Reviewerly/exHarmony huggingface dataset:
Efficient Method For Identification Of Anomalies Based On A Deep Learning Classification Methodology

This research intends to enhance the identification problem in visual processing using the deepanomaly identification system. The Backdrop Estimation (BE)module, an Objective Separation (OS) module, an Extraction of Features (FE) module, and an Activities Recognizing (AR) module are provided in the system to complete the identification of anomaly. An anomaly detection system based on the deep learning classification (ADS-DLC) model is proposed in this research. It initially provided aBackdrop Estimation (BE) module that produced an exact background for generating two frameworks to calculate the background assessment.The OS architecture is employed to collect the target from videos after generating a quality backdrop. The target tracking method is then utilized to track the item using the coinciding detection program. The FE component is removed from the monitored objects for relevant form, frequency, and distribution for unusual action recognition. The deep learning classification categorizes the suggested AR module as an unusual or usual occurrence for the last phase.Investigations are carried out with the benchmarks of aberrant operations, and the approach's benefits are validated with the most advanced methods. It can observe that the suggested activity identification system was superior to the current systems by attaining better simulation outcomes. It also indicates that the proposed technique achieves 91 percent of the structure level of performance.
Spectral analysis of re-parameterized light fields

In this paper, we study the spectral properties of re-parameterized light field. Following previous studies of the light field spectrum, which notably provided sampling guidelines, we focus on the two plane parameterization of the light field. However, we introduce additional flexibility by allowing the image plane to be tilted and not only parallel. A formal theoretical analysis is first presented, which shows that more flexible sampling guidelines (i.e. wider camera baselines) can be used to sample the light field when adapting the image plane orientation to the scene geometry. We then present our simulations and results to support these theoretical findings. While the work introduced in this paper is mostly theoretical, we believe these new findings open exciting avenues for more practical application of light fields, such as view synthesis or compact representation.
Topic Scene Graph Generation by Attention Distillation from Caption

If an image tells a story, the image caption is the briefest narrator. Generally, a scene graph prefers to be an omniscient generalist, while the image caption is more willing to be a specialist, which outlines the gist. Lots of previous studies have found that a scene graph is not as practical as expected unless it can reduce the trivial contents and noises. In this respect, the image caption is a good tutor. To this end, we let the scene graph borrow the ability from the image caption so that it can be a specialist on the basis of remaining all-around, resulting in the so-called Topic Scene Graph. What an image caption pays attention to is distilled and passed to the scene graph for estimating the importance of partial objects, relationships, and events. Specifically, during the caption generation, the attention about individual objects in each time step is collected, pooled, and assembled to obtain the attention about relationships, which serves as weak supervision for regularizing the estimated importance scores of relationships. In addition, as this attention distillation process provides an opportunity for combining the generation of image caption and scene graph together, we further transform the scene graph into linguistic form with rich and free-form expressions by sharing a single generation model with image caption. Experiments show that attention distillation brings significant improvements in mining important relationships without strong supervision, and the topic scene graph shows great potential in subsequent applications.
LIBRARY OF A NEW TYPE AS A CULTURAL UNIVERSAL

The relevance of the study of a new type of library as a cultural universal is due to the fact that the modern library remains the most democratic tool in the world for access to knowledge for all citizens, regardless of their age and social status. The library, being a social organism, cannot exist outside of the spiritual life of society, it is one of the most important tools of its development. Changing role of information in modern society directly affects the transformation of some functions of libraries. The study of the ontological foundations of the library can help to reveal its mission at the turn of the epochs. The aim of the study is to consider the phenomenon of the library in the historical context as an institution of culture, providing circulation of social experience. Transformations in the life of society and in the activity of the library as a social organism create the task of defining a strategy for its development. When considering this problem, a systematic approach was used. Culture is considered as a system of supra-biological programs, in which the library acts as an element of this system. General logical methods of cognition such as analogy, analysis, synthesis, generalization and prediction were also applied. The material of the article characterizes the library of a new type as a cultural universal, accumulating and broadcasting social experience. The article presents the philosophical foundations of the library in the context of the universals of culture, describes its main functions, reveals the essence and characteristics of the library of a new type, identifies socio-cultural practices as an important factor in the formation of information mobility of students. As a result of the study the following conclusions were made: 1. The ontological foundations of the traditional and modern library are common, which characterizes it as a cultural universal. 2. The transformation of the functions of modern libraries led to the emergence of a new type of library. 3. Consideration and study of the philosophical foundations of the library of a new type let to reveal its mission at the turn of the epochs, as well as to predict further ways of its development.
GCN-SE: Attention as Explainability for Node Classification in Dynamic Graphs

