Computer Vision Based Virtual Sketch Using Detection

In todays world during this pandemic situation Online Learning is the only source where one could learn. Online learning makes students more curious about the knowledge and so they decide their learning path . But considering the academics as they have to pass the course or exam given, they need to take time to study, and have to be disciplined about their dedication. And there are many barriers for Online learning as well. Students are lowering their grasping power the reason for this is that each and every student was used to rely on their teacher and offline classes. Virtual writing and controlling system is challenging research areas in field of image processing and pattern recognition in the recent years. It contributes extremely to the advancement of an automation process and can improve the interface between man and machine in numerous applications. Several research works have been focusing on new techniques and methods that would reduce the processing time while providing higher recognition accuracy. Given the real time webcam data, this jambord like python application uses OpenCV library to track an object-of-interest (a human palm/finger in this case) and allows the user to draw bymoving the finger, which makes it both awesome and interesting to draw simple thing. Keyword: Detection, Handlandmark , Keypoints, Computer vision, OpenCV

A Survey on Malware detection using ML

This Malware detection is a field of computer security that deals with the study and prevention of malicious software. It is not the only way to defend a company against a cyber- attack. In order to be effective, companies should analyse their risk and identify the vulnerabilities. In this paper, we will examine different techniques used to detect computer malware and malicious websites as well as future directives in this area of study and also, we will discuss the growth in computer malware and how traditional methods of detection are being replaced by innovative techniques like behavioural-based model and Signature-based model. Future directives involve developing better security products in order to fight against cyber fraud which is on a rise in recent years especially in Asia Pacific region. With this increase in cyber frauds and other malicious activities, traditional methods are not enough to block computers from it as this method has many drawbacks. In order to tackle these issues, researchers have been developing new techniques such as heuristic analysis, static & dynamic analysis which can detect more than 90% of malware samples without any false positives or negatives. Keywords: Behaviour-based approach, Dynamic analysis, Heuristic, Malware, Ransomware, Signature-based model, Static analysis, Vulnerability.

Developing Digital Photomicroscopy

(1) The need for efficient ways of recording and presenting multicolour immunohistochemistry images in a pioneering laboratory developing new techniques motivated a move away from photography to electronic and ultimately digital photomicroscopy. (2) Initially broadcast quality analogue cameras were used in the absence of practical digital cameras. This allowed the development of digital image processing, storage and presentation. (3) As early adopters of digital cameras, their advantages and limitations were recognised in implementation. (4) The adoption of immunofluorescence for multiprobe detection prompted further developments, particularly a critical approach to probe colocalization. (5) Subsequently, whole-slide scanning was implemented, greatly enhancing histology for diagnosis, research and teaching.

A deep learning model for breast ductal carcinoma in situ classification in whole slide images

The pathological differential diagnosis between breast ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) is of pivotal importance for determining optimum cancer treatment(s) and clinical outcomes. Since conventional diagnosis by pathologists using microscopes is limited in terms of human resources, it is necessary to develop new techniques that can rapidly and accurately diagnose large numbers of histopathological specimens. Computational pathology tools which can assist pathologists in detecting and classifying DCIS and IDC from whole slide images (WSIs) would be of great benefit for routine pathological diagnosis. In this paper, we trained deep learning models capable of classifying biopsy and surgical histopathological WSIs into DCIS, IDC, and benign. We evaluated the models on two independent test sets (n=1,382, n=548), achieving ROC areas under the curves (AUCs) up to 0.960 and 0.977 for DCIS and IDC, respectively.

The Computational Thematic Analysis Toolkit

As online communities have grown, Computational Social Science has rapidly developed new techniques to study them. However, these techniques require researchers to become experts in a wide variety of tools in addition to qualitative and computational research methods. Studying online communities also requires researchers to constantly navigate highly contextual ethical and transparency considerations when engaging with data, such as respecting their members' privacy when discussing sensitive or stigmatized topics. To overcome these challenges, we developed the Computational Thematic Analysis Toolkit, a modular software package that supports analysis of online communities by combining aspects of reflexive thematic analysis with computational techniques. Our toolkit demonstrates how common analysis tasks like data collection, cleaning and filtering, modelling and sampling, and coding can be implemented within a single visual interface, and how that interface can encourage researchers to manage ethical and transparency considerations throughout their research process.

