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 Comprehensive Formalization of AADL with Behavior Annex

In safety-critical fields, architectural languages such as AADL (Architecture Analysis and Design Language) have been playing an important role, and the analysis of the languages and systems designed by them is a challenging research topic. At present, a formal method has become one of the main practices in software engineering for strict analysis, and it has been applied on the tools of formalization and analysis. The formal method can be used to find and resolve the problems early by describing the system with precise semantics and validating the system model. This article studies the comprehensive formal specification and verification of AADL with Behavior annex by the formal method. The presentation of this specification and semantics is the aim of this article, and the work is illustrated with an ARINC653 model case study in Isabelle/HOL.

4.1 Strain-Promoted Azide–Alkyne Cycloaddition (SPAAC): Background, Substrate Preparation, and Reactivity

This chapter discusses the creative synthetic approaches to azides and cycloalkynes, provides the rationale for controlling SPAAC reactivity through tuning cycloalkyne and azide backbone modifications, and highlights research on nitrone cycloadditions with cycloalkynes. This synthetic and knowledge toolset will help in the design of better cycloalkynes and their partners to answer challenging research questions and aid the development of new applications.

Selective C2+ Alcohol Synthesis from CO2 Hydrogenation via Reaction-Coupling Strategy

Higher alcohol synthesis (HAS) from non-petroleum carbon resources (a mixture of H2 and CO2) is an attractive but challenging research target. This reaction still suffers from poor higher alcohol (HA)...

A Dynamic Modeling Method for the Bi-Directional Pneumatic Actuator Using Dynamic Equilibrium Equation

Dynamic modeling of soft pneumatic actuators are a challenging research field. In this paper, a dynamic modeling method used for a bi-directionaly soft pneumatic actuator with symmetrical chambers is proposed. In this dynamic model, the effect of uninflated rubber block on bending deformation is considered. The errors resulting from the proposed dynamic equilibrium equation are analyzed, and a compensation method for the dynamic equilibrium equation is proposed. The equation can be solved quickly after simplification. The results show that the proposed dynamic model can describe the motion process of the bi-directional pneumatic actuator effectively.

A Review about the Sustainability of Pit Lakes as a Rehabilitation Factor after Mine Closure

At the end of surface mining activities, the remnant voids are of great concern regarding rehabilitating the final open pits. The investigation of the sustainability of pit lakes in post-mining regions constitutes a challenging research problem. This paper aims to highlight the effectiveness of pit lakes as a rehabilitation factor. In this framework, several cases worldwide and in Greece were examined in detail and evaluated. The results indicate that mine pit lakes must be evaluated as dynamic systems, natural or artificial, which demand rational mine water management to ensure their sustainability. Specifically in Greece, it is of great importance during the transition to the post-lignite era.

A fully homomorphism encryption scheme based on LWR

We believe that isomorphic encryption technology can provide strong technical support for users’ privacy protection in a distributed computing environment. There are three types of quasi-homomorphism encryption methods: partial homomorphism encryption, shallow homomorphism encryption, and full homomorphism encryption. homomorphism encryption methods have important applications for ciphertext data computing in distributed computing environments, such as secure cloud computing, fee computing, and remote file storage ciphertext retrieval. It is pointed out that the construction of the homomorphism encryption method is still in the theoretical stage and cannot be used for real high-density data calculation problems. How to design (natural) isomorphic encryption schemes according to algebraic systems is still a challenging research. This question discusses the problem of Learning With Rounding (LWR). Based on the difficulty of LWR, multiple IDs, and attribute categories, a fully homomorphism encryption method corresponding to an ID is proposed. In this paper, in order to reflect the effectiveness of the proposed method, we propose a homomorphism encryption technology based on the password search attribute.

Development of Leakage Detection Model and Its Application for Water Distribution Networks Using RNN-LSTM

With the advent of the 4th Industrial Revolution, advanced measurement infrastructure and utilization technologies are being noticeably introduced into the water supply system to store and utilize measurement data. From this perspective, the leak detection technology in water supply networks is becoming increasingly vital to sustainable water resource management and the clean water supply worldwide. In particular, leakage detection of buried pipelines is rated as a very challenging research topic given the current level of technology. However, leakage in buried underground pipelines is rated as a very challenging research topic given the current level of technology. Therefore, a data-driven leak detection model was developed through this study using deep learning technology based on inflow meter data. Multiple threshold-based models were applied to reduce the RNN-LSTM (Recurrent Neural Networks–Long Short-Term Memory models) deep learning and false prediction range, which is programmed in conjunction with the Python language and Google Colaboratory (a big data analysis tool). The developed model consists of flow pattern shape extraction, RNN-LSTM-based flow prediction, and threshold setting modules. The developed model was applied to the actual leakage accident data, followed by the performance evaluation. As a result, the leak was recognized at most points immediately after the accident. The performance of leak detection was evaluated by a Confusion matrix and showed more than 90% accuracy at all points except singularities. Therefore, the developed model can be used as a critical software technology to proactively identify various at present with smart water infrastructure being introduced. In addition, this model is highly scalable as it can consider various operational situations based on the expert system, and it can also efficiently reflect the results of pipe network analysis across different scenarios.

The challenge of quality management in crowdsourced translation: the case of the NGO Translators Without Borders

The rise of machine translation and translation memories along with the technologies of the Web 2.0 have brought about new flavours and workflows, setting new challenging research pathways for translation studies. Emerging crowdsourcing-based models have been presented as de facto mainstream approaches in the translation industry. Therefore, exploring the newborn approaches and processes is a priority for translation studies for better insights and further understanding of relevant impacts that may reach the stage of deprofessionalizing the discipline and marginalizing the profession. To pursue this question, the present paper explores a unique and interesting model of translation that is both crowdsourced and collaborative, the non-profit organization Translators Without Borders or TWB. TWB does not only resort to crowdsourcing to provide humanitarian translation services on pro-bono basis but also maintains a global network of volunteers and deploys a fully fledged environment for translation management as well as quality assurance and control. This paper demonstrates the array of processes adopted by TWB to manage quality and the myriad of challenges it presents. Through TWB model study, this paper investigates the way various theoretical concepts are confronting the industry realities and implications and examines the extent of dynamicity and tolerance thresholds in the application of such concepts.

Advances in multiscale modeling for novel and emerging technologies

Computational multiscale modeling encompasses a wide range of end-products and a great number of technological applications. This paper provides an overview of the computational multiscale modeling approach based on utilization of MBN Explorer and MBN Studio software packages, the universal and powerful tools for computational modeling in different areas of challenging research arising in connection with the development of novel and emerging technologies. Three illustrative case studies of multiscale modeling are reviewed in relation to: (i) the development of novel sources of monochromatic high-energy radiation based on the crystalline undulators, (ii) controlled fabrication of nanostructures using the focused electron-beam induced deposition, and (iii) ion-beam cancer therapy. These examples illustrate the key algorithms and unique methodologies implemented in the software. Graphic abstract draftps