Miracle-dz/UniFAR-FTUs huggingface dataset:
Emotion Classification Based On Public Opinion Analysis On Online News

: Technological developments, especially on social media, allow online news readers to channel their opinions in the form of comments and reactions. Opinions given by readers are a great source of data that can be processed for the emotions of readers. This paper intends to classify emotions by comparing two classifiers, namely Naive Bayes and Logistic Regression. The dataset used in this study was taken from Indonesian online news detik.com which has eight class emotion. This study has several experimental scenarios that is a combination of total comment and ratio. Because of the imbalance class data, this study uses the SMOTE oversampling technique. This study also shows that the use of SMOTE oversampling can improve classifier performance. The results of this study show that the accuracy achieved 55.43% for the Naive Bayes classifier and 65.95% for the Logistic Regression classifier after SMOTE. It can increase the accuracy up to 35%.
Why Students Learn More From Dialogue- Than Monologue-Videos: Analyses of Peer Interactions

In 2 separate studies, we found that college-age students learned more when they collaboratively watched tutorial dialogue-videos than lecture-style monologue-videos. In fact, they can learn as well as the tutees in the dialogue-videos. These results replicate similar findings in the literature showing the advantage of dialogue-videos even when observers watched them individually. However, having the observing students watch collaboratively as dyads provided data to carry out in-depth analyses of their conversations and activities in order to understand why dialogue-videos are superior to monologue-videos. Toward that goal, transcripts of video dialogues and monologues, as well as peer-to-peer conversations of the observing students collected in a prior study, were analyzed using the ICAP (interactive, constructive, active, passive) framework as a lens. Three sets of analyses were carried out. The 1st set focused on the content of the videos in terms of the tutors’ and the tutees’ moves. The 2nd set focused on the activities and behaviors of the collaboratively observing dyads. The 3rd set focused on the role of the tutees in the dialogue-videos in eliciting constructive and interactive engagement from the observing students. Our analyses suggest that dialogue-videos naturally elicited more constructive and interactive engagement behaviors from the observers than the monologue-videos, which in turn mediated the observers’ own learning.
An Isolated Modular Multilevel Converter (I-M2C) Topology Based on High-Frequency Link (HFL) Concept

This paper introduces the high-frequency link concept into the modular multilevel converter (MMC) topology, which can totally reduce the individual dc-link capacitors at the high-voltage side. The proposed converter, called isolated MMC, has basic triple ports of medium-voltage ac, medium-voltage dc, and low-voltage dc. Thus, it is especially suitable for hybrid dc and ac applications in power generation and transmission, such as solid-state transformer. The fundamental principle and applied control scheme of phase-shift pulsewidth modulation are presented in detail. The design of the voltage clamping circuit and analysis of duty loss are carried out. The experimental results are given to illustrate the efficient operation characteristics.
Easy/difficult-constructions as triggers of implicit content: comparing covert event elicitations and events extracted from a very large corpus

ENT: letter: write, read automobile: telic quale (driving) but not agentive quale (produce), more typical events are buy, sell, fix, repair EVE: difficult/easy restrict the range of events to those for which the degree of difficulty is relevant (no light verbs) AMB: events related to their entity component (clean the shower), but also to their event component (take the shower) 8. Corpus extraction
Survival analysis : state of the art

Life Testing and Reliability Estimation Under Asymmetric Loss. - Bayesian Computations In Survival Models Via the Gibbs Sampler. - Bayesian Nonparametric Survival Analysis: A Comparison of the Kaplan-Meier and Berliner-Hill Estimators. - Modelling Time-Varying Hazards and Covariate Effects. - Analysis of Trials with Treatment - Individual Interactions. - Assessment of Dependence In the Life Times of Twins. - Estimating Random Effects In the Framingham Heart Study. - Survival Analysis in Genetics: Danish Twin Data Applied To a Gerontological Question. - Some Issues in the Collection and Analysis of Field Reliability Data. - Bayesian Modelling For Fatigue Crack Curves. - Statistical Analysis Of a Weibull Process With Left- Censored Data. - Kernel Density Estimation from Record-Breaking Data. - Semiparametric Estimation Of Parametric Hazard Rates. - Cox-Type Regression Analysis for Large Numbers of Small Groups of Correlated Failure Time Observations. - Information Bounds For the Additive and Multiplicative Intensity Models. - Survival Analysis For Left Censored Data. - Regression Analysis for Discrete and Continuous Truncated and Eventually Censored Data. - Independent Delayed Entry. - Periodic Inspections in a Longitudinal Study: Viewing Occult Tumors Through a Filter. - Survival Under Multiple Time Scales in Dynamic Environments. - Nonparametric Identifiability of Marginal Survival Distributions in the Presence of Dependent Competing Risks and a Prognostic Covariate. - Frailty Models For Multiple Event Times. - A Nonparametric Approach To Dependence For Bivariate Censored Data. - Marginal and Conditional Models for the Analysis of Multivariate Failure Time Data. - Multivariate Failure Time Analysis: Discussion of Papes by Oakes Pons, Kaddour and De Turckheim and Prentice and Cai. - Survivor Functions as Dependent Variables In Demographic Analysis. - Relation Between The Rate Of Return To Tenure, Earnings Growth and Job Switching. - List of Contributors.
Flexible parametric survival models: An application to gastric cancer data

