File Size Research Articles

VoxIsle: A new method in InterDosi code for improving internal dosimetry simulation performances in voxelized phantom

In order to assess the internal dose due to exposure to radiation, the ICRP recommends the use of a reference voxelized phantom. Although voxelized geometry is a very promising geometric representation of a complex body, it showed a limitation in dose calculation for large-voxel array phantoms that requires more memory and CPU time. We have developed a new voxel compression method called VoxIsle that merges adjacent voxels that belong to the same organ/tissue. The VoxIsle was based on the LRAH (Largest Rectangular Area Histogram) algorithm. To evaluate the performances of this method, compressed and uncompressed geometries of some voxel-based phantoms were used to calculate dosimetric coefficients of gamma, electron and alpha particles. Results showed that for a given particle, there is a smooth difference between coefficients calculated using the two types of geometry. Additionally, depending on the characteristics of the voxelized phantom, the memory and CPU time required to construct geometry and material of a phantom, and its file size for a compressed geometry appear to be reduced up to 77%, 73% and 97%, respectively. Regarding computational performance, with the exception of alpha particles for which the results showed a steady increase in CPU time, the simulation with compressed geometry was up to 59.3% faster than the uncompressed geometry. The new compression method can considerably improve the simulation performances of InterDosi code that can perform internal dosimetry studies on voxelized phantoms.

Metaheuristic-based energy-aware image compression for mobile app development

AbstractThe widely applied JPEG standard has undergone recent efforts using population-based metaheuristic (PBMH) algorithms to optimise quantisation tables (QTs) for specific images. However, user preferences, like an Android developer’s preference for small-size images, are often overlooked, leading to high-quality images with large file sizes. Another limitation is the lack of comprehensive coverage in current QTs, failing to accommodate all possible combinations of file size and quality. Therefore, this paper aims to propose three distinct contributions. First, to include the user’s opinion in the compression process, the file size of the output image can be controlled by a user in advance. To this end, we propose a novel objective function for population-based JPEG image compression. Second, we suggest a novel representation to tackle the lack of comprehensive coverage. Our proposed representation can not only provide more comprehensive coverage but also find the proper value for the quality factor for a specific image without any background knowledge. Both representation and objective function changes are independent of the search strategies and can be used with any population-based metaheuristic (PBMH) algorithm. Therefore, as the third contribution, we also provide a comprehensive benchmark on 22 state-of-the-art and recently-introduced PBMH algorithms on our new formulation of JPEG image compression. Our extensive experiments on different benchmark images and in terms of different criteria show that our novel formulation for JPEG image compression can work effectively.

Quantitative Analysis of CGRP-IR Afferent Axons in the Mouse Stomach Using Zeiss Arivis Vision4D for Automated Tracing

