Inspection Of Data Research Articles

Education Intervention on 'Hearing Impairment - Its Assessment and Management' among Medical Practitioners in Sikkim, India.

Health care providers must be aware of the choices in aural rehabilitation methods and assessment procedures available presently to those with hearing impairment in order to facilitate early identification and intervention and ensure quality of care to those hearing impaired individuals. The referrals from the medical fraternities for the audiological services are not uniform across India. Part of reason may be that awareness about the roles of and responsibilities of audiologist's is poor among medical practitioners. In some regions of India medical practitioners may be only grossly be aware of audiologists per se. They may not know enough to refer all individuals with hearing or balance disorders for the required audiological services. To evaluate changes in pre survey and post survey after education intervention specifically planned for medical practitioners in the state of Sikkim, India. Education intervention included awareness about hearing impairment and its assessment and management by audiologists. A pre and post survey comparison research design with purposive convenient sampling technique was applied. Participants were medical practitioners working in geographical area of Sikkim at the time of the study. Inspection of demographic data of respondents showed that they were in their age range of 24 and 60 years and with work experience ranging 1-40 years. Participants were invited for an awareness talk which included, information about hearing loss, early identification and early intervention, tests and management of hearing loss in different age groups, need for hearing aids/cochlear implants, auditory training, and the role of an audiologist in the management of hearing loss and ways to prevent hearing loss. A pre and post awareness program responses were collected from all the participants using a customized questionnaire tool. Respondents exhibited, in the pre-survey questionnaire, lack of awareness in many aspects of audiology, including assessing hearing impairment, diagnosing hearing loss, and the role of an audiologist. There was an overall, statistically significant difference in the level of performance on the pre-awareness and post-awareness responses. Following an awareness campaign among the medical professionals in Sikkim, there was a considerable change in their level of awareness of hearing impairment, its assessment, and management by audiologists. The reach of the awareness campaign was significant as around 70% of subjects showed significant change in their knowledge and attitude towards hearing impairment, its management.

The STEM Wage Premium in the Main Brazilian Technology Clusters

This paper reports research results on Science Technology Engineering and Mathematics – STEM – wage premium in 10 main Brazilian technologic clusters: Manaus, Ilhéus-Itabuna, Belo Horizonte, Pouso Alegre, Curitiba, Porto Alegre, Florianópolis, Campinas, São Carlos and São Paulo. The study adjusts the Oaxaca decomposition method – which allows using the workers’ occupation as a categorical variable – to estimate the median of the STEM wage premium in each of the clusters. The control variables are age, educational level, and experience, which are proxy variables for human capital. Inspection of data reveals that the STEM workforce is more educated and has more stability in the job. The statistical analysis suggests that the median of the STEM wage premium obtained by workers in the ten clusters is higher than observed in development countries. This may indicate that Brazilian STEM labor force should will is still grow to meet demand.

Strategi Penanggulangan Pelanggaran Lalu Lintas Terhadap Remaja (Studi pada Satlantas Polresta Banda Aceh)

This study aims to determine the efforts and obstacles of the Banda Aceh Resort Police Traffic Unit in tackling Traffic Violations by Teenagers as Motorcyclists. This research uses qualitative methods. Data sources are obtained through methods of observation, interviews, and documentation. The data inspection technique uses the triangulation technique method. The results of the study are known that the efforts of the Banda Aceh Resort Police Traffic Unit in tackling traffic violations committed by teenagers as motorcyclists, preventive actions, namely collaborating with several schools in Banda Aceh City to educate students not to do dangerous things using their motorcycles, either by violating traffic rules or by modifying motorcycles that can interfere with the driving comfort of others. Repressive efforts are carried out with raids to regulate traffic violations, to provide education and a deterrent effect so that teenagers who are not old enough to ride motorcycles do not use motorcycles on the road. The obstacles of the Banda Aceh Resort Police Traffic Unit in tackling Traffic Violations by Teenagers as Motorcyclists are, Neglected by parents has led to an increase in the phenomenon of school students using motorcycles even though they are not yet 17 years old. Research advises it is hoped that parents can provide understanding to their teens not to use motorcycles on the road because of the risk of accidents and crossings by the police for violating traffic rules

Sample Size in Behavioral Research: A Systematic Review of JEAB and JABA from 2009 to 2018

