Image Files Research Articles

Towards a clinically-based common coordinate framework for the human gut cell atlas: the gut models

BackgroundThe Human Cell Atlas resource will deliver single cell transcriptome data spatially organised in terms of gross anatomy, tissue location and with images of cellular histology. This will enable the application of bioinformatics analysis, machine learning and data mining revealing an atlas of cell types, sub-types, varying states and ultimately cellular changes related to disease conditions. To further develop the understanding of specific pathological and histopathological phenotypes with their spatial relationships and dependencies, a more sophisticated spatial descriptive framework is required to enable integration and analysis in spatial terms.MethodsWe describe a conceptual coordinate model for the Gut Cell Atlas (small and large intestines). Here, we focus on a Gut Linear Model (1-dimensional representation based on the centreline of the gut) that represents the location semantics as typically used by clinicians and pathologists when describing location in the gut. This knowledge representation is based on a set of standardised gut anatomy ontology terms describing regions in situ, such as ileum or transverse colon, and landmarks, such as ileo-caecal valve or hepatic flexure, together with relative or absolute distance measures. We show how locations in the 1D model can be mapped to and from points and regions in both a 2D model and 3D models, such as a patient's CT scan where the gut has been segmented.ResultsThe outputs of this work include 1D, 2D and 3D models of the human gut, delivered through publicly accessible Json and image files. We also illustrate the mappings between models using a demonstrator tool that allows the user to explore the anatomical space of the gut. All data and software is fully open-source and available online.ConclusionsSmall and large intestines have a natural “gut coordinate” system best represented as a 1D centreline through the gut tube, reflecting functional differences. Such a 1D centreline model with landmarks, visualised using viewer software allows interoperable translation to both a 2D anatomogram model and multiple 3D models of the intestines. This permits users to accurately locate samples for data comparison.

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.

Survey on electronic visual field data transfer practices among Japan Glaucoma Society board members

BackgroundVisual field (VF) testing in combination with a specialized VF analysis software is critical for characterizing and monitoring visual loss in glaucoma. Although performing glaucoma progression analysis requires original VF data rather than printouts or image files, extent of VF data transfer between referring and referred ophthalmologists is unclear. Here, we surveyed glaucoma specialists who belong to the Japan Glaucoma Society (JGS).MethodsAn internet survey of daily practice patterns regarding electronic VF data transfer at the time of glaucoma referrals (referring/referred) was sent to all 50 JGS board members. The survey consisted with 11 questionnaires, and the response rate was 100%.ResultsThe respondents included 33 university hospital ophthalmologists (66%) (Q1), and those scattered throughout Japan (Q2). All respondents used Humphrey Visual Filed Analyzer (HFA) (Q3) and at least one of a VF progression analysis software (Q4). Ten respondents (20%) actively transferred electronic VF data, while 40 (80%) did not (Q5). The major reasons for not actively transferring data electronically were that there was no support for data transfer by neighboring (n = 26, 65%) and/or own (25, 63%) institutes (Q6). All 40 inactive respondents responded that electronic data transfer is ideal (Q7). All 10 active respondents transferred data using USB flash memory (Q8). Of the 10 active respondents, seven (70%) reported that the percentage of referral letters accompanying electronic VF data in a format that allows for progression analysis from the beginning was less than 25% (Q9). When the referral letters did not accompany the electronic VF data, four (40%) reported that they further requested the data transfer in < 25% of cases (Q10). When the 10 active respondents were requested to transfer data, six (60%) had experienced rejection due to various reasons (Q11).ConclusionAn internet survey showed that 80% of the JGS board members were not actively transferring VF data mainly because of the absence of a system in place at institutions for sending and receiving data, although they feel that the electronic VF data transfer is ideal. The results provide basic data for future discussions on the promotion of the VF data transfer.

