nils-herrmann/clean_scirepeval huggingface dataset:
The Role of Global Actors in the Liberalization of Indonesian Economy through its Financial Institutions

In contrast, the political ideology governing on Indonesia seemed to be isolated from any required economic reform. This paper investigates the dynamic role of global actors after liberalization of Indonesian Economy. However, these global actors such as World Bank, International Monetary Fund (IMF) World Trade Organization (WTO) a group of twenty largest economies called as G 20 and Association of Southeast Asian Nations (ASEAN) play an important role in developed and under developed countries of the world. The international market exercises its rules to regulate any new and existing business including the international business market that is free to enter in this globalization era, with a campaign that aims to benefit all people as the effect trickles down. However, it has been questioned why Indonesia extended this commitment, despite the country still suffering from its own foreign loans that floated up to USD 251.2 billion at the end of 2012.
Peer Reviewed Research and the IEP

This article examines a case out of the U.S. Court of Appeals for the Third Circuit: Ridley School District v. M.R and J.R. ex rel. E.R. (2012) The case is the first circuit court case in which the Individuals with Disabilities Education Improvement Act requirement that special education services be based on peer reviewed research (PRR) was at issue. Recommendations for teachers and administrators working to meet the PRR requirement when developing intervention plans for students with disabilities are discussed.
Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural Networks
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence

Deep convolutional networks have proven to be very successful in learning task specific features that allow for unprecedented performance on various computer vision tasks. Training of such networks follows mostly the supervised learning paradigm, where sufficiently many input output pairs are required for training. Acquisition of large training sets is one of the key challenges, when approaching a new task. In this paper, we aim for generic feature learning and present an approach for training a convolutional network using only unlabeled data. To this end, we train the network to discriminate between a set of surrogate classes. Each surrogate class is formed by applying a variety of transformations to a randomly sampled `seed' image patch. In contrast to supervised network training, the resulting feature representation is not class specific. It rather provides robustness to the transformations that have been applied during training. This generic feature representation allows for classification results that outperform the state of the art for unsupervised learning on several popular datasets (STL 10, CIFAR 10, Caltech 101, Caltech 256) While features learned with our approach cannot compete with class specific features from supervised training on a classification task, we show that they are advantageous on geometric matching problems, where they also outperform the SIFT descriptor.
Exploiting generic multi level convolutional neural networks for scene understanding
Venue: 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV)

In this paper, we introduce the application of generic multi level Convolutional Neural Networks (CNN) approach into the scene understanding or image parsing task. Given an input image, first, a set of similar images from the training set are retrieved based on global level CNN feature matching similarities. Then, the input test image and the similar images are overseg mented into superpixels. Next, the class of each test image's superpixel is initialized by the majority vote of the fc nearest neighbor superpixels based on regional level CNN features and hand crafted features matching. The initial superpixel parsing is later combined with per exemplar sliding windows to roughly form the pixel labels. Eventually, the final labels are further refined by the contextual smoothing. Extensive experiments on different challenging datasets demonstrate the potentials of the proposed method.
Stationary dynamic texture synthesis using convolutional neural networks
Venue: 2016 IEEE 13th International Conference on Signal Processing (ICSP)

In this paper, we utilize deep networks to study the problem of modeling and synthesizing stationary dynamic textures that exhibit both spatial and temporal regularity. Our work is a generalization of the generative static texture model based on convolutional neural networks (CNNs) We extend the static texture synthesis method using CNNs to the dynamical setting by adding the temporal dimension, where the multiple layers of spatial temporal filters come from off the shelf deep 3 dimensional convolutional networks (3D ConvNets) trained in a discriminative fashion. Dynamic textures generation is formulated as an iterative optimization procedure which imposes the correlation statistics derived from 3D ConvNets of the input exemplar on the synthesized one. Synthesis experiments on various video texture exemplars show that such generative method can synthesize realistic dynamic textures of good visual quality.
Technology in Language Use, Language Teaching, and Language Learning.

