Reviewerly/exHarmony huggingface dataset:
Sample Balancing for Improving Generalization under Distribution Shifts

Deep neural networks have achieved striking performance when evaluated on testing data which share the same distribution with training ones, but can significantly fail otherwise. Therefore, eliminating the impact of distribution shifts between training and testing data is of paramount importance for building performance-promising deep models. Conventional methods (e.g. domain adaptation/generalization) assume either the availability of testing data or the known heterogeneity of training data (e.g. domain labels). In this paper, we consider a more challenging case where neither of the above information is available during the training phase. We propose to address this problem by removing the dependencies between features via reweighting training samples, which results in a more balanced distribution and helps deep models get rid of spurious correlations and, in turn, concentrate more on the true connection between features and labels. We conduct extensive experiments on object recognition benchmarks including PACS, VLCS, MNIST-M, and NICO which support the evaluation of generalization ability. The experimental results clearly demonstrate the effectiveness of the proposed method compared with state-of-the-art counterparts.
PKM penulisan karya ilmiah mahasiswa Fakultas Ilmu Keolahragaan Universitas Negeri Makassar

Scientific work as an important element in the lecture process is sometimes still considered a scourge by some students. This happens because of the many important elements that students must pay attention to. The scientific work in question is in the form of a thesis, thesis, research report, and so on. Certain types of scientific works must be made by students who are undergoing lectures. The problem among students is the method of writing scientific papers, sometimes students do not follow the standard rules according to existing theories. They should have mastered the rules wrapped in research methodology. The method used in this activity was lecture and question and answer and practice carried out for three days. This activity is very useful for students to know the signs that must be known when conducting research, students will find it easier when the final thesis making process. The participants realized that this activity was able to provide additional knowledge about making scientific papers. Suggestions given with this activity are expected to the local bureaucracy especially FIK UNM and all study programs within FIK UNM to send representatives in each training activity of writing scientific papers and involve students in competitions of writing scientific papers.
Digital Jordan Curves and Surfaces with Respect to a Closure Operator

In this paper, we propose new definitions of digital Jordan curves and digital Jordan surfaces. We start with introducing and studying closure operators on a given set that are associated with n-ary relations (n &gt; 1 an integer) on this set. Discussed are in particular the closure operators associated with certain n-ary relations on the digital line ℤ. Of these relations, we focus on a ternary one equipping the digital plane ℤ2 and the digital space ℤ3 with the closure operator associated with the direct product of two and three, respectively, copies of this ternary relation. The connectedness provided by the closure operator is shown to be suitable for defining digital curves satisfying a digital Jordan curve theorem and digital surfaces satisfying a digital Jordan surface theorem.
Organization of the educational process in the conditions of distance and mixed learning in the new 2020-2021 academic year in the field of training "Journalism and information"

The article raises questions about the specifics of online education in higher education institutions, new teaching methods implemented in accordance with the latest requirements. The use of digital technologies for distance learning of students lies in the importance of programs for evaluating various platforms.
Design and creative activity of students in the process of distance learning in primary classes

The article is devoted to the characteristics of design and creative activity of students in the process of distance learning in primary classes. The article clarifies the concept and essence of project-creative activity of students, reveals its main stages, content, difference from project research activities of adults, features of project implementation by younger students, features of project implementation in the context of distance learning. It is established that the design and creative activity of primary school students in the course of distance learning is an activity with the use of distance educational technologies, aimed at solving educational and (or) scientific problems, creative tasks and tasks, the implementation of which is carried out on the basis of active problem-finding actions, creative self-realization of students and presented as the final result (project).
Performance Evaluation of Word Embeddings for Sarcasm Detection- A Deep Learning Approach

Sarcasm detection is a critical step to sentiment analysis, with the aim of understanding, and exploiting the available information from platforms such as social media.The accuracy of sarcasm detection depends on the nature of word embeddings.This research performs a comprehensive analysis of different word embedding techniques for effective sarcasm detection.A hybrid combination of optimizers including; the Adaptive Moment Estimation (Adam), the Adaptive Gradient Algorithm (AdaGrad) and Adadelta functions and activation functions like Rectified Linear Unit (ReLU) and Leaky ReLU have been experimented with.Different word embedding techniques including; Bag of Words (BoW), BoW with Term Frequency-Inverse Document Frequency (TF-IDF), Word2vec and Global Vectors for word representation (GloVe) are evaluated.The highest accuracy of 61.68% was achieved with theGloVeembeddings and an AdaGrad optimizer and a ReLU activation function, used in the deep learning model.
Visual Analytics for Financial Crime Detection at the University of Perugia

