Miracle-dz/UniFAR-FTUs huggingface dataset:
Challenges and Techniques of Constrained Application Protocol (CoAP) for Efficient Energy Consumption

IoT is a network of connected objects in which these objects can collect data and exchange them using embedded sensors. It permits communication between objects and things, and it binds together units in our universe under a regular infrastructure. It allows not just controlling things around us, but also keeping us educated on the state things. Internet of Things (IoT) devices are used in daily life in many domains such as health, agriculture and many others. In the IoT world, the embedded sensors of connected devices play a major role. These sensors have limited energy capabilities, and any network of such devices is called Low power and Lossy network (LLNs). Many implementations and techniques have been trying to address this issue of energy consumption. This paper focuses on Application Layer techniques and specifically on one of the most important protocols, the Constrained Application Protocol (CoAP). We discuss ten of the best energy-efficient techniques to implement the CoAP, and conduct a comparison among these techniques on different levels.
Fault Classification of Induction Motor Using Discrete Wavelet Transform and Fuzzy Inference System

This paper develops a real-time condition-monitoring algorithm for induction motor. The condition monitoring mechanism is based on the discrete wavelet transform (DWT) and the fuzzy inference system (FIS). In this method, the stator currents are used as an input to the system. No direct access to the induction motor is required. The developed system has been rigorously assessed theoretically and experimentally, and it has been shown that the system is robust and reliable.
MQTTSec Based on Context-Aware Cryptographic Selection Algorithm (CASA) for Resource-Constrained IoT Devices

With the spread and wide adoption of IoT systems, new security and privacy concerns started to arise and be presented as serious issues. To mitigate these new threats, new countermeasures and prevention techniques based on cryptography are introduced. Since most IoT devices are restrained with the sparse availability of resources, such as memory and computational power, using traditional cryptographic algorithms is not practical as it needs special hardware implementation to accommodate these algorithms. In this work an enhancement of the traditional MQTT protocol called MQTTSec is proposed. MQTTSec allows communicating devices to select the appropriate cryptographic technique based on the available resources. A validation of the proposed technique is also provided.
Experimental Research on the Characteristics of SiC MOSFET Module at 180 °C

SiC MOSFET is theoretically suitable for high- temperature applications due to its wide band gap and high thermal conductivity. In response to the lack of relevant experimental research on high-temperature characteristics of high-power SiC MOSFET module, this paper takes 1200V 300A SiC MOSFET module as the research object to evaluate the operation capability of the high-power SiC MOSFET module at 180 °C. Firstly, static and dynamic characteristics of the module are measured at high temperature, and superior high- temperature characteristics have been proved from two aspects of transient electrical characteristics and loss. Then, the thermal equivalent high-temperature power operation test is completed by using the heat-sensitive electrical parameter method. The test value of junction temperature is 186 °C, and the operating current is 280 A. The test verifies that the module can achieve high-temperature operation through reasonable thermal design. The experimental results show that the 1200V 300A SiC MOSFET module has the ability to operate at junction temperature of 180 °C and a good application prospect of high temperature.
EEG Signals Analysis And Classification For BCI Systems: A Review

A Brain-Computer Interface (BCI) system is a computer-based system that obtains brain signals, studies them and then translates them into signals that are provided to an output to perform the desired action. BCI intends to provide an individual with a severe motor disability to have effective communication and control over his or her motor activities. BCI makes use of different techniques and algorithms in order to analyze the Electroencephalography (EEG) signals. This paper intends to give an overview of BCI system’s EEG classification for voluntary actions which can be used for various applications.
Double Stage Solar PV Array Fed Sensorless Vector Controlled Induction Motor for Irrigational Purpose

This paper proposes a double stage solar-powered speed sensorless vector-controlled induction motor drive for irrigational purpose. The proposed system comprises solar photovoltaic (PV) array, boost converter, three-phase voltage source inverter (VSI), induction motor drive (IMD) and a centrifugal pump. The boost converter operates to extract the peak power from the PV source using Perturb & Observe (P&O) algorithm. The control of VSI focuses on the implementation of indirect field-oriented control (IFOC) with space vector modulation (SVM). The speed of induction motor drive is controlled accordingly to the available PV power. The model reference adaptive system (MRAS) based on rotor flux is used to determine the speed of the motor. The system incorporating two-stage PV powered sensorless IMD is modeled and simulated in MATLAB/Simulink environment, and its performance is studied under dynamic insolations levels.
Energy-Latency-Aware Task Offloading and Approximate Computing at the Mobile Edge