Gastric nociceptive afferents detect and respond to noxious stimuli by transmitting signals from the stomach to the brain. Calcitonin gene-related peptide (CGRP) is a marker for nociceptive afferents and is crucial to gastric functions, including gastric acid secretion, gut motility, and inflammation. However, the topographical quantitative analysis of CGRP-immunoreactive (CGRP-IR) axons in the whole stomach is challenging due to the large amount of axon innervation in various targets within the tissue. Manual tracing of axons is time-consuming, labor-intensive, and extremely tedious, while currently existing automatic neuron tracing programs often need help with large file sizes or tracing inaccuracies. In this study, we used Zeiss Arivis Vision4D, a novel and sophisticated software with a user-guided machine learning capability, for automated tracing of CGRP-IR axons in flat-mounts of the whole mouse stomach muscular layers and thick serial sections of the antrum-pylorus region (C57BL/6J, male, 2-3 months old, n=7). We utilized a combination of techniques, including the Zeiss M2 Imager for automated scanning, Zen 3.3 (blue edition) for image processing, and Vision4D for stitching the entire stomach flat-mounts and sections, 3D fiber tracing, and density analysis. Our results demonstrated that: 1) Vision4D detected and traced almost all CGRP-IR axons of different gastric targets (blood vessels, muscles, myenteric neurons) in different regions (fundus, corpus, antrum) of the stomach. 2) The x-y-z tracing allowed the visualization of axons in space, portraying its continuous trajectory across layers in the muscular flat mounts (longitudinal muscle, myenteric plexus, circular muscle) and cross sections (muscles, submucosa, mucosa). 3) Vision4D also enabled quantitative morphological and laminar analysis based on target and layer separations. The axon density heatmap generated from the tracing data showed high CGRP-IR axon innervation in the blood vessels. After the removal of blood vessels, dense innervation was seen in the upper fundus and antrum-pylorus followed by corpus, indicating the abundance of CGRP in these regions. 4) Vision4D is a powerful tool in handling large data sizes (hundreds of gigabytes of optical sections in more than 300 image frames per stomach) and outstanding in its capability to track nerve fibers in a highly accurate and time effcient manner. This has paved the way for data batch processing to be accessible, as well as shown that multi-marker tracing of the same tissue sample is attainable. 5) The tracing data will be integrated into a stomach scaffold for a 3D map of CGRP-IR afferent axons. This study represents, for the first time, the automatically traced CGRP-IR axons using whole stomach preparations and highlights the potential of Vision4D in creating axon tracing models in other organs and species. This study is supported by NIH 1 U01 NS113867-01, NIH R15 1R15HL137143-01A1 and Carl ZEISS Company. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Effect of Taper and Pitch on Nickle-Titanium File with Variable Cross Section to Its Cyclic Fatigue (In Silico Study)

The geometric design of an endodontic file includes cross-sectional shape, taper, and pitch. NiTi endodontic files of OneCurve (MicroMega) are made of two variations of cross-sectional shape, that is, double-s shaped and triple helix. Various kinds of modifications were made to increase the resistance of the NiTi endodontic files from fracture. Cyclic fatigue is the most common factor that causes a fracture of the endodontic file. Objective: The purpose of this study was to obtain a NiTi endodontic file design that has the best cyclic resistance value based on its taper size and number of pitch. Methods: This study used OneCurve endodontic file size 25.06, then scanned with MicroCT Scan and modified the geometric design. The number of file modifications was nine. Taper size modifications were 4%, 6%, and 8%; the number of pitch modifications was reduced by three, fixed, and added by three. Cyclic fatigue measurement simulations were carried out using the finite element method three times each. The result data were analyzed using a two-way ANOVA test and then continued with LSD. Results: The results of the statistical test showed that there was an effect of the size of the taper on the cyclic fatigue values. Endodontic files with a size of a taper 4% had the lowest cyclic fatigue value. Conclusion: The conclusion of this research was that the taper size affects the value of cyclic fatigue in continuous endodontic files made of nickel-titanium with variable cross sections. The number of pitch did not show a significant effect on the cyclic value.

Transforming Tele-Ophthalmology: Utilizing Cloud Computing for Remote Eye Care.

Tele-ophthalmology is gaining recognition for its role in improving eye care accessibility via cloud-based solutions. The Google Cloud Platform (GCP) Healthcare API enables secure and efficient management of medical image data such as high-resolution ophthalmic images. This study investigates cloud-based solutions' effectiveness in tele-ophthalmology, with a focus on GCP's role in data management, annotation, and integration for a novel imaging device. Leveraging the Integrating the Healthcare Enterprise (IHE) Eye Care profile, the cloud platform was utilized as a PACS and integrated with the Open Health Imaging Foundation (OHIF) Viewer for image display and annotation capabilities for ophthalmic images. The setup of a GCP DICOM storage and the OHIF Viewer facilitated remote image data analytics. Prolonged loading times and relatively large individual image file sizes indicated system challenges. Cloud platforms have the potential to ease distributed data analytics, as needed for efficient tele-ophthalmology scenarios in research and clinical practice, by providing scalable and secure image management solutions.

