Data Reduction Process Research Articles

New measurement of the 242Pu(n,γ) cross section at n_TOF-EAR1 for MOX fuels: Preliminary results in the RRR

The spent fuel of current nuclear reactors contains fissile plutonium isotopes that can be combined with 238U to make mixed oxide (MOX) fuel. In this way the Pu from spent fuel is used in a new reactor cycle, contributing to the long-term sustainability of nuclear energy. The use of MOX fuels in thermal and fast reactors requires accurate capture and fission cross sections. For the particular case of 242Pu, the previous neutron capture cross section measurements were made in the 70's, providing an uncertainty of about 35% in the keV region. In this context, the Nuclear Energy Agency recommends in its “High Priority Request List” and its report WPEC-26 that the capture cross section of 242Pu should be measured with an accuracy of at least 7–12% in the neutron energy range between 500 eV and 500 keV. This work presents a brief description of the measurement performed at n_TOF-EAR1, the data reduction process and the first ToF capture measurement on this isotope in the last 40 years, providing preliminary individual resonance parameters beyond the current energy limits in the evaluations, as well as a preliminary set of average resonance parameters.

Measurements of the capture cross sections of natural silver in the resonance range with the time of flight technique

Neutron capture cross section measurements have been performed at the time-of-flight facility GELINA of the EC-JRC-Geel. Prompt gamma rays, originating from a natural silver sample, were detected by a pair of C6 D6 liquid scintillation detectors. The total energy detection principle in combination with the pulse height weighting technique has been used. In this contribution the experimental details together with the data reduction process are described. In addition, first results of calculations with REFIT are presented to verify the quality of recommended cross section data in the resolved resonance region.

마이크로 터보 엔진 배기 플룸에서의 적외선 신호 측정 및 검증

적외선 신호에 대한 측정 시스템은 저피탐 기술 개발 및 전자기 방사의 분광 분석에 기여한다. SR (Spectroradiometer)의 적용은 배기 플룸에서 방사되는 열원만으로 복사량이 측정 가능하다. 마이크로 터보 엔진을 이용한 측정 시스템의 구축은 항공기 플룸을 모사하는데 목적을 두었다. 엔진은 성능 시험을 위해 테이블에 계측 장비와 함께 설치되었다. 배기 플룸 축과 수직을 이루도록 분광복사기를 위치하여 적외선 신호를 측정하였다. 원 데이터에 대한 보정을 위하여 흑체를 사용하여 참조 데이터를 획득하였고 플룸 신호와 비교하기 위해서 배경에 대한 신호도 측정하였다. 보정된 spectral radiance는 데이터 처리를 통해 계산되었고 밴드별로 분석되었다. 본 측정 시스템으로 종합적인 분석 연구가 가능하게 되었다. Development of an accurate infrared signature (IR) measurement system is expected to contribute in the development of low observable technology and the spectroscopic analysis of electromagnetic radiation. Application of a spectroradiometer (SR) allows for the measurement of detailed infrared signature from the exhaust plume due to its own heat source. Establishment of a measurement system using a micro-turbo engine is intended to simulate the modelling of the aircraft plume. The engine was installed on a test stand to measure the engine performance. The IR signature was measured by placing the SR perpendicular to the axis line of the exhaust plume. Reference data from the blackbody were also measured to calibrate the raw data, and the infrared signature of the background was also measured for comparison with that of the plume. The calibrated spectral radiance was obtained through the data reduction process and the results were analyzed in specific bands. The experiments revealed that the measurement system established here showed sufficient performance for further comprehensive analysis.

Monitoring What Matters: A Systematic Process for Selecting Training-Load Measures.

Numerous derivative measures can be calculated from the simple session rating of perceived exertion (sRPE), a tool for monitoring training loads (eg, acute:chronic workload and cumulative loads). The challenge from a practitioner's perspective is to decide which measures to calculate and monitor in athletes for injury-prevention purposes. The aim of the current study was to outline a systematic process of data reduction and variable selection for such training-load measures. Training loads were collected from 173 professional rugby union players during the 2013-14 English Premiership season, using the sRPE method, with injuries reported via an established surveillance system. Ten derivative measures of sRPE training load were identified from existing literature and subjected to principal-component analysis. A representative measure from each component was selected by identifying the variable that explained the largest amount of variance in injury risk from univariate generalized linear mixed-effects models. Three principal components were extracted, explaining 57%, 24%, and 9% of the variance. The training-load measures that were highly loaded on component 1 represented measures of the cumulative load placed on players, component 2 was associated with measures of changes in load, and component 3 represented a measure of acute load. Four-week cumulative load, acute:chronic workload, and daily training load were selected as the representative measures for each component. The process outlined in the current study enables practitioners to monitor the most parsimonious set of variables while still retaining the variation and distinct aspects of "load" in the data.

