In this research, a study of cross-linguistic speech emotion recognition is performed. For this purpose, emotional data of different languages (English, Lithuanian, German, Spanish, Serbian, and Polish) are collected, resulting in a cross-linguistic speech emotion dataset with the size of more than 10.000 emotional utterances. Despite the bi-modal character of the databases gathered, our focus is on

Roundabouts are a highway engineering concept meant to reduce congestion and improve safety. However, experience shows that capacity of roundabouts is limited, and safety is not optimal. However, these improvements in capacity and safety should be compatible with both manually-driven and autonomous vehicles. Incorporating existing advanced technologies to the signaling and control of roundabouts will

In this paper, we propose a reinforcement learning (RL) based Medium Access Control (MAC) protocol with dynamic transmission range control (TRC). This protocol provides an adaptive, multi-hop, energy-efficient solution for communication in underwater sensors networks. It features a contention-based TRC scheme with a reactive multi-hop transmission. The protocol has the ability to adjust to network

To ensure the driving safety in vehicular network, it is necessary to construct a local dynamic map (LDM) for an extended range. Using the standard vehicular communication protocols, however, vehicles can construct the LDM for only one-hop range. Constructing large-scale LDM is highly challenging because vehicles randomly change their position. This paper proposes a dynamic map propagation (DMP) method

An ultra-low quiescent current under-voltage lockout (UVLO) circuit for a high-voltage gate driver integrated circuit (HVIC) is described for application in portable devices. The UVLO circuit consumes the static current in the high-side circuitry and the resistive divider used to detect the supply-voltage was the major consumer of power in the circuit. Hence, a supply-voltage sensor based on a diode-connected

To detect behavioral anomalies (disease/injuries), 24 h monitoring of horses each day is increasingly important. To this end, recent advances in machine learning have used accelerometer data to improve the efficiency of practice sessions and for early detection of health problems. However, current devices are limited in operational lifetime due to the need to manually replace batteries. To remedy this

This paper proposes a backstepping fuzzy sliding mode control method for the antiskid braking system (ABS) of unmanned aerial vehicles (UAVs). First, the longitudinal dynamic model of the UAV braking system is established and combined with the model of the electromechanical actuator (EMA), based on reasonable simplification. Subsequently, to overcome the higher-order nonlinearity of the braking system

Recent studies in data anonymization techniques have primarily focused on MapReduce. However, these existing MapReduce based approaches often suffer from many performance overheads due to their inappropriate use of data allocation, expensive disk I/O access and network transfer, and no support for iterative tasks. We propose “SparkDA” which is a new novel anonymization technique that is designed to

This paper presents a 4-bit 36 GS/s analog-to-digital converter (ADC) employing eight time-interleaved (TI) flash sub-ADCs in 40 nm complementary metal-oxide-semiconductor (CMOS) process. A wideband front-end matching circuit based on a peaking inductor is designed to increase the analog input bandwidth to 18 GHz. A novel offset calibration that can achieve quick detection and accurate correction without

The power production of electrical Renewable Energy Sources (RES), mainly PV and wind energy, is affected by their primary source of energy: solar radiation value or wind strength. Electrical networks with a large share of these sources must manage temporal imbalances of supply and demand. Hybrid Energy Networks (HEN) can mitigate the effects of this unbalancing by providing a connection between the

Conflict detection and resolution is one of the main topics in air traffic management. Traditional approaches to this problem use all the available information to predict future aircraft trajectories. In this work, we propose the use of a neural network to determine whether a particular configuration of aircraft in the final approach phase will break the minimum separation requirements established

The efficient mechanism of light capture by photosynthetic proteins allows for energy transfer and conversion to electrochemical energy at very low light intensities. In this work, reaction center (RC) proteins, or a core complex consisting of the RC encircled by light harvesting (LH1) proteins (RC-LH1) from photosynthetic bacteria, were immobilized on an insulating layer of an ion-sensitive field-effect

The fifth-generation mobile network presents a wide range of services which have different requirements in terms of performance, bandwidth, reliability, and latency. The legacy networks are not capable to handle these diverse services with the same physical infrastructure. In this way, network virtualization presents a reliable solution named network slicing that supports service heterogeneity and

A novel motor fault diagnosis using only motor current signature is developed using a frequency occurrence plot-based convolutional neural network (FOP-CNN). In this study, a healthy motor and four identical motors with synthetically applied fault conditions—bearing axis deviation, stator coil inter-turn short circuiting, a broken rotor strip, and outer bearing ring damage—are tested. A set of 150

Localization has been extensively studied owing to its huge potential in various areas, such as Internet of Things, 5G, and unmanned aerial vehicle services. Its wide applications include home automation, advanced production automation, and unmanned vehicle control. In this study, we propose a novel localization method that utilizes convolutional neural network (CNN) and ultra-wideband (UWB) signals