This paper describes the research activity on financial crime detection developed by the computer engineering group at the University of Perugia. The presented research aims at designing and experimenting advanced visual interfaces to support financial crime detection, with a focus on tax evasion discovery. The activity of the group on this topic, which has been ongoing for ten years now, involves institutional and industrial collaborations and already led to system prototypes in use at different institutions. The scientific relevance of the research is witnessed by several publications in top-tier international journals and conferences.
Optimised one-class classification performance

We provide a thorough treatment of one-class classification with hyperparameter optimisation for five data descriptors: Support Vector Machine (SVM), Nearest Neighbour Distance (NND), Localised Nearest Neighbour Distance (LNND), Local Outlier Factor (LOF) and Average Localised Proximity (ALP). The hyperparameters of SVM and LOF have to be optimised through cross-validation, while NND, LNND and ALP allow an efficient form of leave-one-out validation and the reuse of a single nearest-neighbour query. We experimentally evaluate the effect of hyperparameter optimisation with 246 classification problems drawn from 50 datasets. From a selection of optimisation algorithms, the recent Malherbe–Powell proposal optimises the hyperparameters of all data descriptors most efficiently. We calculate the increase in test AUROC and the amount of overfitting as a function of the number of hyperparameter evaluations. After 50 evaluations, ALP and SVM significantly outperform LOF, NND and LNND, and LOF and NND outperform LNND. The performance of ALP and SVM is comparable, but ALP can be optimised more efficiently so constitutes a good default choice. Alternatively, using validation AUROC as a selection criterion between ALP or SVM gives the best overall result, and NND is the least computationally demanding option. We thus end up with a clear trade-off between three choices, allowing practitioners to make an informed decision.
Morphological filters for global optimization

This paper is devoted to construct an algorithm based on morphological filters, for global optimization of functions in big dimensions. A panel of various benchmark problems with different properties were used to assess the performance of the proposed Optimization morphological filters (OMF) algorithm. The obtained results has shown the scalability of the algorithm in contrast to optimization algorithms encountered in the literature. Moreover, in comparison with some metaheuristics (PSO, CuCkoo, Bat, QPSO...), the computational results revealed that the proposed algorithm is an effective and efficient optimization algorithm.
Mouse Dynamics System for User Verification

This paper includes user verification methods which provides a security layer by continuously validating the identity of logged-on users depending on their mouse activities. We introduced a method that constantly verifies users consistent with properties of their interaction with the mouse. This work is divided in three steps: Client check depends on the arrangement consequences of every clients mouse activity, as opposed to strategies which total mouse activities. Second, we propose the functions that are extracted by hierarchy of mouse moves. Third, new features to characterize the mouse activity, which is used in concurrently with features.
Perancangan Dan Implementa Sisistem Infomrasi Penjualan Pada minimarket Palm Mart Berbasis Multi Tier

The Mini Market Palm Mart, which can be a market for sellers, is addressed in Housing Ogan Permata Indah, Jalan Opi Raya, Jakarta, Palembang. Palm Mart has 6 employees, where they have their respective roles, namely a cashier, 2 shopkeepers and arranging items at the Palm mart and 2 warehouse guards and 1 administration. From year to year, Palm Mart mini-market stores have experienced an increase but it is very limiting for sellers to place their merchandise in Palm Mart Stores, thus impacting on the amount of data processed and the quality of service to consumers. The solution to the problems that exist in Palm Mart Stores is by creating a multi-tiered sales information system to help employees at the Palm Mart. At this writing the author uses descriptive research methods and uses the method of developing the waterfall system and uses Unified Modelling Language analysis.
Experimental Study of Pumping Condensable Vapors by Oil Free Vacuum Scroll Pumps

When operating a vacuum pump, it is often necessary to pump out liquid vapors or vapor-gas media that can condense in its working cavities. To prevent condensation in displacement pumps including scroll pumps, gas ballast device is used. The maximum tolerable water vapor pressure at the inlet and maximum pump capacity by water vapor are the main parameters of a pump with gas ballast device. The highest water vapor pressure at the inlet and the maximum capacity of the oil-free scroll vacuum pump by water vapor were determined experimentally. For this purpose pumping speed, gas flow through the gas ballast device, and gas temperature at the scroll vacuum pump outlet were measured on a specially designed stand. A method for calculating the partial pressure of water vapor in scroll vacuum pumps using a mathematical model of pumping process is proposed. Experimental and calculated results are in good agreement.
Guides: Technical Direction + Scenic Tech + Stage Automation: Technical Reference + Research

