Miracle-dz/UniFAR-FTUs huggingface dataset:
Video (GIF) Sentiment Analysis using Large-Scale Mid-Level Ontology

With faster connection speed, Internet users are now making social network a huge reservoir of texts, images and video clips (GIF). Sentiment analysis for such online platform can be used to predict political elections, evaluates economic indicators and so on. However, GIF sentiment analysis is quite challenging, not only because it hinges on spatio-temporal visual contentabstraction, but also for the relationship between such abstraction and final sentiment remains unknown.In this paper, we dedicated to find out such relationship.We proposed a SentiPairSequence basedspatiotemporal visual sentiment ontology, which forms the midlevel representations for GIFsentiment. The establishment process of SentiPair contains two steps. First, we construct the Synset Forest to define the semantic tree structure of visual sentiment label elements. Then, through theSynset Forest, we organically select and combine sentiment label elements to form a mid-level visual sentiment representation. Our experiments indicate that SentiPair outperforms other competing mid-level attributes. Using SentiPair, our analysis frameworkcan achieve satisfying prediction accuracy (72.6%). We also opened ourdataset (GSO-2015) to the research community. GSO-2015 contains more than 6,000 manually annotated GIFs out of more than 40,000 candidates. Each is labeled with both sentiment and SentiPair Sequence.
APPROVED FOR PUBLIC RELEASE

This Supporting Document analyzes a proposal for reducing the under-packager volume t o decrease the amount of f i s s i l e material that could accumulate there. The analysis shows t h a t restricting the under packager volume t o no more than 4080 in3 will assure t h a t i f accumulated f i s s i l e material beneath the packager is added t o the worst-case mass of f i s s i l e material i n the discharge chute, a keff of 0.98 will not be exceeded.
Efficient Entropy Estimation for Stationary Time Series

Entropy estimation, due in part to its connection with mutual information, has seen considerable use in the study of time series data including causality detection and information flow. In many cases, the entropy is estimated using $k$-nearest neighbor (Kozachenko-Leonenko) based methods. However, analytic results on this estimator are limited to independent data. In the article, we show rigorous bounds on the rate of decay of the bias in the number of samples, $N$, assuming they are drawn from a stationary process which satisfies a suitable mixing condition. Numerical examples are presented which demonstrate the efficiency of the estimator when applied to a Markov process with stationary Gaussian density. These results support the asymptotic rates derived in the theoretical work.
Cannabinoid hyperemesis syndrome: a case report in Mexico

Antecedentes. En 2004 se registro el primer reporte de caso del Sindrome de hiperemesis cannabiniode (SHC). Anos mas tarde, otros grupos de investigacion fueron complementando su descripcion, anadiendo que este se asociaba a comportamientos como: consumo cronico y abusivo de cannabis, episodios agudos de nauseas, vomito incontrolable, dolor abdominal, banos compulsivos de agua caliente, que remitian tras el cese del consumo de cannabis. Objetivo. Presentar una breve revision del SHC y presentar el primer caso documentado en Mexico. Metodo. Mediante una busqueda sistematizada en PUBMED entre 2004 y 2016, se integro una breve revision del SHC. Para el segundo objetivo, se utilizo la guia de reporte de casos CARE para registrar y manejar a un paciente con SHC en un hospital general de alta especialidad. Resultados. Hasta diciembre de 2016 se habia registrado un total de 89 casos en todo el mundo, aunque ninguno en America Latina. Discusion y conclusiones. A pesar de los casos reportados en la literatura cientifica, aun no existe un consenso de expertos mas completo sobre la etiologia, el diagnostico y el tratamiento del SHC. Asimismo la ausencia de un algoritmo integral y estandarizado aumenta la probabilidad de mala praxis, ademas de incrementar el deterioro biopsicosocial del paciente e incrementar el costo de la atencion.
THE ROBUST DESIGN FOR CAPTURE–RECAPTURE STUDIES: ANALYSIS USING PROGRAM MARK

Collecting capture–recapture data under Pollock’s robust design provides an additional source of information on capture probability that can be used to provide less biased and more efficient estimates of population dynamics parameters. In addition, it can be used to estimate the probability of being available for capture, which in some cases (e.g., breeding proportion) has ecological significance. This phenomenon can be modeled as a completely random process, Markovian, or with temporary trap dependence. Analysis of this type of data is an option in program MARK. By using MARK, the relationship between parameters and covariates can be modeled, and various approaches to goodness of fit, model selection, and model averaging can be implemented.
Improving Face Recognition by Online Image Alignment