We experimentally demonstrated full-duplex light-emitting diode (LED)-to-LED visible light communication (VLC) using LEDs as the transmitter and receiver. Firstly, we investigated the performance dependency on the wavelengths of the LED transmitter and receiver by measuring the rise time and signal-to-noise ratio (SNR). Through the investigation, we were able to choose the optimal LED color set for

This paper presents an improved ultra-wideband (UWB) line of sight (LOS)/non-line of sight (NLOS) identification scheme based on a hybrid method of deep learning and transfer learning. Previous studies have limitations, in that the classification accuracy significantly decreases in an unknown place. To solve this problem, we propose a transfer learning-based NLOS identification method for classifying

Physical unclonable functions (PUF) are emerging as a promising alternative to traditional cryptographic protocols for IoT authentication. XOR Arbiter PUFs (XPUFs), a group of well-studied PUFs, are found to be secure against machine learning (ML) attacks if the XOR gate is large enough, as both the number of CRPs and the computational time required for modeling n-XPUF increases fast with respect to

Recently, various deep learning-based models have been applied in the study of recommender systems. Some researches have combined the classic collaborative filtering method with deep learning frameworks in order to obtain more accurate recommendations. However, these models either add additional features, but still recommend in the original linear manner, or only extract the global latent factors of

With the fast expansion of renewable energy systems during recent years, the stability and quality of smart grids using solar energy have been challenged because of the intermittency and fluctuations. Hence, forecasting photo-voltaic (PV) power generation is essential in facilitating planning and managing electricity generation and distribution. In this paper, the ultra-short-term forecasting method

A novel Schottky diode frequency doubler in E-band, using biased series-connected diodes in the output waveguide, is reported. The doubler was implemented using a GaAs Schottky Monolithic Microwave Integrated Circuit (MMIC) process with integrated capacitors and beam leads. A comparison is made with a hybrid doubler using a more conventional single-ended configuration with two discrete diodes in a

A physics-based model for the output current–voltage (I–V) characteristics of AlGaN/GaN HFETs is developed based on AlGaAs/GaAs HFETs. It is demonstrated that Polarization Coulomb Field (PCF) scattering greatly influences channel electron mobility. With different gate biases, channel electron mobility is varied by PCF scattering. Furthermore, a more negative gate bias and a lower ratio of lg/lsd (gate

We have seen a promising acceptance of wireless local area networks (WLANs) in our day-to-day communication devices, such as handheld smartphones, tablets, and laptops. Energy preservation plays a vital role in WLAN communication networks. The efficient use of energy remains one of the most substantial challenges to WLAN devices. Several approaches have been proposed by the industrial and institutional

In this paper, we propose a novel fault tolerant methodology for digital pipelined data-paths called Control Feedback Loop Error Decimation (CFLED), that reduces the error magnitude at the outputs. The data-path is regarded from a control perspective as a process affected by perturbations or faults. Based on the corresponding dynamic model, we design feedback control loops with the goal of attenuating

Intrusion Detection Systems (IDSs) automatically analyze event logs and network traffic in order to detect malicious activity and policy violations. Because IDSs have a large number of false positives and false negatives and the technical nature of their alerts requires a lot of manual analysis, the researchers proposed approaches that automate the analysis of alerts to detect large-scale attacks and

P-grid is a typical feature in power devices to block high off-state voltage. In power devices, the p-grid is routinely coupled to an external electrode with an Ohmic contact, but Schottky contact to the p-grid is also proposed/adopted for certain purposes. This work investigates the role of contact to p-grid in power devices based on the commonly adopted technology computer-aided design (TCAD) device

Inductive power transfer (IPT) systems have become a very effective technology when charging the batteries of electric vehicles (EVs), with numerous research works devoted to this field in recent years. In the battery charging process, the EV consumes energy from the grid, and this concept is called Grid-to-Vehicle (G2V). Nevertheless, the EV can also be used to inject part of the energy stored in

Perceptually motivated audio signal processing and feature extraction have played a key role in the determination of high-level semantic processes and the development of emerging systems and applications, such as mobile phone telecommunication and hearing aids. In the era of deep learning, speech enhancement methods based on neural networks have seen great success, mainly operating on the log-power

Power converters with higher efficiency in a wide load range are important for reducing the overall energy consumption of renewable energy generation systems. A center-tapped LC series resonant dual-active bridge (LC-DAB) converter for DC-DC conversion is proposed in this paper. The proposed converter utilizes a center-tapped bridge to block reverse current and eliminate back flow power to reduce conduction