INNBC DApp, a decentralized application to permanently store biomedical data on a modern, proof-of-stake (POS), blockchain such as BNB Smart Chain

BackgroundA blockchain can be described as a distributed ledger database where, under a consensus mechanism, data are permanently stored in records, called blocks, linked together with cryptography. Each block contains a cryptographic hash function of the previous block, a timestamp, and transaction data, which are permanently stored in thousands of nodes and never altered. This provides a potential real-world application for generating a permanent, decentralized record of scientific data, taking advantage of blockchain features such as timestamping and immutability.ImplementationHere, we propose INNBC DApp, a Web3 decentralized application providing a simple front-end user interface connected with a smart contract for recording scientific data on a modern, proof-of-stake (POS) blockchain such as BNB Smart Chain. Unlike previously proposed blockchain tools that only store a hash of the data on-chain, here the data are stored fully on-chain within the transaction itself as “transaction input data”, with a true decentralized storage solution. In addition to plain text, the DApp can record various types of files, such as documents, images, audio, and video, by using Base64 encoding. In this study, we describe how to use the DApp and perform real-world transactions storing different kinds of data from previously published research articles, describing the advantages and limitations of using such a technology, analyzing the cost in terms of transaction fees, and discussing possible use cases.ResultsWe have been able to store several different types of data on the BNB Smart Chain: raw text, documents, images, audio, and video. Notably, we stored several complete research articles at a reasonable cost. We found a limit of 95KB for each single file upload. Considering that Base64 encoding increases file size by approximately 33%, this provides us with a theoretical limit of 126KB. We successfully overcome this limitation by splitting larger files into smaller chunks and uploading them as multi-volume archives. Additionally, we propose AES encryption to protect sensitive data. Accordingly, we show that it is possible to include enough data to be useful for storing and sharing scientific documents and images on the blockchain at a reasonable cost for the users.ConclusionINNBC DApp represents a real use case for blockchain technology in decentralizing biomedical data storage and sharing, providing us with features such as immutability, timestamp, and identity that can be used to ensure permanent availability of the data and to provide proof-of-existence as well as to protect authorship, a freely available decentralized science (DeSci) tool aiming to help bring mass adoption of blockchain technology among the scientific community.

Influence of helical pitch and gantry rotation time on image quality and file size in ultrahigh-resolution photon-counting detector CT

The goal of this experimental study was to quantify the influence of helical pitch and gantry rotation time on image quality and file size in ultrahigh-resolution photon-counting CT (UHR-PCCT). Cervical and lumbar spine, pelvis, and upper legs of two fresh-frozen cadaveric specimens were subjected to nine dose-matched UHR-PCCT scan protocols employing a collimation of 120 × 0.2 mm with varying pitch (0.3/1.0/1.2) and rotation time (0.25/0.5/1.0 s). Image quality was analyzed independently by five radiologists and further substantiated by placing normed regions of interest to record mean signal attenuation and noise. Effective mAs, CT dose index (CTDIvol), size-specific dose estimate (SSDE), scan duration, and raw data file size were compared. Regardless of anatomical region, no significant difference was ascertained for CTDIvol (p ≥ 0.204) and SSDE (p ≥ 0.240) among protocols. While exam duration differed substantially (all p ≤ 0.016), the lowest scan time was recorded for high-pitch protocols (4.3 ± 1.0 s) and the highest for low-pitch protocols (43.6 ± 15.4 s). The combination of high helical pitch and short gantry rotation times produced the lowest perceived image quality (intraclass correlation coefficient 0.866; 95% confidence interval 0.807–0.910; p < 0.001) and highest noise. Raw data size increased with acquisition time (15.4 ± 5.0 to 235.0 ± 83.5 GByte; p ≤ 0.013). Rotation time and pitch factor have considerable influence on image quality in UHR-PCCT and must therefore be chosen deliberately for different musculoskeletal imaging tasks. In examinations with long acquisition times, raw data size increases considerably, consequently limiting clinical applicability for larger scan volumes.