This article offers a capacious view of technology to suggest broad principles relating technology and language use, language teaching, and language learning. The first part of the article considers some of the ways that technological media influence contexts and forms of expression and communication. In the second part, a set of heuristic questions is proposed to help guide language teachers and researchers in determining how to incorporate technology into their teaching practice or research agenda and evaluate its suitability and impact. These questions are based primarily on the goal of helping learners to pay critical attention to the culturally encoded connections among forms, contexts, meanings, and ideologies that they will encounter and produce in different mediums, both traditional and new.
Learners' Perceptions of the Use of Mobile Technology in a Task Based Language Teaching Experience

This research explored perceptions of learners studying English in private language schools regarding the use of mobile technology to support language learning. Learners were first exposed to both a mobile assisted and a mobile unassisted language learning experience, and then asked to express their thoughts on the incorporation of mobile devices into the language classroom. The mobile assisted tasks involved learners posting a review online based on a real past experience, as well as using web search engines to gather enough information to plan a hypothetical trip. Findings revealed overall positive attitudes amongst the students surveyed. Arguments in favour of the incorporation of mobile technology in the language classroom included: the possibility of having access to a range of materials superior in both quality and quantity when using mobile devices to access the Internet, among others. However, a significant amount of scepticism towards Mobile Assisted Language Learning emerged. Arguments against suggested that the format of presentation, rather than the type of task, seemed to constitute a motivational factor that played a psychologically significant role to some of the learners.
Methodologies of knowledge discovery from data and data mining methods in mechanical engineering

9 September 2016  1 December 2016 The paper contains a review of methodologies of a process of knowledge discovery from data and methods of data exploration (Data Mining) which are the most frequently used in mechanical engineering. The methodologies contain various scenarios of data exploring, while DM methods are used in their scope. The paper shows premises for use of DM methods in industry, as well as their advantages and disadvantages. Development of methodologies of knowledge discovery from data is also presented, along with a classification of the most widespread Data Mining methods, divided by type of realized tasks. The paper is summarized by presentation of selected Data Mining applications in mechanical engineering.
The Teacher Efficacy for Inclusive Practices (TEIP) Scale: Dimensionality and Factor Structure.

The Teacher Efficacy for Inclusive Practices (TEIP) scale is designed to measure teacher self efficacy to teach in inclusive classrooms. The original study identified three scale factors: efficacy in using inclusive instruction (EII) efficacy in collaboration (EC) and efficacy in managing behavior (EMB) (Sharma et al. 2012) The purpose of our study was to examine the TEIP scale for dimensionality and to cross validate its factor structure for pre service teachers in the context of early childhood education. A bifactor model fit to the data revealed that the TEIP scale is essentially unidimensional, that is, there is one dominant latent factor and the originally found three scale factors (EII, EC, and EMB) represent specific aspects of the general factor of teacher self efficacy to teach in inclusive classrooms. Along with providing validation evidence, these findings have important implications for the scoring on the TEIP scale using classical test analysis or unidimensional item response theory models.
Unified Point of Interest Recommendation with Temporal Interval Assessment
Venue: KDD

Point of interest (POI) recommendation, which helps mobile users explore new places, has become an important location based service. Existing approaches for POI recommendation have been mainly focused on exploiting the information about user preferences, social influence, and geographical influence. However, these approaches cannot handle the scenario where users are expecting to have POI recommendation for a specific time period. To this end, in this paper, we propose a unified recommender system, named the 'Where and When to gO' (WWO) recommender system, to integrate the user interests and their evolving sequential preferences with temporal interval assessment. As a result, the WWO system can make recommendations dynamically for a specific time period and the traditional POI recommender system can be treated as the special case of the WWO system by setting this time period long enough. Specifically, to quantify users' sequential preferences, we consider the distributions of the temporal intervals between dependent POIs in the historical check in sequences. Then, to estimate the distributions with only sparse observations, we develop the low rank graph construction model, which identifies a set of bi weighted graph bases so as to learn the static user preferences and the dynamic sequential preferences in a coherent way. Finally, we evaluate the proposed approach using real world data sets from several location based social networks (LBSNs) The experimental results show that our method outperforms the state of the art approaches for POI recommendation in terms of various metrics, such as F measure and NDCG, with a significant margin.
Evaluation of Physiological Control Systems for Rotary Left Ventricular Assist Devices: An In Vitro Study
Venue: Annals of Biomedical Engineering

