Reviewerly/exHarmony huggingface dataset:
Case Study of Improving English-Arabic Translation Using the Transformer Model.

Arabic is a language with rich morphology and few resources. Arabic is therefore recognized as one of the most challenging languages for machine translation. The study of translation into Arabic has received significantly less attention than that of European languages. Consequently, further research into Arabic machine translation quality needs more investigation. This paper proposes a translation model between Arabic and English based on Neural Machine Translation (NMT). The proposed model employs a transformer with multi-head attention. It combines a feed-forward network with a multi-head attention mechanism. The NMT proposed model has demonstrated its effectiveness in improving translation by achieving an impressive accuracy of 97.68%, a loss of 0.0778, and a near-perfect Bilingual Evaluation Understudy (BLEU) score of 99.95. Future work will focus on exploring more effective ways of addressing the evaluation and quality estimation of NMT for low-data resource languages, which are often challenging as a result of the scarcity of reference translations and human annotators.
Hierarchical Flow-Based Anomaly Detection Model for Motor Gearbox Defect Detection

In this paper, a motor gearbox fault-detection system based on a hierarchical flow-based model is proposed.The proposed system is used for the anomaly detection of a motion sound-based actuator module.The proposed flow-based model, which is a generative model, learns by directly modeling a data distribution function.As the objective function is the maximum likelihood value of the input data, the training is stable and simple to use for anomaly detection.The operation sound of a car's side-view mirror motor is converted into a Mel-spectrogram image, consisting of a folding signal and an unfolding signal, and used as training data in this experiment.The proposed system is composed of an encoder and a decoder.The data extracted from the layer of the pretrained feature extractor are used as the decoder input data in the encoder.This information is used in the decoder by performing an interlayer cross-scale convolution operation.The experimental results indicate that the context information of various dimensions extracted from the interlayer hierarchical data improves the defect detection accuracy.This paper is notable because it uses acoustic data and a normalizing flow model to detect outliers based on the features of experimental data.
Time-Matching Poisson Multi-Bernoulli Mixture Filter For Multi-Target Tracking In Sensor Scanning Mode

In Bayesian multi-target tracking, the Poisson multi-Bernoulli mixture (PMBM) filter is a state-of-the-art filter based on the methodology of random finite set which is a conjugate prior composed of Poisson point process (PPP) and multi-Bernoulli mixture (MBM).In order to improve the random finite set-based filter utilized in multi-target tracking of sensor scanning, this paper introduces the Poisson multi-Bernoulli mixture filter into time-matching Bayesian filtering framework and derive a tractable and principled method, namely: the time-matching Poisson multi-Bernoulli mixture (TM-PMBM) filter.We also provide the Gaussian mixture implementation of the TM-PMBM filter for linear-Gaussian dynamic and measurement models.Subsequently, we compare the performance of the TM-PMBM filter with other RFS filters based on time-matching method with different birth models under directional continuous scanning and out-of-order discontinuous scanning.The results of simulation demonstrate that the proposed filter not only can effectively reduce the influence of sampling time diversity, but also improve the estimated accuracy of target state along with cardinality.
SISTEM PAKAR MENDIAGNOSA PENYAKIT TANAMAN MANGGA ARUMANIS DENGAN METODE CERTAINTY FACTOR

Diseases that attack mango plants cause mango farmers to suffer losses due to damaged crops or crop failure. To assist agricultural extension workers in diagnosing temporary diseasesthat attack mango arumanis plants if agricultural experts or experts do not exist or do not exist, a computer-based system is needed that can provide information on diseases and how to control it. This study builds a rule-based expert system using the cairtanty factor method to diagnose diseases in mango arumanis plants based on the symptoms of each diseases. The results obtained are in the form of diseases that attack and control procedures that attack and control procedures that must be carried out, as well as the certanty factor value of the truth of the diseases.
PENERAPAN MODEL COOPERATIVE INTERGRATED READING AND COMPOSITION (CIRC) PADA PEMBELAJARAN IPA SISWA KELAS V SD NEGERI SUKOREJO

