Tool For Scanning Research Articles

Automatic detection for bioacoustic research: a practical guide from and for biologists and computer scientists.

Recent years have seen a dramatic rise in the use of passive acoustic monitoring (PAM) for biological and ecological applications, and a corresponding increase in the volume of data generated. However, data sets are often becoming so sizable that analysing them manually is increasingly burdensome and unrealistic. Fortunately, we have also seen a corresponding rise in computing power and the capability of machine learning algorithms, which offer the possibility of performing some of the analysis required for PAM automatically. Nonetheless, the field of automatic detection of acoustic events is still in its infancy in biology and ecology. In this review, we examine the trends in bioacoustic PAM applications, and their implications for the burgeoning amount of data that needs to be analysed. We explore the different methods of machine learning and other tools for scanning, analysing, and extracting acoustic events automatically from large volumes of recordings. We then provide a step-by-step practical guide for using automatic detection in bioacoustics. One of the biggest challenges for the greater use of automatic detection in bioacoustics is that there is often a gulf in expertise between the biological sciences and the field of machine learning and computer science. Therefore, this review first presents an overview of the requirements for automatic detection in bioacoustics, intended to familiarise those from a computer science background with the needs of the bioacoustics community, followed by an introduction to the key elements of machine learning and artificial intelligence that a biologist needs to understand to incorporate automatic detection into their research. We then provide a practical guide to building an automatic detection pipeline for bioacoustic data, and conclude with a discussion of possible future directions in this field.

MultiMotif: a generalized tool for scanning and visualization of diverse and distant multiple motifs

multiMotif: a generalized tool for scanning and visualization of diverse and distant multiple motifs

TRUENESS AND PRECISION OF DIFFERENT DIGITAL SCAN SYSTEMS IN A TWO IMPLANT COMPLETE ARCH MODEL: AN IN-VITRO STUDY

Background: One of the major concerns in implant-retained prostheses is their accuracy which plays an essential role in implant success and prosthesis adaptation. Although many contemplates stated the indications and merits of different digital scanner systems, little is identified about their trueness and precision in scanning dental implants of implant-retained prostheses. Objectives: This contemplate aimed to evaluate and compare the trueness and precision of two unalike most recent digital scan systems in a mandibular two-implant complete arch model. Materials and Methods: A completely edentulous mandibular cast was utilized into which two conventional dental implant analogs were drilled in its inter-foramina area from which the distance between the analogs was measured by a caliper (Control). The same space was assessed via scanning the whole assembly 13 scans/each digital scanner system. The final distance of each scan attained from both systems was then compared with the control. The accuracy of each system was assessed in terms of trueness and precision. Results: Slight advancement of the Dof Freedom X5 premium digital scanner system than the Medit T300-T500 dental digital scanner regarding trueness although they were still insignificantly different, as P=0.66. The Medit digital scanner system was significantly better than the Dof Freedom one concerning precision, as P=0.001. Conclusion: The two dental laboratory digital scanner systems employed are reliable tools for scanning and reproducing digital dental records accurately for an implant-supported prosthesis. Furthermore, the Medit dental digital scanner system seemed to be more accurate in terms of precision than the Dof Freedom one.

Documentation and management of complex 3D morphologies through digital technology

Digital technologies offer an effective solution for documenting and managing complex three-dimensional morphologies, particularly in the context of Underground Built Heritage (UBH). Our research explores novel digitization strategies by employing various technological tools for 3D scanning. We focus on a selected case study: the Grotta di San Michele Arcangelo. Range-based techniques using LiDAR-UAV (Light Detection and Ranging set in Unmanned Aerial Vehicles) were used for the cave’s exterior, integrated with SLAM (Simultaneous Localization and Mapping) technology was employed for the cave’s interior and close-range photogrammetry techniques captured intricate wall decorations. The results yielded precise geometric information crucial for subsequent three-dimensional modelling of architectural and natural spaces. Furthermore, these techniques were integrated to enhance information management, facilitate conservation efforts, and update existing documentation. The resulting comprehensive database is an essential tool for understanding, monitoring, and effectively managing these intricate underground environments.

