Portable Network Graphics Research Articles

JEDi: java essential dynamics inspector \u2014 a molecular trajectory analysis toolkit

BackgroundPrincipal component analysis (PCA) is commonly applied to the atomic trajectories of biopolymers to extract essential dynamics that describe biologically relevant motions. Although application of PCA is straightforward, specialized software to facilitate workflows and analysis of molecular dynamics simulation data to fully harness the power of PCA is lacking. The Java Essential Dynamics inspector (JEDi) software is a major upgrade from the previous JED software.ResultsEmploying multi-threading, JEDi features a user-friendly interface to control rapid workflows for interrogating conformational motions of biopolymers at various spatial resolutions and within subregions, including multiple chain proteins. JEDi has options for Cartesian-based coordinates (cPCA) and internal distance pair coordinates (dpPCA) to construct covariance (Q), correlation (R), and partial correlation (P) matrices. Shrinkage and outlier thresholding are implemented for the accurate estimation of covariance. The effect of rare events is quantified using outlier and inlier filters. Applying sparsity thresholds in statistical models identifies latent correlated motions. Within a hierarchical approach, small-scale atomic motion is first calculated with a separate local cPCA calculation per residue to obtain eigenresidues. Then PCA on the eigenresidues yields rapid and accurate description of large-scale motions. Local cPCA on all residue pairs creates a map of all residue-residue dynamical couplings. Additionally, kernel PCA is implemented. JEDi output gives high quality PNG images by default, with options for text files that include aligned coordinates, several metrics that quantify mobility, PCA modes with their eigenvalues, and displacement vector projections onto the top principal modes. JEDi provides PyMol scripts together with PDB files to visualize individual cPCA modes and the essential dynamics occurring within user-selected time scales. Subspace comparisons performed on the most relevant eigenvectors using several statistical metrics quantify similarity/overlap of high dimensional vector spaces. Free energy landscapes are available for both cPCA and dpPCA.ConclusionJEDi is a convenient toolkit that applies best practices in multivariate statistics for comparative studies on the essential dynamics of similar biopolymers. JEDi helps identify functional mechanisms through many integrated tools and visual aids for inspecting and quantifying similarity/differences in mobility and dynamic correlations.

Estimating the entropy of neural data by saving them as a .png file

A recommendation of: Mickael Zbili, Sylvain Rama A quick and easy way to estimate entropy and mutual information for neuroscience 10.1101/2020.08.04.236174

Resourceful Investigation of Malnutrition with Machine Learning Using CNN Procedure

This System used to refer to any condition in which the body does not obtain enough nutrients for proper function in this system Image processing is a technique to convert an image into digital form and perform some action on it, in order to get an enhanced image or to citation some useful information from it. There are some types of image that is Tagged Image Format, Joint Photographic Group, Graphic Interchange Format, Portable Network Graphics, Row Image File. Computer can easily classify more than 16 million color where the eye capability has limitation while identifying color and also same people face the problem such as colors carelessness. So the execution nail color Analysis through computer is a higher procedure as compared with human eyes. Human eyes have limited resolution, finding deviation in nearby pixel intensity is not possible for human eyes, but computer vision can detect every pixel appropriately. So, in this system we used the Convolutional Neural Networks (CNN) algorithm & carried out the result. this system is very helpful for the patient, to find out the prediction or detection of diseases without doctor.

Jpeg/Exif Message Digest Compilation With SHA512 Hash Function

Security information method for jpeg / exif documents generally aims to prevent security attack by protecting documents with password and watermark. Both methods cannot used to determine the condition of data integrity at the detection stage of the information security cycle. Message Digest is the essence of a file that used to represent data integrity. This study aims to compile a message digest to detect changes that occur in jpeg / exif documents in information security. The research phase consists of five stages. The first stage, identification of the jpeg / exif document structure conducted using Boyer-Moore string matching algorithm to find jpeg/exif segments location. The Second stage is segment content acquisition, conducted based on segment location and length obtained. The Third step, computing message digest for each segment using SHA512 hash function. Fourth stage, jpeg / exif document modification experiments to identified affected segments. The Fifth stage is selecting and combining the hash value of the segment into message digest. Obtained result show message digest for jpeg / exif documents composed of two parts, the hash value of the SOI segment and the APP1 segment. The SOI segment value used to detect modifications for jpeg to png conversion and image editing. The APP1 hash value used to detect metadata editing. The SOF0 hash values use to detect modification for image recoloring, cropping and resizing.