Article history: Received 21 December 2016 Received in revised form 12 February 2017 Accepted 18 February 2017 Flexible parametric survival models using cubic splines become popular in survival data analysis. The property of allowing converging hazard functions leads them to be the alternatives to Cox proportional hazards model and parametric survival models. In this study, flexible parametric survival models are applied to the data set of 106 gastric cancer patients. According to this data set, metastasis and muscle contraction are found as important risk factors on survival.
Robust nonnegative matrix factorization via L1 norm regularization by multiplicative updating rules

Nonnegative Matrix Factorization (NMF) is a widely used technique in many applications such as face recognition, motion segmentation, etc. It approximates the nonnegative data in an original high dimensional space with a linear representation in a low dimensional space by using the product of two nonnegative matrices. In many applications data are often partially corrupted with large additive noise. When the positions of noise are known, some existing variants of N-MF can be applied by treating these corrupted entries as missing values. However, the positions are often unknown in many real world applications, which prevents the usage of traditional NMF or other existing variants of NMF. This paper proposes a Robust Nonnegative Matrix Factorization (RobustNMF) algorithm that explicitly models the partial corruption as large additive noise without requiring the information of positions of noise. In particular, the proposed method jointly approximates the clean data matrix with the product of two nonnegative matrices and estimates the positions and values of outliers/noise. An efficient iterative optimization algorithm with a solid theoretical justification has been proposed to learn the desired matrix factorization. Experimental results demonstrate the advantages of the proposed algorithm.
Simultaneous preconditioning and symmetrization of non-symmetric linear systems

Motivated by the theory of self-duality which provides a variational formulation and resolution for non self-adjoint partial differential equations [6, 7], we propose new templates for solving large non-symmetric linear systems. The method consists of combining a new scheme that simultaneously preconditions and symmetrizes the problem, with various well known iterative methods for solving linear and symmetric problems. The approach seems to be efficient when dealing withcertain ill-conditioned, and highly non-symmetric systems.
Two-body problem on spaces of constant curvature

The two-body problem with a central interaction on simply connected constant curvature spaces of an arbitrary dimension is considered. The explicit expression for the quantum two-body Hamiltonian via a radial differential operator and generators of the isometry group is found. We construct a self-adjoint extension of this Hamiltonian. Some its exact spectral series are calculated for several potential in the space ${\bf S}^3$. We describe also the reduced classical mechanical system on a homogeneous space of a Lie group in terms of the coadjoint action of this group. Using this approach the description of the reduced classical two-body problem on constant curvature spaces is given.
Trusted Computing Platforms: TPM2.0 in Context

In this book the authors first describe the background of trusted platforms and trusted computing and speculate about the future. They then describe the technical features and architectures of trusted platforms from several different perspectives, finally explaining second-generation TPMs, including a technical description intended to supplement the Trusted Computing Group's TPM2 specifications. The intended audience is IT managers and engineers and graduate students in information security.
COMMON FIXED POINT RESULTS FOR MAPPINGS SATISFYING (PSI, PHI) -WEAK CONTRACTIONS IN ORDERED PARTIAL METRIC SPACES

In this paper, we extend a result of Stojan Radenovic and Zoran Kadelburg [Generalized weak contractions in partially ordered metric spaces, Computers and Mathematics with Applications 60 (2010), 1776-1783] to ordered partial metric spaces. Besides, we present an example illustrating our result and we deduce a fixed point theorem involving contractions of integral type.
Statistical Machine Translation between Unsegmented Japanese and Chinese Texts

Many Asian languages like Japanese and Chinese do not have explicit boundaries between words. Word segmentation is normally treated as the first step for most Natural Language Processing tasks especially for Statistical Machine Translation (SMT). In this paper, we implemented several machine translation experiments on both pre-segmented and unsegmented text corpus. The experiment results showed that word segmentation may not be a prerequisite step for SMT between Japanese and Chinese.
On the synthesis of stable /spl Hscr//sup /spl infin// controllers

