Reviewerly/exHarmony huggingface dataset:
Approximate Bayesian inference for individual-based models with emergent dynamics

Individual-based models are used in a variety of scientific domains to study systems composed of multiple agents that interactwith one another and lead to complex emergent dynamics at the macroscale. A standard approach in the analysis of these systems isto specify the microscale interaction rules in a simulation model, run simulations, and then qualitatively compare outputs to empiricalobservations. Recently, more robust methods for inference for these types of models have been introduced, notably approximate Bayesiancomputation, however major challenges remain due to the computational cost of simulations and the nonlinear nature of many complexsystems. Here, we compare two methods of approximate inference in a classic individual-based model of group dynamics with well-studiednonlinear macroscale behaviour; we employ a Gaussian process accelerated ABC method with an approximated likelihood and with asynthetic likelihood. We compare the accuracy of results when re-inferring parameters using a measure of macro-scale disorder (theorder parameter) as a summary statistic. Our findings reveal that for a canonical simple model of animal collective movement, parameterinference is accurate and computationally efficient, even when the model is poised at the critical transition between order and disorder.
LibGuides: SPC 1017 (Merceron): Free Textbook Access

This research guide is designed to assist Poinciana Campus students in researching careers in Professor Merceron's Interpersonal Communications class. Using the tabs above to navigate, you will find research tools, MLA formatting help, and library contact
Analysis of Various Applications of Blockchain Technology: A Survey

Blockchain is a core technology used as a solution for double spending by Satoshi Nakamoto. This technology is a right solution for problems like forgery and double spending. The technology created many opportunities for the developers and its application not only proved promising solutions for finance industry but many other domain areas such as education, machinery, and commerce industry. This paper covers a survey of using blockchain in different domains and identified successful applications as proof of concept, and it also explores problems with respective domains for future research.
PATH SMOOTHING STRATEGY BASED ON METAHEURISTIC ALGORITHMS FOR PROBABILISTIC FOAM

The probabilistic Foam method (PFM) is a sampling-basedpath planning algorithm that ensures a feasible path boundedby a safe region. This method is ideal for assistive roboticsapplications, which demands a high level of safety, such asperforming a motion by an active exoskeleton. However,PFM generates non-smoothed paths, which results in nonanthropomorphicmovements. Thus, this paper presentssome optimization strategies based on metaheuristics to smooththe paths generated by PFM. Simulated experiments wereperformed using the Harmony Search Algorithm, and GeneticAlgorithm and they were applied to an exoskeleton toovercome an obstacle. Results show that our proposed approachis capable of smoothing paths for this application,which resulted in more anthropomorphic motions.
Statistical physics approaches to unique games

We show how two techniques from statistical physics can be adapted to solve a variant of the notorious Unique Games problem, potentially opening new avenues towards the Unique Games Conjecture. The variant, which we call Count Unique Games, is a promise problem in which the yes case guarantees a certain number of highly satisfiable assignments to the Unique Games instance. In the standard Unique Games problem, the yes case only guarantees at least one such assignment. We exhibit efficient algorithms for Count Unique Games based on approximating a suitable partition function for the Unique Games instance via (i) a zero-free region and polynomial interpolation, and (ii) the cluster expansion. We also show that a modest improvement to the parameters for which we give results would be strong negative evidence for the truth of the Unique Games Conjecture.
Representation of a convolutional neuronal network as a high level paralel composition applied to the recognition of DNA sequences

This work proposes the use of Structured Parallel Programming using the process communication pattern called Pipeline in its version of High-Level Parallel Composition (HLPC) to implement a process composition that represents a convolutional neuronal network or CNN and that is used to solve a specific problem of DNA sequences.The HLPC Pipeline-CNN is then shown, which represents the implementation of a convolutional neural network making use of the three types of parallel objects that make up an HLPC: A manager object, one or more stage objects and a collector object.The manager object represents the HLPC itself and makes an encapsulated abstraction out of it that hides the internal structure, the stage objects are objects of a specific purpose, in charge of encapsulating an client-server type interface that settles down between the manager and the slave-objects and the collector object that is an object in charge of storing the results received from the stage objects to which is connected.To show the usefulness and performance of the HLPC Pipeline-CNN implemented, it was used in the recognition of DNA sequences from a database with 4 types of hepatitis C virus (type 1, 2, 3 and 6).The results of this classification were obtained in terms of percentages of training precision and validation precision, as well as performance results in terms of speedup from 1000 to 4000 training steps with 2, 4, 8, 16 and 32 exclusive processors in one parallel machine of up to 64 processors with shared-distributed memory.
Formal Proof of the Group Law for Edwards Elliptic Curves