The purpose of this study was to find out whether the application of the Cooperative Integrated Reading And Composition (CIRC) learning model can significantly improve the science learning outcomes of fifth grade students at SD Negeri Sukorejo. This type of research uses a quasi-experimental method, the research design is One-Group Pretest-Posttest Design. Place and Time The research was carried out at SD Negeri Sukorejo, Stl Ulu Terawas District, Musi Rawas Regency with research time in odd semesters. The study population consisted of 24 students of class V SD Negeri Sukorejo, the research sample used saturated sampling technique. Pre-test and post-test data collection techniques with 21 multiple choice questions. From the results of data analysis using the Z-test with a significant level of α = 0.05 it was found that Zcount &gt; Ztable (2.50 &gt; 1.64), so it can be concluded that there are science learning outcomes for fifth grade students of SD Negeri Sukorejo by applying the Cooperative Learning Model Integrated Reading And Composition (CIRC).&#x0D; Keywords: Cooperative Integrated Reading And Composition (CIRC), Science Learning Outcomes
An analysis of the linguistic features and the text difficulty of the National Assessment of Academic Achievement

This study examines the linguistic characteristics and the text difficulty of the National Assessment of Academic Achievement (NAAA). First, the linguistic features of NAAA conducted in June, September, and November were compared to examine the difference among the tests by the scope of the assessment. Second, the linguistic features of NAAA and the reading texts in six high school English textbooks were compared. Lastly, the correlation between the linguistic features of NAAA and the correct answer rate for each question was analyzed. Corpus analysis was conducted by using Coh-Metrix 3.0. The indices were selected for descriptive analysis, lexical diversity, connectives, syntactic complexity, and readability. One-way ANOVA, Kruskal-Wallis H test, independent t-test, Mann-Whitney U test, and correlation analysis were conducted to investigate the Coh-Metrix data. The result revealed the statistical differences among NAAA tests held in June, September, and November regarding the differences in ‘mean number of words of sentences and readability score.’ In addition, discrepancies in linguistic features between the text in NAAA and the English textbooks were found. Lastly, it was found that ‘number of words, mean number of words, CELEX Log frequency for all words, argument overlap, and readability score' had a correlation with the correct answer rate. Implications and the limitations of the study were discussed.
The role of technical in the preservation and reproduction of the living principle in a human

Introduction. The tendency to strengthen the priority of the technical side of life and the activity of a modern person, characterized by increasing complexity and ambiguity in the definition of a human and his world, aggravates the problem of preserving and reproduction of a living principle in a human. A problematic question arises: is a person – a living person – possible in a technical and technologized world in general? Theoretical analysis. The article notes that when solving the indicated problem, the rejection of the technique, the process of technicalization, technical in general are not provided. However, the absolutization of the meaning of the technical in the life and activity of a human is not supposed, when the existence of a person is reduced to the technical. A modern person needs a kind of reorientation – not to be included in the world of technology and techniques, but, on the contrary, to include them in his life in order to remain modernly alive. All the diversity of life at the expense of new techniques is ensured. Conclusion. In relations between the human and the technical, it is proposed to be based on the principles of the eco-humanistic approach (integrity, coordination, consistency and optimality), when favorable development opportunities, the realization of the internal potential of each side are provided.
Mathematics and physical reality: The theme of the absence of the “Transcendental Signified” in the language of modern fundamental science

Introduction. It is argued that today the expansion of mathematics into the field of physical reality is not being performed in line with the classical paradigm, but in line with the linguistic turn of non-classical philosophy. Theoretical analysis. Such aspect of nature’s “non-fittability” into the conceptual network of mathematics as the problem of asymmetry is explored. It is stated that the world, constructed according to the logic of ideal mathematical symmetries, passes into a state called unmanifested in Hinduism. In the same direction the concept of J. Baudrillard is considered, where the structures of ideal reversibility are supposed to be the most radical way to destroy what exists and the symbol of nothingness. Accordingly, ideal mathematical symmetry describes states that cannot exist as a physical reality. The settlement of “dense” reality in the mathematical language of theoretical physics is seen in irrational, transcendent and imaginary numbers, in which the ideal reversibility of mathematical operations is violated. Conclusion. The search for “supersymmetry” is regarded as a variation of general language problems. Ideal symmetry in mathematics, “supersymmetry” in fundamental physics, like any “transcendental signified”, can only exist “under the sign of strikeout”. Variations on the theme of differance are revealed here. A generating source of difference, according to J. Derrida, is always on the other side of the language.
Software Defects Prediction At Method Level Using Ensemble Learning Techniques

Creating error-free software artifacts is essential to increase software quality and potential re-usability. However, testing software artifacts to find defects and fix them is time-consuming and costly, so predicting the most error-prone software components can optimise the testing process by focusing testing resources on those components to save time and money. Much software defect prediction research has focused on higher granularities, e.g., file and package levels, and fewer have focused on the method level due to the lack of method-level bug-related datasets . In this paper, software defect prediction will be performed on highly imbalanced method-level datasets extracted from 23 open source Java projects . Eight ensemble learning algorithms will be applied to the datasets: Bagging, Ada-Boost, Random Forest, Random Under sampling Boost, Easy Ensemble, Balanced Bagging and Balanced Random Forest. The results showed that the Balanced Random Forest classifier achieved the best results regarding Recall and Roc_Auc values .
A self-adaptive deep learning-based model to predict cloud workload

