Reviewerly/exHarmony huggingface dataset:
Publication of a scientific article in for an english-language journal. Part 5

This article is the continuation of analysis and discussion from the book by Professor AI Nevorotin "Matrix phraseological collection: a manual for writing a scientific article in English". The Matrix phraseological collection is a kind of catalog of text samples. The samples were from articles selected from the leading English-language scientific journals and were systematized in such a way that when writing an article in English, Russian researchers are able easy to find examples suitable for his/her own work. Furthermore, the selected samples can be transformed accordingly saving the semantic and syntactic relations between the elements and, finally, be inserted into the text. The next, fifth, article of this series is devoted to the comparative evaluation of experimental findings. Particular attention is drawn to the description nuances of the biological processes' course. Preferred phrases and most relevant terms are presented.
Numeric Encoding Options with Automunge

Mainstream practice in machine learning with tabular data may take for granted that any feature engineering beyond scaling for numeric sets is superfluous in context of deep neural networks. This paper will offer arguments for potential benefits of extended encodings of numeric streams in deep learning by way of a survey of options for numeric transformations as available in the Automunge open source python library platform for tabular data pipelines, where transformations may be applied to distinct columns in “family tree” sets with generations and branches of derivations. Automunge transformation options include normalization, binning, noise injection, derivatives, and more. The aggregation of these methods into family tree sets of transformations are demonstrated for use to present numeric features to machine learning in multiple configurations of varying information content, as may be applied to encode numeric sets of unknown interpretation. Experiments demonstrate the realization of a novel generalized solution to data augmentation by noise injection for tabular learning, as may materially benefit model performance in applications with underserved training data.
Penggunaan OJS untuk Penerbitan Jurnal Penelitian dengan studi kasus pada Kelompok Keahlian T.Telekomunikasi, STEI, ITB

Utilization of an online journal management system at one of the expertise group institutions in Bandung still needs some development, especially in the case of journal publications where the expertise group needs to have its own journal management system. For this reason, research and development of a system that is suitable to meet the needs of online journal management is needed. The system used in managing this journal is the Open Juornal System or abbreviated OJS. This journal management system has several advantages compared to the system currently being used by researchers, namely the merging of publication and publication management, the use of plugins and indexation optimization. Implementation of the research includes the process of sending articles, reviewing articles, editing articles and publications. Implementation also includes the process of indexation, customization, and accreditation. The results of research and implementation arrangements indicate the use of OJS can be used as a journal management system properly according to the needs of the institution. Journal management needs to be developed in the process of legalization and accreditation. Further analysis is needed regarding the use and selection of tool and plugin features.
Relationship between education and economic development in building a knowledge economy

The paper deals with the interrelation between the economy and the educational system in the state, the dependence of their development. The authors show it by the example of two contrasting countries in terms of development, Norway and the Central African Republic. The article considers the position of these countries in various ratings reflecting the success of the policy pursued in the state. The authors point to the general characteristics of the economies and education systems of each of the countries under consideration. Emphasis is placed on the fact that education policy and the successful functioning of education itself have an impact on the sustainable development of the state, and the indicators of management effectiveness in the education system and changes in its financing are important aspects of this policy. The paper looks at "educational services" and "education services market" as economic categories. The field of educational services is considered to be one of the most developed economic sectors, because of its productive and profitable function. The article describes the importance and relevance of such science as the knowledge economy and its impact on the development of a competitive economy. The knowledge economy researches features of action of laws of economy in education and preparation of qualified experts for increase of level of knowledge of the population.
DEVELOPING PROFESSIONAL CREATIVE SKILLS OF FUTURE TEACHERS IN THE TECHNOLOGY FIELD OF EDUCATION

The ongoing renewal of educational technologies in higher education, the introduction of innovative didactics, the formation of the education, development, and personal growth systems of the future specialist within the university are faced initially with a number of intractable psychological and pedagogical problems. The most significant of them are associated with the fact that not all teachers are ready today to become the innovative personnel in their field of specialization. of innovation [1]. It is more and more obvious that the creativeness of an individual cannot be the result of mass systems and forms of education. Modern education on the verge of entering the information age can become a cultural space that will allow a person to acquire a new cultural identity. But at the same time, the world of education must change itself significantly. Determination of the personal qualities of the future teacher, the characteristics of his professional activity and progress, the formation of self-development skills is today one of the main directions of improving teacher training. The preparation of a future teacher should be built as a system of conditions for ensuring the professional and self development. It is necessary that a novice teacher theoretically and practically be able to analyze his or her own professional capabilities and, on this basis, be able to form a routine for his own further professional growth at any stage of professional activity. This can be achieved by creating a desire of future teachers.to be ready for professional self-development. A pedagogical institution needs to prepare future specialists for creative pedagogical activity, in which the acquired professional skills will be a means of developing the student's personality as well. The most important component of such training is an advanced creative imagination and the ability to evolve it. If in-depth knowledge is a platform for training a new generation of competent specialists, then creative activity is a springboard that gives them an advantage in everyday professional field, therefore, at the moment, the need to develop a technology for developing creative skills of students of the pedagogical institutions is of especial relevance
Detection of phishing attacks using probabilistic neural network with a novel training algorithm for reduced Gaussian kernels and optimal smoothing parameter adaptation for mobile web services