ChemSpectra: a web-based spectra editor for analytical data

ChemSpectra, a web-based software to visualize and analyze spectroscopic data, integrating solutions for infrared spectroscopy (IR), mass spectrometry (MS), and one-dimensional 1H and 13C NMR (proton and carbon nuclear magnetic resonance) spectroscopy, is described. ChemSpectra serves as web-based tool for the analysis of the most often used types of one-dimensional spectroscopic data in synthetic (organic) chemistry research. It was developed to support in particular processes for the use of open file formats which enable the work according to the FAIR data principles. The software can deal with the open file formats JCAMP-DX (IR, MS, NMR) and mzML (MS) proposing these data file types to gain interoperable data. ChemSpectra can be extended to read also other formats as exemplified by selected proprietary mass spectrometry data files of type RAW and NMR spectra files of type FID. The JavaScript-based editor can be integrated with other software, as demonstrated by integration into the Chemotion electronic lab notebook (ELN) and Chemotion repository, demonstrating the implementation into a digital work environment that offers additional functionality and sustainable research data management options. ChemSpectra supports different functions for working with spectroscopic data such as zoom functions, peak picking and automatic peak detection according to a default or manually defined threshold. NMR specific functions include the definition of a reference signal, the integration of signals, coupling constant calculation and multiplicity assignment. Embedded into a web application such as an ELN or a repository, the editor can also be used to generate an association of spectra to a sample and a file management. The file management supports the storage of the original spectra along with the last edited version and an automatically generated image of the spectra in png format. To maximize the benefit of the spectra editor for e.g. ELN users, an automated procedure for the transfer of the detected or manually chosen signals to the ELN was implemented. ChemSpectra is released under the AGPL license to encourage its re-use and further developments by the community.

CaReAl: capturing read alignments in a BAM file rapidly and conveniently

Some of the variants detected by high-throughput sequencing (HTS) are often not reproducible. To minimize the technical-induced artifacts, secondary experimental validation is required but this step is unnecessarily slow and expensive. Thus, developing a rapid and easy to use visualization tool is necessary to systematically review the statuses of sequence read alignments. Here, we developed a high-performance alignment capturing tool, CaReAl, for visualizing the read-alignment status of nucleotide sequences and associated genome features. CaReAl is optimized for the systematic exploration of regions of interest by visualizing full-depth read-alignment statuses in a set of PNG files. CaReAl was 7.5 times faster than IGV ‘snapshot’, the only stand-alone tool which provides an automated snapshot of sequence reads. This rapid user-programmable capturing tool is useful for obtaining read-level data for evaluating variant calls and detecting technical biases. The multithreading and sequential wide-genome-range-capturing functionalities of CaReAl aid the efficient manual review and evaluation of genome sequence alignments and variant calls. CaReAl is a rapid and convenient tool for capturing aligned reads in BAM. CaReAl facilitates the acquisition of highly curated data for obtaining reliable analytic results.