Evaluating Urine Cytology Slide Digitization Efficiency: A Comparative Study Using an Artificial Intelligence-Based Heuristic Scanning Simulation and Multiple Z-Plane Scanning

Introduction: Digitizing cytology slides presents challenges because of their three-dimensional features and uneven cell distribution. While multi-Z-plane scan is a prevalent solution, its adoption in clinical digital cytopathology is hindered by prolonged scanning times, increased image file sizes, and the requirement for cytopathologists to review multiple Z-plane images. Methods: This study presents heuristic scan as a novel solution, using an artificial intelligence (AI)-based approach specifically designed for cytology slide scanning as an alternative to the multi-Z-plane scan. Both the 21 Z-plane scan and the heuristic scan simulation methods were used on 52 urine cytology slides from three distinct cytopreparations (Cytospin, ThinPrep, and BD CytoRich™ [SurePath]), generating whole-slide images (WSIs) via the Leica Aperio AT2 digital scanner. The AI algorithm inferred the WSI from 21 Z-planes to quantitate the total number of suspicious for high-grade urothelial carcinoma or more severe cells (SHGUC+) cells. The heuristic scan simulation calculated the total number of SHGUC+ cells from the 21 Z-plane scan data. Performance metrics including SHGUC+ cell coverage rates (calculated by dividing the number of SHGUC+ cells identified in multiple Z-planes or heuristic scan simulation by the total SHGUC+ cells in the 21 Z-planes for each WSI), scanning time, and file size were analyzed to compare the performance of each scanning method. The heuristic scan's metrics were linearly estimated from the 21 Z-plane scan data. Additionally, AI-aided interpretations of WSIs with scant SHGUC+ cells followed The Paris System guidelines and were compared with original diagnoses. Results: The heuristic scan achieved median SHGUC+ cell coverage rates similar to 5 Z-plane scans across three cytopreparations (0.78–0.91 vs. 0.75–0.88, p = 0.451–0.578). Notably, it substantially reduced both scanning time (137.2–635.0 s vs. 332.6–1,278.8 s, p < 0.05) and image file size (0.51–2.10 GB vs. 1.16–3.10 GB, p < 0.05). Importantly, the heuristic scan yielded higher rates of accurate AI-aided interpretations compared to the single Z-plane scan (62.5% vs. 37.5%). Conclusion: We demonstrated that the heuristic scan offers a cost-effective alternative to the conventional multi-Z-plane scan in digital cytopathology. It achieves comparable SHGUC+ cell capture rates while reducing both scanning time and image file size, promising to aid digital urine cytology interpretations with a higher accuracy rate compared to the conventional single (optimal) plane scan. Further studies are needed to assess the integration of this new technology into compatible digital scanners for practical cytology slide scanning.

How Much Storage Precision Can Be Lost: Guidance for Near-Lossless Compression of Untargeted Metabolomics Mass Spectrometry Data.

Several lossy compressors have achieved superior compression rates for mass spectrometry (MS) data at the cost of storage precision. Currently, the impacts of precision losses on MS data processing have not been thoroughly evaluated, which is critical for the future development of lossy compressors. We first evaluated different storage precision (32 bit and 64 bit) in lossless mzML files. We then applied 10 truncation transformations to generate precision-lossy files: five relative errors for intensities and five absolute errors for m/z values. MZmine3 and XCMS were used for feature detection and GNPS for compound annotation. Lastly, we compared Precision, Recall, F1 - score, and file sizes between lossy files and lossless files under different conditions. Overall, we revealed that the discrepancy between 32 and 64 bit precision was under 1%. We proposed an absolute m/z error of 10-4 and a relative intensity error of 2 × 10-2, adhering to a 5% error threshold (F1 - scores above 95%). For a stricter 1% error threshold (F1 - scores above 99%), an absolute m/z error of 2 × 10-5 and a relative intensity error of 2 × 10-3 were advised. This guidance aims to help researchers improve lossy compression algorithms and minimize the negative effects of precision losses on downstream data processing.

