Reviewerly/exHarmony huggingface dataset:
Hubungan Motivasi Berprestasi, ( English ) Self Efficacy dan Jenis Kelamin dengan Prestasi Belajar Bahasa Inggris Siswa Kelas XII MAN Salatiga

The aim of this research is to find out the relation of achievement motivation, English self efficacy and sex with English Learning Motivation Achievement of Student Grade 12 th English at MAN Salatiga. The population in this research is the whole students of grade 12 th which amounts 295 students, while the number of the samples that has been used in this research were 100 students. To measure the achievement motivation it has been used questionnaire adapted by McLelland (dalam Wijono, 2012). To measure the variable of English self efficacy it has been used questionnaire by Corsini (dalam Siregar, 2012) , while the student’s achievement has been measured by using the mid test in the second semester period 2013/2014. Before testing the hypothesis, first, it is measureed the validity and reliability of measuring instruments by using a standard p<0.05 for validity and p<0.05 for reliability. After the writer/researcher test the hypothesis, then there are some research results as follows: there is no a significant relationship of achievement motivation and English self efficacy with student achievement, there is no interaction effect of peer achievement motivation and sex with student achievement, there is no interaction effect of English self efficacy and sex with student achievement, the population rates there was no difference in student learning achievement in terms of gender.
A Two tenant Secure Data Sharing Scheme Using Cloud Resource Mediation Service

Sharing of assets on the cloud can be accomplished on a huge scale since it is savvy and area free. Regardless of the publicity encompassing distributed computing, associations are as yet hesitant to send their organizations in the distributed computing condition because of worries in secure asset sharing. In this paper, we propose a cloud asset intervention benefit offered by cloud specialist co-ops, which assumes the part of confided in outsider among its distinctive occupants. This paper formally determines the asset sharing system between two unique occupants within the sight of our proposed cloud asset intervention benefit. The rightness of authorization enactment and assignment component among various occupants utilizing four unmistakable calculations (Activation, Delegation, Forward Revocation and Backward Revocation) is likewise exhibited utilizing formal confirmation. The execution examination recommends that sharing of assets can be performed safely and productively crosswise over various inhabitants of the cloud.
PERANCANGAN GEOGRAPHIC INFORMATION SYSTEM UNTUK TRACKING DAN ROUTING MENGGUNAKAN ALGORITMA DIJKSTRA PADA KENDARAAN ANGKUTAN UMUM

The ability to do tracking and routing of a motorized vehicle is very useful in everyday life, such as security on private vehicles, public transportation systems, mass transportation fleet management and others. In this study, we designed a Geographic Information System (GIS) application that will be applied to public transport services. This system will in real time track the position of each vehicle (taxi) and be able to perform automatic service for every taxi request by the customer.&#x0D; Dijkstra's algorithm is a graph search algorithm that solves the shortest path problem that originates from one node for a graph where the weight of the node must not be negative. The analysis is done by examining the node with the smallest weight and inserting it into the set of solutions with the initial search for the origin node requiring knowledge of all paths and weights. Dijkstra's algorithm which is applied to this system will function to find the most suitable taxi for customers by using distance parameters and traffic density levels as the weight value.
SISTEM PAKAR NUTRITION PLANUNTUK ORANG DEWASA DENGAN METODE FORWARD CHAINING BERBASIS WEBSITE

The problem of nutrition is still a public health problem in Indonesia. Malnutrition has not been resolved, the prevalence of overweight and obesity has begun to increase, especially in the middle and upper socioeconomic groups in urban areas. This is particularly troubling because it threatens the quality of Human Resources (HR) is indispensable in the future (Depkes RI, 2007). Changes in diet and physical activity resulted in the increasing number of people experiencing nutritional problems, such as overweight/obesity and malnutrition. Diet as the main factor nutritional problems, basically can be overcome by regulating the intake of good nutrition for consumption. But unfortunately, not many people know the setting of a good and proper diet. The Nutrition Plan was created as an expert system in determining balanced nutrition for adults based on body mass index and daily diet using forward chaining inference. This system will recommend what foods are suitable for every adult in accordance with the needs of calories per day in the hope of prevalence rates for the Indonesian people suffering from malnutrition and overweight can be reduced significantly. In addition to facilitating the public, especially normal adults to know the nutritional information in order to achieve a healthy lifestyle.
A new chase-type soft-decision decoding algorithm for Reed-Solomon codes

