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Securing Hardware from Malicious Attacks

Hardware security is considered a major design and manufacturing target area with a broad range of research and development topics such as protection of intellectual property (IP), metering of hardware, detection of hardware Trojans, and a lot of other topics. This paper discusses Trojan realization in integrated circuits (ICs), as well as the possible security measures, also exploring the usage

Artificial Intelligence

Utilization of Machine Learning In RTL-GL Signals Correlation

Verification is an important part of the Electronic Design Automation (EDA) design flow which currently takes a considerable amount of time. During the synthesis process, Different optimizations are done to the Register-Transfer-Level (RTL) code to optimize the power, area, and speed of the circuit. These optimizations result in changes in the names of signals at the gate level. Automatic signal

Artificial Intelligence

Using machine learning algorithms for breast cancer diagnosis

There are many cancer patients, especially breast cancer patients as it is the most common type of cancer. Due to the huge number of breast cancer patients, many breast cancer-focused hospitals aren't able to process the huge number of patients and might expose some women to late stages of cancer. Thus, the automation of the process can help these hospitals in speeding up the process of cancer

Artificial Intelligence

Nanocomposite matrix conjugated with carbon nanomaterials for photocatalytic wastewater treatment

The problem of hazardous wastewater remediation is a complicated issue and a global challenge. Herein, a layered Co0.5Ni0.5Fe2O4/SiO2/TiO2 composite matrix was prepared and incorporated with three carbon nanomaterials having different dimensionalities, carbon dots (C-dots, 0D), single-walled carbon nanotubes (1D), and reduced graphene oxide (2D), in an effort to create effective photocatalytic

Energy and Water
Innovation, Entrepreneurship and Competitiveness

Advanced methods for missing values imputation based on similarity learning

The real-world data analysis and processing using data mining techniques often are facing observations that contain missing values. The main challenge of mining datasets is the existence of missing values. The missing values in a dataset should be imputed using the imputation method to improve the data mining methods’accuracy and performance. There are existing techniques that use k-nearest

Artificial Intelligence

Using Blockchain Technology for the Internet of Vehicles

The Internet of Vehicles (IoV) aims to connect vehicles with their surroundings and share data. In IoV, various wireless technologies like 5G, WIFI, DSRC, WiMAX, and ZigBee are used. To share data within wireless surroundings in a secure way, some security aspects need to be fulfilled. Blockchain technology is a good fit to cover these countermeasures. IoV uses a lot of technologies and interacts

Artificial Intelligence

A Multitier Deep Learning Model for Arrhythmia Detection

An electrocardiograph (ECG) is employed as a primary tool for diagnosing cardiovascular diseases (CVDs). ECG signals provide a framework to probe the underlying properties and enhance the initial diagnosis obtained via traditional tools and patient-doctor dialogs. Notwithstanding its proven utility, deciphering large data sets to determine appropriate information remains a challenge in ECG-based

Artificial Intelligence

A Novel Hadoop Security Model for Addressing Malicious Collusive Workers

With the daily increase of data production and collection, Hadoop is a platform for processing big data on a distributed system. A master node globally manages running jobs, whereas worker nodes process partitions of the data locally. Hadoop uses MapReduce as an effective computing model. However, Hadoop experiences a high level of security vulnerability over hybrid and public clouds. Specially

Artificial Intelligence

Software-Defined Networks Towards Big Data: A Survey

Both Big Data and Software-Defined Network have a significant impact in both academic and practical aspects. These two areas have been addressed separately, but both did not contribute to the same subset area of contribution. However, Big Data can greatly facilitate, improve, and have a great impact on Software Defined Network, and vice versa. In this paper, we show how SDN helps Big Data solve

Artificial Intelligence

Multimodal Video Sentiment Analysis Using Deep Learning Approaches, a Survey

Deep learning has emerged as a powerful machine learning technique to employ in multimodal sentiment analysis tasks. In the recent years, many deep learning models and various algorithms have been proposed in the field of multimodal sentiment analysis which urges the need to have survey papers that summarize the recent research trends and directions. This survey paper tackles a comprehensive

Artificial Intelligence
Software and Communications