Ahead-of-time forecasting of the output power of power plants is essential for the stability of the electricity grid and ensuring uninterrupted service. However, forecasting renewable energy sources is difficult due to the chaotic behavior of natural energy sources. This paper presents a new approach to estimate short-term solar irradiance from sky images. The proposed algorithm extracts features from

Salient object detection has achieved great improvements by using the Fully Convolutional Networks (FCNs). However, the FCN-based U-shape architecture may cause dilution problems in the high-level semantic information during the up-sample operations in the top-down pathway. Thus, it can weaken the ability of salient object localization and produce degraded boundaries. To this end, in order to overcome

The rapid proliferation of user devices with access to mobile broadband has been a challenge from both the operation and deployment points of view. With the incorporation of new services with high demand for bandwidth such as video in 4K, it has been deemed necessary to expand the existing capacity by including new bands, among which the unlicensed 5-GHz band is a very promising candidate. The operation

The recent advancement in the application of the internet of things in the smart grid has led to an industrial revolution in the power industry. The Industry 4.0 revolution has already set in, allowing computers to interact for an efficient and intelligent approach in solving smart grid issues. multilevel inverters (MLIs) are an integral part of the smart grid system for integrating the distributed

A novel technique for estimating the asymptotic stability region of nonlinear autonomous polynomial systems is established. The key idea consists of examining the optimal Lyapunov function (LF) level set that is fully included in a region satisfying the negative definiteness of its time derivative. The minor bound of the biggest achievable region, denoted as Largest Estimation Domain of Attraction

The Information-Centric Network (ICN) is one of the most influential future network architectures and in-network caching in ICN brings some helpful features, such as low latency and mobility support. How to allocate cache capacity and place content properly will greatly influence the performance of ICN. This paper focuses on the cache allocation problem and content placement problem under the given

One of the most important parts of a text-independent speaker verification system is speaker embedding generation. Previous studies demonstrated that shortcut connections-based multi-layer aggregation improves the representational power of a speaker embedding system. However, model parameters are relatively large in number, and unspecified variations increase in the multi-layer aggregation. Therefore

Wind power is positioned as one of the fastest-growing energy sources today, while also being a mature technology with a strong capacity for creating employment and guaranteeing environmental sustainability. However, the stochastic nature of wind may affect the integration of power plants into power systems and the availability of generation capacity. In this sense, as in the case of conventional power

Addition is the key operation in digital systems, and floating-point adder (FPA) is frequently used for real number addition because floating-point representation provides a large dynamic range. Most of the existing FPA designs are synchronous and their activities are coordinated by clock signal(s). However, technology scaling has imposed several challenges like clock skew, clock distribution, etc

The growth of wireless networks has been remarkable in the last few years. One of the main reasons for this growth is the massive use of portable and stand-alone devices with wireless network connectivity. These devices have become essential on the daily basis in consumer electronics. As the dependency on wireless networks has increased, the attacks against them over time have increased as well. To

In this work, line-of-sight multiple-input multiple-output (MIMO) measurements in the frequency range from 1 GHz to 40 GHz are presented for an indoor environment in the scope of new 5G bands. For the sake of comparison, the measured radio channels are reproduced with great accuracy using ray-tracing techniques by tuning all propagation mechanisms. The relative received power, root mean square of the

Advances in neuroscience have encouraged researchers to focus on developing computational models that behave like the human brain. HMAX is one of the potential biologically inspired models that mimic the primate visual cortex’s functions and structures. HMAX has shown its effectiveness and versatility in multi-class object recognition with a simple computational structure. It is still a challenge to

This study explores an info-structural model of cognition for non-interacting agents affected by human sensation, perception, emotion, and affection. We do not analyze the neuroscientific or psychological debate concerning the human mind working, but we underline the importance of modeling the above cognitive levels when designing artificial intelligence agents. Our aim was to start a reflection on

While IEEE 802.15.4 and its Time Slotted Channel Hopping (TSCH) medium access mode were developed as a wireless substitute for reliable process monitoring in industrial environments, most deployments use a single/static physical layer (PHY) configuration. Instead of limiting all links to the throughput and reliability of a single Modulation and Coding Scheme (MCS), you can dynamically re-configure

The advent in Online Social Networks (OSN) and Internet of Things (IoT) has created a new world of collaboration and communication between people and devices. The domain of internet of things uses billions of devices (ranging from tiny sensors to macro scale devices) that continuously produce and exchange huge amounts of data with people and applications. Similarly, more than a billion people are connected

In this work, we analyze in depth multiple characteristic data of a representative population of radenv-ADCs (analog-to-digital converters able to operate under radiation). Selected ADCs behave without latch-up below 50 MeV·cm2/mg and are able to bear doses of ionizing radiation above 50 krad(Si). An exhaustive search of ADCs with radiation characterization data has been carried out throughout the

