Reviewerly/exHarmony huggingface dataset:
Automated Design of Realistic Contingencies for Big Data Generation

The work proposes an algorithm for big data generation based on realistic selection of a set of contingencies for power systems described by undirected graphs. Every contingency is created by eliminating a certain number of elements in the system represented by graph edges. The number of elements as well as the distance between elements of the contingency is randomly selected according to a geometric probability distributions based on historical data. The duration of a fault that starts the contingency as well as the time intervals between elements of the contingency are chosen by sampling from a gamma distribution. In addition, the absence of islands in the system is assessed by analyzing the connectedness of the graph with deleted edges, which is quantified by computing the number of zero eigenvalues of the Laplacian matrix of the resulting graphs. The algorithm is validated on the Nordic 44-bus power system.
Introduction to the Special Issue on Deep Structured Learning for Natural Language Processing, Part 3

introduction Introduction to the Special Issue on Deep Structured Learning for Natural Language Processing, Part 3 Share on Editors: Gunasekaran Manogaran View Profile , Hassan Qudrat-Ullah View Profile , Qin Xin View Profile Authors Info & Claims ACM Transactions on Asian and Low-Resource Language Information ProcessingVolume 20Issue 5September 2021 Article No.: 72epp 1–3https://doi.org/10.1145/3476464Published:31 August 2021 0citation11DownloadsMetricsTotal Citations0Total Downloads11Last 12 Months11Last 6 weeks8 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Citizen Unique ID Based Real Time Face Recognition for Surveillance and National Security

Provision of home security services has become an integral part of our lives in today’s technological society where attackers usually have all the necessary means and resources at their disposal. Face Recognition is producing gigantic enthusiasm because of government worries about character the executives and worldwide fear based oppressor movement. One aspiration of Intelligent CCTV is to help counteract fear based oppression and a key innovation is solid face acknowledgment. The movement discovery module is dependable to decide the degree of action while the face identification module separates between approved individuals and interlopers. Our system is better than many proposed systems as it combines both motion detection and face recognition in a single system. Our framework has three noteworthy segments containing: 1) a Viola-Jones face discovery module 2) a Pose Normalization Module to evaluate facial posture and make up for extraordinary posture points 3) Adaptive Principal Component Analysis to perceive the standardized appearances.
Optical Information Processing with Noise-Resistant Entangled Topological States

Linear-optical photonic quantum walks are used to jointly entangle polarization and winding number. This joint entanglement allows polarization entanglement-based quantum information processing tasks to be performed with high degree or error protection.
Research on the Influence of Urban-rural Dual Structure on the Social Mobility Function of Rural Education — Based on the Empirical Investigation of the Loss of Rural Junior High School Students in S City, Hubei Province

Based on the empirical investigation of the loss of rural junior high school students in S City, Hubei Province, this article explores the weakening of the social mobility function of rural education under the dual structure of urban and rural areas, and points out the deep-seated reasons — the urban-centric orientation of the national education system under the dual urban-rural structure. At the same time, the article reveals the harm of the weakening of the social mobility function of rural education under the urban-rural dual structure.
The Future of Internet of Things for Anomalies Detection using Thermography

Abnormal temperature of human body is a natural extensive indicator of illness.Infrared thermography (IRT) is a fast, non-invasive, non-contact and passive substitution to ordinary medical thermometers for monitoring and observation human body temperature.Aside from, IRT is able to chart body surface heat remotely.Last five decades testified a stationary development in thermal imaging cameras utilization to obtain relations between the thermal physiology and surface temperature.IRT has effectively used in diagnosis and detection of breast cancer, diabetes neuropathy and peripheral vascular disorders.It has been employed to detect issues related to gynecology, dermatology, heart, neonatal physiology, and brain imaging.With the advent of modern infrared cameras, data acquisition and processing techniques, it is now possible to have real time high resolution thermographic images, which is likely to surge further research in this field.The emergent technology known as the Internet of Things (IoT) has guided practitioners, physicians and researchers to design innovative solutions in different environments, particularly in medical and healthcare using smart sensors, computer networks and a remote server.This paper aims to propose IoT-enabled medical system enables diagnostics and detection for several medical anomalies remotely; in real-time and simultaneous depend on combination of IoT and Thermal Infrared imaging techniques.It will detect and diagnostics any abnormal and alert the user through IoT remotely and in real-time.
A Fuzzy Based Analysis of Software Confidentiality at Specific Stage