PEMBELAJARAN IPS PADA KELOMPOK BELAJAR (KEJAR) PAKET B DI PUSAT KEGIATAN BELAJAR MASYARAKAT (PKBM) BARITO KOTA BANJARMASIN

Nonformal education in Paket A, B, and C is one of the civil right for the citizens to be easily accessible and this is held by PKBM. The research has to objective to know the characteristics of learning community and tutor, the role of PKBM Barito in providing facility and equipment for learning, social learning process of Kejar Paket B celebrated by PKBM Barito. The research uses the qualitative method. The source of data is chosen purposively, and the data collection uses observation, interview, and documentation. The research instruments are interview guide, observation sheet, and documentation. Data analysis by data reduction process, data display, and verification. The research finding say that (1) the characteristics of learning community are in variation whether in age, marital status, profession, education background, motivation, skill, the interestedness to subject, expectation after graduation, and problem in their lives. Whereas characteristics of tutor could be seen from the education level, professional competence, and pedagogic competence; (2) the role of PKBM does not work maximally whether in recruiting community learning, providing facility and equipment for learning celebration, and learning evaluation; however PKBM has the role in recruiting tutor and celebration fund; (3) the learning process of social science for Paket B has fulfilled minimal standar involving preparation, implementation, and evaluation but does not work maximally in learning for the mature learners.Key words: social science learning, Kejar Paket, PKBM role, learning community, tutor.

Penanaman Sikap Cinta Tanah Air dalam Pramuka di Dabin 5 UPTD Pendidikan Wirosari Brobogan

The purpose of this study was to describe the attitude of patriotism planting in extracurricular activities scouts on the General Terms and Conditions Skills Special Skills in Dabin 5 UPTD Wirosari Subdistrict Grobogan. Type ethnographic qualitative research design. The research subjects principals, teachers and students. Data collection techniques with interviews, observation, and documentation. Data analysis techniques to the analysis of the flow of the process of data collection, data reduction, display, and verification, conclusion. The validity of the data sources and data triangulation. The research result is habituation attitude of patriotism at the General Proficiency Requirements can memorize at least three daily prayers, prayers can carry, can maintain the cleanliness of the room school or place of worship, is able to help someone in the vicinity, following the flag ceremony with wisdom. Exemplary attitude of patriotism at the General Proficiency Requirements can use Indonesian well and correctly, not littering, can show true deference to the Red and White Flag, can be memorized to sing the national anthem Indonesia Raya. SKK is used to apply the attitude of patriotism is SKK singer, conductor SKK, SKK P3K, SKK Explorer / Searching for Traces, SKK Camping, SKK Greening.

A qualitative study of perceived needs and factors associated with the quality of care for common mental disorders in patients with chronic diseases: the perspective of primary care clinicians and patients.

BackgroundThe prevalence of comorbid anxiety and depressive disorders is high among patients with chronic diseases in primary care, and is associated with increased morbidity and mortality rates. The detection and treatment of common mental disorders in patients with chronic diseases can be challenging in the primary care setting. This study aims to explore the perceived needs, barriers and facilitators for the delivery of mental health care for patients with coexisting common mental disorders and chronic diseases in primary care from the clinician and patient perspectives.MethodsIn this qualitative descriptive study, we conducted semi-structured interviews with clinicians (family physician, nurse, psychologist, social worker; n = 18) and patients (n = 10) from three primary care clinics in Quebec, Canada. The themes explored included clinician factors (e.g., attitudes, perception of roles, collaboration, management of clinical priorities) and patient factors (e.g., needs, preferences, access to care, communication with health professionals) associated with the delivery of care. Qualitative data analysis was conducted based on an interactive cyclical process of data reduction, data display and conclusion drawing and verification.ResultsClinician interviews highlighted a number of needs, barriers and enablers in the provision of patient services, which related to inter-professional collaboration, access to psychotherapy, polypharmacy as well as communication and coordination of services within the primary care clinic and the local network. Two specific facilitators associated with optimal mental health care were the broadening of nurses’ functions in mental health care and the active integration of consulting psychiatrists. Patients corroborated the issues raised by the clinicians, particularly in the domains of whole-person care, service accessibility and care management.ConclusionsThe results of this project will contribute to the development of quality improvement interventions to increase the uptake of organizational and clinical evidence-based practices for patients with chronic diseases and concurrent common mental disorders, in priority areas including collaborative care, access to psychotherapy and linkages with specialized mental health care.Electronic supplementary materialThe online version of this article (doi:10.1186/s12875-016-0531-y) contains supplementary material, which is available to authorized users.

