Miracle-dz/UniFAR-FTUs huggingface dataset:
Is Arduino a suitable platform for sensor nodes?

Over the last years, a significant amount of research papers based their practical evaluation of wireless sensor network-related topics on deployments consisting of Arduino-based sensor nodes. Arduino, on the other hand, offers prototyping boards not tailored for in-the-field deployments. Also, the boards are not specifically designed for ultra low power operation required for long-lasting wireless sensor nodes.We consequently raise the question, whether Arduino is indeed a suitable platform for wireless sensor nodes. For this reason, we evaluated recent Arduino boards by (i) comparing their specifications with common sensor nodes and (ii) analyzing their power consumption in active as well as different sleep modes. Additionally, we evaluated the software components provided by Arduino (i.e., bootloader and libraries). In conclusion, Arduino offers an easy-to-use and cheap basis for early development or analysis, but it falls short in terms of high power consumption as well as issues caused by the bootloader and other integrity issues in the libraries. Therefore, Arduino may be suitable to support the sensor node development but has noticeable drawbacks for actual deployments.
Towards Real-time Learning for Edge-Cloud Continuum with Vehicular Computing

Sensor-driven IoT systems are well-known for their capacity to accelerate massive amounts of data in a comparatively short period of time. To have any use, the information delivery and decision making based on the data require efficient learning models together with dynamically deployed computing and network resources. The current cloud and high-performance computing infrastructures, as well as modern edge computing systems especially in the 5G and beyond networks, can be addressed to resolve these challenges. However, there are several application areas especially in vehicular and urban computing, where just harnessing more computational power does not solve computational and real-time requirements of the modern sensing systems that operate in mobile and context-dependent environments. For now, the mathematical challenges of distributed computing and real-time learning algorithms have not been profoundly addressed in the context of the IoT and real-world sensing applications. Data-driven systems also require giving full attention to information delivery, data management, data cleaning, and sensor fusion technologies that need to be equally distributed and real-time competent as the learning algorithms themselves. New software-defined computing and networking approaches and architectures are required to orchestrate the numerous connected resources dynamically, controllably, and securely along with the evolving needs. The key challenge here is to uniform collaboration between different aspects of the system, from data processing and delivery to the algorithms and learning models, not forgetting the computational capacity and networking capabilities, all this in real-time with real-world applications.
Statistical procedures for corrosion studies

Decision-makers evaluating corrosion treatment alternatives under the Lead and Copper Rule need the statistical tools to choose the optimum treatment from pipe loop studies. In many cases, the data generated by pipe loop studies do not follow a normal distribution; therefore, nonparametric statistics apply. Techniques that are discussed include determination of data normality using the Kolmogorov-Smirnov and chi-square tests, determination of stabilization using the Spearman coefficient, and comparison of treatments using the Wilcoxon signed ranks or rank sum test. Other data issues that are important to evaluating corrosion studies include determining sample size and frequency, determining the confidence and accuracy of results, and evaluating data outliers.
Novel Switched-Capacitor Compact Multilevel Converter Based on Packed E-Cell Design with Fault Tolerant Operation

In this paper a novel single dc-source switch-capacitor compact multilevel topology is designed based on Packed E-Cell to have the boosting potency for the 11-level operation and to merit as a reliable AC-DC converter for fault tolerant capability. The proposed single-phase compact converter is reduced the active/passive components counts while the output voltage levels are increased which it includes 6 normal power switches and 3 bidirectional switches as well as 2 dc capacitors as the auxiliary dc sources. While the conventional compact converter is incapable of fault tolerant operation, the proposed topology could emerge as a reliable while it has the boosting ability due to its switched-capacitor feature. Moreover, the dc capacitors are actively balanced thanks to various switching states redundancy. The proposed single-phase switched-capacitor converter is validated by theoretical analyses as well as simulation results obtained by Matlab-Simulink where it shows the accurate dc capacitors voltages balancing and prefect 11-level generation in the AC output terminal.
Economical Operation and Unit Commitment on IEEE 9 Bus

The total load of the electric power system varies throughout the day and reaches different peaks from one day to another. Thus, electric utility needs to decide which generating units to start up and shut down the best time to connect to the grid, and the sequence of operating units that should be shut down and its duration. This paper considers unit commitment with fossil fuels which have different production costs due to differences in efficiency designs and types of fuel. This paper focuses on unit commitment on the IEEE 9 Bus with an experiment on ETAP 12.6. 0 by looking at the optimal power flow calculated using the Dynamic Program Solution. It is expected to identify the generators that were on-off for several levels of loads.
Electronic sensory systems for the visually impaired

