Reviewerly/exHarmony huggingface dataset:
Identification of Rainfall events on Climate Phenomena in Medan based on Machine Learning

Indonesia has diverse topographical conditions that result in Indonesia having a unique climate. One of the unique climate elements to be studied is rainfall, because rainfall has a different pattern in each region, this different rainfall pattern is caused by several climate phenomena factors that affect the rainfall pattern, including El-Nino Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Madden Julian Oscillation (MJO). Medan City is the capital of North Sumatra province which is one of the areas in the flood-prone category in North Sumatra, where the factor of flooding is due to rainfall events in a long period of time, so the author wants to know which climatic phenomena factors can affect rainfall events in Medan city by using Machine Learning technology through the Matlab application, where in this study has a method by forming four combination models, namely the combination of the influence of IOD, SOI and MJO; second combination of IOD and SOI; third combination of SOI and MJO; and fourth combination of MJO and IOD, these four combinations will be the rainfall value of the four models. Furthermore, the rainfall value of the model is compared with the observed rainfall value and verification test using Mean Absolute Error (MAE) and correlation. Then the calculation of the comparison between the four rainfall models with the observed rainfall obtained the lowest MAE value during the SOI and MJO phenomenon of 15.0 mm and the highest correlation value during the IOD and SOI and SOI and MJO phenomena. So it is concluded that the combination of SOI and MJO has the best verification value. This shows that based on Machine Learning modeling, the model shown as the best predictor in Medan city is when the model combination consists of SOI and MJO.
STUDENT FEEDBACK MANAGEMENT SYSTEM

The landslide that hit Taliye village in Maharashtra, India, in July 2021 was a devastating tragedy that resulted in significant loss of life and damage to property.As a result, there is an urgent need to assess landslide hazard zones in the region, using advanced geospatial tools such as GIS and remote sensing.This review paper evaluates the use of these tools to identify and analyze such zones, and to provide recommendations for effective mitigation strategies.Using digital elevation models, satellite imagery, and geological maps, the study identifies four distinct hazard zones in Taliye, ranging from high to very low risk.The contributing factors to landslide hazards in the region are steep slopes, high rainfall, loose soil, and weak geological formations.The paper highlights the importance of providing data for mitigation, vulnerability assessment and helps administration in case of landslide hazard by providing data required for Disaster Management.The study recommends the use of advanced geospatial tools to monitor the landslide hazard zones in Taliye continuously, providing valuable insights for researchers and practitioners working on landslide risk reduction in similar regions.The findings underscore the need for concerted action to mitigate the risks associated with landslides in Taliye and similar regions.
Generating six pairs of bandwidth-expanded entangled sideband modes via time delay compensation

Quantum entanglement is an important pillar of quantum information processing. In addition to the entanglement degree, the bandwidth of entangled states becomes another focus of quantum communication. Here, by virtue of a broadband frequency-dependent beam splitter, we experimentally demonstrate six pairs of independent entangled sideband modes with maximum entanglement degree of 8.1 dB. Utilizing a time delay compensation scheme, the bandwidth of independent entangled sideband modes is expanded to dozens of megahertz. This work provides a valuable resource to implement efficient quantum information processing.
A Study on Teaching and Learning Methods for Secondary Music Creation Projects Using Artificial Intelligence(AI)

