File Processing Research Articles

CodeLabeller: A Web-Based Code Annotation Tool for Java Design Patterns and Summaries

While constructing supervised learning models, we require labeled examples to build a corpus and train a machine learning model. However, most studies have built the labeled dataset manually, which, on many occasions, is a daunting task. To mitigate this problem, we have built an online tool called CodeLabeller. CodeLabeller is a web-based tool that aims to provide an efficient approach to handling the process of labeling source code files for supervised learning methods at scale by improving the data collection process throughout. CodeLabeller is tested by constructing a corpus of over a thousand source files obtained from a large collection of open source Java projects and labeling each Java source file with their respective design patterns and summaries. Twenty-five experts in the field of software engineering participated in a usability evaluation of the tool using the standard User Experience Questionnaire online survey. The survey results demonstrate that the tool achieves the Good standard on hedonic and pragmatic quality standards, is easy to use and meets the needs of annotating the corpus for supervised classifiers. Apart from assisting researchers in crowdsourcing a labeled dataset, the tool has practical applicability in software engineering education and assists in building expert ratings for software artefacts.

Статистические оценки параметров центров действия атмосферы в зимнем и летнем сезонах по данным реанализа за период 1992–2021 годов

The subject of the present study is climatological atmospheric centers of action (permanent and seasonal) of the Northern and Southern hemispheres for the central months of the winter and summer seasons. Data on 1000 hPa geopotential height from the NCEP/DOE AMIP-II reanalysis of atmospheric parameters for 1992-2021 are used as initial information. Software-implemented processing of long-term reanalysis data files made it possible to map of the distribution of synoptic centers of action at regular grid points (with a step of 2.5 in latitude and longitude). Statistical estimates of the parameters of atmospheric centers of action (location and intensity), including concentration ellipse characteristics, are presented. An analysis of the change in the characteristics as compared to the base climate period of 1961–1990 (according to the NCEP/NCAR reanalysis data) is given. The dynamics of the characteristics of the centers of action in the form of moving 10-year averages for 2000–2021 is demonstrated. Keywords: atmospheric center of action, reanalysis, geopotential height, concentration ellipse, moving average, trend

Penegakan Hukum Oleh Polri Terhadap Pelaku Tindak Pidana Judi Online (Studi Pada Kepolisian Daerah Sumatera Utara)

Law enforcement is carried out by law enforcers. The implementation of the law in society, apart from depending on the legal awareness of the community, is also very much determined by law enforcement officials. Law enforcement by the Indonesian National Police against perpetrators of online gambling crimes at the North Sumatra Regional Police is carried out in accordance with the provisions of Law No. 19 of 2016 on amendments to Law No. 11 of 2008 concerning Information and Electronic Transactions. Law enforcement against perpetrators of online gambling crimes in the Police. The increasing mode of online gambling crimes is not accompanied by an increase in the quality and quantity of Polri personnel. Lack of mastery of information technology by investigators in revealing perpetrators of online gambling crimes. Lack of identity of perpetrators and lack of witnesses. Lack of evidence in the filing process. Lack of cooperation between the Police and providers and the public to obtain information related to online gambling crimes. The lack of cooperation between the Police and the Public Prosecutor in the process of investigating online gambling crimes

ExpressAnalyst: A unified platform for RNA-sequencing analysis in non-model species

The increasing application of RNA sequencing to study non-model species demands easy-to-use and efficient bioinformatics tools to help researchers quickly uncover biological and functional insights. We developed ExpressAnalyst (www.expressanalyst.ca), a web-based platform for processing, analyzing, and interpreting RNA-sequencing data from any eukaryotic species. ExpressAnalyst contains a series of modules that cover from processing and annotation of FASTQ files to statistical and functional analysis of count tables or gene lists. All modules are integrated with EcoOmicsDB, an ortholog database that enables comprehensive analysis for species without a reference transcriptome. By coupling ultra-fast read mapping algorithms with high-resolution ortholog databases through a user-friendly web interface, ExpressAnalyst allows researchers to obtain global expression profiles and gene-level insights from raw RNA-sequencing reads within 24 h. Here, we present ExpressAnalyst and demonstrate its utility with a case study of RNA-sequencing data from multiple non-model salamander species, including two that do not have a reference transcriptome.