Loyal Consumers: Efforts to Improve and Maintain Consumer Databases Using Youtube Optimization Techniques

This study tries to test the ranking model on youtube search. Youtube brings up search results based on the number of visits and video recommendations available. The method used in this research begins by collecting 10 keywords that appear in a youtube search. Of the 10 results will be used as the image file name to be used. The 10 image files are then turned into a video. The link generated from the upload process is then registered with a free ping service on the internet. For testing, day parameters are used, namely 1 day, 2 days and 3 days. Within 3 days the video has appeared on the first page of a Google search with keywords that match the names of the image files.

Comprehensive study of deep learning based Telugu OCR: A survey

There will be no computer-editable text in the image file. The method of optical character recognition (OCR), which can read handwritten or printed text in images, turns that text into a file that can be edited on a computer. English has a well-developed OCR system. OCR is currently required for Indian languages in order to process application forms, categorise books in libraries, and preserve historical records that are mostly written in Indian languages. The Telugu language presents challenges for OCR since each character is made up of a single consonant, a single vowel, or a compound of vowels and consonants.

New functionality of BIOKEYS software: Displaying character pictures in identification dialogboxes

BIOKEYS is software built in DELPHI development environment with PASCAL as the base programming language. BIOKEYS allows creating and working with biological databases, creating and working with polyclave and dichotomous keys. This study has added the feature of displaying character image in the identification dialog. The purpose of displaying character images in the identification dialog is to make it easy for the user to select the correct specimen character. In the BIOKEYS software, displaying the character images in the identification dialog is implemented by creating an information file containing the character names and the names of the corresponding image files. By using the information in this file, every time the user clicks on a character, BIOKEYS opens its image file and displays it in the identification dialog. That helps the user to check if the characteristics he read in the sample are correct and helps the classification process to get more accurate results.

Combining Beaufort cipher and RSA-CRT algorithm in a hybrid scheme to secure images

RSA algorithm is one type of algorithms in public-key cryptographic systems where the private keys are kept secret and the public keys can be disseminated. Beaufort Cipher algorithm is a type of classical symmetric algorithm. Meanwhile, the RSA-CRT is one variant of RSA cryptosystem. The RSA-CRT is not efficient for encrypting large files such as image files, since it uses modular exponentiation, which is slow, and the resulting ciphertext would be very much larger than the message. To avoid this problem, a hybrid cryptosystem scheme using RSA-CRT and Beaufort algorithm is designed to encrypt images. Beaufort Cipher algorithm is used for encryption and decryption of digital images, while RSA-CRT algorithm for decryption and decryption of beaufort cipher keys. The results showed that the size of the image (*.BMP) files and the encrypted image files are the same.

Fusion Fuzzy Logic and Deep Learning for Depression Detection Using Facial Expressions

One of the critical issues in detecting depression is using facial expressions with image data classification. In This research paper, we proposed Fusion Fuzzy Logic((FFL) with deep learning for identifying depressed people based on their facial expressions. Our proposed model the based on an advanced fuzzy algorithm with deep learning for unordered fuzzy rule(FR) initiation to offer appropriate and suitable opinions based on depressed people's facial expressions(FE), to allow Depression Recognition(DR) from image files and recorded video files. The primary goal of this research work was to use the fusion method to turn these facial expressions (FE) into the detection of depressed states. To elevate the performance of the Fusion Fuzzy Logic((FFL) (fuzzy logic and CNN)), delivering them entreated them several times to imitate specific facial expressions. Our proposed FFL with the CNN model produces exact and dependable results with a 94.3% overall accuracy comparable to human recognition.