Face recognition accuracy is affected by many factors. This paper studies one of the factors, and provides a reliable image alignment for face recognition. For this purpose, a performance metric is extracted from an analysis of face recognition similarity scores. The metric varies with face alignment, and has a relationship with the actual recognition accuracy. Our method adjusts face alignment online by selecting an alignment candidate corresponding to the largest performance metric. The experimental results show that the presented method can improve the accuracy and robustness of current face recognition systems
Different Brain Connectivity between Responders and Nonresponders to Dual-Mode Noninvasive Brain Stimulation over Bilateral Primary Motor Cortices in Stroke Patients

Noninvasive brain stimulation (NBS), such as repetitive transcranial magnetic stimulation (rTMS) or transcranial direct current stimulation (tDCS), has been used in stroke patients with motor impairment. NBS can help recovery from brain damage by modulating cortical excitability. However, the efficacy of NBS varies among individuals. To obtain insights of responsiveness to the efficacy of NBS, we investigated characteristic changes of the motor network in responders and nonresponders of NBS over the primary motor cortex (M1). A total of 21 patients with subacute stroke (13 males, mean age 59.6 ± 11.5 years) received NBS in the same manner: 1 Hz rTMS on the contralesional M1 and anodal tDCS on the ipsilesional M1. Participants were classified into responders and nonresponders based on the functional improvement of the affected upper extremity after applying NBS. Twelve age-matched healthy controls (8 males, mean age 56.1 ± 14.3 years) were also recruited. Motor networks were constructed using resting-state functional magnetic resonance imaging. M1 intrahemispheric connectivity, interhemispheric connectivity, and network efficiency were measured to investigate differences in network characteristics between groups. The motor network characteristics were found to differ between both groups. Specifically, M1 intrahemispheric connectivity in responders showed a noticeable imbalance between affected and unaffected hemispheres, which was markedly restored after NBS. The responders also showed greater interhemispheric connectivity and higher efficiency of the motor network than the nonresponders. These results may provide insight on patient-specific NBS treatment based on the brain network characteristics in neurorehabilitation of patients with stroke. This trial is registered with trial registration number NCT03390192.
Issues in the Computer-based Assessment of Collaborative Problem Solving

Abstract Collaborative problem solving skills are considered necessary skills for success in today's world of work and school. Collaborative learning refers to learning environments in which small groups of people work together to achieve a common goal, and problem solving is using cognitive processing to find a solution to a problem. Thus, collaborative problem solving is defined as problem solving activities that involve interactions among a group of individuals. This paper will address several key issues (e.g. theory and measurement of collaborative problem solving and issues in measuring problem solving processes). We rely on computerisation of the administration, scoring and reporting of collaborative problem solving skills, thus potentially increasing reliability and validity.
Seismic Behavior of Two-Story Shear Wall with Concrete Filled Steel Tube Columns

Abstract—To investigate the seismic behavior of concrete filled steel tube columns precast shear walls, a study of 3 specimens failure cases were conducted in Quasi-static loading. The shear walls were designed in 1/3 scaled, and grouted sleeve connection detail were applied in steel tubular joints. The failure pattern, the hysteretic behavior, ductility and the energy dissipating capacity were discussed under different axial compression ratios. The results show: The failure mode is similar that steel tubular joints brittle failure occur. The hysteretic curve plumpness and energy dissipating capacities are strong. The ductility coefficient range from 1.6~2.5 and the deformation performance decreases with the increase of axial compression ratios. The yield strength in substituted for the ultimate strength in steel tubular joints design.
Digital inclusion projects in developing countries: Processes of institutionalization

This article concerns digital inclusion projects in developing countries and, in particular, focuses on processes of institutionalization of such projects. Three case studies are described and analysed. The first is the Akshaya telecenter project in the state of Kerala in India. The second is a community-based ICT project in a town in a rural area of South Africa. The third is the efforts of various agencies on telecenter projects in the mega-city of São Paulo in Brazil. The cases are analysed through a simple theoretical schema derived from institutional theory. The analyses are used to derive four key processes of institutionalization, which are argued to be of relevance to all digital inclusion projects: getting symbolic acceptance by the community, stimulating valuable social activity in relevant social groups, generating linkage to viable revenue streams, and enrolling government support. The article concludes with some theoretical, methodological, and policy implications. © 2009 Wiley Periodicals, Inc.
Review of Optical MEMS Devices