Among movement disorders, essential tremor is by far the most common, as much as eight times more prevalent than Parkinson’s disease. Although these two conditions differ in their presentation and course, clinicians do not always recognize them, leading to common misdiagnoses. Proper and early diagnosis is important for receiving the right treatment and support. In this paper, the development of a

Traffic congestion is one of the most notable urban transport problems, as it causes high energy consumption and air pollution. Unavailability of free parking spaces is one of the major reasons for traffic jams. Congestion and parking are interrelated because searching for a free parking spot creates additional delays and increase local circulation. In the center of large cities, 10% of the traffic

Two dual-band second-order highly selective band pass filters operated at 3.5/5.5 GHz and 3.5/6 GHz for wireless local area network /worldwide interoperability for microwave access WLAN/WiMAX applications are introduced in this paper. The designed filters are inspired of utilizing two coupled open-loop resonators loaded with stub, spiral resonators and lumped capacitors. The filters are designed based

Nowadays, lower-limb prostheses are reaching real-world usability especially on ground-level walking. However, some key tasks such as stair walking are still quite demanding. Providing haptic feedback about the foot placement on the steps might reduce the cognitive load of the task, compensating for increased dependency on vision and lessen the risk of falling. Experiments on intact subjects can be

The problem associated with economic dispatch of battery energy storage systems (BESSs) in alternating current (AC) distribution networks is addressed in this paper through convex optimization. The exact nonlinear programming model that represents the economic dispatch problem is transformed into a second-order cone programming (SOCP) model, thereby guaranteeing the global optimal solution-finding

With the growing need for software-driven devices in modern life, the pervasive necessity of energy efficiency is also rising dramatically. Considering the importance of energy-efficient software in the IT-sphere, many companies started to search and uncover ways for minimizing energy loss. We study the software development process in terms of energy consumption. This depends on various factors that

The performance of a massive multi-user Multi-Input Multi-Output (MIMO) system, operating in Frequency Division Duplex (FDD) mode, severely degrades under imperfect Channel State Information (CSI). Among the main challenges toward the acquisition of sufficiently accurate CSI at the transmitter is the issue of enormous CSI feedback overhead. In this paper, a novel interference cancellation strategy

Unmanned aerial vehicles (UAV) are spreading their usage in many areas, including last-mile distribution. In this research, a UAV is used for performing light parts delivery to workstation operators within a manufacturing plant, where GPS is no valid solution for indoor positioning. A generic localization solution is designed to provide navigation using RFID received signal strength measures and sonar

Hyperspectral images can comprise hundreds of spectral bands, which means that they can represent a large volume of data difficult to manage with the available on-board resources. Lossless compression solutions are interesting for reducing the amount of information stored or transmitted while preserving it at the same time. The Hyperspectral Lossless Compressor for space applications (SHyLoC), which

Blockchain is an emerging technology that has shaken the financial sector, and which is already perceived as having an impact. A blockchain is a network of many interconnected nodes, both trustworthy and malicious, which can reach a consensus and generate valid data. The resulting information is packed into a block and permanently saved on the network in a tamper-proof way. In this paper, we propose

Currently, the outbreak of COVID-19 pandemic has caused catastrophic effect on every aspect of our lives, globally. The entire human race of all countries and regions has suffered devastating losses. With its high infectiousness and mortality rate, it is of great significance to carry out effective precautions and prevention of COVID-19. Specifically, the transportation system has been confirmed as

Nowadays, regulation standards regarding the injection of harmonics in the grid power supply are becoming stricter. These standards have a direct impact on the design and control of converters, especially in medium-voltage drives. To fulfil these standards, converters are designed to work with the power factor as close to unity as possible and to correct the harmonics spectrum in case of a grid power

Machine Learning (ML) and Deep Learning (DL) have been used for building Intrusion Detection Systems (IDS). The increase in both the number and sheer variety of new cyber-attacks poses a tremendous challenge for IDS solutions that rely on a database of historical attack signatures. Therefore, the industrial pull for robust IDSs that are capable of flagging zero-day attacks is growing. Current outlier-based

This work focuses on designing a grammar detection system that understands both structural and contextual information of sentences for validating whether the English sentences are grammatically correct. Most existing systems model a grammar detector by translating the sentences into sequences of either words appearing in the sentences or syntactic tags holding the grammar knowledge of the sentences

In video streaming over vehicular communication, optimal selection of a video packet forwarder is a daunting issue due to the dynamic nature of Vehicular Ad-hoc NETworks (VANETs)and the high data rates of video. In most of the existing studies, extensive considerations of the essential metrics have not been considered. In order to achieve quality video streaming in vehicular network, important metrics