Comparison of CAD Software for Designing Cellular Structures for Additive Manufacturing

Additive manufacturing (AM) technologies provide significant design freedom, which is highly desirable in today’s fast-paced product design processes. However, most of the parametric CAD software tools used today do not fully utilize this potential for freedom of form and design. Design mechanisms, such as topology optimization (TO), generative design (GD), and lattice structures, are available on the market to help designers minimize weight and material cost while maximizing the stiffness and flexibility of planned designs. This paper proposes a benchmarking approach for designers and engineers to select a suitable software tool for lattice structure generation for their specific applications. The approach includes preselecting software tools based on a weighted point evaluation of seven significant criteria. The tools are then evaluated based on key metrics such as computing time and file size of exported structures, as well as the following six distinctive attributes: usability, reliability, availability, performance, support, and cost. The evaluation process considers a total of 32 defined features. The investigation produced clear recommendations regarding overall performance, reliability, and user experience. The findings indicate that the option of a comprehensive support offering, as well as the initial and operational costs, are significant drivers in the decision-making process.

Comparative Evaluation of Solite RS3 and HyFlex Remover Retreatment Files in Conserving Remaining Dentin Thickness During Endodontic Retreatment Using Cone Beam Computed Tomography: An In Vitro Analysis.

Introduction Non-surgical retreatment is seen as a conservative choice for dealing with recurrent infections, instead of opting for periapical surgery. The retreatment processes should be promptly and efficiently carried out, utilizing a suitable armamentarium. The objective of this experiment is to evaluate the quantity of root dentin that remains following the removal of gutta-percha (GP) from the root canal employing two distinct retreatment files. Materials and methods Sixty single-rooted teeth were selected for the examination. The process of shaping and cleaning was performed using the step-back approach, with a master apical file size of 40. The smear layer was effectively eliminated by rinsing with a solution of 3% sodium hypochlorite and 17% ethylenediaminetetraacetic acid. Paper points were employed to desiccate the canals. The obturation process involved the utilization of the lateral compaction technique with the AH Plus sealer (Dentsply Sirona, NC, USA). The teeth were classified into two groups: Group I (n=30) underwent retreatment using HyFlex Remover (Coletene India, Pvt., Ltd.), whereas Group II (n=30) received therapy with Solite RS3 retreatment files (Solite Dental in Chennai, India). The remaining dentin thickness (RDT) was assessed by cone beam computed tomography at levels 3, 6, and 9 mm from the cemento enamel junction after the removal of GP. The acquired data underwent examination using an independent t-test to determine statistical significance. Results The findings demonstrate that the utilization of Solite RS3 files led to a higher level of dentin thickness remaining at 3 mm, 6 mm, and 9 mm on the mesial side in comparison to HyFlex Remover retreatment files. The observed difference was found to be statistically significant at a significance level of p<0.05 on the mesial side. Nevertheless, there was no notable disparity seen between the two file types at these three levels on the distal side (p>0.05). Conclusion Based on the obtained results of the study, it can be concluded that Solite RS3 files show promise in preserving the RDT. However, further studies encompassing diverse parameters are needed to establish a conclusive and definitive conclusion.

A hyperspectral surgical microscope with super-resolution reconstruction for intraoperative image guidance.

Hyperspectral imaging (HSI) is an emerging imaging modality in medical applications, especially for intraoperative image guidance. A surgical microscope improves surgeons' visualization with fine details during surgery. The combination of HSI and surgical microscope can provide a powerful tool for surgical guidance. However, to acquire high-resolution hyperspectral images, the long integration time and large image file size can be a burden for intraoperative applications. Super-resolution reconstruction allows acquisition of low-resolution hyperspectral images and generates high-resolution HSI. In this work, we developed a hyperspectral surgical microscope and employed our unsupervised super-resolution neural network, which generated high-resolution hyperspectral images with fine textures and spectral characteristics of tissues. The proposed method can reduce the acquisition time and save storage space taken up by hyperspectral images without compromising image quality, which will facilitate the adaptation of hyperspectral imaging technology in intraoperative image guidance.