In this article, I have summarized the required features in electronic sensory systems for the visually impaired (ESSVI) development and described how we have addressed these features at the Department of Electrical Electronic and System Engineering (DIEES). The "Committee on Vision" document on electronic travel aids explored the needs of the visually impaired (VI) and the features of devices that are needed to support them in their daily activities. High-performance devices can improve the life quality of visually impaired people. Many aids have already been developed that extend their "range of observation". Design engineers who understand the individual needs of the VI can build effective aids.
Target spectral estimation using direct detection and coherent detection ladar

The ability to estimate the mean frequency, peak frequency, and frequency spread of angularly unresolved hard targets is examined using both coherent and direct detection ladar simultaneously. It has been proposed that the direct detection of the return speckle intensity can be used to enhance the coherent detection ladar spectral estimates and signal processing algorithms. The direct detection ladar uses the orthogonally polarized speckle E-field return, with respect the local-oscillator laser, and does not affect the coherent detection sequence. We are concerned in obtaining precise frequency information with only coarse range requirements and, therefore, consider Q-switched laser pulses whose spectral width is much narrower than the target’s spectral bandwidth. We use spinning diffuse cones for examples. The direct detection speckle intensity spectrum is computed and is shown to be corrupted by a strong DC-component and interference between the positive and negative frequencies, which causes additional frequency spread of nearly twice the target spectral width. However, useful target spectral width information can be obtained by direct detection to help in the coherent detection signal processing. Three algorithms are described which are each shown to be within a factor of about 2 times the Cramer-Rao lower bound estimate on mean and peak frequency precision. Surprisingly robust performance of the autocorrelation function first-lag algorithm (“pulse-pair”) is demonstrated for these targets.
Evaluation of Construction Practices That Influence the Bond Strength at the Interface between Pavement Layers

This study investigated the influence of several construction practices on the bond strength at the interface between pavement layers. These practices included the surface treatment, curing time, residual application rate, and equipment tracking. Three tests were performed for estimating the bond strength between an existing hot mix asphalt (HMA) and a newly constructed HMA overlay, namely the Florida Dept. of Transportation shear tester, the University of Texas at El Paso pull off test, and the torque bond test. Testing involved a CSS-1 type emulsion as the tack coat. The results from the three tests were statistically analyzed. Generally, milling provided a significantly better bond at the interface between the existing surface and the new overlay. Curing time had a minimal effect on the bond strength. The results indicated that the absence of tack coat did not significantly affect the bond strength at the interface for the milled sections, whereas it severely decreased the strength for the nonmilled sections. The results also showed that increasing the residual rate of tack coat did not generally affect the bond strength at the interface.
Fuel Flexibility at Ignition Conditions for Industrial Gas Turbines

The variety of gaseous fuels that Siemens Industrial Turbomachinery (SIT) is requested to consider during sales enquiries has prompted product development projects that have allowed to continuously increase gas turbine fuel flexibility. The fuel flexibility often has to be guaranteed at all engine load conditions including ignition. The gas turbine ignition capabilities have therefore been analyzed in order to assess the engines current capabilities and identify further potentials.The authors’ approach for ignition fuel flexibility has been to model the minimum ignition energy (MIE) required for successful ignition and to validate the model by experiments conducted under test conditions reproducing engine start up flows at a combustion test rig. The experiments were performed using two hydrocarbon gases individually mixed with two inert gases at various concentrations. The mathematical model predicting the minimum ignition energy is applicable also to hydrocarbon and inert gases mixtures that were not used during the experimental campaign. The model was studied and developed in order to produce a tool for support of gas fuel enquiries received during the sales phase.In accordance to the predictions of the mathematical model, the experimental validation in the paper shows that the difference in MIE required to ignite the gas fuel composition depends on the inert gas used as well as the hydrocarbon used. The MIE model showed the capability of assessing if a specific gas composition can be used as a reliable start-up fuel.Copyright © 2013 by ASME
How can the exploding senior population be accommodated? Japanese struggle towards inclusive design

It was the mid-1980s when Japan was told that it will become a highly aged society in the years to come. To cope with the rapid change, a research and development project was conducted with government funding, followed by policy implementation of several kinds, in particular the proposal of dwelling design concepts acceptable in people's later years. The paper attempts to report progress, and discusses the remaining issues to be resolved to bring about an inclusive society.
A Novel Sensor-less Voltage Balancing on PUC5 to Reduce the Size of Flying Capacitor

