Reviewerly/exHarmony huggingface dataset:
Energy Consumption by Servers under Unknown Service Demand

We evaluate energy consumption under unknown service demands using three policies: task assignment based on guessing size (TAGS), the shortest queue strategy and random allocation in a homogeneous environment. We modelled these policies using performance evaluation processing algebra (PEPA) to derive numerical solutions. Our results show that servers running under TAGS consumes more energy than other policies in terms of total energy consumption. In contrast, TAGS consumes less energy than random allocation in terms of energy per job when the arrival rate is high and the job size is variable.
On the frequency of symbols in sequences generated by nonlinear Feedforward generators

Due to their simple construction, LFSRs are commonly used as building blocks in various random number generators. Nonlinear feedforward logic is incorporated in LFSRs to increase the linear complexity of the generated sequences. This work deals with Nonlinear Feedforward Generators (NLFGs) that generate sequences over arbitrary finite fields. We analyze the frequency of symbols in sequences generated by such configurations. Further, we propose a method of using nonlinear feedforward logic with word-based σ-LFSRs wherein vectors over a finite field are seen as elements of an extension field. We then briefly analyze sequences generated by an existing scheme and show that sequences generated by the proposed scheme are statistically more balanced.
PHICON: Improving Generalization of Clinical Text De-identification Models via Data Augmentation

De-identification is the task of identifying protected health information (PHI) in the clinical text.Existing neural de-identification models often fail to generalize to a new dataset.We propose a simple yet effective data augmentation method PHICON to alleviate the generalization issue.PHICON consists of PHI augmentation and Context augmentation, which creates augmented training corpora by replacing PHI entities with named-entities sampled from external sources, and by changing background context with synonym replacement or random word insertion, respectively.Experimental results on the i2b2 2006 and 2014 deidentification challenge datasets show that PH-ICON can help three selected de-identification models boost F1-score (by at most 8.6%) on cross-dataset test.We also discuss how much augmentation to use and how each augmentation method influences the performance. 1
Visualisasi Pemain Sepak Bola Indonesia pada DBPedia dengan menggunakan Node2Vec dan Closeness Centrality

Abstract. Visualization of Indonesian Football Players on DBpedia through Node2Vec and Closeness Centrality Implementation. Through Semantic Web, data available on the internet are connected in a large graph. Those data are still raw so that they need to be processed to be an information that can help humans. This research aims to process and analyze the Indonesian soccer player graph by implementing node2vec and closeness centrality algorithm. The graph is modeled through a dataset obtained from the DBpedia by performing a SPARQL query on the SPARQL endpoint. The results of the Node2vec algorithm and closeness centrality are visualized for further analysis. Visualization of node2vec shows that the defenders are distributed over the players. Meanwhile, the result of closeness centrality shows that the strikers have the highest centrality score compared to other positions.Keywords: visualization, node2vec, closeness centralityAbstrak. Dengan adanya web semantik, data yang tersebar di internet dapat saling terhubung dan membentuk suatu graf. Data yang ada pada graf tersebut masih berupa data mentah sehingga perlu dilakukan pengolahan agar data mentah tersebut dapat menjadi informasi yang dapat membantu manusia. Penelitian ini bertujuan untuk melakukan pengolahan dan analisis terhadap graf pemain sepak bola Indonesia dengan mengimplementasikan algoritma node2vec dan closeness centrality. Graf dimodelkan melalui dataset yang didapat dari website DBpedia dengan cara melakukan query SPARQL pada SPARQL endpoint. Hasil dari algoritma node2vec dan closeness centrality divisualisasikan untuk dianalisis. Visualisasi dari node2vec menunjukkan pemain defender tersebar. Hasil closeness centrality menunjukkan bahwa pemain striker memiliki nilai tertinggi daripada posisi lainnya.Kata Kunci: visualisasi, node2vec, closeness centrality
Active Re-identification Attacks on Periodically Released Dynamic Social Graphs

Active re-identification attacks pose a serious threat to privacy-preserving social graph publication. Active attackers create fake accounts to enforce structural patterns that can be used to re-identify legitimate users on published anonymised graphs, even without additional background knowledge. So far, this type of attacks has only been studied in the scenario where the inherently dynamic social graph is published once. In this paper, we present the first active re-identification attack in the more realistic scenario where a dynamic social graph is periodically published. Our new attack leverages tempo-structural patterns, created by a dynamic set of sybil nodes, for strengthening the adversary. We evaluate our new attack through a comprehensive set of experiments on real-life and synthetic dynamic social graphs. We show that our new attack substantially outperforms the most effective static active attack in the literature by increasing success probability by at least two times and efficiency by at least 11 times. Moreover, we show that, unlike the static attack, our new attack remains at the same level of efficiency as the publication process advances. Additionally, we conduct a study on the factors that may thwart our new attack, which can help design dynamic graph anonymisation methods displaying a better balance between privacy and utility.
Assessment of the Impact of COVID-19 on the Educational Activity in Russia

