Reviewerly/exHarmony huggingface dataset:
A Hybrid Watermarking Scheme for Increasing Watermark Capacity and Security

Imperceptible and robust watermarking schemes have been vastly used recently as powerful tools to guard the copyright protection, rightful ownership, and content authentication.This paper introduces a secure hybrid digital image watermarking algorithm based on bi-dimensional empirical mode decomposition (BEMD); redundant discrete wavelet transform (RDWT); discrete cosine transform (DCT) and singular value decomposition (SVD).A watermark is scrambled by Arnold transform to boost up its secrecy and robustness.The main purpose of this scheme is to increase the embedding watermark capacity and encryption while keeping it robust against different types of attacks.The number of changing pixel rate (NPCR) and the unified averaged changed intensity (UACI) are two most common quantities used to estimate the strength of watermark image encryption algorithms/ciphers with reference to differential attacks.A high NPCR/UACI score is usually explicated as a high resistance to differential attacks, as well as higher PSNR evaluation metrics.Experimental using PSNR, WDR, MSE, NC and BCR metrics on different host images (Lena, Barbara, and Boat) and the cameraman as the watermark image show that the presented scheme is rich in terms of imperceptibility, capacity, security and robustness.This has been also highlighted by comparing its performance against other stateof-the-art schemes.
INTEGRITY AUDITING OF CLOUD DATA WITH HOMOMORPHIC AUTHENTICATORS

An access control mechanism for the integrity of shared data with user resciding in cloud.By utilizing the idea of signatures, once a user entered in the group, the user can able to upload the file in cloud, with the use of secret key.The user needs to store only secret keys and signatures.It allows verification without the need for the challenger to compare against the original data.A public verifier is always able to audit the integrity of shared data without retrieving the entire data from the cloud.To securely introduce an effective auditor, the auditing process should bring no new vulnerabilities towards user data privacy.It enables an external auditor to examine the user's cloud data without knowing about the data script.As a result, the efficiency of user resciding can be significantly improved by the third party auditing mechanism.
Real-Time Algorithms for Head Mounted Gaze Tracker

We introduce a set of real-time algorithms for head mounted gaze tracker consisting of three cameras: two cameras for the eyes and one camera for the scene. The direction of the optical axis of the eye in three-dimensional space is calculated using the reflection of IR LEDs from the cornea. Individual features of the user are taken into account using the short-term calibration procedure. The described algorithms combine high accuracy in determining the point of gaze with high speed. The procedure for determining the point of gaze consists of the following algorithms: estimation of the position of the pupils on the eye cameras frames using of the threshold processing taking into account the histogram of the frame and further approximation of the pupil by an ellipse; estimation of the IR LEDs glare position on the frames of the eye cameras using threshold processing; filtration of the glares by brightness, size, circularity, and of the glares beyond the iris, the size of the iris is estimated by the distance from eye camera to pupil position calculated on the previous frame; indexation of the glares with the template matching; estimation of the optical axis angles of the eye using a spherical model of the cornea with the nonlinear optimization methods; estimation of the point of gaze on the scene camera frame using individual user features found during the calibration process. During calibration, the movement of the ArUco calibration mark and its selection on the scene camera frame are used. To calculate the gaze position on the scene camera, a regression algorithm is used, which implicitly takes into account the individual characteristics of the user.
Systematic Literature Review of Web Search Personalization

The existing studies have already revealed that the information on the web is increasing rapidly. Ambiguous queries and users’ ability to express their intention through queries have been one of the key challenges in retrieving accurate search results from the search engine. This paper in response explored different methodologies proposed during 2005-2019 by the eminent researchers for obtaining better search results. Some of these methodologies are based on the users’ geographical location while others rely on re-ranking the web results and refinement of the users’ queries. Fellow researchers can use this literature to define the fundamental literature of their work. Furthermore, a brief case study of major search engines like Google, Yahoo, Bing, etc. along with the techniques used by these search engines for personalization is also discussed. Finally, the paper discusses some current issues and challenges related to personalization which further defines the future research directions.
AI- BASED TOOLS FOR FOREIGN LANGUAGE TRAINING: OPINIONS FROM DIFFERENT AUDIENCES