The rapid escalation of smartphones and online transactions increases the rate of phishing attacks that exploit the user credentials for fraudulent financial gains. The existing detection methods suffer from low detection accuracy and high false positive rate (FPR). In this study, the probabilistic neural network (PNN) with a novel training algorithm is used for detecting phishing attacks. A novel fuzzy dense K-modes (FDKM) clustering algorithm is proposed for obtaining the Gaussian kernels in pattern layer. Moreover, the proposed optimisation procedure called modified harmony search with generation regrouping (MHS_GR) finds the optimal smoothing parameter for training the network. The proposed approach was evaluated on benchmark phishing datasets obtained from UCI machine learning repository and on our Phish_Net dataset. The experimental results reveal that the proposed PNN with MHS_GR (PNN_HS3) obtained 98.53%, 96.92%, and 97.12% of detection accuracy and 2.02%, 3.39%, and 3.12% of FPR for UCI_1, UCI_2, and Phish_Net dataset respectively.
Mutual information-assisted Adaptive Variational Quantum Eigensolver Ansatz Construction

Adaptive construction of ansatz circuits offers a promising route towards applicable variational quantum eigensolvers (VQE) on near-term quantum hardware. Those algorithms aim to build up optimal circuits for a certain problem. Ansatz circuits are adaptively constructed by selecting and adding entanglers from a predefined pool in those algorithms. In this work, we propose a way to construct entangler pools with reduced size for those algorithms by leveraging classical algorithms. Our method uses mutual information (MI) between the qubits in classically approximated ground state to rank and screen the entanglers. The density matrix renormalization group (DMRG) is employed for classical precomputation in this work. We corroborate our method numerically on small molecules. Our numerical experiments show that a reduced entangler pool with a small portion of the original entangler pool can achieve same numerical accuracy. We believe that our method paves a new way for adaptive construction of ansatz circuits for variational quantum algorithms.
Kemampuan Menulis Recount Text dengan Menggunakan Teknik Picture Series pada Kelas VIII di SMP Negeri 3 Baubau

This study aimed at finding out whether the use of picture series technique can improve students writing skill of recount text or not. The subject of this research was 31 students of class VIII SMPN 3 Baubau. This was a classroom action research involving four steps in each cycles, they are planning, action, observation, and reflection. The instruments of this research were test, observation, questionnaires and documentations. The data analysis was presented in the table and chart of progressive analysis, and also in descriptive explanation.&#x0D; The result of quantitative analysis showed that using of picture series can improve students writing skill of the eight grade student of SMP Negeri 3 Baubau. It can be seen from the result of the students’ writing tests and the student‘s involvement which increased continuously during the application of the techniques. The mean score of students was 70.22 before techniques applied as the indications that this score categorized into a insufficient level. After having treatment in the first cycles, the student‘s mean sco improved to 75.15 which categorized into a sufficient level. In the second cycles, the student‘s mean score54 which improved was categorized good to level.79. This improvement was supported by qualitative data.
DEALING WITH SPEAKING ANXIETY; A CASE STUDY OF THE IMPLEMENTATION OF SIDANG AKADEMI AT A SCHOOL IN CENTRAL JAVA

Speaking skill becomes a very important issue in second language acquisition. Among the four English skills being developed, speaking is crucial for students. Speaking anxiety is one of the burdens experienced by the students so that the exploration of the willingness to communicate is needed to maintain the problem. Moreover, in the Indonesian context, English is still a second/ foreign language so that when the student is required to speak in public using English the problem will be double. This research discussed the implementation of Sidang Akademi (Academic Preliminary Meeting) in a private Senior High School in Central Java as an obligatory activity for the students. This research employs a qualitative study specifically a case study. The result of the study presents that the implementation of the activity causes the student to experience speaking anxiety caused by many factors. There are also some ways in managing speaking performance conducted by the student in the implementation of the activity.
PROPUESTA DE GESTIÓN DE INFORMACIÓN PARA TRABAJOS DE LAS MATERIAS DE TALLER DE INVESTIGACIÓN 1 Y 2 DEL INSTITUTO TECNOLÓGICO DE PINOTEPA (PROPOSAL OF INFORMATION MANAGEMENT FOR WORKS IN THE SUBJECTS OF RESEARCH WORKSHOP 1 AND 2 OF THE TECHNOLOGICAL INSTITUTE OF PINOTEPA)