WITHDRAWN: Contrasting the performance metrics of discrete transformations on digital image steganography using artificial intelligence

Image steganography is the impressive art of hiding or embedding a secret image within cover image without any loss when subject to human vision system. The digital image steganography is initially performed by using Least Significant Bit (LSB) technique in spatial domain. Later, the image steganography is implemented by using various frequency domain techniques in which the secret images are transformed to frequency domain and their payload bits are embedded to the frequency domain of the cover image. In this work, the most commonly used transformation techniques like Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) are applied to the colour images of different formats such as portable network graphics (png), bitmap (bmp), joint photographic experts group (jpeg) and tagged image file format (tiff) and their performance metrics are compared. Additional to the various transformation techniques and colour image formats, various payloads of the secret images are also used. From the overall experimental results and the comparison of performance metrics like mean square error (MSE), peak signal to noise ratio (PSNR), structural similarity index (SSIM) and structural dissimilarity (DSSIM), it is evident that DWT is highly recommendable transformation technique for image steganography compared to other techniques expect for lesser payloads, where DFT exhibits better PSNR and for JPEG images, DCT shows better PSNR.

Comparing a deep learning model's diagnostic performance to that of radiologists to detect Covid -19 features on chest radiographs.

Background:Whether the sensitivity of Deep Learning (DL) models to screen chest radiographs (CXR) for CoVID-19 can approximate that of radiologists, so that they can be adopted and used if real-time review of CXRs by radiologists is not possible, has not been explored before.Objective:To evaluate the diagnostic performance of a doctor-trained DL model (Svita_DL8) to screen for COVID-19 on CXR, and to compare the performance of the DL model with that of expert radiologists.Materials and Methods:We used a pre-trained convolutional neural network to develop a publicly available online DL model to evaluate CXR examinations saved in .jpeg or .png format. The initial model was subsequently curated and trained by an internist and a radiologist using 1062 chest radiographs to classify a submitted CXR as either normal, COVID-19, or a non-COVID-19 abnormal. For validation, we collected a separate set of 430 CXR examinations from numerous publicly available datasets from 10 different countries, case presentations, and two hospital repositories. These examinations were assessed for COVID-19 by the DL model and by two independent radiologists. Diagnostic performance was compared between the model and the radiologists and the correlation coefficient calculated.Results:For detecting COVID-19 on CXR, our DL model demonstrated sensitivity of 91.5%, specificity of 55.3%, PPV 60.9%, NPV 77.9%, accuracy 70.1%, and AUC 0.73 (95% CI: 0.86, 0.95). There was a significant correlation (r = 0.617, P = 0.000) between the results of the DL model and the radiologists’ interpretations. The sensitivity of the radiologists is 96% and their overall diagnostic accuracy is 90% in this study.Conclusions:The DL model demonstrated high sensitivity for detecting COVID-19 on CXR.Clinical Impact:The doctor trained DL tool Svita_DL8 can be used in resource-constrained settings to quickly triage patients with suspected COVID-19 for further in-depth review and testing.

MeteoRead: Client Software for Inserting Observed Atmospheric Data into MySQL<sub>TM</sub> Database and Downloading them into Different File Format

The investigation of the tendency of climate change and its effects on ecology, economy and sociology is essential for long term policy making. The long-term measurement of the physical and chemical properties of the atmosphere with state-of-the-arts instruments provides high-quality data for these studies. The evaluated data are stored in really special file structures and formats that cannot be inserted in one common database. Moreover, the observed data usually available in ASCII format and the users sometimes need to convert them in other format. The file conversion is usually time consuming procedure and can contribute to the uncertainties. MeteoRead is a client database software that imports the observed atmospheric data e.g. wind direction, wind speed, aerosol particle concentration etc. and makes them available in different file formats, which are most commonly used in climate research. This JavaTM based program applies the Structured Query Language (SQL) functions such as table creation on a database server, data or figures insertion into the table and data selection via Graphical User Interface. The selected data can be stored in NetCDF, HDF5, DataBase or TXT file formats and the figures can be available in PNG, JPG, JPNG, PDF or GIF file formats. The program was tested on Linux and Windows platforms with different JavaTM Development Kit. The MeteoRead is planned to be developed to visualizing the annual, seasonal, monthly, daily or hourly average value of the selected data and to use the functionality of the SQL database to calculate various mathematical and statistical correlations.