이 연구의 목적은 중등학교 현장에서 인공지능 프로그램을 활용한 음악창작 프로젝트 교수·학습 모형을 제안하여, 인공지능을 활용한 음악학습에서 발견되는 특징과 유의사항에 대해 살펴보고, 인공지능이 단순한 소프트웨어(SW) 교육을 넘어 음악 교과교육 자체에 유의미한 교육적 가치를 제공할 수 있음을 시사하는 것이다. 인공지능 시대의 도래는 학습자들의 미디어 리터러시와 소통 및 공동체 역량이 프로젝트 학습에 의해 성장될 수 있음을 드러내었다. 학습자가 가진 음악적 역량을 보완하여 내재된 상상력과 잠재력을 표현할 수 있도록 적극적으로 돕는다는 점에서 인공지능을 활용한 음악창작 학습은 높은 수준의 흥미 유발뿐만 아니라, 그 자체로 음악 요소의 발견학습으로 연계될 수 있다는 측면에서 음악교육 현장에 마중물 역할을 할 것이다. 프로젝트 학습의 결과물은 인공지능이 제안한 음악창작 이후 학습자의 능동적인 수정 및 개선과정을 통해 그들이 마주한 문제 상황에 효과적으로 대응할 수 있도록 전개할 수 있다. 따라서 본 연구에서는 이와 같은 과정을 통해 인공지능을 활용한 음악 교수·학습 모형이 미래 음악교육적 학습으로서 가치가 있음을 제안하였다.The purpose of this study is to help plan music lessons using artificial intelligence in school‘s music class. Music classes using artificial intelligence have a unique feature, which is that they provide results that are independent of students' musical abilities. In order to make this an educationally valuable activity, a project learning model was proposed. Through this, it is meaningful to shed light on the value of music learning using artificial intelligence as a unique music learning beyond simple interest and SW education. Artificial intelligence has learners who complement musical limitations, helping them to develop contacts and potential. This point is important in that it not only increases the learning of music creation using artificial intelligence, but also leads to learning through the discovery of musical elements.
A High Dimensional Goldreich-Levin Theorem

In this work we prove a high dimensional analogue of the beloved Goldreich-Levin Theorem (STOC 1989). We consider the following algorithmic problem: given oracle access to a function f:ℤqm→ℤqn such that Prx∼ℤqm[f(x)=Ax]≥ε for some A∈ℤqn× m and ε>0, recover A (or a list of all such matrices). We focus on the case ε≤ 1/q since when ε ≥ 1/q+δ, the problem is solved by the original Goldreich-Levin Theorem. As stated, this problem cannot be efficiently solved, since when ε ≤ 1/q the list of A with good agreement with f might be exponentially large. Our main theorem gives an algorithm which efficiently recovers a list of affine maps of size (1/ε ) which have good agreement with f, and such that every linear map which has good agreement with f, also has good agreement with some affine map in our list. Our proof makes novel use of Fourier analysis. Our main theorem has applications to effective property testing.
Implementation of the Trend Line Analysis Method on Newspaper Demand in the Digitalization Era: A Case Study

The rapid development of communication and information technology has given birth to new digital-based media that have changed people's behavior in consuming mass media.Consumers are significantly moving from conventional media to digital.Print media lost readers drastically, especially from the young group.This had some negative effects on the demand for printed newspapers, with frequent supply-demand inaccuracies resulting in many newspapers being returned.For this reason, it is necessary to determine the method of forecasting the number of newspaper requests that has the smallest error rate so that it can help companies reduce losses due to newspaper returns.This study calculates demand forecasting using the trend line analysis method in three conditions, namely when demand decreases, increases, and is seasonal.Furthermore, the three conditions are compared with the forecasting results.The selection of the forecasting method for the best conditions is done by comparing the error rate (MAPE) of each condition with the trend line analysis method, then the trend line analysis method is chosen under certain conditions with the smallest error rate.Based on the comparisons made, it can be seen that the forecasting method that has the smallest error rate is the trend line analysis method with an uptrend with a MAPE value of 4.56%.Therefore, the conditions that are suitable for using the trend analysis method are obtained, namely when demand increases or has an uptrend.
Risk Assessment of the Impact of Oil Spill on the Heavy Metal Content of Santa Barbara River in Bayelsa State, Nigeria

