Brain cancer classification is an important step that depends on the physician's knowledge and experience. An automated tumor system very essential to support radiologists physicians identify brain tumors. However, accuracy of current systems needs be improved for suitable treatments. In this paper, we propose a hybrid feature extraction method with regularized extreme learning machine (RELM) developing accurate approach. The approach starts by preprocessing images using min-max...

The network intrusion detection system is an important tool for protecting computer networks against threats and malicious attacks. Many techniques have recently been proposed; however, these face significant challenges due to the continuous emergence of new that are not recognized by existing systems. In this paper, we propose a novel two-stage deep learning (TSDL) model, based on stacked auto-encoder with soft-max classifier, efficient detection. model comprises two decision stages:...

In recent years, computation offloading has become an effective way to overcome the constraints of mobile devices (MDs) by delay-sensitive and computation-intensive application tasks remote cloud-based data centers. Smart cities can benefit from edge points in framework so-called cyber-physical-social systems (CPSS), as for example traffic violation tracking cameras. We assume that there are computing networks (MECNs) more than one region, they consist multiple access points, multi-edge...

In this article, a comprehensive overview of the Crow Search Algorithm (CSA) is introduced with detailed discussions, which intended to keep researchers interested in swarm intelligence algorithms and optimization problems. CSA new algorithm recently developed, simulates crow behavior storing excess food retrieving it when needed. theory, searcher, surrounding environment search space, randomly location feasible solution. Among all locations, where most stored considered be global optimal...

Citrus fruit diseases are the major cause of extreme citrus yield declines. As a result, designing an automated detection system for plant is important. Deep learning methods have recently obtained promising results in number artificial intelligence issues, leading us to apply them challenge recognizing and leaf diseases. In this paper, integrated approach used suggest convolutional neural networks (CNNs) model. The proposed CNN model intended differentiate healthy fruits leaves from...

The alarmingly high mortality rate and increasing global prevalence of cardiovascular diseases signify the crucial need for early detection schemes. Phonocardiogram (PCG) signals have been historically applied in this domain owing to its simplicity cost-effectiveness. In paper, we propose CardioXNet, a novel lightweight end-to-end CRNN architecture automatic five classes cardiac auscultation namely normal, aortic stenosis, mitral regurgitation valve prolapse using raw PCG signal. process has...

The industrial control systems are facing an increasing number of sophisticated cyber attacks that can have very dangerous consequences on humans and their environments. In order to deal with these issues, novel technologies approaches should be adopted. this paper, we focus the security commands in IoT against forged misrouting commands. To end, propose a architecture integrates Blockchain Software-defined network (SDN) technologies. proposed is composed of: (a) intrusion detection system,...

Human activity recognition from multimodal body sensor data has proven to be an effective approach for the care of elderly or physically impaired people in a smart healthcare environment. However, traditional machine learning techniques are mostly focused on single sensing modality, which is not practical robust applications. Therefore, recently increasing attention being given by researchers development that can exploit and provide important decision making Smart healthcare. In this paper,...

The trustworthiness of an industrial Internet Things (IIoT) network is important stakeholder expectation. Maintaining the such a crucial to void loss lives. A trustworthy IIoT system combines security characteristics IT trustworthiness-safety, security, privacy, reliability, and resilience. Conventional tools techniques are not enough safeguard platform due difference in protocols, limited upgrade opportunities, mismatch older versions operating used system. In this article, we propose...

Data analytics, machine intelligence, and other cognitive algorithms have been employed in predicting various types of diseases health care. The revolution artificial neural networks (ANNs) the medical discipline emerged for data‐driven applications, particularly healthcare domain. It ranges from diagnosis diseases, image processing, decision support system (DSS), disease prediction. intention conducting research is to ascertain impact parameters on diabetes data predict whether a particular...

In recent years, researchers have proposed many deep learning (DL) methods for various tasks, and particularly face recognition (FR) made an enormous leap using these techniques. Deep FR systems benefit from the hierarchical architecture of DL to learn discriminative representation. Therefore, techniques significantly improve state-of-the-art performance on encourage diverse efficient real-world applications. this paper, we present a comprehensive analysis that leverage different types...

Reducing energy loads while maintaining the degree of hotness and coldness plays an essential role in designing energy-efficient buildings. Some previous methods have been proposed for predicting building using traditional machine learning methods. However, these suffer from overfitting problems, which leads to inaccurate prediction results. To achieve high accuracy results, ensemble approach is this paper. The uses extreme gradient boosting (XGBoost) algorithm avoid problems builds...

Global human pollutant activities have raised greenhouse gas (GHG) emissions, which directly affected the climate. Fossil fuel-based energy has brought a negative impact on environment and is considered one of largest sources GHG emissions. It envisaged that emissions will increase in future due to rapid population growth industrialization. Thus, it imperative mitigate climate variability reduce GHGs by adopting renewable (RE) for electricity generation. In this regard, multi-criteria...

Abstract Social media is popular in our society right now. People are using social platforms to purchase various products. We collected the data from platforms. analyzed for prediction of consumer behavior on platform. considered Facebook, Twitter, Linked In and YouTube, Instagram, Pinterest, etc. There diverse high-speed, high volume which coming platform, so we used predictive big analytics. this paper, have concept technology process analyze it predict media. based some parameters...

Nowadays, drones are not just deployed for defense and military establishments, but they widely used in many applications such as natural disaster monitoring, soil crop analysis, road traffic surveillance, consumer product delivery. Some information, drone identification flight modes, can be transmitted to other drones. This information shared between by using radio frequency (RF) signals through 5G networks. Recently, few studies have been proposed use deep neural networks (DNNs) on RF...

Brain tumor (BTs) is considered one of the deadly, destructive, and belligerent disease, that shortens average life span patients. Patients with misdiagnosed insufficient medical treatment BTs have less chance survival. For analysis, magnetic resonance imaging (MRI) often utilized. However, due to vast data produced by MRI, manual segmentation in a reasonable period time difficult, which limits application standard criteria clinical practice. So, efficient automated techniques are required....

A speech impairment limits a person’s capacity for oral and auditory communication. great improvement in communication between the deaf general public would be represented by real-time sign language detector. This work proposes deep learning-based algorithm that can identify words from gestures detect them. There have been many studies on this topic, but development of static dynamic recognition models is still challenging area research. The difficulty obtaining an appropriate model...

An Intrusion detection system is an essential security tool for protecting services and infrastructures of wireless sensor networks from unseen unpredictable attacks. Few works machine learning have been proposed intrusion in that achieved reasonable results. However, these still need to be more accurate efficient against imbalanced data problems network traffic. In this paper, we a new model detect attacks based on genetic algorithm extreme gradient boosting (XGBoot) classifier, called...

In recent years, connected home healthcare, which involves multiple technologies such as wearable sensors, audio and video technology, pervasive computing, has drawn attention for its ability to improve quality of life elderly people. One most important services is fall detection. Falls represent a significant threat the health independence adults older than 65. However, commercial detection devices are expensive charge monthly fee their use. A more cost-effective, adaptable, reliable system...

Cancer can be considered as one of the leading causes death widely. One most effective tools to able handle cancer diagnosis, prognosis, and treatment is by using expression profiling technique which based on microarray gene. For each data point (sample), gene usually receives tens thousands genes. As a result, this large‐scale, high‐dimensional, highly redundant. The classification profiles (NP)‐Hard problem. Feature (gene) selection methods A hybrid approach presented in paper, several...