Pulmonary infection is a common clinical respiratory tract infectious disease with a high incidence rate and a severe mortality rate as high as 30%–50%, which seriously threatens human life and health. Accurate and timely anti-infective treatment is the key to improving the cure rate. NGS technology provides a new, fast, and accurate method for pathogenic diagnosis, which can provide effective clues

This study was to analyze the sport-induced ankle joint injury (AJI) images based on the neural network algorithms using the magnetic resonance imaging (MRI). 20 patients and 20 volunteers were included in the experimental and control groups, respectively. The hybrid diffusion equation (HDE) neural network (HDENN) algorithm was compared with the fully convolutional neural network (FCNN) and the FCNN

Recently, massive online academic resources have provided convenience for scientific study and research. However, the author name ambiguity degrades the user experience in retrieving the literature bases. Extracting the features of papers and calculating the similarity for clustering constitute the mainstream of present name disambiguation approaches, which can be divided into two branches: clustering

This study was carried out to explore the promotion role of computed tomography (CT) imaging three-dimensional (3D) reconstruction technology and rapid rehabilitation nursing intervention (RRNI) in the treatment of patients with renal cell cancer (RCC) laparoscopic radical nephrectomy (LRN) in view of the patient’s condition. 98 RCC patients who were admitted to the hospital from July 2019 to July

This study was to analyze the diagnostic value of magnetic resonance imaging (MRI) for gastric cancer (GC) lesions and the treatment effect of complete laparoscopic radical resection (CLSRR). A malignant tumor recognition algorithm was constructed in this study based on the backprojection (BP) and support vector machine (SVM), which was named BPS. 78 GC patients were divided into an experimental group

Due to the explosive growth trend of cross-border e-commerce, a series of problems such as high transportation costs and insufficient publicity are to be solved urgently by researching on supply chain from both decision-making and coordination perspectives. Under the four-incomplete cooperative Stackelberg decision-making modes of cross-border e-commerce supply chain members, the transportation cost

The aim of this paper is to present a design of a metaheuristic search called improved monkey algorithm (MA+) that provides a suitable solution for the optimization problems. The proposed algorithm has been renewed by a new method using random perturbation (RP) into two control parameters (p1 and p2) to solve a wide variety of optimization problems. A novel RP is defined to improve the control parameters

With the rapid development of the Internet, network attacks often occur, and network security is widely concerned. Searching for practical security risk assessment methods is a research hotspot in the field of network security. Network attack graph model is an active detection technology for the attack path. From the perspective of the attacker, it simulated the whole network attack scenario and then

Nowadays, the method of simple-feature extraction has been extensively studied and is used in PPG biometric recognition; some promising results have been reported. However, some useful information is often lost in the process of PPG signal denoising; the time-domain, frequency-domain, or wavelet feature extracted is often partial, which cannot fully express the raw PPG signal; and it is also difficult

Education is an area where innovation moves slowly. In this study, we will propose a framework with a novel approach that will support the development of a multi-interactive chatbot’s system for an educational area using AIML 2.0. The system will facilitate the students for their learning towards an outcome-based education domain. The proposed framework will be composed of a user module which consists

During the venture capital development, replacing the management work team or keeping up the status quo is a key strategy choice for venture capitalist and venture entrepreneur about the long-term development of enterprise and the control right transferring. In fact, the contract designing focuses on the distribution of cash flow to encourage both efforts in order to avoid double moral hazard, and

MicroRNAs are a group of noncoding RNAs that are about 20–24 nucleotides in length. They are involved in the physiological processes of many diseases and regulate transcriptional and post-transcriptional gene expression. Therefore, the prediction of microRNAs is of great significance for basic biological research and disease treatment. MicroRNA precursors are the necessary stage of microRNA formation

Clustering web services is an effective method to solving service computing problems. The key insight behind it is to extract the vectors based on the service description documents. However, the brevity of natural language service description documents typically complicates the vector construction process. To circumvent the difficulty, we propose a novel web service clustering method to vectorize documents

In transfer learning, two major activities, i.e., pretraining and fine-tuning, are carried out to perform downstream tasks. The advent of transformer architecture and bidirectional language models, e.g., bidirectional encoder representation from transformer (BERT), enables the functionality of transfer learning. Besides, BERT bridges the limitations of unidirectional language models by removing the

Infrequent behaviors of business process refer to behaviors that occur in very exceptional cases, and their occurrence frequency is low as their required conditions are rarely fulfilled. Hence, a strong coupling relationship between infrequent behavior and data flow exists. Furthermore, some infrequent behaviors may reveal very important information about the process. Thus, not all infrequent behaviors