Graph Convolutional Networks (GCNs) are a popular method from graph representation learning that have proved effective for tasks like node classification tasks. Although typical GCN models focus on classifying nodes within a static graph, several recent variants propose node classification in dynamic graphs whose topologies and node attributes change over time, e.g., social networks with dynamic relationships, or literature citation networks with changing co-authorships. These works, however, do not fully address the challenge of flexibly assigning different importance to snapshots of the graph at different times, which depending on the graph dynamics may have more or less predictive power on the labels. We address this challenge by proposing a new method, GCN-SE, that attaches a set of learnable attention weights to graph snapshots at different times, inspired by Squeeze and Excitation Net (SE-Net). We show that GCN-SE outperforms previously proposed node classification methods on a variety of graph datasets. To verify the effectiveness of the attention weight in determining the importance of different graph snapshots, we adapt perturbation-based methods from the field of explainable machine learning to graphical settings and evaluate the correlation between the attention weights learned by GCN-SE and the importance of different snapshots over time. These experiments demonstrate that GCN-SE can in fact identify different snapshots' predictive power for dynamic node classification.
Cross Domain Emotion Recognition using Few Shot Knowledge Transfer

Emotion recognition from text is a challenging task due to diverse emotion taxonomies, lack of reliable labeled data in different domains, and highly subjective annotation standards. Few-shot and zero-shot techniques can generalize across unseen emotions by projecting the documents and emotion labels onto a shared embedding space. In this work, we explore the task of few-shot emotion recognition by transferring the knowledge gained from supervision on the GoEmotions Reddit dataset to the SemEval tweets corpus, using different emotion representation methods. The results show that knowledge transfer using external knowledge bases and fine-tuned encoders perform comparably as supervised baselines, requiring minimal supervision from the task dataset.
A Mapping-Based Convex Constraint-Handling Technique for Evolutionary Algorithms

This paper proposes a new mapping-based constraint-handling technique for Evolutionary Algorithms (EAs) applied to linearly constrained optimization problems in which the feasible region is given by a convex hull. The search space of EAs is usually given by a hyper-cube. The proposed technique called Convex-Hull (CH) mapping transforms a real vector in the search space of EA to a solution in the feasible region. Therefore, CH-mapping makes any EAs applicable directly to linearly constrained optimization problems. The performance of Differential Evolution (DE) using CH-mapping is evaluated on test problems and a real-world application, namely the portfolio optimization problem.
Effective Certification of Monotone Deep Equilibrium Models.

Monotone Operator Equilibrium Models (monDEQs) represent a class of models combining the powerful deep equilibrium paradigm with convergence guarantees. Further, their inherent robustness to adversarial perturbations makes investigating their certifiability a promising research direction. Unfortunately, existing approaches are either imprecise or severely limited in scalability. In this work, we propose the first scalable and precise monDEQ verifier, based on two key ideas: (i) a novel convex relaxation enabling efficient inclusion checks, and (ii) non-trivial mathematical insights characterizing the fixpoint operations at the heart of monDEQs on sets rather than concrete inputs. An extensive evaluation of our verifier on the challenging $\ell_\infty$ perturbations demonstrates that it exceeds state-of-the-art performance in terms of speed (two orders of magnitude) and scalability (an order of magnitude) while yielding 25% higher certified accuracies on the same networks.
Enterprise Architecture Desa Menggunakan Framework TOGAF ADM

Sudagaran Village is one of the villages that has implemented Information Technology (IT) to support business processes and village government operations. One of the business processes that utilize IT is a letter request service, using the SMARD application. However, in the business process for the letter application, the community must come to the Village Hall to collect the required documents and fill out the letter application form. This process is considered less effective. So that the village government expects the planning and development of a better and more effective information system, which can be accessed by the community starting from collecting files, filling out forms to receiving/downloading letters without having to go to the Village Hall. An enterprise architecture is needed for the design of the Sudagaran Village information system, which is focused on the business processes of 5 types of mail services, namely Letter of Introduction, Certificate of Population Move, Cover Letter of SKCK, Certificate of Underprivileged, and Business Certificate using TOGAF ADM. This study uses 6 stages of TOGAF ADM, namely the Preliminary Phase to Phase E – Opportunities & Solutions because it focuses on planning. This study resulted in an EA document containing business artifacts, data, applications, and technology made using Sparx, which can be used as a guide for Sudagaran Village to support the smart village concept in Banyumas Regency.
Ising Model Selection Using $\ell_{1}$-Regularized Linear Regression: A Statistical Mechanics Analysis