Rotary left ventricular assist devices (LVADs) show weaker response to preload and greater response to afterload than the native heart. This may lead to ventricular suction or pulmonary congestion, which can be deleterious to the patient's recovery. A physiological control system which optimizes responsiveness of LVADs may reduce adverse events. This study compared eight physiological control systems for LVAD support against constant speed mode. Pulmonary (PVR) and systemic (SVR) vascular resistance changes, a passive postural change and exercise were simulated in a mock circulation loop to evaluate the controller's ability to prevent suction and congestion and to increase exercise capacity. Three active and one passive control systems prevented ventricular suction at high PVR (500 dyne s cm 5) and low SVR (600 dyne s cm 5) by decreasing LVAD speed (by 200 515 rpm) and by increasing LVAD inflow cannula resistance (up to 1000 dyne s cm 5) respectively. These controllers increased LVAD preload sensitivity (to 0.196 2.415 L min 1 mmHg 1) compared to the other control systems and constant speed mode (0.039 0.069 L min 1 mmHg 1) The same three active controllers increased pump speed (600 800 rpm) and thus LVAD flow by 4.5 L min 1 during exercise which increased exercise capacity. Physiological control systems that prevent adverse events and/or increase exercise capacity may help improve LVAD patient conditions.
Feature extraction from handwritten documents for personality analysis
Venue: 2016 International Conference on Computer, Electrical Communication Engineering (ICCECE)

Handwriting can be used to predict or analyze a person's behavioral or personality traits. Characteristics of a handwriting are studied for that. In this work various characteristics like size, spacing, slant, skew, pressure, etc are studied. Since signature reflects important characteristics of human being, we analyze them also. As our objective is to build an automated or computerized handwriting analysis system, we discuss the features from algorithmic view points. For experimental purpose, various handwriting of different writers are collected. Identical as well as different texts is used for that. Implementing these algorithms on the data sets, we obtain experimental results which are given here.
Circadian regulation of sunflower heliotropism, floral orientation, and pollinator visits
Venue: Science

Searching for the Sun The growth of immature sunflower plants tracks the Sun's movement. The young plants lean westward as the day progresses but reorient to the east each night. As the flowers mature and open, they settle into a stable east facing orientation. Atamian et al. show how circadian rhythms regulate the east west elongation of cells in the young plants' stems (see the Perspective by Briggs) They show that eastward oriented flowers are warmer than westward oriented flowers, and this warmth attracts pollinators. Auxin signaling pathways in the stem coordinate to fix the eastward orientation of the mature plant. Science, this issue p. 587; see also p. 541 Sun tracking when young, east facing when mature, warmer sunflowers attract more pollinators. Young sunflower plants track the Sun from east to west during the day and then reorient during the night to face east in anticipation of dawn. In contrast, mature plants cease movement with their flower heads facing east. We show that circadian regulation of directional growth pathways accounts for both phenomena and leads to increased vegetative biomass and enhanced pollinator visits to flowers. Solar tracking movements are driven by antiphasic patterns of elongation on the east and west sides of the stem. Genes implicated in control of phototropic growth, but not clock genes, are differentially expressed on the opposite sides of solar tracking stems. Thus, interactions between environmental response pathways and the internal circadian oscillator coordinate physiological processes with predictable changes in the environment to influence growth and reproduction.
Improvement of relative accreditation methods based on data mining and artificial intelligence for higher education
Venue: 2016 15th International Conference on Information Technology Based Higher Education and Training (ITHET)

Expansion of higher education has a great significance for development of the country and this case should not be ignored. Quality evaluation at higher education is also an important issue. This process takes shape with prospects and requests placed on higher education institutions. Especially some fields such as engineering began to progress teaching and learning and to set apart resources for quality education curricula. Accreditation concept in higher education is seen as defining of quality of education and it has to be under constantly modify. With expansion of higher education, accreditation system has become necessary. Effective implementation of accreditation purposes will provision proper functioning of the education system. In this study, an IT based method is proposed which simplifies application of the accreditation system to departures. High efficiency and more accurate results can be obtained by being given results obtained from proposed method as feedback. There are determined whether success accreditation criteria by examining each of accreditation criteria with knowledge extracting and processing techniques.
A Study on Digital Media Technology Courses Teaching Based on Flipped Classroom