Microscopic examination of peripheral blood smears and bone marrow is the preliminary step for the diagnosis of several life-threatening diseases. Acute lymphocytic leukemia (ALL) is the most common disease in children that also needs an early diagnosis for on-time treatment as it spreads rapidly in the blood and forms immature lymphocytes. This might cause death in some weeks if left untreated. Manual

Since the declaration of COVID-19 as a pandemic, the world stock markets have suffered huge losses prompting investors to limit or avoid these losses. The stock market was one of the businesses that were affected the most. At the same time, artificial neural networks (ANNs) have already been used for the prediction of the closing prices in stock markets. However, standalone ANN has several limitations

Because the sensors are constrained in energy capabilities, low-energy clustering has become a challenging problem in high-density wireless sensor networks (HDWSNs). Usually, sensor nodes tend to be tiny devices along with constrained clustering abilities. To have a low communication energy consumption, a low-energy clustering scheme should be designed properly. In this work, a new cloned chaotic parallel

Objective. Infantile hemangioma (IH) is the most common infantile benign tumor derived from endothelial cells (ECs). The mechanism of IH degeneration into fibroadipose tissue is still unclear. We aimed to explore the effects of endothelial mesenchymal transformation (EndMT) on IH and explore its underlying mechanism. Methods. HemECs were treated with different concentrations of transforming growth

The development of industrial Internet of Things (IIoT), big data, and artificial intelligence technologies is leading to a major change in the production system. The change is being propagated into the wave of transforming the existing system with a vertical structure into the corresponding horizontal platform or middleware. Accordingly, the way of acquiring IIoT data from an individual system is

Aiming at the real-time requirements for industrial control systems, we proposed a corresponding trust chain method for industrial control system application software and a component analysis method based on security sensitivity weights. A dynamic length trust chain structure is also proposed in this paper. Based on this, the industrial control system software integrity measurement method is constructed

In recent years, video production has become one of the key challenges for researchers in the area. In the face of the poor video effects of earlier video production methods and approaches, this study has considered the MOOC-based microclass combined with the MOOC video production method for improving the video production effect. According to the idea of MOOC, based on the early design stage and shooting

In the digital information age, data mining technology is becoming more widely used in libraries for its useful impact. In the context of big data, how to efficiently mine big data, extract features, and provide users with high-quality personalized service is one of the important issues that needs to be solved in the current university library big data application. Brain computing is a kind of comprehensive

In this paper, we focus on recognizing epileptic seizure from scant EEG signals and propose a novel transfer enhanced -expansion move (TrEEM) learning model. This framework implants transfer learning into the exemplar-based clustering model to improve the utilization rate of EEG signals. Starting from Bayesian probability theory, by leveraging Kullback-Leibler distance, we measure the similarity relationship

Cultural tourism has gained much attention in the last decade and has promoted the preservation of a variety of tangible and intangible assets of culture. In order to accurately predict the cultural tourism passenger flow in the Yangtze River Delta and improve its economic benefits, this paper designs the prediction model of cultural tourism passenger flow in the Yangtze River Delta based on regression

Crude oil is the main raw material for the petrochemical industry and a major component of total production costs. It is also an indispensable resource for petrochemical enterprises. The implementation of crude oil e-commerce procurement by petrochemical enterprises can not only reduce the procurement cost of crude oil but also create good economic benefits in the field. It can also establish strategic

The revolution in software development is increasing with the use of advanced techniques and tools. Software development organizations are considering standards, methods, approaches, and tools to support them in maintaining the effectiveness of software. An effective implementation of software process improvement (SPI) is important in order to gain effectiveness in the software industry. Disasters

Retinal blood vessels are the only deep microvessels in the blood circulation system that can be observed directly and noninvasively, providing us with a means of observing vascular pathologies. Cardiovascular and cerebrovascular diseases, such as glaucoma and diabetes, can cause structural changes in the retinal microvascular network. Therefore, the study of effective retinal vessel segmentation methods

With the continuous development of economy, the number of motor vehicles has increased sharply, and urban traffic congestion has become more and more frequent. Urban traffic congestion has become one of the important reasons that hinder the continuous development of major cities. In order to better solve the problem of urban traffic congestion, it is more urgent to build urban intelligent transportation

Glioma is one of the most common and deadly malignant brain tumors originating from glial cells. For personalized treatment, an accurate preoperative prognosis for glioma patients is highly desired. Recently, various machine learning-based approaches have been developed to predict the prognosis based on preoperative magnetic resonance imaging (MRI) radiomics, which extract quantitative features from