Influence of the file format and transmission app on the radiographic diagnosis of caries lesions

This in vitro study aimed to evaluate the influence of the radiographic image file format and the transmission application (app) on the diagnosis of proximal caries lesions. Twenty bitewing radiographs of 40 posterior human teeth placed in phantoms were acquired using the Digora Toto digital sensor. All images were exported as TIFF (Tagged Image File Format), BMP (Windows Bitmap), PNG (Portable Network Graphics), and JPEG (Joint Photographic Experts Group) and transmitted online via WhatsApp and Messenger. Five examiners evaluated the radiographs with no online transmission and as transmitted through the 2 apps for the presence of proximal caries lesions using a 5-point scale. The reference standard for caries lesions was established using micro-computed tomography. Two-way analysis of variance compared values of sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (α=.05). The kappa test was used to assess intra- and interexaminer agreement. Sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve values showed no significant differences in the diagnosis of proximal caries lesions between the different image file formats (P ≥ .773) and transmission apps (P ≥ .608). Intraexaminer agreement was substantial (κ=0.742) and interexaminer agreement was moderate (κ=0.475). The digital file format and transmission app did not influence the radiographic diagnosis of proximal caries lesions.

Optimasi Steganografi Berbasis Citra Digital Menggunakan Modifikasi Bit

Keamanan dan kerahasiaan menjadi aspek yang sangat penting bagi pengguna teknologi informasi. Untuk menghindari pesan yang dikirimkan jatuh pada pihak-pihak yang tidak berkepentingan dan terjadi penyalahgunaan terhadap pesan. Banyak cara yang dapat dilakukan untuk menyembunyikan data atau pesan yang akan dikirim. Salah satunya adalah steganografi. Steganografi adalah teknik menyisipkan pesan ke media lain, sehingga pesan tersebut akan tersembunyi dan yang akan nampak adalah media lain untuk menyisipkan pesan. Steganografi memerlukan pesan dan cover. Cover adalah media yang digunakan untuk menyisipkan pesan. Penelitian ini bertujuan untuk menyisipkan pesan berupa citra ke dalam cover berupa citra dengan format JPG dan PNG. Pada penelitian ini menggunakan metode Least Significant Bit (LSB) sebagai metode penyisipan dan metode modifikasi bit untuk mengoptimalkan kinerja LSB dalam menyisipkan pesan 1 hingga 4 bit. Hasil penelitian menunjukkan bahwa proses penyisipan citra berdasarkan unjuk kerja koefisien korelasi dan PSNR menunjukkan jumlah bit terbaik dalam proses penyisipan adalah berjumlah 1 bit. Pada proses ekstraksi citra pesan berdasarkan unjuk kerja koefisien korelasi dan MAPE menunjukkan jumlah bit terbaik dari proses penyisipan adalah berjumlah 4 bit. Sedangkan format terbaik adalah jika citra cover dan citra pesan dalam format PNG. Disimpulkan, semakin banyak bit yang disisipkan maka kualitas cover akan semakin menurun tetapi hasil ekstraksi semakin tinggi tingkat keberhasilannya dalam kembalinya pesan.

Selection-driven tumor evolution with public goods leads to patterns of clonal expansion consistent with neutral growth.

SummaryCancers are the result of eco-evolutionary processes fueled by heritable phenotypic diversification and driven by environmentally dependent selection. Space represents a key growth-limiting ecological resource, the ability to explore this resource is likely under strong selection. Using agent-based modeling, we explored the interplay between phenotypic strategies centered on gaining access to new space through cell-extrinsic degradation of extracellular matrix barriers and the exploitation of this resource through maximizing cell proliferation. While cell proliferation is a cell-intrinsic property, newly accessed space represents a public good, which can benefit both producers and non-producers. We found that this interplay results in ecological succession, enabling emergence of large, heterogeneous, and highly proliferative populations. Even though in our simulations both remodeling and proliferation strategies were under strong positive selection, their interplay led to sub-clonal architecture that could be interpreted as evidence for neutral evolution, warranting cautious interpretation of inferences from sequencing of cancer genomes.

