Reviewerly/exHarmony huggingface dataset:
Deep Meta-Learning and Dynamic Runtime Exploitation of Knowledge Sources for Traffic Control

In the field of machine learning and artificial intelligence, meta-learning describes how previous learning experiences can be used to increase the performance on a new task. For this purpose, it can be investigated how prior (similar) tasks have been approached and improved, and knowledge can be obtained about achieving the same goal for the new task. This paper outlines the basic meta-learning process which consists of learning meta-models from meta-data of tasks, algorithms and how these algorithms perform on the respective tasks. Further, a focus is set on how this approach can be applied and is already used in the context of deep learning. Here, meta-learning is concerned with the respective machine learning models themselves, for example how their parameters are initialised or adapted during training. Also, meta-learning is assessed from the viewpoint of Organic Computing (OC) where finding effective learning techniques that are able to handle sparse and unseen data is of importance. An alternative perspective on meta-learning coming from this domain that focuses on how an OC system can improve its behaviour with the help of external knowledge sources, is highlighted. To bridge the gap between those two perspectives, a model is proposed that integrates a deep, meta-learned traffic flow predictor into an organic traffic control (OTC) system that dynamically exploits knowledge sources during runtime.
Sistem Pakar Untuk Mengidentifikasi Hama Dan Penyakit Pada Tanaman Apel Menggunakan Metode Dempster Shafer

In this study, the identification of pest and disease attack on apple plant on with case study in Balitjestro. The problem faced is the difficulty of determining the information of pests or diseases that attack on apple plants that must meet an expert directly, it takes a long time and cost. The purpose of this study is to accelerate the information obtained from the identification of pests and diseases of the apple plant and its solution without having to meet an expert. Types of pests and diseases that is in pests are Green Lice, Mites, Trips, Leaf Cats, Leaf Sucking Insects, Black Leaf Caterpillars and Fruit Flies. In the disease there are Flour Powder, Leaf Spot, Upas Mushroom, Cancer and Rotten Fruit. From pest and disease data, all symptom data is 38 data. To get the information, made Expert System. Expert system in this study to determine the results of identification using Dempster Shafer calculation method. Demster Shafer is one of the mathematical theories used to perform a proof that is based on the function of trust and also logic makes sense. At the test stage yields an accuracy value of 100%. However there is one test of the expert only producing one and the results of the system show more than one. But one of the results given by  the system is the same as the result given by an expert, then it is justified.
Analisis Rancangan Siaran Radio Streaming Menggunakan Icecast2

Radio Streaming is a technology which used to send audio files simultaneously on many computers on a network by using small data packages and producing semi-realtime output. In the streaming process, the music file will play when the computer starts receiving music file data. Icecast is an open source software that is used for streaming radio technology. Icecast2 helps users to provide Radio Internet servers using the software provided. This study aims to build a Radio Streaming system and study bandwidth requirements, as well as factors that affect the transmission delay. The result is that the unstable connection causes disconnection in the connection, the processor speed and also the connection speed and the internet affect the buffering of the recipient of the stream
Analysis of Gradient-Based Expectation-Maximization-Like Algorithms via Integral Quadratic Constraints.

The Expectation-Maximization (EM) algorithm is one of the most popular methods used to solve the problem of distribution-based clustering in unsupervised learning. In this paper, we propose an analysis of a generalized EM (GEM) algorithm and a designed EM-like algorithm, as linear time-invariant (LTI) systems with a feedback nonlinearity, and by leveraging tools from robust control theory, particularly integral quadratic constraints (IQCs). Towards this goal, we investigate the absolute stability of dynamical systems of the above form with a sector-bounded feedback nonlinearity, that represent the aforementioned algorithms. This analysis allows us to craft a strongly convex objective function, which led to the design of the aforementioned novel EM-like algorithm for Gaussian mixture models (GMMs). Furthermore, it allows us to establish bounds on the convergence rates of the studied algorithms. In particular, the derived bounds for our proposed EM-like algorithm generalize bounds found in the literature for the EM algorithm on GMMs, and our analysis of an existing gradient ascent GEM algorithm based on the $Q$-function allowed us to approximately recover bounds found in the literature.
Training Of A Teacher Of The Higher School To Design The Adaptive Educational Environment Of A Student