Big forensic data management in heterogeneous distributed systems: quick analysis of multimedia forensic data

SummaryThe growth in the data volume and number of evidential data from heterogeneous distributed systems in smart cities, such as cloud and fog computing systems and Internet‐of‐Things devices (e.g. IP‐based CCTVs), has led to increased collection, processing and analysis times, potentially resulting in vulnerable persons (e.g. victims of terrorism incidents) being at risk. A process of Digital Forensic Data Reduction of source multimedia and forensic images has provided a method to reduce the collection time and volume of data. In this paper, a methodology of Digital Forensic Quick Analysis is outlined, which describes a method to review Digital Forensic Data Reduction subsets to pinpoint relevant evidence and intelligence from heterogeneous distributed systems in a timely manner. Applying the proposed methodology to real‐world data from an Australian police agency highlighted the timeliness of the process, resulting in significant improvements in processing times in comparison with processing a full forensic image. The Quick Analysis methodology, combined with Digital Forensic Data Reduction, has potential to locate evidence and intelligence in a timely manner. Copyright © 2016 John Wiley & Sons, Ltd.

Voices of the "99 Percent": The Role of Online Narrative to Improve Health Care.

Communal blogs facilitate online narratives by providing opportunities for individuals to co-construct meaning and to engage in discussion about lived health experiences. To examine the role of health as a connective narrative among individuals organizing collectively in an online community. The "We are the 99 percent" Tumblr blog emerged as a spontaneous community platform of the Occupy Wall Street movement in the US. Researchers conducted a qualitative content analysis of a total of 2003 blog posts. Data analysis included a process of data reduction, display, and conclusion drawing and verification. Bloggers discussed medical crises and the role of injury and illness in maintaining financial solvency. The difficulty of obtaining health care and the lack of accessible quality care emerged as themes. In particular, unemployment and underemployment limited access to health insurance coverage. The bloggers expressed dissatisfaction with the health care system and the impact of financial status on health. These challenges were exacerbated for marginalized populations, such as women and veterans. Findings offer implications for the value of online narrative to improve health care initiatives and to provide insight to integrated health care systems, including health care practitioners, nonprofit organizations, hospitals, and policy makers. Results suggest opportunities to address the health care gaps of marginalized populations and to develop public health policy.

Use of Data Reduction Process to Bankruptcy Prediction

Predicting corporate bankruptcy has been an important challenging problem in research topic in accounting and finance. In bankruptcy prediction, researchers often confront a range of observations and variables which are often vast amount of financial ratios. By reducing variables and select relevant data from a given dataset, data reduction process can optimize bankruptcy prediction. This study addresses four well-known data reduction methods including t-test, correlation analysis, principal component analysis (PCA) and factor analysis (FA) and evaluated them in bankruptcy prediction in the Tehran Stock Exchange (TSE). To this end, considering 35 financial ratios, the results of data reduction methods were separately used to train Support Vector Machine (SVM) as the powerful prediction model. Regarding the empirical results, among the aforementioned methods, the t-test lead to the most prediction rate with 97.1% of predictability and PCA by 95.1% provides the next position.

THE VLT LEGA-C SPECTROSCOPIC SURVEY: THE PHYSICS OF GALAXIES AT A LOOKBACK TIME OF 7 Gyr

ABSTRACT The Large Early Galaxy Census (LEGA-C) is a Public Spectroscopic Survey of ∼3200 K-band selected galaxies at redshifts z = 0.6 − 1.0 with stellar masses M * > 10 10 M ⊙ , conducted with VIMOS on ESO’s Very Large Telescope. The survey is embedded in the COSMOS field (R.A. = 10h00; decl . = + 2 deg ). The 20 hr long integrations produce high-signal-to-noise ratio continuum spectra that reveal ages, metallicities and velocity dispersions of the stellar populations. LEGA-C’s unique combination of sample size and depth will enable us for the first time to map the stellar content at large lookback time, across galaxies of different types and star formation activity. Observations started in 2014 December and are planned to be completed by mid 2018, with early data releases of the spectra and value-added products. In this paper we present the science case, the observing strategy, an overview of the data reduction process and data products, and a first look at the relationship between galaxy structure and spectral properties, as it existed 7 Gyr ago.

