Data Reduction System Research Articles

Characterization of K2-167 b and CALM, a new stellar activity mitigation method

ABSTRACT We report precise radial velocity (RV) observations of HD 212657 (= K2-167), a star shown by K2 to host a transiting sub-Neptune-sized planet in a 10 d orbit. Using Transiting Exoplanet Survey Satellite (TESS) photometry, we refined the planet parameters, especially the orbital period. We collected 74 precise RVs with the HARPS-N spectrograph between August 2015 and October 2016. Although this planet was first found to transit in 2015 and validated in 2018, excess RV scatter originally limited mass measurements. Here, we measure a mass by taking advantage of reductions in scatter from updates to the HARPS-N Data Reduction System (2.3.5) and our new activity mitigation method called CCF Activity Linear Model (CALM), which uses activity-induced line shape changes in the spectra without requiring timing information. Using the CALM framework, we performed a joint fit with RVs and transits using exofastv2 and find Mp = $6.3_{-1.4}^{+1.4}$ $\, M_{\hbox{$\oplus $}}$ and Rp = $2.33^{+0.17}_{-0.15}$ $\, R_{\hbox{$\oplus $}}$, which places K2-167 b at the upper edge of the radius valley. We also find hints of a secondary companion at a ∼22 d period, but confirmation requires additional RVs. Although characterizing lower mass planets like K2-167 b is often impeded by stellar variability, these systems especially help probe the formation physics (i.e. photoevaporation, core-powered mass-loss) of the radius valley. In the future, CALM or similar techniques could be widely applied to FGK-type stars, help characterize a population of exoplanets surrounding the radius valley, and further our understanding of their formation.

Analisis Dampak Perilaku Bullying Terhadap Hasil Belajar Siswa Kelas V SD Kayuapu

This research was motivated by students who experienced bullying and affected learning outcomes. The purpose of this study is to describe the analysis of the impact of bullying on the learning outcomes of grade V students of SD Kayuapu. The type of research used is qualitative descriptive research. This type of data collection consists of interviews and observations. Analysis of data used in research is carried out through the use of data reduction systems, data presentation, and conclusions. The stages used in this study are the stages of preparation, implementation, and data analysis. Based on the results of the study, it was found that there are three dimensions of student learning difficulties. that is, in the school environment and home environment. In the school environment, students feel afraid to be near their classmates. This is because the student is under pressure from several other students in the form of verbal bullying. The second is that student learning motivation is disrupted due to the bullying they face, making students feel alone and have no learning motivation or learning encouragement from those around them, the third One of the important impacts in mental health is that students tend to be quiet, keep their distance, and prefer not to mingle with their friends

Adaptive data reduction workflows for astronomy: The ESO Data Processing System (EDPS)

Context. Astronomical data reduction is usually done via processing pipelines that consist of a series of individual processing steps that can be executed one at a time. These processing steps are then strung together into workflows and fed with data to address a particular processing goal. Examples of such pipeline processing goals are the quality control of incoming data from telescopes, unsupervised production of science and calibration products for an archive, and supervised data reduction to serve the specific science goals of a scientist. For each of these goals, individual workflows need to be developed. These workflows need to evolve when the pipeline, observing strategies, or calibration plans change. Writing and maintaining such a collection of workflows is therefore a complex and expensive task. Aims. In this paper we propose a data processing system that automatically derives processing workflows for different use cases from a single specification of a cascade of processing steps. Methods. The system works by using formalised descriptions of data processing pipelines that specify the input and output of each processing step. Inputs can be existing data or the output of a previous step. The rules for selecting the most appropriate input data are directly attached to the description. Results. A version of the proposed system has been implemented as the ESO Data Processing System (EDPS) in the Python language. The specification of processing cascades and data organisation rules use a restrictive set of Python classes, attributes, and functions. Conclusions. The EDPS implementation of the proposed system was used to demonstrate that it is possible to automatically derive from a single specification of a pipeline processing cascade the workflows that the European Southern Observatory uses for quality control, archive production, and specialised science reduction. The EDPS will be used to replace all data reduction systems using different workflow specifications that are currently in use at the European Southern Observatory.