The current research conducted a systematic review on sample size and the use of inferential statistics in basic and applied behavioral research by assessing all experimental studies from 2009 to 2018 in the Journal of the Experimental Analysis of Behavior (JEAB) and the Journal of Applied Behavior Analysis (JABA) which was 1,155 articles. The use or non-use of inferential statistics in behavioral research remains controversial as visual inspection has deep historical roots. JEAB had a median number of eight subjects and JABA had a median number of four subjects, which was statistically different using Mood’s median test. In addition, articles in JEAB were more likely to use inferential statistics compared to JABA. In general, inferential statistics were used in the presence of larger sample sizes, however, the use of animal subjects was associated with smaller sample sizes. Although patterns of the use of inferential statistics varied across journal, sample size, and species, this does not preclude the use of statistical methods by applied behavioral researchers, which should be used to support and confirm visual inspections of data. Keywords: sample size, inferential statistics, behavioral research, systematic review.

A Robust Deep Learning Ensemble-Driven Model for Defect and Non-Defect Recognition and Classification Using a Weighted Averaging Sequence-Based Meta-Learning Ensembler.

The need to overcome the challenges of visual inspections conducted by domain experts drives the recent surge in visual inspection research. Typical manual industrial data analysis and inspection for defects conducted by trained personnel are expensive, time-consuming, and characterized by mistakes. Thus, an efficient intelligent-driven model is needed to eliminate or minimize the challenges of defect identification and elimination in processes to the barest minimum. This paper presents a robust method for recognizing and classifying defects in industrial products using a deep-learning architectural ensemble approach integrated with a weighted sequence meta-learning unification framework. In the proposed method, a unique base model is constructed and fused together with other co-learning pretrained models using a sequence-driven meta-learning ensembler that aggregates the best features learned from the various contributing models for better and superior performance. During experimentation in the study, different publicly available industrial product datasets consisting of the defect and non-defect samples were used to train, validate, and test the introduced model, with remarkable results obtained that demonstrate the viability of the proposed method in tackling the challenges of the manual visual inspection approach.

Experimental Validation of Shifted Position-Diffuse Reflectance Imaging (SP-DRI) on Optical Phantoms.

Numerous diseases such as hemorrhage, sepsis or cardiogenic shock induce a heterogeneous perfusion of the capillaries. To detect such alterations in the human blood flow pattern, diagnostic devices must provide an appropriately high spatial resolution. Shifted position-diffuse reflectance imaging (SP-DRI) has the potential to do so; it is an all-optical diagnostic technique. So far, SP-DRI has mainly been developed using Monte Carlo simulations. The present study is therefore validating this algorithm experimentally on realistic optical phantoms with thread structures down to 10 μm in diameter; a SP-DRI sensor prototype was developed and realized by means of additive manufacturing. SP-DRI turned out to be functional within this experimental framework. The position of the structures within the optical phantoms become clearly visible using SP-DRI, and the structure thickness is reflected as modulation in the SP-DRI signal amplitude; this performed well for a shift along the x axis as well as along the y axis. Moreover, SP-DRI successfully masked the pronounced influence of the illumination cone on the data. The algorithm showed significantly superior to a mere raw data inspection. Within the scope of the study, the constructive design of the SP-DRI sensor prototype is discussed and potential for improvement is explored.

A Framework to Evaluate the Quality of Integrated Datasets

Evaluation is a bottleneck in data integration processes: it is performed by domain experts through manual onerous data inspections. This task is particularly heavy in real business scenarios, where the large amount of data makes checking all integrated tuples infeasible. Our idea is to address this issue by providing the experts with an unsupervised measure, based on word frequencies, which quantifies how much a dataset is representative of another dataset, giving an indication of how good is the integration process. The paper motivates and introduces the measure and provides extensive experimental evaluations, that show the effectiveness and the efficiency of the approach.

A TCP Acceleration Algorithm for Aerospace-Ground Service Networks

The transmission of satellite payload data is critical for services provided by aerospace ground networks. To ensure the correctness of data transmission, the TCP data transmission protocol has been used typically. However, the standard TCP congestion control algorithm is incompatible with networks with a long time delay and a large bandwidth, resulting in low throughput and resource waste. This article compares recent studies on TCP-based acceleration algorithms and proposes an acceleration algorithm based on the learning of historical characteristics, such as end-to-end delay and its variation characteristics, the arrival interval of feedback packets (ACK) at the receiving end and its variation characteristics, the degree of data packet reversal and its variation characteristics, delay and jitter caused by the security equipment's deep data inspection, and random packet loss caused by various factors. The proposed algorithm is evaluated and compared with the TCP congestion control algorithms under both laboratory and ground network conditions. Experimental results indicate that the proposed acceleration algorithm is efficient and can significantly increase throughput. Therefore, it has a promising application prospect in high-speed data transmission in aerospace-ground service networks.