Task offloading with Mobile-Edge Computing (MEC) is envisioned as a promising technique for prolonging battery lifetime and enhancing the computation capacity of mobile devices. In this paper, we consider a multi-user MEC system with a Base Station (BS) equipped with a computation server assisting mobile users in executing computation-intensive real-time tasks via offloading technique. We formulate the Energy-Latency-aware Task Offloading and Approximate Computing (ETORS) problem, which aims at optimizing the trade-off between energy consumption and application completion time. Due to the centralized and mixed-integer natures of this problem, it is very challenging to derive the optimal solution in practical time. This motivates us to employ the Dual-Decomposition Method (DDM) to decompose the original problem into three subproblems—namely the Task-Offloading Decision (TOD), the CPU Frequency Scaling (CFS), and the Quality of Computation Control (QoCC). Our approach consists of two iterative layers: in the outer layer, we adopt the duality technique to find the optimal value of Lagrangian multiplier associated prime problem; and in the inner layer, we formulate the subproblems that can be solved efficiently using convex optimization techniques. We show that the computation offloading selection depends not only on the computing workload of a task, but also on the maximum completion time of its immediate predecessors and on the clock frequency as well as on the transmission power of the mobile device. Simulation results coupled with real-time experiments on a small-scale MEC testbed show the effectiveness of our proposed resource allocation scheme and its advantages over existing approaches.
The Three-Port Three-Phase 3L-NPC Isolated Bidirectional DC-DC Converter

The multiport 3 level neural point clamped (3L-NPC) isolated bidirectional DC-DC converter (IBDC) can double the voltage level using the standard switching devices and connects different type sources together to meet the high-power application such as the ROV systems. A kind transformer coupled three-phase three-port 3L-NPC IBDC was put forward in this paper, and two operation modes were analyzed in detail according to the phase shift ratio and the duty cycle relationship. The regulating strategy of power flow for the three-port 3L-NPC IBDC was to get the minimum loss, hence the zero averaged power in the storage port and/or the zero-power flow between the storage port and load port were applied. The control was the multi-loop negative feedback of output voltage and current at the load port and a single-loop feedback of output current at the storage port. The linearization small signal mode was set up to analyze the control property and to determine the parameters. The three-port 3L-NPC IDBC can improve the electromagnetic compatibility obviously for high-power high-voltage application.
A simple device for determination of incubation stages in eggs

Many methods to determine the stage of incubation in birds' eggs are available. In field studies of species which have boldly marked eggs, like waders, only those methods using floating characteristics are practicable. In order to standardize methods, and to obtain comparable results from different researchers, we developed an 'incubometer', and calibrated it for the Lapwing Vanellus vanellus (based on 45 nests), and the Black-tailed Godwit Limosa limosa (based on 11 nests).
Early understory successional changes following clearcutting in the balsam fir-yellow birch forest

Abstract Community response to disturbance is influenced by species life history and the nature of disturbance. In this study we investigated the effects of clearcutting on the early successional changes of an understory species community in the balsam fir-yellow birch forest type of the Lower St. Lawrence Region of Québec, Canada. Clearcuts of 5, 10 and 20 years were sampled along with mature stands. In each of these communities, ten circular quadrats of 400 m2 were established where the percent cover of herb, fern, and shrub species was estimated. Along a 150-m transect starting in the middle of each quadrat, the seedling density of commercial tree species was measured in ten 4-m2 plots. Detrended Correspondence Analysis (DCA; cover values) was used to describe the early successional changes in the understory community and a Correspondence Analysis (CA) was used with presence/absence data to evaluate the compositional differences. The results revealed a time gradient associated with understory community changes, in which the first 10 years of successional changes are characterized by the dominance of shade intolerant species. A decrease in the floristic heterogeneity was associated with clearcut logging. Small herb species with a shallow root system were most affected by logging. For commercial tree seedlings, the changes following clearcutting were characterized by a decrease over time in the density and stocking of shade intolerant and mid-tolerant species (principally white and yellow birches). In the older clearcuts, sugar maple appeared to be the dominant commercial species in the seedling understory. The results suggested that clearcut logging in the balsam fir-yellow birch forest type may contribute to rapidly shifting the seedling understory composition towards dominance by shade tolerant species. This situation may be related to the dominance of mountain maple in the understory of old clearcuts that contribute to reducing the available light in the understory, thus increasing mortality of shade intolerant seedling species. Clearcutting may also have deleterious effects on some understory herb species that need particular conditions before re-establishing in a site. Logging tends to reduce micro-site heterogeneity over large extended areas—a situation that may preclude the re-establishment of some late successional herb species.
Information Asset Classification and Labelling Model Using Fuzzy Approach for Effective Security Risk Assessment