Enhanced Security in Medical Imaging: A Novel Watermarking and Compression Approach

Medical images, including magnetic resonance imaging (MRI), ultrasound (US), computerized tomography (CT), X-rays, and electrocardiography (ECG), each have distinct benefits and drawbacks. Accurate identification of these images is crucial for maintaining patient-specific data integrity. This study proposes a novel watermarking technique that employs Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT), and Singular Value Decomposition (SVD) to enhance the security, confidentiality, and integrity of medical images. Previous research by Badshah et al. underlines that digital watermarking significantly bolsters the protection of medical images. Additionally, we incorporate Run Length Encoding (RLE) as a compression method to efficiently reduce data memory requirements. The implementation of these techniques demonstrated a marked improvement in the Peak Signal-to-Noise Ratio (PSNR), increasing by up to 5 dB in watermarked images compared to non-watermarked ones, indicating enhanced imperceptibility. Moreover, the file size reduction achieved through our compression approach ranged from 15% to 30%, ensuring that high-quality images consume less storage space. These advancements facilitate the secure and efficient handling of medical image data, supporting their use in clinical environments.

E2EE enhanced patient-centric blockchain-based system for EHR management.

To secure sensitive medical records in the healthcare clouds, this paper proposes an End-to-End Encryption (E2EE) to enhance a patient-centric blockchain-based system for electronic health record (EHR) management. The suggested system with a focus on the patient enables individuals to oversee their medical records within various involved parties by authorizing or withdrawing permission for access to their records. Utilizing the inter-planetary file system (IPFS) for record storage is chosen due to its decentralized nature and its ability to guarantee the unchangeability of records. Then an E2EE enhancement maintains the medical data integrity using dual level-Hybrid encryption: symmetric Advanced Encryption Standard (AES) and asymmetric Elliptic Curve Cryptography (ECC) cryptographic techniques. The proposed system is implemented using the Ethereum blockchain system for EHR data sharing and integration utilizing a web-based interface for the patient and all users to initiate the EHR sharing transactions over the IPFS cloud. The proposed system performance is evaluated in a working system prototype. For different file sizes between 512 KB to 100 MB, the performance metrics used to evaluate the proposed system were the time consumed for generating key, encryption, and decryption. The results demonstrate the proposed system's superiority over other cutting-edge systems and its practical ability to share secure health data in cloud environments.

Influential Metrics Estimation and Dynamic Frequency Selection Based on Two-Dimensional Mapping for JPEG-Reversible Data Hiding.

JPEG Reversible Data Hiding (RDH) is a method designed to extract hidden data from a marked image and perfectly restore the image to its original JPEG form. However, while existing RDH methods adaptively manage the visual distortion caused by embedded data, they often neglect the concurrent increase in file size. In rectifying this oversight, we have designed a new JPEG RDH scheme that addresses all influential metrics during the embedding phase and a dynamic frequency selection strategy with recoverable frequency order after data embedding. The process initiates with a pre-processing phase of blocks and the subsequent selection of frequencies. Utilizing a two-dimensional (2D) mapping strategy, we then compute the visual distortion and file size increment (FSI) for each image block by examining non-zero alternating current (AC) coefficient pairs (NZACPs) and their corresponding run lengths. Finally, we select appropriate block groups based on the influential metrics of each block group and proceed with data embedding by 2D histogram shifting (HS). Extensive experimentation demonstrates how our method's efficiently and consistently outperformed existing techniques with a superior peak signal-to-noise Ratio (PSNR) and optimized FSI.

Hybrid RSA–AES-Based Software-Defined Network to Improve the Security of MANET

Abstract Software-defined networking offers a flexible and programmatically efficient network design. Security in today’s ad hoc mobile wireless network is paramount and incredibly challenging. Software-defined network is used to automatically and dynamically manage and control large network devices, network services, traffic paths, network topology, and packet management (quality of service). Recently different attackers are attacking our data when forwarding from one device to another. Therefore, software-defined networking and a Hybrid Rivest, Shamir, and Adelman (RSA)–Advanced Encryption Standard (AES) cryptography algorithm are needed to establish the concept of software-defined networking in mobile ad hoc networks to improve security and routing efficiency. The proposed Hybrid Cryptography Algorithm (HCA)-Based SDN mainly creates strong detection, prevention, and authentication mechanisms for MANET. The proposed secure data channel throughput increased by 0.4%, and the suggested system latency was 3.6% lower than the Normal MANET. It is already proved that the Hybrid cryptography algorithm also generates a key for security faster than RSA (Rivest, Shamir, and Adelman). The performance of the RSA–AES (hybrid) approach for encrypting and decrypting broad data significantly beats the RSA-Blowfish algorithm. In decrypting files, the hybrid approach (RSA–AES) outperforms the RSA-Blowfish method 11.2 times more efficiently when the file size is 32 kB; however, efficiency is increased by 77.1 times when the file size exceeds 4,096 kB. The experimental result shows that as the file size increases the hybrid RSA–AES solution outperforms RSA when the file is only 145 bytes; however, when the file is 6,460 bytes in size, the efficiency is multiplied by 61.3. As file size increases, RSA is less efficient than the hybrid encryption method. This is more preferred to be implemented for different parts of wireless networks like MANET.