Resumen En este trabajo se presenta una propuesta para la gestion de la informacion en trabajos de investigacion. La metodologia consta de cinco pasos. El paso uno es la determinacion del tema del trabajo de investigacion, el cual sera la base para el paso dos. El paso dos es la determinacion de fuentes de informacion, las cuales son seleccionadas de acuerdo a la revista objetivo. El paso tres es el proceso de revision de los articulos. El paso cuatro consiste en la clasificacion de los articulos de acuerdo a las caracteristicas del tema, objetivos del trabajo y resultados, los datos mas importantes se registran en una tabla. Finalmente, el paso cinco consiste en almacenar la informacion en formato electronico para su uso posterior. Esta metodologia tiene por objetivo servir de base a futuros investigadores. Dentro del trabajo se muestran ejemplos en cada paso. Finalmente se presentan las conclusiones. Palabras Clave : Gestion de la informacion, trabajos de investigacion, metodologia. Abstract This document presents a proposal for information management in research work. The Methodology consists of five steps. Step one is basically determinate the research topic itself through certain mechanisms in order to make the research functional. Step two is meant to set the information sources, which are intended to be the most optimal for the investigation overall. Step three consist in the revision of the veracity of the articles, thus, the entire support of the research lays here. Step four consists in the classification of the articles according to topic´s characteristics and objectives. Finally, step five consists in store the information in electronic format for later use. This methodology has its primal purpose in helping other investigators ease their work by giving them a trustworthy method to research successfully. Keywords : Information management, Investigation work, methodology.
Towards quantum simulation of spin systems using continuous variable quantum devices

We study Bosonic representation of spin Ising model with the application of simulating two level systems using continuous variable quantum processors. We decompose the time evolution of spin systems into a sequence of continuous variable logical gates and analyze their structure. We provide an estimation of quantum circuit scaling with the size of the spin lattice system. Furthermore, we discuss the possibility of using a Gaussian Boson sampling device to estimate the ground state energy of Ising Hamiltonian. The result has potential application in developing hybrid classical-quantum algorithms such as continuous variable version of variational quantum eigensolver.
Federated Averaging as Expectation Maximization

Federated averaging (FedAvg), despite its simplicity, has been the main approach in training neural networks in the federated learning setting. In this work, we show that the algorithmic choices of the FedAvg algorithm correspond to optimizing a single objective function that involves the global and all of the shard specific models using a hard version of the well known Expectation-Maximization (EM) algorithm. As a result, we gain a better understanding of the behavior and design choices of federated averaging while being able to provide interesting connections to recent literature. Based on this view, we further propose FedSparse, a version of federated averaging that employs prior distributions to promote model sparsity. In this way, we obtain a procedure that leads to reductions in both server-client and client-server communication costs as well as more efficient models.
Blockguard: Adaptive Blockchain Security (Short Paper)

We change the security of blockchain transactions by varying the size of consensus committees. To improve performance, such committees operate concurrently. We present two algorithms that allow adaptive security by forming concurrent variable size consensus committees on demand. One is based on a single joint blockchain, the other is based on separate sharded blockchains. For in-committee consensus, we implement synchronous Byzantine fault tolerance algorithm (BFT), asynchronous BFT and proof-of-work consensus. We evaluate the performance of our adaptive security algorithms.
Using Grammatical Cohesion in the Students’ Final Project Proposal (A Case Study in UIN Walisongo Semarang in Academic Year 2019/2020)

The practice of grammatical cohesion is broadly significant to be procedurally employed for the students to accomplish academic writing.This scientific study informed how the grammatical cohesion in the texts applied to show the unity of the texts.This study was qualitatively designed to inform the units of grammatical cohesion which were realized in a single text of students' manuscripts.The researcher served the documentation sheet as the principal instrument to classify the type of grammatical cohesion.The data analysis was taken from 10 manuscripts of the English students in UIN Walisongo in Academic Year 2019/2020.The findings then showed that the most usage of grammatical cohesion was grammatical conjunction with 238 occurrences, whereas the grammatical reference was 235 times; the grammatical ellipsis was 13 times, while the grammatical substitution was only 6 times.This study influenced students' writing competence where they were advantaged to organize the final manuscript cohesively besides the teaching and learning practice.
Towards Robust and Efficient Contrastive Textual Representation Learning

