Reviewerly/exHarmony huggingface dataset:
DESIGN AND DEVELOPMENT OF TARGET DESIGN WITH BASIC IMAGE PROCESSING ON OTHTT SYSTEM PROTOTYPE (OVER THE HORIZON TARGET TRACKING)

Based on Law No. 34 of 2004, the Indonesian Navy has the main task of maintaining state sovereignty in territorial waters. Various attempts have been made to strengthen the Navy so that it can carry out these basic tasks, one of which is to add defense equipment, namely ships that have the ability to shoot missiles. This missile possession is important because in addition to being a deterence effect, modern naval battles are dominated by long-distance warfare or Over The Horizon. In missile fire, accurate intelligence is needed to determine the position of the target. So far what has been done is sending submarines or reconnaissance aircraft. This is very inefficient because in addition to requiring large resources, the risk of losing personnel and material is also very large. Based on this, the researcher makes a prototype of a vehicle that can identify and determine the position of a target. The vehicle in the form of a UAV is equipped with GPS, altimeter, compass and camera. This equipment will provide data in the form of UAV latitude and longitude position, UAV height, UAV heading and UAV camera angle. From the four data above, the ground station on themissile carrier gets the target's latitude and longitude data based on image processing. While the method used is color thresholding which can distinguish a target based on its color. After several trials, the UAV has been able to carry out the target positioning up to a height of 15.4 meters. At these heights the target latitude can be determined with a system accuracy of 3.3 meters. To be used as a reference for missile firing, it is necessary to increase the capability of the equipment specifications to reach the desired distance.&#x0D; Keywords: Target, Latitude, Longitude, Image Processing.
Research Guides: Button Maker Guide: Button Resources

Basic information on how to make buttons using the button makers available for in-library use at the Asa H. Gordon Library.
Revisiting Concentration of Missing Mass.

We revisit the problem of \emph{missing mass concentration}, developing a new method of estimating concentration of heterogenic sums, in spirit of celebrated Rosenthal's inequality. As a result we slightly improve the state-of-art bounds due to Ben-Hamou at al., and simplify the proofs.
Stochastic Approximation versus Sample Average Approximation for population Wasserstein barycenter calculation

In machine learning and optimization community there are two main approaches for convex risk minimization problem. The first approach is Stochastic Approximation (SA) and the second one is Sample Average Approximation (SAA) with proper regularization in non-strongly convex case. At the moment, it is known that both approaches are on average equivalent (up to a logarithmic factor) in terms of oracle complexity (required number of stochastic gradient evaluations). What is the situation with total complexity? The answer depends on specific problem. However, starting from work \cite{nemirovski2009robust} it was generally accepted that SA is better than SAA. Nevertheless, in case of large-scale problems SA may run out of memory since storing all data on one machine and organizing online access to it can be impossible without communications with other machines. SAA in contradistinction to SA allows parallel/distributed calculations. In this paper, we show that SAA may outperform SA in the problem of calculating an estimation for population ($\mu$-entropy regularized) Wasserstein barycenter even for non-parallel (non-decentralized) setup.
Propaganda of drug use is a veiled reality of the surrounding reality

The article is devoted to the analysis of advertising methods of illegal distribution of narcotic drugs in a non-contact way. The author assesses the circumstances and risks of acquiring drugs through visual announcements for adolescents and students.
miniKanren as a Tool for Symbolic Computation in Python

In this article, we give a brief overview of the current state and future potential of symbolic computation within the Python statistical modeling and machine learning community. We detail the use of miniKanren as an underlying framework for term rewriting and symbolic mathematics, as well as its ability to orchestrate the use of existing Python libraries. We also discuss the relevance and potential of relational programming for implementing more robust, portable, domain-specific "math-level" optimizations--with a slight focus on Bayesian modeling. Finally, we describe the work going forward and raise some questions regarding potential cross-overs between statistical modeling and programming language theory.
Sistem Pendukung Keputusan Pemilihan Penyidik Pegawai Negeri Sipil (PPNS) dengan Menggunakan Metode Electre Studi Kasus: Balai Wilayah Sungai Sumatera II Medan

The Civil Servant Investigator is one of the law enforcement officers that has the function to carry out an investigation process that is given special authority to carry out an investigation process for a violation of the Regional Government Legal Product (PERDA) which contains elements of criminal acts. Usually the crime is not a general crime that can be handled by police investigators. In making the decision on the selection of Civil Servant Investigators (PPNS) at the Medan Sumatera River Region II Medan the writer uses the Electre method, where Electre is one of the methods for determining the order or priority in MCDM (Multi-Criterion Decision Making). In the use of decision support systems with the Electre method will provide a matching rating value for each alternative. In it all data are combined into one with the weight of the assessment that has been obtained through test assessment. The author tries to design and build a decision support system for the selection of Civil Servant Investigators using the Electre method, providing information needed by the committee in making decisions and applying the Electre Method in determining the Civil Servant Investigator Balai Sumatera River Region II Medan Medan Decision support system is not a making tool decision, but rather a system that helps decision makers by equipping them with information from data that has been processed with relevance and is needed to make decisions about an issue more quickly and accurately
Blended Learning: Perception and Achievement of Postgraduate Program Students of Yogyakarta State University