A sufficient condition is derived for the existence of a stable suboptimal /spl Hscr//sup /spl infin// controller. It is shown that if a certain algebraic Riccati equation, determined from a parameterization of all suboptimal /spl Hscr//sup /spl infin// controllers, has a positive definite stabilizing solution, then a stable /spl Hscr//sup /spl infin// controller of order 2n can be constructed, where n is the order of the generalized plant.
Scheduling scientific workflow applications in computational grids

A computational grid, built using grid computing technology, is a network of computing resources that work together as a single, uniform operating environment. It can be viewed as a virtual supercomputer designed for large-scale applications. One important characteristic of these applications is that they are no longer being developed as monolithic and single-executable codes, but incorporate multiple dependent computational modules. The execution of these applications involves the concurrent and sequential execution of multiple modules in a predefined order, and the automatic and timely data transfer between modules. These applications are often referred to as scientific workflow applications. A very important issue in executing a scientific workflow application in computational grids is how to map and schedule workflow modules onto multiple distributed resources, and handle module dependencies in a timely manner to deliver users' expected performance. The goal of this research is to develop a workflow system to address the issue of workflow scheduling in computational grid environments. In our work, we have developed a grid workflow description language that addresses the limitation of lacking support for resource request specification in current related efforts. An integrated workflow scheduling architecture has been defined that provides the capabilities of workflow execution planning, resource allocation and execution coordination. Our workflow scheduler applies advanced scheduling techniques, such as planning, resource reservation and performance predictions in the resource allocation process. The simulation results show that our workflow scheduler reduces the workflow execution time by about 20% on average under moderate to high resource load, compared to the scheduling policies used in most of current workflow systems.
Adaptive parallel sorting

The capacity of an algorithm to modify its behavior to the size, difficulty or structure of the problem instance has been named adaptivity. The literature on parallel algorithms qualifies as adaptive those algorithms that work with a fixed amount of processors on input of arbitrary size while the literature on sorting algorithms qualifies as adaptive those algoritms that perform work proportional to the amount of disorder in the input. We combine these two concepts and present the first two parallel sorting algorithms that -are designed for a fixed number of processors and reconfigure according to the size of the input. - adapt to the amount of disorder in the input, and -are cost optimal.
An In-depth Analysis of Co-occurrence Matrix-based Features

In this paper, we do in-depth analysis of image based on gray-level co-occurrence matrices for various features. Image texture and property analysis has ample applications in various fields. Hence, we employ eleven different features on standard dataset to evaluate them on twenty-one images of varied textures and increasing complexities. We implement these features based on the co-occurrence matrices on each image. We analyze these features and demonstrated their variations and impact on different gray-scale images. This is the first time to evaluate these in such extensive manner and we find significant variations from which one can evaluate the required features for specific image classes.
On Identifying Structural VAR Models via ARCH Effects

Abstract: We consider the local identification of parameters in structural VAR models with ARCH type errors. By establishing a mapping between the structural and reduced-form models, we provide a set of sufficient conditions for the joint identification of all parameters. Under these conditions, as the structural parameters are identified, various restrictions on the parameters can be tested in a standard manner. For example, the significance test for the ARCH effect in the usual GARCH formulation for a structural shock does not suffer the complications caused by a lack of identification encountered in univariate GARCH models.
Detecting the Image Forgery from Color Images Using SURF and DWT

Forensics means the use of science and technology in the investigation and establishment of facts. So the photos or different pictures can be transmitted to and reconverted into pictures by another PC. Computerized crime scene investigation (in some cases known as advanced legal science) is a branch of measurable science including the recuperation and examination of material found in computerized gadgets. Advanced picture crime scene investigation goes for recovering so as to approve the genuineness of pictures data about their history. Two primary issues are tended to: the recognizable proof of the imaging gadget that caught the picture, and the identification of hints of phonies. These days, because of the promising results achieved by ahead of schedule studies and to the continually developing number of uses, advanced picture legal sciences speak to an engaging examination area for some scientists. With the across the board accessibility of picture altering programming, advanced pictures have been turning out to be anything but difficult to control and alter notwithstanding for non-proficient clients. Picture control has gotten to be typical with developing simple access to effective registering capacities. A standout amongst the most widely recognized sorts of picture imitations is the duplicate glue falsification, wherein a district from a picture is supplanted with another area from the same picture (With conceivable changes). Since the replicated part originate from the same picture, its critical properties, for example, clamor, shading palette and Composition will be perfect with whatever is left of the picture and hence will be harder to recognize and identify these parts. Computerized picture crime scene investigation is a fresh out of the plastic new research field which goes for recovering so as to approve the legitimacy of pictures data about their history. Computerized picture criminology goes for recovering so as to approve the validness of pictures data about their history. We propose a progression of calculations which are mix of speeded-up strong component changes and Wavelet Transforms. In doing as such we will first examine Speeded-Up Robust Feature (SURF), SURF in mix with Discrete Wavelet Transform (DWT), SURF in mix with Discrete Wavelet Transform (DWT). These calculations are not the same as the beforehand proposed calculation in the way that they are connected on the whole picture to concentrate highlights instead of separating the picture into the squares. From the outcomes got we have the capacity to close the proposed calculations are superior to their partners both as far as computational multifaceted nature and invariance to scale and pivot furthermore for the blend of assaults. We have located the 97% precision of the work. Keywords— Digital Image forgery, DWT (Discrete Wavelet Transform), SURF (Speeded-Up Robust Feature), Image, Forensics etc.
High-enthalpy, hypersonic compression corner flow