VIDEO COPY DETECTION UTILIZING THE LOG-POLAR TRANSFORMATION

Video copy detection is the process of comparing and analyzing videos to extract a measure of their similarity in order to determine if they are copies, modified versions, or completely different videos. With video frame sizes increasing rapidly, it is important to allow for a data reduction process to take place in order to achieve fast video comparisons. Further, detecting video streaming and storage of legal and illegal video data necessitates the fast and efficient implementation of video copy detection algorithms. In this paper some commonly used algorithms for video copy detection are implemented with the Log-Polar transformation being used as a pre-processing step to reduce the frame size prior to signature calculation. Two global based algorithms were chosen to validate the use of Log-Polar as an acceptable data reduction stage. The results of this research demonstrate that the addition of this pre-processing step significantly reduces the computation time of the overall video copy detection process while not significantly affecting the detection accuracy of the algorithm used for the detection process.

Big forensic data reduction: digital forensic images and electronic evidence

An issue that continues to impact digital forensics is the increasing volume of data and the growing number of devices. One proposed method to deal with the problem of "big digital forensic data": the volume, variety, and velocity of digital forensic data, is to reduce the volume of data at either the collection stage or the processing stage. We have developed a novel approach which significantly improves on current practice, and in this paper we outline our data volume reduction process which focuses on imaging a selection of key files and data such as: registry, documents, spreadsheets, email, internet history, communications, logs, pictures, videos, and other relevant file types. When applied to test cases, a hundredfold reduction of original media volume was observed. When applied to real world cases of an Australian Law Enforcement Agency, the data volume further reduced to a small percentage of the original media volume, whilst retaining key evidential files and data. The reduction process was applied to a range of real world cases reviewed by experienced investigators and detectives and highlighted that evidential data was present in the data reduced forensic subset files. A data reduction approach is applicable in a range of areas, including: digital forensic triage, analysis, review, intelligence analysis, presentation, and archiving. In addition, the data reduction process outlined can be applied using common digital forensic hardware and software solutions available in appropriately equipped digital forensic labs without requiring additional purchase of software or hardware. The process can be applied to a wide variety of cases, such as terrorism and organised crime investigations, and the proposed data reduction process is intended to provide a capability to rapidly process data and gain an understanding of the information and/or locate key evidence or intelligence in a timely manner.

IO:I, a near-infrared camera for the Liverpool Telescope

IO:I is a new instrument that has recently been commissioned for the Liverpool Telescope, extending current imaging capabilities beyond the optical and into the near-infrared. Cost has been minimized by the use of a previously decommissioned instrument’s cryostat as the base for a prototype and retrofitting it with Teledyne’s 1.7-μm cutoff Hawaii-2RG HgCdTe detector, SIDECAR ASIC controller, and JADE2 interface card. The mechanical, electronic, and cryogenic aspects of the cryostat retrofitting process will be reviewed together with a description of the software/hardware setup. This is followed by a discussion of the results derived from characterization tests, including measurements of read noise, conversion gain, full well depth, and linearity. The paper closes with a brief overview of the autonomous data reduction process and the presentation of results from photometric testing conducted on on-sky, pipeline processed data.

A statistical study of magnetospheric ion composition along the geomagnetic field using the Cluster spacecraft for L values between 5.9 and 9.5

AbstractUsing ion density data obtained by the CODIF (ion Composition and Distribution Function analyser) instrument on board the Cluster spacecraft, for the interval spanning 2001–2005, an empirical model describing the average ion mass distribution along closed geomagnetic field lines is determined. The empirical model describes the region spanning 5.9≤L < 9.5, with dependences on L shell and magnetic local time included, and represents ions in the energy range of 0.025 to 40 keV/charge. The data reduction process involves the identification and rejection of CODIF data contaminated by penetrating energetic radiation belt particles, found to frequently occur for L < 5.9. Furthermore, a comparison of data with observations of the cold plasma population in the region provides evidence that the CODIF data set is representative of the full plasma population. The variations in average ion mass along the field lines were modeled using a power law form, which maximizes toward the magnetic equatorial plane, with observed power law index values ranging between approximately −2.0 and 0.0. The resulting model illustrates some key features of the average ion mass spatial distribution, such as an average ion mass enhancement at low L in the evening sector, indicating the transport of high‐latitude heavy ion outflows to the closed inner magnetosphere.