Mostly software security flaws are most important for the customers and industry. Assessing software security is necessary to reduce faults. Various quantification methods are available include fault, errors, and vulnerabilities from various perspectives. It is a very difficult task to quantify security through a model. Experts develop a new innovative idea or constructive way of evaluating security attributes such as confidentiality. In this paper, the attention that how reduces the fault during the uses of a confidentiality environment. Experts evaluate the literature review with limitations and various quantification techniques that can develop a model. The proposed model uses fuzzy techniques to correlate their parameters with the software metric sat design level. In the developed model, one can generate the surface boundary with parameters and given the complete index value of the confidentiality index.
Instructional Programs

Higher Education AbstractsVolume 55, Issue 3 p. 265-271 INSTRUCTIONAL PROGRAMS Instructional Programs First published: 30 July 2020 https://doi.org/10.1111/hea.28_12154Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Volume55, Issue3July 2020Pages 265-271 RelatedInformation
Hyperledger Sawtooth Blockchain-Iot E-Provenance Platform for Pharmaceuticals

This paper investigates the Blockchain traceability framework necessary to develop supply chain application for pharmaceuticals, particularly for life saving drugs which need special logistic conditions. The thorough knowledge of the application specific design assists in the development phase. A solution framework has been proposed for the e-provenance platform for medicines addressing the issue of data streaming between the IoT and the Sawtooth Blockchain unit. A distinct three layered Blockchain-IoT architecture presented, is well suited for this design application. A classification of the Assets in this context distinguishes the properties of each asset type. The pharmaceutical supply chain flow indicates the modules to be deployed along with the transaction between the concerned parties. The application specific system design presents the platform requirements of both the IoT data acquisition and Blockchain data processing units. The theme of the paper namely provenance, can be realized only after investigating the data payload structure that distinguishes the ownership of the IoT sensors and clients namely manufacturer, distributor, retailer and consumer. The overview of the Docker containers illustrates the programming requirements for the specific application, giving the deployment needs at the application side. Finally, application deployment methodology indicates the Blockchain IoT designer, which software modules and hardware components are required to develop the design.
Hopping Rover Navigation Method for Rugged Environments

In this paper a navigation method is presented for space exploration robots using hopping motion in environments with large elevation differences. A monocular camera system is used to reconstruct the flight trajectory and environment around the robot using Structure from Motion while traveling. The created environmental point cloud is projected to 2D to create a variable resolution image and image processing is used to find the most suitable position for the next landing based on normals with the help of gradient maps and error estimation. The method is evaluated in a simulation environment against the previously used protrusion based method to show that the proposed system can extend the operation of the robot to terrains with large elevation differences while still successfully avoid obstacles and dangerous areas.
Bilateral multi-issue negotiation of execution contexts by proactive document agents

A proactive document can react to its actual environment by autonomously selecting and performing actions integrated into its body and interact with its user. When migrating over a network of execution devices it may encounter diverse execution contexts, each one set up according to temporal characteristics of a receiving device and preferences of its owner. A concept to augment proactive documents with negotiation capability is proposed - to make them responsive to such dynamically changing contexts, and implemented in a system, where they can migrate as attachments to e-mail messages, owing to a dedicated e-mail client capable of handling them. Negotiation is based on a simple game-theoretic mechanism to minimise computation load on execution devices. Four negotiation algorithms are proposed and two of them evaluated in more detail in a series of experiments, when respectively, negotiating parties do not or do have knowledge on past encounters and negotiated contracts.
Real Time Attendance System using Convolutional Neural Networks(CNN)

The management of the attendance can be an incredible weight on the instructors in the event that it is completed in registers. Determining this issue, keen and automatic attendance marking system by using the executive’s framework is being used. In any case, verification is a significant problem in this framework. Brilliant attendance framework is implemented commonly along with the assistance of soft biometrics. Acknowledgment of face is one of the updated biometric techniques this framework got to be enhanced. Being a principle element of biometric confirmation, facial acknowledgment feature has become most utilized enormously in a few such applications, similar to video observing and surveillance-based CCTV film framework, a connection between PC and people and admittance frameworks existing inside and in network security. By using this structure, the issue present in along with intermediaries, understudies also have been checking on the present despite the fact that they are not physically present can without much of a stretch be illuminated. The primary usage steps utilized regarding this sort of framework are facial discovery and perceiving the distinguished the different face of the people. This term paper recommends a perfect model for actualizing a computerized attendance the board framework in order to make understudies for a class by utilizing the procedure of acknowledgment-based face detection procedure, by means of utilizing Convolutional Neural Network (CNN), Max pooling.
Lower Bounds for Summaries