TRIUMPH OF SECURITY : FORTIFYING DIGITAL FORTRESSES WITH TRIPLE GUARD AUTHENTICATION

Abstract : Network security is crucial in today’s interconnected world, and traditional text-based passwords are insufficient. This paper introduces a Three-Level Security system to enhance protection with a multi-tiered approach: Level-1 Login-based Password, Level-2 Graphical Authentication, and Level-3 Image-Based Password. The system ensures authorized access, defines user permissions, and encrypts data. It includes monitoring, rate limiting, regular updates, and penetration testing, using Python-based tools for vulnerability scanning. Triple Guard encrypts data both at rest and in transit, ensuring confidentiality and integrity. It adaptive to emerging threats and vulnerabilities, integrating Python-based security testing tools for vulnerability scanning and code analysis. By providing developers and administrators with a robust and extensible password security solution . Triple Guard encrypts data both at rest and in transit, preserving its confidentiality and integrity. Index Terms :-. Login Password Authentication, Graphical Authentication, Image Authentication, Python, Chatgpt.

A Comprehensive MATLAB based Optical Mark Reader and Database Generation System for the Windows Operating System

The importance of software systems in business cannot be overstated. Often, there are numerous processes involved in developing software solutions, including problem definition, solution design, building, testing, and maintenance. The objective of this study is to propose an optical mark reader (OMR) that is practical, affordable, and compatible with Windows. The OMR can be used to process data in polling places, schools, elections, and other comparable places. It was created especially for grading multiple-choice tests. It may be easily integrated with a multipurpose printer and comes with an updated tool for image scanning and reading. The article also provides a database that generates thorough reports and was built in a soft environment. The paper uses an aptitude test grading system for a university to show how well the system works, and the database successfully creates a detailed report of the student’s data and final results. The system was created utilizing state-of-the-art software, including MATLAB and SQL server.

Research on the algorithm of image feature detection and matching

In-depth research on feature detection technology affects people's modern life. Modern artificial intelligence can act as the eyes of human beings and efficiently filter out effective information from complex pictures. Corner detection has now evolved into a tool for efficient image scanning. People's increasingly stringent requirements for image processing continue to promote the birth of new technologies. Corner detection methods have been improved and perfected, and have experienced detectors such as Harris, FAST, Scalriant Feature Transform (SIFT), Speeded Up Robust Feature (SURF), Binary Robust Invariant Scalable Keypoints (BRISK), KAZE, AKAZE and Oriented FAST and Rotated BRIEF (ORB). In the face of many mainstream detectors, the main research purpose of this paper is to rely on Python and Computer vision to study the detection efficiency of various detectors in different environments. In this experiment, thirteen groups of pictures were selected, and after being flipped, complicated, and blurred respectively, they were detected by different detectors to obtain the results. Finally, by comparing the feature detection points, detection time and other factors, this study found that the ORB detector can be competent in most situations and is currently the fastest and stable feature point detection and extraction algorithm. On the other hand, the BRISK detector can handle highly blurred images more efficiently.

