Reviewerly/exHarmony huggingface dataset:
Convolutional Code Theory based Steganography Technique

Steganography, as it is known, is a technique to hide a secret message within a message or collection of data that is not secret, and a problem in mathematics is to decipher the secret included in the message, to solve this problem a good tool It is the theory of codes. Unlike the existing works that use block codes to hide information using the steganographic process, in this work, we propose the use of convolutional coding theory in steganography to encrypt and decrypt messages methods to decrypt messages. Here, we suggest a steganographic protocol based on convolutional codes in which they are defined as discrete linear dynamical systems with which the properties on controllability and observability characteristic of linear systems theory can be applied, in particular the properties of output observability character which can be easily described using matrix language. The proposed decoding algorithm used for dissimulation is a linear decoding method, which has decreased both the time and space complexity, compared to the Viterbi decoding algorithm, sometimes used in other cases; indeed, we go from 2h.n to 2h=2.n, in memory space (with h: constraint height, and n: length of cover object). Moreover, the time complexity is better, while we can also denote that with the convolutional approach, we intend to take advantage of the time-depending transaction.
DKEMA: GPU-based and dynamic key-dependent efficient message authentication algorithm

Recently, benefiting from the advancement in the Graphic Processing Unit (GPU) technology, there is an increased interest in implementing and designing new efficient cryptographic schemes. Existing cryptographic algorithms, especially the Message Authentication Algorithms (MAAs) such as Hash Message Authentication Code (HMAC) and Ciphered Message Authentication Code (CMAC), are not designed to benefit from the GPU characteristics, which results in degraded performance of their GPU implementations. This gives rise to a trade-off between the design concept and the performance level. In this paper, a new MAA, called ’DKEMA’, is proposed to better suit the GPU functionality. This scheme is based on the dynamic key-dependent scheme with one round of substitution and diffusion operations. The experimental results show that the proposed solution is highly effective on Tesla V100 and A100 GPUs, and the throughput is, respectively, more than 400GB/s and 500GB/s. Therefore, DKEMA can be considered as a promising MAA candidate for GPU implementation, achieving the desired cryptographic properties such as high randomness, collision tolerance in addition to message and key avalanche effect. The experimental results show that the proposed solution, based on the dynamic key approach, is immune towards well-known authentication and cryptanalysis attacks. In addition, DKEMA, consisting of one round compression function, presents an enhancement in terms of performance compared to existing algorithms (e.g. AES and SHA). The code is available in GitHub: https://github.com/rcouturier/GPU-DKEMA.git .
Digitalization Of Education And The Formation Of Moral Consciousness Of Modern Students

The article attempts to show the specifics of the formation of moral consciousness in the context of the digital transformation of the educational space. The concepts of freedom and responsibility are viewed as the basic ethical values that organize moral experience. The study of the problem is carried out on the basis of the concepts of digital socialization and digital personality. It should be noted that the actions of the subject of training are technologically predetermined. The transformation of content into an online product means that the technology already carries a certain part of new practices, a certain organizational capital: the ability to be creative, innovative, have high communication skills. It is shown that the pragmatic aspect of understanding and actions of the individual within the framework of freedom and responsibility is manifested as the need to "fit" into the new innovative system of professional requests. The article presents such features of the mentality of modern students as a rapid change in the system of moral assessments, lack of experience of reflection, amorphous idea of individual ethical responsibility. Freedom and responsibility as ethical guidelines for activity are largely concretized as emotionally experienced ideas about the "field of possibilities" of self-realization, that is, largely in an individualistic context. It is shown that in conditions of information overload, developed communicativeness, one of the important ways of manifesting moral feelings is an intuitive moral judgment and action.
A Linear Transformation for the Reconstruction of the Responses of Systems in Similitude

Abstract Recent years have seen an increasing interest towards similitude methods. In fact, the possibility of testing a scaled model, instead of a full-scale prototype, leads to many advantages: financial and time savings, easier experimental setups, etc. However, similitudes have drawbacks, too, mainly due to non-scalable effects and partial similitude, which prevent from an accurate reconstruction of the prototype response. For these reasons, an alternative method which can bypass these limitations is needed. A new method, called VOODOO (Versatile Offset Operator for the Discrete Observation of Objects), is herein proposed: it is based on the definition of a transformation matrix which links the outputs of a given linear systems to those belonging to another system, which may be a scaled model. The responses are acquired on a discrete number of points for both the systems. This work aims at investigating the method’s strengths and limitations of the method. The results show that, although VOODOO exhibits some lack of accuracy in off-design conditions due to the loss of spatial correlation, it is able to overcome some major restrictions that affect all similitude methods.
A flashback to changes across the Cretaceous-Paleogene boundary (K/Pg) in Turkey: &amp;#160;a faunal and environmental portray