The research team identified one of the vectors for solving the problem of the quality of vocational training in the higher school — designing an adaptive educational environment for a student - a future geography specialist, whose process depends on the level of professionalism of a higher school teacher. . The developed methodology of gradual training of a higher school teacher for designing the student’s adaptive educational environment in formal and non-formal education is presented. The intra-departmental training of a teacher of the higher school was tested, with its involvement in the work of an interim research working party where its own pedagogical experience and the experience of colleagues were reflected. Three stages of teacher training for designing the student’s adaptive educational environment have been characterized: “simulation of environment” - mastering the reproductive complex of professional skills that helps to form students’ competences at the threshold level; “combining the environment” - when teachers acquire a set of constructive skills, the possession of which ensures the formation of students professional competence at the advanced level; “transformation of the environment” - when teachers master a complex of creative skills that helps students to form professional competences at the high level of their development. The technology of tutor support and case technology are described that provide students at the stage of “combining the environment” with the ability to organize and manage independent teaching and research activities at the advanced level of mastering professional competencies. Experimental testing has confirmed that the design of the student’s adaptive educational environment effectively ensures the development of the professional experience of the higher school teacher.
Minimizing the Negative Side Effects of Planning with Reduced Models.

Reduced models of large Markov decision processes accelerate planning by considering a subset of outcomes for each state-action pair. This reduction in reachable states leads to replanning when the agent encounters states without a precomputed action during plan execution. However, not all states are suitable for replanning. In the worst case, the agent may not be able to reach the goal from the newly encountered state. Agents should be better prepared to handle such risky situations and avoid replanning in risky states. Hence, we consider replanning in states that are unsafe for deliberation as a negative side effect of planning with reduced models. While the negative side effects can be minimized by always using the full model, this defeats the purpose of using reduced models. The challenge is to plan with reduced models, but somehow account for the possibility of encountering risky situations. An agent should thus only replan in states that the user has approved as safe for replanning. To that end, we propose planning using a portfolio of reduced models, a planning paradigm that minimizes the negative side effects of planning using reduced models by alternating between different outcome selection approaches. We empirically demonstrate the effectiveness of our approach on three domains: an electric vehicle charging domain using real-world data from a university campus and two benchmark planning problems.
Grievances Redress Mechanism

The objective of the Regional Off-Grid Electrification Project for Western Africa is to increase electricity access to households and businesses using modern off-grid technology through a harmonized regional approach. Some of the negative impacts and mitigation measures include: policy dialogue at country and regional level technical assistance to governments to put in place specific e-waste management measures for solar industry; design and testing of private sector solutions; awareness raising of end users and implementing e-waste collection programs; creating awareness among the end users of the consequences of the increase in water usage as their operations increase; and enterprise involvement in the education of end users in the productive use of the technology.
Multi-Order Information for Working Set Selection of Sequential Minimal Optimization

A new working set selection method for sequential minimal optimization (SMO) is proposed in this paper. Instead of the method adopted in the current version of LIBSVM, which uses the second order information of the objective function to choose the violating pairs, we suggest a new method where a higher order information is considered. It includes the descent degree of the objective function and the stride of variables update. Many experimental results show, in contrast to LIBSVM, the number of iterations obtained by the proposed method is less in the vast majority of cases and the training of support vector machines (SVMs) is sped up. Meanwhile, the convergence of the proposed approach can be guaranteed and its accuracy is at the same level as LIBSVM's.
Perbedaan Profil Hematologi Rutin pada Penderita Demam Berdarah Dengue Anak dan Dewasa di RSUD Dr. Harjono Ponorogo

Dengue fever is a common disease in tropical and sub-tropical regions. Age is a big factor that could affects the severity of dengue hemorrhagic fever. Pediatric patients have higher capillary permeability which could cause plasma leakage, whereas adult patients have higher risks of hemorrhage. This research aims to identify the differentiations of hematology routine profile on adult and children hemorrhagic dengue patients. This research uses analytic observation method with cross sectional approach. The research observes 66 samples consisting of 33 pediatric patients (under 12 years old) and 33 adult patients (over 18 years old), taken with purposive sampling technique. Data analyzed with unpaired T-tests and Mann-Whitney tests. Mean leukocyte value on children is lower than on adult p=0,029 (p 0,05), and mean thrombocyte value on children is higher then on adult p=0,037 (p<0,05). There were significant differentiations of mean value of leukocytes, hemoglobin, and platelets on pediatric and adult hemorrhagic dengue patients. There is no significant difference of hematocrit increase value on pediatric and adult hemorrhagic dengue patients.Keywords: DHF, Leukocytes, Hemoglobin, Hematocrit, Platelets, Ages.
Application of Response Surface Methodology for Global Solar radiation Analysis in Maiduguri-Nigeria

Meteorological parameters namely; relative sunshine duration, maximum ambient temperature and relative humidity were used to develop an empirical model for the analysis of global solar radiation in Maiduguri. Response surface methodology was used for the analysis. The predicted and measured values of the global solar radiation have shown good agreement. A coefficient of determination of 99.8% was recorded with maximum percentage error of 0.0558 and root mean square error of0.2396. The model has appreciable advantage in comparison with existing models.
Introduction to PySpark SQL