The paper aims to analyze the attitude of various audiences to practice and the prospects of AI-based tools use for language learning. In the course of investigation the authors consider Academia major research trends on AI use for educational tasks and language learning in particular. The opinions of developers involved in creating AI-based educational products are also subject to consideration. Moreover, the authors also explore opinions of foreign language teachers and students with regard to the use of AI-based applications in foreign language training.The research methodology combines qualitative and quantitative approaches to desk and field studies. The research incorporates a theoretical analysis of the relevant literature, opinions of the target audiences collected from the mass media (views of AI developers) and the surveys that the authors conducted in the focus-groups interviews and discussions with foreign language teachers and students. The factor and discriminant types of analysis were used to consider the variables and lay grounds for the data interpretation.The findings reveal that despite a strong social and profession difference among the target audiences who formed the present research sample they partly coincide in their perceptions of AI-based apps use in foreign language training due to a number of reasons that are specified in the conclusion.
AI and pathology: The path ahead

Pathologists are quickly reaching a state where they are able to leverage advances in computation, digital pathology, big data analytics and deep learning. When coupled with artificial intelligence (AI) tools this creates many opportunities to improve clinical practice and patient outcomes. There is tremendous potential for AI in all fields of pathology that extend from the womb to the tomb. AI can triage cases, enhance routine tasks, better diagnose disease, provide prognosis and make new discoveries. Not surprisingly, several vendors have shifted towards developing AI tools and we have witnessed a spurt of AI start-up companies targeting pathology. Pathologists are important at all stages of an AI tool creation including algorithm design, development, validation, regulatory approval and integration. Academic industry partnerships have consequently becoming key in the innovation cycle in AI. However, only a handful of labs around the world have started to deploy AI technology. There are four important questions we need to consider before adopting AI in pathology. These include: (1) What are the appropriate tasks for AI? (2) What are the right data for developing AI tools? (3) What is the right evidence standard for accepting AI? (4) What is the right method for deploying AI in routine practice? The risks of prematurely using AI include poor algorithm performance and misdiagnoses due to biased algorithms, failed implementations with unintended consequences, workflow disruption, driving up health care cost, liability concerns, as well as deskilled pathologists and trainees. Guidelines will help pathologists facilitate how to best use AI technology in clinical practice.
Career Development Expert System Application Using the Entrepreneurship Personality Inventory

This study aims to describe the process of designing expert system applications in career development using entrepreneurship personality inventory. The reason for conducting this research is a) the limited number of instruments that are able to measure the entrepreneurship personality of vocational students, b) the high costs incurred in conducting personality tests in career development of vocational students, c) The need for an application that is able to speed up the process of identifying personality and provide recommendations careers for vocational students. The research methodology used is Research and Development. There are four stages that must be carried out: Define, Design, Develop and Disseminate. The instrument used to measure entrepreneurial personality is inventory (non-test) with four indicators of entrepreneurship personality, namely Extroverted, Leader, Moderate Risk Taker, Ambisious, and tested fit using Confirmatory Factor Analysis. The research sample was 30 vocational high school students in the field of Information Technology and Computers. Bayes Method is used for the process of transferring knowledge from experts to the system and decision making, after Based on the results of data analysis, it was found that a) Career development applications based on Entrepreneurship Personality are valid with a percentage (0.887) and very practical (91.11), the results of product effectiveness are 82.47 (effective). Therefore this application is declared valid, practical and effective in measuring the personality of vocational student entrepreneurship.
Heisenberg-limited single-mode quantum metrology in a superconducting circuit

Two-mode interferometers lay the foundations for quantum metrology. Instead of exploring quantum entanglement in the two-mode interferometers, a single bosonic mode also promises a measurement precision beyond the shot-noise limit (SNL) by taking advantage of the infinite-dimensional Hilbert space of Fock states. Here, we demonstrate a single-mode phase estimation that approaches the Heisenberg limit (HL) unconditionally. Due to the strong dispersive nonlinearity and long coherence time of a microwave cavity, quantum states of the form $$\left( {\left| 0 \right\rangle + \left| N \right\rangle } \right)/\sqrt 2$$ can be generated, manipulated and detected with high fidelities, leading to an experimental phase estimation precision scaling as ∼N−0.94. A 9.1 dB enhancement of the precision over the SNL at N = 12 is achieved, which is only 1.7 dB away from the HL. Our experimental architecture is hardware efficient and can be combined with quantum error correction techniques to fight against decoherence, and thus promises quantum-enhanced sensing in practical applications. Reaching a quantum advantage in metrology usually requires hard-to-prepare two-mode entangled states such as NOON states. Here, instead, the authors demonstrate single-mode phase estimation using Fock states superpositions in a superconducting qubit-oscillator system.
Research on Load Recognition Algorithms Based on Current Distortion and Harmonic Content