&amp;lt;p&amp;gt;The interplay between continental flood basalt volcanisms and major mass extinctions has been known for long. The importance of the K/Pg boundary extinction is due to the coincidence of two cataclysmic events (the Deccan volcanism and the Chicxulub impact, respectively) in a very short time. The effects of Deccan activity on the ecosystem have to be scrutinized in order to understand the causality between volcanic eruptions and associated environmental stress. To do so, here we document this relation in terms of high-resolution biostratigraphy, quantitative species analysis, and isotope and geochemical measurements on two complete sections in Mudurnu-G&amp;amp;#246;yn&amp;amp;#252;k and Haymana basins, Central, Anatolia, Turkey.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Quantitative analysis on planktonic foraminifera of the Haymana Basin reveals a systematic reduction in the species richness through the late Maastrichtian, and then sudden annihilation of large, ornamented ecological specialists (e.g. Globotruncanids, Racemiguembelinids, Planoglobulinids) at the boundary. This extinction level (i.e., the K/Pg boundary) corresponds to a 2-3 mm thick reddish oxidized layer in which we found enrichments in Ir, Te, Hg, Ba, Ni, Cr, Co. Additionally, measurements on Maastrichtian and Danian samples show a significant correlation between Hg and Te. Moreover, acmes of &amp;lt;em&amp;gt;Thoracosphaera&amp;lt;/em&amp;gt; and &amp;lt;em&amp;gt;Guembelitria cretacea&amp;lt;/em&amp;gt; demonstrate ecosystem collapse after the K/Pg event. The same levels correspond to a surge in fecal pellets.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Overall, our results show that the deteriorating effects of Deccan volcanism had already started before the Chicxulub impact which predisposed faunas to eventual extinction at the K/Pg boundary.&amp;lt;/p&amp;gt;
Histopathological image classification based on self-supervised vision transformer and weak labels

Whole Slide Image (WSI) analysis is a powerful method to facilitate the diagnosis of cancer in tissue samples. Automating this diagnosis poses various issues, most notably caused by the immense image resolution and limited annotations. WSI’s commonly exhibit resolutions of 100, 000 × 100, 000 pixels. Annotating cancerous areas in WSI’s on the pixel-level is prohibitively labor-intensive and requires a high level of expert knowledge. Multiple instance learning (MIL) alleviates the need for expensive pixel-level annotations. In MIL, learning is performed on slide-level labels, in which a pathologist provides information about whether a slide includes cancerous tissue. Here, we propose Self-ViT-MIL, a novel approach for classifying and localizing cancerous areas based on slide-level annotations, eliminating the need for pixel-wise annotated training data. Self-ViTMIL is pre-trained in a self-supervised setting to learn rich feature representation without relying on any labels. The recent Vision Transformer (ViT) architecture builds the feature extractor of Self-ViT-MIL. For localizing cancerous regions, a MIL aggregator with global attention is utilized. To the best of our knowledge, Self-ViTMIL is the first approach to introduce self-supervised ViT’s in MIL-based WSI analysis tasks. We showcase the effectiveness of our approach on the common Camelyon16 dataset. Self-ViT-MIL surpasses existing stateof-the-art MIL-based approaches in terms of accuracy and area under the curve (AUC). Code is available at <a href="https://github.com/gokberkgul/self-learning-transformer-mil">https://github.com/gokberkgul/self-learning-transformer-mil</a>
IS IT ENJOYING OR BURDENING? STUDENTS’ PERCEPTIONS ON HOME LEARNING AND ONLINE LEARNING (An Overview of Corona Virus Disease “COVID-19” Impact to Education Field)

Teaching and learning is a good way to reach the educational goals. Since the Corona Virus Disease (COVID-19) hits the word, the process of teaching and learning totally change that creates new problem for teachers and students. This study aims to find out the students’ perceptions of the implementation of home learning and online learning during the pandemic era (COVID-19) in SMA Negeri 1 Soe. This study used a qualitative descriptive design. The instruments used were questionnaires and interviews. The data of this study was collected through spreading questionnaires and doing interviews. The data of this study were analyzed by using SPSS. The result of the study showed that students perceive the implementation of home learning and online learning during pandemic era (COVID-19) is a good way because it could protect the students from the spread of the COVID-19, it helped the students to keep learning. It could make the students to be responsible for their learning improvement.
Comparison of frameworks for developing web applications in PHP