Microelectromechanical systems or MEMS technology is a technology that in its most general form can be defined as miniaturized mechanical and electro-mechanical elements (i.e., devices and structures) that are made using the techniques of microfabrication. The critical physical dimensions of MEMS devices can vary from well below one micron on the lower end of the dimensional spectrum, all the way to several millimeters. Likewise, the types of MEMS devices can vary from relatively simple structures having no moving elements, to extremely complex electromechanical systems with multiple moving elements under the control of integrated microelectronics. Optics/photonics is one of these research fields impacted by MEMS techniques. Generally, micro-optical elements with sizes ranging from a few microns to a few millimeters belong to the category of optical MEMS. They are inherently suited for cost effective wafer scale manufacturing as the processes are derived from the semiconductor industry. Due to the ongoing improvement of fabrication technologies, MEMS technology has become feasible and steadily attracted attention in the fields of optics and photonics. This article summarizes the state of the art of Optical MEMS technologies and applications.
Programmable Logic Controllers in Process Automation

The energy flow modelling in automotive propulsion systems aimed to provide base data for the choice of the differential parameters in consideration of the impact on the lateral dynamics of the vehicle is presented in the paper. The characteristics of the differential in the torque transmission chain are concerned. Description of the characteristics and operational conditions of the limited slip differential gear train is given. The virtual differential (algorithm of energy flow) has been provided. The topics of this paper have been developed in co-operation between Chalmers University of Technology, Göteborg, Sweden, Tallinn Technical University and Estonian Agricultural University.
Learning to Cope With Diversity in Music Retrieval

The approach presented here makes productive use of the multidimensionality of music retrieval. It exploits heterogeneous representations of music objects into a self-adapting retrieval system. The different perspectives of users can be expressed by relevance feedback and serve as the direction for a learning process which ultimately leads to an optimal solution for a user within a certain context. The paper explores the diversity within music retrieval stemming from an abundance of approaches for representing musical objects as well as methods for searching for similarity. As a result, the system designer is usually confronted with a large number of arbitrary decisions. These challenges are discussed within the M-MIMOR framework, which provides an appropriate solution. A fusion with linear combination guarantees that every perspective is integrated. The weight and therefore the strength of one perspective is reflected by the weight of the representation scheme or matching algorithm into the fusion. These weights are adapted according to their success in previous retrieval tasks.
MultiLing 2017 MultiLing 2017 Workshop on Summarization and Summary Evaluation Across Source Types and Genres

In this brief report we present an overview of the MultiLing 2017 effort and workshop, as implemented within EACL 2017. MultiLing is a community-driven initiative that pushes the state-of-the-art in Automatic Summarization by providing data sets and fostering further research and development of summarization systems. This year the scope of the workshop was widened, bringing together researchers that work on summarization across sources, languages and genres. We summarize the main tasks planned and implemented this year, also providing insights on next steps.
Influential Factors in the Adoption and Use of E-Business and E-Commerce Information Technology (EEIT) by Small & Medium Businesses

This study addresses factors commonly examined in the research concerning adoption and use of e-business and e-commerce information technology EEIT by small and medium enterprises SMEs. The primary objectives are to determine: 1 what barriers and incentives SMEs perceive in adopting EEIT; 2 how the level of adoption of EEIT influences perceptions of incentives and barriers; and 3 whether results vary depending on demographic characteristics of size, geographic market scope, or industry sector. This paper also examines how homogenous SMEs' perceptions are in their consideration of EEIT adoption factors. Data were collected from 290 U.S. SMEs. The findings revealed that among 25 factors identified in the research literature as incentives or barriers to adoption of EEIT by SMEs, only 16 factors were significant in the population studied, 12 as incentives and four as barriers. Factors were perceived differently as incentives or barriers by adopters, intended adopters, and non-adopters of EEIT. A number of differences were found among SMEs based on demographic characteristics, particularly size and industry-sector.
ACTIVE LONGITUDES AND OCCURRENCE OF CORONAL MASS EJECTIONS

The spatial inhomogeneity of the distribution of coronal mass ejection (CME) occurrences in the solar atmosphere could provide a tool to estimate the longitudinal position of the most probable CME-capable active regions in the Sun. The anomaly in the longitudinal distribution of active regions themselves is often referred to as active longitude (AL). In order to reveal the connection between the AL and CME spatial occurrences, here we investigate the morphological properties of active regions. The ﬁrst morphological property studied is the separateness parameter, which is able to characterise the probability of the occurrence of an energetic event, such as solar ﬂare or CME. The second morphological property is the sunspot tilt angle. The tilt angle of sunspot groups allows us to estimate the helicity of active regions. The increased helicity leads to a more complex built-up of the magnetic structure and also can cause CME eruption. We found that the most complex active regions appear near to the AL and the AL itself is associated with the most tilted active regions. Therefore, the number of CME occurrences is higher within the AL. The origin of the fast CMEs is also found to be associated with this region. We concluded that the source of the most probably CME-capable active regions is at
A Comparative Analysis of Dimensionality Reduction Techniques