This study aims to describe blended learning in terms of perceptions and achievements of postgraduate program students of Yogyakarta State University (UNY). The perception includes satisfaction, convenience, and involvement. This study used a survey method. The population of the study was all postgraduate students of UNY who had used blended learning. The sampling technique used random sampling with a total sample of 123 postgraduate students. The instruments used included questionnaires and documentation. Data were analyzed using quantitative descriptive. The resultsshow that the respondents agreed with the items on the satisfaction dimension, namely learning with the blended learning system increased understanding of their core concepts, and students were motivated to succeed.Meanwhile, on the convenience dimension, student perceptions are more diverse.However, there are three items in a broad category, where blended learning can make time and costs efficient, feeling isolated, and video material that helps them in different relationships.In the last dimension, the involvement, the most prominent is the better quality of interaction with fellow friends.
Keyboard user authentication methods

This article provides an overview, a brief description and analysis of user authentication methods for working with the keyboard (the so-called "keyboard handwriting"), as well as a variant of distributed and parallel training of such algorithms.We examined the architecture of the authentication system and the mathematical foundations of the models used in user recognition, as well as the method of distributed learning of the algorithm.
Sound Calculation Simulation System for Distribution of Chair Parliament Using Hare Quota and Sainte Lague Methods

The conversion of the ballot for the division of parliamentary seats has become one of the historical points inthe development of the democratic order in Indonesia. How not, through a plenary session, the DPR RI finally finalizesthe discussion and decision making on the Election Bill proposed by the government. Conversion of votes is one of thecrucial issues to get the word consensus in the House of Representatives, because the method of voting conversionused will greatly determine the acquisition of seats for a political party. For example, if using the quota method, aparty can get 5 seats, but it is not certain if the calculation method uses the Sainte Lague method, it could be that oneparty will get 4 to 6 seats. That is why the voting conversion method is one of the main variables of an electoral system.The method of converting votes is the procedure for calculating the results of elections to determine theacquisition of seats for political parties in representative institutions based on the results of the acquisition of validvotes of each political party participating in the election. The Hare Quota method is characterized by a calculationmethod using the Number of Voters Dividers (BPP) which divides the total number of valid voting votes by the numberof seats allocated to one particular constituency, and always has the remaining choice of votes that requirescalculation at the next stage for the remaining votes of choice / residual the chair is the Sainte Lague method (theremaining votes are voted on).
Research Guides: LGS 306: State Laws Regarding Animals on the Internet

A research guide to help you use Westlaw and find information in scholarly journals on your topics.
초등학교 교사의 행복에 영향을 미치는 변인 분석 : 교사효능감, 집단효능감, 자아탄력성, 학교조직문화를 중심으로

The purpose of this study was to investigate the structural relationships between individual factors(teacher efficacy, ego-resilience) and environmental factors(collective efficacy, school organizational culture), which affect the happiness of elementary school teachers. Data were collected through electronic questionnaires from 349 teachers in 24 elementary schools located in Gwangju, Korea. The collected data were analyzed through a t-test, one-way ANOVA, multiple regression analysis, and structural equation modeling(SEM). The results found in this study are as follows: first, there was a significant difference in happiness according to two sociodemographic characteristics of elementary school teachers: length of teaching career and average monthly household income. Second, teacher efficacy and collective efficacy had no significant effect on the happiness of elementary school teachers and only ego-resilience and school organizational culture had a significant effect on happiness. Third, it was found that the collective efficacy of elementary school teachers has a significant mediated effect on happiness through both ego-resilience and school organizational culture. Collective efficacy also had a significant double-mediated effect on happiness sequentially through teacher efficacy and ego-resilience. This study has addressed the limitations of previous studies, which had partially validated the relationship between the variables. It is meaningful that the structural relationship of the variables affecting teachers’ happiness have been demonstrated in the integrative framework of the structural relationship between these variables in two dimensions of individual factors and environmental factors.
Towards an Efficient Code-Mixed Grapheme-to-Phoneme Conversion in an Agglutinative Language: A Case Study on To-Korean Transliteration