The article presents a comparative analysis of two frameworks of PHP application development such as Laravel and Code Igniter. Test results obtained using the implemented implementation problem compare the application code size, code execution time, hardware resources used, as well as the complexity of the code. The purpose of the research was to present the possibilities of given application development skeletons, with the help of which the web application programmer will be able to decide on its use depending on the implemented solution.
A + B = C: How the Effective License Position Calculation for Software Isn’t That Simple

A foundation of effective software asset management, the Effective License Position (ELP) is a seemingly straightforward calculation: What software is deployed in your organization versus what your organization is entitled to use. This is simple in theory, but more complicated in practice. Software deployment and entitlement datasets have multiple sources which must be collected and processed to provide useful information to IT operational, financial, and compliance activities. This talk will introduce the Effective License Position, why it is important, how to calculate it, and what to do with it.
An Image Decompression Model with Reversible Pixel Interchange Decryption Model Using Data Deduplication

The images may or may not be confidential if communications occur via images.But it becomes complicated when we want to convey a picture, which only the sender and the recipient must know.Since data that have been sent during transmission can be lost or an individual may hack and misuse this picture.Safety of the data is important in such scenarios.In order to reduce storage space and costs, imaging deduplication (DD) technology is proposed.The concept of convergent encryption and decryption was suggested to protect the confidentiality of the image.The deduplication scheme encrypts/recodes an image with a convergent encryption/decryption key obtained from computing the hash value of the content of the image.Implementing DD over encrypted/decrypted data is a major challenge to optimize storage efficiently in a highly secured way in an integrated storage and computer environment.The original image is segmented into blocks of same size during the initial step, and sub classification is performed for accurate image extraction within the limits.The pixels of neighboring sub blocks are swapped using a random matrix.Following that, each pixel is randomly exchanged for neighboring blocks using a random matrix, and each block is encrypted using the suggested function before being sent to the receiver.In this manuscript, an Image Decompression Model with Reversible Pixel Interchange Decryption model using Data Deduplication (IDRPID-DD) is introduced that provides security during storage and data transmission.The proposed model is compared with the traditional methods and the results show that the proposed model deduplication identification and eradication levels are high and the proposed decryption model is strong.
Augmented reality for visualization the narrow areas in jaw surgery: modified Correntropy based enhanced ICP algorithm

Abstract Over time, Augmented Reality (AR) based technology becomes not being properly to implement with oral and maxillofacial surgery to visualise the narrow area spot in jaw surgery as blood vassals and root canals in these types of surgeries. Image registration is considered the major limitation of using the AR in these types of surgeries and reduces the accuracy of visualising the narrow areas. In this research, we propose a Correntropy based scale ICP algorithm as a solution to improve the image registration during jaw surgery. Correntropy is considered here to minimise the error metric of the ICP algorithm instead of the Euclidean distance measurement compared to the state-of-the-art solution. This led to decrease the registration error, increase the video accuracy and reduce the processing time simultaneously. The proposed system consists of Enhanced Tracking Learning Detection (TLD), which is used as an occlusion removal featured algorithm in the intra-operative stage of the AR-based jaw surgery system. In this research, a Modified Correntropy-based enhanced ICP (MCbeICP) algorithm is proposed for the system’s pose-refinement phase. Moreover, this proposed algorithm (MCbeICP) has a new function to process the point set registration with great noises and outliers. It eliminates the poor performance of the ICP algorithm of the noisy point set. Furthermore, the ICP algorithm considers the scale factor to register the point with different scales of the real-time video and the sample models. Additionally, this method improves the result of the pose refinement stage in terms of registration accuracy and processing time. By this method, the pose refinement stage gives an improved result in terms of registration accuracy and processing time. The samples, which were taken from the upper (maxillary) and the lower (mandible) jaw bone show that the proposed algorithm provides a significant accuracy improvement in alignment to 0.21- 0.29 mm from 0.23 to 0.35 mm and an increment in processing time from 8 to 12 frames per second (fs/s) to 10-14 fs/s compared to the result provided by state of the art. The proposed augmented reality (AR) system is focused on the overlay accuracy and processing time. Finally, this study addressed the limitation of Image registration with AR using modified Correntropy-based enhanced ICP algorithm to implement oral and maxillofacial surgery successfully.
World experience in identifying metacognitive competencies of a teacher in the course of professional development and work with gifted children