This study was aimed at assessing both the effect (risk) and impact of a recent oil spill on heavy metal concentration in the Santa Babara River in Bayelsa State, Nigeria. Samples were collected and preserved based on standard methods. The heavy metals of interest were Mercury (Hg), Arsenic (As), Cadmium (Cd), Chromium (Cr) and Copper (Cu) due to their levels of toxicities and presence in water bodies while the five study stations were Worokuma (W), Uwanga (W), Tuweni (T), Shellikiri (S), Inarakiri (I) and Esenfakiri (E). The solar thermos elemental flame atomic absorption spectrometer (AAS), model SE-71096 made in Germany with detection limit of 0.001 mg·kg−1 was used for the heavy metal analysis. The trend of heavy metal abundance was found in this order Cr&gt;Cu&gt;Cd&gt;Pb&gt;Hg=As. All the detectable metals had risk index of greater than 5 but the highest was found in the order, Cd&gt; Pb &gt; Cu &gt; Cr (149, 35, 26 and 12 respectively) which meant extremely high level of pollution. This also indicated the probability of non-carcinogenic effects occurring and increases as HI increases signifying carcinogenic risk via direct ingestion of water. Graphs were used to show trends in both mean heavy metal concentrations and risk assessment indices. Chromium and Pb had moderate contaminations for CF and CDI values, hence regular monitoring of the Santa Barbara River is of essence as most of the inhabitants take this as the only source of potable water as their wells have very high iron content.
Automatic Authorship Classification for German Lyrics Using Naïve Bayes

Text classification is a prevalent and essential machine-learning task. Machine learning classifiers have developed immensely since their inception. The naïve Bayes classifier is one of the most prominent supervised machine learning classifiers. In this experiment, we highlight the performance of Naïve Bayes for classifying of authors/artists on the German lyrics corpus (“Songkorpus”) and compare the classification results with other classifier algorithms. The corpus of investigation consists of six artists with 970 songs in total. Bayes model evaluation measures revealed a precision of 0.91, recall of 0.94, and F1-measure of 0.9. Furthermore, the classification performance with other classifier algorithms did not reveal any statistically significant difference in performance. The results of the study add to the high volume of reports on the classification accuracy of Naive Bayes for the task of lyrical classification.
Delightful screen time visualizations: A sketching-based exploration

Uncontrolled smartphone usage and excessive screen time are detrimental to people’s wellbeing. Informing people about screen time behavior is one strategy to help them attain digital wellbeing—a pleasurable, efficient, and controlled relationship with smartphones and other everyday technologies. This paper presents a series of sketches that explore unconventional, delightful screen time visualization on smartphones, illustrating an alternative to conventional screen time graphs. By showcasing these design concepts, this paper seeks to promote analog sketching as a valuable off-screen practice for design research, as it involves immersion, patience, and reflection.
Blockchain-Enabled IoT: Enabling Trust and Security in a Connected World

Abstract: Blockchain technology has gained significant attention for its potential applications in the Internet of Things (IoT) realm. By combining blockchain with IoT, a new paradigm emerges that offers enhanced security, transparency, and trustin IoT networks. In the context of IoT, a blockchain serves as a decentralised and immutable ledger that records all transactions and interactions among connected devices. This decentralisednature eliminates the need for a central authority, ensuring that data exchanges and smart contract executions occur in a transparent and tamper-proof manner. Blockchain enables the creation of trusted ecosystems and facilitates direct peer-to-peer interactions between IoT devices. Through the use of smart contracts, devices can autonomously execute predefined actions based on predetermined conditions, eliminating the need for intermediaries and central control. This decentralised approach enhances efficiency, reduces costs, and improves scalability in IoT networks. Blockchain enhances privacy in IoT networks through cryptographic techniques. Individuals can maintain ownership and control over their personal data, selectively granting access for specific purposes while preserving privacy. However, integrating blockchain and IoT also presents challenges; issues such as scalability, interoperability, and the computational requirements of blockchain consensus algorithms require further research and development to ensure widespread adoption. The paper suggests various approaches to opportunities and challenges
THE IMPORTANCE OF THE GAME IN THE CREATIVE DEVELOPMENT OF CHILDREN OF PRESCHOOL AGE

The importance of the game in the creative development of children of preschool age. The importance of play therapy in the activities of preschool children, ways of using game methods in the creative activities of preschool children and mental development of the child
A Novel Hybrid Optimization Algorithm for Materialized View Selection from Data Warehouse Environments

