Dohnshepard3840

Meanwhile, the lightweight deep learning algorithm is used to optimize the proposed P-D logistics linkage-oriented decision-making model, namely, the Collaborative Optimization (CO) method. Finally, the proposed P-D logistics linkage-oriented decision-making model is applied to a domestic Enterprise H. It is simulated by the Matlab platform using sensitivity analysis. The results show that the production, storage, distribution, punishment, and total costs of linkage operation are 24,943 RMB, 3,393 RMB, 2,167 RMB, 0 RMB, and 30,503 RMB, respectively. The results are 3.7% lower than the nonlinkage operation. The results of sensitivity analysis provide a high reference value for the scientific management of enterprises.Feature extraction and Chinese translation of Internet-of-Things English terms are the basis of many natural language processing. Its main purpose is to extract rich semantic information from unstructured texts to allow computers to further calculate and process them to meet different types of NLP-based tasks. However, most of the current methods use simple neural network models to count the word frequency or probability of words in the text, and it is difficult to accurately understand and translate IoT English terms. In response to this problem, this study proposes a neural network for feature extraction and Chinese translation of IoT English terms based on LSTM, which can not only correctly extract and translate IoT English vocabulary but also realize the feature correspondence between English and Chinese. The neural network proposed in this study has been tested and trained on multiple datasets, and it basically fulfills the requirements of feature translation and Chinese translation of Internet-of-Things terms in English and has great potential in the follow-up work.Railway engineering generates large amounts of construction and demolition waste (CDW). RHPS 4 nmr To quantify the amount of CDW generated from railway engineering projects throughout the whole life cycle, a process-based life cycle assessment model is proposed in this paper. The life-cycle CDW is divided into four parts CDW from off-site transportation of construction materials (OSTCM), CDW from site operation wastage of construction materials (SOWCM), discard ballast from roadbeds, stationyard, bridges and tunnels (DB), and CDW from reparation and renewal of aging components (RRAC). Yun-Gui Railway is selected as a case study to validate the developed model, and an uncertainty analysis is conducted with Oracle Crystal Ball software. The results show that between 175 and 311 million tons of CDW is generated throughout the whole life cycle of Yun-Gui Railway. DB is the largest component of the life-cycle CDW from railway engineering projects. This indicates the negative environmental impacts of railway construction can be significantly mitigated by optimizing the location of ballast disposal sites and developing suitable landfill proposals. Also, the CDW generated by wastage of construction materials during off-site construction and site operation is important in waste management in railway engineering projects, in which rubble, sand, and cement have the high potential for waste reduction. Findings from this study can contribute to the knowledge body as well as the engineering practice in green railways.The purpose of this paper is to understand the digital 3D multimedia panoramic visual communication technology based on virtual reality. Firstly, the key concepts and characteristics of virtual reality are introduced, including the development and application of digital three-dimensional panorama technology. Then, according to the theoretical research, some basic knowledge of 3D panoramic image Mosaic is introduced, including camera image modeling, image sharing, and image exchange. Finally, with the development of the virtual tour at the College of Normal University, the hardware of panoramic technology and the demand of panoramic image search have been expanded in the application. The design of panoramic Mosaic, panoramic image generation, and virtual tour school construction considers real-world issues. The innovation of this paper lies in that will be used by SketchUp8.0 software builds the geometry of 3d virtual scene and by the cylindrical panoramic images based on image of building 3 d virtual scene organic unifies in together and makes a panoramic image can be as the change of seasons in the real scene and real-time change, enhance the sense of the reality of the system and user immersive.A 4-tuple (y, x, v, w) in a graph is a 3-arc if each of (y, x, v) and (x, v, w) is a path. The 3-arc graph of H is the graph with vertex set all arcs of H and edge set containing all edges joining xy and vw whenever (y, x, v, w) is a 3-arc of H. A Hamilton cycle is a closed path meeting each vertex of a graph. A graph H including a Hamilton cycle is called Hamiltonian and H has a Hamiltonian decomposition provided its edge set admits a partition into disjoint Hamilton cycles (possibly with a single perfect matching). The current paper proves that every connected 3-arc graph consists of more than one Hamilton cycle. Since the 3-arc graph of a cubic graph is 4-regular, it further proves that each 3-arc graph of a cubic graph in a certain family has a Hamiltonian decomposition.Crowdsourcing has become a new distributed paradigm, which uses online crowds to solve complex problems. Recently, in order to reduce the development workload and research threshold of crowdsourcing applications, crowdsourcing process modeling is attracting more and more attention. However, complex crowdsourcing processes used for creative and open-ended work have remained out of reach for process modeling, because this type of process usually has a dynamic execution, in which the type, number, and order of tasks and subtasks are often unknown in advance but are determined dynamically at runtime. In this paper, we propose a modeling approach and supporting framework to fill this gap. Specifically, we provide a task model composition to allow task creation on demand, while collaborating