Today, there are significant requirements for the professional competencies of a teacher, among which a special place is occupied by competencies that determine the effectiveness of work with different categories of students. The article presents the results of a theoretical comparison of conceptual approaches to the identification and development of professional competencies of future teachers. The metacognitive competencies underlying self-learning are analyzed. The role of special work within the framework of individual educational courses, trainings and practices in higher education, aimed at developing metacognitive strategies and competencies of future teachers, is substantiated. The article proposes a support structure for the components of metacognitive competence (metacognitive knowledge, declarative knowledge, metacognitive strategies). After analyzing the concept map and comparing various models of identification and development of metacognitive competence, the authors single out research, managerial and communicative competences in its structure. An analysis of domestic research highlights the role of managing competencies for working with a gifted child and shows that a future teacher must constantly develop regulatory and personal qualities in himself and in a gifted student. When working with a gifted student, a teacher needs metacognitive competence, which is formed in the process of asking questions to oneself, in attempts to try other strategies for solving pedagogical situations. The teacher is required not only to be able to teach, but also to constantly learn himself in order to be able to solve non-trivial situations together with students. It is shown how the relationship between a teacher and students affects psychological health, well-being, psychological burnout, the quality of professional activity, the ability to work with a gifted person. The conclusion is made about how approaches to the professional training of specialists in the educational sphere should change in order to provide the opportunity to work with the category of gifted children.
All-dummy k-anonymous privacy protection algorithm based on location offset

Abstract While k-anonymous algorithms can effectively protect users’ private location information, the problem of selecting an appropriate location in the anonymous area to construct the k-anonymous area remains a significant one. When selecting real users from the surrounding area to co-construct anonymous regions, it is easy to cause the leakage of user location information. Moreover, using false addresses to construct a region requires calculating the probability of location queries, which increases the computational complexity. In this paper, an all-dummy k-anonymous algorithm based on location offset is proposed to construct anonymous regions. This algorithm randomly selects k−1 locations and real users in the selected anonymous compose an anonymous group at first. Subsequently, these coordinates are centered on migration, generating multiple dummy addresses of each location migration, such that the dummy address distance is greater than the radius of the user's query, with the dummy address location information used for the location server queries. Through experimental verification, compared with the circle-based dummy address generation algorithm and the random k-anonymous algorithm, the all-dummy k-anonymous algorithm is found to achieve an entropy value and tracking success rate closer to the optimal k-anonymous algorithm without increasing the communication cost.
N B Interpolation Technique for Improved Arbitrarily missing values in Data Mining

In data mining in order to reduce the numerical computations associated to the repeated application of the existing interpolation formula in computing a large number of interpolated values, a formula has been derived from Newton’s backward interpolation formula for representing the numerical data on a arbitrarily missing vales in database. A suit approach of the formula to numerical data has been shown in the case of representing the data on the dataset global carbon dioxide emissions from fossil fuel burning by Fuel Type corresponding as a method of time. The formula is suitable in the situation where the values of the argument are at equal interval.
Analytical Processing and Insights

Throughout the book you’ve focused on building your data engineering toolbox and learning powerful techniques for processing and transforming data, both at rest and in stream. Parallel to learning Spark, you have also been hands-on learning to use containers and operate additional technologies that interoperate well in the Apache Spark ecosystem.
Quantum kernels with Gaussian state encoding for machine learning

Kernel methods are powerful for machine learning, as they can represent data in feature spaces that similarities between samples may be faithfully captured. Recently, it is realized that quantum-enhanced machine learning is closely related to kernel methods, where the exponentially large Hilbert space can be a feature space more expressive than classical ones. Here we investigate quantum kernel methods of encoding data into continuous-variable quantum states, with two newly introduced quantum kernels named squeezing amplitude kernel and coherent phase kernel from Gaussian state encoding, in which data is encoded as either in the amplitude or the phase. The kernels can be calculated on a quantum computer and then are combined with classical machine learning, e.g. support vector machine, for training and predicting tasks. Their comparisons with other classical kernels are also addressed. Lastly, we briefly discuss the universal approximation property of continuous-variable quantum kernels.
Probe Machine Based Computing Model for Maximum Clique Problem

Probe machine (PM) is a recently reported mathematic model with massive parallelism. Herein, we presented searching the maximum clique of an undirected graph with six vertices. We constructed data library containing n sublibraries, each sublibrary corresponded to a vertex in the given graph. Then, probe library according to the induced subgraph was designed in order to search and generate all maximal cliques. Subsequently, we performed probe operation, and all maximal cliques were generated in parallel. The advantages of the proposed model lie in two aspects. On one hand, solution to NP-complete problem is generated in just one step of probe operation rather than found in vast solution space. On the other hand, the proposed model is highly parallel. The work demonstrates that PM is superior to TM in terms of searching capacity when tackling NP-complete problem.