Responding to complex analytical queries in the data warehouse (DW) is one of the most challenging tasks that require prompt attention.The problem of materialized view (MV) selection relies on selecting the most optimal views that can respond to more queries simultaneously.This work introduces a combined approach in which the constraint handling process is combined with metaheuristics to select the most optimal subset of DW views from DWs.The proposed work initially refines the solution to enable a feasible selection of views using the ensemble constraint handling technique (ECHT).The constraints such as self-adaptive penalty, epsilon (ε)-parameter and stochastic ranking (SR) are considered for constraint handling.These two constraints helped the proposed model select the finest views that minimize the objective function.Further, a novel and effective combination of Ebola and coot optimization algorithms named hybrid Ebola with coot optimization (CHECO) is introduced to choose the optimal MVs.Ebola and Coot have recently introduced metaheuristics that identify the global optimal set of views from the given population.By combining these two algorithms, the proposed framework resulted in a highly optimized set of views with minimized costs.Several cost functions are described to enable the algorithm to choose the finest solution from the problem space.Finally, extensive evaluations are conducted to prove the performance of the proposed approach compared to existing algorithms.The proposed framework resulted in a view maintenance cost of 6,329,354,613,784, query processing cost of 3,522,857,483,566 and execution time of 226 s when analyzed using the TPC-H benchmark dataset.
Appraisal Attitude Analysis of Debate Verbal Adjudication

This research investigates the appraisal attitudinal framework to identify the level of attitude (affect, judgment, and appreciation) in debate verbal adjudication conducted through descriptive qualitative method. The theories supporting this thesis are the ones proposed by Martin &amp; White, Halliday, and Austin J. Freeley. The primary data sources in this thesis were five verbal adjudications of debate adjudicators from preliminary rounds of AEO 2020. The data in this study were lexical resources and phrases for appraisal attitudinal framework. The steps passed in this analysis are collecting the data by transcribing the recorded debate verbal adjudication into text, identifying the lexical resources and phrases, and concluding the analysis. The result of this thesis shows the score obtained for appraisal attitude resources in five debate verbal adjudications. The results present that the Appreciation score obtained was 59.1% in average, Judgment score obtained was 33.2% in average, and Affect score obtained was 7.7% in average. Thus, the level of appraisal attitudinal framework in debate verbal adjudications account for higher attitude of language evaluation. It is also demonstrates that the appraisal attitudinal element plays pivotal role in terms of directing evaluation towards the debater’s performance
Development and Application of Bioinformatics Program Using ICT for High School Students Under the Theme of COVID-19

Objectives The purpose of this study is to analyze the effect of the students' knowledge and information processing capabilities and scientific interest by developing and applying ICT (Information &amp; Communication Technology) bioinformatics program for high school students under the theme of COVID-19.&#x0D; Methods The 15th class program consisted of 5 topics was developed based on the appropriate teaching and learning types using ICT. The completed program was received internal validity from seven incumbent science teachers with more than eight years of educational experience. The developed program was applied to six first-year students in a special winter vacation class at G High School in G City in January 2022. In order to confirm the effect of the program, pre-post-test and semi-structural interviews were conducted on knowledge information processing capabilities and scientific interest. The pre-post test results were analyzed using the Wilcoxon signed rank test method. And the interview contents were transcribed and classified by sub-factors of knowledge information processing capacity and scientific interest to derive meaning.&#x0D; Results The program consists of the experiments of ACE(angiotensin I converting enzyme) gene which is the homolog of the coronavirus receptor, ACE2 (angiotensin converting enzyme 2), and COVID-19 vaccine and medicine card news production, bioinformatics card news production, and ACE and coronavirus gene analysis using NCBI (National Center for Biotechnology Information). As a result of conducting a pre-post test of knowledge information processing capability and scientific interest, it was confirmed that the pre-post difference was statistically significant (p&lt;.05). As a result of the pre-post inspection by sub-factor of knowledge information processing capability, the average of the sub-factor ‘information analysis’ is the most improved. In addition, as a result of the pre-post-test for each sub-factor of scientific interest, the average of the sub-factors ‘interest and enjoyment in science’ was improved the most. As a result of the interview, it was confirmed that students showed a positive effect on improving their ability to produce various outputs and internal interest in science through the ICT-based bioinformatics program under the theme of COVID-19.&#x0D; Conclusions This study is consisted of classes applicable to the general high school level and can be provided as various forms of basic teaching-learning guidance in classes related to bioinformatics, and is expected to be referred to in future bioinformatics-related educational research. In addition, it can be used as basic data for ICT utilization classes suitable for the digital age in science subjects.
Spontaneous Speech and Its Features Are Taken into Account When Creating Recognition Programs