In this paper a sensor-less voltage balancing algorithm integrated with phase-shift pulsed width modulation (PS-PWM) is proposed to reduce the size of the flying capacitor (FC) on Packed U-cell (PUC5) converter. The size of the flying capacitor that is achieved by proposed method is the least value heretofore. In conventional modulation methods charge and discharge of the FC is carried out in power frequency. In contrast, in proposed method this process is accomplished in carrier frequency. Increased frequency of FC with PS-PWM carriers leads to highly reduce the FC size. Moreover, all the benefits of Phase-shift modulation such as filters size reduction and total harmonic distortion (THD) reduction is achieved. The comparison between previous literatures and the proposed method is carried out in this paper to compare among the size of FC. Simulation is run by Matlab/Simulink to validate the performance of this proposed method on stand alone and grid connected mode.
Nanotechnology as a Preventive Engineering Solution to Highway Infrastructure Failures

AbstractThis paper reports the results of research on the application of nanomaterials to improve the quality and durability of road infrastructure. The research investigated road transportation infrastructure failures and the feasibility of preventive engineering solutions using nanotechnology. Laboratory experiments were conducted on different treated and untreated Nigerian soil samples (laterite, clay, and black soils) to study the changes in their fundamental geotechnical properties. Common engineering standards were used for the experiments and results analysis. Laboratory tests showed that treated laterite and clay soils had improved the liquid limit, plastic limit, and shrinkage index, including hydrophobic properties. The California bearing ratio (CBR) improved by as much as 87–125%. However, the black soil sample only passed the hydrophobicity test. The black soil did not exhibit any bearing strength in the CBR test, even after treatment with the nanomaterial. The paper contributes to understandi.
Influence of the Magnetic Load on High Speed Synchronous Reluctance Machines Design

Synchronous reluctance machines are becoming a widespread solution in many engineering areas thanks to their simple rotor structure, the absence of rare-earth permanent magnets and high efficiency. The design of such machines is a widely investigated research topic, given the challenge of analytically estimating their electromagnetic performance, especially when a high-speed scenario is considered. The design choices and assumptions, which include the selection of the magnetic load and the stator and rotor lamination materials, play an important role in the machine performance. Consequently, it is of paramount importance to assess their validity. This paper, after a brief re-call of a general design methodology able to consider all the magnetic non-linearities and structural and thermal limitations occurring at high-speed, presents a sensitivity analysis against the magnetic load when a Cobalt-based alloy is adopted for both stator and rotor laminations. The analysis is carried out for different speeds up to 90 krpm, in order to draw general design guidelines for a given outer envelope and cooling system.
Recommendation System for Energy Consumption Behavior Change on Residents’ Response and Stress

Home energy management system (HEMS), enabled by the development of the Internet of Things (IoT), issue behavior change recommendations to encourage residents to reduce their energy consumption. Receiving these suggestions from HEMS makes it easier for them to set specific reduction goals and raise their awareness of energy saving. This feedback will lead to effective power reduction in the household sector. However, each user has unique preferences, and uniformly generated recommendations may not be followed if they do not match the preferences of the specific user. In addition, frequent recommendations that are not aligned with their preferences may stress users and decrease their motivation to reduce energy consumption. This paper presents a practical method of making behavior change recommendations reflecting users’ response rates and considering their stress. Targeting the action of opening a window, we illustrate how our system induces behavioral change. To increase the users’ response rate and reduce their stress, we adjust the recommendation for each user from two perspectives. First, assuming that users open windows mainly depending on the external temperature, humidity, wind, and weather, we introduce the k-nearest neighbors (k-NN) classification using these parameters as the explanatory variables to predict the possibility that the user accepts the window-opening recommendation. Generating recommendations only when the predicted probability is high enables building a unique recommendation system considering user preferences. Second, if the recommendations are sent frequently, users may become tired of following them; this leads to a situation in which users ignore recommendations or turn off their notifications. To avoid such a situation, we propose adjusting the delivery interval according to the users’ response rate. When we schedule the notification cycle, we introduce a forgetting curve, assuming that the users’ stress on the recommendation decreases over time. We conducted a simulation using historical weather data. The response rate and thermal sensation of users with different variations were set, and the delivery timing of the recommendation was changed according to these factors. The proposed methods are expected to effectively generate behavioral changes by having users take medium- to long-term initiatives without lowering their motivation.
Individual Exposure Levels in People Environmentally Exposed to Crocidolite

Abstract The objective of this article is to assign individual airborne crocidolite exposure levels to former residents of the town of Wittenoom, Western Australia. All environmental monitoring programs carried out in the town since 1966 were reviewed and assessed for their suitability for use in estimating individual exposure to crocidolite. These programs measured respirable fibers greater than 5 μm in length. Duration of residence was determined from questionnaires, work history sheets of the Australian Blue Asbestos Company, and the various sources used to assemble a cohort of previous residents. All exposure measurements were calculated assuming continuous exposure over 24 hours per day, 7 days per week. Intensity of exposure and cumulative exposure were estimated for each person in the cohort. All environmental monitoring surveys carried out at Wittenoom have detected some crocidolite fibers. The levels of fibers have shown a continuing decrease since the mining operations ceased in 1966. Most of th.
Using Deep Convolutional Neural Networks and Infrared Thermography to Identify Coal Quality and Gangue

