Reviewerly/exHarmony huggingface dataset:
DOMINANT SPEECH ACT TYPE IN DAILY CONVERSATION: A PRAGMATIC STUDY

Speech act is an act of communication that must be understood by the speaker and listener. Misunderstanding of speech act in conversation or dialogue can cause the misleading in the conversation. Therefore, this study aims to analyze the speech act types in daily conversation between students and parents at home. Qualitative research design was undertaken by the researcher to gain the speech act types. The research participants were twenty-four students of English Education department. Checklist was used to obtain the data. Moreover, the data were analyzed by using qualitative analysis by applying several stages from reduction, displaying and drawing conclusion. The result showed that several types of speech were found during conversation of students and parents at home. Those were directive, declarative, expressive and commissive. The dominant speech act type was directive because the parents asked the students to do something at home. Another finding showed that the students and parents did not use representative speech act in the conversation. It is because in the conversation between students and parents at home were informal conversation that seldom or never use representative. In short, it is not all speech appeared in the conversation because it depends on the function of speech act itself.
Geochemical and geological characteristics indicate the wolframite mineralization for seeking the type of wolframite mine in Vau village and ajacent area (Dong Giang district, Quang Nam province)

Wolfram mineralization in the area of Vau village (Dong Giang district, Quang Nam province) is distributed along the small stream together with other sulfide mineralizations in the form of small to large boulders. Ore minerals are mainly sheelite, pyrhotite, arsenopyrite a little of chalcopyrite and pyrite. The ore is distributed in stockwork type in the gray, light gray metamorphic sedimentary rocks with quartz - mica composition alternated with quartz feldspar mica schist, sericite schist and sericitized schist of the A Vuong formation (Sequene 3). Sheelite exists in the area manifested by hornflization and bezeritization. Ajacent area have weak skarnation. They have manifestations of the wolframite deposit of skarn type. Geochemical characteristics: W in the ore reaches 2,323 ppm (0.023%), As - 110,366 ppm (1.10%), Co - 212.3 ppm, related granite (Ba Na block’s granite) reaching 1,517 ppm wofram situated at the edge of the magma block (fine-grained alaskite, similar to the composition of boulders in the ore strip). There is small-grained granite with a content of 794 ppm at the center of mass. Thus, the two granite types have high level of metallogical specialization of wolframite (Ktt = 397 is fine-grained granite and Ktt = 758.7 is alaskite Granite). Besides, this rock has metallogical specialization of As (277.4 ppm in fine-grained granite, 29.9 ppm in alaskite).
Rationalization of Rainfall Station Density in the Jatiroto Sub-Watershed Using Ground and Satellite Rainfall Data

This study uses ground and CHIRPS data to rationalize the density of rainfall stations in the Jatiroto Sub-watershed, Lumajang Regency. This study aimed to determine the suitability of the CHIRPS satellite rainfall data to the measurement data. In addition, it determines the density of rainfall stations based on WMO standards. Also, the Kagan-Rodda method uses measurement and satellite data to determine rainfall station recommendations' results. The method used for the suitability test uses the value of RMSE, NSE, Correlation Coefficient, and Relative Error. And the WMO standard for analyzing the number of rainfall station. Knowing the rationalization and recommendations for placing rainfall stations using the Kagan-Rodda method by considering WMO standards, root mean square error, and interpolation errors. The results obtained include the appropriateness of satellite data, the number of rainfall stations at the research location according to WMO standards, and recommendations for rainfall stations based on Kagan-Rodda
Macroscopic distinguishability and scalability of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>N</mml:mi></mml:math> -mode field states

We compare the global properties of different types of $N$-mode states and discuss their distinguishability in the macroscopic limit $N\ensuremath{\gg}1$ by using the collective Wigner function, which is obtained by averaging over all the individual modes. It is shown that factorized $N$-mode states with a concentration of photons in a few modes are asymptotically indistinguishable from their symmetrized (i.e., highly correlated) counterparts in the case of collective measurements. In contrast, the collective properties of states with intermode distributed excitations are very different when compared to their symmetrized versions. We also discuss a class of scalable states for which the functional form of the collective Wigner function does not depend on the number of field modes, and we present results for the negativity of the collective Wigner function, for which in the macroscopic limit some states lose negativity and some do not.
A Novel Technique for Data Quality Improvement in Human Health PHM