To overcome the disadvantage of harmonic analysis algorithm that cannot accurately identify low power load, a load identification algorithm based on current distortion and harmonic content is proposed. For resistive loads, regardless of power, the current distortion and voltage distortion are the same, and the current harmonic component is only the fundamental component, the other order harmonic content is almost zero. Resistive load access circuit increases current fundamental wave content. While the other harmonic components are almost unchanged, so the distortion and harmonic content are lower than before. For common non-resistive loads, the current distortion and harmonic content are very large, and they are higher than before. Based on the characteristics of resistive and non-resistive loads mentioned above, the current distortion and harmonic content are introduced into the existing harmonic analysis algorithm, and the current distortion and harmonic content before and after load access are calculated and analyzed to identify small power loads. Experiments show that the recognition accuracy of this algorithm for small power load is higher than that of harmonic analysis.
MagnifierNet: Towards Semantic Regularization and Fusion for Person Re-identification.

Although person re-identification (ReID) has achieved significant improvement recently by enforcing part alignment, it is still a challenging task when it comes to distinguishing visually similar identities or identifying the occluded person. In these scenarios, magnifying details in each part features and selectively fusing them together may provide a feasible solution. In this work, we propose MagnifierNet, a triple-branch network which accurately mines details from whole to parts. Firstly, the holistic salient features are encoded by a global branch. Secondly, to enhance detailed representation for each semantic region, the Semantic Adversarial Branch is designed to learn from dynamically generated semantic-occluded samples during training. Meanwhile, we introduce Semantic Fusion Branch to filter out irrelevant noises by selectively fusing semantic region information sequentially. To further improve feature diversity, we introduce a novel loss function Semantic Diversity Loss to remove redundant overlaps across learned semantic representations. State-of-the-art performance has been achieved on three benchmarks by large margins. Specifically, the mAP score is improved by 6% and 5% on the most challenging CUHK03-L and CUHK03-D benchmarks.
08: Kognitive Systeme, Vorlesung, SS 2019, 03.06.2019

08 | 0:00:00 Start0:01:37 Wiederholung0:04:54 Neural Networks0:23:42 Performance0:28:20 Using Neural Nets0:35:44 Generalization0:43:04 Neural Nets-Modeling0:45:59 Speech0:50:55 A few Related Sciences0:53:58 Anatomy of speech Production1:09:21 Different vocal Tract Shapes1:12:57 Formants
Aplikasi Tracer Study Alumni Universitas Katolik Santo Thomas

ABSTRACT&#x0D; Catholic University of Saint Thomas is one of the private universities in North Sumatra that was founded in 1984. Currently Unika Saint Thomas has 8 faculties with 16 study programs that have produced many undergraduate graduates. Graduates' data have not been properly stored in each unit so that they will find it difficult to record the alumni. To evaluate a tertiary institution, a number of information systems are needed to support the data storage of the alumni, data on graduation years, place of work, work suitability and waiting time to get a job. To meet the obstacles in obtaining data from alumni, an information system for tracer study is needed. The tracer study application is used as a medium in obtaining information from graduates on the learning process during college studies needed in the world of work. This application is built based online with the Hypertext Preprocessor (PHP) programming language, MySQL database server which makes it easy for alumni to fill out questionnaires and profiles from the websites provided.
Word Embeddings at Post-Editing

After more than 60 years of research in Machine Translation, it has not been possible yet to develop a perfect fully automatic translation system for unlimited purposes. Thus, it is still necessary post-editing to correct possible mistranslations output by the Machine Translation system. Several approaches have been proposed in order to also automate the post-editing task. This work addresses one of the main steps of an automatic post-editing tool: the automatic proposition of word replacements for a Machine Translation output. To do so, we propose a novel method based on bilingual word embeddings. In the experiments present in this paper we show the effectiveness of this approach in two of the most frequent lexical errors: ‘not translated word’ and ‘incorrectly translated word’.
DOCÊNCIA NO ENSINO PROFISSIONAL DE NÍVEL MÉDIO EM ENFERMAGEM E ESTRATÉGIAS PEDAGÓGICAS QUE INFLUENCIAM NA PRÁXIS DO PROFESSOR ENFERMEIRO: REVISÃO NARRATIVAa práxis do professor enfermeiro: revisão narrativa

This work objectives identify the teaching praxis and possible pedagogical strategies for teaching building for learning in the professional teaching at secondary level in nursing. This is a bibliographic research of the narrative type, with a descriptive characteristic in qualitative approach, carried out from October to November 2018. To perform analysis and discussion of the notes from this study, a sample of articles was selected, which present in their content the relation between training, nursing and professional education. As a result, five articles related to the subject matter were obtained, which grounded the discussion. The study allowed the identification of elements that compose the teaching praxis and possible pedagogical strategies of teaching and learning building in nursing secondary education in nursing, such as (self) reflexive posture on the practice, the search for pedagogical dimension approach based on a close look at the student, the dialogue as a teaching and learning process and its relationship with care and attention.
TECHNOLOGY OF FORMATION OF STUDENTS’ MOTIVATIONAL WILLINGNESS FOR PROFESSIONAL ACTIVITY