Research on optimization of index system design and its inspection method: data quality diagnosis, index classification and stratification

PurposeThe purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.Design/methodology/approachUsing modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.FindingsBased on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.Originality/valueThe innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

Generalized multiple dependent state sampling plan for quality inspection in ocean dataset

The present article develops the generalized multiple dependent state sampling plan for testing the quality of the ocean data. The plan parameters for the inspection of the ocean data are selected through the optimization process. The operational procedure for the inspection of ocean data is given under the proposed sampling scheme. The efficiency of the proposed plan is compared with the existing plan used for the inspection of the quality of ocean data in terms of sample size. From the comparative study, it is concluded that the proposed plan is efficient than the existing plan in an inspection of the ocean data.

Anomaly Detecting Geometric Transformation Network with Outlier Exposure Defect Inspection of Real Industrial Data

Anomaly Detecting Geometric Transformation Network with Outlier Exposure Defect Inspection of Real Industrial Data

The impacts of performance-based assessment on reading comprehension achievement, academic motivation, foreign language anxiety, and students’ self-efficacy

The types of assessment tasks affect the learners’ psychological well-being and the process of learning. For years, educationalists were in search of finding and implementing accurate and convenient approaches to assess learners efficiently. Despite the significant role of performance-based assessment (PBA) in affecting second/foreign language (L2) learning processes, few empirical studies have tried to explore how PBA affects reading comprehension achievement (RCA), academic motivation (AM), foreign language anxiety (FLA), and students’ self-efficacy (SS-E). To fill this lacuna of research, the current study intended to gauge the impact of PBA on the improvement of RCA, AM, FLA, and SS-E in English as a foreign language (EFL) context. In so doing, a sample of 88 intermediate EFL learners were randomly divided into experimental group (EG) and CG (control group). During this research (16 sessions), the learners in the CG (N = 43) received the tradition assessment. In contrast, the learners in the EG (N = 45) were exposed to some modification based on the underpinning theories of PBA. Data inspection applying the one-way multivariate analysis of variance (i.e., the one-way MANOVA) indicated that the learners in the EG outperformed their counterparts in the CG. The results highlighted the significant contributions of PBA in fostering RCA, AM, FLA, and S-E beliefs. The implications of this study may redound to the benefits of language learners, teachers, curriculum designers, and policy makers in providing opportunities for further practice of PBA.

THE COMPARATIVE STUDY ANALYSIS LOGICAL FILES RECOVERY AND LOW LEVEL FILES RECOVERY USING DIGITAL FORENSIC METHODS

The development of application and network technology is currently so rapid. This technology is widely used as a solution to overcome data inspection problems in the field of Digital Forensics. The importance of Digital Forensics as evidence, especially on computers and mobile devices, is increasing, along with the rapid use of these mobile devices in daily communication. Data and files on computers and smartphones can be deleted intentionally or unintentionally. To recover the data, it is necessary to have Files Recovery. Furthermore, Logical Files Recovery can be made through password encryption, obtained through hack/attack password applications such as Password or even hacked with the "RecoveryMyFile" application. In addition, a search with a file that has a password description can be done. One of the file recovery applications that can be used is the Agent ransack search application, which is more powerful and convenient than Windows Search, which is more complicated if you need to search faster, indexing needs to be done, and restarts. By using Files Recovery analysis, the development of file or data deletion crimes can be overcome with increasingly rapid and advanced information technology, in this case through applications that can be used for file recovery and to restore deleted files.

Analytical Performance of Next-Generation Sequencing and RT-PCR on Formalin-Fixed Paraffin-Embedded Tumor Tissues for PIK3CA Testing in HR+/HER2- Breast Cancer.