Research resources for the study of technical direction, scenic technology, and stage automation.
EXPLORING STUDENTS’ WRITING OF NEWS REPORT AT ENGLISH LANGUAGE EDUCATION STUDY PROGRAM OF KHAIRUN UNIVERSITY

The aim of this research is to know students’ competence in writing news report at the sixth semester of English Education Study Program at Khairun University. The researcher focuses on students’ writing news report text concering generic structure of the news that included headline, newsworthy of event, background of event and source. The researcher applied qualitative research method, this research involved 15 respondents of sixth Semester of English Language Education Study Program at Khairun University. The researcher used written test the data obtained were analyzed by using content analysis. The result of the data analysis shows that students’ writing in headline of the news 60% (nine students) acquired low competence, 26.6% (four students) acquired middle competence and 13.3% (two students) acquired high competence. Students’ writing in newsworthy of event 53.3% (eight students) acquired low competence, 40% (six students) acquired middle competence and 6.66% (one student) acquired high competence. students’ writing in background of event 53.3% (eight students) acquired low competence, 33.3% (five students) acquired middle competence and 13.3% (two students) acquired high competence. Students’ writing in source there are 6.66% (one student) acquired low competence, 86.6% (13 students) acquired middle competence and 6.66% (one student) acquired high competence. This suggests that, 1) More than 80% students have middle competence in writing source; 2) as accurate, 50-60% students have low competence in writing headline, newsworthy of event and background of event; 3) however, 26-53% students have middle competence in writing newsworthy of event, background of event and headline; 4) moreover, 6-13% students have high competence in writing headline, background of event and source.
Sistem Rekomendasi Podcast menggunakan Metode N-Gram dan Term Frequency

One of the main forms of information and entertainment presentation is in the form of on-demand audio content or often referred as podcast. The problem met is the difficulty of users to find podcasts that match their preferences among hundreds of thousands of podcasts that are now available on the internet. Besides the number of podcasts, the incompletion of podcasts metadata is one of the problems in developing a recommendation system in general.This system is designed by utilizing N-Gram and Term Frequency to generate queries from the title and description of a podcast which will then be used to find other podcasts that are similar by utilizing Cosine Similarity calculations. The testing phase is done through by testing the system using nDCG calculations to determine the relevance level of the recommendation results. From the results, the average value of the relevance level of podcast recommendations is 53.8% and the best average f1-score of the 10 best categories is 14%.
Intelligent Jacket for Monitoring Mobility of People with Reduced Disabilities

IoT represents the expansion of technology in all aspects of everyday life. There are various initiatives according to the needs of the people. In this sense, visual impairment constitutes a greater difficulty for mobilization in unfamiliar environments. The obstacles present in the environments increase the risks and damage to the physical integrity of the person suffering from said disability. The use of wearable IoT technology allows the integration of different services that provide a practical and reliable solution. This work presents the design of a smart jacket that improves the mobility of people with visual disabilities. The design consists of two components of hardware and software. The first integrates an electronic design with ultrasonic sensors implemented in a smart jacket whose purpose is to determine the obstacles present on the road, and the second a mobile application that allows you to send a message or make a call to a pre-registered contact in case of emergency. In addition, the results allowed to validate the functional and non functional requirements defined for the project. Finally, this work contributes to improving the quality of life of this group of people in relation to their care and mobility independently.
Using multimedia applications in teaching foreign language in terms of digitalization of education

The article deals with the didactic potential and the possibilities of using educational multimedia applications in the teaching process. In the study the importance of teachers' mastering the skills of using multimedia ap-plications, as well as the knowledge of their essence and capabilities, methodological and psychological-didactic foundations of their usage is stated. The authors consider the notion and types of educational multi-media applications, peculiarities of their usage in various pedagogical scenarios. The technical support for creating multimedia applications by teachers can be represented by the special authoring software tools, that is, programs that provide opportunities for independent building of effective interactive multimedia applica-tions for non-programmers, such as Macromedia Flash, iSpring Suit, Macromedia Director, Authorware Pro-fessional, etc. Multimedia applications can be recommended for usage as a communicative component of the educational environment. The effective performance of pedagogical scenarios of multimedia usage in the ed-ucational process contributes to the development of the learner’s independence and creativity, his active posi-tion as a subject of communicative interaction.
Kreativitas Belajar Spreadsheet Ditinjau Dari Keterampilan Mengajar Guru Dan Keaktifan Belajar Siswa Kelas X Akuntansi Smk Muhammadiyah 2 Karanganyar