The amount of data that’s generated increases every day. Technology advances have facilitated the storage of huge amounts of data. This data deluge has forced users to adopt to the distributed system. Distributed systems look for distributed programming, which require extra care for fault tolerance and efficient algorithms. Distributed systems always look for two things—reliability on the system and availability of all the components.
Compact Representation of Value Function in Partially Observable Stochastic Games

Value methods for solving stochastic games with partial observability model the uncertainty about states of the game as a probability distribution over possible states. The dimension of this belief space is the number of states. For many practical problems, for example in security, there are exponentially many possible states which causes an insufficient scalability of algorithms for real-world problems. To this end, we propose an abstraction technique that addresses this issue of the curse of dimensionality by projecting high-dimensional beliefs to characteristic vectors of significantly lower dimension (e.g., marginal probabilities). Our two main contributions are (1) novel compact representation of the uncertainty in partially observable stochastic games and (2) novel algorithm based on this compact representation that is based on existing state-of-the-art algorithms for solving stochastic games with partial observability. Experimental evaluation confirms that the new algorithm over the compact representation dramatically increases the scalability compared to the state of the art.
FACEBOOK AND ENGLISH LANGUAGE LEARNING: EFL LEARNERS’ EXPERIENCES (A QUALITATIVE STUDY)

The purpose of this quantitative study was to identify the EFL learners’ practices and understand their experiences with SNSs (social networking sites) as a tool for English language learning. The study results were obtained from a survey of 144 undergraduate Jordanian EFL learners in the English and Translation Departments at Yarmouk University in Jordan. In the quantitative phase of the study, the research questions focused on the actual practices and strategies of EFL students on SNSs. This study was guided by the following research questions: To what extent do Jordanian EFL learners use Facebook as a tool for language learning? And what language learning practices do Jordanian EFL learners engage in on Facebook? The results revealed that most participants felt comfortable using Facebook in English language learning. However, less than half of them used Facebook on a regular basis to learn English. In addition, they tended to read and observe discussions in English rather than participate in them or produce language output. The results also revealed that learners’ practices or behaviors in the SNS environment changed depending on certain factors, such as the context, audience, sense of belonging, self – confidence, and the learners’ needs and interests. The results of the study brought to light some implications in the context of formal and informal language learning. The study might raise learner, teacher, and educator awareness about SNSs as a tool for language learning, particularly for countries with limited resources. The results also showed the need for a theoretical and pedagogical framework for the teaching and learning process that identifies the best practices and ways to avoid any harm in a SNS environment. Integrating SNSs in language teaching and learning is a topic that requires further study. Using SNSs inside and outside the classroom to practice different language skills is an important topic for future research. Article visualizations:
Targeted Solicitation of Product Reviews

Customer reviews have become an essential resource when people search for goods or services on the Internet. Previous work has shown that reducing a product's uncertainty is critical to its purchase decision. Thus, reviews are more effective when they reduce a product's uncertainty. Existing e-commerce platforms typically ask users to write free-form text reviews, which are sometimes augmented by a small set of predefined questions, e.g., “rate the product description's accuracy from 1 to 5.” In this paper, we argue that this “passive” style of review solicitation is suboptimal in achieving low-uncertainty “review profiles” for products. Its key drawback is that some product aspects receive a very large number of reviews while other aspects do not have enough reviews to draw confident conclusions. Therefore, we hypothesize that we can achieve lower-uncertainty review profiles by carefully selecting which aspects users are asked to rate. To test this hypothesis, we propose various techniques to dynamically select which aspects to ask users to rate given the current review profile of a product. We use Bayesian principles to define reasonable review profile uncertainty measures; specifically, we apply Bayesian inference to measure an aspect's rating variance. We compare our proposed aspect selection techniques to several baselines on several review profile uncertainty measures. Experimental results on two real-world datasets show that our methods lead to better review profile uncertainty compared to aspect selection baselines and traditional passive review solicitations.
Comparative evaluation of malaria antigen test and peripheral blood smears in diagnosis of malaria

Comparative evaluation of malaria antigen test and peripheral blood smears in diagnosis of malaria - IJMMTD- Print ISSN No: - 2581-4753 Online ISSN No:- 2581-4761 Article DOI No:- 10.18231/2581-4761.2019.0008, IP International Journal of Medical Microbiology and Tropical Diseases-IP Int J Med Microbiol Trop Dis
LibGuides: How to Set Up Speech Recognition System in Windows 10: Home