СARDIAC ARRHYTHMIAS ANALYSIS BASED ON THE PHASE PORTRAIT OF ECG SIGNAL

The article illustrates the development of virtual system in LabVIEW software environment for processing and analysis of electrocardiographic signals. In the system, the issues of processing ECG signal with classical methods and in phase space have been considered, the comparison of these methods have been carried out, characteristic changes of the shapes of ECG phase portraits corresponding to the change of diagnostic signs haveb been analyzed, and additional diagnostic signs determined on the the base of phase portrait in order to increase the reliability of ECG diagnosis have been interpreted. As a result of the analysis of the sequence of RR intervals using the developed program, a histogram, a scatterogram, a fast Fourier transform, an autoregressive spectrum, a short-term Fourier transform and the corresponding informative parameters characterizing heart rate variability were obtained: the average length and standard deviation of RR intervals, the mean value and standard deviation heart rate, spectral parameters, etc. The results obtained during the processing and analysis of ECG files taken from the MIT BIH databases using the HRV analysis program and the determination of informative parameters implemented in the LabVIEW environment confirm the adequacy of the developed program. Keywords: ECG signal, phase space, phase portrait, RR intervals, LabVIEW software, heart rate, QRS complexes.

AWARENESS OF DIGITAL LIBRARIES IN SIVAGANGAI TOWN, SIVAGANGAI DISTRICT, TAMIL NADU: A STUDY

A Digital library, also called an online library, an internet library, a digital repository, a library without walls, or a digital collection is an online database of digital objects that can include text, still images, audio, video, digital documents, or other digital media formats or a library accessible through the internet. Objects can consist of digitized content like print or photographs, as well as originally produced digital content like word processor files or social media posts. Research and practice in digital Libraries (DL) has exploded worldwide in the 1990s. Substantial research findings have become available, libraries are actively involved in Digital Libraries projects and conference, journals and online news lists proliferate. In general, researchers view digital libraries as content collected on behalf of user communities, while practicing librarians view digital libraries as institutions or services. Future trends point toward the need for extensive research in digital libraries and for the transformation of libraries as institutions. This study is to analyze the awareness on Digital Libraries among the users in Sivagangai Town, Sivagangai District, Tamil Nadu

Investigating learning processes through analysis of navigation behavior using log files

The empirical study investigates what log files and process mining can contribute to promoting successful learning. We want to show how monitoring and evaluation of learning processes can be implemented in the educational life by analyzing log files and navigation behavior. Thus, we questioned to what extent log file analyses and process mining can predict learning outcomes. This work aims to provide support for learners and instructors regarding efficient learning with computer-based learning environments (CBLEs). We evaluated log file and questionnaire data from students (N = 58) who used a CBLE for two weeks. Results show a significant learning increase after studying with the CBLE with a very high effect size (p < .001, g = 1.71). A cluster analysis revealed two groups with significantly different learning outcomes accompanied by different navigation patterns. The time spent on learning-relevant pages and the interactivity with a CBLE are meaningful indicators for Recall and Transfer performance. Our results show that navigation behaviors indicate both beneficial and detrimental learning processes. Moreover, we could demonstrate that navigation behaviors impact the learning outcome. We present an easy-to-use approach for learners as well as instructors to promote successful learning by tracking the duration spent in a CBLE and the interactivity.