There has been growing interest in representation learning for text data, based on theoretical arguments and empirical evidence. One important direction involves leveraging contrastive learning to improve learned representations. We propose an application of contrastive learning for intermediate textual feature pairs, to explicitly encourage the model to learn more distinguishable representations. To overcome the learner's degeneracy due to vanishing contrasting signals, we impose Wasserstein constraints on the critic via spectral regularization. Finally, to moderate such an objective from overly regularized training and to enhance learning efficiency, with theoretical justification, we further leverage an active negative-sample-selection procedure to only use high-quality contrast examples. We evaluate the proposed method over a wide range of natural language processing applications, from the perspectives of both supervised and unsupervised learning. Empirical results show consistent improvement over baselines.
Predicting Response Time of Concurrent Queries with Similarity Models

Predicting query response time is an essential task for managing database systems, especially in modern large distributed data centers that execute heterogeneous query workloads concurrently. The core of such a model is to quantify query interaction, which is neglected by the state of the art models. This paper proposes a novel model that estimates query response time based on the similarity of query mixes. We introduce a notion called query rating for constructing the feature vector of a query and developed a measure of the similarity between two query mixes. We propose a static similarity model to estimate the response time of a query by using that of the most similar query mixes containing the query. We also build a dynamic model based on the static model to predict the remaining execution time of a query on-the-fly whenever a new query mix forms. A scheduling method is proposed with the similarity models as the key enablement, which schedules a workload with minimum execution time. The experimental evaluation shows that our models perform approximately 12% and 35% of the actual response time on average for static and dynamic respectively, and the scheduler with our model outperforms, up to 2.9x, that with conventional models consistently.
SURVEI DAN PEMETAAN TOPOGRAFI LAHAN DAN GEDUNG PONDOK PESANTREN AL-IHSAN BENTOK DESA BENTOK KAMPUNG

Pondok Pesantren Al-Ihsan Bentok is located in Bentok Kampung village, Bati-Bati sub-district, Tanah Laut District. It is the sixth branch of Pondok Pesantren Al-Ihsan Tahfizh located in Banjarmasin city. As the new branch, they are facing some problems. The high demand from parents about making their son and daughter tahfizh and tahfizhah, causes the new branch's lack of infrastructure. Because of that problem, the management of Pondok Pesantren Al-Ihsan Bentok decides to build some new infrastructure. In order to build new infrastructure, they need Detailed Engineering Design (DED). One of the components of the DED document is Pondok Pesantren Al-Ihsan Bentok topographic map. Through D-III Teknik Geodesi community service team, Pondok Pesantren Al-Ihsan Bentok topographic map will available. It helps the management of Pondok Pesantren Al-Ihsan Bentok to complete the DED document.  The implementation of the topographic survey used the terrestrial survey method. The survey used instruments like Total Station and GPS receiver Handheld type. The topographic survey started by build a mapping network, survey all of the details in Pondok Pesantren Al-Ihsan Bentok and draw the map digitally. All the details include existing buildings, roads, Pondok Pesantren Al-Ihsan boundary, sewer, river, and contour. The result is a Pondok Pesantren Al-Ihsan topographic map with a scale of 1:3.500. Based on the topographic map, the Pondok Pesantren Al-Ihsan surface area is 113266.751 square meters or 11.33 hectares. The male dormitory area is 500 m2 and the female dormitory area is 650 m2.
Context-adaptive Gaussian Attention for Text-independent Speaker Verification

Multi-head attention (MHA) has shown its effectiveness on aggregating frame-level features for speaker verification task. However, MHA weights each frame individually without considering context information which is important for modeling speaker characteristics of the speech. Based on the assumption that the highly relevant context information should follow a temporal Gaussian distribution, we propose a novel variant of multi-head attention, named as context-adaptive Gaussian attention (CGA), which employs a set of Gaussian functions with different parameters to dynamically model the distributions of the weights obtained from each head. Furthermore, a Gaussian Clustering algorithm (GC) is designed to merge the overlapped Gaussian distributions between different heads. In this way, the proposed method can facilitate the model to better capture multi-span context information compared to the traditional multi-head attention. Experiments on Voxceleb1 dataset demonstrate that the proposed CGA outperforms the state-of-the-art pooling approaches.
Features of the translation of elliptical statements

This article deals with the problem of translating elliptical sentences in a literary text.It represents the results of the research carried out on the material of translation of Englishlanguage fiction.It correlates results of a quantitative analysis of the frequency of translation techniques for elliptic sentences.The author specifies the concepts of ellipsis, translation methods and quality translation.
Batch Photo Editor | Homepage | batch converts images in a post-editing phase.

Batch Photo Editor | Homepage | batch converts images in a post-editing phase. Allows to quantize images (color reduction) in a professional way, for responsive web pages