Code-mixed grapheme-to-phoneme (G2P) conversion is a crucial issue for modern speech recognition and synthesis task, but has been seldom investigated in sentence-level in literature. In this study, we construct a system that performs precise and efficient multi-stage code-mixed G2P conversion, for a less studied agglutinative language, Korean. The proposed system undertakes a sentence-level transliteration that is effective in the accurate processing of Korean text. We formulate the underlying philosophy that supports our approach and demonstrate how it fits with the contemporary document.
A Study for Dynamic Decision Making Framework for Tsunami Evacuation

Lee, G.; Lee, C.; Shin, H.; Sunwoo, W., and Jun, K.S., 2020. A study for dynamic decision making framework for tsunami evacuation. In: Malvárez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 855-859. Coconut Creek (Florida), ISSN 0749-0208.This study aims to construct a systematic decision making framework, which can apply response plans dynamically for mitigation of casualties by reflecting regional characteristics, based on Tsunami hazard and evacuation route analysis. Tsunami is a serious disaster that can cause an extensive damage and an early prevention of tsunami is crucial for reduction in the number of casualties. In addition, the safety of the residents vary depending on the information of evacuation routes. Therefore, the priority details that must be considered in counter-measures in target area need to be derived through an evacuation routes based on the conditions and the characteristics of local situation. Hazard assessment is determined by considering tsunami inundation and travel time obtained by a numerical model. Finally, a dynamic decision making framework is proposed considering both hazard risk and evacuation route analysis. The outcome from this study will help not only the management of evacuation map, but also the response plan which provides evacuation information based on the characteristics of local area and residents. Therefore, many lives can be protected from tsunami by applying the decision making framework proposed in this study.
Dynamic Masking for Improved Stability in Spoken Language Translation

For spoken language translation (SLT) in live scenarios such as conferences, lectures and meetings, it is desirable to show the translation to the user as quickly as possible, avoiding an annoying lag between speaker and translated captions. In other words, we would like low-latency, online SLT. If we assume a pipeline of automatic speech recognition (ASR) and machine translation (MT) then a viable approach to online SLT is to pair an online ASR system, with a a retranslation strategy, where the MT system re-translates every update received from ASR. However this can result in annoying "flicker" as the MT system updates its translation. A possible solution is to add a fixed delay, or "mask" to the the output of the MT system, but a fixed global mask introduces undesirable latency to the output. We show how this mask can be set dynamically, improving the latency-flicker trade-off without sacrificing translation quality.
Improving Movie Recommendation Systems Filtering by Exploiting User-Based Reviews and Movie Synopses

This paper addresses the subject of Movie Recommendation Systems, focusing on two of the most well-known filtering techniques, Collaborative Filtering and Content-based Filtering. The first approach proposes a supervised probabilistic Bayesian model that forms recommendations based on the previous evaluations of other movies the user has watched. The second approach composes an unsupervised learning technique that forms clusters of users, using the K-Means algorithm, based on their preference of different movie genres, as it is expressed through their ratings. Both of the above approaches are compared to each other as well as to a basic method known as Weighted Sum, which makes predictions based on the cosine similarity and the euclidean distance between users and movies. In addition, Content-based Filtering is implemented through K-Means clustering techniques that focus on identifying the resemblance between movie plots. The first approach clusters movies according to the Tf/Idf weighting scheme, applying weights to the terms of movie plots. The latter identifies the likeness between movie plots, utilizing the BM25 algorithm. The efficiency of the above methods is calculated through the Accuracy metric.
Research Guides: Tips for Using Library Search: Your Account

Provides some tips and strategies for effectively using the University of Michigan Library search engine.
Tensor Factor Analysis for Arbitrary Speaker Conversion

This paper describes a novel approach to flexible control of speaker characteristics using tensor representation of multiple Gaussian mixture models (GMM). In voice conversion studies, realization of conversion from/to an arbitrary speaker's voice is one of the important objectives. For this purpose, eigenvoice conversion (EVC) based on an eigenvoice GMM (EV-GMM) was proposed. In the EVC, a speaker space is constructed based on GMM supervectors which are high-dimensional vectors derived by concatenating the mean vectors of each of the speaker GMMs. In the speaker space, each speaker is represented by a small number of weight parameters of eigen-supervectors. In this paper, we revisit construction of the speaker space by introducing the tensor factor analysis of training data set. In our approach, each speaker is represented as a matrix of which the row and the column respectively correspond to the dimension of the mean vector and the Gaussian component. The speaker space is derived by the tensor factor analysis of the set of the matrices. Our approach can solve an inherent problem of supervector representation, and it improves the performance of voice conversion. In addition, in this paper, effects of speaker adaptive training before factorization are also investigated. Experimental results of one-to-many voice conversion demonstrate the effectiveness of the proposed approach.
Factors associated with intraoperative hypothermia in elderly patients and management strategies