Explainable multi-task convolutional neural network framework for electronic petition tag recommendation

Electronic petition (e-petition) is an electronic government (e-government) service that allows citizens to file petitions to governments via the internet. The complexity of the e-petition filing process and the unexplainable e-government tools would reduce the perceived ease of use and trust of users, which causes citizens to make errors when tagging their e-petition. These errors may lead to failure and delay in resolving the e-petition, which further restrains citizen engagement and electronic participation (e-participation) adoption on e-petition platforms (EPP). The purpose of this study is to develop an explainable tag recommender system to assist citizens in tagging their e-petitions. Specifically, we design an explainable multi-task learning framework for e-petition tag recommendation based on convolutional neural networks and layer-wise relevance propagation. We also conduct both quantitative and qualitative experiments to demonstrate the recommendation effectiveness as well as interpretability of our model. This is among the first attempt to design an e-petition tag recommender system and an explainable e-government recommender system. The practical implications of our research are two-fold. For citizens, our proposed model recommends more accurate tags with human-understandable explanations, which could assist citizens’ tagging decisions and increase the possibility for an e-petition to be resolved. For governments, the e-petition service quality of governments would be enhanced, which further promotes e-participation adoption, citizen engagement, and e-government success on EPPs.

Achieving Sub-Parts-per-Million Mass Measurement Accuracy on an Orbitrap Mass Spectrometry Imaging Platform without Automatic Gain Control

The collection of profile data is standard practice within the field of mass spectrometry (MS). However, profile data collection often results in large data files that require extensive processing times, especially in mass spectrometry imaging (MSI) studies where thousands of high-resolution scans are recorded. Natively collecting centroid MS data is an alternative that effectively reduces both the resulting file size and the data processing time. Herein, high-resolution accurate mass (HRAM) Orbitrap MSI data on mouse liver tissue sections without automatic gain control (AGC) were natively collected in both profile and centroid modes and compared based on the file size and processing time. Additionally, centroid data were evaluated against the profile data with regard to the spectra integrity, mass measurement accuracy (MMA), and the number of lipid annotations to ensure that centroid data did not compromise the data quality. For both native and postacquisition centroided data, the variation in mass measurement accuracy decreased relative to the profile data collection. Furthermore, centroid data collection increased the number of METASPACE database annotations indicating higher sensitivity and greater accuracy for lipid annotation compared to native profile data collection. Profile MSI data was shown to have a higher likelihood of false positive identifications due to an increased number of data points on either side of the peaks, whereas the same trend was not observed in data collected in native centroid data collection. This publication explores and explains the importance in properly centroiding MSI data, either natively or by adequate centroiding methods, to obtain the most accurate information and come to the best conclusions. These data support that natively collecting centroid data significantly improves MMA to sub-ppm levels without AGC and reduces false positive annotations.

Espadon, an R package for automation, exploitation and processing of DICOM files in medical physics and clinical research

IntroductionOne of the main issues in the field of clinical research is to enhance clinical databases with information from imaging (CT, MR, PET-scan), contouring (RTstruct), or produced by TPS such as dose distribution (RTdose) or treatment plans (RTplan). To perform these analyses automatically, we propose the new open-source package “espadon”, developed in R environment. This package also opens up numerous perspectives for TPS-independant calculation, automation and processing of DICOM data. ResultsThe espadon package converts DICOM objects into espadon objects. Several tools have been developed to manipulate these objects and extract the desired information. In addition to decode DICOM files and pseudonomize them, the great advantage of espadon is that it presents the links between patient data (images, structures, treatment plans) in a didactic way, respecting the dates of the examinations. It can visualize volumes or structures in 2D or 3D, resample volumes, segment them, and change geometric frames of reference. It integrates dose-volume histogram functions on a selection, with Monte Carlo calculations of random shifts of contours. It offers the automatic calculation of several usual radiotherapy indices, as well as the calculation of Gamma and Chi indices. ConclusionsEspadon is a toolkit designed to be easily used by radiotherapists, medical physicists or students. Espadon's functions are implemented in an R script, and allow the automatic extraction or calculation of data from DICOM files, which can be used for statistical modelling or machine-learning in the R environment. This package is available on the Comprehensive R Archive Network (CRAN) repository.