Pengkondisi Sinyal RTD Presisi pada Terowongan Angin Indonesian Low-Speed Tunnel

The temperature of the Indonesian Low-Speed Tunnel (ILST) wind tunnel test section was measured using a Pt100-type Resistance Temperature Detector (RTD) sensor. With the upgrade of the Indonesian Low-Speed Tunnel - Data Acquisition and Reduction System (ILST-DARS) using Ethernet communication, an integrated RTD linearization circuit was designed with the Conditioning Unit (CU) Mk3 to replace the Newport 267B 16-bit parallel and DAS-Hub as the current RTD interface. In this research, the design of the signal conditioner uses the RTD_Linearization_v7.xls program from Texas Instruments, the LTspice simulator software, and the AMP01E precision instrumentation amplifier. Based on the calibration results in the range of 20 – 50 0C, this signal conditioner has an average deviation value of 0.38 0C (1.31%). In the wind tunnel speed variation testing with a range of 30 – 65 m/s, the RTD signal conditioner had an average deviation of 0.41 K (0.14%). The Repeatability Test procedure was carried out at a wind speed of 65 m/s with an angle of attack for the test model from -90 to 200 and data were collected 10 times at each angle. The average deviation of temperature against variations in the angle of attack of the test model in this procedure is 0.25 K (0.08%) and the average deviation of wind speed against variations in the angle of attack of the test model is 0.03 m/s (0.04%).

Aerodynamic shape optimization based on discrete adjoint and RBF

This paper presents a new framework for Aerodynamic Shape Optimization (ASO) implemented inside the open-source software SU2. A parametrized surface is iteratively morphed to improve a desired aerodynamic coefficient. At each loop, the computational grid must be updated. The radial basis function (RBF) mesh deformation technique is introduced to extend the capability to explore the design space. RBF is implemented with some state-of-the-art data reduction systems to lower the computational cost. The Discrete Adjoint is adopted to compute the sensitivity in combination with Automatic Differentiation to calculate the required Jacobians. RBF is differentiated as well, resulting in a method-dependent surface sensitivity. The gradient-based algorithm “Sequential Least Squares Programming” drives the research of the minimum. The study demonstrates that the presented combination is more robust than an ASO, including linear elasticity analogy (ELA) as mesh deformation method. It can handle complex geometries and apply larger displacements, making possible the optimization of a wing-winglet configuration and a rotating wind turbine. Results are presented in two and three-dimensions for compressible and incompressible flows, showing a stronger reduction of the drag without affecting the lift.

TBDRS: Threshold Based Data Reduction System for Data Transmission and Computation Reduction in WSNs

Wireless sensor networks, consisting of sensor nodes, monitoring the real-world phenomena generate a huge amount of data. However, the transmission of these measured values consumes most of the battery power of energy constrained sensor nodes. In this paper, threshold based data reduction system (TBDRS) is proposed in order to reduce the transmissions from the sensor node by exploiting the correlation between the measured values. Unlike other systems, TBDRS uses a control mechanism for threshold based switching on the basis of estimation error. This switching allows the system to achieve better trade-off between convergence speed and misadjustment, thereby improving the lifetime of the wireless sensor network by reducing the number of transmissions and computations. Due to the settling time, misadjustment trade-off capability, TBDRS can also be used in disaster management applications where the sensor data variations are more. The performance analysis of the system is evaluated in terms of mean square error. Moreover, the performance of TBDRS is evaluated for different parameters including length, step size and scaling factor. The simulation results validate that the proposed system achieves 70.56% and 83.01% better performance than the state-of-the-art system for an accuracy of 0.1 in terms of data reduction and number of computations, respectively.

