Miracle-dz/UniFAR-FTUs huggingface dataset:
A low cost master and slave distributed intelligent meter for non-intrusive load classification and anomaly warning

In the recent years, there is a growing need for remote monitoring of electrical systems to assist users in making informed decision in managing their electrical systems. On top of the energy consumption and power usage, it is very useful to provide users fault detections, anomaly warnings and classification of load for predictive maintenance. This paper describes a low-cost solution that consists of multiple distributed slave meters with a single master computer. The distributed slave meter acquires the current waveform from the investigated cable of interest with non-intrusive current transducer. The low-cost hardware and small computer conditioned the data and extract a 2-feature data that will be send to the master computer remotely over Wi-Fi network. The master computer identifies each slave meters by their IP addresses and will perform logging, high level processing for classification, fault detection and anomaly warning. This solution can be implemented as a distributed monitoring network over a number of circuits in a building or vicinity, with the option of expanding into an Internet of Things (IoT) implementation. It can also be used as an ad hoc standalone investigation of a suspicious branch circuit for faults or anomalies. This solution has been tested with lighting, thermal and motor loads in an electrical circuit.
Decentralized state estimation for distribution systems using artificial neural network

In this paper we present a decentralized state estimation method to support real-time Volt/Var optimization in distribution network with high penetration of distributed generation. The network is divided into sub-areas according to the location of the generation units and the mutual information (MI) between the states of interest and the available measurements. The proposed decentralized state estimation scheme only relies on local information and on a limited amount of information from neighboring areas. In each area, an artificial neural network (ANN) is used to estimate the loads consumptions. The proposed approach is tested using a modified IEEE 34-node test feeder. The effectiveness of the method is validated on a Hardware-In-the-Loop (HIL) simulation platform. To evaluate the accuracy and efficiency of the proposed decentralized approach we compared the results obtained to a centralized and a totally local approach.
Nearly Non-Coupling Coil Array Allowing Many Independent Channels for Magnetic Communication

Crosstalk between coil array components in magnetic systems has to be minimized to achieve enhanced performance, such as high data rate, high-power transfer efficiency, and simultaneous wireless information and power transfer. This paper presents a scalable non-coupling coil array composed of perpendicularly arranged quadrupole loop coils. The proposed coil array permits the number of fully or nearly independent channel streams to be increased to meet user’s requirements, unlike conventional coil arrays which have a limited number of channel streams. The proposed non-coupling coil array structure is investigated by theoretical analysis and 3-D electromagnetic simulation, and the performance of the proposed non-coupling coil array is verified with a prototype implementation. The proposed coil array shows relatively high signal-to-interference and noise power ratio of around 20 dB even at the three times further distance of a coil diameter.
Increasing the reliability of drones due to the use of quaternions in motion

The article suggests a positioning system structure for a small unmanned aerial vehicle (SUAV), which performs a short-term flight autonomously. Special attention is paid to LibrePilot autopilot structure and the variant of connecting external systems to it, which allows performing autonomous flight without operator intervention, based on the obtained data. The implementation of the built-in inertial navigation system in conjunction with a GPS receiver, a video camera and the OpenCV library for image recognition is investigated for solving orientation problems and autonomous control of SUAV. In addition, the ability of Kalman filter, which is built into the LibrePilot controller, is analysed, as well as the performance of the computing system based on the received data from gyroscopes.
An Efficient Transmit Power Control Strategy for Underlay Spectrum Sharing Networks With Spatially Random Primary Users

With the ever-increasing spectrum requirements for transmitting explosively growing mobile data, spectrum-efficient solutions need to be integrated into future mobile networks. Spectrum sharing enables the primary system to share licensed spectrum with the secondary system. Thus, it is conceived as an appealing solution for improving spectrum usage to eliminate the spectrum supply-demand gap. In this paper, we develop an efficient transmit power control strategy for underlay spectrum sharing networks with spatially Poisson-distributed primary users. A distinguishing feature of the proposed strategy is that it only requires channel state information and location information of a few primary users close to the secondary transmitter, rather than those for all primary users. Furthermore, we evaluate the outage performance of the secondary system and the interference situation of the primary system under this kind of transmit power control strategy. Numerical results demonstrate that the proposed transmit power control strategy can achieve near-optimal outage performance compared to the perfect power control strategy, while reducing the control complexity and the feedback burden significantly at the same time.
The Flow of Learning

Europe's Journal of Psychology, 2018, Vol. 14(2), 291–295, doi:10.5964/ejop.v14i2. 1660 Published (VoR): 2018-06-19. *Corresponding author at: Institute of Psychology, University of Wroclaw, Dawida 1 St., 50-527 Wroclaw, Poland. E-mail: maciej.karwowski@uwr.edu. pl This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/ licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Vision Odometer Based on RGB-D Camera

