Reviewerly/exHarmony huggingface dataset:
ВДОСКОНАЛЕНА ПОЛІНОМІАЛЬНО-СКЛАДНА АТАКА ВІДНОВЛЕННЯ ВІДКРИТОГО ТЕКСТУ НА РАНЦЕВИЙ ШИФР НА ОСНОВІ МАТРИЦЬ

Asymmetric ciphers are widely used to ensure the confidentiality of data transmission via insecure channels. These cryptosystems allow the interacting parties to create a shared secret key for a symmetric cipher in such a way that an eavesdropper gets no information useful for cryptanalysis. Network security protocols that use asymmetric ciphers include TLS, S/MIME, OpenPGP, Tor, and many others. Some of the asymmetric encryption schemes are homomorphic, that is, that they allow calculations on encrypted data to be performed without preliminary decryption. The aforesaid property makes possible using these cryptosystems not only for symmetric key establishment but also in several areas of application, in particular in secret voting protocols and cloud computing. The matrix-based knapsack cipher is a new additively homomorphic asymmetric encryption scheme, which is based on the properties of isomorphic transformations of the inner direct product of diagonal subgroups of a general linear group over a Galois field. Unlike classic knapsack encryption schemes, the cryptographic strength of this cipher depends on the computational complexity of the multidimensional discrete logarithm problem. Despite some useful properties, further research into the cryptographic strength of the matrix-based knapsack cipher has found serious drawbacks inherent in this cryptographic scheme. In the given paper an improved polynomial-time plaintext-recovery attack on the matrix-based knapsack cipher is proposed. Applying this cryptanalytic method requires only public information and has time complexity O(t1.34), where t denotes the decryption time of the attacked cryptosystem. The aforementioned attack is more productive and easier to implement in software in comparison with the original one. The advantages of the proposed method are due to using in its algorithm the simple and relatively fast matrix trace operation instead of more complex and slower transformations.
Disasters: Spatio-Temporal Distribution of Dhankuta District, Nepal

This paper attempts to analyze the temporal and spatial distribution of disaster in Dhanktua district, Nepal. It provides information regarding when and where the disasters have mostly occurred in Dhankuta. Disaster can occur at any time at anywhere although every disaster has a temporal and spatial dimension which helps to predict the future events In this context, this paper provides the history and trend of disasters in Dhankuta. This paper is based on mostly secondary data extracted from the Ministry of Home Affairs, Disaster Risk Reduction (DRR) Portal. To analyze this, mostly descriptive methods has been applied where the quantitative method also applied for the reflection of disaster data. Fire, landslide, heavy rainfall and thunderbolt were the major disasters that frequently occurred in this district during 2017-2019. It is found that fire incidents were frequently occurred in the month of March, the landslide in July, heavy rainfall in July and thunderbolt in April. It is interesting that, those years where the incidents of fire were higher the incidents of the landslide were low and vice versa and there is a positive relationship between landslide and heavy rainfall. This study will important to local levels and relevant agencies for disaster preparedness because the impact of the disaster is based on the level of preparedness. This analysis is based on limited data which covered 10 March 2017 to 31 December 2019. This study provides a new perspective in the field of disaster where temporal and spatial dimensions are considered.
Predicting Long-Term Skeletal Motions by a Spatio-Temporal Hierarchical Recurrent Network

The primary goal of skeletal motion prediction is to generate future motion by observing a sequence of 3D skeletons. A key challenge in motion prediction is the fact that a motion can often be performed in several different ways, with each consisting of its own configuration of poses and their spatio-temporal dependencies, and as a result, the predicted poses often converge to the motionless poses or non-human like motions in long-term prediction. This leads us to define a hierarchical recurrent network model that explicitly characterizes these internal configurations of poses and their local and global spatio-temporal dependencies. The model introduces a latent vector variable from the Lie algebra to represent spatial and temporal relations simultaneously. Furthermore, a structured stack LSTM-based decoder is devised to decode the predicted poses with a new loss function defined to estimate the quantized weight of each body part in a pose. Empirical evaluations on benchmark datasets suggest our approach significantly outperforms the state-of-the-art methods on both short-term and long-term motion prediction.
Erythrocyte Morphology in Women of Reproductive Age (WORA) with Anemia