Wireless sensor network (WSN) is usually organized in a particular area for achieving some specific tasks and functions. It has broad application prospects in military, environmental monitoring, disaster relief, and other many commercial areas. Measuring the significance of distributed nodes is the foundation of many applications of WSN. Therefore, this paper studies the distributed node measurement

Software process improvement methodologies support to incessantly regulate and advance the process of software for its performance development. This development arises in terms of software product quality, time, changes reduction, and so on. The aim of software process improvement is to make software process effective and to increase quality of software product through continuous evaluation. Various

Convolutional neural networks (CNNs) require significant computing power during inference. Smart phones, for example, may not run a facial recognition system or search algorithm smoothly due to the lack of resources and supporting hardware. Methods for reducing memory size and increasing execution speed have been explored, but choosing effective techniques for an application requires extensive knowledge

Long-distance transportation systems play an important role in economic growth. Yet, these systems are incurred with multifaceted delays and cost problems. The major incites affecting transportation systems are congestion, breakdowns, emergencies, and inclement weather. Scarcity of information about the environment also exacerbates travel problems. It is essential to employ monitoring and guidance

Accurate measurement of the critical buckling stress is crucial in the entire field of structural engineering. In this paper, the critical buckling load of Y-shaped cross-section steel columns was predicted by the Artificial Neural Network (ANN) using the Levenberg-Marquardt algorithm. The results of 57 buckling tests were used to generate the training and testing datasets. Seven input variables were

The novel coronavirus (COVID-19) outbreak produced devastating effects on the global economy and the health of entire communities. Although the COVID-19 survival rate is high, the number of severe cases that result in death is increasing daily. A timely prediction of at-risk patients of COVID-19 with precautionary measures is expected to increase the survival rate of patients and reduce the fatality

Feature selection (FS) is a fundamental task for text classification problems. Text feature selection aims to represent documents using the most relevant features. This process can reduce the size of datasets and improve the performance of the machine learning algorithms. Many researchers have focused on elaborating efficient FS techniques. However, most of the proposed approaches are evaluated for

The existing grey relational clustering method has limitations in the application of multidimensional sequences and cannot directly calculate the grey correlation degree between unequal-length sequences. In this paper, by introducing the multidimensional dynamic DTW distance into the existing 3D grey relational model, a new grey relational analysis model that can be applied to multidimensional data

A synthetic aperture radar (SAR) target classification method has been developed, in the study, based on dynamic target reconstruction. According to SAR azimuthal sensitivity, the truly useful training samples for the reconstructing the test sample are those with approaching azimuths and same labels. Hence, the proposed method performs linear presentation of the test sample on the local dictionary

With the rapid development of information technology, the integration of multimedia technology and traditional institutional systems is increasing. However, at present, the establishment and construction of the higher education system in China are not proportional, the function is vague, and the communication efficiency is not high. The reason for this phenomenon is that the traditional higher education

Volume calculation from 3D point cloud is widely used in engineering and applications. The existing methods either have large errors or are time-consuming. This paper focuses on the coal measurement. Based on the triangular mesh generated from the point cloud, each triangle is projected downward to the base plane to form a voxel. We derive the calculation formula of voxel by an integral method, which

Floods after monsoon rains are frequent disasters that affect millions of lives in Pakistan. Human lives are lost, agriculture economies are destroyed, and livestock animals, houses, fruit farms, and crops are lost which are the major livelihoods of thousands of people in Punjab. Each year there are heavy rains in the monsoon season and, due to global warming, there is the rapid melting of snow in

Online posts have gradually become a major carrier of network public opinion in social media, and the social network hotspots are the important basis for the study of network public opinion. Therefore, it is significant to extract hotspots for monitoring Internet public opinion from online posts textual big data. However, the current hotspot extraction methods are focused on the users’ features that

Aiming at the diversified requirements of network application QoS (Quality of Service) in the terminal equipment of Internet of Vehicles, this paper proposes a distributed congestion control strategy based on harmony search algorithm and the Throughput Evaluation Priority Adjustment Model (TEPAM) to ensure real-time transmission of high-priority data messages related to security applications. Firstly

In this research, we study an extended version of the joint order batching and scheduling optimization for manual vegetable order picking and packing lines with consideration of workers’ fatiguing effect. This problem is faced by many B2C fresh produce grocers in China on a daily basis which could severely decrease overall workflow efficiency in distribution center and customer satisfaction. In this

