Reviewerly/exHarmony huggingface dataset:
Pengembangan E-Book Pekerjaan Dasar Elektromekanik Berbasis Student Facilitator and Explaining

This research is based on the background of learning media for Electromechanical Basic Work subjects that are still minimal and the learning model used is still teacher-centered. This study aims to develop an e-book of Electromechanical Basic Work subjects using the student facilitator and explaining a learning model that is valid, practical and effective. This type of research is a development research method (Research and Development). The method used is the 4-D model which consists of defining (Define), designing (Design), developing (Development), and disseminating (Disseminate) stages. The research subjects were students of class X TITL SMK Negeri 1 Kerinci. Data collection techniques use evaluation sheets in the form of questionnaires for validity and practicality data, while objective tests are used for effective data. The results showed that (1) the validity test of the Electromechanical Basic Work e-book using the SFAE learning model had been checked and declared valid. (2) the practicality test of the Electromechanical Basic Work e-book using the SFAE learning model has been checked and declared practical. (3) the effectiveness test of the Electromechanical Basic Work e-book using the SFAE learning model has been checked and declared effective. It can be concluded that the e-book of Electromechanical Basic Work subjects based on the student facilitator and explaining learning model is worth distributing because it has been declared valid, practical, and effective.
Pelatihan Penggunaan Aplikasi Rumah Belajar Bagi Siswa Yang Ada di Desa Ubung Sebagai Sarana Belajar Mandiri di Rumah

The purpose of this service is to minimize the negative impact of the internet. Methods of implementing community service, including: Preparation of activities; The mechanism for implementing the activity, before going into the field, it is necessary to do a number of things as a form of preparation, including: (a) Collect data and verify students in Ubung village. (b) Socialization of the program to students in Ubung village regarding the service program plan and the characteristics of local students who will be involved in implementing the work program. The results to be achieved from this Community Service activity or program are as much as possible for the benefit of local students, namely having a learning homeapplication and creating independent learning for students by utilizing the learning home application to reduce the negative impact of the internet and increase motivation and increase student learning achievement. In conclusion, by utilizing the learninghouse application, it is hoped that it can provide technology and skills to students on how to use the learning house application, so that it can reduce the negative impact of the internet.
The Prospects of Computer-Enabled Voting Systems in Pakistan

Democracy is the power vested in people to choose and elect their representatives. However, theprocess of election and voting is prone to rigging leading to undeserving people leading a nationwhich further causes mistrust and agitation amongst the people. Various methods have beenproposed and implemented towards free and fair elections. In this survey we list and discussdifferent methods proposed and adopted for voting. These include the techniques which wereintroduced in past and can be implied in future, the techniques by which voting system can bemade more secure are, the remote voting, internet/online voting, a RFID tags, a fingerprinttechnology and IOT for updating, two languages the extensible markup language and anotherone is the extensible style language are used to design a unique content and cannot be copied.Other technology like electronic voting machine with battery can be useful in rural areas whereinternet is not available and last one is the blockchain technology by which the voter can casttheir vote in no time, and can have trust on that as this technology is end-to-end encrypted, heredata can be saved in sealing blocks. All this work is to find a better way to make the votingsystem more reliable and trustable for the future. In the end we discuss the efficacy of thesesystems in current infrastructure and requirements of Pakistan.
Penerapan Sistem Proposional-Integral-Derivatif Pada Hatchery untuk Meningkatkan Produktivitas Day Old Chick (DOC)