The relevance of the stated subject of this scientific research is determined by the numerous difficulties of spontaneous speech recognition due to the presence of a complex of unrelated factors, as well as the need to find the best ways to overcome them through recognition programs that are used in the development of a multilingual corpus.This research aims to identify and study the key features of spontaneous speech that should be considered when creating recognition programs.The basis of the methodological approach in this scientific study is a combination of methods combining a systematic analysis of the principles of building a multilingual corpus with an analytical study of the principles of operation of spontaneous speech recognition programs.In the course of this scientific study, results were obtained that indicate a significant increase in the practical efficiency of automatic speech recognition systems when introducing sound signal correction algorithms, which opens up additional opportunities for developing such software.In addition, the results of this scientific study clearly demonstrate the significant impact of the accuracy of the effects of speech recognition programs on the quality of development of multilingual corpora, which include relatively large volumes of texts.The practical significance of the results obtained in the course of this scientific work, as well as the conclusions formulated on their basis, lies in the possibility of their use in the development of a multilingual corpus and spontaneous speech recognition programs for their subsequent use in various information systems, to obtain results related to the need accurate decoding of automatic speech, taking into account all its characteristic features.
Comparison of an automated digital cell morphology analysis system with manual counting

Abstract Background Bionovation's CSFA800 is a new automated digital cell imaging analyzer. We evaluated the performance of the CSFA800 by comparing it with artificial peripheral blood white blood cell counting. Methods According to inclusion and exclusion criteria, 131 randomly selected samples (77 abnormal samples and 54 normal samples) were compared. Correlations between automated and manual counting results were analyzed. Manual counting was carried out according to the guidelines of the Association of Clinical and Laboratory Standards. Results Counts of neutrophils, lymphocytes, monocytes, eosinophils, basophils, and immature granulocytes obtained from CSFA800 and artificial methods were linearly and positively correlated, with R values of 0.73, 0.65, 0.24, 0.2, 0.4, and 0.63, respectively, all p &lt; 0.05. Therefore, correlations between CSFA800 and manual counting are acceptable. Compared with the DI‐60 Automated Digital Cell Morphology System (DI‐60; Sysmex), CSFA800 is more efficient and can analyze 20,000 cells in 1 min. However, the overall accuracy of CSFA800 is not as good as DI‐60, although its counting performance is better for basophils. Conclusions The performance of CSFA800 for WBC counts is acceptable, and it displayed good performance for neutrophils, lymphocytes, and immature granulocytes. Compared to DI‐60, CSFA800 is more efficient but has slightly lower overall accuracy. To some extent, CSFA800 is helpful to optimize the clinical laboratory workflow and improve the working efficiency of inspectors.
On plane conic arrangements with $$A_{5}$$ and $$A_{7}$$ singularities

Abstract In the present note we provide combinatorial constraints on certain conic arrangements in the plane admitting $$A_{5}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>A</mml:mi> <mml:mn>5</mml:mn> </mml:msub> </mml:math> and $$A_{7}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>A</mml:mi> <mml:mn>7</mml:mn> </mml:msub> </mml:math> singularities. As a corollary, we provide upper bounds on the number of $$A_{5}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>A</mml:mi> <mml:mn>5</mml:mn> </mml:msub> </mml:math> and $$A_{7}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>A</mml:mi> <mml:mn>7</mml:mn> </mml:msub> </mml:math> singularities for such arrangements.