ОБ ИТОГАХ VI ВСЕРОССИЙСКОЙ НАУЧНО-ПРАКТИЧЕСКОЙ КОНФЕРЕНЦИИ "ИНФОРМАЦИОННАЯ БЕЗОПАСНОСТЬ: ВЧЕРА, СЕГОДНЯ, ЗАВТРА"

The article analyzes results of the All-Russian Scientific and Practical Conference held in Moscow at the Russian State University for the Humanities (RGGU), at which more than 20 reports from various scientific and educational organizations were heard. The reports dealt with general issues of information security, software and hardware methods of the information protection; prospects for the development of various areas of the information security were also considered. The topics of the plenary reports included: trends in the development of the information warfare in the context of global informatization, the risks of outsourcing and attracting contractors to the implementation of an information security system, the import-independence of the national ICT infrastructure: an ethical and engineering view, software and algorithmic support for assessing the destructiveness of telegram channels, modeling the evaluation of the effectiveness of the information security control system of open sociotechnical systems, issues of building a reliable enterprise information security systems, etc. The reports in three sections considered: features of ensuring the information security of critical information infrastructure facilities in the field of electric power, analysis of methods of hacking and destruction of a steganographic container in an image file, analysis of the consequences of a breach of personal data security from the standpoint of the intruder’s interests, testing models of analysis and forecasting of the information warfare in society in the simulation environment of Anylogic, etc.

Python programming code for stellar photometry in astrophysics teaching on a cloud computing service

Nowadays, there is various software used for both education and astronomy research. For photometry, licensed software and high-performance computer operating systems are required, which is a fund limitation for some schools in Thailand. Thus, in this article, we develop and present the Demonstration Photometry Scripts for Astrophysics Teaching (DPSAT version 1.0). The program is designed to work on cloud computing services via internet browsers to avoid hardware and operation requirement pain points. The DPSAT is programming on flexible, low-cost, on-trend language, Python, and Jupyter Notebook online editor. In advance, our new code supports the home-use image or video file format, i.e., jpg, png, or mp4. Thus, it will be more accessible for teachers and students who do not have standard astronomical instruments. The DPSAT measures the stellar light intensity from the time-series still-images or video files from a smartphone or other digital devices. The code can extract video files into sequenced still images, then transform the RGB color space images into greyscale. The light intensity signal of selected pixels is counted with a simple aperture method in time series. It shows the results, for example, the mean signal, standard variation, measured signal as light intensity versus time, and image of light sources. This will be fruitful for low-cost and easily accessible teaching of astrophysics subjects.

ARTRODESE LOMBAR ANTERIOR: PERFIL EPIDEMIOLÓGICO, RADIOLÓGICO

ABSTRACT Objective: Evaluate the epidemiological and radiographic data of patients submitted to the Anterior Lumbar Interbody Fusion (ALIF) technique and the possible complications related to this procedure. Methods: A longitudinal and retrospective study was carried out to analyze electronic medical records and image files of patients who underwent spinal surgery using the ALIF technique between February 2019 and January 2021. Epidemiological data such as age, gender, and level of surgery were analyzed. Radiographic evaluations of lumbar lordosis from L1 to S1 were performed using the COBB technique and the anterior and posterior height of the disc space. The presence of intraoperative and postoperative complications in the patients was analyzed. Results: Initially, 70 patients were analyzed. The most prevalent operated level was L5-S1. The length of stay of the patients varied between 36 and 72 hours. Intraoperative bleeding ranged from 20mL to 400mL. Three patients had significant venous lesions. Differences between anterior and posterior lordosis and height measurements were significant (p &lt; 0.001). Lordosis had a mean increase of 10.3°, anterior height had a mean increase of 7.9mm, and posterior height of 4.0mm. Six cases of intra and postoperative complications were observed. Conclusion: The patients showed improvement in the radiological parameters of the anterior and posterior height of the vertebral discs, with a significant increase in lumbar lordosis. Complication rates were 9.8%, and we had a short hospital stay. Level of Evidence II; Retrospective Longitudinal Study.