This article gives an elementary computational proof of the group law for Edwards elliptic curves. The associative law is expressed as a polynomial identity over the integers that is directly checked by polynomial division. Unlike other proofs, no preliminaries such as intersection numbers, Bézout’s theorem, projective geometry, divisors, or Riemann Roch are required. The proof of the group law has been formalized in the Isabelle/HOL proof assistant.
TO WHICH EXTENT CAN WE USE AUGMENTED REALITY IN MATH LEARNING? A SURVEY ON THE POTENTIALS AND LIMITATIONS OF UTILIZING AR IN HIGH-SCHOOL MATH LECTURES IN IRAN

TO WHICH EXTENT CAN WE USE AUGMENTED REALITY IN MATH LEARNING? A SURVEY ON THE POTENTIALS AND LIMITATIONS OF UTILIZING AR IN HIGH-SCHOOL MATH LECTURES IN IRAN
Sistem Pendukung Keputusan Untuk Pemilihan Buruh Harian Lepas Menjadi Karyawan Tetap Menggunakan Metode Profile Matching (Studi Kasus : PT. Nafasindo)

A daily freelance worker is someone who works alone and is not committed to a certain long-term business owner. Temporary daily workers also have obligations that must be fulfilled as something that must be done if the day laborer wants to get his salary, by doing work with a large target without taking into account working hours, this is the only obligation that must be done because casual daily laborers do not bound to a permanent work agreement where usually in the permanent employment agreement the worker must obey every regulation set by the business owner both the company and individual business. Permanent employees are someone who works with the conditions made by the company in work and all work activities have been arranged and the payroll process is carried out with the basic salary set by the company monthly. So from that the plantations of PT. Nafasindo make an assessment in choosing daily burh employees to become permanent employees by making decisions based on the judgments made in the field. thus the need for decision making such as a computerized decision support system so that decision making can be done quickly and accurately. thus this decision support system uses a profile matching or profile matching method which will be used between a fixed profile and a casual day laborer profile with a review process on the criteria that will be set to fulfill permanent employment.
The Semantics of Structure in Large Historical Corpora

Structuring large historical corpora that are too big to be processed manually can take two approaches. The first is an inductive method extracting implicit entities and meaning from textual (and sometimes visual) content. With the help of AI or manually compiled (existing) lists of entities, the entities are converted into information. The second, that Colavizza (2019) calls referential information systems, takes existing reference systems (like archival indexes) and uses them to contextualize individual documents. Both methods are used to turn corpora into computer accessible information systems. Ideally a more complete information system would result from combining both approaches, but in practice they are hard to bridge because of a number of different problems. This paper presents an approach that addresses those problems and combines inductive methods of automated text analysis and information extraction techniques with knowledge of the referential information systems to add rich semantic layers of information to large historical corpora.
Projection of Economic Volatility Level Based on Multiple Regression Analysis of Key Data

This paper studies the prediction model of economic fluctuation level, reduces the risk of economic fluctuation, and puts forward the prediction method of economic fluctuation level based on multivariate regression analysis of key data. To construct the multivariate statistical analysis model of the key data of the economic fluctuation level under the globalization environment, to extract the fuzzy characteristic quantity reflecting the economic fluctuation level under the globalization environment, to establish the statistical characteristic quantity of the economic fluctuation level forecast under the globalization environment, to use the economic fluctuation level correlation data fusion tracking identification method, to carry on the world economic fluctuation level forecast model transmission information adaptive fusion and the characteristic clustering, to combine the fuzzy judgment method to carry on the economic fluctuation level optimization judgment under the globalization environment, the economic fluctuation level appraisal and the optimization decision tare obtained based on the key data multivariate regression analysis technology under the globalization environment, the stability and adaptability of economic fluctuation level prediction in the global environment is improved. The simulation results show that the accuracy of the prediction of economic fluctuation level is high and the convergence of the prediction process is good, which improves the stability and safety of the economic development level.
Students’ Knowledge on Topic and their Ability to Write

This study was aimed to investigate the correlation between students’ knowledge on topic to be written and their ability to write. The writing course for the second semester students of English Department of STKIP PGRI Tulungagung is Academic Reading and Writing. In this course, the students should be able to develop their competence in reading academic essays as well as composing the essays using the correct organization. However, it has been observed that their ability to write the essays are in relation with their knowledge on the topic to be written. From the findings, it can be concluded that the hypothesis can be accepted since the statistical analysis using Kendal Tau showed that the coefficient of the correlation was positive medium correlation 0.473 and the correlation was significant (0.016 < 0.05). Therefore, it can be concluded that there is significant correlation between students’ knowledge on topic to be written and their writing ability and the students with better knowledge on topics also have better writing ability.
Creating New Information and Communication Models in Working with Users within the Google Library Project