A new Chase-type soft-decision decoding algorithm for Reed-Solomon codes is proposed, referred to as tree-based Chase-type algorithm. The proposed tree-based Chase-type algorithm takes the set of all vectors as the set of testing patterns, and hence definitely delivers the most-likely codeword provided that the computational resources are allowed. All the testing patterns are arranged in an ordered rooted tree according to the likelihood bounds of the possibly generated codewords, which is an extension of Wu and Pados’ method from binary into q-ary linear block codes. While performing the algorithm, the ordered rooted tree is constructed progressively by adding at most two leafs at each trial. The ordered tree naturally induces a sufficient condition for the most-likely codeword. That is, whenever the tree-based Chase-type algorithm exits before a preset maximum number of trials is reached, the output codeword must be the most-likely one. But, in fact, the algorithm can be terminated by setting a discrepancy threshold instead of a maximum number of trials. When the tree-based Chase-type algorithm is combined with Guruswami-Sudan (GS) algorithm, each trial can be implement in an extremely simple way by removing from the gradually updated Gröbner basis one old point and interpolating one new point. Simulation results show that the tree-based Chase-type algorithm performs better than the recently proposed Chase-type algorithm by Bellorado et al. with less trials (on average) given that the maximum number of trials is the same.
Structuring E-Brainstorming to Better Support Innovation Processes

Innovation is a key instrument to start a transformational process based on collaboration. It is fundamental for organisations and institutions to have well defined strategies. In this context, brainstorming sessions - and e-brainstorming tools - are effective techniques to put together and associate draft ideas. Yet, in many cases, those ideas and associations do not leave enough digital footprints, are no further used or are lost. This paper introduces the use of Social and Semantic Web technologies to support e-brainstorming. In particular, we present a lightweight ontology to structure e-brainstorming sessions, and the enrichment of existing e-brainstorming tools to do so.
Mining Rules from Player Experience and Activity Data

Feedback on player experience and behaviour can be invaluable to game designers, but there is need for specialised knowledge discovery tools to deal with high volume playtest data. We describe a study witha commercial third-person shooter, in which integrated player activity and experience data was captured and mined for design-relevant knowledge. We demonstrate that association rule learning and rule templates can be used to extractmeaningful rules relating player activity and experience during combat. We found that the number, type and quality of rules varies between experiences, and is affected by feature distributions. Further work is required on rule selection and evaluation.
A Microcontroller Based Solar Panel Tracking System

Renewable energy is rapidly gaining importance as an energy resource as fossil fuel prices fluctuate.At the educational level, it is therefore critical for engineering and technology students to have an understanding and appreciation of the technologies associated with renewable energy.One of the most popular renewable energy sources is solar energy.This paper describes a capstone design project where a student in Electrical Engineering Technology designed and built a microcontroller-based solar panel tracking system.Solar tracking enables more energy to be generated because the solar panel is able to maintain a perpendicular profile to the sun's rays.This system builds upon a prior senior design project where students built a solar-powered battery charger, thus making this system ideally self-contained.The student was able to demonstrate a working system, thus validating the design.Potential improvements to the system are presented.
Parallel RMCLP Classification Algorithm and Its Application on the Medical Data

To make better use of the cloud computing technology, and to overcome the computing and storage requirements which increase rapidly with the number of training samples, in this paper, a new parallel algorithm is proposed-Parallel Regularized Multiple-Criteria Linear Programming (PRMCLP) algorithm-The RMCLP model is converted into a unconstrained optimization problem, and then, in the parallel version, it is split into several tasks, where each part is mapped and computed on a separate processor. This approach enables us to obtain efficiently the final optimization solution of the whole classification problem. At last, we apply this algorithm to Medical data classification. All experiments show that our method and approach greatly increases the training speed of RMCLP in the parallel case.
An Authoring Tool to Derive Valid Interactive Scenarios

In recent years, many tools have been proposed to design interactive scenarios. The aim of these tools is to provide users with a framework in order to write a story with many branches which will be unfolded by an artificial intelligence application. However, the consistency and quality of the generated narratives are not guaranteed (deadlocks, flaws, etc.). Previous work has defined the properties of a valid interactive scenario and proposed an approach as well as a tool based on a formal model, Linear Logic, to validate these properties. Nevertheless, the application of this tool requires many special skills and so is not really suitable for normal users. In this paper, we present an authoring tool which allows modeling interactive scenarios and analysing them at the structural level using the deduction rules in Linear Logic. Thanks to our tool, normal users are able to create and validate interactive scenarios in comparison with a rich set of predefined properties/criteria of quality.
Teams Battling Teams: Introducing Software Engineering Education in the First-Year with RoboCode

description languages, and systems-of-systems modeling.His doctoral work focused on supporting selfadaptive software using an architecture-and policy-based approach with an emphasis on the robotics domain.
Spatial Variational Auto-Encoding via Matrix-Variate Normal Distributions