Predicting cloud workload is a problematic issue for cloud providers. Recent research has led us to a significant improvement in workload prediction. Although self-adaptive systems have an imperative impact on lowering the number of cloud resources, those still have to be more accurate, detailed and accelerated. A new self-adaptive technique based on a deep learning model to optimize and decrease the use of cloud resources is proposed. It is also demonstrated how to prognosticate incoming workload and how to manage available resources. The PlanetLab dataset in this research is used. The obtained results have been compared to other relevant designs. According to these comparisons with the state-of-theart deep learning methods, our proposed model encompasses a better prediction efficiency and enhances productivity by 5%.
An Empirical Study on the Internal Assets of Local Governments Regions where the Integration of Administrative Districts is Proposed

지역불균형 해소방안이라는 문제가 제기될 때마다 제기되는 주장이 지방자치단체 통합이다. 최근 대표적인 사례가 경북도청 신도시를 두고 있는 안동시와 예천군이다. 여러 선거 때마다 후보자들이 안동시와 예천군의 통합을 주장한 경우가 많았다. 특히 2022년 지방선거에서 당선된 안동시장이 공약으로 제시하였고 통합을 위하여 여러 행정적인 절차에 돌입하자 예천군은 강력하게 반발하는 등 두 지역이 갈등의 양상을 보이고 있다. 이에 본 연구는 최근 통합에 대한 논란이 일고 있는 경북 안동시와 예천군의 통합에 대한 다각적인 측면에서 논의를 하고자 했다. 이를 위하여 기존 연구가 재정 여건에 대한 지출과 경제의 성장 측면에서의 효과를 분석했다면 이 연구에서는 지역이 가지고 있는 내부자산 활용을 중심으로 주민들의 통합에 대한 의견을 분석하고자 했다. 그 결과 보다 소규모의 지방자치단체는 실증적 분석에서는 지역내부자산이 우위적이었고, FGD조사에서는 경제적 효율성, 주민 화합, 지역간 균형 발전, 쾌적한 주거환경 등 여러 요인에서 유리하게 작동되는 것으로 나타났다. 자치단체간 통합 효과에 대해서는 일관성이 부족하고, 갈등적 요소가 많다는 점에서 우선적으로 행정서비스 중심으로 효율성 제고를 위한 자치단체간 협력방식의 적용을 제안한다. Whenever the issue of resolving regional imbalances is raised, the argument that is raised is the integration of local governments. A recent representative example is Andong City and Yecheon County, which have a new city in Gyeongbuk Provincial Government. The purpose of this study is to analyze the opinions of the residents about the integration of Andong City and Yecheon County in Gyeongbuk Province, which has recently been controversial about integration. As a result, it was found that smaller local governments operate favorably in various factors such as economic efficiency, residents" unity, balanced regional development, and pleasant residential environment. Therefore, it is suggested to apply the cooperation method between local governments to improve efficiency based on administrative services.
A Conceptual Framework of Data Literacy for Decision Makers