Implementation of Encrypt National ID Card in Sinovi Application Use Waterfall Methodology

In this era of increasingly rapid technology, the development of information systems is also growing rapidly, because information systems provide what users need. Information is a very valuable thing. When information or data falls into irresponsible hands, it will bring disaster to the owner, and there have been many cases of data leaks in the past that have harmed several parties. There are various ways to protect data or information. Therefore, data security techniques are needed, the message security process is very diverse, including using cryptography. Cryptography aims to scramble messages so that they are difficult to read by unauthorized parties. In this study, we will use the AES 256 encryption method with the waterfall research method to secure KTP images on the Sinovi application, Sinovi is a copyright registration application at the Telkom Institute of Technology Purwokerto. The results of this study are the AES method will convert data or information in the form of plain text into cipher-text then stored in a file to replace the image file so that in this way the image cannot be viewed directly because it must pass the decryption technique first and the research data will be presented. in a table of blackbox testing. It is hoped that a security system like this can protect data from unauthorized parties and further research is expected to have research that tests AES 256 with different methods. https://github.com/teguh02/T-Encryption

Whole Slide Images in Artificial Intelligence Applications in Digital Pathology: Challenges and Pitfalls.

The use of digitized data in pathology research is rapidly increasing. The whole slide image (WSI) is an indispensable part of the visual examination of slides in digital pathology and artificial intelligence applications; therefore, the acquisition of WSI with the highest quality is essential. Unlike the conventional routine of pathology, the digital conversion of tissue slides and the differences in its use pose difficulties for pathologists. We categorized these challenges into three groups: before, during, and after the WSI acquisition. The problems before WSI acquisition are usually related to the quality of the glass slide and reflect all existing problems in the analytical process in pathology laboratories. WSI acquisition problems are dependent on the device used to produce the final image file. They may be related to the parts of the device that create an optical image or the hardware and software that enable digitization. Post-WSI acquisition issues are related to the final image file itself, which is the final form of this data, or the software and hardware that will use this file. Because of the digital nature of the data, most of the difficulties are related to the capabilities of the hardware or software. Being aware of the challenges and pitfalls of using digital pathology and AI will make pathologists' integration to the new technologies easier in their daily practice or research.

Tools for Drawing Informative Idiograms.

Each species has a typical karyotype, which represents the phenotypic appearance of the somatic chromosomes including number, size, and morphology. An idiogram is a diagrammatic representation of the chromosomes showing their relative size, homologous groups, and different cytogenetic landmarks. Chromosomal analysis of cytological preparations is an essential component of many investigations, which involves the calculation of karyotypic parameters and the generation of idiograms. Although various tools are available for karyotype analysis, here we demonstrate karyotype analysis using our recently developed tool named KaryoMeasure. KaryoMeasure is a semi-automated free and user-friendly karyotype analysis software that facilitates data collection from different digital images of metaphase chromosome spreads and calculates a wide variety of chromosomal and karyotypic parameters along with the related standard errors. KaryoMeasure draws idiograms of both diploid and allopolyploid species into a vector-based SVG or PDF image file.

Performance evaluation of LSB steganography based on multiple image formats

In the proposed research work steganography technique has been designed and developed for carrier images having different formats. The algorithm is applicable for the image formats: PNG (Portable Network Graphics), TIFF (Tagged Image File Format), JPEG (Joint Photograph Expert Group), and BMP (Bitmap). A single algorithm for almost all types of image formats provides many advantages. Depending upon the size of the secret message, network bandwidth, and allowable distortion we can choose the format of the carrier. For embedding secret messages, the LSB substitution technique is applied in this paper. We utilized the concept of imperceptibility by calculating PSNR (Peak Signal to Noise Ratio), MSE (Mean Square Error), SSIM (Structure Similarity Index Metrics), Histogram, and Entropy. The proposed work is analyzed for robustness with favorable results. Two steganalysis tools: Stegexpose and Stegdetect are used to detect the hidden secret message. For analyzing the complexity of work capacity, concealing and retrieval times are calculated. Furthermore, the comparative outcome for the proposed work is very promising for different carrier image formats.