The key idea of variational auto-encoders (VAEs) resembles that of traditional auto-encoder models in which spatial information is supposed to be explicitly encoded in the latent space.However, the latent variables in VAEs are vectors, which can be interpreted as multiple feature maps of size 1x1.Such representations can only convey spatial information implicitly when coupled with powerful decoders.In this work, we propose spatial VAEs that use feature maps of larger size as latent variables to explicitly capture spatial information.This is achieved by allowing the latent variables to be sampled from matrix-variate normal (MVN) distributions whose parameters are computed from the encoder network.To increase dependencies among locations on latent feature maps and reduce the number of parameters, we further propose spatial VAEs via low-rank MVN distributions.Experimental results show that the proposed spatial VAEs outperform original VAEs in capturing rich structural and spatial information.
Learning From Stories: Using Crowdsourced Narratives to Train Virtual Agents

In this work we introduce Quixote, a system that makes programming virtual agents more accessible to non-programmers by enabling these agents to be trained using the sociocultural knowledge present in stories. Quixote uses a corpus of exemplar stories to automatically engineer a reward function that is used to train virtual agents to exhibit desired behaviors using reinforcement learning. We show the effectiveness of our system with a case study conducted in a virtual environment called Robbery World that simulates a bank robbery scenario. In this case study, we use a corpus of stories crowdsourced from Amazon Mechanical Turk to guide learning. We evaluate Quixote under a variety of different conditions to determine the overall effectiveness of the system in Robbery World.
USASBE: United States Association for Small Business and Entrepreneurship 2017

About USASBEThe United States Association for Small Business and Entrepreneurship (USASBE) bills itself as the "largest independent, professional, academic organization in the world dedicated to advancing the discipline of entrepreneurship."USASBE has about 1,000 members. Nature of the USASBE ConferenceAround 500 business faculty, Ph.D. students, and vendors attended the USASBE annual conference in Philadelphia on January 19-22, 2017.The main conference ran from Thursday afternoon through Sunday, with pre-conferences on the Wednesday before.Early-bird registration was $675 (full cost was $750), making USASBE much more expensive than most library conferences.However, the fee covered breakfasts, lunches, and one year of membership in the association.All USASBE programming was held in Loews Philadelphia Hotel on Market Street, between City Hall and Independence Mall.The conference provided an opening-night reception at the Drexel Academy of Natural Sciences.The Saturday-night dinner gala included circus acrobats performing in the hotel ballroom.The conference offered eight types of programs:• Competitive papers (short solo presentations on research, teaching, or program design, followed by discussion) • Teaching cases (presentations of case studies used in the classroom) • Developmental papers (roundtable feedback on research in progress) • Competitive workshops (interactive panel discussions) • Rocket workshops (short workshops) • Experiential exercises (presentations of classroom exercises) • Student pitches (featuring students from Philadelphia-area universities, with several rounds of voting on multiple days of the conference) • Exhibitor sessions (mostly related to entrepreneurship educational software)
Irony and Sarcasm Detection in Twitter: The Role of Affective Content

PhD thesis in Computer Science written by Delia Irazu Hernandez Farias under the supervision of Dr. Paolo Rosso (Universitat Politecnica de Valencia) and Dra. Viviana Patti (University of Turin). This thesis was developed under a cotutelle between the Universitat Politecnica de Valencia, Spain and the University of Turin, Italy. The thesis defense was done in Valencia, Spain on September 25, 2017. The doctoral committee was integrated by: Horacio Saggion (Universitat Pompeu Fabra), Elisabetta Fersini (Universita degli Studi di Milano-Bicocca), and Roberto Basili (Univerita di Roma Tor Vergata). The International mention was achieved after a 12 months internship at University of Turin.
Gardien du Temple: An Interactive Installation Involving Poetry, Performance and Spatial Augmented Reality

Gardien du Temple is an interactive installation where the concealment or revelation of poems and images is achieved through diminished reality, a new approach to augmented reality using a projector-camera system. By capturing the environment with a camera and canceling parts of the scene by reprojecting inverted images, Gardien du Temple questions the control of our perception, of what is present or not. It reveals new perspectives for installations and performing arts aiming at erasing parts of the physical space.
2D Dimensionality Reduction Methods without Loss

In this paper, several two-dimensional extensions of principal component analysis (PCA) and linear discriminant analysis (LDA) techniques has been applied in a lossless dimensionality reduction framework, for face recognition application. In this framework, the benefits of dimensionality reduction were used to improve the performance of its predictive model, which was a support vector machine (SVM) classifier. At the same time, the loss of the useful information was minimized using the projection penalty idea. The well-known face databases were used to train and evaluate the proposed methods. The experimental results indicated that the proposed methods had a higher average classification accuracy in general compared to the classification based on Euclidean distance, and also compared to the methods which first extracted features based on dimensionality reduction technics, and then used SVM classifier as the predictive model.
Digital Video Forensics: A Comprehensive Survey