This study aims to determine: (1) the effect of teacher teaching skills, and learning activeness on the creativity of learning spreadsheets in class X accounting SMK Muhammadiyah 2 Karanganyar. (2) the effect of teaching skills on the creativity of learning spreadsheets, (3) the influence of active learning on creativity in learning spreadsheets. This type of research is quantitative research. The population in this study were 136 students of class X accounting SMK Muhammadiyah 2 Karanganyar. The sample in this study was 95 students, sampling technique using proportional random sampling. Data collection techniques using questionnaires and documentation, the previous questionnaire was tested for validity and reliability testing. The data analysis technique used is multiple linear regression analysis, with the F test, t test, determination coefficient test, relative contribution and effective contribution. The results of the analysis obtained Y = 9.843 + 0.231X1 + 0.539X2. The equation shows that teacher teaching skills and learning activeness affect the creativity of learning spreadsheets. The conclusion drawn is (1) there is an effect of teacher teaching skills on creativity in learning spreadsheets. Obtained tcount> ttable is 2.405> 1.986 and a significance value of 0.018 ttable is 5.584> 1.986 and a significance value of 0.000 Ftable was 36.450> 3.10 with a significance value of 0.000 <0.05. The coefficient of determination (R2) is 0.442 or 44.2%, while the remaining 55.8% is influenced by other variables not examined.
LibGuides: ACRL, IPEDS, and National Surveys: Title Holdings Quantity

Support guides and tutorials for PALNI libraries completing the ACRL, IPEDS, and other national surveys.
Nonstationary Gauss-Markov Processes: Parameter Estimation and Dispersion

This paper provides a precise error analysis for the maximum likelihood estimate â_(ML)(u <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sup> ) of the parameter a given samples u <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sup> = (u <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> , ..., u_n) <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sup> drawn from a nonstationary Gauss-Markov process U_i = aU_(i-1) + Z)_i, i ≥ 1, where U <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> = 0, a > 1, and Zi <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sup> s are independent Gaussian random variables with zero mean and variance σ <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . We show a tight nonasymptotic exponentially decaying bound on the tail probability of the estimation error. Unlike previous works, our bound is tight already for a sample size of the order of hundreds. We apply the new estimation bound to find the dispersion for lossy compression of nonstationary Gauss-Markov sources. We show that the dispersion is given by the same integral formula that we derived previously for the asymptotically stationary Gauss-Markov sources, i.e., |a|<;1. New ideas in the nonstationary case include separately bounding the maximum eigenvalue (which scales exponentially) and the other eigenvalues (which are bounded by constants that depend only on a) of the covariance matrix of the source sequence, and new techniques in the derivation of our estimation error bound.
InfoGuides: Leganto - Course Reserves: Frequently Asked Questions

Instruction and guidance for Faculty and Staff for using Leganto in Blackboard to manage their e-reserves
Classical algorithms for quantum mean values

Quantum algorithms hold the promise of solving certain computational problems dramatically faster than their classical counterparts. The latest generation of quantum processors with ~50 qubits are expected to be at the brink of outperforming classical computers. However, due to the lack of fault tolerance, the qubits can be operated for only a few time steps, making the quantum circuits shallow in depth. Variational quantum algorithms are leading candidates in the effort to find shallow-depth quantum algorithms that outperform classical computers. Here we consider the task of computing the mean values of multi-qubit observables, which is a cornerstone of variational quantum algorithms for optimization, machine learning and the simulation of quantum many-body systems. We develop sub-exponential time classical algorithms for solving the quantum mean value problem for general classes of quantum observables and constant-depth quantum circuits. In the special case of geometrically local two-dimensional quantum circuits, the runtime of our algorithm scales linearly with the number of qubits. Our results demonstrate that appropriate choices of circuit parameters such as geometric locality and depth are essential to obtain quantum speed-ups based on variational quantum algorithms. Finding expectation values is a key step in variational quantum algorithms that are hoped to provide a near-term quantum advantage. Bravyi et al. show that a classical approximation is possible when the quantum circuits are limited to constant depth.