Anemia is a decrease in the number of erythrocytes in the blood circulation or the level of hemoglobin that is less than normal. The three major body mechanisms that cause anemia are excessive destruction of erythrocytes, blood loss, and decreased erythrocyte production. Based on the Basic Health Research (Riskesdas) in 2013, the prevalence of anemic women of reproductive age (WORA) aged 15-44 years in Indonesia was 35.3%. Anemia is classified based on the morphology of erythrocytes, including hypochromic microcytic, normocytic normochromic, and macrocytic. Erythrocyte morphology can be observed using peripheral blood smear examination. The objective of this study was to determine the morphology of erythrocytes in anemic women of reproductive age. This study belongs to descriptive research. The population of the study was 136 women of reproductive age, covering the students of D-IV in Medical Laboratory Technology at Setia Budi University. Forty-one respondents suffering from anemia were taken using a purposive sampling technique. The types of anemia were determined with examination using an Easy Touch hemoglobinometer with the Hb level of less than 12g/dL. Preparation of peripheral blood smear examination using EDTA venous blood and stained with Giemsa. Microscopic examination was performed with 1000x objective magnification. The peripheral blood smear reading showed the erythrocyte morphology that includes normocytic normochromic (38 samples or 93%), microcytic hypochromic (three samples or 7%), and poikilocytosis consisting of teardrop cells, target cells, ellipstocytes, and stomatocytes (five samples or 18%). Further study is required to investigate the correlation of erythrocyte index and peripheral blood smear in anemia.
Security ambiguity and vulnerability in G2C eGovernance system: Empirical evidences from Indian higher education

The Higher Education Institutions (HEIs) in India enhanced dependency on Information Communication Technology (ICT) based on G2C eGovernance applications persistently raised apprehension regarding cyber-attacks and breach of security.Objectives:The present study assesses the status of ambiguity and vulnerability pertaining to security aspects of HEIs G2C eGovernance web portals.Methods:Five prominent central and state HEIs i.e.
AN ANALYSIS OF ENGLISH LANGUAGE AND LITERATURE DEPARTMENT STUDENTS’ ABILITY IN CONSTRUCTING ADJECTIVE CLAUSE IN ESSAY WRITING

Grammar is an essential language component that should be concerned to create a good writing, no exception to the use of adjective clause. However, there are still some problems identified in the adjective clause construction. The purpose of the research is to figure out students’ ability in constructing adjective clause. The design used in this research is descriptive research with second year students of English Language Education Program of UNP as the research population. There were 31 students taken as the research sample selected by using stratified sampling technique out of 162 students. The data were collected through document analysis and Hortatory Exposition essays were chosen as the source of the data. The essays were analyzed by two raters and the score was classified based on score classification. Then, the problems were identified from the students’ adjective clause construction in the essays. The result of the study showed that the students’ ability in constructing adjective clause is categorized into excellent with the average percentage 87. 94%. The common problem found in the students’ adjective clause construction is in sentence element which has total 37.04% problems identified. Students tend to disregard the element of the sentence, such as subject and verb.
Influence of Visual Support Media in Developing Expressive Language and Logical Thinking of Children Aged 4-5 Years in Inclusion Kindergarten Sidoarjo District

The research objectives were to (1) examine the effect of visual support media on the development of expressive language and logical thinking of children aged 4-5 years in inclusion kindergarten; (2) examining the effect of visual support media on the development of language expression and logical thinking in children aged 4-5 years in inclusive kindergartens; Type and quantitative research design with a quasi-experimental design type of non-equivalent control group. The sample used in the study was Kindergarden Diti School class A1 with 15 students and class A2 with 10 students as the experimental class; and TK Batik class A1 15 students and class A2 10 students as the control class. Data collection techniques using tests and observations. Data analysis techniques used analysis of variance (ANOVA) and MANOVA. The results showed that the SPSS output obtained a significance probability value &lt;0.05, so it could be concluded that Ho was rejected and H1 was accepted, meaning (1) there was a significant influence between visual support media on expressive language development and logical thinking in children aged 4-5 years in Inclusion Kindergarten. Future research is expected to test media and educational aids that can develop expressive language and logical thinking.
Efficient GPU Implementation of Multiple-Precision Addition based on Residue Arithmetic

In this work, the residue number system (RNS) is applied for efficient addition of multiple-precision integers using graphics processing units (GPUs) that support the Compute Unified Device Architecture (CUDA) platform.The RNS allows calculations with the digits of a multiple-precision number to be performed in an element-wise fashion, without the overhead of communication between them, which is especially useful for massively parallel architectures such as the GPU architecture.The paper discusses two multiple-precision integer algorithms.The first algorithm relies on if-else statements to test the signs of the operands.In turn, the second algorithm uses radix complement RNS arithmetic to handle negative numbers.While the first algorithm is more straightforward, the second one avoids branch divergence among threads that concurrently compute different elements of a multiple-precision array.As a result, the second algorithm shows significantly better performance compared to the first algorithm.Both algorithms running on an NVIDIA RTX 2080 Ti GPU are faster than the multi-core GNU MP implementation running on an Intel Xeon 4100 processor.
Computer Music Technologies in the System of Present-Day Musical Education: An Attempt of Terminological Analysis