The Livestock Product Processing Technology Laboratory is one of the centers of practicum, research or community service activities at the Banyuwangi State Polytechnic where it has a hatchery machine with a capacity of 500 grains, the hatchery machine has been modified so that the temperature and humidity can be controlled properly, but the machine still has some disadvantages. In addition to frequent errors in the heater, The system used still uses an on/off control system as a temperature and humidity regulator, so it can cause over shoot or under shoot which can cause fluctuations in temperature and humidity, so it is necessary to apply Proposional-Integral-Derifativ (PID) control which is able to accelerate the response of a system, eliminate offsets and produce large initial changes The purpose of this study was to determine the performance of the tool by applying PID control to hatchery machines that were tested to hatchability and Knowing the temperature and humidity settings to get the best results from the application of PID control on the hatchery machine. This research began with the preparation of the PID control series, namely making hardware and software designs using Arduino, sterilizing hatchery machines and setting temperatures of 37ºC and temperatures of 38ºC and humidity of 65 and 67%, entering eggs for 21 days and collecting data, hatchability and hatching. The results showed that PID control provided constant temperature and humidity stability at 37ºC and 38ºC temperatures, the best temperature and humidity use treatment at 38ºC was able to hatchability of 78.26%.
Simulating Humans at Scale to Evaluate Voice Interfaces for TVs: the Round-Trip System at Comcast

Evaluating large-scale customer-facing voice interfaces involves a variety of challenges, such as data privacy, fairness or unintended bias, and the cost of human labor. Comcast's Xfinity Voice Remote is one such voice interface aimed at users looking to discover content on their TVs. The artificial intelligence (AI) behind the voice remote currently powers multiple voice interfaces, serving tens of millions of requests every day, from users across the globe.In this talk, we introduce a novel Round-Trip system we have built to evaluate the AI serving these voice interfaces in a semi-automated manner, providing a robust and cheap alternative to traditional quality assurance methods. We discuss five specific challenges we have encountered in Round-Trip and describe our solutions in detail.
Micro to Macroscale: the three-dimensional network characteristics of serpentinite dehydration veins

On Earth, subduction zones facilitate the cycling of volatiles between the Earth&amp;#8217;s surface and interior. Volatile cycling has significant effects on the long-term state of the Earth&amp;#8217;s climate and tectono-magmatic events, including volcanism and earthquakes. A key stage in the volatile cycle is the devolatilization of the subducting oceanic lithosphere, in which volatiles can escape the previously hydrated rocks. However, it is not well known how efficiently volatiles are transported at this stage. To better understand how volatiles escape at these conditions, we have analyzed the dehydration-related vein networks of the Erro-Tobbio meta-serpentinites (ET-MS), Italy. The ET-MS display well preserved networks of metamorphic olivine veins. These veins are the result of the dehydration reaction of antigorite and brucite to produce H2O and olivine. However, due to the low permeability of serpentinite at depth, the dehydration reaction requires the formation of self-organizing vein networks to allow the produced fluid to escape [1]. Thus, the metamorphic olivine veins in ET-MS may be used as a proxy for fluid flow pathways. We took a multiscale approach to analyzing the network architectures. For microscale (~16 &amp;#181;m voxel size) and mesoscale (~200 &amp;#181;m voxel size) resolutions, X-ray tomography methods are sufficient to visualize the three-dimensional structure of the networks. However, for large scale observations these methods are inapplicable. To solve this, we apply a novel workflow to analyze outcrop scale (~10 m) network systems in three dimensions using only two-dimensional data. By training a generative adversarial network (GAN) with two-dimensional data conditioned by spatial orientation, we can generate statistically representative three-dimensional networks that mimic those of the ET-MS. These representations also display similar characteristics in their respective pore-network-models. With this method, it is possible to produce reasonable three-dimensional approximations of the ET-MS vein networks using only photogrammetry data of the outcrops. In turn, this allows us to extract metrics, such as permeability, that describe the volatile transport efficiency of the ET-MS, and further, how these characteristics change at a broad range of scales.&amp;#160;&amp;#160; [1] Pl&amp;#252;mper et al. (2017) Nature Geoscience 10(2), 150-156.&amp;#160;
Causes of the extremely low solar radiation in the 2021 growing season over southeastern Tibetan Plateau and its impact on vegetation growth