The article analyzes characteristic features and development logic of the library project by Google, which started from the famous Google Book Search project (also known as Google Books and Google Print), and later as Google Play Books within the multi-platform multimedia service Google Play. For decades, a constant trend of the corporation’s activity has been the development and testing of new social and communication models in working with users, combining the complexity and global reach of the audience with the use of its interactive potential. In the early 2000s, the company initiated mass scanning of library collections, thus starting the development of a new institutional paradigm for electronic libraries. Later, having developed new business models for the distribution of electronic copies of printed products in the course of numerous legal proceedings on charges of copyright infringement, it also pioneered the new information market development. From the very beginning, Google Book Search was aimed at the mass user, which was facilitated by its constantly expanding set of options and increasing level of comfort of access to the resource. In 2006—2010, the service presented an opportunity for users to download, in pdf format, books free of copyright law; a new viewing interface “About this book” was added; an opportunity to operate texts using “My library” option was provided; a mobile version of the service was launched; access to statistical information on diachronic frequency dynamics of word usage based on the collected database was provided. The article analyzes the further development of the library project within the Google Play Books service, which allows users to read, buy and sell e-books, use bookmarks, download their own books in pdf and EPUB formats, and synchronize data on all user’s devices. There is assessed the social significance of the project in the context of the global electronic civilization development.
Keynote: Issues of annotations in designing ubiquitous applications

Annotating user data is an important part of the design and evaluation of ubiquitous systems that support the user based on data. The preparation of training data for learning tasks is essential for research in data-driven models. Hence, the quality of annotations has a significant impact on the performance of the derived systems. Furthermore, we should discuss the ethical and privacy problems related to providing annotation. We have annotated many data in our research such as behavior recognition in a smart home, curation of baseball video, and position recognition in the care house. The annotation performance gives affect the performance of behavior recognition, curation, position recognition. On the other hand, the annotation task is a burden for the user and the correct annotation is difficult. Therefore, we have been considering the methods and tools of annotation data collection, cleaning, and confirmation in our research. We would like to discuss the resolutions of those problems.
TECHNOLOGY ENHANCED ASSESSMENT AS A TOOL OF SELECTION OF INTERNATIONAL STUDENTS IN HIGHER EDUCATION INSTITUTIONS

TECHNOLOGY ENHANCED ASSESSMENT AS A TOOL OF SELECTION OF INTERNATIONAL STUDENTS IN HIGHER EDUCATION INSTITUTIONS
Autocorrelation and Lower Bound on the 2-Adic Complexity of LSB Sequence of <i>p</i>-Ary <i>m</i>-Sequence

LSB (Least Significant Bit) sequences are widely used as the initial inputs in some modern stream ciphers, such as the ZUC algorithm-the core of the 3GPP LTE International Encryption Standard. Therefore, analyzing the statistical properties (for example, autocorrelation, linear complexity and 2-adic complexity) of these sequences becomes an important research topic. In this article, we first reduce the autocorrelation distribution of the LSB sequence of a p-ary m-sequence with period p <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sup> -1 for any order n≥2 to the autocorrelation distribution of a corresponding Costas sequence with period p-1, and from the computing of which by computer, we obtain the explicit autocorrelation distribution of the LSB sequence for each prime p<; 100. In addition, we give a lower bound on the 2-adic complexity of each of these LSB sequences for all primes p<; 20, which proves to be large enough to resist the analysis of RAA (Rational Approximation Algorithm) for FCSRs (Feedback with Carry Shift Registers). In particular, for a Mersenne prime p=2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</sup> -1 (i.e., k is a prime such that p is also a prime), our results hold for all its bit-component sequences since they are shift equivalent to the LSB sequence.
La biblioteca come facilitatore del processo di produzione di conoscenza

The dossier “Innovative Libraries” presents a review of the experiences of libraries that have in common the search for solutions aimed at redefining their role, with particular attention to the social dimension and new paths of access to knowledge. From a library experience conceived as a community hub, we move on to examine a case of involvement of local businesses in a cultural welfare perspective. The case of Turin is original. Here libraries offer to citizens hospitality in their offices to meet with professionals (accountants, notaries, etc.) to obtain advice, while in Rome and Milan there is a growing commitment to the prison population. The case of proximity libraries and condominium libraries is unique, while the promotion of active citizenship and the practice of listening is growing. Innovating also means transferring skills to students that enable them to operate in a Wikimedian environment or use the collections as an opportunity for conversation with the community. Innovation for academic libraries also passes through their ability to present themselves as digital and participatory thanks to the opportunities offered by the Third Mission and the opportunities offered to academic libraries to respond to the strong drives towards open science. Finally in a short article is described the new alliance between a public library and a library for patients of an oncology institute.
Another Problem in Possible World Semantics