Computer music technologies present an autonomous section in the domain of contemporary informational technologies, a complex of programs and apparatuses which makes it possible to carry out operations with sounds, to create and edit musical material, to form and perfect the process of musical education. The development of the methodology of mastery of this new category of musical instruments, as well as its developing international scholarly significance pose the problem of elaboration and utilization of a single terminological apparatus which could categorize the present phenomenon most precisely and fully. The article offered by the authors aims at revealing the possibilities of generalization of terminological elaborations existing in of various scholarly and pedagogical schools and traditions. Keywords: methodology of scholarship, computer music technologies, scholarly methodology.
An efficient storage-optimizing tick data clustering model

Tick data is a large volume of data, related to a phenomenon such as stock market or weather change, with data values changing rapidly over time. An important issue is to store tick data table in a way that it occupies minimum storage space while at the same time it can provide fast execution of queries. In this paper, a mathematical model is proposed to partition tick data tables into clusters with the aim of minimizing the required storage space. The genetic algorithm is then used to solve the mathematical model which is indeed a clustering model. The proposed method has been evaluated on a real-world weather tick dataset and compared to the storage-optimizing hierarchical agglomerative clustering (SOHAC) algorithm. The experiments show that our proposed method substantially outperforms SOHAC in achieving smaller values for compression ratio while reducing the execution time for small number of clusters.
AN EFFICIENT RESOURCE SELECTION AND ALLOCATION IN CLOUD COMPUTING USING ARTIFICIAL NUTRIENTS DISTRIBUTION MODEL

The recent emergence of cloud computing and its rapid advancement in recent time indicates a promising technology. However, the increasing number of providers with different policies has induced a challenge for customers to select providers that can efficiently satisfy their requirements. This research work is regarding resource selection and allocation in cloud computing using artificial nutrients distribution model. Cloud computing makes it possible for system administrators to allocate resources whenever it is required. It provides multiple servers that are expandable and can meet future needs without buying any physical computer equipment. Because there are lots of providers available commercially selection of resources from reliable provider has become difficult for cloud users. This research proposed a new intelligent model using the idea of nutrients distribution in human body to optimally select and allocate resources in cloud. This model enables users to efficiently select resources from the integrated providers as a single unit of resource pool. The model intelligently evaluates the available resources from different providers and expeditiously selects a resource of highest value for the customer. This research has designed an intelligent architecture, algorithm and the UML model for Resource Selection, Evaluation and allocation. The simulation showed that the overhead cost of searching from one provider to another as opposed to the existing methods is minimized. This model is of good quality and could obtain solution with a worthy efficiency by only making a single selection attempts as providers’ resources are interwoven to a single resource pool.
Approaching Quantum-Optimal Imaging without Prior Knowledge of the Object Location

Spatial-mode-sorting (SPADE) receivers surpass Rayleigh’s criterion for in coherent imaging but are sensitive to nuisance parameters (e.g., misalignment). Our multistage detection strategy uses preliminary physical measurement(s) to build up required prior information for near-quantum-optimal, sub-diffraction imaging.
Changes in Education under the Influence of Digital Technologies: main Problems and Risk of Division

Digital technologies are rapidly changing the process of education. Online courses have become a common tool of gaining knowledge outside the university. Multimedia education, penetrating traditional educational institutions (schools, colleges, and universities), changes the structure of education and brings new elements to the communications during the educational process. This article considers one level of change in the model of education. On the one hand, there are advantages associated with the democratization of education. At the time of their foundation, universities were the creators of new elites – scientific and educational meanwhile, in the twenty-first century, the process of democratization and the accessibility of university education has been linked to the digitalization. On the other hand, territorial and other restrictions have been lifted. And this is a very controversial process that poses many challenges for students, one of the most noticeable of which is the lack of real contact with the teacher and the transformation of the educational process into an ”educational conveyor belt.” At the same time, personal contact with the teacher is becoming more expensive. The authors have collected studies that examine the dynamics of this emerging stratification of education. Based on the work of the pioneers in the study of digital education, the authors develop their ideas, focusing on the formation of the modern models of education, defined as affordable electronic and elite traditional.&#x0D; Keywords: online courses, online education, MOOC
Towards a Model of Learner-Directed Learning: An Approach Based on the Co-construction of the Learning Scenario by the Learner

