Design And Simulation of An Electro-Optic Even Parity Bit Error Detection System

In the present day, optical communication technology is proving to be one of the potential replacements to the current electronic-based systems due to its much higher data transmission rate with low loss and electromagnetic interference. This paper designed and simulated our proposed circuit of a digital photonic even parity bit error detection system that is widely employed for the long-range digital signal transmission. Silicon photonic micro-ring resonators are used as their core component. Each of the rings is configured to operate as a digital logic XOR mode by taking advantage of the silicon waveguide's resonance shifting properties. Dynamic response characterization was carried out by simulating the proposed circuits at the data rate of 1-Gbps, with the data sampling rate of 1.6-THz. A clear timing waveform was generated to confirm that the proposed circuit operates as the parity bit error detection system.

Effect of Sampling Rate on Photovoltaic Self-Consumption in Load Shifting Simulations

Grid-connected photovoltaic (PV) capacity is increasing and is currently estimated to account for 3.0% of worldwide energy generation. One strategy to balance fluctuating PV power is to incentivize self-consumption by shifting certain loads. The potential improvement in the amount of self-consumption is usually estimated using smart meter and PV production data. Smart meter data are usually available only at sampling frequences far below the Nyquist limit. In this paper we investigate how this insufficient sampling rate affects the estimated self-consumption potential of shiftable household appliances (washing machines, tumble dryers and dishwashers). We base our analyses on measured consumption data from 16 households in the UK and corresponding PV data. We found that the simulated results have a marked dependence on the data sampling rate. The amount of self-consumed energy estimated with data sampled every 10 min was overestimated by 30–40% compared to estimations using data with 1 min sampling rate. We therefore recommend to take this factor into account when making predictions on the impact of appliance load shifting on the rate of self-consumption.

A passive energy-based method for footstep impact localization, using an underfloor accelerometer sensor network with Kalman filtering

An underfloor accelerometer sensor network can be used to track occupants in an indoor environment using measurements of floor vibration induced by occupant footsteps. To achieve occupant tracking, each footstep impact location must first be estimated. This paper proposes a new energy-based algorithm for footstep impact localization. Compared to existing energy-based algorithms, the new algorithm achieves higher localization accuracy and removes a previously required calibration step (removal of the need to estimate floor-dependent parameters). Furthermore, the algorithm uses a much smaller data sampling rate compared to time of flight/arrival localization methods, which greatly reduces data and data-processing time. The new algorithm is a two-step location estimator: the first step is a coarse location estimate, with the second step as a fine location search through a nonlinear minimization problem. The performance of the proposed algorithm is evaluated using a single occupant walking experiment on an instrumented floor inside an operational smart building. This paper also demonstrates that higher localization accuracy is obtained using an additional Kalman filtering scheme.

094 Towards objective testing in parkinson’s disease: a systematic review of the literature looking at assessment of postural sway

IntroductionParkinson’s Disease (PD) is associated with increased mortality and reduced quality of life. There is currently no accurate objective measure for use in diagnosis or assessment of severity. Analysis of postural sway may help in this regard. This systematic review aimed to assess the effectiveness of the various features currently used to analyse postural sway.MethodsFive databases were searched for articles that examined postural sway in both PD patients and controls. An effect size (ES) was derived for every feature reported in each article. The most effective features and feature-families were determined, along with the influence on these measures of data sampling rate and experimental condition.Results441 papers were initially retrieved, of which 31 met the requirements for analysis. The most commonly-used features were not the most effective (e.g. PathLength had an ES of 0.47 while TotalEnergy had an ES of 1.78). Decreased sampling rate was associated with decreased ES (e.g. ES of PathLength lowered from 1.12 at 100 Hz to 0.40 at 10 Hz). Being off medication was associated with a larger ES (e.g. ES of PathLength was 0.21 on medication and 0.83 off medication).ConclusionsSome measures of postural sway are better able to distinguish PD patients from controls than others. ES is enhanced by using a higher sampling rate and studying patients off medication. These results will inform future studies looking at postural sway in PD and contribute to the aim of finding an objective marker of the disease.

Data Requirements for Applying Machine Learning to Energy Disaggregation

Energy disaggregation, or nonintrusive load monitoring (NILM), is a technology for separating a household’s aggregate electricity consumption information. Although this technology was developed in 1992, its practical usage and mass deployment have been rather limited, possibly because the commonly used datasets are not adequate for NILM research. In this study, we report the findings from a newly collected dataset that contains 10 Hz sampling data for 58 houses. The dataset not only contains the aggregate measurements, but also individual appliance measurements for three types of appliances. By applying three classification algorithms (vanilla DNN (Deep Neural Network), ML (Machine Learning) with feature engineering, and CNN (Convolutional Neural Network) with hyper-parameter tuning) and a recent regression algorithm (Subtask Gated Network) to the new dataset, we show that NILM performance can be significantly limited when the data sampling rate is too low or when the number of distinct houses in the dataset is too small. The well-known NILM datasets that are popular in the research community do not meet these requirements. Our results indicate that higher quality datasets should be used to expedite the progress of NILM research.