Human healthcare data cover different signals related to the functioning of the human body such as blood pressure, blood glucose, heart rate, among others. This kind of data plays an important role on ill patients in the intensive care unit. Unfortunately, the recorded data may include connection &amp; human errors, measurement errors due to the movement of patients, among others. These errors are better known as Artifacts and they should be removed in case the data needs to be used for clinical purposes. Different methods have been proposed for artifact detection; however, the existing methods only analyze one signal at a time or rely on feature engineering. In this study, we present an alternative solution for artifact detection that integrates signals such as Intracranial Pressure (ICP), Electrocardiogram (ECG), and Arterial Blood Pressure (ABP). Time raw domain data, Fourier transform, and the combination of both were studied as the input of neural network models. Four deep learning algorithms were employed: convolutional neural network (CNN), long short-term memory (LSTM), bidirectional LSTM (BiLSTM), and transformer neural network. By performing a cross-validation ensemble using a dataset of 39 patients with noisy signals, the Fourier transform and CNN (FT-CNN) model outperformed the other deep learning models in terms of accuracy and computational time. This study shows that deep learning, Fourier transform, and cross-validation ensemble combined have a great potential in data quality improvement in healthcare.
Cohesion and Coherence in Students' Thesis Abstract Writing

Final-year students should have the ability and competence to write, including in writing their thesis abstracts. Although short, abstract writing must pay attention to several things. One indicator of good writing is marked by using logical, consistent words that are easy to understand. This study aims to identify the types of cohesion (grammatical and lexical) and coherence in writing abstracts for final students of AKI University and whether they have fulfilled cohesive and coherent writing. This study analyzes 16 undergraduate thesis abstracts for the English Literature study program for the 2019-2022 and 2020-2021 academic years. This study uses qualitative and quantitative research methods to achieve this goal. The result shows that the students use lexical cohesion devices much more than grammatical ones. Unfortunately, neither substitution nor ellipsis devices were found. Even so, the students have pretty good competence in making cohesive abstracts. On the other hand, the results of the coherence analysis show that all students have a good understanding of using all aspects of coherence. But even though they use all aspects, not all students succeed in creating coherent writing wholly.
Biphoton engineering using modal spatial overlap on-chip

Photon pairs generated by spontaneous parametric downconversion are essential for optical quantum information processing, in which the quality of biphoton states is crucial for the performance. To engineer the biphoton wave function (BWF) on-chip, the pump envelope function and the phase matching function are commonly adjusted, while the modal field overlap has been considered as a constant in the frequency range of interest. In this work, by using modal coupling in a system of coupled waveguides, we explore the modal field overlap as a new degree of freedom for biphoton engineering. We provide design examples for on-chip generations of polarization entangled photons and heralded single photons. This strategy can be applied to waveguides of different materials and structures, offering new possibilities for photonic quantum state engineering.
DESIGNING MADING ONLINE AT AMIK WAHANA MANDIRI, SOUTH TANGERANG

Mading in general contains positive and informative things so that it can be an up to date, cheap, and creative communication medium. In terms of campus information, Mading can be conveyed news about the progress of the campus, both in the academic side of students and teaching lecturers as well as campus facilities and infrastructure. Inseparable from that, Mading Kampus can function as a campus promotion medium. However, with the development of the technological age that is increasingly practical in sharing information, Mading's role on campus is less interested by students because it is less interesting and less practical. In terms of work and achievements, Mading will accommodate the creativity of students who are very diverse in the form of ideas, ideas, thoughts, imagination, art, existing creative power. There needs to be a place to channel this creativity, therefore it is necessary to form an Online Mading at the dynamic AMIK Wahana Mandiri South Tangerang Campus by utilizing advanced PHP-based web technology.&#x0D; Keywords : Mading, Online, Web, PHP, MySQL, Technology, Information
Uniform Resource Locator Classification Using Classical Machine Learning &amp; Deep Learning Techniques