Many information assets have been exposed to threats as a result of business owners not having access to an efficient model for classifying their information assets into appropriate security risk levels, required level of protection and priority. Manual and machine learning among several approaches have been employed in classifying information; these were not effective in considering users’ preferences and are also not based on security standard. This study proposed a Fuzzy-based Information Asset Classification and Labeling framework based on ISO/IEC 27001 security standard. The framework comprises of six major phases: expert based information asset security assessment and classification (IAC), fuzzy based information assets security assessment and classification (FIACL), information asset labeling, information security risk assessment, and information asset handling and information asset storage. The implementation of the model will be done by developing an automated system with an enhanced classification using fuzzy logic and Delphi method for the security risk assessment. The comparative analysis revealed that FIACL was more efficient and accurate in classifying information assets for proper security risks assessment and control. This model will foster effective classification of information assets in any organization.
Comprehensive Benefit Analysis of Energy Saving and Loss Reduction for Flexible Substation Applied to Active Distribution Network

The comprehensive benefits of energy saving and loss reduction for flexible substation in active distribution network are related to application and promotion prospect of this technology. To this end, the working principle of power electronic transformers in flexible substations is analyzed, and the functions of flexible substations are clarified according to their composition. The characteristics of loss reduction and energy conservation for flexible substation are defined. The resulting benefits are identified and the corresponding benefit calculation method is determined. Taking a 10kV flexible substation as an example, the comprehensive benefit of energy saving and loss reduction in distribution network is calculated according to the actual configuration, and compared with the conventional substation with the same boundary conditions, the effectiveness advantage of flexible substation in energy saving and loss reduction is demonstrated. It also provides calculation methods and reference basis for energy saving and loss reduction analysis of similar projects in the future.
Forecasting of Network Intrusion by means of Efficient Machine Learning Algorithm

It has been highly prescribed that our network needs to be locked as the use of storing data on the network has increased the number of snoopers. When an unauthorized or an unwanted activity occurs in a computer system then we refer it as network intrusion. It may allow a third party network to peek into our data, steal the data as well as change it. Therefore, the need to secure our network is highly recommended. To achieve this level of security, different machine learning algorithms are used and compared. The several algorithms which are compared are Naïve Bayes, Decision Table, K-Nearest Neighbor, Random Forest and Ad boost. The motive of this comparison is to identify the best performance algorithm. The following best algorithm will provide the high network attack accuracy. The dataset is produced which may contain a variety of intrusions. Our system will provide detection of the vicious network and establish the type of attack that has occurred in the system. Likewise, we can protect break off spiteful connection and provide security to our system.
Optimised Wind Farm Active and Reactive Power Dispatch While Considering Fatigue Distribution

In the traditional optimization of wind farms (WFs) power dispatch, the strategies of active and reactive dispatches are decoupled. However, the electrical power losses inside a WF is related to both the active power dispatch and reactive power dispatch. This paper unites active and reactive power dispatches to make the output power of WF maximal. In addition, the uneven fatigue distribution of WF caused by wake effect and the improper active power dispatch will lead to high maintenance frequency, which means high maintenance costs. Therefore, this paper also takes the fatigue distribution of WF into account. The fatigue coefficient is selected to represent the fatigue suffered by wind turbines (WTs). And the standard deviation is take to evaluate fatigue distribution. Simulations are made in a WF consisting of 50 PMSG WTs. The PSO algorithm is implemented to solve problems. The active and reactive power of each WT are the control variables. The case study section shows the new strategy’s superiority.
Performance Analysis of Defused VLC Channel for Mobile Environment

Visible light communication (VLC) is proposed to complement the radio frequency (RF) spectrum. In the VLC systems, the existing LED lighting infrastructure is utilized for data communication. The visible light cannot penetrate walls and other objects, and thus mainly relies on the line-of-sight (LOS) communication. The critics have reservations on the application of VLC in mobile scenarios, either due to device orientation or user movement. In practical scenarios, it is observed that visible light experiences reflections from diffused surfaces such as walls, ceilings, and floor, and thus creates defused/non-line of sight (NLOS) channels. For VLC systems, in many recent studies, it is considered that first-order reflections arrive simultaneously without any propagation delay with LOS signal and can thus contribute to the optical gain, which can be helpful to provide data communication to highly mobile users. This research work, therefore, evaluates the NLOS channels and study their effect on mobile users. In this paper, the analytical model is evaluated for two simulation scenarios: a) LOS only, b) LOS and NLOS. Results show that NLOS contributes to optical gain and maintains communication in mobility scenarios.
Study on the evolution of equivalent impedance parameters for lithium-ion batteries under combined AC-DC conditions