To improve the learning process, the evolution of learner's characteristics (cognitive, affective, prior knowledge, workflow, organization, …) must be taken into account during the personalization or adaptation. This requires generating several scenarios (a description of activities, their order and links in the learning sequence as well as the expected outcome for the learner) adapted to the identified profiles. We propose a model which aims at improving learners' learning processes by giving them control over two key aspects: (1) the steps of the learning scenario to be followed: after each learning goal is completed, the learner chooses the next one among several possible ones (in terms of their current knowledge) while respecting pedagogical constraints (time and quality of the solutions produced according to satisfaction thresholds); (2) the assessment mode: the learner chooses a mode corresponding to their own goals in terms of mastery, while respecting the minimum thresholds set by the teacher. We assess our approach with learners in terms of (a) adequacy of the model with learners' expectations and (b) usability of the system through self-report questionnaires and an analysis of the data collected over 16 learners who used an implementation of our system on the LMS (Learning Management System) in the context of a real computer course. The results reveal that our model is mostly well-received, that various scenarios are indeed followed by the learners and that the 3 assessment modes have been used by learners.
Multiple object tracking using feature fusion in hierarchical LSTMs

Multiple object tracking sets the foundation for many intelligent video applications. The authors present a novel tracking solution using the ability of recurrent neural networks to effectively model complex temporal dynamics between objects irrespective of appearances, pose, occlusions, and illumination. For online tracking, a real-time and accurate association of objects with active tracks poses the major algorithmic challenge. Additionally, re-entry of objects should also be correctly resolved. They follow tracking-by-detection methodology using hierarchical long short term memory (LSTM) network structure for modelling the motion dynamics between objects by learning the fusion of appearance and motion cues. Existing works capture object's perspective for tracking within the detected bounding boxes. They also incorporate object instance segments for track modelling by applying the maskRCNN detector. They present a novel motion coding scheme that anchors the LSTM structure to effectively model the motion and relative position between objects in a single representation scheme. The proposed motion representation and deep features representing objects appearances are fused in an embedded space learned by the hierarchical LSTM structure for predicting the object to track association. The authors present experimental validation of the proposed approach on multiple object tracking challenge datasets and demonstrate that their solution naturally deals with major tracking challenges under all uncertainties.
Framework and Solution for Assigning Shares to Communication Network Domains under Secret Sharing Scheme

We describe a framework for assigning shares to communication network domains, where shares are split data in the secret sharing scheme. The secret sharing scheme offers higher security than that of the encryption scheme in some situations, such as when the hardware containing the data is stolen. The previous research focused on how to make it impossible for shares to be recovered without aggregating them. Here, we claim that the security of this scheme depends on the domains the shares are assigned to. We formulate a mathematical model of secret sharing among different network domains and propose an evaluation measure of security strength together with its evaluation algorithm. Numerical examples show the effectiveness of our model, measure, and algorithm.
Reinventing Universities: Agile Project Management in Higher Education

Universities worldwide are facing similar problems, decrease in public funding, increase of international competition and slow bureaucratic organization.One of the possibilities to increase flexibility and to respond better to students' needs and job market changes is implementing Agile Project Management practices.Both Agile and its most popular Scrum methodology have origins in Software development but have been successfully adopted in other industries as well.This paper examined specific Agile Project Management practices that can be implemented in different areas of Universities, such as Governance and Structure, Curriculum Design, Teaching, Learning, Evaluation, Online Courses and Virtual Classroom.It is concluded that Universities could foster benefits by implementing Agile practices partly, incrementally or by having a full Agile transformation, but either way a goodwill to test it and internal champions to lead the change represent crucial elements of such transformation.
ANALISIS EFIKASI DIRI DAN HASIL BELAJAR BERBASIS E-LEARNING PADA MAHASISWA PROGRAM STUDI PENDIDIKAN MATEMATIKA

The purpose of this study is to see the relationship between self-efficacy and e-learning-based learning results in students of semester 4 of Flores university mathematics education study program. The research method used in this study is quantitative research, with linear regression analysis using SPSS with a random sample of 40 fourth semester students. The data analysis techniques used are the Prerequisite Test (Kolmogorov–Smirnov Normality Test) and its research Hypothesis test using Pearson Bivariate correlation analysis with the help of SPSS. The results of this study show self-efficacy (X) has a positive influence on e-learning based Learning Results (Y) known from the results of correlation analysis obtained from the value of R count to X to Y of 0.895 and the value of significance between X to Y obtained two asterisks (**) so that there is a positive influence with a significance level of 1%. In other words, better or better self-efficacy will increase the learning outcomes of the students themselves.