The number of schoolchildren and students, as well as teachers and university professors who do not attend schools and universities due to the outbreak of the coronavirus infection (COVID-19) is growing significantly.Governments around the world, including Russia, were forced to decide to close their educational institutions in order to contain the global COVID-19 pandemic.However, the closure of schools and universities across the country has led millions of students to switch from traditional learning to distance learning.In this regard, the authors attempted to assess the impact of the coronavirus pandemic on education in Russia.The study was conducted using nonparametric methods to assess the degree of correlation between the transition to distance learning during the pandemic and the effectiveness of training in higher education institutions.The study showed that the major Russian universities have coped with the problem of distance learning by using information services and training platforms.
THE EVALUATION OF DISTANCE LEARNING IN PANDEMIC ERA: CASE STUDY OF FINANCIAL EDUCATION AND TRAINING AGENCY OF MAKASSAR

The objectives of this research are to: (i) evaluate the trainees’s satisfaction on trainers and training performance; (ii) evaluate learning gain or improvement of trainees’s skills, knowledge, and attitude after training; and (iii) know the significant obstacles that can reduce the effectiveness of training. Using the Kirkpatrick Evaluation Model through questionnaire, interview, and descriptive statistics method, this research reveals that: (i) the overall aspect of the implementation evaluation was assessed by participants in the good category although it could not meet the level of expectations of participants that could be seen from the ratio of the average total perception to reality below 100%. On the other hand, the trainers aspect has been able to meet the expectations of participants where the overall level of trainers performance has been assessed by participants and entered into the category of very good; (ii) the results of the evaluation analysis at Level 2 (learning gain) show that most participants graduate with good predicate and get an up/up score so that it can be said that participants have gained additional knowledge after attending the training; (iii) although in general the evaluation results showed good results, there are still some obstacles faced by participants in attending the training. In terms of organizing, participants generally complained about inadequate internet quality in some areas. Meanwhile, in the trainers aspect, participants generally give feedback that teachers can multiply case studies and raise the latest issues in the confectionery of problems related to training materials.
On a number of isogeny classes of simple abelian varieties over finite fields

In this paper, we investigate the asymptotic behavior of the number $$s_q(g)$$ of isogeny classes of simple abelian varieties of dimension g over a finite field $${\mathbb {F}}_q$$ . We prove that the logarithmic asymptotic of $$s_q(g)$$ is the same as the logarithmic asymptotic of the number $$m_q(g)$$ of isogeny classes of all abelian varieties of dimension g over $${\mathbb {F}}_q$$ . We also prove that $$\begin{aligned} \limsup _{g \rightarrow \infty }\frac{s_q(g)}{m_q(g)}=1. \end{aligned}$$ This suggests that there are much more simple isogeny classes of abelian varieties over $${\mathbb {F}}_q$$ of dimension g than non-simple ones for sufficiently large g, which can be understood as the opposite situation to a main result of Lipnowski and Tsimerman (Duke Math. 167:3403–3453, 2018).
Memory Efficient High Speed Systolic Array Architecture Design with Multiplexed Distributed Arithmetic for 2D DTCWT Computation on FPGA

This paper presents customized Systolic Array Architecture (SAA) design of Dual Tree Complex Wavelet (DTCWT) sub band computation based on multiplexed Distributive Arithmetic Algorithm (DAA). The proposed architecture is memory efficient and operates at frequencies greater than 300 MHz in decomposing 256 x 256 input images. Three architectures such as reduced order structure, multiplexed DA structure and zero pad structure are designed and evaluated for its performances for DTCWT computation minimizing arithmetic operations with improved latency. The proposed design is modeled in Verilog HDL and is implemented on Spartan-6 and Virtex-5 FPGA considering Xilinx ISE FPGA design flow. The latency of proposed architectures is evaluated to be 15 clock cycles and throughput is estimated to be 4 outputs for every 5 clock cycles. The SAA architecture occupies less than 12% of FPGA resources and consumes less than 10 mW of power on FPGA platform.
Qubit transformations on Rashba ring with periodic potential

Abstract A spin-qubit transformation protocol is proposed for an electron in a mesoscopic quantum ring with tunable Rashba interaction controlled by the external electric field. The dynamics of an electron driven around the ring by a series of Landau–Zenner-like transitions between a finite number of local voltage gates is determined analytically. General single-qubit transformations are demonstrated to be feasible in a dynamical basis of localized pseudo-spin states. It is also demonstrated that by the use of suitable protocols based on changes of the Rashba interaction full Bloch sphere can be covered. The challenges of a possible realization of the proposed system in semiconductor heterostructures are discussed.
Acoustic optimization of curved architecture in practice: The new Strait Cultural Arts Center in Fuzhou