We theoretically analyze the typical learning performance of $\ell_{1}$-regularized linear regression ($\ell_1$-LinR) for Ising model selection using the replica method from statistical mechanics. For typical random regular graphs in the paramagnetic phase, an accurate estimate of the typical sample complexity of $\ell_1$-LinR is obtained. Remarkably, despite the model misspecification, $\ell_1$-LinR is model selection consistent with the same order of sample complexity as $\ell_{1}$-regularized logistic regression ($\ell_1$-LogR), i.e., $M=\mathcal{O}\left(\log N\right)$, where $N$ is the number of variables of the Ising model. Moreover, we provide an efficient method to accurately predict the non-asymptotic behavior of $\ell_1$-LinR for moderate $M, N$, such as precision and recall. Simulations show a fairly good agreement between theoretical predictions and experimental results, even for graphs with many loops, which supports our findings. Although this paper mainly focuses on $\ell_1$-LinR, our method is readily applicable for precisely characterizing the typical learning performances of a wide class of $\ell_{1}$-regularized $M$-estimators including $\ell_1$-LogR and interaction screening.
Representer Theorems in Banach Spaces: Minimum Norm Interpolation, Regularized Learning and Semi-Discrete Inverse Problems

Constructing or learning a function from a finite number of sampled data points (measurements) is a fundamental problem in science and engineering. This is often formulated as a minimum norm interpolation problem, regularized learning problem or, in general, a semi-discrete inverse problem, in certain functional spaces. The choice of an appropriate space is crucial for solutions of these problems. Motivated by sparse representations of the reconstructed functions such as compressed sensing and sparse learning, much of the recent research interest has been directed to considering these problems in certain Banach spaces in order to obtain their sparse solutions, which is a feasible approach to overcome challenges coming from the big data nature of most practical applications. It is the goal of this paper to provide a systematic study of the representer theorems for these problems in Banach spaces. There are a few existing results for these problems in a Banach space, with all of them regarding implicit representer theorems. We aim at obtaining explicit representer theorems based on which convenient solution methods will then be developed. For the minimum norm interpolation, the explicit representer theorems enable us to express the infimum in terms of the norm of the linear combination of the interpolation functionals. For the purpose of developing efficient computational algorithms, we establish the fixed-point equation formulation of solutions of these problems. We reveal that unlike in a Hilbert space, in general, solutions of these problems in a Banach space may not be able to be reduced to truly finite dimensional problems (with certain infinite dimensional components hidden). We demonstrate how this obstacle can be removed, reducing the original problem to a truly finite dimensional one, in the special case when the Banach space is $\ell_1(\mathbb{N})$.
أَثر انموذج الرحلات المعرفیة فی تنور تکنولوجیا التعلیم لطلاب الصف الثانی المتوسط فی مادة الاحیاء

This study aims to know the effect of applying the cognitive journeys model on technological enlightenment for biology students in the second intermediate grade, as the following null hypothesis was developed to verify this goal: - There is no statistically significant difference in the technological enlightenment scale at the level of (0.05) between the average scores of students who study by applying the model of cognitive trips in the experimental group, and the average scores of students who study in the usual way in the control group. This experiment was applied in the second semester of the academic year (2018-2019) on an intended sample of students, most of them males, in the second intermediate grade, the sample included (42) students, who were distributed randomly to the two groups (control and experimental) equally, the experimental design was adopted. The post-test and partial adjustment of two equal groups, where three chapters (seventh, eighth, and ninth) of the biology textbook were taught for the second intermediate grade, and the research tool represented by the Technological Enlightenment Scale was prepared, which consists of (30) items distributed into three main areas (knowledge , Skill, and sentimental) and the validity and reliability of its construction were verified against the Cronbach alpha measurement (72%). Several statistical methods such as arithmetic averages, the Mann-Whitney test and the Pearson correlation coefficient were adopted to analyze the data that showed no statistically significant difference between both groups (experimental and control) in the electronic enlightenment scale.
Encrypted Cloud Storage Merge Data Manager and Server Access Control

Individuals back the extraordinary control of cloud computing, but since of the need of user-to-cloud access, the cloud providers cannot rely entirely on privacy details. Data controllers use encrypted data rather than plain-texts to ensure secrecy. For exchanging encrypted files with other users, a fine grained and proprietary access protection can be achieved by Cipher text-Policy Attribute-based Encryption (CP-ABE). But against other threats, this is not safe enough. Most prior programs have not allowed the cloud provider to test whether a down-loader can decode. In this way, all of these records utilized for cloud capacity ought to be accessible. An assailant can download thousands of records in arrange to dispatch the Cloud Resource's Financial Refusal of Supportability (EDoS) assaults. The burden is paid by the cloud payer. The cloud provider also acts both as administrator and as payer, without the data owners being transparent, of the resource consumption bill. For real public cloud storage, these issues should be addressed. In this article, we are proposing a method for protecting secure EDoS data and the control of resource consumption. This black-boxes CP-ABE systems and conforms to unreasonable CP-ABE entry rules. In addition to performed and protection analyzes, we propose two guidelines for different settings.
Fuzzy Algebraic Theories.