In the Internet era, there is no doubt that the Internet has helped us in many ways by providing us with a means to communicate with anyone around the world. That is said, some people misuse such technology to conduct malicious behaviors. Many things could be exploited to perform such acts, but this work focuses on exploitation methods that use the uniform resource locator (URL). This paper presents the means to extract features from a raw URL. These are used to predict whether a URL is safe for a user to visit or not. The whole process of extracting the data and preparing it for a model is discussed thoroughly in this paper. Several machine learning (ML) models have been trained using different algorithms, including Catboost, RandomForest, and Decision trees, in addition to using and exploring several feedforward deep neural networks learning models. The best model achieved an accuracy of 95.61% on a test set using a deep learning model.
Review on Types of Attacks on Bitcoin and Ethereum crypto currencies

Among the new way of exchanging money, using crypto currency has been very popular. Its also an investment to get good returns over the period of time. Cryptocurrency has grown to more than 120 million investors around the world as per a survey of 2021.Its growing at the 15 to 20% ratio around the world every year. This fact leads to a serious consideration of security and its vulnerabilities in block chain. Apart from market risks, high volatility, lack of rules and regulations, cyber risks are one of the most required types which needs proper attention and technical understanding. Because the crypto currencies are fully decentralized the risk of attacks is exposed and in most of the cases defenseless. Proof of stake and proof of work are two major algorithms followed by almost all crypto currencies to allot stocks to the holders. In this paper, different types of risks and attacks with POS and POW are explained with its mitigation. The problems and outcomes are examined, reviewed and conferred in case of Ethereum and Bitcoin crypto currencies. These currencies decentralized frameworks and anonymity attracts unlawful activities. Recognizing and preventing them needs understanding of the mechanism of attacks which are discussed in easiest possible ways for even a new-bee or an outsider person.
A Wavelet Based Digital Image Watermarking Technique through Encryption with DCT

Recently, due to the increase in popularity of the Internet, the problem of digital data security over the Internet is increasing at a phenomenal rate. Watermarking is used for various notable applications to secure digital data from unauthorized individuals. Digital image watermarking is an attractive research area since it protects the multimedia data from unauthorized access. Digital images are widely communicated over the internet. The security of digital images is an essential and challenging task on shared communication channel. In the era of big data and networking, it is necessary to develop a secure and robust digital watermarking scheme with high computational efficiency to protect copyrights of digital works. Digital watermarking is need for the security of digital images to achieve security goals, i.e. confidentiality, integrity and availability. With the use of sophisticated signal/image processing algorithms, manipulations and duplications of audio, images, and videos are much easier. Hence, content authentication through encryption and resistance to general attacks such as noise, compression, and geometric has become an urgent and important issue. Hence in this work a wavelet based digital image watermarking technique through encryption with DCT (Discrete Cosine Transform) is presented that can guarantee robustness of image against salt and pepper attack.
A Case Study of 271 Education Group’s Learning Protocols: Reconstruction of Course Contents Based on Holistic Module Learning

The holistic module learning and protocol-guided learning concepts underpin 271 Education Group’s learning protocols. This article discussed the history of learning protocol development and its significance. Using the experience of 271 Education Group as an example, we attempted to illustrate the fundamental structure of learning protocols. It is hoped that this study will have an effect on how the new national curriculum program and course standards are put into place.
A<sup>3</sup>R: Argumentative explanations for recommendations