Author(s): Ding, Yifeng; Holliday, Wesley Halcrow | Abstract: In A Problem in Possible-World Semantics, David Kaplan presented a consistent and intelligible modal principle that cannot be validated by any possible world frame (in the terminology of modal logic, any neighborhood frame). However, Kaplan's problem is tempered by the fact that his principle is stated in a language with propositional quantification, so possible world semantics for the basic modal language without propositional quantifiers is not directly affected, and the fact that on careful inspection his principle does not target the world part of possible world semantics---the atomicity of the algebra of propositions---but rather the idea of propositional quantification over a complete Boolean algebra of propositions. By contrast, in this paper we present a simple and intelligible modal principle, without propositional quantifiers, that cannot be validated by any possible world frame precisely because of their assumption of atomicity (i.e., the principle also cannot be validated by any atomic Boolean algebra expansion). It follows from a theorem of David Lewis that our logic is as simple as possible in terms of modal nesting depth (two). We prove the consistency of the logic using a generalization of possible world semantics known as possibility semantics. We also prove the completeness of the logic (and two other relevant logics) with respect to possibility semantics. Finally, we observe that the logic we identify naturally arises in the study of Peano Arithmetic.
Bank Loans, Default Probabilities, and Differential Credit Treatment in Sub-Saharan Banks

This paper investigates the bank credits, default probabilities, and differential credit treatment in banks of 16 selected Sub-Saharan Africa (SSA) countries by inclusion of annual data of 20 years.The parameters used were obtained from World Bank Development Indicators online database (WDI), Africa Development Bank (ADB), International Monetary Fund (IMF), International Financial Statistics (IFS), and Regional Economic Outlook.By mitigating the problems of spurious causality and unobserved heterogeneity, panel estimation techniques overcome common weaknesses of most cross-country approaches.Panel estimation techniques often give all countries, either small or large, an equal weighting since they are assumed to be homogeneous and the coefficients represent only average relationship, which may or may not apply to individual countries in the sample.Following Arellando and Bond (1991) and as later used by Christopoulous and Tsionas ( 2004), and Baltagi et al. ( 2008) a dynamic Generalized Method of Moments (GMM) is applied in the assessment.A dynamic panel estimator allows for the exploitation of time series variations in the data, accounts for unobserved country specific effects, allows for the inclusion of lagged variables as regressors, and controls for endogeneity of all explanatory variables.
A indústria do livro é frágil demais

The publisher Angel Bojadsen is a pedestrian who circulates between the cities of culture. Promoter of an intangible cultural heritage, he works so that Brazilians know what Europeans, Japanese or Chinese create. But, without organized public support, quality publishing will remain a devastated economic sector driven by the bankruptcy of education. Keywords : Publishing, Social sciences, Translation, City, Cultural policies
BOTS AMONG US: PREVALENCE, INFLUENCE, AND ROLES OF AUTOMATED ACCOUNTS IN THE GERMAN TWITTER FOLLOW NETWORK

Social bots are undermining trust in social media. They spread low-credibility content, fake news, and spam. However, most research is based on bots that actively share links or keywords, rather than assessing the longer-term presence of bots as an integral part of platforms. To address this gap, we present what to our knowledge is the first study that assesses the prevalence, influence, and roles of automated accounts in a Twitter follow network on a national scale. This allows us to analyse the potential impact of bots beyond the context of single events and topics.&#x0D; To collect a follow network of the most central accounts in the German-speaking Twittersphere, we have adapted the rank-degree method, a graph exploration method that is able to identify the most influential spreaders within complex networks, as a data mining method using the cost-free standard Twitter API. To identify bots, we employ the Botometer API. Both methods combined allow us to localise bots within topical clusters, to estimate their potential influence, and to assess the roles of the most central bots.&#x0D; Our findings indicate that bots have only a low negative impact on the German-speaking Twittersphere. However, the most sophisticated bots will likely remain absent from our study, as false negatives. Similarly, trolls and semi-automated accounts necessitate further research. Our new sampling approach combined with Botometer is promising, for example, for Twitterspheres based on other languages. The study itself opens further avenues of enquiry, such as a long-term monitoring of automated accounts in the German Twittersphere.