Web-based Live Chat Application uses Advanced Encryption Standard Methods and Rivest Shamir Adleman

The development of technology, especially in the data security system in maintaining the security of information data has been growing rapidly. In maintaining the security of information data there are branches of science in its development such as cryptography and steganography. In its application is not only done on one security technique, but can be done in combination with information security data. This study aims to create a data security system by implementing cryptography on messages in the live chat application. The message security in live chat applies a combination of AES and RSA algorithms. The AES (Advanced Encryption Standard) method is a cryptographic algorithm that can be used to secure data, the AES algorithm is a symmetric chipertext block that can encrypt and decrypt information, and the RSA Method is the RSA Algorithm is a block cipher algorithm (an algorithm that works per block of data) that groups plaintext into blocks first before being encrypted to become ciphertext. This application aims to secure messages sent by the sender to stay safe when received by the recipient. The system will be based on a website using the PHP programming language, using a codeigniter framework and a MySQL database. This information system is in the form of live chat which will be encrypted by 2 methods. The sender will send a message through the live chat website then the message is encrypted so that its security is guaranteed, the message stored in the database will be automatically encrypted by the two methods applied then after arriving at the recipient the message is automatically described. The message sent is in the form of text and png files.

Upgrade of the QA system in the BM@N experiment at the NICA

The BM@N (Baryonic Matter at the Nuclotron) is an experiment at the NICA (Nuclotron-based Ion Collider fAcility). The first physics runs were carried out with the collection of experimental data in 2018. For the physics analysis of events recorded by detectors of the BM@N the BmnRoot framework is used. It provides a powerful tools for detector performance studying, event simulation, data analysis and developing new algorithms that continually improve this environment. The QA (Quality Assurance) system is used to evaluate the quality of the event reconstruction procedures and collected data. It displays the results of comparing the properties of the simulated events with the reconstructed ones. However, previous version of QA system was nonflexible because its output was just a set of PNG images. Result of QA system modernization by using JSROOT library is described in current report. After this upgrade histograms are displayed in web browser. User can zoom histograms, change scales, get value of bin by moving the cursor on it, etc. It also became possible to get sample mean and standard deviation for each histogram. Upgraded system is quite scalable, so it can easily be extended with new histograms. At the moment, the modernized system is part of the BmnRoot framework.

Teaching AND reaching our students from a distance

Teaching AND reaching our students from a distance

Nutil: A Pre- and Post-processing Toolbox for Histological Rodent Brain Section Images.

With recent technological advances in microscopy and image acquisition of tissue sections, further developments of tools are required for viewing, transforming, and analyzing the ever-increasing amounts of high-resolution data produced. In the field of neuroscience, histological images of whole rodent brain sections are commonly used for investigating brain connections as well as cellular and molecular organization in the normal and diseased brain, but present a problem for the typical neuroscientist with no or limited programming experience in terms of the pre- and post-processing steps needed for analysis. To meet this need we have designed Nutil, an open access and stand-alone executable software that enables automated transformations, post-processing, and analyses of 2D section images using multi-core processing (OpenMP). The software is written in C++ for efficiency, and provides the user with a clean and easy graphical user interface for specifying the input and output parameters. Nutil currently contains four separate tools: (1) A transformation toolchain named “Transform” that allows for rotation, mirroring and scaling, resizing, and renaming of very large tiled tiff images. (2) “TiffCreator” enables the generation of tiled TIFF images from other image formats such as PNG and JPEG. (3) A “Resize” tool completes the preprocessing toolset and allows downscaling of PNG and JPEG images with output in PNG format. (4) The fourth tool is a post-processing method called “Quantifier” that enables the quantification of segmented objects in the context of regions defined by brain atlas maps generated with the QuickNII software based on a 3D reference atlas (mouse or rat). The output consists of a set of report files, point cloud coordinate files for visualization in reference atlas space, and reference atlas images superimposed with color-coded objects. The Nutil software is made available by the Human Brain Project (https://www.humanbrainproject.eu) at https://www.nitrc.org/projects/nutil/.