A novel data reduction technique for single slanted hot-wire measurements used to study incompressible compressor tip leakage flows

The single slanted hot-wire technique has been used extensively as a method for measuring three velocity components in turbomachinery applications. The cross-flow orientation of probes with respect to the mean flow in rotating machinery results in detrimental prong interference effects when using multi-wire probes. As a result, the single slanted hot-wire technique is often preferred. Typical data reduction techniques solve a set of nonlinear equations determined by curve fits to calibration data. A new method is proposed which utilizes a look-up table method applied to a simulated triple-wire sensor with application to turbomachinery environments having subsonic, incompressible flows. Specific discussion regarding corrections for temperature and density changes present in a multistage compressor application is included, and additional consideration is given to the experimental error which accompanies each data reduction process. Hot-wire data collected from a three-stage research compressor with two rotor tip clearances are used to compare the look-up table technique with the traditional nonlinear equation method. The look-up table approach yields velocity errors of less than 5 % for test conditions deviating by more than 20 °C from calibration conditions (on par with the nonlinear solver method), while requiring less than 10 % of the computational processing time.

Kostum Dalam Membangun Karakter Tokoh Pada Film Soekarno

This study discusses the procedures of costumes and characters in the Sukarnofilm. This qualitative descriptive research apply the Sukarno film as source of data. Thecollection of data by purposive sampling, with the method of observation, interviews,and literature. Data were analyzed through data reduction, data display, drawingconclusions and verification process. The results showed that the costumes portraythe characterization of the characters. Costume adjusted with basic clothing, headclothing, body clothing, legs underwear, and accessories are known for costume parts.Each character has a unique costume and a differentiator from other figures. Costumealso build characterization of actors according to the physiological dimension (neatness,cleanliness, beauty, beauty, valor, charm, charisma, and authority). Sociological dimensionsindicate socioeconomic class, role in the family / community, ideology, ancestry, levelof education, religion, ethnicity / race, and interaction between the actors. While thepsychological dimensions adapted to the atmosphere and scene. Color and layoutcostume describing feelings, honesty, sincerity, emotion, desire, desire, passion, inneraction, as well as the vision of each character in the film.Keywords: costume, characterization, actor, film, and Soekarno

Spirituality and Religiosity in Adolescents Living With Sickle Cell Disease.

This study purports to address paucity in the literature regarding how adolescents with sickle cell disease (SCD) describe and experience spirituality and religiosity (S/R). This was a qualitative descriptive study. Two semi-structured interviews were conducted with nine adolescents (Mage = 16.2 years). Data were analyzed using a template analysis style and a concurrent analysis process of data reduction. Three major themes encompassed the participants' descriptions of the relationships between S/R, health and illness in their lives including S/R as sources for coping, influence of S/R beliefs on health and illness, and sharing S/R with Health Care Providers (HCPs). S/R as coping mechanisms included six threads: interconnecting with God, interconnecting with others, interconnecting with creative arts, scriptural metanarratives, transcendent experiences, and acceptance and finding meaning. Expectations of health providers included two threads: Religiosity is private/personal and sharing spiritual and religious beliefs is risky. S/R are particularly salient for adolescents with SCD.

Discovery of Long Tail Keywords in Paid Search

The following work describes an elegant, efficient keyword clustering method to discover long tail keywords in paid search data. In keyword auctions, such words often go undiscovered as their cost in being bid to higher ranking positions is deemed too high to justify the potential of significantly added conversion revenue. By discovering clusters with low volume keywords and established, high-performing and high volume keywords, the quality of the low volume (long tail) keywords is inferred by association. After a brief introduction, the data used to train the clustering algorithm is described. Then, the data reduction process (the discovery of the most predictive features) is described. We then describe the method, followed by the results and interpretation.

How can Acoustic Emission Signals be Used in Condition Monitoring and Diagnosis of Diesel Engine Condition?

Acoustic emission (AE) technique has recently been extensively used in machine health monitoring and diagnosis of diesel engine. Although it offers many advantages for early detection of fault symptoms, it also comes with many challenging problems. Due to its operation in high frequency range (stress waves), from a few kHz to MHz, it poses a problem of massive data storage and transmission. Furthermore, the non-linearity of AE sensors is also another challenge as it does not provide any quantitative/comparative analysis if multiple sensors are used, such in multi-cylinder diesel engine. Hence, this short paper will present the work carried out in the author’s laboratory by introducing a simple and innovative data reduction process termed as Peak Hold down Sampling (PHDS) and a normalization approach for diagnosis of diesel engine.