In a vehicular communications environment, the need for information sharing, entertainment, and multimedia will increase, leading to congestion of backhaul networks. The major challenge of this network is latency and resource limitations. Proactive caching can be obtained from local caches rather than from remote servers, which can avoid long delays resulting from limited backhaul capacity and resources. Therefore, proactive caching reduces latency and improves the quality of services. Determining which files should be cached in memory is a critical issue. The paper proposes various placement

In this paper, a resource partitioning scheme combined with a new multi-carrier optical modulation technique for indoor visible light communication (VLC) system is proposed. In VLC systems, the coverage area is divided into multiple atto-cells. In each atto-cell, multiple LED arrays are used as access points (APs) serving the assigned users. The coverage area of APs might be overlapped to avoid service discontinuity for mobile users. The overlapped coverage zones result in co-channel interference (CCI). We develop a shared frequency reuse (SFR) technique combined with two resource allocation

This paper develops a lane-change geometric representation that can be used in an on-road vehicle. The design of the proposed system uses the data collected from active a host vehicle and measures the relative speed between host vehicle and obstacle vehicles in real-time. The available distance to the target lanes measures the separated distance between the host and obstacle vehicles in real-time. These data are generated automatically using a dynamic environment and updated using time and object dynamics laws. The main algorithm uses the data to test the availability of using lane-change

This paper aims to help self-driving cars and autonomous vehicles systems to merge with the road environment safely and ensure the reliability of these systems in real life. Crash avoidance is a complex system that depends on many parameters. The forward-collision warning system is simplified into four main objectives: detecting cars, depth estimation, assigning cars into lanes (lane assign) and tracking technique. The presented work targets the software approach by using YOLO (You Only Look Once), which is a deep learning object detector network to detect cars with an accuracy of up to 93%

Epileptic seizures occur as a result of functional brain dysfunction and can affect the health of the patient. Prediction of epileptic seizures before the onset is beneficial for the prevention of seizures through medication. Electroencephalograms (EEG) signals are used to predict epileptic seizures using machine learning techniques and feature extractions. Nevertheless, the pre-processing of EEG signals for noise removal and extraction of features are two significant problems that have an adverse effect on both anticipation time and true positive prediction performance. Considering this, the

Indoor localization has recently attended an increase in interest due to the potential for a wide range of services. In this paper, indoor high-precision positioning and motion prediction algorithms are proposed by using light fidelity (LI-FI) system with angular diversity receiver (ADR). The positioning algorithm uses to estimate the location of an object in the room. Furthermore, the prediction algorithm applies to predict the motion of that object. The simulation results show that the average root mean squares error of the positioning algorithm is about 0.6 cm, and the standard deviation

Long-Term Evolution (LTE) technology is expected to shift some of its transmissions into the unlicensed band to overcome the spectrum scarcity problem. Nevertheless, in order to effectively use the unlicensed spectrum, several challenges have to be addressed. The most important of which is how to coexist with the incumbent unlicensed WiFi networks. Incorporating the "intelligence"component into the network radios is foreseen to resolve the intrinsic network challenges, rather than conventional non-adaptive action plans. Specifically, an intelligent cognitive engine (CE) that continuously

Background: The buckling load as well as the natural frequency under axial load for non-prismatic beam is a changeling problem. Determination of buckling load, natural frequency, and elastic deflection is very important in civil applications. The current paper used both perturbation method (PM), analytic method, and differential quadrature method (DQM), numerical method, to find buckling load and natural frequency with different end supports. The deflection of the beam resting on an elastic foundation under transverse distributed and axial loads is also obtained. Both PM and DQM are used for

Detection of lane boundaries is the primary role for monitoring an autonomous car's trajectory. Three lane identification methodologies are explored in this paper with experimental illustration: Edge detection, Hough transformation, and Birds eye view. The next step after obtaining the boundary points is to add a regulation rule to effectively trigger the regulation of steering and velocity to the motors. A comparative analysis is made between different steering controllers like PID or by using PID with a pure pursuit controller for the Lane Keeping Assist (LKA) system. A camera that sends

Fuzzy C-Means clustering is among the most successful clustering techniques available in the literature. The capacitated vehicle routing problem (CVRP) is one of the most studied NP-hard problems. CVRP has attracted the attention of many researchers due to its importance within the supply chain management field. This study aims to develop a fuzzy c-means clustering heuristic to efficiently solve the CVRP with large numbers of customers by using cluster-first route-second method (CFRS). CFRS is a two-phase technique, where in the first phase customers are grouped into, and in the second phase