Within the next several years, there will be a high level of autonomous technology that available for widespread use, which reduce labor costs, increase safety, save energy, enable difficult unmanned tasks in harsh environments, and eliminate human error. Compared to software development other vehicles, maritime development, especially aging but still functional fleets, is described as being very early emerging phase. This presents great challenges opportunities researchers engineers develop...

Recently the research community has believed that an e-learning ecosystem is next generation e-learning. However, current models of ecosystems lack support underlying infrastructures, which can dynamically allocate required computation and storage resources for ecosystems. Cloud computing a promising infrastructure provides as services. Hence, this paper introduces into its infrastructure. In paper, based on presented. related mechanisms allow stability, equilibrium, efficient resource use,...

With the emergence of smartphones and location-based services, user mobility prediction has become a critical enabler for wide range applications, like advertising, early warning systems, citywide traffic planning. A number techniques have been proposed to either conduct spatio-temporal or forecast next-place. However, both produce diverse performance different users display poor some users. This paper focuses on investigating effect living habits models next-place prediction, selects one...

Smart devices bring us the ubiquitous mobile accessing to Internet, making Internet grow rapidly. Using traffic data collected at core metropolitan 2G and 3G networks of China over a week, this paper studies user behavior from three aspects: 1) usage; 2) mobility pattern; 3) application usage. We classify users into different groups study resource consumption in Internet. observe that heavy high tend consume massive radio resources simultaneously. Both usage pattern are closely related...

Due to the pervasiveness of mobile devices, a vast amount geolocated data is generated, which allows us gain deep insight into human behavior. Among other sources, analysis traffic from Internet enables study subscribers' movements over long time periods at large scales, paramount research wide range disciplines, e.g., sociology, transportation, epidemiology, networking, etc. However, efficiently analyze massive view user mobility, several technical challenges have be tackled before...

Call admission control (CAC) plays a significant role in providing the desired quality of service (QoS) cellular networks. We investigate pricing as an additional dimension call process order to efficiently and effectively use wireless network resources. First, we prove that, for given network, there exists new arrival rate which can maximize total utility users while maintaining required QoS. Based on this result observation, propose integrated scheme where price is adjusted dynamically...

Power-aware routing in Wireless Sensor Networks (WSNs) is designed to adequately prolong the lifetime of severely resource-constrained ad hoc wireless sensor nodes}. Recent research has identified energy hole problem single sink-based WSNs, a characteristic many-to-one (convergecast) traffic patterns. In this paper, we propose HYbrid Multi-hop routiNg (HYMN) algorithm, which hybrid two contemporary multi-hop algorithm architectures, namely, flat that utilizes efficient transmission...

Cloud platforms offer resource utilization as on demand service, which lays the foundation for applications to scale during runtime. However, just-in-time scalability is not achieved by simply deploying cloud platforms. Existing approaches require developers rewrite their leverage on-demand utilization, thus bind specific infrastructure. In this paper, profiles are used capture expertspsila knowledge of scaling different types applications. The profile-based approach automates deployment and...

Due to the booming industry of location-based services, analysis human location histories is increasingly important. Next prediction essential many services. Predicting user's next usually involves obtaining significant places from history trajectories and predicting with a certain statistic model. This paper presents new approaches deal both above problems. For former problem, hierarchical clustering algorithm proposed. We first identify specific features stay points then group GPS...

With the increasing cases of thyroid malignant tumors, diagnosis nodule has attracted more and attention. Deep learning achieved promising results in computer-aided due to advantages obtaining high-dimensional features. In this paper, we proposed a hybrid multi-branch convolutional neural network based on feature cropping method for extraction classification ultrasound images. Firstly, designed backbone extract shared maps as global branch. Next, added branch perform multi-cropping batch...

Touchscreen IoT devices, such as smartphones and tablets, have been seamlessly integrated into our daily lives. Drawing sketches on the touch screen is an extremely convenient mode of interaction, when combined with generative AI, it makes customized data generation digital twin based devices more straightforward. However, scarcity free-hand sketch construction data-driven AI models a thorny issue. Despite emergence some large-scale datasets, these datasets primarily consist at single-object...

Introduction The three dimensions of the tobacco silk components (cut stem, silk, reconstituted shred, and expanded silk) cigarettes directly affect cigarette combustibility; by accurately measuring different silks in cigarettes, it is possible to optimize combustibility reduce production harmful substances. Identifying shred a prerequisite for three-dimensional measurement. two-dimensional image method can identify measure its characteristics but cannot determine thickness. This study...

Mango leaf disease segmentation is an essential foundation for accurate diagnosis and intelligent grading. The size shape of mango diseases vary significantly at different times, making it difficult mainstream semantic methods to segment areas accurately. Therefore, this paper proposes a method called MAU-Net fine over the whole period. based on traditional Unet architecture, integrates Self-Aligning Attention Feature Fusion (SAFF) module Multiscale Enhancement (MFE) module, designs new loss...

With the rapid development of urban rail transit, floating slab vibration isolation system has become widely used in field due to its effective reduction and capabilities. Traditional vibration-isolation systems mainly focus on blocking transmission, neglecting energy harvesting. This paper proposes a magnetic-coupled double-wing negative stiffness harvester for slabs. A single-wing piezoelectric beam model finite element module are established. The modal output characteristics analyzed....

Diffusion-weighted magnetic resonance imaging (DWI) is sensitive to acute ischemic stroke and a common diagnostic method for the stroke. However, result relies on visual observation of neurologists which may vary from doctor under different circumstance. And manual segmentation often time-consuming subjective process. The time onset thrombus removal has significant impact prognosis patients with shorter time, better prognosis. For this purpose we present novel framework quickly automatically...

Real-time target detection plays an important role in campus intelligent surveillance systems. This paper introduces Soft-NMS, GSConv, Triplet Attention, and other advanced technologies to propose a lightweight pedestrian vehicle model named SGST-YOLOv8. In this paper, the improved YOLOv8 is trained on self-made dataset, tracking algorithm combined achieve accurate efficient real-time system. The achieved accuracy of 88.6%, which 1.2% higher than baseline YOLOv8. Additionally, mAP0.5:0.95...

Smart devices bring us ubiquitous mobile access to the Internet, making it possible surf Internet in environments. With pervasiveness of much evidence shows that human mobility has heavy impact on app usage behavior. However, relationship between them not been quantified any form. In this article, a rating framework is presented demonstrate existence their connection. The core idea selects most significant features may influence particular, we focus three aspects urban areas: individual...

Element detection is an important step in the process of non-destructive testing printed circuit boards (PCB) based on computed tomography (CT). Compared with traditional manual method, image semantic segmentation method deep learning greatly improves efficiency and accuracy. However, models often require a large amount data for supervised training to generalize better model performance. Unlike natural images, PCB CT annotation task more time-consuming laborious than task. In order reduce...

The recent explosion of data traffic calls for specialized systems to monitor the status networks. Traditionally, Internet service providers collect and analyze IP flow as they present an aggregated view traffic. In era mobile big data, new approaches are required address challenges regarding characterization in next generation wireless this article, we propose a framework referred FMBD, which provides massive collection, storage, processing, analysis, management functions, cope with...

Linking online identities of users among countless heterogeneous network services on the Internet can provide an explicit digital representation users, which benefit both research and industry. In recent years, user identity linkage (UIL) through has become emerging task with great potential many challenges. Existing works mainly focus social networks that consider inconsistent profiles, content, as features or use sparse location-based data sets to link behaviors a real person. To extend...