Aim. This study aims to compare the postoperative analgesia between preoperative and postoperative ultrasound-guided transversus abdominis plane (TAP) blocks for different durations of laparoscopic gynecological surgery. Methods. A total of 120 patients, ASA I-III, 18–65 years of age, were divided randomly into 2 groups: preoperative TAP group (pre-TAP group) and postoperative TAP group (post-TAP group)

Precision agriculture is now essential in today’s world, especially for countries with limited water resources, fertile land, and enormous population. Smart irrigation systems can help countries efficiently utilize fresh water and use the excess water for barren lands. Smart water management platform (SWAMP) is an IoT-based smart irrigation project designed for efficient freshwater utilization in agriculture

A successful football team not only consists of more than a dozen people on the field but also includes a complete training, analysis, coaching team behind it, and the same basic education and youth training system. With the development of scientific concepts and the advancement of computer technology, more people have begun to study the use of modern technology to replace part of the traditional human

The development of green transportation technologies in China has grown rapidly due to increasing concerns about climate change and environmental pollution. Collaboration innovations covering kinds of participating entities and various linked relationships have become one of the critical drivers for the transportation sector. Some researchers have analysed the collaborative innovation of scientific

Support vector machines (SVMs) are designed to solve the binary classification problems at the beginning, but in the real world, there are a lot of multiclassification cases. The multiclassification methods based on SVM are mainly divided into the direct methods and the indirect methods, in which the indirect methods, which consist of multiple binary classifiers integrated in accordance with certain

When SaaS software suffers from the problem of response time degradation, scaling deployment resources that support the operation of software can improve the response time, but that also means an increase in the costs due to additional deployment resources. For the purpose of saving costs of deployment resources while improving response time, scaling out the SaaS software is an alternative approach

Information security is defined as preventing actions such as unauthorized access and use, modification, and removal of information. It consists of certain basic elements of confidentiality, integrity, and accessibility. There are numerous studies in published literature which have been conducted to ensure information security. However, there is no previous study that covers these three basic elements

In recent years, competitive aerobics has been rapidly popularized and developed, and the level of sports skills has also been greatly improved. The performance of some events has gradually approached and reached the advanced level. Therefore, it is vital to invest in the quantitative analysis and cross-disciplinary comprehensive research of aerobics performance and related factors. This paper adopts

Text-to-image synthesis is an important and challenging application of computer vision. Many interesting and meaningful text-to-image synthesis models have been put forward. However, most of the works pay attention to the quality of synthesis images, but rarely consider the size of these models. Large models contain many parameters and high delay, which makes it difficult to be deployed on mobile applications

In this digital era of technology and software development tools, low-cost digital cameras and powerful video editing software (such as Adobe Premiere, Microsoft Movie Maker, and Magix Vegas) have become available for any common user. Through these softwares, editing the contents of digital videos became very easy. Frame duplication is a common video forgery attack which can be done by copying and

Cloud-based ERP solutions offer many benefits to small and medium enterprises (SMEs) and help them to integrate their activities, such as improve communications and reduce operational and maintenance costs. Primarily, it was only adopted by large organizations, but now SMEs are also keen on adoption. However, the motivation regarding the adoption of these systems in SMEs is relatively low in developing

This study aims to investigate the molecular mechanism of LncRNA NKILA underlying promoting cardiomyocytes apoptosis and relevant diabetic cardiomyopathy. We utilized high concentration of glucose to induce human cardiomyocytes cell line AC16 to imitate diabetic cardiomyopathy. And then, we performed high-throughput big data analysis, RT-PCR, and western blot assays to evaluate the expression levels

This paper proposes a perceptual medical image fusion framework based on morphological component analysis combining convolutional sparsity and pulse-coupled neural network, which is called MCA-CS-PCNN for short. Source images are first decomposed into cartoon components and texture components by morphological component analysis, and a convolutional sparse representation of cartoon layers and texture

This study focuses on the coastal features, environments, and dynamics to accurately describe and regularly monitor the Qingdao shoreline in eastern China. It collects categorical ETM+ and OLI data from 2000, 2010, and 2019 on the mainland coastline and explores the characteristics and spatiotemporal differences across the past 19 years by using remote sensing and geographic information system (GIS)

High-Efficiency Video Coding provides a better compression ratio compared to earlier standard, H.264/Advanced Video Coding. In fact, HEVC saves 50% bit rate compared to H.264/AVC for the same subjective quality. This improvement is notably obtained through the hierarchical quadtree structured Coding Unit. However, the computational complexity significantly increases due to the full search Rate-Distortion