The Tibetan Plateau (TP), known as the &amp;#8216;Third Pole&amp;#8217; region, is one of the most sensitive places to global climate change, which possesses the highest surface incident solar radiation (SSR) in China. In the 2021 growing season, i.e., May to September, southeastern Tibetan Plateau (SETP) registered a widespread and extremely low SSR since 1950 with approximately -18.65 W/m2 of regional mean anomaly relative to 1950-1979 mean. Through the analyses using observations, reanalysis and CMIP6 model simulations, the extremely low SSR event in 2021 is mainly attributed to more clouds and abundant atmospheric moisture caused by anomalous southerlies from the Bay of Bengal. The existence of abnormal south winds could increase the probability ratio of such low SSR events like 2021 to be 9.25 (95% CI: 6.56-19.02). Anthropogenic aerosols and GHGs-induced warming might increase the probability of such SSR events to be a factor of 4.70 (95% CI: 1.66-15.49) and 1.66 (95% CI: 1.01-6.59), respectively. As a result, the extremely low SSR event could significantly reduce local gross primary productivity in the 2021 growing season over SETP, especially in the humid eastern SETP where SSR has a stronger impact on vegetation photosynthesis.
"Paleopedology of Siwalik Paleosols of Kangra Sub-Basin, NW Himalaya: Implication for Weathering and Climate change 11 Ma to 6 Ma"

The Himalayan Mountain range is the most prominent and active intracontinental range in the world. The outer part of this range is marked by the Himalayan foreland basin (HFB) in south that resulted due to the thrust loading and subsidence with synorogenic sedimentation from the hinterland. The lowermost part of the HFB is marked by the molassic sediments of &amp;#8220;Siwalik&amp;#8221; which thins out to the south. The time frame between 11Ma to 6 Ma (mid to late Miocene) is critical to understand the changes related to monsoon and vegetation as there is no detailed record or systematic study of late Cenozoic weathering and paleopedogenesis in fluvial sediments of the HFB. In the present study, we present a high-resolution paleopedological record of the paleosols along a traverse of ~ 1.8 km in the Kotla-Brail section of the Kangra sub-basin of the HFB. In the field, the paleosols are characterized by 1-2 m thick Bw, Bt, Bk, Bss, Bk horizons, rhizocretions, pedogenic carbonates (PC), and Fe/Mn mottles and concretions. The paleosols in the Lower Siwaliks show a dominance of 2.5 Y and 5 YR hue, whereas in the Middle Siwaliks they are defined by 5 YR and 7.5 YR hue. Micromorphology of these paleosols confirmed varying degrees of weathering, and paleopedogenesis showing a blocky structure, clay coatings, biogenic activity, and diffused impure micritic nodules as PC in the Bw and Bt, Btk horizons. These pedofeatures are more strongly developed in paleosols of the Lower Siwaliks than in comparison to weakly-moderately paleosols of the Middle Siwaliks.Clay mineralogy determined based on XRD study of the total (&lt;2 &amp;#181;m) fine clay (&lt;0.2 &amp;#181;m) fractions of these paleosols is characterized by the dominance of smectite, vermiculite, and mixed-layer minerals in paleosols of the Lower Siwalik. The clay mineral assemblage shows a&amp;#160; decrease in the abundance of smectite and increase of kaolinite towards the transitions to Middle Siwalik at ~10 Ma. This also shows transformation of the smectite and vermiculite to interstratified clays at about ~8 Ma. After ~8.5 &amp;#8211; 8.0 Ma, the paleosols are again marked an increase of the amount of smectite, vermiculite, and mixed-layer minerals in paleosols of the Middle Siwalik towards their transitions to Upper Siwalik. The varying intensity of weathering, paleopedogenesis, and clay mineral assemblage of the paleosols in the Lower and Middle Siwalik suggest fluctuating climatic conditions that evolved from initial semi-arid to sub-humid at ~11 Ma that to higher precipitation at ~8.5 to 8 Ma then again to semi-arid to arid conditions at ~6.5 Ma.&amp;#160;Keywords: Himalayan Foreland Basin (HFB), Siwalik, Paleosols, Micromorphology, Clay Minerals
Combining Bayesian Neural Networks with explainable AI techniques for trustworthy probabilistic post-processing