Putting It in Writing

In the medical device industry, the practice of creating a "Letter to File," "Note to File," or "Memo to File" is employed to document modifications to a device in the USA for regulatory and compliance purposes. Although the U.S. Food and Drug Administration (FDA) have provided guidance on this topic over the years, there has not been a thorough exploration of this concept. Medical device manufacturers frequently make changes to their FDA-cleared products, but determining whether to handle the change internally using a Letter to File or notify the FDA can be unclear. This article provides a comprehensive overview of what a Letter to File is, the purpose of writing one, and the appropriate situations in which a company might use it. Additionally, it also discusses the contents of a typical Letter to File, including the necessary elements and the best practices for writing it effectively and consequences of making the wrong decision. By providing guidance on the Letter to File process, this article aims to assist professionals in the medical device industry in maintaining precise records that can support their organizations in any regulatory situation.

Визначення еталонних напрямків на сертифікованому поліґоні з використанням GNSS вимірювань

The relevance of PPP technology has greatly increased over the past 10 years. While the centimeter level of accuracy has already been practically ensured in most spheres of economic activity, first of all, in geodesy, the millimeter level for scientific tasks related to the study of the influence of geophysical factors on the environment is still the subject of research. The purpose of this work is to identify the real accuracy of the modification of the PPP-AR method using the example of data from four permanent GNSS stations: SULP (Lviv), FRAN (Ivano-Frankivsk), RAHI (Rakhiv), TERN (Ternopil), included in the European the EPN network (EUREF Permanent GNSS Network). Method. To fulfill the given task, we used data from four permanent GNSS stations. 3 weeks of observations were processed: one in July (2217 GPS week), one in August (2222 GPS week) and one in September (2226 GPS week). Processing of the observation files was carried out in the PRIDE PPP-AR software environment, which was pre-installed on the server with the Ubuntu operating system. The coordinates of each station were calculated with the same input parameters, namely, taking into account the second-order ionospheric correction and the function of displaying inclined zenith delays of signals from satellites in the direction of the VMF3 zenith. We compared the obtained sets of coordinates with the control coordinates of these stations. For the time periods we chose, the coordinates calculated by the relative method based on the formation of phase differences in the combined EPN processing center were taken as control. The results. The main results of our research were the difference of coordinates (comparison of the received coordinates with control ones). For each station, the obtained differences are unidirectional in nature and vary little between stations. The average value of the coordinate differences was from 0.6 to 7.2 mm and practically does not depend on the processing time interval. The root mean square error (RMS) of the coordinate differences is at the level of 1.5 – 3 mm and also changes little over time. It was found that the accuracy of determining the coordinates based on the processing of GNSS measurement data at permanent stations SULP, TERN, FRAN, RAHI using the PPP-AR method is quite high, but a systematic difference of several millimeters is noticeable, which may be caused by insufficient consideration of some factors of geophysical origin . Scientific novelty and practical significance. It is shown that the PPP-AR method at the current stage of development of GNSS technologies achieves the accuracy of the coordinate determination method based on phase differences and can be applied not only in geodesy tasks, but also in geodynamic studies, provided the results of daily GNSS observations are used. A promising direction for further research is the identification of unaccounted sources of systematic errors.

Management of Inpatient Medical Records at Dr. Tajuddin Chalid Hospital Makassar

Hospitals are health care institutions that organize comprehensive individual health services that provide inpatient, outpatient, and emergency services. Therefore, hospitals are expected to be able to carry out good medical recording activities. Since pre-independence Indonesia has carried out medical recording activities, it's just that it has not been implemented properly, in terms of structuring and processing or following the correct information system. One of the supports for improving the quality of the hospital is in its Medical Record activities. Medical records are related to recording, processing data, and reporting information needed for hospital activities. Medical records as patient health records are useful for providing information from various data on activities carried out to patients while patients are undergoing treatment at the hospital. This study aims to determine how the processing of inpatient medical record files at Ujung Pandang Dr. Tajuddin Chalik Hospital. The research conducted used qualitative research methods with a descriptive approach, namely research that describes and describes the inpatient medical record management system at Dr. Tajuddin Chalik General Hospital. The results of this study are the process of processing medical record files consisting of the process of Completeness (Assembling), Coding (Coding), and Storage (Filling). Conclusion Based on the results of research on the Inpatient Medical Record Management System at Dr Tajuddin Chalid Hospital Makassar that for the input component, namely the medical record personnel of Dr Tajuddin Chalid Hospital Makassar still lacks officers so that it is no longer in accordance with the workload. For facilities and infrastructure, there is a shortage of storage shelves and expansion is needed for medical record storage rooms.