In order to solve the problem of self-localization of robots in unknown environment, a method based on RGB-D camera is proposed. RGB-D camera is a visual sensor that can collect RGB images and depth images simultaneously in recent years. Firstly, the introduction of the mainstream RGB-D camera is introduced. Then, the ORB feature of the current image is extracted from the visual odometer and the features are matched with the key frames. The RANSAC algorithm is used to estimate the interframe motion iteratively. Finally, the key frames are extracted and utilized the ICP is optimized to get the optimal registration of key frame pose. The method can effectively improve the positioning accuracy of mobile robots.
Colouration in Local Wave Field Synthesis

Sound field synthesis techniques including wave field synthesis and near-field-compensated higher order ambisonics aim at a physically accurate reproduction of a desired sound field inside an extended listening area. This area is surrounded by loudspeakers individually driven by their respective driving signals. The latter have to be chosen such that the superposition of all emitted sound fields coincides with the desired one. Due to practical limitations, artefacts impair the synthesis accuracy resulting in a perceivable change in timbre. Recently, two approaches to so-called local wave field synthesis were published that enhance the reproduction accuracy in a limited region while allowing stronger artefacts outside. This paper reports on two listening experiments comparing conventional techniques for sound field synthesis with the mentioned approaches. Furthermore, the influence of different parametrizations for local wave field synthesis is investigated. The results show that the enhanced reproduction accuracy in local wave field synthesis leads to a reduction of perceived colouration, if a suitable parametrization is chosen.
Towards accurate classification of HTTPS traffic in Software-Defined Networks

In nowadays Internet, there is a strong trend to encrypt the traffic in order to protect users' privacy. This results in a hard challenge for traffic classification, as the payload in the packets cannot be accessed anymore. In this context, some techniques were proposed for traditional networks in order to classify this traffic. However, we could not find previous works addressing encrypted traffic classification considering the particularities of the Software-Defined Networking (SDN) paradigm. In this paper we present an OpenFlow-based classification system which combines techniques leveraging information in SSL/TLS certificates and DNS traffic to perform accurate flow-level classification for encrypted traffic. We make experiments with real-world traffic to evaluate the overall classification accuracy of our system as well as the accuracy detecting specific popular applications (e.g., Netflix). Furthermore, we assess the processing overhead when deploying our system in SDN environments. As a result, we observe that the support provided by OpenFlow enables to achieve a high accuracy with a more reduced processing overhead than in traditional networks, where typically the whole traffic is mirrored to an external collector that classifies the traffic.
The Determination of an Appropriate Time for Placement of the Classic Laryngeal Mask Airway in Patients Undergoing General Anesthesia

Background The management of the airways is an essential component of anesthesia planning. Laryngeal mask airway (LMA) plays an important role in modern anesthesia, however, intubation by LMA has some complications. It may cause inadequate anesthesia depth, which can lead to adverse events. The aim of this study was to evaluate the optimal time for intubation by LMA under general anesthesia. Methods This study was conducted on 96 patients, who underwent operation and were appropriate candidates for intubation with appropriate LMA. The participants were divided to four groups, each with 24 cases, based on the time interval between anesthetic agent administration and intubation with LMA; 15 seconds for the first group, 16 to 30 seconds for the second group, 31 to 45 seconds for the third group, and 45 to 60 seconds for the fourth group. The patients involved in these groups were selected based on the following prerequisites, patients’ age, gender, easy intubation, need for additional drug administration, basic blood pressure before drug administration, within the time intervals one, three, and five minutes after placement of LMA, duration of LMA, SaO2 before and after placement of LMA, coughing, patient’s movement, laryngospasm, gag reflex after intubation, allowing appropriate ventilation, presence of sore throat after surgery, number of attempts, extent of mouth opening and leak in peri-LMA space. Results Overall, 72 males and 24 females participated in this study with a mean age of 40.64. Intubation by LMA was performed easily during the first attempt in 58% of the participants, with minimal resistance in 28.6% and with some problems during the second attempt in 10.5% of the cases. Throat pain after the operation was significantly lower. Systolic and diastolic pressure and heart rate had no statistically significant difference. Conclusions The results showed that in the first 15 seconds after the drug (e.g. propofol) administration, there were lower complications, rapid placement, and optimized time for the placement of LMA. The rate of success and its quality were reduced during the first attempt of insertion and termination of the effect of propofol.
Detection of the vocal cords' vibrations: Effect of the transducer's position