How can we represent a data residing in high dimensional space onto a low dimensional space without the loss of important information? In image processing, pattern recognition, machine learning and in many other fields like social science, statistics, signal processing etc, the measured data set often resides in a very high dimensional space which leads to a number of computational and representational problems (also known as the curse of dimensionality). This paper present Dimensionality Reduction as a means to counter the curse of Dimensionality by finding a compact but meaningful representation of the high dimensional data. We discuss a range of dimensionality reduction techniques on the basis of their underlying concept. The methods of PCA, FA, ICA, MDS, ISOMAP, LLE and GA based methods have been discussed in this paper. We also comparatively analyze each of them based on their merit, demerits and the areas where they have been used or best used for. We run some experiments on linear projection based methods of PCA, Factor Analysis and ICA and present the results of our experiment.
Building 3 D stochastic exploration models from borehole geophysical and petrophysical data : A Case Study

We demonstrate how geostatistical tools can be applied to a petrophysical database for constructing a 3D exploration model that honours the statistics of the physical properties observed from borehole logs and cores. The framework for using geostatistics in this study is primarily supported by the presence of a relatively dense spatial sampling within the study area of various borehole information which is otherwise absent or sparsely available in most exploration projects. Sequential Gaussian simulation (SGS) based on cokriging can be useful to constrain the 3D exploration model by incorporating the correlation between existing information of various categories based on a preestablished hierarchy. We show an application of SGS where the derived stochastic density models are used for base metal exploration in the Nash Creek area, New Brunswick, Canada. The proposed strategy for building 3D heterogeneous exploration models honours the information at all available borehole locations. Such heterogeneous models are useful in assessing the impact of heterogeneity on a variety of geophysical imaging methods, such as those applicable to near surface exploration problems in groundwater, environmental and geotechnical investigations. In this work, the statistical analysis of the rock densities and geochemical data suggests that the disseminated nature of the sulfide rich zones may undermine the effectiveness of geophysical imaging techniques such as seismic and gravity.
Preserving Integrity in Remote File Location and Retrieval

We present a service for locating and retrieving les from an untrusted network such that the integrity of the retrieved les can be veriied. This service enables groups of people in geographically remote locations to share les using an untrusted network. For example, distribution of an organization's software to all the or-ganization's sites can be accomplished using this service. Distribution of les in an untrusted network is complicated by two issues: (1) location of les and (2) veriication of le integrity. ftp and Worldwide Web (WWW) services require some user intervention to locate a le, so they cannot be embedded in automated systems. Distributed systems have mechanisms for automated le location and retrieval, but they require trust in all system principals and do not provide an appropriate balance between availability of les and retrieval cost for our applications. Veriication of the integrity of a le retrieved from an untrusted network is necessary because the le is subject to malicious modiication attacks. Our service provides the capability to automatically locate, retrieve, and verify les speciied by a client using a single trusted principal. We demonstrate our service by building a system shell that automatically downloads remote software when needed.
ScholarWorks@BGSU ScholarWorks@BGSU

High-throughput phenotyping systems provide abundant data for statistical analysis through plant imaging. Before usable data can be obtained, image processing must take place. In this study, we used supervised learning methods to segment plants from the background in such images and compared them with commonly used thresholding methods. Because obtaining accurate training data is a major obstacle to using supervised learning methods for segmentation, a novel approach to producing accurate labels was developed. We demonstrated that, with careful selection of training data through such an approach, supervised learning methods, and neural networks in particular, can outperform thresholding methods at segmentation. High throughput plant phenotyping is a broad umbrella. The field includes researchers working in the fields of plant biology, engineering, computer science, and statistics. A common goal to make the collection of plant trait data as efficient and scalable as the collection of plant genetic data unites the
Compositional refinement of interactive systems

We introduce a method to describe systems and their components by functional specification techniques. We define notions of interface and interaction refinement for interactive systems and their components. These notions of refinement allow us to change both the syntactic (the number of channels and sorts of messages at the channels) and the semantic interface (causality flow between messages and interaction granularity) of an interactive system component. We prove that these notions of refinement are compositional with respect to sequential and parallel composition of system components, communication feedback and recursive declarations of system components. According to these proofs, refinements of networks can be accomplished in a modular way by refining their compponents. We generalize the notions of refinement to refining contexts. Finally, full abstraction for specifications is defined, and compositionality with respect to this abstraction is shown, too.