on tasks in a tree structure to adapt to the dynamic execution. Moreover, we introduce a set of message communication modes to support data exchange among tasks. Finally, we construct a framework named CrowdModeller to embody this approach. Through two evaluations, we demonstrate its effectiveness.Traditional training methods such as card teaching, assistive technologies (e.g., augmented reality/virtual reality games and smartphone apps), DVDs, human-computer interactions, and human-robot interactions are widely applied in autistic rehabilitation training in recent years. In this article, we propose a novel framework for human-computer/robot interaction and introduce a preliminary intervention study for improving the emotion recognition of Chinese children with an autism spectrum disorder. The core of the framework is the Facial Emotion Cognition and Training System (FECTS, including six tasks to train children with ASD to match, infer, and imitate the facial expressions of happiness, sadness, fear, and anger) based on Simon Baron-Cohen's E-S (empathizing-systemizing) theory. Our system may be implemented on PCs, smartphones, mobile devices such as PADs, and robots. The training record (e.g., a tracked record of emotion imitation) of the Chinese autistic children interacting with the device implementedom other countries, children with different cultural/sociological/linguistic contexts should be recruited in future studies.Adding the adequate level of security of information systems dealing with sensitive data, privacy, or defense systems involves some form of access control. The audits performed are dealing with the determination of the allowed activities of the legal users, when attempting to access resources of the system. Usually, full access is provided after the user has been successfully authenticated through an authentication mechanism (e.g., password), while the corresponding authorization control is based on the confidentiality level of the respective resources and the authorization level assigned to each user. A very important diversification occurring in modern digital technologies is related to the identification based on blockchain technology, which is presented as a public, distributed data series, unable to modify its history and grouped in time-numbered blocks. In this work, a blockchain-based verifiable user data access control policy for secured cloud data storage is suggested for a version associated with big data in health care. It is an innovative system of applying classified access policies to secure resources in the cloud, which operates based on blockchain technology. System evaluation is carried out by studying a case in its resilience to Eclipse attack under different malicious user capabilities for routing table poisoning.In practice, PE teaching evaluation based on probabilistic convolutional neural network still faces some practical problems. At present, the existing research mainly focuses on how to improve the accuracy of PE (physical education) teaching evaluation, but ignores the balance between accuracy and speed of the model, which is the key to achieve efficient PE teaching estimation. Aiming at the problem of optimization contradiction existing in the traditional probabilistic stochastic convolution neural network regression method, a position adaptive probabilistic stochastic convolution neural network regression method was proposed. Firstly, the basic principle of probabilistic and random convolution neural network regression method is given. Secondly, the contradiction and reasons between hot trial regression and coordinated regression are analyzed. It is found that the process heat will return to the optimization with irreconcilable contradiction with the coordinates due to the lack of learning parameters when thpractical tool for PE teaching quality evaluation.Heilongjiang Province is the main grain producing region in China and an important part of Northeast China Plain, which is one of the three black soil belts in the world. The cultivated region of black soil accounts for 50.6% of the black soil region in Northeast China. Due to the obvious rise of temperature and uneven distribution of precipitation in the 20th century, it has been considered to be one of the important reasons for agricultural drought and aridity. Under the background of climate change, understanding the multiyear changes and occurrence characteristics of cultivated land drought in different agricultural regions in Heilongjiang Province is of great significance for the establishment of agricultural drought prediction and early warning system in the future, guiding agricultural high-standard farmland irrigation in different regions, promoting black soil protection, and then improving grain yield. This paper calculates the temperature vegetation drought index (TVDI) based on the normalized diffenal food security. At the same time, severe drought will affect the terrestrial ecosystem, resulting in the distribution of crops and microorganisms, and the transformation between carbon sink and carbon source.

To explore the effect of applying Dahuang Zhechong pills (DHZCP) from

to patients with early-to-mid prostate cancer undergoing radical resection and carry out a theoretical clinical study of traditional Chinese medicine (TCM) to verify the effect of DHZCP formula under the guidance of TCM theory.

The clinical data of 98 patients with early-to-mid prostate cancer undergoing radical resection treated in our hospital (July 2014 to July 2016) were selected for the retrospective analysis, and the patients were divided into group A (

 = 49, routine hormonal therapy) and group B (

 = 49, routine hormonal therapy plus DHZCP) according to the double blind method, so as to compare the trauma symptoms, cancer recurrence rate, etc., after treatment between the two groups.

Compared with group A, group B obtained significantly higher total effective rate of complication treatment at different time points (

 < 0.05), significantly lower mean HAMA score after treatment (

 < 0.05), and significantly lower total recurrence rate (

 < 0.