Curved surfaces are increasingly part of the architectural language used in buildings for the performing arts, yet have known challenges both in reality and in ray-tracing-based computer simulations. The designs of the 1000-seat symphony hall, the 1600-seat opera house and the 800-seat multi-purpose hall in Fuzhou, China, were all based on curved surfaces, both convex and concave, often covered with local ceramic tiles. Providing the right amount, distribution and quality of early reflections thus required a precise analysis of the acoustic behavior of curved surfaces. The acoustic design interacted with the architecture in precisely shaping those curves in 3D. In order to explore the acoustic potential and detect problems related to the architectural concept of both rooms, novel geometrical acoustics analysis algorithms were developed within NURBS modeling software rather than relying on commercial ray-tracing algorithms. Optimization of the curved surfaces is obtained when the output of these algorithms, the interpretation of the acoustic consultant, and the required integration of acoustic solutions within the global architectural concept are all aligned – a “meeting of minds” between acoustics and architecture. The analysis procedure and geometrical acoustics algorithms used will be presented in detail, as well as the related decision-making process, the acoustic predictions and the measurement results of the three built halls.
The Effects of Monitoring and Evaluation Systems on Organizational Performance: A Case of Tanzania Airport Authority-Dar es Salaam, Tanzania

Worldwide public sector and private sector put more effort in promotion of good environment for conducting monitoring and evaluation to the project conducted within their organization for the purpose of increase transparency, strengthen accountability, and improve organization performance. The study aims to determine the role of Monitoring and Evaluation systems on the Organizational performance and to examine resource monitoring and evaluation affect organization performance. A case of Tanzania Airport Authority. The study deployed descriptive quantitative research design, the study used Slovenes formula to obtain sample size of 187 from targeted population was 350 employees of TAA located in Ilala Municipality and purposively sampling was used. Questionnaire, and documents reviewed were used as the research instruments for collecting data needed in this study. The study uses multiple regression analysis models to test the relationship between monitoring and evaluation systems on organizational performances. The study concluded that monitoring and Evaluation systems improves organization performance in Tanzania and recommended that any organization(both private and public) should employ constant improvement in monitoring and Evaluation system in order to reach organization For the very rationale monthly time set of data has been approved from Jan 2014 to Dec 2019. The investigative outline contains.
Parallelizing Bidirectional A* Algorithm

Dijkstra’s algorithm is one of the simplest shortest path finding algorithm. A star(A*) algorithm is a variation of the shortest path first Dijkstra’s algorithm and is very commonly used in games using heuristics. The idea behind A* is to assign weight to each open node and then use a heuristic to calculate the cost from start to finish. A* uses heuristics and cost functions to find the most appropriate path in games and robotics. Games are needed to be fast and so we can have tradeoffs between speed and accuracy. So instead of accuracy we focus more on speed which is not needed in some of the situations like autonomous vehicles and simulation games. So, the A* algorithm may underestimate the costs but will never overestimate it. Bidirectional A*reduces the computation by calculating the shortest path from the source as well as the destination. A solution may be the General-Purpose Graphics Processing Units. It can be used to enhance the processing and execution speed of Bidirectional A* algorithm by using parallel processing and multiple threads. GPU based path finding may be approximately 45 times as fast as CPU pathfinding mechanism.
Machine Learning Algorithm for Anthropomorphic Manipulator Control System

Service robots are one of the relevant areas of modern robotics.Many service robots are equipped with a pair of anthropomorphic manipulators, so that they are able to perform complex operations.However, this approach leads to new challenges in development of the robot control systems.In this paper we propose an algorithm for training the control system of two anthropomorphic manipulators with 7 degrees of mobility having intersecting work areas.The algorithm is based on deep reinforcement learning approach applied to the artificial neural network (ANN).The paper also describes the practical implementation of the ANN-based manipulator control system that avoids collisions and achieves an average accuracy of reproducing target positions of manipulator end effector of 98.3%.The ANN training was carried out using Keras framework.The obtained results indicate the promise of applying the proposed method for the development of control systems for anthropomorphic manipulators based on deep reinforcement learning.
Automated synthesis of local time requirement for service composition