The results of an experimental investigation of high-enthalpy, hypersonic flow over sharp leading-edge compression corners are presented and discussed. In particular, the possible effects of real gas behavior are examined. Measurements have been made of the heat transfer and pressure distributions for flat plate and compression corner flow. Some flow visualization data have also been obtained. Test flows were generated using a free-piston shock tunnel operating in the reflected mode. The reservoir enthalpy ranged from 3 to 19 MJ kg -1 , giving freestream speeds of 2.3-5.5 km s -1 . For these conditions, the flow remains laminar throughout. The flat plate data for both high- and low-enthalpy flows are in agreement with the reference enthalpy method for heat transfer and the weak interaction theory for pressure. Also, the measured flat plate boundary-layer thickness compares well with an expression strictly valid for perfect gas flows only. The high- and low-enthalpy compression corner flows have upstream influence and plateau pressure behavior similar to perfect gas flow. That is, real gas effects for the present flows appear to be negligible. This is consistent with the essentially chemically frozen viscous and inviscid flow upstream of the interaction.
The optimization of bus rapid transit route based on an improved particle swarm optimization

ABSTRACT We present a method for identifying bus rapid transit routes optimized for serving the greatest number of passengers. Because formulating a relevant model is a complex problem, a particle swarm optimization scheme that improves on previous such approaches is applied. The optimization contains some more advanced strategies, such as dual population, self-adaptive inertia weight, and crossover operation, to enhance the abilities of the algorithm. Data collected from Dalian City, China, are then used for examining the proposed model and the optimization. Computational results demonstrate that the model is feasible and the improved particle swarm optimization is an effective method for optimizing bus rapid transit routes.
Validating Constructs of Web Usage in Education and Learning

E-learning has become an ever-increasing delivery method in school and workplace. Many Web sites provide Internet users with lots of information and resources on study, research, and career development in workplace. First, this study aimed at presenting a process of validating instruments to measure perception of using the Web for learning. Secondly, this paper attempted to find out a list of critical constructs that university students recognize when they access Web sites to get some resources on their fields of study. This study also suggested the features of those constructs. This paper would help improve our understanding of Web usage for schoolwork and research. This result of the paper will facilitate further understanding of constructs associated with Web usage in other areas, thereby enabling researchers, practitioners, and policy makers to draw much attention to e-learning.
Sentiment Analysis Through Text Mining-A Review

Emotions are an important part of human life. It creates direct effect when the gestures of people are visible to the audience, but it is unclear when only texts are used rather than used in combination with gestures and facial expression. As the wide use of internet and mobile, text data has become the main source of communication in several social networking sites. One way of making such textual based interaction more interactive is to make a system that can recognize the sentimental purpose present behind the text. Now a days several researches are ongoing to make computer and human interaction as effective as it can detect the sentimental state of a person. This paper focuses on studying different work done in the area of sentiment analysis through text mining and provides a review that covers the best method and techniques used based on the previous experimental result.
System Identification and Control Design of an Unmanned Helicopter Using a PI-MPC Controller

This paper presents the study of the system identification and controller design for an unmanned helicopter using the integration of Proportional Integral (PI) and Model Predictive Control (MPC). Since the dynamic model of a helicopter is highly nonlinear and contains many uncertainties, the system identification and control are challenging and complicated. To accelerate the development, the autonomous flight and trajectory tracking of an unmanned helicopter, this study first setup a software simulation environment of the helicopter using the X-Plane flight simulator. The prediction-error minimization (PEM) and subspace methods were applied in this study to identify the dynamic model of the interested flight trim conditions. The lateral, longitudinal, heave, and yaw dynamic models were predicted by using the System Identification Toolbox of MATLAB. To enhance the stability and eliminate the uncertainty of the control system, the Integration of Proportional Integral (PI) and MPC were introduced. The developed control system was then applied to perform the trajectory tracking of a helicopter. The simulation results show that the performance of the proposed approach can track the desired trajectory.