Algorithm for Extraction of Keyframes of Images in Video Retrieval Systems

As a part of this work, there was a study of image processing algorithms used in video search systems.With the development of search engines and an increase in the types of queries possible for searching, the need for indexing an increasing amount of diverse information is growing. New data in the form of images and videos require new processing techniques to extract key content descriptions. In video search engines, according to this description, users can find the video files most relevant to the search query. The search query, in turn, can be of various types: text, search by image, search by video file to find a similar one, etc. Therefore, it is necessary to accurately describe the objects in the video in order to assign appropriate labels to the video file in the search engine database.In this article, we focused on the algorithm for extracting key frames of faces from a video sequence, since one of the important objects in the video are people themselves. This algorithm allows you to perform the initial processing of the file and save the identified frames with faces in order to later process this data with the help of the face recognition algorithm and assign the appropriate labels. An alternative application for this algorithm is the current processing of video files to form datasets of faces for the development and training of new computer vision models. The main criteria for such an algorithm were: the accuracy of face detection, the ability to distinguish keyframes of all people from each other, comprehensive evaluation of candidate frames and sorting by the relevance of the entire set for each face.After an analysis of existing solutions for specific stages of the algorithm, the article proposes a sequence of steps for the algorithm for extracting key frames of faces from a video file. An important step is to assess the quality of all candidates and sort them by quality. For this, the work defines various metrics for assessing the quality of the frame, which affect the overall assessment and, accordingly, the sorting order. The article also describes the basic version of the interface for using the proposed algorithm.

SMEs filing for bankruptcy in Spain: The best of luck!

The aim of this work is to analyze the factors that help companies avoid liquidation following the spirit of the Spanish insolvency law. This work focuses on the phase starting when companies file for bankruptcy and ending with the completion of the common phase. We apply the agency theory to explain how insolvency administrators and court characteristics influence the outcome of the bankruptcy process (liquidation or reorganization). We analyze unique accounting data from 2,627 companies that filed for bankruptcy during the period 2008–2014. The findings reveal the significant roles played by the liquidation trustee, Big 4 administrators, and higher remunerations, along with the type of court in charge. Processes are more likely to result in reorganization if they are handled by specialized courts, managed by the Big 4, and if the insolvency administrator has longer experience in bankruptcy filing and receives a higher remuneration. These findings have important implications for all the agents involved. It is necessary to rationalize the filing process, foment better training for insolvency administrators, provide courts with more funds, and create more specialized courts. The principal contribution of this article is to examine the role played by insolvency administrators and the courts, and their influence on the outcome of the insolvency process. JEL CLASSIFICATION C35; D21; D22; G33; G38

LabVIEW programming for the KSTAR XICS towards real-time ion temperature measurement

The X-ray Imaging Crystal Spectrometer (XICS) for Korea Superconducting Tokamak Advanced Research (KSTAR) provides the ion temperature and toroidal rotation velocity. These parameters are calculated through the Doppler broadening and its shift from the He-like argon spectra. A Matlab-based data analysis program for XICS has been used in KSTAR since 2009. This analysis program utilizes a least-square fit to provide a spatially resolved X-ray image so that it takes a long time for the image file processing procedures including the image correction. A new LabVIEW-based program is recently developed in order to reduce the data processing time with focusing only in the plasma core region where the image correction is not critical. This program integrates the detector control, transferring of the collected image to the analysis server, and image processing for the spectral analysis. It is also shown that a possible solution to acquire the measured image directly from the detector allows quasi-real-time measurements of the ion temperature and toroidal rotation velocity by using the LabVIEW-based program.