On Windows 10, Speech Recognition is an easy-to-use experience that allows you to control your computer entirely with voice commands.Please follow the Guide to set up your Window 10.
Jumps of optimal measurement angle and fractures on the curves of quantum correlation functions

The one-way quantum work deficit, a measure of quantum correlation, exhibits the regions with the bimodal behavior of post-measurement entropy versus the measurement angle &theta; &epsilon; (0, &pi;/2). Under certain conditions this can lead to the finite jumps &Delta;&nu;&gt; 0 of optimal measurement angle &nu; from the endpoint 0 or &pi;/2 to the interior minimum and vice versa. In turn, such sudden jumps lead to the fractures, i.e., non-analytical points on the dependencies of quantum correlation upon the state parameters. We examine a possibility to experimentally observe these phenomena on an example of three-component mixture consisting of one pair of Bell-diagonal states and a basis state orthogonal to the Bell ones. Observation of named effects, beyond their intrinsic interest, could demonstrate the experimental ability in controlling and manipulating the quantum states.
Developments and Challenges of Language Testing: Past, Presents, and Future

ABSTRACT: This article discusses recent developments and challenges in language testing. It starts with past, present and future parts that are applied to all measurement and frameworks in the area of Language Testing. Representation on Alderson' influential work in order to show the development of each time for evaluating language tests. It will be concisely reviewed the indication and limitations of traditional until modern assessment are compared to see the challenging of it and also the advantages and disadvantages of each type of tests. Some problems in language testing are discussed: the methods effect, classification errors, arrangement of each test, the local independence problems, and a careless attitude towards the error of measurement that happened unconsciously. This article concludes with new developments in language testing area and the problem on the context of test such as TOEFL, TOEIC, etc about four skills of English namely reading, speaking, writing and listening test. Keywords: language testing, past, present, future assesment, error of measurement
Specifications for Elementary Particles, Dark Matter, Dark Energy, and Unifying Physics Theories

We suggest united models and specific predictions regarding elementary particles, dark matter, aspects of galaxy evolution, dark energy, and aspects of the cosmology timeline. Results include specific predictions for new elementary particles and specific descriptions of dark matter and dark energy. Some of our modeling matches known elementary particles and extrapolates to predict other elementary particles, including bases for dark matter. Some modeling explains observed ratios of effects of dark matter to effects of ordinary matter. Some models suggest aspects of galaxy formation and evolution. Some modeling correlates with eras of increases or decreases in the observed rate of expansion of the universe. Our modeling framework features mathematics for isotropic quantum harmonic oscillators and provides a framework for creating and unifying physics theories. Aspects of our approach emphasize existence of elementary particles and de-emphasize motion. Some of our models complement traditional quantum field theory and, for example, traditional calculations of anomalous magnetic dipole moments.
Ψηφιακή καταγραφή και επεξεργασία αναλογικών σημάτων πολλαπλών ηλεκτρικών μουσικών οργάνων για την παραγωγή μουσικής μέσω Η/Υ

The current thesis is a case study on the process of digital recording and processing of analog signals from various musical instruments for a music piece production. During the first part of the process synthesis, performance and digital recording of the music piece were conducted, while during the second part the analog signals from the music instruments were digitally processed through specialised software tools, in order to complete the production. Through this thesis, both theoretical basis related to the abovementioned process and production technical steps are presented. More specifically, the current thesis provides theoretical information on the nature of sound, on the process of an analogue audio signal conversion to digital form and on editing, mastering and mixing. Moreover, basic tools and capabilities of softwares used in digital signal processing are presented. Also, theoretical and technical information about digital recording and digital processing is provided. Last but not least, the current thesis contains a step-by-step description of a music piece’s mixing and mastering. It contains a detailed description of the software tools used during digitization and processing of the analogue signals that were received from each musical instrument. Also, the overall process of the music piece’s mixing and mastering is described.
Incorporating Social Practices in BDI Agent Systems

When agents interact with humans, either through embodied agents or because they are embedded in a robot, it would be easy if they could use fixed interaction protocols as they do with other agents. However, people do not keep fixed protocols in their day-to-day interactions and the social environment is often dynamic, making it impossible to use fixed protocols. Deliberating about interactions from fundamentals is not very scalable either, because in that case all possible reactions of a human have to be considered in the agent’s plans. In this paper we argue that social practices can be used as an inspiration for designing flexible and scalable interaction mechanisms that are also robust. However, using social practices requires extending the traditional BDI deliberation cycle to monitor landmark states and perform expected actions by leveraging existing plans. We define and implement this mechanism in Jason using a periodically run meta-deliberation plan, supported by a metainterpreter, and illustrate its use in a realistic scenario.