Predicting bovine tuberculosis status of dairy cows from mid-infrared spectral data of milk using deep learning

Bovine tuberculosis (bTB) is a zoonotic disease in cattle that is transmissible to humans, distributed worldwide, and considered endemic throughout much of England and Wales. Mid-infrared (MIR) analysis of milk is used routinely to predict fat and protein concentration, and is also a robust predictor of several other economically important traits including individual fatty acids and body energy. This study predicted bTB status of UK dairy cows using their MIR spectral profiles collected as part of routine milk recording. Bovine tuberculosis data were collected as part of the national bTB testing program for Scotland, England, and Wales; these data provided information from over 40,500 bTB herd breakdowns. Corresponding individual cow life-history data were also available and provided information on births, movements, and deaths of all cows in the study. Data relating to single intradermal comparative cervical tuberculin (SICCT) skin-test results, culture, slaughter status, and presence of lesions were combined to create a binary bTB phenotype labeled 0 to represent nonresponders (i.e., healthy cows) and 1 to represent responders (i.e., bTB-affected cows). Contemporaneous individual milk MIR spectral data were collected as part of monthly routine milk recording and matched to bTB status of individual animals on the single intradermal comparative cervical tuberculin test date (±15 d). Deep learning, a sub-branch of machine learning, was used to train artificial neural networks and develop a prediction pipeline for subsequent use in national herds as part of routine milk recording. Spectra were first converted to 53 × 20-pixel PNG images, then used to train a deep convolutional neural network. Deep convolutional neural networks resulted in a bTB prediction accuracy (i.e., the number of correct predictions divided by the total number of predictions) of 71% after training for 278 epochs. This was accompanied by both a low validation loss (0.71) and moderate sensitivity and specificity (0.79 and 0.65, respectively). To balance data in each class, additional training data were synthesized using the synthetic minority over sampling technique. Accuracy was further increased to 95% (after 295 epochs), with corresponding validation loss minimized (0.26), when synthesized data were included during training of the network. Sensitivity and specificity also saw a 1.22- and 1.45-fold increase to 0.96 and 0.94, respectively, when synthesized data were included during training. We believe this study to be the first of its kind to predict bTB status from milk MIR spectral data. We also believe it to be the first study to use milk MIR spectral data to predict a disease phenotype, and posit that the automated prediction of bTB status at routine milk recording could provide farmers with a robust tool that enables them to make early management decisions on potential reactor cows, and thus help slow the spread of bTB.

An Improved VLSI Design of the ALU Based FIR Filter for Biomedical Image Filtering Application.