Compression Supports Spatial Deep Learning

In the last decades, the domain of spatial computing became more and more data driven, especially when using remote sensing-based images. Furthermore, the satellites provide huge amounts of images, so the number of available datasets is increasing. This leads to the need for large storage requirements and high computational costs when estimating the label scene classification problem using deep learning. This consumes and blocks important hardware recourses, energy, and time. In this article, the use of aggressive compression algorithms will be discussed to cut the wasted transmission and resources for selected land cover classification problems. To compare the different compression methods and the classification performance, the satellite image patches are compressed by two methods. The first method is the image quantization of the data to reduce the bit depth. Second is the lossy and lossless compression of images with the use of image file formats, such as JPEG and TIFF. The performance of the classification is evaluated with the use of convolutional neural networks (CNNs) like VGG16. The experiments indicated that not all remote sensing image classification problems improve their performance when taking the full available information into account. Moreover, compression can set the focus on specific image features, leading to fewer storage needs and a reduction in computing time with comparably small costs in terms of quality and accuracy. All in all, quantization and embedding into file formats do support CNNs to estimate the labels of images, by strengthening the features.

An algorithm for steganographic embedding of encrypted files in raster images

The aim of this paper is proposing a method for the application of algorithms for hiding an encrypted file inside of a digital image for cybersecurity purposes. The originality of the method is expressed in the possibility of studying the mathematical algorithms for creating computer graphics. The development of a comprehensive algorithm should contribute to the practical realization of the method proposed. It emphasizes on built-in algorithms in software systems for creating computer graphics and the advantages of steganographic embedding by opensource products that hides any archive file in a digital image. Its application contribution is supported by practical examples of software hiding and archiving an encrypted file in a graphic image.

A methodology for empirical research and analysis in the field of cybersecurity

This article is considered to be a continuation of a publication by the author devoted to an algorithm for steganographic embedding of encrypted files in raster images (Yearbook Telecommunication, №9, 2022). The aim of this paper is proposing a methodology for empirical research and analysis on the field of cybersecurity which to contribute to various areas in cybersecurity. Its originality is expressed in the joint application of methods for research and analysis realized by various simulation environments for conducting experiments. This methodology has a specific structure as it is conditionally divided into two major parts depending on the type of the simulation process and software products used – a study of the direct impact of cyberattacks on communication networks by the method of the agent-based modelling and a study of potential steganography attacks using software for simulation of Artificial Neural Networks (ANNs) for the purposes of steganalysis.

Securing Data in Image and Audio Files using Steganography Technique

Securing Data in Image and Audio Files using Steganography Technique

IMAGE-IN: Interactive web-based multidimensional 3D visualizer for multi-modal microscopy images.

Advances in microscopy hardware and storage capabilities lead to increasingly larger multidimensional datasets. The multiple dimensions are commonly associated with space, time, and color channels. Since "seeing is believing", it is important to have easy access to user-friendly visualization software. Here we present IMAGE-IN, an interactive web-based multidimensional (N-D) viewer designed specifically for confocal laser scanning microscopy (CLSM) and focused ion beam scanning electron microscopy (FIB-SEM) data, with the goal of assisting biologists in their visualization and analysis tasks and promoting digital workflows. This new visualization platform includes intuitive multidimensional opacity fine-tuning, shading on/off, multiple blending modes for volume viewers, and the ability to handle multichannel volumetric data in volume and surface views. The software accepts a sequence of image files or stacked 3D images as input and offers a variety of viewing options ranging from 3D volume/surface rendering to multiplanar reconstruction approaches. We evaluate the performance by comparing the loading and rendering timings of a heterogeneous dataset of multichannel CLSM and FIB-SEM images on two devices with installed graphic cards, as well as comparing rendered image quality between ClearVolume (the ImageJ open-source desktop viewer), Napari (the Python desktop viewer), Imaris (the closed-source desktop viewer), and our proposed IMAGE-IN web viewer.