PyRERT: Python Research Environment for Radiation Therapy

The Python research environment for radiation therapy (PyRERT) is a set of business software for hospital physicists to conduct radiation therapy research. Choose the open source Enthought Tool Suite（ETS） as the core external dependency library of PyRERT. PyRERT is divided into base layer, content layer and interaction layer, and each layer is composed of different functional modules. PyRERT V1.0 provide a good development environment for scientific research programming in DICOM RT file processing, batch processing of water tank scan data, digital phantom creation, 3D medical image volume visualization, virtual radiotherapy equipment driver, and film scan image analysis. PyRERT enables the results of the research group to be iteratively inherited in the form of software. It's reusable basic classes and functional modules greatly improve the efficiency of scientific research task programming.

Single patch super-resolution of histopathology whole slide images: a comparative study.

The latest generation of scanners can digitize histopathology glass slides for computerized image analysis. These images contain valuable information for diagnostic and prognostic purposes. Consequently, the availability of high digital magnifications like and is commonly expected in scanning the slides. Thus, the image acquisition typically generates gigapixel high-resolution images, times as large as . Naturally, the storage and processing of such huge files may be subject to severe computational bottlenecks. As a result, the need for techniques that can operate on lower magnification levels but produce results on par with outcomes for high magnification levels is becoming urgent. Over the past decade, the digital solution of enhancing images resolution has been addressed by the concept of super resolution (SR). In addition, deep learning has offered state-of-the-art results for increasing the image resolution after acquisition. In this study, multiple deep learning networks designed for image SR are trained and assessed for the histopathology domain. We report quantitative and qualitative comparisons of the results using publicly available cancer images to shed light on the benefits and challenges of deep learning for extrapolating image resolution in histopathology. Three pathologists evaluated the results to assess the quality and diagnostic value of generated SR images. Pixel-level information, including structures and textures in histopathology images, are learnable by deep networks; hence improving the resolution quantity of scanned slides is possible by training appropriate networks. Different SR networks may perform best for various cancer sites and subtypes.

Digital Video Compression Using DCT-Based Iterated Function System (IFS)

Large video files processing involves a huge volume of data. The codec, storage systems and network needs resource utilization, so it becomes important to minimize the used memory space and time to distribute these videos over the Internet using compression techniques. Fractal image and video compression falls under the category of lossy compression. It gives best results when used for natural images.&#x0D; This paper presents an efficient method to compress an AVI (Audio Video Interleaved) file with fractal video compression(FVC). The video first is separated into a sequence of frames that are a color bitmap images, then images are transformed from RGB color space to Luminance/Chrominance components (YIQ) color space; each of these components is compressed alone with Enhanced Partition Iterated Function System (EPIFS), then fractal codes are saved.&#x0D; The classical IFS suffers from a very long encoding time that needed to find the best matching for each range block when compared with the domain image blocks. In this work, the (FVC) is enhanced by enhancing the IFS of the fractal image compression using a classification scheme based on the Discrete Cosine Transform (DCT). Experimentation is performed by considering different block sizes and jump steps to reduce number of the tested domain blocks. Results shows a significant reduction in the encoding time with good quality and high compression ratio for different video files.

Theta Activity Dynamics during Embedded Response Plan Processing in Tourette Syndrome

Gilles de la Tourette syndrome (GTS) is a neuropsychiatric disorder. Because motor signs are the defining feature of GTS, addressing the neurophysiology of motor processes is central to understanding GTS. The integration of voluntary motor processes is subject to so-called "binding problems", i.e., how different aspects of an action are integrated. This was conceptualized in the theory of event coding, in which 'action files' accomplish the integration of motor features. We examined the functional neuroanatomical architecture of EEG theta band activity related to action file processing in GTS patients and healthy controls. Whereas, in keeping with previous data, behavioral performance during action file processing did not differ between GTS and controls, underlying patterns of neural activity were profoundly different. Superior parietal regions (BA7) were predominantly engaged in healthy controls, but superior frontal regions (BA9, BA10) in GTS indicated that the processing of different motor feature codes was central for action file processing in healthy controls, whereas episodic processing was more relevant in GTS. The data suggests a cascade of cognitive branching in fronto-polar areas followed by episodic processing in superior frontal regions in GTS. Patients with GTS accomplish the integration of motor plans via qualitatively different neurophysiological processes.