Existing recommender systems often apply factorization-based models, which have been proved to be efficient in rating prediction. However, the explicit semantics of the learned latent factors are not clear, which makes it difficult to explain the recommendations returned. In another line of research, argumentation-based methods have become an important tool in explainable artificial intelligence. In this work, we propose an Attribute-Aware Argumentative Recommender (A <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> R) that combines factorization-based methods and argumentation. With the help of argumentation framework, each step of A <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> R is endowed with explicit semantics, enabling A <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> R to generate easily understandable explanations for recommendations. Experiments on five datasets from three different domains (movie, music, and book) show that A <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> R can achieve competitive rating prediction when compared with factorization-based methods; A <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> R can largely improve prediction accuracy when compared with state-of-art argumentative recommendation methods.
Pengaruh Motivasi Belajar terhadap Prestasi Belajar IPS Siswa Kelas VI di UPTD SD Negeri 122348 Pematangsiantar

The Influence of Motivation on Social Studies Learning Achievement of Class VI Students at UPTD SD Negeri 122348 Pematangsiantar. Thesis. UHKBPNP University Primary School Teacher Education and Education Studies Program. Advisor I Lisbet Novianti Sihombing,S.Pd.,M.Pd and Advisor II Hetdy Sitio M.Pd. This study aims to determine whether there are. The Influence of Motivation on Social Studies Learning Achievement of Grade VI Students at UPTD SD Negeri 122348 Pematangsiantar. This study aims to determine the description of the social studies learning motivation of grade VI students and how much influence the social studies learning motivation of students at UPTD SD Negeri 122348. This study is a quantitative method, with the entire research population. class VI students totaling 33 people. The results showed that the description of the social studies learning motivation of students at UPTD SD Negeri 122348 Pematangsiantar was in the high category, namely 87% of the social studies learning achievement of students and the influence of social studies learning motivation.
Pengaruh Model Pembelajaran Inkuiri terhadap Hasil Belajar Siswa pada Subtema 2 Di Kelas III SD Negeri 091316 Pematang Raya

This research purpose is to know the effect of inquiry model to study result students, the types of research of experiment with quasi design a give pre-test and post-test. This research do the class III in SD Negeri 091316 Pematang Raya .where experiment class used learning inquiry class while in control class used conventional model. Where the analysis data can find by an application program SPSS statistics 21.0 and Microsoft excel application. Based on explain above the analysis data result research find result T-test where the t-test &gt;t-table namely 3,204 &gt;2,010 with counting score significant (2-tailed)&lt;0,05.sothat find the different experiment class with control class. Can see by score significant (2-tailed) = 0,002 &lt; 0,05. So, Ho can say not significant and Ha significant. Based the result can conclude that the effect of model learning inquiry to study result students in Subtema 2 class III SD Negeri 091316 Pematang Raya. The improving presentation study result to learning give with used learning model inquiry and study result students the use learning model conventional is 13%
POJOK PENGINYONGAN PERPUSTAKAAN UIN PROF. K.H SAIFUDDIN ZUHRI PURWOKERTO SEBAGAI SARANA PELESTARIAN BUDAYA LOKAL BANYUMAS

UIN Prof. K.H. Saifuddin Zuhri Library has a uniqueness, namely the availability of Pojok Penginyongan which provides various collections of local Banyumas culture. This can be said to be unique because it is still rare for university libraries to provide such services. This study aims to determine the purpose of the implementation, the obstacles faced in the technical aspects of collection management, both in terms of procurement, maintenance, and to service the collection. This research is a descriptive qualitative research. Research data collection are interviews, observations, and documentation. Data analysis was carried out by data reduction, data presentation, and drawing conclusions. Based on the research findings, it can be seen that the purpose of the Pojok Penginyongan is to realize the Rector's work program to preserve local culture in the Banyumas residency. In relation to the number of collections, the library continues to develop or add to it by collaborating with public libraries and other university libraries and Banyumas community figure. For collection maintenance, the library applies the same mechanism as other collections, for example routinely fumigating, maintaining room temperature, and there are special guidelines for library users to minimize errors in the utilization of the Pojok Penginyongan collection.
[Medical image super-resolution reconstruction via multi-scale information distillation network under multi-scale geometric transform domain].