The wide spread of digital devices and tools causes the simplification of the manipulation of any digital multimedia content. As a result, digital videos and photos are not trusted to be used as evidence in courts. This fact raises the need for finding techniques to ensure the authenticity of digital multimedia contents. Experts in digital-signal processing conducted a huge number of researches to find new strategies, using digital forensics, to verify digital evidences and trace its origins. The aim of this paper is to collect and provide the definitions of the main concepts related to media forensics. Also, this paper gives an overview of the different techniques used in media forensics concentrating on video forensics. Furthermore, it classifies the work done in the field according to the main technique used in the proposed solution approach.
DEIXIS IN MALEFICENT MOVIE SCRIPT

This study is an attempt to analyze types of deixis those are: personal deixis ( first. Second, and third person deixis), place deixis, time deixis, and discourse deixis.  This study only focused on the movie script. This study was purposed to find out the types and the dominant of deixis are used in  Maleficent Movie Script. This script got from the internet. The study applied descriptive qualitative method.  Steps of analyses the data, it applied was the first, this study looked for the movie, the second, this study watched the movie, then, looked for the movie script of the movie “Black Swan”, the fourth, this study identified the sentence of the movie script based on four types of deixis. The result of this research shows dominant in person deixis: I, you, we, he, she, our, king Stephan, because from the result personal deixis in the movie script is dominant from the place, time, and discourse deixis.
Sign Language Translator

Author(s): Lo, Brandon; Mohanraj, Harshithaa; Ngo, Brandon; Phan, Daniel | Abstract: The Sign Language Translator is a glove that translates sign language to text and speech in real time. The glove is outfitted with an Arduino Lilypad, an Accelerometer, Flex Sensors and Contact Sensors. Values from these sensors are sent via bluetooth to an iPhone application which predicts and displays the translated gesture. Through the application, users are able to calibrate the glove and view the translation.Team Advisor: Professor Pooria M. YaghiniDepartment of Electrical Engineering and Computer ScienceWebsite: http://projects.eng.uci.edu/projects/asl-communications-device
Dynamic system with random structure for modeling security and risk management in cyberspace

We deal with the investigation of \(L_{2}\)-stability of the trivial solution to the system of difference equations with coefficients depending on a semi-Markov chain. In our considerations, random transformations of solutions are assumed. Necessary and sufficient conditions for \(L_{2}\)-stability of the trivial solution to such systems are obtained. A method is proposed for constructing Lyapunov functions and the conditions for its existence are justified. The dynamic system and methods discussed in the paper are very well suited for use as models for protecting information in cyberspace.
Cyber Risk Management in Banks

Security vulnerabilities available in cyber security systems lead to virtual and physical damages to financial systems which in turn cause national- and individual-level security issues. Today's world is being shaped by digital technology, and cyber threats to information constitute a significant risk factor for businesses. This study explores the cyber security risks the banking system may encounter. The status of banking system, a system which includes a number of online services, in Turkey with respect to cyber security risks and the current risks are assessed and presented along with possible solutions. This study analyzes e-payment systems (online banking and e-trade/the use of debit/credit cards) and the supply chain, the backbone of the e-finance system, with respect to national cyber security risks. Nevertheless, cyber risk insurance, an emerging tool for cyber risk management, was analyzed in detail.
Elementary teachers on orchestrating teaching for mathematically highly able pupils

Studies on high ability in mathematics rarely take a teacher's perspective.The purpose of our study is to add such a perspective, which we will do by using positioning theory to analyze elementary teachers' discussions on mathematical tasks, aiming to challenge all pupils, including the highly able.The study is conducted in the context of a two-year long teacher professional development program on high ability.Teachers expressed both their teaching and the mathematical tasks as helpful in orchestrating teaching suitable for highly able pupils.They highlight the opportunities given by some tasks as well as the importance of guiding highly able pupils to go further in such tasks.However, they expressed their own limited mathematical knowledge and time needed for pupils with learning difficulties as obstacles to orchestrate teaching for the highly able.The results show that it is important to, in close cooperation with teachers, further explore how to orchestrate teaching that challenges highly able pupils.
The matching pursuit algorithm revisited: A variant for big data and new stopping rules

The matching pursuit algorithm (MPA) is used in many applications for selecting the best predictors for a vector of measurements of size n from a dictionary that contains pn atoms, where usually n ≤ pn. A major unsolved problem is to determine the optimal stopping rule. In this work, we investigate various stopping rules which are modifications of the information theoretic (IT) criteria derived for Gaussian linear regression. Because all of them involve the degrees of freedom (df) given by the trace of the hat matrix, we provide some theoretical results concerning this matrix. We also propose novel stopping rules. An important contribution of this paper is a method for computing the df efficiently when big data (n ≫ pn) are processed. The significance of the auxiliary variables appearing in MPA for big data is clarified via a theoretical analysis. The superiority of the new stopping rules in comparison with the traditional approaches is demonstrated in simulations involving big data (n ≫ pn) or overcomplete dictionaries (n < pn) and in experiments with air pollution data.