Service composition aims at achieving a business goal by composing existing service-based applications or components. The response time of a service is crucial, especially in time-critical business environments, which is often stated as a clause in service-level agreements between service providers and service users. To meet the guaranteed response time requirement of a composite service, it is important to select a feasible set of component services such that their response time will collectively satisfy the response time requirement of the composite service. In this work, we use the BPEL modeling language that aims at specifying Web services. We extend it with timing parameters and equip it with a formal semantics. Then, we propose a fully automated approach to synthesize the response time requirement of component services modeled using BPEL, in the form of a constraint on the local response times. The synthesized requirement will guarantee the satisfaction of the global response time requirement, statically or dynamically. We implemented our work into a tool, Selamat and performed several experiments to evaluate the validity of our approach.
Automated metric profiling and comparison of Ancient Greek verse epics in Hexameter

This article describes a software tool, named Dactylo, which is capable of performing metrical analysis, alias scansion, of epics written in hexameter. The automated scansion is based on well-known scanning rules of various theoretical works. The development methodology introduces the concept of computerized metric profiling and metric distance, which is a measurement value that reflects the degree of similarity or dissimilarity between different epics. For this purpose, eight renowned epics have been scanned, including Iliad and Odyssey, with plenty of statistical information. Based on these outcomes, these epics can be classified in groups that reflect very well the three periods of their creation, namely Classical, Hellenistic and Late Antiquity. Dactylo demonstrates its ability to produce statistics for hexameter’s metric patterns in a massive scale, easily and accurately, becoming so a contribution of Computational Linguistics to the diachronic comparative and quantitative language studies.
The Development of Audio Visual Learning Media Based on Genius Learning in Exposition Text Learning by Grade X SMK Tritech Informatika Medan

This study aims to determine: (1) Describe the audio visual learning media based on genius learning which is effective for class X students of SMK Tritech Informatika Medan, (2) Describe the results of the development carried out on genius learning-based audio visual media for class X SMK Tritech Informatika students. Medan, (3) Describe the reasons for using audio-visual learning media based on genius learning in developing exposition text learning media. This research is a development research using the Borg &amp; Gall model which aims to develop an audio-visual learning media based on genius learning that will be used as an exposition text learning medium. This learning media will be tested from material experts, design experts, media experts, Indonesian language teachers, and students of SMK Tritech Informatika Medan, consisting of 3 students in individual trials, 9 students in small group trials, and 25 students in field trials. The instrument used in this study was a questionnaire. (1) The results of validation by material experts with an average of 79% with good criteria, (2) validation results by media experts with an average of 80% with good criteria, (3) validation by instructional media design experts with an average of 82 % with very good criteria, (4) the response of Indonesian language teachers with an average of 86% with very good criteria, (5) the acquisition of individual trial results with an average of 78.5% with good criteria, (6) The acquisition of trial results small group with an average of 79% with good criteria, (7) Acquisition of field trial results with an average of 83.54% with very good criteria, (8) Student learning outcomes before using audio-visual learning media based on genius learning were 66.2 and after using audio-visual learning media based on genius learning with an average score of 78 in the good category. The difference obtained is 11.8. This proves that the genius learning-based audio-visual learning media developed can improve student learning outcomes, thus, this genius-based audio-visual learning media is effectively used in learning exposition text.
Continuous-monitoring measured signals bounded by past and future conditions in enlarged quantum systems

In a quantum system that is bounded by past and future conditions, weak continuous-monitoring forward-evolving and backward-evolving quantum states are usually carried out separately. Therefore, measured signals at a given time t cannot be monitored continuously. Here, we propose an enlarged quantum system method to combine these two processes together. Therein, we introduce an enlarged quantum state that contains both the forward- and backward-evolving quantum states. The enlarged state is governed by an enlarged master equation and propagates one-way forward in time. As a result, the measured signals at time t can be monitored continuously and can provide advantages in the signals amplification and signal processing techniques. Our proposal can be implemented on various physical systems, such as superconducting circuits, NMR systems, ion traps, quantum photonics, and among others.
Global Solar Radiation Estimation in Mansoura, Egypt (Dept.M)

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An Analysis Translation Techniques in Indonesian-English Subtitle in Alice In Wonderland Movie By Indoxxi.Net

AbstractTranslating a text is certainly not arbitrary, it needs to pay attention to various aspects. Especially in translating in a film. In this study, the author will examine the translation technique in Indonesian-English subtitles in the film Alice in Wonderland by indoxxi.net. This study uses descriptive research related to the identification of translation techniques in Indonesian-English subtitles by INDOXXI.NET. The results are known, that in Indonesian-English subtitles in Alice in Wonderland has 11 translation techniques. There is a literal meaning, adaptation, loan, reduction, modulation, particularization, explicitation, transposition, amplification, equivalence, and compensation. After analyzing the subtitles, most of them use the literal meaning. Found almost 75% of the literal meaning for this technique. Also, we found about 8% using adaptation techniques, 7% using loan techniques. So, 10% is about other techniques, such as explicitation, equivalence, modulation, amplification, particularization, transposition, compensation, and reduction techniquesKeywords: Translation technique, film