Owing to the enormous demand for and growing large-scale use of coal in the China, India and USA speculation has arisen about possible hazards to environmental quality and human health. The contents of fly ash and volatile matter in low-quality coal are extremely harmful to the environment. As a result, there is still much to be explored regarding known hazards and harms to the natural environment of the Earth. For the detection of high-quality coal, we propose a new method of distinguishing coal quality or types (i.e., anthracite, bituminous coal, subbituminous coal and lignite) and efficiently separating gangue and rock from the production lines of coal preparation plants (CPPs) by exploiting infrared machine vision and convolutional neural networks (CNNs) for deep learning, which can make coal use less harmful to humans and nature and/or more useful for general welfare. In this paper, we carried out two experiments. First experiment to study the reaction coal types, gangue and rock with infrared radiation at temperatures of 50°C, 70°C, 90°C, 110°C, and 150°C. Second experiment, several common CNN models (i.e., AlexNet, DarkNet-58, GoogLeNet, NasNet_Mobileb, ResNet-18, MobileNet-v2, Inception-v3 and DenseNet-201) are trained and tested to classify coal types and distinguish gangue and rock. We achieve a remarkable classification accuracy of 100% in these training and testing processes when employing the ResNet-18 and DenseNet-201 models.
GRU and LSTM Comparison for Black-Box Modeling of Power Electronic Converters

Considering the vast application of Power Electronic Converters (PEC) in numerous modern technologies, modeling their behavior is of immense importance. These components are non-linear and modeling their precise behavior requires a relatively substantial amount of computational resources. In this paper, a modeling method based on Gated Recurrent Unit (GRU) networks is proposed that is capable of modeling PECs with the aid of machine learning. Furthermore, the precise datasheets of many commercial over-the-shelf converters are not readily available. Thus, the proposed method is a black-box modeling method that only requires the input and output signals of a converter to model its dynamic behavior. For a performance comparison, the proposed GRU-based method, as well as another similar method based on Long-short Term Memory (LSTM) networks, are used to model a voltage-regulated variable-load DC/DC buck converter. A detailed switching model of the aforementioned converter is simulated in Matlab/Simulink environment to generate the required datasets. This model is also used as a reference for comparison. Ultimately, both of the models are exported to Matlab/Simulink after training to be simulated and assessed.
A Novel Routing Method with Load-Balancing in Wi-SUN FAN Network

This paper proposes a novel routing method considering load balancing to improve transmission characteristics of a large-scale Wi-SUN field area network (Wi-SUN FAN) based on IEEE 802.15. 4. Wi-SUN FAN is a wireless communication standard that enables the interconnection of many Internet-of-Things (IoT) devices outdoors. Wi-SUN FAN prevents packet collisions by frequency hopping in the media access control (MAC) layer. Besides, Wi-SUN FAN constructs multi-hop networks autonomously using Internet protocol version 6 routing protocol for low-power and lossy networks (RPL) at the network layer. In RPL, each node determines its parent node based on the quality of communication. Therefore, many nodes are likely to choose the same parent node with good radio reachability, resulting in many packets being sent to the parent node. The heavy load for the specific node makes frequency hopping not work effectively, and transmission characteristics deteriorate. The proposed routing method with a load-balancing algorithm eliminates the load concentration and improves the average transmission success rate by approximately 9.4% on the specific nodes.
Physical properties of solid waste materials

The physical properties of several common solid waste materials including poultry manure and compost were quantified under a variety of management practices and programs. Parameters relevant to the design and analysis of handling, transporting, and spreading equipment including moisture content, bulk density, angle of repose, maximum lump size as well as the static coefficient of friction characteristics were evaluated. Poultry manures tested included fresh crust and fresh total cleanout as well as crust and total cleanout stored outside and exposed to rainfall. Fresh composted materials tested were poultry manure with poultry mortalities, municipal solid waste (MSW) with dewatered sludge, and MSW with poultry manure. Analysis of variance results indicated outside storage and exposure to rainfall of both total cleanout and crusted poultry manure significantly increased moisture content, wet bulk density, and static friction properties. The moisture contents of each of the compost materials were significantly different, but there were no significant differences in bulk density or angle of repose. Overall trends for the design and analysis of solid waste handling systems were: wet bulk densities of solid waste materials depend primarily on moisture content and can be predicted without specific knowledge of the type or source of waste, the averages and ranges of static friction values measured suggest there is little practical difference between the construction and waste materials tested, and unscreened wastes do exhibit large lump sizes which should be considered when developing handling and conveying systems.