Somatic mutations in PIK3CA are present in ~40% breast cancers (BC); their detection in hormone receptor (HR)+/HER2- tumors allows for selecting patients with advanced disease eligible for PIK3CA targeting with alpelisib. The choice of what type of PIK3CA testing approach to adopt and which tissue sample to analyze is a new task in breast pathology. In this methodological study, we sought to assess the performance of next-generation sequencing (NGS) and RT-PCR for PIK3CA testing on archival formalin-fixed paraffin-embedded (FFPE) primary tumors and corresponding metastases. Sixteen HR+/HER2- BC with known PIK3CA-mutated status (ex. 7, 9, and 20) on metastatic samples by means of amplicon-based targeted NGS were selected, and n = 13 of these samples were re-tested with a commercially available CE-IVD RT-PCR assay. All available primary tumors (n = 8) were tested with both methods. NGS detected mutations in all samples, while RT-PCR in n = 2 sample-pairs and overall, in n = 5/8 (62.5%) primary tumors and 7/13 (53.8%) metastases (κ = 0.09; 95% CI, -0.69-0.87). Slight agreement (κ = 0; 95% CI, -0.59-0.59) was observed between NGS and RT-PCR, with the former being generally more sensitive in cases with low DNA quality and quantity. Post hoc visual inspection of the RT-PCR data increased the concordance to 76.9%. Targeted NGS offers reliable and robust PIK3CA testing on both tumor and metastasis FFPE samples; the accuracy of RT-PCR depends on the DNA quantity and quality. In HR+/HER2- BC, both the selection of the PIK3CA testing strategy of FFPE tissues and which sample to analyze should consider several technical parameters and should be tailored for each case.

JSD: A Dataset for Structure Analysis in Jazz Music

Given a music recording, music structure analysis aims at identifying important structural elements and segmenting the recording according to these elements. In jazz music, a performance is often structured by repeating harmonic schemata (known as choruses), which lay the foundation for improvisation by soloists. Within the fields of music information retrieval (MIR) and computational musicology, the Weimar Jazz Database (WJD) has turned out to be an extremely valuable resource for jazz research. Containing high-quality solo transcriptions for 456 solo sections, the dataset opened up new avenues for the understanding of creative processes in jazz improvisation using computational methods. In this paper, we complement this dataset by introducing the Jazz Structure Dataset (JSD), which provides annotations on structure and instrumentation of entire recordings. The JSD comprises 340 recordings with more than 3000 annotated segments, along with a segment-wise encoding of the solo and accompanying instruments. These annotations provide the basis for training, testing, and evaluating models for various important MIR tasks, including structure analysis, solo detection, or instrument recognition. As an example application, we consider the task of structure boundary detection. Based on a traditional novelty-based as well as a more recent data-driven approach using deep learning, we indicate the potential of the JSD while critically reflecting on some evaluation aspects of structure analysis. In this context, we also demonstrate how the JSD annotations and analysis results can be made accessible in a user-friendly way via web-based interfaces for data inspection and visualization. All annotations, experimental results, and code for reproducibility are made publicly available for research purposes.

Memo Writing Procedures in Grounded Theory Research Methodology

This paper develops memo writing techniques within the framework of grounded theory methodology of qualitative research in social sciences. In grounded theory, memoing is one of the most important processes to develop and enrich theory. Memo is the written record of the researcher’s thinking. It is an analytical strategy that facilitates the researcher to achieve clear concept and truth from the data. It is considered as the tool of all kinds of notes taken by the researchers in grounded theory during their research. But yet there is a limited use of memo writing in other qualitative researches. Memoing increases investigation, inspection and continuity of data during the research analysis. In this study an attempt has been taken to discuss the aspects of memoing along with its benefits.

MarsQuakeNet: A More Complete Marsquake Catalog Obtained by Deep Learning Techniques

AbstractNASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport (InSight) seismometer has been recording Martian seismicity since early 2019, and to date, over 1,300 marsquakes have been cataloged by the Marsquake Service (MQS). Due to typically low signal‐to‐noise ratios (SNR) of marsquakes, their detection and analysis remain challenging: while event amplitudes are relatively low, the background noise has large diurnal and seasonal variations and contains various signals originating from the interactions of the local atmosphere with the lander and seismometer system. Since noise can resemble marsquakes in a number of ways, the use of conventional detection methods for catalog curation is limited. Instead, MQS finds events through manual data inspection. Here, we present MarsQuakeNet (MQNet), a deep convolutional neural network for the detection of marsquakes and the removal of noise contamination. Based on three‐component seismic data, MQNet predicts segmentation masks that identify and separate event and noise energy in time‐frequency domain. As the number of cataloged MQS events is small, we combine synthetic event waveforms with recorded noise to generate a training data set. We apply MQNet to the entire continuous 20 samples‐per‐second waveform data set available to date (>1,000 Martian days), for automatic event detection and for retrieving denoised amplitudes. The algorithm reproduces all high quality, as well as majority of low quality events in the manual, carefully curated MQS catalog. Furthermore, MQNet detects ∼60% additional events that were previously unknown with mostly low SNR, that are verified in manual review. Our analysis on the event rate confirms seasonal trends and shows a substantial increase in the second Martian year.