Anomaly Detection Techniques in the Gaia Space Mission Data

In this paper we deal with classification of anomalous data detected by the data reduction system of the Gaia space mission, in operation since 2013. Given the size and complexity of intermediate data and plots for diagnostics, beyond practical possibility of full human evaluation, the need for automated signal processing tools is becoming more and more relevant. Our classification task consists in discriminating among “normal” data and data affected by anomalies, which at present are grouped into four different classes. We investigate the use of some clever pre-processing approaches that allow the application of a tailored technique based on the Hough transform, and of some machine learning tools, evidencing that the task can be exactly solved in the former case. In the latter case, random forests and support vector machine provide less than satisfactory performance, while convolutional neural networks achieve very good classification accuracy, up to 91.22%. Statistics show satisfactory results also in terms of precision and recall of each class.

Autonomous on-board data processing and instrument calibration software for the Polarimetric and Helioseismic Imager on-board the Solar Orbiter mission

A frequent problem arising for deep space missions is the discrepancy between the amount of data desired to be transmitted to the ground and the available telemetry bandwidth. A part of these data consists of scientific observations, being complemented by calibration data to help remove instrumental effects. We present our solution for this discrepancy, implemented for the Polarimetric and Helioseismic Imager on-board the Solar Orbiter mission, the first solar spectropolarimeter in deep space. We implemented an on-board data reduction system that processes calibration data, applies them to the raw science observables, and derives science-ready physical parameters. This process reduces the raw data for a single measurement from 24 images to five, thus reducing the amount of downlinked data, and in addition, renders the transmission of the calibration data unnecessary. Both these on-board actions are completed autonomously.

End to end simulators: a flexible and scalable cloud-based architecture

Simulations of frames from existing and upcoming high-resolution spectrographs, targeted for high accuracy radial velocity measurements, are computationally demanding (both in time and space). We present in this paper an innovative approach based on both parallelization and distribution of the workload. By using NVIDIA CUDA custom-made kernels and state-of-the-art cloud-computing architectures in a Platform as a Service (PaaS) approach, we implemented a modular and scalable end-to-end simulator that is able to render synthetic frames with an accuracy of the order of few cm/sec, while keeping the computational time low. We applied our approach to two spectrographs. For VLT-ESPRESSO we give a sound comparison between the actual data and the simulations showing the obtained spectral formats and the recovered instrumental profile. We also simulate data for the upcoming HIRES at the ELT and investigate the overall performance in terms of computational time and scalability against the size of the problem. In addition we demonstrate the interface with data-reduction systems and we preliminary show that the data can be reduced successfully by existing methods.

PENERAPAN POLA PERKULIAHAN MUHADATSAH MELALUI METODE DEBAT AKTIF PADA PRODI PENDIDIKAN BAHASA ARAB FAKULTAS TARBIYAH DAN KEGURUAN UIN AR-RANIRY BANDA ACEH

The study is entitled The Application of Arabic Conversation Lecture Patterns in the Department of Arabic Language Education, UIN Ar-Raniry Banda Aceh Through Active Debate Method. It is aimed at understanding the level of effectiveness of the method, knowing students‘ ability in Arabic conversation class towards student-centered learning, and finding the obstacles encountered in the transformation of lecture patterns in Arabic Conversation Class. This study used quantities quasi-experimental design with control group as well as a pre-test and post-test mechanisms combined with statistical analysis to look for the effects of certain treatments under controlled conditions. There are two variables in this study, namely the independent variable in the form of the use of the active debate method and the dependent variable in the form of Arabic conversation‘ student. The population of this study students’ representation from the incoming 2018-2019 batch totaling 205 students. The sampling technique applied was random sample sampling with the number of samples in this study were 53 students from units 02 and 07. Data collection techniques employed were observation, experiment, interview, and document study. Data analysis in this study was carried out repeatedly with data reduction systems, data presentation, and verification or conclusion drawing. The calculation results show the level of student ability is 83.13%, this shows that the active debate method is very effective in lecturing Muhadatsah. Findings also showed that the active debate usage in Arabic conversation classroom only causing averagely 9, 52 percentage of obstacles namely: understanding the problem, understanding the intention, and controlling emotion.