빅데이터 시대에 데이터 문해력은 조직의 합리적 의사결정에 필수적인 역량이 되고 있다. 하지만 조직의 의사결정자들은 데이터 활용의 중요성을 인식하면서도 데이터 문해력이 부족하여 의사결정 과정에서 데이터를 충분히 활용하지 못하고 있는 실정이다. 지금까지 데이터 문해력에 관한 선행 연구들은 전문적인 데이터 기술을 이용하여 데이터 분석 결과를 생성하는 생산자 관점에서 데이터 문해력을 정의하고 역량을 기술하였다. 하지만 조직의 의사결정자는 데이터 분석 결과를 이해하고 해석하고 활용하는 이용자 관점의 업무를 주로 수행한다. 이에 본 연구는 문헌 조사와 검토를 통해 의사결정자에게 필요한 문해력을 정의하고 역량을 기술하는 개념적인 프레임워크를 개발하였다. 프레임워크를 통해 살펴본 바에 의하면, 의사결정자는 문제를 주도적으로 정의하고 데이터 전문가와 소통하고 협업할 수 있는 수준의 데이터 기술에 대한 기초적인 이해가 필요하다. 의사결정자에게 가장 중요한 데이터 문해력은 도메인의 전문 지식을 바탕으로 분석 결과를 비판적이고 맥락적으로 해석하여 가능성이 높은 실행 계획을 수립하는 것이다. 본 연구에서 제시하는 프레임워크는 의사결정자의 역할과 책임에 부합하는 데이터 문해력을 이해하고 개발하는 데 도움이 될 것이다. In the era of big data, data literacy is becoming an essential competency for rational decision-making in organizations. Although decision makers in organizations recognize the importance of utilizing data, their lack of data literacy prevents them from fully utilizing data in the decision-making process. Previous studies on data literacy have defined data literacy and described competencies from the perspective of producers who use professional data skills to generate data analysis results. However, organizational decision makers are mainly responsible for understanding, interpreting, and utilizing data analysis results from a user perspective. Therefore, this study develops a conceptual framework for defining data literacy and describing competencies in a decision makers’ perspective through literature research and reviews. As we’ve seen with the framework, decision makers need to take the initiative to define the problem and have a basic understanding of data technology that allows them to communicate and collaborate with data experts. Most importantly, they need to be able to critically and contextually interpret analytical results based on domain expertise to create a high-potential action plan. The proposed framework will help understand and develop data literacy competencies that are consistent with the roles and responsibilities of decision makers.
Exploring the Predictors of University Students’ Dropout - Case of H University in Daejeon

본 연구는 H 대학교 학생들의 중도탈락 관련 요인을 분석하여 H대학교에서 중도탈락의 가능성이 있는 학생들을 대상으로 중도탈락 의도를 낮추기 위한 방안을 모색하기 위해 수행되었다. 이를 위해 첫째, 중도탈락 집단과 학업유지 집단의 현황을 카이제곱을 사용해서 살펴보았다. 둘째, 중도탈락 집단과 학업유지 집단의 평균평점 등과 같은 대학생활의 차이를 t 검증을 사용해서 비교해보았다. 셋째, 중도탈락 예측 요인을 알아보기 위해 로지스틱 회귀분석을 사용하였다. 주요 연구결과는 다음과 같다. 첫째, 남학생의 중도탈락 비율이 여학생보다 더 높았다. 입학전형별로 비교해보면, 중도탈락 집단에서는 수시전형과 정시전형의 비율이 비슷하지만, 학업유지 집단에서는 수시전형 입학생의 비율이 높게 나타났다. 둘째, 중도탈락 집단은 신청학점에 비해서 이수학점이 적었으며 결석횟수도 학업유지 집단보다 더 많았다. 학업유지 집단은 평균평점 등이 중도탈락 집단보다 더 높게 나타났다. 셋째, 중도탈락 예측 요인을 학년별로 살펴보면 전학년에서 공과대학이 예측 요인으로 도출되었으며, 인문사회대학은 3, 4학년에서 예측 요인으로 도출되었다. 또한 평균평점은 1, 2 학년에서만 유의한 예측요인으로 도출되었다. 결론적으로, 집단 특성(성별, 입학전형 등)에 따라 중도탈락과 학업유지에 차이가 있었으며 학년별 중도탈락 예측요인은 각각 다름을 알 수 있었다. 이에 따라 중도탈락을 낮추기 위한 방안은 학년별로 차별적으로 수립되어야 할 것이다. This study was conducted to analyze the factors of dropout of H University students and to find ways to lower the intention of dropout of students who are likely to drop out. In order to conduct the study, first, the current status of the dropout group and the academic maintenance group was examined using chi-square. Second, t-test was used to compare the difference in college life between the dropout group and the academic maintenance group. Third, logistic regression analysis was used to find out the predictors of dropout. The results of the study are as follows. First, when comparing the dropout rate, the dropout rate of the male group was higher than that of the female group. Comparing by admissions screening, there is no difference in the ratio of early admission and regular admissions in the dropout group. And in the school maintenance group, the proportion of students admitted to the early admission program was high. Second, in the dropout group, students completed fewer credits than the applied credits. And the number of absences of students who were dropped out was high. Third, engineering colleges were derived as predictors of dropout in all grades. The College of Humanities and Social Affairs was derived as a predictor in the 3rd and 4th grades. In addition, the average score was derived as a significant predictor only in the first and second grades. In conclusion, it can be said that students do not drop out due to maladjustment, but choose to drop out to explore their career path. Accordingly, in order to reduce dropout in the middle, universities should establish a plan for students to have positive potential for their careers.
Efektifitas Model Problem Based Learning Berbantuan Lembar Kerja Siswa Untuk Meningkatkan Kemampuan Literasi Numerasi Ditinjau Dari Rasa Ingin Tahu Siswa Sekolah Dasar