CALCULATION OF ENGINE PARAMETERS USING RECONFIGURABLE HARDWARE

The feasibility of real-time calculation of parameters for an internal combustion engine via reconfigurable hardware implementation is investigated as an alternative to software computation. A detailed in-hardware field programmable gate array (FPGA)-based design is developed and evaluated using input crank angle and in-cylinder pressure data from fully instrumented diesel engines in the QUT Biofuel Engine Research Facility (BERF). Results indicate the feasibility of employing a hardware-based implementation for real-time processing for speeds comparable to the data sampling rate currently used in the facility, with acceptably low level of discrepancies between hardware and software-based calculation of key engine parameters.

INSTRUMENTASI PEMANTAUAN JARAK JAUH UNTUK MENGUKUR KINERJA TURBIN ARUS PASANG SURUT LAUT

Tulisan ini menjelaskan tentang sistem instrumentasi yang dapat diaplikasikan pada turbin arus pasang surut laut. Sistem instrumentasi pada turbin arus pasang surut laut ini meliputi seperangkat sensor pembaca parameter kinerja turbin, perekam data untuk mencatat dan menyimpan data yang dihasilkan sensor, dan sistem telemetri untuk mengirim data ke operator turbin. Sistem instrumentasi tersebut digunakan agar kinerja turbin arus pasang surut laut yang dipasang di suatu tempat dapat dipantau dari jarak jauh secara kontinu dan real time.Tujuan penelitian instrumentasi pengukuran kinerja turbin arus pasang surut laut adalah untuk merancang dan menguji sistem instrumentasi dalam mencatat, menyimpan, dan mengirimkan data parameter kinerja turbin. Pengujian dilakukan di perairan Muara Karang, Jakarta pada 15 November - 25 Desember 2012. Data parameter kinerja turbin yang diambil meliputi teganganlistrik generator, arus listrik generator, putaran turbin, serta tegangan baterai. Data tersebut akan tersimpan pada perekam data dengan kerapatan data(sampling rate) setiap 8 detik. Data tersebut juga akan dikirim ke operator turbin, dengan waktu pengiriman data setiap satu jam, yang berisi data parameter kinerja turbin setiap 5 menit. Dari data hasil uji coba, dapat dibuat grafik hubungan antara putaran turbin dengan tegangan generator dan putaran turbin dengan daya generator. Pada grafik putaran turbin dengan tegangan generator dan putaran turbin dengan daya generator, diperoleh hasil bahwa secara umum tegangan generator dan daya generator akan naik seiring dengan kenaikan putaran turbin, dengan kenaikan bersifat fluktuatif. Dari data pengujian, dapat disimpulkan bahwa perangkat keras instrumentasi turbin arus pasang surut laut telah berhasil dibuat dan dapat berfungsi dengan baik dalam mencatat, menyimpan, dan mengirimkan data parameter kinerja turbin.

Impact Analysis of Guidance Instrument Error Separation Accuracy on Sampling Rate of Inertial Navigation Equipment

Based on the linear model of guidance instrument error separation, study on the separation accuracy affected by data sampling rate of inertial navigation equipment. First, theoretically proved that the higher data sampling rate is, the higher separation accuracy we can get. Second, a method for determining the optimal sampling rate is presented, whose idea is from the model itself. At last, the simulation results can verify the above two conclusions.

Inhomogeneous Structure in High-Speed and High-Number-Density Sprays

A L2F (Laser 2-Focus velocimeter) was applied for the measurements of the velocity and size of droplets in diesel fuel sprays. The micro-scale probe of the L2F has an advantage in avoiding the multiple scattering from droplets in a dense region of fuel sprays. A data sampling rate of 15MHz has been achieved in the L2F system for detecting almost all of the droplets which passed through the measurement probe. Diesel fuel was injected into the atmosphere by using a common rail injector. Measurement positions were located in the planes 15, 20, and 25 mm apart from the injector nozzle exit. Measurement result showed that the integral time scale of turbulence in size was nearly the same as the one in frequency. And the integral time scale of turbulence in velocity was about two times larger than the time scale of size and frequency.