The large data volumes available in weather forecasting make post-processing an attractive field for applying machine learning. In turn, novel statistical machine learning methods that can be used to generate uncertainty information from a deterministic forecast are of great interest to forecast users, especially given the computational cost of running high resolution ensembles. In this work, we show how one such method, a Bayesian Neural Network (BNN), can be used to post-process a single global high resolution forecast for 2m temperature. This methodology improves both the accuracy of the forecast and adds uncertainty information, by predicting the distribution of the forecast error relative to its own analysis.Here we assess both model and data uncertainty using two different BNN approaches. In the first approach, the BNN&amp;#8217;s parameters are defined to be distributions rather than deterministic parameters, thereby generating an ensemble of models that can be used to quantify model uncertainty. In the second approach, the BNN remains deterministic but predicts a distribution rather than a deterministic output thereby quantifying data uncertainty. Our BNN results are benchmarked against simpler statistical methods, as well as statistics from the ECMWF operational ensemble.Finally, in order to add trustworthiness to the BNN predictions, we apply an explainable AI technique (Layerwise Relevance Propagation) so as to understand whether the variables on which the BNN bases its prediction are physically reasonable or whether it is instead learning spurious correlations.
Corrigendum: Digitalization and digital transformation in higher education: A bibliometric analysis

[This corrects the article DOI: 10.3389/fpsyg.2022.1081595.].
Embedded Foucault’s Pendulum Amplitude Measurement and Control System

This article deals with the problem of measuring the amplitude of the Foucault’s pendulum. In this context, the applied methods and procedures are first described, after which the structure of the embedded system for measuring and controlling the amplitude of the Foucault’s pendulum is presented. It is mentioned that in order to provide planetary astronomical measurements, the architecture of the measurement and control system must fit into the edge-to-cloud continuous computing paradigm. For this purpose, the pendulum must be kept in oscillation mode, without interfering with natural phenomena affecting the pendulum.
Human Pose Estimation Based on SNHRNet

Human pose estimation is the basis of human action recognition, and it is the guarantee to realize human-computer interaction. Occlusion, interference, complex background and different human scales have great influence on single-human pose estimation. To obtain more semantic information and reduce the impact of different human scales, an improved SNHRNet deep learning network is proposed to achieve more accurate single-human pose estimation. The improved SNHRNet network is established based on the HRNet network. The optimized NHRNet network is obtained by cutting the low-resolution high-level features of the HRNet. Compared with HRNet, the parameters of the NHRNet network are reduced, but the attention mechanism is missing. On this basis, the SE module is integrated into the Basic residual module to make up for the lack of attention mechanism in NHRNet network, and the SNHRNet network model comes into being. Finally, the public dataset is used for single-human pose estimation experiment. The results of relevant experiment show that the proposed SNHRNet network is effective for single-human pose estimation.
Deixis Analysis on Article in CNN International

Each language, including English, uses deixis differently due to various distinct settings, such as grammatical restrictions and cultural or customary backgrounds in society. Descriptive qualitative research is the method used to analyze the data. As data-gathering instruments, human instruments and text analysis were used. All of which are used in written form to refer to the speaker, recipients, and references who are not speakers or recipients. According to the research, the personal pronoun deixis is most commonly used in the human subject's second, third, and possessive plural forms. Additionally, deixis with a temporal focus is used in CNN International articles as speech moments, and there are two different times: the "coding" and "receiving" times (the time of recovering information by the listener who is informed). Keywords: CNN International, Deixis, Pragmatics
Security Challenges from the Integration of AI with Blockchain

The way things are done in the computer world has changed because of the Internet of Things (IoT).Therefore, it's so important to integrate cloud computing with IoT devices because of how much data such devices create and how much storage and processing power they need.The fact that users share a variety of cloud computing services among their devices in different ways makes security issues more crucial even so.In a world when unprotected data might endanger our welfare, privacy is even more important.Therefore, the IoT and cloud computing must constantly assure the users' worries about security and privacy.This study examined security concerns and potential IoT application tactics for cloud computing.According to the results, there are still significant security dangers and issues that need to be resolved.To reach that purpose, it is necessary to build the architecture and modify the present program.This article covers the many security issues that the IoT and cloud computing are experiencing, particularly the worries about user privacy and cybersecurity risks.
Underwater Image and Under Exposed Image Enhancement Using Convolution Neural Network