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Text to Speech Synthesis using Fraction Based Waveform Concatenation and Optimal Coupling Smoothing Technique

Text to Speech System is a Speech Synthesis application that converts a text to speech. The current project focuses on developing a TTS System for the Tamil Language with the Synthesis Technique as Unit Selection Synthesis. Letter Level Segmentation of an input text helps in the reduction of corpus size compared to Syllable Level Segmentation. The segmented units are retrieved with respect to Unicode values, concatenated and the synthesized speech is produced. Intelligibility and Naturalness of the spoken word can be improved using the Smoothing Techniques. Optimal Coupling Smoothing Technique is implemented for the smooth transition in between the concatenated speech segments to create continuous Speech output like human voice. Fraction based Waveform Concatenation method is used to produce the intelligible speech segments as output from the pre-recorded speech database.
Chat-bot: An Information Retrieving for Myocardial Infarction and Diabetes

Medical information is being very important type for clinicians. We aim to build clinical chat-bot which holds information about diseases namely diabetes and heart diseases. Chat- bots are designed to make people feel they are interacting to a human for their related queries rather to believe for machine feelings. These chat-bot are computer program coded to build textual and conversation which are intelligent and gives us logical replies which are already learned. This research focuses to design such type of bot which act on two said major diseases so the working chat-bot will provide interaction between machine and man where machine will function as a virtual doctor here chat-bot will play a leading role by working as a virtual assistant and skipping the gap between patients and clinicians.
Impact of organisational innovation on non-financial organisational performance: an exploratory study of higher education institutions in Oman

Organisational innovation may contribute in enhancing the skills and knowledge for the employees which will lead to improving the organisational performance. However, the research literature has been dominated with studies examining the association between organisational innovation and financial organisational performance. There has been increased interest in the non-financial organisational performance (NFOP) in higher education institutions (HEIs) in the Sultanate of Oman. The aim of the study is to measure the impact of organisational innovation on non-financial organisational performance in the HEIs in the Sultanate of Oman. The study used exploratory research design to validate the proposed relationships described in the research objectives and to develop a reliable discussion extending to the findings attained. To achieve the research objectives, primary data were collected by surveying 329 staff working in three HEIs in Oman through a structured questionnaire. The finding of the study showed that organisational innovation has a positive impact on non-financial organisational performance.
A Synthesis of Optimal Unknown Number Clustering System and Categorical

Big data makes data dynamic and research moves from sample to population.These circumstances imply data mining, specifically clustering, should be able to produce the formed clusters of population as much as possible, thus leaving only a little "junk" of data.Unknown number clustering data mining is a term for set of clustering algorithms which cluster without defining number of formed clusters.Without intending to let others and their data types, this research proposes a synthesis of optimal unknown number clustering system and categorical, because the excellence of DBSCAN algorithm performance on spatial and non-spatial data, and the expectance of standard clustering system presence for population statistics.After reanalyzing its Spatial Coordinate Way and the radius parameter range, the synthesis is done with structural analysis based on general data mining steps for framing the complete clustering process.Then, the result of analysis is compared against the cluster analysis requirements to convince the conclusion on the system synthesis.The categorical data without weighting are also possibly converting into spatial form, but imply qualitative value.Therefore, the synthesis recommends that the standard clustering system should have special items on unweighted categorical data in addition to a numeric type.
Implementing Aggregate – Cryptographic Encryption Key for Sharing Data in Cloud Environment

Sharing is the main convenience for an appropriate restriction. In this study, we deal with the most appropriate framework to ask for significant and flexible sharing of information with others in real motivation driving constrainment. We are diagraming fresh open focal cryptosystems that show the size of the figure texts to such a degree that it is sensible to fairly circle the knowledge of the rights of any cipher text structure. Everything respected, the Secret Key Holder can release a valuable size all around the key for an adaptable choice of ciphertext set in scattered cutoff, some other mixed records referenced outside the set remain.
Enhancement of Underwater Images using Pixel Arrangements and Image Enhancement Algorithm