ObjectiveTo investigate the incidence of intraoperative hypothermia in elderly patients, and to analyze and discuss related influencing factors and targeted management strategies.MethodsFrom February 2017 to February 2019, 220 elderly patients admitted into our hospital for surgery were selected.According to whether or not they had intraoperative hypothermia, patients were divided into the hypothermia group and the non-hypothermia group.General information and surgical data were compared between the two groups.Measures for the prevention of intraoperative hypothermia were discussed.ResultsOf the 220 patients, 103 had intraoperative hypothermia, and the incidence rate was 46.8%.The proportion of patients aged ≥70 years or with BMI <24 kg/m2 was higher in the hypothermia group than in the non-hypothermia group(all P<0.05). The proportion of patients with the anesthesia time ≥60 min or total intraoperative fluid intake ≥2000 ml was higher in the hypothermia group than in the non-hypothermia group(all P<0.05). BMI <24 kg/m2 and total intraoperative fluid intake ≥2000 ml were the key risk factors for intraoperative hypothermia in elderly patients(all P<0.05).ConclusionsIntraoperative hypothermia is a common complication for elderly patients undergoing surgery.Intraoperative fluid intake and body mass are the key risk factors for intraoperative hypothermia.Targeted treatment measures based on the above related factors should be considered for elderly patients receiving surgery.Key words: Body temperature changes; Related factors
La dimensione costituzionale dell’emergenza: come l’epidemia moltiplica le disuguaglianze

The Coronavirus pandemic in spreading worldwide with important effects on the fundamental rights of everyone. The author’s argues that a compression of fundamental rights can be constitutionally justified under specific conditions, however there is a need to consider and address how these measures impact on the situation of people who already face structural discriminations, such as people deprived of personal freedom, people with disability, women and others.
Prototype Alat Olah Limbah Cair Laboratorium dengan Prinsip Fisika, Kimia dan Biologi dengan Hasil Akhir yang Aman dibuang dan tidak Mencemari Lingkungan

Background: Laboratory of Chemical Engineering Environmental Pollution is one of the laboratories that produce liquid waste. However, during this treatment, liquid waste is only stored in a temporary storage area. It will cause part and quality of wastewater produced. It is necessary to research the design of laboratory-scale sports equipment to minimize pollution due to the accumulation of wastewater in conditions without maintenance. Methods: in its design, this tool applied three methods of physical, chemical and biological. This tool will be applied in management using coagulation, electrocoagulation, adsorption, and phytoremediation technologies. Results: This tool can work optimally with an initial capacity of 45 Liters. The parameters tested were pH, TDS, Total Hardness and Lead. The test is carried out to find out the rate of decrease of parameters in each process and the decrease parameter. Conclusion: After testing, it was proven that the biggest decrease in the adsorption process and the result of the calculation of the biggest decrease in TDS was 72.64%. The existence of this tool is expected to overcome the presence of accumulation of liquid waste in the laboratory so that no environmental pollution occurs.
LinTO Platform: A Smart Open Voice Assistant for Business Environments.

In this paper, we present LinTO, an intelligent voice platform and smart room assistant for improving efficiency and productivity in business. Our objective is to build a Spoken Language Understanding system that maintains high performance in both Automatic Speech Recognition (ASR) and Natural Language Processing while being portable and scalable. In this paper we describe the LinTO architecture and our approach to ASR engine training which takes advantage of recent advances in deep learning while guaranteeing high-performance real-time processing. Unlike the existing solutions, the LinTO platform is open source for commercial and non-commercial use
E:Calm Resource: a Resource for Studying Texts Produced by French Pupils and Students

The E:Calm resource is constructed from French student texts produced in a variety of usual contexts of teaching. The distinction of the E:Calm resource is to provide an ecological data set that gives a broad overview of texts written at elementary school, high school and university. This paper describes the whole data processing: encoding of the main graphical aspects of the handwritten primary sources according to the TEI-P5 norm; spelling standardizing; POS tagging and syntactic parsing evaluation.
Extending Narrative Planning Domains with Linguistic Resources

Interactive Narrative (IN) is an emerging application of planning for control of virtual character behaviours. Despite popularity in research, more widespread adoption of planning has been hindered by the difficulty of authoring planning domain models as IN's require models which are robust to dynamic environments and capable of generating a diversity of solutions. To reduce this authoring burden we explored automated extension of partially developed planning domains to address robustness and diversity. We introduce a novel algorithm, thype, which proposes additional types of characters and objects to extend a domain model. The extensions increase robustness by enlarging the range of ways to enact planned behaviours. In the paper we embed thype within a modular and extensible framework that allows multiple off-line generated extensions to be combined. We present results of a user study that show thype suggestions are plausible. We also empirically demonstrate the ability of thype extensions to increase the robustness of the models, demonstrate the modular nature of our extension framework by combining thype with another extension approach dedicated to recovery from plan failure and present results which show that enhanced performance results from combining multiple extensions.