The turbidity media (for example, particulates, liquid) throughout the air degrades pictures from outside sceneries. Smog, mist, as well as smoky were examples of air absorptive processes. All along sight line, the lens receives less irradiation from video frame. In addition, the entering sunlight gets mixed with the sunlight from atmosphere (ambient light reflected into the line of sight by atmospheric particles). Intensity and correct information are lost in deteriorated photos. The deterioration is spatially variable because of the quantity of dispersion varies mostly on distances between the arty as well as the lens. In both customer imaging and image processing systems, fog removal1 (or poor) was widely sought. Firstly, reducing fog may greatly improve picture vision while also correcting that could go produced by the air sunlight. In speaking, the picture with no mist is far more attractive. Secondly, many neural networks presume that input layer (following rectangular grid) represents full animation, through reduced image processing to elevated object detection. This skewed, low - light picture illumination would unavoidably decrease the quality of machine vision (for example, focused product, filtration, and radiometric analyses). Finally, fog reduction may generate detailed information, which would be useful for several computer vision and sophisticated photo retouching. For picture comprehension, mist or foggy could be a helpful height indication. This picture of lawful fog could be put to good advantage. Decreased activity, on the other hand, is indeed a difficult challenge since the fog was based upon uncertain depth data. If indeed the data is merely a small hazy picture, then issue is under constrained. As a result, numerous solutions based on various pictures or other data were presented.
Implementation of Bound Morpheme Through A Text to The Students of HKBP Nommensen Pematangsiantar University

Words are composed of morphemes. The notion that morphemes are words is not necessarily true. While some single morphemes can function as words, some words have two or more morphemes. Furthermore, it is wrong to consider morphemes to be syllables. In contrast, many words only have one syllable and two morphemes; examples are "cats," "runs," and "barked." Morpheme can be classified as either Free or Bound Morpheme. It applies the Bound Morpheme's restriction, which included eight inflectional affixes. The goal is to determine how pupils use bound morphemes. This study's research tool was acquired through testing. Knowing the sort of error and where it happens helps with testing. The procedures for data analysis were applied by the data analysis methodologies. Counted the Bound Morpheme first. Second, they were divided into groups. Thirdly, the number of frequently occurring terms was counted. Fourthly, determined which word should be chosen and which should not be. Then, based on the total number of words with the ratings Excellent, Good, Fair, and Poor, percentages were calculated. Meanwhile, based on the results of the The student’s ability in implementing the Inflectional Affixes is 38% as a very good category, 25% as a good category, 25% as a fair category, and 12% as a low category in implementing the Inflectional Affixes of Bound Morpheme on the text.
Influence Number literacy Letters and Number Hope Life to Amount Number PovertyYear 2015-2021

This study aims to determine how much influence the Literacy Rate and Life Expectancy Rate on Poverty Levels in the Provinces of Aceh, West Java, DKI Yogyakarta, and East Java in 2015-2021.The method used is a quantitative method.Data obtained from the Central Statistics Agency and processed by the author using the E-views 9 application to help obtain conclusions.Poverty is one of the fundamental problems, because poverty involves meeting the most basic needs in life and poverty is a global problem because poverty is a problem faced by many countries.Life Expectancy (AHH) is the estimated average number of years for a person can live for a lifetime.Literacy is the ability to identify, understand, translate, communicate, create, and process the contents of a series of texts contained in printed and written materials related to various situations.The literacy rate variable has no significant effect on the level of poverty in the provinces of Aceh, West Java, DKI Yogyakarta, and East Java.When the literacy rate increases, the poverty rate will decrease.Meanwhile, life expectancy has a positive and insignificant effect on the Poverty Level in the Provinces of Aceh, West Java, DKI Yogyakarta, and East Java.when the life expectancy increases, the poverty rates will increase.