Studies on the Metrological Need and Capabilities of 3D Scanning Technologies

3D scanning technologies are deployed toward developing a digital 3D model for Additive Manufacturing (AM) applications. It collects data, turning it into a 3D model that uses designated 3D printing processes. Many scanners, ranging from low-cost alternatives to professional series that are far more accurate and reliable, are now available to assist in bringing designs to reality. 3D scanning solutions enable the appropriate measurement of 3D physical parts into the virtual world, allowing factory production teams and corporate offices to share critical design information. These techniques are utilized everywhere in the design process, including product design and development, reverse engineering, quality control and quality assurance. The manufacturing sector can decrease costs while accelerating time to market and resolving quality issues. This study investigates the metrological need as per the advancements of 3D scanners. The procedural steps of the 3D scanners, along with specific metrological components and soft tools for 3D scanning, are discussed briefly. Finally, various 3D scanning applications are identified and discussed in detail. Because of the overall relative advantages of these non-contact measurement techniques, 3D metrological tools are crucial for modern production. Almost every sector aims for smaller, more complex components, which are more vulnerable to contamination or injury from even the slightest touch with a probe. The market is driven by global Research and Development (R&D) investment to develop game-changing technologies and solutions. Precision inspection and quality control are significant market drivers for industry progress. Smart factories will have lifetime access to 3D metrological data, allowing them to enhance quality and gain a competitive advantage in the marketplace.

Investigations on the Influence of Subsequent Electron Beam (EB) Remelting on the Microstructure of an Aluminium Nitride Layer Formed on an Aluminium Substrate (Part II)

Nitriding of Al alloys leads to the formation of a thin, hard nitride layer (AlN) on the surface. A subsequent EBR can both eliminate the nitriding-related cavities under the nitride layer and increase the hardness of the substrate without melting or destroying the nitride layer. This paper deals with investigations regarding the influence of the energy/heat input on the microstructure within both the AlN layer and the remelted Al substrate. Of particular interest was the interface between the AlN and the Al substrate, which changed to a transition zone with a depth of approximately 80 µm. A range of high-resolution imaging and analytical tools for both scanning and transmission electron microscopy were used for these investigations. Based on the findings from the microstructural investigations, a schematic model was developed of the processes occurring within the nitride layer and at the interface as a result of remelting.

Development of COVID-19 Detection Smart Doorbell Based on IoT

A unique thermal sensor camera must be utilised to detect a person with covid 19 symptoms. A Coronavirus doorbell has been invented in this research, which can be used to uniquely identify persons using their fingerprints, and they can also be identified for COVID positive. This is an electronic based gadget made with a Raspberry Pi 3, an IR sensor, a Serial 16x2 Serial LCD, a Raspberry Pi camera, and tools for fingerprint scanning. A COVID doorbell has been obtained by combining these tools to detect an infected person based on his temperature. When a person’s temperature exceeds 104 degrees Celsius, it detects it by touching his finger with a finger print sensor, captures an image of the infected person, and alerts the person inside the house with the appropriate message. This system thus has the potential to save human lives from COVID.

Study on Horizon Scanning by Citation Network Analysis and Text Mining: A Focus on Drug Development Related to T Cell Immune Response

Certain innovative technologies applied to medical product development require novel evaluation approaches and/or regulations. Horizon scanning for such technologies will help regulators prepare, allowing earlier access to the product for patients and an improved benefit/risk ratio. This study investigates whether citation network analysis and text mining of scientific papers could be a tool for horizon scanning in the field of immunology, which has developed over a long period, and attempts to grasp the latest research trends. As the result of the analysis, the academic landscape of the immunology field was identified by classifying 90,450 papers (obtained from PubMED) containing the keyword “immune* and t lymph*” into 38 clusters. The clustering was indicative of the research landscape of the immunology field. To confirm this, immune checkpoint inhibitors were used as a retrospective test topic of therapeutics with new mechanisms of action. Retrospective clustering around immune checkpoint inhibitors was found, supporting this approach. The analysis of the research trends over the last 3 to 5 years in this field revealed several candidate topics, including ARID1A gene mutation, CD300e, and tissue resident memory T cells, which shows notable progress and should be monitored for future possible product development. Our results have demonstrated the possibility that citation network analysis and text mining of scientific papers can be a useful objective tool for horizon scanning of life science fields such as immunology.