A method to acquire the signal of the vocal cords' vibrations was developed and presented. It is a non-invasive method that is based on attaching a transducer element to a collar and wrapping it around the individual's neck. The Short Term Fourier Transform (STFT) technique is applied on the collected signal to decompose it into its frequency contents. The features defined in terms of a range of frequencies are extracted for speaker identification purposes. The position of the transducer on the human's neck could affect the quality of the collected signal and consequently, the extracted features. Therefore, the study of the effect of the transducer's location is in accordance. In this context, the mediums through which the vocal cords' vibrations are propagated until their detection by the transducer are modeled. Subsequently, numerical simulation experiments are performed to determine the best location on the human's neck for transmission purposes.
Structural representation of synthesis methods of finite state machine with datapath of transitions

In this paper it is shown that many different methods can be used to synthesize a finite state machine with datapath of transitions. The choice of method depends on the given initial conditions and on the existing limitations of the design process. A number of synthesis methods possessing similar features are proposed to be represented in the form of a structure. As components of such structure are elements of a mathematical model of a finite state machine with datapath of transitions. The connections between components of the structure reflect their mutual influence in the process of synthesis of the finite state machine.
Smart meter for the IoT

In recent years, smart devices are increasingly. These devices allow making cities smart, enabling communication not only among people but also among things, creating a new system nowadays known by the term IoT (Internet of Things). A smart city is based on a smart grid that allows to intelligently manage the power grid. In order to do this, the network must have intelligent meters that can communicate bidirectionally with the network. This market has led to a proliferation of smart meters that give the opportunity to measure the consumption of each single device in homes. The most part of smart meters are based on a chip that calculates the parameters needed to estimate energy consumption. In this paper, the authors consider a smart meter based on a common chip that calculate the power consumption and the meter characterization is reported.
Adaptive Approximate Computing in Arithmetic Datapaths

Editor’s note: Approximate arithmetic units are used in error tolerant applications, like image processing, to minimize energy, and resource usage in general, by keeping accuracy to the minimum level required. However, in a datapath errors may accumulate over successive approximate operations. This article proposes a scheme to bound the size of the errors with adaptive error detection and correction as an integral part of the datapath. —Axel Jantsch, TU Wien
Universell eller inntektsavhengig barnetrygd

For i storre grad a rette barnetrygden mot barnefamilier med lavere inntekter, kan en vurdere a beskatte eller inntektsprove ordningen. I denne artikkelen diskuterer vi virkninger pa inntektsfordeling og arbeidstilbud av a endre barnetrygden fra a vaere en universell ordning til en behovsprovd stonad, med basis i et datamateriale for familier med gifte foreldre. De direkte fordelingsvirkningene er analysert ved skattemodellen LOTTE, mens effekter pa arbeidstilbudet er analysert ved simuleringer av en arbeidstilbudsmodell for diskret valg. Vi finner at dersom stonaden i storre grad ytes til familier med lave inntekter, vil arbeidstilbudet for kvinner kunne bli betydelig redusert. En jevnere fordeling av inntekt byttes mot redusert arbeidstilbud (og redusert markedsbasert verdiskapning).
A cloud system to improve sensor availability and data reliability in remote monitoring

Despite the advancement of embedded devices, low-power sensors and networking technologies, one of the main challenges in remote monitoring systems is sensor availability and data reliability. Sensors' fault and failure may affect the reliability of the monitored data, and subsequently corrupt the outcome of the data analytics. Existing solutions focus on improving sensor nodes to enhance data reliability and couple it with various energy harvesting techniques to prolong the availability of sensor nodes. This paper presents a complementary solution to the existing solutions, by analyzing the correlation between data from different sensor nodes using cloud computing resources during operation time. The discovered relationship between the sensor nodes can then be used to improve data reliability and availability of sensor nodes. Performance evaluations using real datasets show that there are relationships between the collected data, and that the Mean Absolute Percent Error (MAPE) can be as low as 4% when using our solution.
Optimization of low-power oscillator topology for frequency modulated MEMS inertial sensors

This work proposes two different feedback oscillator loops for MEMS frequency-modulated (FM) inertial sensors, identifying the optimum topology in terms of power-noise trade-off. More in detail, the focus is on the critical 90-degree shifter stage, realizable through either an analog integrator or a phase-locked-loop (PLL). After a theoretical analysis, the first option turns out to minimize noise-folding related issues, obtaining lower noise level at lower power consumption with respect to the PLL approach. In order to verify the theoretical model, the two loops are fabricated and coupled with a frequency modulated accelerometer measuring the oscillator loop phase noise at the system output.
Intramedullary spinal cord metastasis from malignant melanoma: a case report of a central nervous system secondary lesion occurred 15 years after the primary skin lesion resection