FIR filter is the most widely used device in DSP applications, which is also applicable to integrate with image processing approaches. The ALU based FIR structure is applicable for various devices to increase the performance. The ALU design operation includes accumulation, subtraction, shifting, multiplication and filtering. Existing methods are designed with various multipliers like Wallace tree multiplier, DADDA multiplier, Vedic multiplier and adders like carry select adder, and carry look-ahead adder. The main objective is to reduce the area, delay and power factors since optimum VLSI circuit is employed in this paper. By these adders and multipliers, operations are independently enabling main operations in DSP. The FIR filter is designed using a MAC unit with clock regenerative comparators. In the field of the VLSI industry, the low power, reduced time, and area-efficient designs are mostly preferred for various applications. Adders and multipliers play a vital role in VLSI circuit designs. The recent electronics industry uses a digital filter for various real-time applications. This utilizes Finite Impulse Response (FIR) and Infinite Impulse Response (IIR) filters, here the FIR filter is most stable than IIR filter. This FIR filter indicates the impulse signal into finite form and it is used mainly in DSP processors for getting high-speed. In these two ALU and FIR circuits, the adders and multiplier block's usage is increased, it consumes much power. The proposed research work uses the clock-gating technique for reducing power consumption. Here the latch-based clock gating technique provides an efficient result. XOR-based logic circuit reduces the design complexity and utilizes the less area. Carry save accumulator is a digital adder used for addition. It provides the two set of output, which is partial sum and carry output. The ripple carry adder uses a full adder circuit for its operation. It propagates the carry value in the last bit. In addition, the combination of CSA and RCA utilizes less area, high speed and provides the better throughput. In multiplier block, the booth multiplier algorithm is used with XOR-based logic. Here this proposed FIR filter is designed for performing image filtration of retina image. This process improves the better visualization approach inthe medical field. Thus, the proposed ALU based FIR filter with a latch-based clock gating technique is designed and analyzed with various parameters. Here the modified adders and multipliers are proposed for the efficiency of the system. The modified carry save adder is proposed with combining ripple carry adder logic for improving the adders' performance. The enhanced booth multiplier is designed using add and shift method for reducing the numberof stages to calculate the result. This process is applied to perform image processing of the retina image. After designing the ALU based FIR filter structure in the VLSI environment, the image is loaded on the MATLAB as the .png format, then it is converted into a hex file, which is read from the Xilinx to perform filtering the process. Then the 'dataout' is converted into a binary file to obtain the result of the filtering process. The enhanced booth multiplier reduces the delay by reducing the number of stages to calculate the result. Here the clock gating technique is proposed with the latch-based design for reducing the dynamic and clock power consumption. The number of adder's circuit in both ALU and FIR circuits is less since it improves the overall efficiency of the system. Thus, the proposed methodology concluded that the design and analysis of ALU based FIR filter for medical image processing give the efficient result on the way of achieving the factors such as power (Static & Dynamic), Delay (Path delay) area utilization, MSE and PSNR. Here the image processing of FIR results to MSE and PSNR values, which obtained a better result than the existing VLSI based image processing works. The latch-based clock gating circuit is connected with the proposed circuit, based on the gated clock signal, it optimizes the gated circuit of the whole design since it also reduces the error and provides the efficient power report. This proposed VLSI model is simulated using Xilinx ISE 14.5 and Modelsim synthesizes it; here with the help of MATLAB, with the adaptation of the 2018a tool, the image filtering was done.

Seleksi Wajah Digital Menggunakan Algoritma Camshift

Real time for digital face database selection using camshift algorithm] Education taken 4-5 years affects physical development. This study uses student digital video data. The recording results are used to identify certain characteristics possessed by a student later stored in the digital file database catalog. The stages of the study consisted of identification, recognition and matching of faces. It starts from converting .mp4 videos to .AVI format. The CAMShift algorithm uses basic HSV colors for tracking face position (tracking) and faces recognition. 1-2 seconds video produces 45-200 frames PNG file. The face matching test results were carried out on several video play, the success of detection: 100% selected, 45%-60%, 80-90%, concluded around 50%-100% successful. Face movements will be caught by the centroid bounding box, if the color of the face is dominant in Hue.

Graphic Library Optimization for MIPS Architecture

The aim of this paper and research was to analyse the efficiency of the compiler-generated code for the graphics library and to present results obtained by optimization for the MIPS (Million Instructions Per Second) architecture. Libpng is the official Portable Network Graphics reference library for use in applications that read, create, and manipulate PNG (Portable Network Graphics) raster image files. Given the data structure in the PNG files, as well as the capabilities of the MIPS instruction set, it was expected that significant improvements could be made. Graphic library libpng is optimized by using MIPS instruction set extension and tested on MIPS Malta 74K platform. Test results show, that by using MIPS optimization test, execution times are substantially improved. Our libpng optimization have achieved performance increase of 10 %–78 % depending on optimized routine.