Forbidden hugs in pandemic times

We present an observational study of the luminous red nova (LRN) AT 2021biy in the nearby galaxy NGC 4631. The field of the object was routinely imaged during the pre-eruptive stage by synoptic surveys, but the transient was detected only at a few epochs from ∼231 days before maximum brightness. The LRN outburst was monitored with unprecedented cadence both photometrically and spectroscopically. AT 2021biy shows a short-duration blue peak, with a bolometric luminosity of ∼1.6 × 1041 erg s−1, followed by the longest plateau among LRNe to date, with a duration of 210 days. A late-time hump in the light curve was also observed, possibly produced by a shell-shell collision. AT 2021biy exhibits the typical spectral evolution of LRNe. Early-time spectra are characterised by a blue continuum and prominent H emission lines. Then, the continuum becomes redder, resembling that of a K-type star with a forest of metal absorption lines during the plateau phase. Finally, late-time spectra show a very red continuum (TBB ≈ 2050 K) with molecular features (e.g., TiO) resembling those of M-type stars. Spectropolarimetric analysis indicates that AT 2021biy has local dust properties similar to those of V838 Mon in the Milky Way Galaxy. Inspection of archival Hubble Space Telescope data taken on 2003 August 3 reveals a ∼20 M⊙ progenitor candidate with log (L/L⊙) = 5.0 dex and Teff = 5900 K at solar metallicity. The above luminosity and colour match those of a luminous yellow supergiant. Most likely, this source is a close binary, with a 17–24 M⊙ primary component.

Technical feasibility of using auditory phase-targeted stimulation after pediatric severe traumatic brain injury in an intensive care setting

BackgroundSupplementary treatment options after pediatric severe traumatic brain injury (TBI) are needed to improve neurodevelopmental outcome. Evidence suggests enhancement of brain delta waves via auditory phase-targeted stimulation might support neuronal reorganization, however, this method has never been applied in analgosedated patients on the pediatric intensive care unit (PICU). Therefore, we conducted a feasibility study to investigate this approach: In a first recording phase, we examined feasibility of recording over time and in a second stimulation phase, we applied stimulation to address tolerability and efficacy.MethodsPediatric patients (> 12 months of age) with severe TBI were included between May 2019 and August 2021. An electroencephalography (EEG) device capable of automatic delta wave detection and sound delivery through headphones was used to record brain activity and for stimulation (MHSL-SleepBand version 2). Stimulation tolerability was evaluated based on report of nurses, visual inspection of EEG data and clinical signals (heart rate, intracranial pressure), and whether escalation of therapy to reduce intracranial pressure was needed. Stimulation efficacy was investigated by comparing EEG power spectra of active stimulation versus muted stimulation (unpaired t-tests).ResultsIn total, 4 out of 32 TBI patients admitted to the PICU (12.5%) between 4 and 15 years of age were enrolled in the study. All patients were enrolled in the recording phase and the last one also to the stimulation phase. Recordings started within 5 days after insult and lasted for 1–4 days. Overall, 23–88 h of EEG data per patient were collected. In patient 4, stimulation was enabled for 50 min: No signs of patient stress reactions were observed. Power spectrums between active and muted stimulation were not statistically different (all P > .05).ConclusionResults suggests good feasibility of continuously applying devices needed for auditory stimulation over multiple days in pediatric patients with TBI on PICU. Very preliminary evidence suggests good tolerability of auditory stimuli, but efficacy of auditory stimuli to enhance delta waves remains unclear and requires further investigation. However, only low numbers of severe TBI patients could be enrolled in the study and, thus, future studies should consider an international multicentre approach.

Effectiveness of the Perceive, Recall, Plan and Perform intervention for persons with brain injury in community-based rehabilitation: protocol for a single-case experimental design with multiple baselines

IntroductionThere is a need for standardised interventions in community-based rehabilitation to improve everyday performance for older adults with cognitive challenges due to acquired brain injury (ABI). The Perceive, Recall, Plan...