In traffic accident, an accurate and timely severity prediction method is necessary for the successful deployment of intelligent transportation system to provide corresponding levels medical aid in a manner. The existing accident's methods mainly use shallow models statistical models. To promote accuracy, novel prediction-convolutional neural network (TASP-CNN) model proposed that considers combination relationships among features. Based on weights features, feature matrix gray image (FM2GI)...

Digital twin technology, a new type of digital technology emerging in recent years, realizes real-time simulation, prediction and optimization by digitally modeling the physical world, providing idea method for design, operation management water conservancy projects, which is great significance realization transformation informatization to intelligent conservancy. In view this, this paper systematically discusses concept development history smart conservancy, compares its differences with...

Summary Cloud services are open, shared, and complex. These characteristics will lead to many security risks affect the development of cloud services. Therefore, it is necessary identify measure However, there still deficiencies in this area. In light this, paper carries out an in‐depth study from perspective technical risk. Firstly, combines three aspects on service problems, objectives, technologies. It attempts explore technological solutions get risk problems achieve expected goals,...

Crop diseases pose a major threat to agricultural production, quality, and sustainable development, highlighting the importance of early disease risk prediction for effective control. Tea anthracnose can easily occur in Yunnan under high-temperature high-humidity environments, which seriously affects ecosystem tea gardens. Therefore, establishment accurate, non-destructive, rapid models has positive impact on conservation biodiversity plantations. Because linear relationship between...

A digital twin is a new trend in the development of current smart water conservancy industry. The main research content intelligent clarified. This paper first summarizes and combs relevant system architecture conservancy, puts forward framework based on twins, highlighting characteristics virtual real interaction, symbiosis platform. Secondly, status quo “sky, air, ground water” integrated monitoring technology, big data artificial intelligence, model platform knowledge graph security...

Deep learning models are widely used in crop leaf disease image recognition. These can be divided into two categories: global model and local model. The directly takes the whole images as input to training It achieve end-to-end recognition, which is very convenient use. But this kind of cannot accurately completely extract features from small diseased spots image. Before recognizing, needs part by segmentation technology. Then Features extracted more accurate complete. will bring additional...

The abundance of event data in current software configuration management systems makes it possible to discover process models automatically by using actual observed behavior. However, traditional mining algorithms cannot be applied logs recorded (SCM) systems, such as SVN, because missing activity attributes. To address this problem, a classifier is proposed build event-activity mapping relationships from development streams, revealing attributes and associating the original SVN log....

Software knowledge community contains a large scale of software entities with complex structure and rich semantic relations. Semantic relation extraction is critical task for graph construction, which has an important impact on based tasks such as document generation expert recommendation. Due to the problems entity sparsity, ambiguity, lack annotated dataset in user-generated content community, it difficult apply existing methods domain. To address these issues, we propose novel model...

<title>Abstract</title> The index weight determines the scientificity and rationality of comprehensive evaluation results. However, traditional calculation method, which is scored directly by decision-makers, excessively depends on degree experience knowledge accumulation decision-makers. Different decision-makers’ understandings have great differences fuzziness, makes results biased or even wrong due to influence human subjective factors. To solve this problem, paper considers that value...

Urban–Rural Water supply integration is one of the effective ways to address rural drinking water safety issues. With rapid economic development and urbanization, gap between urban has become increasingly evident, areas face severe challenges such as insufficient sources substandard quality. Yunnan Province, due its unique topography natural environment, encounters numerous difficulties in promoting construction urban–rural integration, there a lack research specifically focused on...

Background: Problems of cloud user privacy leaks have already hindered the further development computing, as described in various patents. Therefore, comprehensive analysis and measurement computing risks factors is an effective way to control identify risks. However, researches about this issue not yet been discovered, so relevant issues focused paper. Methods: This paper combines Analytic Hierarchy Process(AHP) with Information Entropy theory measure security computing. Results: constructs...

Background: Event log data generated in the software development process contains historical information and future trends activities. The mining analysis of event contribute to identify discover activities provide effective support for modeling. Methods: Firstly, a deep learning model (Word2vec) was used feature extraction vectorization logs. Then, K-means clustering algorithm measure silhouette coefficient intra-cluster SSE were effect evaluation vectorized Results: This paper obtained...

Background: The most important question about the application and development of cloud computing is privacy risk, as it has become key factor for users in selecting services. In order to have a better understanding resolve or make controllable an acceptable range, risk assessment very necessary. However, specialized research on not yet been found. Methods: This paper used Information Entropy Theory Fuzzy Set evaluate security risk. Results: analyzes actuality combs number risks basis digging...

Software is rapidly evolving and operates in a changing environment; therefore, addition to software design testing, it essential observe understand the execution behavior by modeling data recorded during of improve its reliability. The nested call relationship between methods common, but most process-mining are unable discover them, only generating flat models with low fitness. Meanwhile, easy generate “spaghetti-like” comprehensibility when dealing complex data. This paper proposes...

The current algorithm for detecting drift in the business process can only detect of log multi-instance. However, generated software development is mainly single-instance. Hence, this paper proposes an sudden First, we apply LDA topic model extraction to obtain Then location point single-instance be detected according change lowest frequency direct successor relation. Finally, numbers actual points were obtained by corresponding original data. Multiple sets simulated data evaluate algorithm....

Abstract The text of software knowledge community contains abundant engineering field. triplet can be extracted automatically and efficiently to form the graph, which is helpful for knowledge-centric intelligent applications, such as question answering, automatic document generation expert recommendation. Most existing methods are confronted with problems task dependence entity overlap. In this paper, we propose a extraction method based on span-level contrastive learning. From level...