Multi‐chaotic maps and blockchain based image encryption

SummaryThe vast technological developments make data transmission more frequent over networks. So, the data needs to be secured and for that reason, there is a requirement to develop an effective encryption model. This article proposes a novel image encryption model using multi‐chaotic maps and blockchain (MCBE). Chaotic maps have been used in encryption models as chaotic maps have the properties of randomness, and non‐periodicity that get utilized in improving the efficiency of an encryption model. Logistic and tent maps have been employed as multi‐chaotic maps to make the encryption process effective in this work. A logistic map has a simple structure and is easily implementable but has some drawbacks like small keyspace. Keyspace and randomness are enhanced by using a tent map along with a logistic map. The proposed MCBE methodology applies to grayscale or colored images having different file formats and sizes. Initially, in the confusion phase, the permutation of the original image is performed based on a random permutation that changes the original image pixel's position. The encryption model applies multi‐chaotic maps, row‐wise and column‐wise in the diffusion phase to promote the efficiency of the encryption model. Finally, blockchain has been implemented using the SHA‐256 hash function to obtain the encrypted image that enhances the security by increasing the keyspace, to resist brute force attacks. The evaluation performance of the MCBE has been analyzed against various attacks namely statistical attacks, differential attacks, NIST randomness test, noise, and cropping attacks. The evaluated keyspace is which has high key sensitivity with a correlation of encrypted images close to 0. Maximum achieved entropy value of 7.9998, SSIM value between original and encrypted images nearby 0 confirms the dissimilarity. The Number of Pixels Change Rate (NPCR) value of 99.62%, and the value of Unified Average Changed Intensity (UACI) value of 33.54% are within the specified standard range. The calculated correlation coefficient, NPCR, and UACI values have been compared with the existing algorithms, and the results show that the proposed MCBE methodology has better performance than the other state‐of‐the‐art methods. The experimental results indicate that the chaotic ranges generated by multi‐chaotic maps and the SHA‐256 hash function improve the keyspace and security of the encryption model confirming the efficacy of the proposed model MCBE.

PERFORMANCE ANALYSIS OF BUSINESS STARTUP WEBSITE USING GT-METRIX WITH WATERFALL SOFTWARE DEVELOPMENT LIFE CYCLE METHOD

Business ventures began to expand towards technology that initially used conventional sales and payment methods, then developed by young people who saw business opportunities could be simplified in an easy way but had a lot of profit. They utilize computer technology by creating ways to sell through online, namely website media as startup business people. The purpose of the study was to analyze the performance of the "bikinian ibu" website with a http://bikinanibu.lovestoblog.com/ url address. Analysis activities in the form of measuring website speed performance, testing browser timing, testing Tab Structure, Testing Tab Waterfall in diagram form, Testing Tab History, Testing website vitals, Testing Tab Speed. The method used is the Waterfall method by following the following stages: analysis, design or design, coding, testing and maintenance. Based on the results of testing the performance of the "mother-made" website in the GTMetrix section, a Performance analysis score of 93% was obtained, CLS (Cumulative Layout Shift) has not shown good results because it exceeds the maximum standard score on CLS (Cumulative Layout Shift), the structure score covers 89% with the grade A category which means it shows good results. Website loading time also shows good results, website testing looks like there are constraints in the medium and low urgency categories. On the Waterfall tab of the website in the form of waterfall chart results there are 2 404 errors, 20 requests with a total file size of 622KB and 0.96MB for uncompressed files, while the time to load the website is 1.4 seconds. From the results of the Total Page Size of the website is 624KB, while the total page request is obtained as much as 20.