Localization of irritative zones in epilepsy with thermochromic silicone

Background: During epilepsy surgery, the gold standard to identify irritative zones (IZ) is electrocorticography (ECoG); however, new techniques are being developed to detect IZ in epilepsy surgery and in neurosurgery in general, such as infrared thermography mapping (ITM), and the use of thermosensitive/thermochromic materials. Methods: In a cohort study of consecutive patients with focal drug-resistant epilepsy of the temporal lobe treated with surgery, we evaluated possible adverse effects to the transient placement of a thermochromic/thermosensitive silicone (TTS) on the cerebral cortex and their postoperative evolution. Furthermore, we compared the precision of TTS for detecting cortical IZ against the gold standard ECoG and with ITM, as proof of concept. Results: We included 10 consecutive patients, 6 women (60%) and 4 men (40%). Age ranges from 15 to 56 years, mean 33.2 years. All were treated with unilateral temporal functional lobectomy. The mean hospital stay was 4 days. There were no immediate or late complications associated with the use of any of the modalities described. In the 10 patients, we obtained consistency in locating the IZ with ECoG, ITM, and the TTS. Conclusion: The TTS demonstrated biosecurity in this series. The accuracy of the TTS to locate IZ was similar to that of ECoG and ITM in this study. More extensive studies are required to determine its sensitivity and specificity.

How academic sabbaticals used and how they contribute to research – a small-scale study of the University of Cambridge using interviews and analysis of administrative data

Background: Academic sabbaticals are seen as an important aspect of academic life and require considerable resources, however, little research has been done into how they are used and whether their effects can be measured. We explored these issues at the University of Cambridge. Methods: A mixed method approach including 24 interviews with academics, eight interviews with administrators; alongside analysis of administrative and publication data between 2010 and 2019. Results: Academics underline the importance of sabbaticals in providing uninterrupted time for research that is used to think, explore new ideas, master new techniques, develop new collaborations, draw together previous work, set work in a wider context, and provide personal discretion in research direction. They also highlight sabbaticals’ contributions in allowing the beneficial effects of combining teaching and research, while mitigating some of the disadvantages. However, it is difficult to detect the effect of sabbaticals on publications using a time series approach. Conclusions: Sabbaticals provide manifold contributions to academic research at the University of Cambridge; however, detecting and quantifying this contribution, and extending these findings requires wider and more detailed investigation.

Laser Reconstruction of Spinal Discs Experiments and Clinic

Degenerative disease of the intervertebral discs (DDD) is currently a serious problem facing the world community. The surgical methods and conservative therapy used today, unfortunately, do not stop the pathological process, but serve as a palliative method that temporarily relieves pain and improves the patient’s quality of life. Therefore, at present, there is an active search for new methods of treating DDD. Among new techniques of treatment, biological methods, and minimally invasive surgery, including the use of laser radiation, which, depending on the laser parameters, can cause ablative or modifying effects on the disc tissue, have acquired considerable interest. Here, we analyze a new approach to solving the DDD problem: laser tissue modification. This review of publications is focused on the studies of the physicochemical foundations and clinical applications of a new method of laser reconstruction of intervertebral discs. Thermomechanical action of laser radiation modifies tissue and leads to its regeneration as well as to a long-term restoration of disc functions, elimination of pain and the return of patients to normal life.

Phylogeny and age of cockroaches: a reanalysis of mitogenomes with selective fossil calibrations

In spite of big data and new techniques, the phylogeny and timing of cockroaches remain in dispute. Apart from sequencing more species, an alternative way to improve the phylogenetic inference and time estimation is to improve the quality of data, calibrations and analytical procedure. This study emphasizes the completeness of data, the reliability of genes (judged via alignment ambiguity and substitution saturation), and the justification for fossil calibrations. Based on published mitochondrial genomes, the Bayesian phylogeny of cockroaches and termites is recovered as: Corydiinae + (((Cryptocercidae + Isoptera) + ((Anaplectidae + Lamproblattidae) + (Tryonicidae + Blattidae))) + (Pseudophyllodromiinae + (Ectobiinae + (Blattellinae + Blaberidae)))). With two fossil calibrations, namely, Valditermes brenanae and Piniblattella yixianensis, this study dates the crown Dictyoptera to early Jurassic, and crown Blattodea to middle Jurassic. Using the ambiguous ‘roachoid’ fossils to calibrate Dictyoptera+sister pushes these times back to Permian and Triassic. This study also shows that appropriate fossil calibrations are rarer than considered in previous studies.