In this work we propose a formal system for fuzzy algebraic reasoning. The sequent calculus we define is based on two kinds of propositions, capturing equality and existence of terms as members of a fuzzy set. We provide a sound semantics for this calculus and show that there is a notion of free model for any theory in this system, allowing us (with some restrictions) to recover models as Eilenberg-Moore algebras for some monad. We will also prove a completeness result: a formula is derivable from a given theory if and only if it is satisfied by all models of the theory. Finally, leveraging results by Milius and Urbat, we give HSP-like characterizations of subcategories of algebras which are categories of models of particular kinds of theories.
Personalized CAPTCHA Using Cognitive Cryptography

Cognitive Cryptography is used to improve personal verification process using the individual’s characteristics. The personal information contained can be biometrics because it is the unique information that identifies the owner. In advanced cryptographic protocol oriented for authentication of user, there is a possibility of using personal characteristics and perception abilities are required to create a new authentication procedure. This paper presents a new approach for creation of advanced multilevel user authentication protocol by using Image grid CAPTCHA codes. Here the user needs the special skills or knowledge while verifying, this is because of cognitive CAPTCHA’s. Instead of generating some random numbers or text while authentication procedure these CAPTCHA’s can be used. In multilevel authentication code the user verification can be realized in several iterations, in which the user attention can be oriented on different visual elements, region of interest or semantic content. This cognitive code will able to identify the recognition abilities of the user. Cognitive codes are having high security feature similar to traditional CAPTCHA’s because of understanding or recognizing the blurred or distorted patterns and also requires background knowledge to experience the connection with evaluated patterns. This feature guarantees the high level of security and allows to get succeeded in authentication process because the user possess specific skill that or not available for computers or answering systems. The traditional authentication protocols are to be involved with human mental capability is the vital idea of the proposed solution.
Music Sentiment Transfer

Music sentiment transfer is a completely novel task. Sentiment transfer is a natural evolution of the heavily-studied style transfer task, as sentiment transfer is rooted in applying the sentiment of a source to be the new sentiment for a target piece of media; yet compared to style transfer, sentiment transfer has been only scantily studied on images. Music sentiment transfer attempts to apply the high level objective of sentiment transfer to the domain of music. We propose CycleGAN to bridge disparate domains. In order to use the network, we choose to use symbolic, MIDI, data as the music format. Through the use of a cycle consistency loss, we are able to create one-to-one mappings that preserve the content and realism of the source data. Results and literature suggest that the task of music sentiment transfer is more difficult than image sentiment transfer because of the temporal characteristics of music and lack of existing datasets.
Security and Efficiency Trade-offs for Elliptic Curve Diffie-Hellman at the 128-bit and 224-bit Security Levels

Within the transport layer security (TLS) protocol version 1.3, RFC 7748 specifies elliptic curves targeted at the 128-bit and the 224-bit security levels. For the 128-bit security level, the Montgomery curve Curve25519 and its birationally equivalent twisted Edwards curve Ed25519 are specified; for the 224-bit security level, the Montgomery curve Curve448, the Edwards curve Edwards448 (which is isogenous to Curve448) and another Edwards curve which is birationally equivalent to Curve448 are specified. Our first contribution is to provide the presently best known 64-bit assembly implementations of Diffie–Hellman shared secret computation using Curve25519. The main contribution of this work is to propose new pairs of Montgomery–Edwards curves at the 128-bit and the 224-bit security levels. The new curves are nice in the sense that they have very small curve coefficients and base points. Compared to the curves in RFC 7748, the new curves lose two bits of security. The gain is improved efficiency. For Intel processors, we have made different types of implementations of the Diffie–Hellman shared secret computation using the new curves. The new curve at the 128-bit level is faster than Curve25519 for all types of implementations that we considered, while the new curve at the 224-bit level is faster than Curve448 using 64-bit sequential implementation using schoolbook multiplication, but is slower than Curve448 for vectorized implementation using Karatsuba multiplication. Overall, the new curves provide good alternatives to Curve25519 and Curve448.