Underwater image processing is faced with a number of challenges from distinct resolutions, format variations, scattering, absorption of light etc. It is also affected by contrast difference and orientation. Conveying different resolved underwater images using enhanced pixel arrangement and image algorithm. This can be proceeded by converting the multi scale fused resolution images to high resolution images. Image enhancements has some in-built pixels properties having low intensities in at least one-color channel. Such kind of images are then converted to high resolution imaging by using the tools of enhanced pixel arrangement algorithm and then the output images are clarified.
Public Perception on Dreams

The dream is the succession of images emotions of our mind It is involuntary action. The present investigation took at convictions states of mind towards and impacts of dreams, in a bigger, basically It was additionally discovered, that dreams essentially were imparted to an accomplice, and generally with the reason for excitement. A dream is a progression of pictures, thoughts, feelings, and vibes that normally happen automatically in the brain amid specific phases of sleep. The substance and motivation behind dreams are not completely comprehended, The logical investigation of dreams is called oneirology. The objective of the study is to understand the public opinion about dream, to identify whether is difference in expectation of type of dream and gender, to analyze the association of emotional tone and age To interpret relationship in dreams are meaningful and educational qualification. this is done by descriptive research by convenience sampling method the sampling size is 1860.the independent variables is age, gender and educational qualification and the statistics are chi square, correlation, and independent sample t test. The study concludes that public require more knowledge regarding dreams. They have not thought or concentrated on dreams.
Performance Evaluation of Various Image Features Detectors and Descriptors Used in the Development of Panorama from Real Time Video Files

Image mosaicing is a method where two or more pictures of the same image can be combined into a big picture and a high resolution panorama created. It is helpful for constructing a bigger picture with numerous overlapping pictures of the same scene. The image mosaic development is the union of two pictures. The significance of image mosaicing in the sector of computer vision, medical imaging, satellite data, army automatic target recognition can be seen. Picture stitching can be performed from a broad angle video taken from left to right to develop a wide-scale panorama to obtain a high-resolution picture. This research paper includes valuable content which will be very helpful for creating significant choices in vision-based apps and is intended primarily to establish a benchmark for scientists, regardless of their specific fields. In this paper it has been seen that distinct algorithms perform differently in terms of time complexity and image quality. We have looked at a variety of feature detectors and descriptors such as SIFT-SIFT, SURF-SURF, STAR-BRIEF and ORB-ORB for the development of video file panoramic images. We have noted that SIFT provides excellent outcomes, giving the image the largest amount of key points identified at the cost of computational time and SURF, ORB, has fewer key points obtained, where it has been seen that ORB is the simplest of the above algorithms, but produces no good performance quality image outcomes. A good compromise can be achieved with SURF. Depending on the application, the metric for image feature extraction would change. In addition, the speed of each algorithm is also recorded. This systemic analysis suggests many characteristics of the stitching of images.
Cryptography

Cryptography is a necessary component in many parts of secure architecture. However, just adding cryptography to the code does not make it more secure; care must be given to such topics as secrets generation, secrets storage, and plain-text management. Properly designing secure software is a complicated matter, more so when cryptography is involved.
Secure Cloud Storage using Secret Key Sharing and Proxy Re-Encryption Based Third Party Auditing Service

Cloud Computing (CC) provides an easy way to access and store the information by vast remote servers, instead of using personal computer. There is no physical control over personal data by user, hence some security issues may arise for users and organization to secure the data in cloud. The sensitive data can be hacked by attackers, so the integrity of data stored in cloud is a major concern for users. In this research work, the data integrity can be ensured by using Third Party Storage Auditing Service (TPSAS), where it satisfies all the requirements of users in cloud. The ultimate aim of this research is to avoid the unauthorized access of user’s data stored in the cloud. In this paper, two major problems are considered for attaining the integrity of data in the cloud. The first one is, the unauthorized user tries to modify the data, which is solved by the proposed TPSAS. The second problem considered in this research is, since the Cloud Service Provider (CSP) is semi trustable it can be malfunctioned at any time, which can be solved based on the secure secret key sharing algorithm and proxy re-encryption methodology. The secure secret key sharing is implemented based on the Shamir key sharing algorithm and the proxy re-encryption process is implemented based on the bear and lion proxy re-encryption methodology.