High resolution (HR) magnetic resonance images (MRI) or computed tomography (CT) images can provide clearer anatomical details of human body, which facilitates early diagnosis of the diseases. However, due to the imaging system, imaging environment and human factors, it is difficult to obtain clear high-resolution images. In this paper, we proposed a novel medical image super resolution (SR) reconstruction method via multi-scale information distillation (MSID) network in the non-subsampled shearlet transform (NSST) domain, namely NSST-MSID network. We first proposed a MSID network that mainly consisted of a series of stacked MSID blocks to fully exploit features from images and effectively restore the low resolution (LR) images to HR images. In addition, most previous methods predict the HR images in the spatial domain, producing over-smoothed outputs while losing texture details. Thus, we viewed the medical image SR task as the prediction of NSST coefficients, which make further MSID network keep richer structure details than that in spatial domain. Finally, the experimental results on our constructed medical image datasets demonstrated that the proposed method was capable of obtaining better peak signal to noise ratio (PSNR), structural similarity (SSIM) and root mean square error (RMSE) values and keeping global topological structure and local texture detail better than other outstanding methods, which achieves good medical image reconstruction effect.高分辨率磁共振成像（MRI）和计算机断层扫描（CT）影像能够提供更清晰的人体解剖细节，有助于疾病的早期诊断。但是，由于成像系统、成像环境和人为等因素限制，清晰的高分辨率图像难于获得。本文提出一种非下采样剪切波变换域（NSST）多尺度信息蒸馏（MSID）网络的医学影像超分辨率重建方法（即NSST-MSID网络）。首先，提出一种MSID网络，主要由多个级联的MSID块构成，充分探取图像的多尺度特征，有效恢复低分辨率图像至高分辨率图像。此外，由于现有方法往往在空间域预测高分辨率图像，使得输出过于平滑且丢失了纹理细节，因此将医学图像的超分辨率问题描述为NSST系数的预测问题，使得MSID网络比空间域保持更丰富的结构细节。最后，在建立的医学影像数据集上对提出的方法进行性能评价。实验结果表明，与其他现有杰出的方法相比，NSST-MSID网络可以得到较优的峰值信噪比（PSNR）、结构相似性（SSIM）及均方根误差（RMSE）值，更好地保留了局部纹理细节与全局拓扑结构，实现了不错的医学影像重建效果。.
A Chaotic Clifford Attacker Map-based Image Encryption in Double Random Phase Encoding

Encryption is the most useful technique used for the security of data during storage and transmission. A well-known encryption scheme called Double Random Phase encoding was introduced by Refregier and Javidi. But due to its linear nature, this scheme has been proven vulnerable against Known plaintext and chosen plaintext attacks. Here in this paper, we propose a chaotic map-based nonlinear encryption scheme that enhances the security of the DRPE encryption scheme for images. Clifford attacker is a non-linear chaotic map that has four parameters and two initial values. This map is highly sensitive to these values. Therefore, these parameters and initial values work as extra secret keys. MATLAB simulation shows that the proposed technique enhances the security level of the DRPE and at the same time has a better immunity to noise and occlusion attacks.
Jarvis: Artificial Intelligence-based Voice Assistant

In this project, we'll create a voice assistant named Jarvis that can open files, conduct web searches, retrieve Wikipedia results, read PDF files, launch applications, and even make jokes and provide you advice. Artificial intelligence based Voice assistants are the working frameworks that can perceive human voice and answer through coordinated voices. The voice assistant will collect audio from the microphone, convert it to text, and send it over GTTS (Google text to speech). The English-language audio file created by the GTTS engine will be played using the play sound module of the Python programming language. We are importing libraries such as "os" for operating system tasks, "speech recognition" for voice command analysis, "pyttsx3" for voice command into text strings, "Time" for fetching the current time and date, "web browser" for web-based tasks on default web browsers, and "SMTP" (Simple Mail Transfer Protocol) for email transmission between accounts over the internet.