The Internet of Things (IoT) technology has the means to shape future many industries. Data is language communication between different nodes through network; networks are channel. cloud home and destination data which adds intelligence analytics software, Precision agriculture uses IoT features help in managing crops production, by optimizing quality applying required nutrients reduce harmful impacts on environment due application excess pesticides. In this paper, we deployed a sensing...

Abstract There is an increasing interest in energy harvesting for wearable biomedical devices. This requires power conservation and management to ensure long-term steady operation. Hence, task scheduling algorithms will be used throughout this work provide a reliable solution minimize consumption while considering the system operation constraints. study proposes novel power-aware scheduler manage operations. For example, we handle operations, including heart rate temperature sensors. Two...

As a trending medical imaging technique, Elastography and B-mode (ultrasound) are combined as diagnostic tool to differentiate between benign malignant breast lesions based on their stiffness geometric properties. Image processing techniques applied the resulting images for feature extraction. Data preprocessing methods principal component analysis (PCA) dimensionality reduction technique dataset. In this paper, supervised learning algorithm "support vector machine (SVM)" is used...

Automatic lane detection is a classical task in autonomous vehicles that traditional computer vision techniques can perform. However, such lack reliability for achieving high accuracy while maintaining adequate time complexity the context of real-time complex and dynamic road scenes. Deep neural networks have proved their ability to achieve competing training them on manually labeled data. Yet, unavailability segmentation masks host lanes harsh environments hinders fully supervised methods'...

Breast cancer constitutes a significant threat to women's health and is considered the second leading cause of their death. result abnormal behavior in functionality normal breast cells. Therefore, cells tend grow uncontrollably, forming tumor that can be felt like lump. Early diagnosis proved reduce risks death by providing better chance identifying suitable treatment. Machine learning artificial intelligence play key role healthcare systems assisting physicians diagnosing early, better,...

Optimization of the LTE network is crucial to obtain best performance. The handover margin (HOM) and time trigger (TTT) should be chosen so that system will have minimum number handovers per user second, delay, maximum throughput. In this paper a new optimization algorithm for long term evolution (LTE) based on Q-learning presented. proposed operates by testing different values HOM TTT then observes output performance corresponding these parameters, it eventually selects produce technique...

The rising interest in assistive and autonomous driving systems throughout the past decade has led to an active research community perception scene interpretation problems like lane detection. Traditional detection methods rely on specialized, hand-tailored features which is slow prone scalability. Recent that deep learning trained pixel-wise segmentation have achieved better results are able generalize a broad range of road weather conditions. However, practical algorithms must be...

The market needs a deeper and more comprehensive grasp of its insight, where the analytics world methodologies such as "Sentiment Analysis" come in. These methods can assist people especially "business owners" in gaining live insights into their businesses determining wheatear customers are satisfied or not. This paper plans to provide indicators by gathering real Amazon reviews from Egyptian customers. By applying both Bidirectional Encoder Representations Transformers "Bert" "Text Blob"...

Abstract Network Intrusion Detection Systems (NIDS) are critical for protecting computer networks from unauthorized activities. Traditional NIDS rely on rule-based signatures, which can be limiting in detecting emerging threats. This study investigates the effectiveness of random forest classifier advancing capabilities through machine learning. Using CICIDS-2017 dataset, data preprocessed to enhance their quality by removing redundancies. feature selection and permutation importance were...

This paper proposes a Vehicle-to-Vehicle (V2V) communication-based forward collision avoidance algorithm by alarming the driver for normal mode and controlling driving wheel self-governed (autonomous) mode. The proposed benefits from information exchange between host vehicle leading to calculate safe distance guarantee of collision. system gives advisory imminent warnings according predicted accident levels, using three different levels Also, in autonomous mode, it follows an alternative...

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

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

Throughout the last years, there has been an increasing interest in developing useful computer vision techniques that help many fields. Face shape classification is considered a common task beauty and fashion purposes. The aim of this paper to represent comparative study different supervised learning algorithms used face classification. was based on extracted facial features for 5 shapes: Heart, Square, Long, Oval Round as labels. Different use landmark distance ratios angles were compared:...

Abstract Wearable devices are a growing field of research that can have wide range applications. The energy harvester is the most common source power for wearable as well in wireless sensor networks require battery-free operation. However, their restricted; consequently, saving crucial devices. Finding best schedule various tasks run on device help to reduce consumption. This paper presents task scheduler medical based Gaining–Sharing Knowledge (GSK) algorithm. purpose this handle heart rate...

This paper introduces a robust algorithm for real-time lane detection using the markers in urban streets or highway roads. It is based on applying Region of Interest (ROI) input image road from calibrated camera front car, generating top view Inverse Perspective Mapping (IPM), core Line Segment Detection (LSD) which followed by post-processing steps. Applying curve fitting to line segments get right and left lines curves. Finally, output stream inverse IPM applied. The proposed can detect...

Autonomous Vehicles (AV) is one of the most evolving industries in last decade. However, bottlenecks this evolution providing data that contains different scenarios and scenes to improve models without exposing privacy security edge vehicles. The authors research propose a secure efficient novel solution for lane segmentation AVs through use Federated Learning (FL). FedLane involves initial training U-Net, ResUNet, ResUNet++ models, followed by real-time inference devices application FL...

Object depth estimation is the cornerstone of many visual analytics systems. In recent years there a considerable progress has been made in this area, while robust, efficient, and precise real-world video remains challenge. The approach utilized presented paper to estimate distance surrounding cars using mono camera. Using YOLO (You Only Look Once) detection process, by generating boundary box object, then an inversion proportional correlation between box's dimensions (height, width)...

Text classification has been one of the most common natural language processing (NLP) objectives in recent years. Compared to other languages, this mission with Arabic is relatively restricted and its early stages, combination medical application area rare. This paper builds an health care assistant, specifically a pediatrician that supports dialects, especially Egyptian accents. The proposed chatbot based on Artificial Intelligence (AI) models after experimenting Two Bidirectional Encoder...

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 algorithm uses estimate location object room. Furthermore, applies predict that object. simulation results show average root mean squares error is about 0.6 cm, standard deviation from 1.188 ×10 <sup...

This paper studies Dual site processing in Virtualized Radio Access Network (V-RAN) and it recommends the amount of dual sites for functional splits which are proposed by ETSI. leads to ease management flexibility operation increases power efficiencies. To recommend both sites, consumption at several percentages is identified compromise tradeoff between midhaul capacity consumption. Furthermore, Joint optimization performed validate optimal split function.

This paper proposes a hardware implementation of Vehicle-to-Vehicle (V2V) communication-based forward collision avoidance algorithm by alarming the driver about potential crashes. The proposed system benefits from information exchange between host vehicle and leading to calculate safe distance guarantee collision. gives advisory imminent warnings according predicted accident levels, using three different levels avoidance. work tests prototype complete V2V communication, designed Basic Safety...

Summary The Orthogonal Frequency Division Multiplexing (OFDM) has emerged as one of the promising techniques because its robustness to multipath fading with high‐speed data transmission. Classical bipolar OFDM cannot be used in intensity modulated direct detection (IM/DD) optical communication systems, visible light (VLC), so many modulation asymmetrical clipped (ACO‐OFDM) and DC‐Clipped (DCO‐OFDM) have been investigated. In this paper, we introduce a novel scheme that meets communications...