Numerical neutron attenuation correction for partially-illuminated powder samples

Chemical phase quantification from neutron diffraction measurements relies on accurate Bragg peak intensities at all diffraction angles. Amongst others these intensities are influenced by the total distance that the neutron beam has traversed through the sample in reaching the contributing volume segment and the distance from the contributing volume segment to the outer edge of the sample in the direction of the neutron detector. Since the total path length is dependent on the diffraction angle, gauge volume position inside the sample, as well as the sample dimensions and shape, the measured diffraction pattern should be corrected to account for this non-constant attenuation effect. Results show that in highly attenuation materials this can influence refined parameters during chemical phase quantification. A module was designed and integrated into the data reduction system ScanManipulator used at the neutron diffraction facility at the SAFARI-1 research reactor. The correction technique can further be used to accurately determine diffraction patterns obtained from position-resolved neutron diffraction experiments.

METODOLOGI PENAFSIRAN SAID NURSI DALAM KITAB ISYARAT AL-I’JAZ FI MAZANN AL-IJAZ

Subject matter in this research is how the methodology of interpretation of Said Nursi in Scripture Isyarat al-I’jaz fi Mazann al-Ijaz The purpose of this research is to 1) to know the method of interpretation of Said Nursi in Scripture Isyarat al-I’jaz fi Mazann al-Ijaz, 2) to know the approach to and interpretation of Said Nursi in Isyarat al-I’jaz fi Mazann al-Ijaz, 3) to know the techniques of interpretation of Said Nursi in Scripture Isyarat al-I’jaz fi Mazann al-Ijaz, 4) to know the advantages and limitations of the interpretation of Said Nursi in Scripture Isyarat al-I’jaz fi Mazann al-Ijaz. This type of research is the research library research. Research approach in this research is the approach of science of tafseer. As for the data sources used are primary and secondary sources. The next method of data collection was done by affirming the theme data is searchable, affirmed the source data, do data coding or classification to facilitate the researchers in this study. And techniques of processing and data analysis is performed using data reduction system, data and cereal drawdown conclusion. The results showed that: 1) method of interpretation used Said Nursi in Scripture Isyarat al-I’jaz fi Mazann al-Ijaz is a method of tahlili or analysis, 2) approach is Said Nursi use in Scripture Isyarat al-I’jaz fi Mazann al-Ijaz is the theological approach. And the pattern is the pattern of Isyari, 3) Said Nursi interpretation techniques apply in the book Isyarat al-I’jaz fi Mazann al-Ijaz textual interpretation and technique is contextual, 4) the advantages of book Isyarat al-I’jaz fi Mazann al-Ijaz are: a) the sentence that concisely, b) use three stages in interpreting the Qur'an, verse by verse previous relationships, relationship verse in the form of phrases, the texts in each relationship, c) reveal the secrets and wisdom which contained in every verse of the Qur'an, d) forms of questioning in its interpretation, e) proposes nazm al-Qur'an, f) independently thinking israiliyyat, g) combines several disciplines in interpreting the Qur'an. As for the limitations that are owned are: a) interpreted the surah al-Fatihah and surah al-Baqarah, b) the language used is very elusive, c) understanding book of Isyarat al-I’jaz fi Mazann al-Ijaz limited to people who had the insight a vast, d) does not mention the asbab al-nuzul ayah, e) are not listed the sources reference. The implications of research in this research study is expected to contribute to the academic community in reviewing the methodology of interpretation of which has a significant role in helping understand the Systematics of the scholars in the interpret the verses of the Qur'an.