Study on Horizon Scanning with a Focus on the Development of AI-Based Medical Products: Citation Network Analysis

Horizon scanning for innovative technologies that might be applied to medical products and requires new assessment approaches to prepare regulators, allowing earlier access to the product for patients and an improved benefit/risk ratio. The purpose of this study is to confirm that citation network analysis and text mining for bibliographic information analysis can be used for horizon scanning of the rapidly developing field of AI-based medical technologies and extract the latest research trend information from the field. We classified 119,553 publications obtained from SCI constructed with the keywords “conventional,” “machine-learning,” or “deep-learning" and grouped them into 36 clusters, which demonstrated the academic landscape of AI applications. We also confirmed that one or two close clusters included the key articles on AI-based medical image analysis, suggesting that clusters specific to the technology were appropriately formed. Significant research progress could be detected as a quick increase in constituent papers and the number of citations of hub papers in the cluster. Then we tracked recent research trends by re-analyzing “young” clusters based on the average publication year of the constituent papers of each cluster. The latest topics in AI-based medical technologies include electrocardiograms and electroencephalograms (ECG/EEG), human activity recognition, natural language processing of clinical records, and drug discovery. We could detect rapid increase in research activity of AI-based ECG/EEG a few years prior to the issuance of the draft guidance by US-FDA. Our study showed that a citation network analysis and text mining of scientific papers can be a useful objective tool for horizon scanning of rapidly developing AI-based medical technologies.

Automatic Segmentation of Dental Root Canal and Merging with Crown Shape.

In this paper, machine learning approaches are proposed to support dental researchers and clinicians to study the shape and position of dental crowns and roots, by implementing a Patient Specific Classification and Prediction tool that includes RootCanalSeg and DentalModelSeg algorithms and then merges the output of these tools for intraoral scanning and volumetric dental imaging. RootCanalSeg combines image processing and machine learning approaches to automatically segment the root canals of the lower and upper jaws from large datasets, providing clinical information on tooth long axis for orthodontics, endodontics, prosthodontic and restorative dentistry procedures. DentalModelSeg includes segmenting the teeth from the crown shape to provide clinical information on each individual tooth. The merging algorithm then allows users to integrate dental models for quantitative assessments. Precision in dentistry has been mainly driven by dental crown surface characteristics, but information on tooth root morphology and position is important for successful root canal preparation, pulp regeneration, planning of orthodontic movement, restorative and implant dentistry. In this paper we propose a patient specific classification and prediction of dental root canal and crown shape analysis workflow that employs image processing and machine learning methods to analyze crown surfaces, obtained by intraoral scanners, and three-dimensional volumetric images of the jaws and teeth root canals, obtained by cone beam computed tomography (CBCT).

Wall shear stress mapping for human femoral artery based on ultrafast ultrasound vector Doppler estimations.

Wall shear stress (WSS), a type of friction exerted on the artery wall by flowing blood, is considered a crucial factor in atherosclerotic plaque development. Currently, achieving a reliable WSS mapping of an artery noninvasively by using existing imaging modalities is still challenging. In this study, a WSS mapping based on vector Doppler flow velocity estimation was proposed to measure the dynamic WSS on the human femoral artery. Because ultrafast ultrasound imaging was used here, flow-enhanced imaging was also performed to observe the moving blood flow condition. The performance of WSS mapping was verified using both straight (8mm in diameter) and stenosis (70% of stenosis) phantoms under a pulsatile flow condition. A human study was conducted from five healthy volunteers. Experimental results demonstrated that the WSS estimation was close to the standard value that was obtained from maximum velocity estimation in straight phantom experiments. In a stenosis phantom experiment, a low WSS region was observed at a site downstream of an obstruction, which is a high-risk area for plaque formation. Dynamic WSS mapping was accomplished in measurement in the femoral artery bifurcation. In measurements, the time-averaged WSS of the common femoral artery, superficial femoral artery, and deep femoral artery was 0.52± 0.19, 0.44 ± 0.21, and 0.29 ± 0.16Pa, respectively, for the anterior wall and 0.29 ± 0.11, 0.54 ± 0.24, and 0.23 ± 0.10Pa, respectively, for the posterior wall. All results indicated that WSS mapping has the potential to be a useful tool for vessel duplex scanning in the future.

