source near the seabed. The GuLF STUDY is investigating the health effects of workers involved in the oil spill response and clean-up after the DWH explosion, and estimates of possible exposure to chemical dispersants were needed. Exposures were estimated to the volatile components of COREXIT™ EC9500A [petroleum distillates, hydrotreated light, and propylene glycol (PG)] and of COREXIT™ EC9527A [2-butoxyethanol (2-BE) and PG] using two of AIHA IHMOD2.0© mathematical modeling tools along with the dispersants’ chemical and physical properties. Monte Carlo simulations were used to reflect uncertainty in input parameters with both the two-box, constant emission model and the near and mid field plume model for indoor and outdoor activities, respectively. Possible exposure scenarios considered various evaporation rates, sizes of the dispersant pool, wind speeds, and ventilation rates. For the two-box model, mean near field exposure estimates to 2-BE ranged from 0.9 to 5.7 ppm, while mean far field estimated exposures ranged from 0.3 to 3.5 ppm. Estimates of mean near field plume model exposures ranged from 0.01 to 3.7 ppm at 2.5 ft from the source, and &lt;0.01 to 0.3 ppm at 10 ft from the source. Estimated exposures to PG were approximately 10% of the calculated 2-BE exposures and exposures to petroleum distillates about 40% higher than the 2-BE estimates. Results indicate that compared with current occupational exposure guidelines, overexposure to petroleum distillates and PG probably did not occur in our study, but under some conditions, for short periods, exposure to 2-BE may have exceeded the limits for peak exposures. These estimates were developed for use in job-exposure matrices to estimate exposures of workers having contact with dispersant vapors for the GuLF STUDY.