Literacy skills mark the quality of human resources in a country. However, Indonesia's performance in literacy assessment on an international scale has not been very good. The results of interviews with teachers of SD Inpres 18 subsay Manokwari district on March 14, 2022 found the fact that students' numeracy literacy skills were still very low. This study aims to test the effectiveness of the problem-based learning model assisted by student worksheets to improve numeracy literacy skills in terms of the curiosity of elementary school students in Manokwari district. The approach used in the implementation of this research is a quantitative approach. This type of research is experimental research. Data collection techniques in this study are Numeration literacy test, Observation, Validation Sheet and Documentation. Data analysis includes data analysis of validity and effectiveness. The effectiveness data analysis includes the completeness test for numeracy literacy skills, the average difference test for numeracy literacy skills, testing the effect of curiosity character on numeracy literacy skills. The results of the Effectiveness Test Analysis show that problem based learning models assisted by student worksheets are effective in improving numeracy literacy skills by criteria: (1) The proportion of classical learning completeness can be said to be more than 75% of students getting a score of 65, (2) The numeracy literacy ability of students in classes that use problem based learning models assisted by student worksheets is better than students' numeracy literacy skills with conventional learning, (3) There is an effect of curiosity character (X) on posttest numeracy literacy ability (Y).
Application of clustering cooperative differential privacy in spatial crowdsourcing task allocation

A framework for spatial crowdsourcing task allocation based on centralized differential privacy is proposed for addressing the problem of worker’s location privacy leakage. Firstly, by combining two stages of differential privacy noise addition and clustering matching, a spatial crowdsourcing worker dataset with high differential privacy protection can be obtained; Secondly, the dynamic problem of spatial crowdsourcing task allocation is transformed into a static combinatorial optimization problem by dividing the spatiotemporal units and the “delay matching” strategy; Finally, the improved discrete glowworm swarm optimization algorithm is used to calculate the results of spatial crowdsourcing task allocation. It has been demonstrated that, compared to the direct differential privacy noise-adding assignment method and the discrete glowworm swarm optimization assignment method, the proposed method achieves better task assignment results, with the total travel distance reduced by 12.42% and 3.56%, respectively, and the task assignment success rate increased by 11.75% and 3.34%, respectively.
Look-up the Rainbow: Table-based Implementation of Rainbow Signature on 64-bit ARMv8 Processors

The Rainbow Signature Scheme is one of the finalists in the National Institute of Standards and Technology (NIST) Post-Quantum Cryptography (PQC) standardization competition, but failed to win because it has lack of stability in the parameter selection. It is the only signature candidate based on a multivariate quadratic equation. Rainbow signatures have smaller signature sizes compared with other post-quantum cryptography candidates. However, they require expensive tower-field based polynomial multiplications. In this article, we propose an efficient implementation of Rainbow signatures using a look-up table–based multiplication method. The polynomial multiplications in Rainbow signatures are performed on the 𝔽 16 field, which is divided into sub-fields 𝔽 4 and 𝔽 2 under the tower-field method. To accelerate the multiplication process on target processors, we propose a look-up table–based tower-field multiplication technique. In 𝔽 16 , all values are expressed in 4-bit data format and can be implemented using a 256-byte look-up table access. The implementation uses the TBL and TBX instructions of the 64-bit ARMv8 target processor. For Rainbow III and Rainbow V, they are computed on the 𝔽 256 field using an additional 16-byte table instead of creating a new look-up table. The proposed technique uses the vector registers of 64-bit ARMv8 processors and can calculate 16 result values with a single instruction. We also proposed implementations that are resistant to timing attacks. There are two types of implementations. The first one is the cache side-attack resistant implementation, which utilizes the 128-byte cache lines of the M1 processor. In this implementation, cache misses do not occur, and cache hits always occur. The second type is the constant-time implementation. This method takes a step-by-step approach to finding the required look-up table value and ensures that the same number of accesses is made regardless of which look-up table value is called. This implementation is designed to be constant-time, meaning it does not leak timing information. Our experiments on modern Apple M1 processors showed up to 428.73× and 114.16× better performance for finite field multiplications and Rainbow signatures schemes, respectively, compared with previous reference implementations. To the best of our knowledge, this proposed Rainbow implementation is the first optimized Rainbow implementation for 64-bit ARMv8 processors.