RetroScan: An Easy-to-Use Pipeline for Retrocopy Annotation and Visualization.

Retrocopies, which are considered “junk genes,” are occasionally formed via the insertion of reverse-transcribed mRNAs at new positions in the genome. However, an increasing number of recent studies have shown that some retrocopies exhibit new biological functions and may contribute to genome evolution. Hence, the identification of retrocopies has become very meaningful for studying gene duplication and new gene generation. Current pipelines identify retrocopies through complex operations using alignment programs and filter scripts in a step-by-step manner. Therefore, there is an urgent need for a simple and convenient retrocopy annotation tool. Here, we report the development of RetroScan, a publicly available and easy-to-use tool for scanning, annotating and displaying retrocopies, consisting of two components: an analysis pipeline and a visual interface. The pipeline integrates a series of bioinformatics software programs and scripts for identifying retrocopies in just one line of command. Compared with previous methods, RetroScan increases accuracy and reduces false-positive results. We also provide a Shiny app for visualization. It displays information on retrocopies and their parental genes that can be used for the study of retrocopy structure and evolution. RetroScan is available at https://github.com/Vicky123wzy/RetroScan.

ECOA-6. Genomic and transcriptomic analyses reveal diverse mechanisms responsible for deregulation of epigenetic enzyme/modifier expression in glioblastoma

Malignant gliomas represent over 70% of primary brain tumors and the most deadly is glioblastoma (GBM, WHO grade IV), due to frequent dysfunctions of tumor suppressors or/and oncogenes. Recent whole genome studies of gliomas demonstrated that besides genetic alterations, epigenetic dysfunctions contribute to tumor development and progression. Alterations in genes encoding epigenetic enzyme/protein or aberrations in epigenetic modification pattern have been found in gliomas of lower grade, yet no epigenetic driver was identified in GBM. We sought to identify different mechanisms driving aberrant expression of epigenetic genes in GBM.We analyzed gene expression and coding/non-coding regions of 96 major epigenetic enzymes and chromatin modifiers in 28 GBMs, 23 benign gliomas (juvenile pilocytic astrocytomas, JPAs, WHO grade I) and 7 normal brain samples. We found a profound and global down-regulation of expression of most tested epigenetic enzymes and modifiers in GBMs when compared to normal brains and JPAs. For some genes changes in mRNA level correlated with newly identified single nucleotide variants within non-coding regulatory regions. To find a common denominator responsible for the coordinated down-regulation of expression of epigenetic enzymes/modifiers, we employed PWMEnrich tool for DNA motif scanning and enrichment analysis. Among others, we discovered the presence of high affinity motifs for the E2F1/E2F4 transcription factors, within the promoters of the epigenetic enzyme/modifier encoding genes. Knockdown of the E2F1/E2F4 expression affected the expression of a set of epigenetic enzymes/modifiers. Altogether, our results reveal a novel epigenetic-related pathway by which E2F1/E2F4 factors contribute to glioma pathogenesis and indicate novel targets for glioma therapy.Supported by a National Science Centre grant 2013/09/B/NZ3/01402 (MM).

Finding exceedance locations in a large spatial database using nonparametric regression

In the era of big data analysis, it is of interest to develop diagnostic tools for preliminary scanning of large spatial databases. One problem is identification of locations where certain characteristics exceed a given norm, e.g. timber volume or mean tree diameter exceeding a user-defined threshold. Some of the challenges are, large size of the database, randomness, complex shape of the spatial mean surface, heterogeneity and others. In a step-by-step procedure, we propose a method for achieving this for large spatial data sets. For illustration, we work through a simulated spatial data set as well as a forest inventory data set from Alaska (source: USDA Forest Services). Working within the framework of nonparametric regression modeling, the proposed method can attain a high degree of flexibility regarding the shape of the spatial mean surface. Taking advantage of the large sample size, we also provide asymptotic formulas that are easy to implement in any statistical software.