At present, lithium-ion batteries are often used as energy storage system in electric vehicles or power system connecting with power electronic equipment, so they will be in the excitation conditions with high frequency ripples. In this paper, the evolution rules of lithium-ion battery parameters under combined AC-DC conditions are studied. Firstly, at a fixed State of Charge (SOC) point, impedance characteristics of 8 capacity rate (C) points selected in 0~1C superimposed with the same AC excitation are studied. The charge transfer process controlled by kinetic is fitted by simplified Butler-Volmer (B-V) equation, and the goodness-of-fit is close to 1. Then 10 SOC points are selected in the whole SOC range to analyze the evolution rules of impedance parameters under superimposed conditions. At the same time, the ohmic impedance in time domain and frequency domain is compared and analyzed, and the composition of 1s internal resistance in time domain is explained theoretically, and verified by experimental results.
A Control Strategy for Suppressing the DC Overvoltage under the Fault of DC Power Grid

Unbalanced power in DC power grid causes DC overvoltage, which damages the capacitors, IGBT and other devices, so it is essentially important to suppress the DC overvoltage. Aiming at the problem of DC overvoltage suppression, this paper proposes a new control strategy to suppress the rise of DC voltage by adding DC voltage signal to traditional constant AC voltage controller. Firstly, the mechanism of DC overvoltage is studied, and the relationship between the DC voltage and the unbalanced power in DC power grid is qualitatively and quantitatively analyzed according to the law of energy conservation. Then the relationship between the DC voltage and AC voltage is obtained, and an additional DC voltage control strategy is proposed for constant AC voltage control to suppress the rise of DC voltage. Based on the PSCAD/EMTDC, the simulation model of four terminal VSC-HVDC is built. In the case of blocking fault at the receiving end, the effectiveness of the proposed control strategy is verified.
Human Activity Classification with Frequency Modulated Continuous Wave Radar Using Deep Convolutional Neural Networks

Radar is an attractive sensor for human activity classification due to its ability to work in low lighting conditions, its invariance to the environment and its ability to operate through obstacles. Human activity classification finds applications in human-computer interfaces, user-intent understanding and contextual-aware smart homes. Radar reflections from humans produce unique micro-Doppler and range signatures that can be used to recognize target movements. In this paper, we study such features obtained from a compact short-range 60-GHz frequency modulated continuous wave radar for various human activities. We present novel Convolutional Neural Network architectures to leverage these features for human activity classification.
A LDPC codes based Authentication Scheme

Verifying multiple digital signatures in a batch to reduce verification time and computation has caught the interest of many researchers since many years. There are various batch verification schemes proposed for various popular digital signature algorithms such as DSS, RSA, ECDSA and other signature schemes. If there are any bad signatures in the given batch of signatures, then the batch verification test fails but the test does not indicate the location of the bad signature. In literature, there are very few efficient schemes, which locate the index of the bad signature/s in the given batch. These existing schemes perform poorly when the bad signature/s count is unknown or when the entire batch of signatures is faulty. To overcome these disadvantages, we propose a new Low-Density Parity-Check (LDPC) based verification scheme to locate the index of the bad signature/s. Our proposed scheme outperforms the other bad signature identification schemes. The comparative analysis of our scheme with the other schemes is provided. The primary advantage of the scheme is, it removes all the transmission errors in the received batch of signatures.
UAV-Mounted Mobile Base Station Placement via Sparse Recovery

In order to deploy minimum number of unmanned aerial vehicle (UAV)-mounted mobile base stations (MBSs) to service all given ground terminals, this paper proposes an MBS placement based on sparse recovery (MBS-PBSR) algorithm. By exploiting the sparsity inherent in the differences between any two dedicated MBSs, the problem of UAV-mounted MBS placement could be formulated as an <inline-formula> <tex-math notation="LaTeX">$\ell _{0}$ </tex-math></inline-formula>-norm constrained optimization problem, which is then be solved by the reweighted <inline-formula> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula>-norm method. Subsequently, the resulted solutions to the MBS placement are adjusted by the iterative redundant circle deletion algorithm, eventually leading to the redundant MBSs removal as much as possible. Simulation results demonstrate that our proposed MBS-PBSR algorithm works well with affordable computational complexity, and is nearly optimum in the sense of the number of deployed UAV-mounted MBSs.
Spectral Efficiency and Information Transfer Rate Over Optical Fibers in Spatial Parallelism

Spatial parallelism contribution to optical fibers spectral efficiency and to signal transfer rate is being estimated. Parallelism multiplier system parameter is introduced. Using this parameter analytical expressions are constructed to determine the optical fibers spectral efficiency and information transfer rate. Examples of spatial parallelism of optical signal transmission in few-mode and multicore fibers are given.