Understanding the private car aggregation effect is conducive to a broad range of applications, from intelligent transportation management urban planning. However, this work challenging, especially on weekends, due inefficient representations spatiotemporal features for such and considerable randomness mobility weekends. In article, we propose deep learning framework attention network (STANet) with neural algorithm logic unit (NALU), so-called STANet-NALU, understand dynamic cars...

In this paper, with the aims of alleviating pressure from shortage spectrum resource and addressing inefficient utilization, we investigate sharing for moving vehicles in Heterogeneous Vehicular Networks (HVNs) consisting macrocells Road Side Units (RSUs) Cognitive Radio (CR) technology. We first propose an incentive mechanism encouraging to share vehicle users, which CR-enabled RSUs perform sensing availability surrounding urban environments. Furthermore, downlink allocation users...

In this paper, we propose a new paradigm of GPS and OBD Integration (GOI) based on receiver on-board diagnostics (OBD) reader, which offers feasible way for large-scale trajectory collection especially suitable private cars. With GOI, adopt to obtain vehicle location design low-cost reader retrieve the driving information, such as velocity steering direction from in-vehicle motion sensors through interface. order deal with inherent errors outage issue, positioning approach by employing...

Vehicle state including location and motion information plays an important role in various applications such as Internet of Vehicles (IoV), autonomous cars, driving safety monitoring. Achieving accurate vehicle is a challenging task those due to the noise disturbances. Recent studies suggest that not generally Gaussian distributed many physical environments can be handled more accurately non-Gaussian rather than model. Inspired by this observation, we strive improve estimation investigating...

Convolutional neural networks (CNNs) have achieved remarkable performance in driver drowsiness detection based on the extraction of deep features drivers' faces. However, methods decreases sharply when complications, such as illumination changes cab, occlusions and shadows driver's face, variations head pose, occur. In addition, current are not capable distinguishing between states, talking versus yawning or blinking closing eyes. Therefore, technical challenges remain detection. this...

In order to provide a robust estimate of vehicle position in all environments, especially, challenging urban areas where GPS signals are blocked, fusion framework based on sparse Gaussian-Wigner prediction (SG-WP) is proposed. This new approach combines the advantages both random matrix theory and property enhanced localization capabilities. this method, measurement noises assumed be non-Gaussian distributed, generalized error distribution adopted as an approximation densities. To ensure...

A road network is a critical aspect of both urban planning and route recommendation. This article proposes an efficient approach to build fine-grained based on sparsely sampled private car trajectory data under complex environment. In order resolve difficulties introduced by low sampling rate data, we concentrate sample points around intersections utilizing the turning characteristics from large-scale ensure accuracy detection segments. front networks including many intersections, such as...

In this paper, we investigate the precoder design for multiple-input multiple-output (MIMO) dual-functional radar-communication (DFRC) system with one-bit digital-to-analog converters (DACs). order to form beam-pattern, formulate precoding problem as a weighted optimization constant modulus constraint, which aims at minimizing average error power and guaranteeing radar waveform similarity. The is divided into three sub-problems corresponding multiple variables, i.e., factor, transmit signal...

Vehicle trajectory collection usually faces challenges such as inaccurate and incomplete data, mainly due to missing trajectories caused by Global Navigation Satellite System (GNSS) outages. In this paper, a novel ensemble transfer regression framework is proposed for urban environments with learning the primary solution constructing fine-grained dataset during GNSS First, motion information are fused training process. Then, regression-to-classification (R2C) process employed implement...

E-health holds significant potential to address healthcare challenges in the Democratic Republic of Congo (DRC), a nation grappling with limited resources, vast geographical distances, and fragile health system. This paper examines current state e-health implementation DRC, exploring existing initiatives, key achievements, persistent obstacles. While nascent, adoption is gaining momentum, driven by factors like increasing mobile phone penetration government recognition its potential....

In this paper, we investigate the problem of resource allocation and cross-tier interference mitigation in full-duplex orthogonal frequency division multiple access -based heterogeneous networks consisting macrocell underlaying femtocells. First, design a price mechanism to maximize utility both macro base station femtocell stations under finite constraint. We then propose triple optimization strategy for power control, subcarrier allocation, regulation mitigate interference. For macrocell,...

Short-term traffic flow prediction plays a crucial component in transportation management and deployment. In this paper, novel regression framework for short-term with automatic parameter tuning is proposed, the SVR being primary model Bayesian Optimization major method parameters selection. First, preprocessing of raw carried out by seasonal difference to eliminate non-stationary data. Then, Support Vector Regression trained pre-processed order optimize parameters, generalization...

This article aims to analyze the role of digital and e-learning systems in higher education Burundi. In this article, we used a semi-structured interview which got four interviewers who did with 343 students (ladies gentlemen) from different universities Burundi public private sectors various cities Results were recorded Kobo collect analyzed IBM SPSS Microsoft Office Excel. Findings show at an average only 16.3% our respondents confirm that there are ICT services institutions Students...

Recently, optical remote-sensing images have been steadily growing in size, as they contain massive data and complex backgrounds. This trend presents several problems for object detection, example, increased computation time memory consumption more false positives due to the backgrounds of large-scale images. Inspired by deep neural networks combined with time-frequency analysis, we propose a analysis-based detection method We utilize wavelet decomposition carry out transform then integrate...

In recent years, unmanned aerial vehicles (UAVs) have been widely used in various industries (e.g., search and rescue, express delivery, etc.) due to their high flexibility. addition, the deployment of UAVs equipped with mobile-edge computing (MEC) servers provide services at edges networks has become an emerging method. Under complex limited resource constraints, increasing total number computation bits system becomes a challenging problem. Motivated by this, this article, we propose...

With the fast development of urbanization and motorization, an increasing number people choose to buy private cars fulfill their daily travel needs. In particular, many from various positions city drive specified areas, then they will stop stay for a certain period time, leading spatiotemporal evolution urban area attractiveness (AA). this paper, we aim at understanding AA based on analyses car trajectory datasets. Specifically, by extracting point-of-stop (PoS) data trajectories, design...

With the tremendous amount of research publications online, finding relevant ones for a particular topic can be an overwhelming task. As solution, papers recommender systems have been proposed to help researchers find their interested or related fields. Most existing recommendation approaches are based on paper collections, citations and user profile which is not always available (not all users registered with profiles). The assume that already published in systems. Consequently, this...

Achieving reliable intervehicle positioning is one of the most fundamental elements for many vehicular applications, including collision avoidance and autonomous driving. Vehicle position generally provided by a global navigation satellite system (GNSS), which unfortunately suffers from inaccuracy to varying degrees in challenging environments, example, GNSS outages. In this article, fusion technique, called non-Gaussian Redheffer weighted least squares ( n GRWLSs), proposed. This new...

In many advanced driver-assistance systems (ADAS), lane detection is often necessary. Vision-based popular because of its cost efficiency, but it can be easily affected by illumination changes, especially abrupt ones. Moreover, since most camera have a very limited angle view (AOV), single ADAS only perceive portion highly curved road. This introduces another challenge to when fitting models. this paper, we propose method for model inference, which uses one the two lane-markings if there...

Auto-recharging system is one of an interesting progress in the field autonomous robot. This paper describes design and implementation a new docking strategy auto-recharging called power management (PMS) for give to robot possibility quickly docks at station. The PMS controls battery recharging process then allowing redundant verification (repetitive) connection status between We define first global navigational space composed working using three infrared transmitters (IRTs). Secondly,...