Influence of VF and SOR-Filtering Methods on Tree Height Inversion Using Unmanned Aerial Vehicle LiDAR Data

Forests, as the main body of the terrestrial ecosystem, have long been focal points for accurate structural parameter extraction. Among these parameters, tree height is a fundamental measurement factor that plays an important role in monitoring forest structure and biomass. The emergence of unmanned aerial vehicle light detection and ranging (UAV-LiDAR) technology has provided a strong guarantee of the acquisition of forest tree height parameters. However, UAV-LiDAR point cloud data have problems such as a large volume and data redundancy, and different point cloud data processing methods have different effects. Based on voxel filtering (VF) and statistical outlier removal (SOR)point cloud data processing experimental analysis, this study explored the influence of different filtering methods on the forest tree height inversion efficiency and accuracy. First, the point cloud data processed by VF is significantly better than that of SOR in terms of point cloud number, file size, running time, etc. The number of point clouds for VF decreased by an average of 96.91% compared with the original point clouds. Second, the VF tree height inversion accuracy was better than the tree height inversion data using SOR. The average accuracy of VF was 96.24%, while that of SOR was 94.17%. In summary, VF can effectively reduce data redundancy and improve tree height inversion accuracy.

Effect of Coronal Flaring on Initial Apical File Size Estimation in Curved Canals Using Three Distinct Rotary Instruments: A Comparative In Vitro Study.

The initial size of a root canal is established by progressively introducing K-files according to the increase in the International Organization for Standardization (ISO) size in the apical region. The initial file-fit sensation is caused by coronal interferences rather than always occurring at the apex, as is commonly believed. Flaring the canal at its earliest stages enables the practitioner to accurately assess the size of the canal approaching the apex. This enables more informed judgments on the selection of the master apical file required for shaping and cleaning the apex. The aim of this in vitro study is to examine the impact of cervical flaring on the first estimation of apical file size using three distinct rotary instruments. Sixty-four extracted permanent maxillary first molars with a curvature of between 10⁰ and 20⁰ were chosen. Conventional access openings were made, and the precise length of the canal was determined, leaving it 1 mm short of the apex. The apical fit was deemed to have materialized when the largest file successfully reached the apex, and further progression beyond that depth was unattainable. An initial file that exhibited tactile resistance both before and following expansion at the designated working length (WL) was observed. The initial file that elicited a sensation of being securely attached was affixed using methacrylate into the root canal. A diamond sectioning disc was used to horizontally cut the apical 0.5 mm of the mesiobuccal root. This was done to expose the canal and the instrument at the WL. The uppermost portions were observed using a 3D optical profilometer, and digital photographs were captured for each sample. The occurrence of coronal interferences and the choice of instruments for flaring had a notable impact on the estimation of the initial apical file (IAF) size. The file size frequency was augmented following flaring using various rotary instruments, namely ProTaper, HyFlex CM, and Endoflare. Group 1, which did not undergo preflaring, exhibited the highest disparity of 257.3 ± 54.4. The variation was substantially different (p<0.01) from all the groups that underwent flaring. The use of HyFlex CM (group 3) for preflaring resulted in the smallest average difference (124.4 ± 29.6) between the maximum diameter of the canal at the apex and the diameter of the initial file used. Endoflare (group 4) exhibited the second lowest mean disparity (178.7 ± 46) between the maximum width of the apical root canal and the diameter of the IAF, with the ProTaper group (211 ± 43.5) following closely behind. Nevertheless, there was no statistically significant discrepancy observed in the average differences between groups 2 and 4 (ProTaper and Endoflare groups, respectively). Coronal preflaring significantly contributes to minimizingthe variation between the IAF and the diameter of the apical canal. Prior coronal expansion using rotary files enables a more precise identification of the IAF. The choice of equipment used for flaring affects the estimation of the IAF size.