Neonatal Behavioral Assessment Scale (NBAS): Confirmatory factor analysis of the six behavioral clusters

The Neonatal Behavioral Assessment Scale (NBAS) is a widely used in the neurobehavioral assessment of neonates in clinical practice and research. Lester's data reduction system for the NBAS items is the most often used in research, but the few factor analytic studies carried out with it leave gaps in its validation. The current study aimed to test and compare (a) the factorial structure of the Lester's data reduction system for the NBAS and (b) an alternative data reduction system, slightly modified from Lester's system. The NBAS was administered to 196 healthy Portuguese full-term infants (51% male) in the first 72 h of life (M = 43.63 h). Construct validity of the data reduction systems was tested through confirmatory factor analysis (CFA). Lester's original system was compared to three alternative models, two of which included a revision of the scoring rules for three items and the exclusion of five items. The CFA generally supported the six-factor structure. However, fit indices for Lester's original model were only fair. An alternative, revised model with a second-order factor – Self-Organizing System – demonstrated a better fit. The results provide evidence to support a modified form of Lester's six behavioral clusters as a data reduction model for the NBAS items.

A 950 nW Analog-Based Data Reduction Chip for Wearable EEG Systems in Epilepsy

Long-term electroencephalogram (EEG) monitoring is an important tool used for the diagnosis of epilepsy. Truly Wearable EEG can be considered as the future of ambulatory EEG units, which are the current standard for long-term EEG monitoring. Replacing these short lifetime, bulky units with long-lasting miniature and wearable devices which can be easily worn by patients will result in more EEG data being acquired for longer monitoring periods. This paper presents an analog-based data reduction integrated circuit that would reduce the amount of power required to transmit EEG data by identifying the sections of data that are interesting for diagnostic purposes while discarding the background activity. Using the data reduction system as part of a miniature wireless, EEG monitoring unit would yield significant reductions in power consumption since the transmitter will only be switched ON based on the data reduction system output. A system prototype chip has been fabricated in a 0.35 $\mu \text{m}$ CMOS process. The system consumes 760 nA from a 1.25 V supply and is able to achieve a sensitivity of 87%, while transmitting 45% of the overall EEG data.

Pengembangan dan Integrasi Piranti Lunak Pendukung Sistem Akuisisi dan Reduksi Data Terowongan Angin Kecepatan Rendah Indonesia

Data acquisition and reduction system plays important roles in a wind tunnel test and determine the validity of aerodynamic characteristics information of the test object in Indonesian Low Speed Tunnel. Although it has been modernized recently, the main software components of the system are still requiring supporting counterparts to optimize the efficiency and the effectivity of the test execution. Several supporting softwares have been engineered so far and further developments are still in progress as attempts to fulfill those needs. Coordinating both main and supporting softwares in a well manner should be considered to realize fully integrated system which functions from the pre-test to the post-test phases as well as to anticipate various possible needs in the future.
 Index Terms—data acquisition and reduction system, software engineering, wind tunnel test

Key factors affecting the competence of quantity surveyors

Purpose The purpose of this paper is to examine the factors affecting quantity surveyors’ competence with a view to reducing them to key components. Design/methodology/approach The research adopts a data reduction system using the factor analysis statistical technique. A structured questionnaire was administered among major stakeholders in the Nigerian construction industry. The respondents were asked to give ratings on a 5-point Likert scale on factors affecting the competence of quantity surveyors. Based on the identified 11 factor variables, factor analysis was used to explore and detect the underlying relationship among the identified variables. Important measures such as Bartlett’s test of sphericity, Kaiser-Meyer-Olkin measure of sampling accuracy and measure of sampling adequacy were used to test the appropriateness of the factor extraction. Findings The data reduction results in three key factor components: organization structure and team development, industrial exposure and route of educational training. Practical implications The findings provide a considerable insight into the issue of factors affecting quantity surveyors’ competence and could have considerable implications on the training of quantity surveyors in Nigeria. Originality/value The paper provides information on major factors influencing the competence of quantity surveyors and the resulting implications on the training, development and practice of quantity surveying in Nigeria.

Data acquisition and analysis software for gamma coincidence spectrometry.