Address for correspondence: Agnieszka Nowacka PhD, Department of Neurosurgery, Neurotraumatology and Pediatric Neurosurgery, Collegium Medicum, Nicolaus Copernicus University, 9 Skłodowskiej-Curie St, 85-094 Bydgoszcz, Poland, phone: +48 601 644 756, e-mail: dr.agnieszka. nowacka@gmail.com Received: 11.09. 2017, accepted: 12.10. 2017. Intramedullary spinal cord metastasis from malignant melanoma: a case report of a central nervous system secondary lesion occurred 15 years after the primary skin lesion resection
Joint-Space Impedance Control Using Intrinsic Parameters of Compliant Actuators and Inner Sliding Mode Torque Loop

A new control law for joint-space impedance in robots with variable impedance actuators is presented. The objective is achieved using reduced information on high order derivatives compared to standard approaches, therefore leading to more reliable interactions with unknown environments. Most importantly, the impedance characteristic is given by the real stiffness and damping coefficients of each actuator, therefore updating strategies of the latter directly modify the system response obtained on the link side. The method is evaluated both in simulations and experiments. Additionally, the control law is also adapted for systems with series elastic actuators.
Location and fault detection of catenary support components based on deep learning

Catenary support components (CSCs) are the most important devices that support the overhead line and messenger of catenary system in electric railway. The faults of CSCs can result in the poor state of catenary system, and directly influence the normal operation of trains. In order to efficiently locate and identify the faults of CSCs, the deep learning algorithms are tried to process the captured images of CSCs in this paper. First at all, a dataset of CSCs that contains 50k labeled instances with 12 categories is built. Second, some traditional location methods of CSCs are introduced, and four recent representative deep learning networks, namely Faster RCNN (VGG16 and ResNet101), YOLOv2 and SSD, are applied to locate 12 categories CSCs, simultaneously and separately. In order to find more suitable algorithms of deep learning, their location performances are compared and evaluated. For the location of single category of CSCs, these algorithms show good performance. However, the models that are adopted to simultaneously locate all categories have a poor location performance on small-scale components of CSCs. Third, aiming at the fault detection of CSCs, some common methods are presented and compared, and the deep learning algorithms are tried to detect the faults of CSCs. Finally, the issues of deep learning for location and fault detection of CSCs, especially for the simultaneous location of CSCs are proposed and discussed, and further prospects are given.
To What Extent Are Cryopreserved Sperm and Testicular Biopsy Samples Used in Assisted Reproduction?

Background: Testicular biopsies and ejaculated spermatozoa are routinely cryopreserved in many units but the fate of these samples has not provoked large interest. This prompted us to review our data accumulated during a period of 20 years (1997 to 2016). Methods: For patients with biopsies (group 1) or ejaculated spermatozoa (group 2), an attempt was made to evaluate whether the samples stored, had been discarded with the patient’s consent or because the patient had died, or whether they had been transported to another laboratory. In each of these categories, a previous use in our program of assisted reproduction was assessed. Results: The total utilization rate in group 1 (n=95) was 53.7% and only 5.48% in group 2 (n=365). In both groups, deceased patients had not previously used their cryopreserved samples. In detail, the utilization rates for still banked, discarded and transferred samples were 84.2%, 50% and 27.3%, respectively in group 1 and 2.88%, 10.4% and 10%, respectively in group 2. Conclusion: The exact reasons for the low utilization rates of cryopreserved male gametes remain to be explored. A closer contact between sperm banking units and patients might be useful to discuss the need for further storage of the probes, their possible disposal or the prospects when a specific use for assisted reproduction is intended.
Smart Transducer Integrator (STI) for standardized system-of-systems monitoring

With the proliferation of embedded devices and communication systems as well as their optimization in cost, size, and power requirements, at the moment we can find a large number of applications for Smart Sensor Networks (SS-Net) and Internet of Things (IoT) systems. Applications include transport systems (such as oil, water, and gas pipelines), smart houses, and wearables, just to mention a few. Needs when working with these types of systems are standardization, modularity, and scalability considering reducing costs associated with integration, upgrades, interoperability, portability, manageability, and the preparation required to design and configure new systems. Measurability, testability, and reliability are also important aspects that should be considered in the design of critical systems. In this paper, the Smart Transducer Integrator (STI) system is introduced, which provides a building block for the implementation of SS-Nets and IoT. The STI aims to respond to the current SS-Net and IoT needs. Innovative aspects of the STI system are embedded standardized mechanisms for enhanced reliability and ubiquitous operation considering the capability to operate even in completely sealed or inaccessible environments, such as metallic confinements.