The process of formation of the professional personality begins from the moment of choosing a profession and lasts throughout the professional life of a person, during which the most important problems of the relationship between a person and a profession are revealed. In psychology and pedagogy of Western countries, the problem of incentives to activity is revealed in a number of concepts and theories from different positions. Currently, motivation as a mental phenomenon is interpreted in different ways. The main theories of motivation should be divided into two directions: substantive theories, which consider motivation from structural positions, and procedural theories, which consider motivation as a dynamic formation. What unites these areas is the understanding of motivation as secondary to the motive of education. The concept of “willingness” for activity is considered as an active and effective state of the person, the installation to determine behavior, mobilization of forces to perform the task. In the structure of professional willingness of the individual, researchers identify different components, among which the most important is the motivational one –attitude to the profession, the need to solve successfully the task and interest in the activity. An essential component of professional willingness is psychological willingness, which should be considered as a complex functional-psychological and personal formation, including: a positive attitude to a particular type of activity; adequate character traits and temperament to the requirements of the activity; the necessary knowledge, skills, abilities, and habits; stable professionally important features of cognitive and emotional-volitional processes.
The Framework of an AR-Quest Instructional Design Model Based on Situated Learning to Enhance Thai Undergraduate Students’ Khmer Vocabulary Ability

The application of Augmented Reality technology in education has been increasing from year to year. The researchers conducted this study to propose a framework for an AR-Quest instructional design model based on situated learning to enhance Thai undergraduate students’ Khmer vocabulary ability. The proposed framework was evaluated by experts from the fields of Educational Technology and Communications, Instructional Design, and Language Teaching. The data from the evaluation form from the experts were calculated using the mean value. Then, thirty students were taught using the instruction developed from the model; and they were assessed by a pretest and posttest vocabulary test. The results found that the AR-Quest instructional design model comprises 1) analysis, 2) AR Package Development, 3) AR Quest Development, 4) Instruction Development, 5) Model Implementation, and 6) Model Revision. The result from the Khmer vocabulary ability score of the posttest of the students suggested a higher score than the pretest, showing a difference at a .05 significance level.
Random Invertible Key Matrix Decomposition for Classical Cryptography

Cryptography is assumed to be an important part of the secret message composing. It is the way of securing plain text by changing it into cipher text using some algorithms. Cryptography is utilized to provide the secrecy of cipher text during transmission from an adversary. The intent of this paper is to introduce LU decomposition technique to generate the key matrix which makes the key more complex by enhancing the security of the message using invertible key matrix.
Sulla sostenibilità della dignità come autodeterminazione

The paper, considering that, in recent years, the concept of dignity is opposed to that of life and frequently combined with the alleged right to assisted suicide, aims to identify the cultural premises of this assumption and to evaluate it in the light of the Constitution. Crucial appear the theories based on the distinction between man and person, such as social Darwinism. In these views the dignity of every human being depends on capacities of autonomy or self-determination. However, the implications are distant from the constitutional axiological framework and risk undermining many human rights and equality. The right to assisted suicide is then only apparently liberal, as it is pretensive and implies the duty to kill. Above all, it presupposes a conception of life that is instrumental for other ends and not itself a basic good and a sufficient reason, because based on a judgment that discriminates according to the quality of life. On the contrary considering the life’s innate dignity is the most democratic of principles. Moreover, there is a very close relationship between this recognition and “equal social dignity”. Hence a norm that prevents to act intentionally against life does not result an unreasonable restriction of freedom and appears to be acceptable even in a moderately neutralist or utilitarian perspective.
DESIGN AND IMPLEMENTATION OF ANDROID APPLICATION FOR IMPROVED SYSTEM FOR COLLEGE AUTOMATION

This project is an android application and a modified version of the present application which is used by the institution. Mobile phones and android applications play a major role in human lives, from being an ordinary talking device to a human companion. College management system focuses on helping the staff’s, lecturers who are working in the institution. The android application is focussed to help the staff’s for the progression and the academic development of the institution. i e. by reducing the manual labour, checking the performance of the students. It maintains a database of all the information that are recorded and received. It helps the staff’s to help students who need individual attention for their academic performance and also in case of any personal grievance.