Coincidence counting in neutron activation analysis has well-known advantages, most importantly improvement of detection limits. One obstacle to the wider use of this technique is the complexity of the data acquisition and reduction systems that it requires. The usual approaches to multi-detector data acquisition incur significant dead-time, involve redundant work in repeatedly developing limited tools and risk potential errors in low-level code. The paper describes progress made in developing a software framework to address these shortcomings.

DEEP-South: Automated Observation Scheduling, Data Reduction and Analysis Software Subsystem

AbstractWe started ‘DEep Ecliptic Patrol of the Southern sky’ (DEEP-South, DS) (Moon et al. 2015) in late 2012, and conducted test runs with the first Korea Microlensing Telescope Network (KMTNet) (Park et al. 2012), a 1.6 m telescope with 18k x 18k CCD stationed at CTIO in early 2015. While the primary objective of DEEP-South is the physical characterization of small Solar System bodies, it is also expected to discover a large number of such bodies, many of them previously unknown. An automated observation scheduling, data reduction and analysis software subsystem called ‘DEEP-South Scheduling and Data reduction System’ (DS SDS) is thus being designed and implemented to enable observation planning, data reduction and analysis with minimal human intervention.

The ONSEN Data Reduction System for the Belle II Pixel Detector

We present an FPGA-based online data reduction system for the pixel detector of the future Belle II experiment. The occupancy of the pixel detector is estimated at 3 %. This corresponds to a data output rate of more than 20 GB/s after zero suppression, dominated by background. The Online Selection Nodes (ONSEN) system aims to reduce the background data by a factor of 30. It consists of 33 MicroTCA cards, each equipped with a Xilinx Virtex-5 FPGA and 4 GiB DDR2 RAM. These cards are hosted by 9 AdvancedTCA carrier boards. The ONSEN system buffers the entire output data from the pixel detector for up to 5 seconds. During this time, the Belle II high-level trigger PC farm performs an online event reconstruction, using data from the other Belle II subdetectors. It extrapolates reconstructed tracks to the layers of the pixel detector and defines regions of interest around the intercepts. Based on this information, the ONSEN system discards all pixels not inside a region of interest before sending the remaining hits to the event builder system. During a beam test with one layer of the pixel detector and four layers of the surrounding silicon strip detector, including a scaled-down version of the high-level trigger and data acquisition system, the pixel data reduction using regions of interest was exercised. We investigated the data produced in more than 20 million events and verified that the ONSEN system behaved correctly, forwarding all pixels inside regions of interest and discarding the rest.

Demonstrator of the Belle II Online Tracking and Pixel Data Reduction on the High Level Trigger System

The future Belle II experiment will employ a computer-farm based data reduction system for the readout of its innermost detector, a DEPFET-technology based silicon detector with pixel readout. A large fraction of the background hits can be rejected by defining a set of Regions Of Interest (ROI) on the pixel detector sensors and then recording just the data from the pixels inside the ROI. The ROIs are defined on an event by event basis by extrapolating back onto the PXD the charged tracks detected in the outer trackers (a 4 layer double-sided silicon strip detector surrounded by a wire chamber). The tracks are reconstructed in real time on the High Level Trigger (HLT). The pixel detector is then read out based on the ROI information. A demonstrator of this architecture was under beam test earlier this year in DESY (Hamburg, Germany). The demonstrator was operated in an electron beam whose momentum was in the 2-6 GeV/c range with a typical trigger rate of a few kHz in a magnetic field of strength up to 1 T. The demonstrator consists of one pixel sensor and 4 silicon strip sensors arranged in a 5 layers configuration mimicking the Belle II vertex detector. The detector readout was a scaled down version of the full Belle II DAQ + HLT chain. The demonstrator was used to detect the particles, reconstruct in real time the trajectories, identify the ROIs on the PXD plane and record the PXD data within. We describe the requirements and the architecture of the final system together with the results obtained with the demonstrator.