Multilayered non‐uniform atomic force microscope piezoelectric microcantilever control and vibration analysis considering different excitation based on the modified couple stress theory

Atomic force microscope (AFM) is one of the most powerful tools for surface scanning, force measurement, and nano-manipulation. To improve its performance, vibration and control of AFM micro-cantilever (MC) should be studied. Hysteresis, as an undesired phenomenon affecting vibration amplitude and phase, is also another important issue to be examined. In this paper, vibration analysis and control of a ZnO non-uniform multi-layered piezoelectric MC has been investigated in non-contact mode. A modified couple stress theory has been used to obtain the strain energy for modeling the MC. In order to control the amplitude, a sliding mode controller (SMC) has been utilized on AFM, due to its application in uncertain and nonlinear systems. For applying the control signal, two methods of piezo and base actuation are studied. The results are compared with proportional integral derivative (PID) control method and it is demonstrated that SMC method reduces the control input close to the surface and increases the accuracy near the surface. In addition to MC control, hysteresis amplitude and phase differences are investigated by applying the Prandtl-Ishlinskii model. Also, surface topography is studied with hysteresis. The simulations show backward phase difference and an increase in amplitude, accordingly.

40-MHz high-frequency vector Doppler imaging for superficial venous valve flow estimation.

Doppler ultrasound imaging has been used widely for diagnosing vascular diseases. Recently, vector Doppler imaging (VDI) has been proposed for visualizing the blood flow in all directions to yield more detailed information for estimating flow conditions. Increasing the resolution of VDI is important for the structural mapping of superficial vessels with microstructure. However, VDI that operates under a high-frequency ultrasound (HFUS; >30MHz) is rare. In this study, a 40-MHz high-frequency VDI (HFVDI) based on ultrafast ultrasound imaging was developed to obtain the vector information of blood flow around the superficial venous valve. The use of HFUS imaging system causes an overload of data acquisition easily. In order to provide sufficient recording time, the frame rate should be reduced. Because the aliasing problem worsens due to a low frame rate when operating Doppler imaging, phase-unwrapping processing methods based on spatial and temporal continuities were applied. Flow phantom experiments were performed to validate the accuracy. In vivo experiments were performed on the valve of superficial veins of healthy volunteers. The experimental results from the phantom study indicated that the error of velocity estimation was <10% in most cases. Dynamic changes of valve movements and flow conditions (including velocity profiles and vector) were observed. Because of the high resolution of HFVDI, the jet and vortex phenomena were observed between the leaflets and in the sinus pocket, respectively. Flow velocities ranging from 2 to 15mm/s were measured at different locations around the venous valve during the opening and closing phases. All the results indicated that HFVDI has the potential to be a useful tool for vessel duplex scanning.

Real measurement of optimal access point localizations

The widely applied location-based services require a high standard for positioning technology. With the development of the wireless communication technology, the positioning services based on Wi-Fi are increasingly demanded. To understand the positioning accuracy limits under a certain given Access Point topology and to be able to make design recommendations. This paper proposed a method for proper deployment of AP devices on the building of the electrical department in the university of technology and computing the measurements of the Received Signal Strength (RSS). Received Signal Strength measurement was obtained from different received points located within the targeted building. Many software can be used for the measuring of RSS values. In our work, it has been used Net Spot pro software. Net Spot is a software tool for wireless network assessment, scanning, and surveys, analyzing Wi-Fi coverage and performance. RSS reading were measured for four directions (North-South-East – West). It should mention that each RSS measurement obtained per each direction, is actually the average of 4 RSS measurement samples. This trend is to provide more accurate results than a single measurement Floor layout has been designed and imported to the software and used to allocate the measurements in the exact received point locations. The objective of this paper is to achieve full coverage area with less number of AP devices and reduce the total implementation costs.