This essay, beginning with the problems existed in digital media technology course, introduces the flipped classroom, and then establishes the digital media technology course teaching mode based on this theory. And finally, an empirical research of flipped classroom teaching based on "web page design and production" is conducted. And according to the study, flipped classroom is appropriate for digital media technology course, because it helps inspire students' enthusiasm and initiative, train their practice ability in computer media technology. The flipped classroom provides a new method for traditional teaching reform.
New concepts of play and the problem of technology, digital media and popular culture integration with play based learning in early childhood education

Technology, digital media and popular culture form an important aspect of young children's life worlds in contemporary post industrial societies. A problem for early childhood educators is how to most effectively integrate these aspects of children's life worlds into the provision of play based learning. Traditionally, research has considered barriers to teacher uptake of technologies in the early years, or teacher beliefs and attitudes about using technologies with young children. An alternative perspective focuses on children's play as the foundation for early childhood curriculum provision and argues that what is needed instead are 'new' concepts of play more appropriate for explaining children's contemporary play experiences in post industrial societies. This article examines the influence of a new concept of play called 'web mapping' on teachers' curriculum practices in early childhood education, and finds that, according to Vygotsky's ideas about explicit and implicit mediation, new concepts of play are likely to provide a fruitful avenue for addressing the 'problem' of technology, digital media and popular culture integration in early childhood education.
Biting the Cow's Tongue: Securitization and Capacity Building in the South China Sea

The South China Sea (SCS) territorial disputes have become one of the most significant security challenges in the East Asian Supercomplex (EAS) Described in Buzan and Waever's classic study as a Great Power Bipolar Supercomplex defined by China and Japan, the emergence and actions of South Korea and Indonesia as regional powers have rendered the EAS multipolar and unusually volatile. As the hierarchy in the EAS transforms into a multipolar one, the securitization of China has allowed Japan and South Korea to facilitate the capacity building efforts of Southeast Asian states at the expense of China. As a result, the littoral states surrounding the SCS have taken advantage of this strategic competition in order to advance their own interests.
Historical Geographic Information Systems and Social Science History
Venue: Social Science History

The interdisciplinary field of historical geographic information systems (HGIS) took root and flourished at the Social Science History Association (SSHA) in the late 1990s and early 2000s. This essay first recounts the growth of HGIS at SSHA and beyond. It then considers challenges that GIS continues to pose for historians and other scholars, such as the unfamiliarity of its conceptual framework and the time and expense often involved in building HGIS databases. The bare bones visual culture of Social Science History may inhibit submissions by HGIS scholars, whose work typically includes color maps. Yet the enduring methodological and interdisciplinary interests of SSHA members provide a strong basis for continuing involvement by historians who use GIS. The essay closes with new directions in HGIS scholarship, including study of empirical uncertainty, historical gazetteers, textual analysis linked to GIS mapping, and comparison of topology and topography.
Effect of Shin'iseihaito on murine allergic reaction induced by nasal sensitization
Venue: Journal of traditional and complementary medicine

Shin'iseihaito (Magnolia Flower Lung Clearing Decoction; Xin Yi Qing Fei Tang xin yi qing fei tang) a formula of traditional Japanese kampo medicine (Ri Ben Han Yi ri ben han yi) and traditional Chinese medicine (TCM; Zhong Yi zhong yi) has been used for the treatment of chronic sinusitis. The objective of this study was to evaluate the anti allergic effect of shin'iseihaito on murine allergic reaction induced by nasal sensitization using ovalbumin (OVA) as an antigen. Extract of shin'iseihaito (SSHT) could reduce the eosinophil, serum IgE and interleukin (IL) 4 levels, while increased the interferon (IFN) g levels in allergic mouse. Furthermore, allergic murine serum treated with SSHT could not activate passive cutaneous anaphylaxis (PCA) reaction in murine model. Thus, our study showed that SSHT may possess anti allergic activity. We suggested that SSHT may contribute to inhibit the exacerbation of allergic reaction induced by nasal sensitization.
Towards fake sources for source location privacy in wireless sensor networks with multiple sources
Venue: 2016 IEEE International Conference on Communication Systems (ICCS)

Wireless sensor networks (WSNs) are regularly used in asset monitoring applications, where the location of an asset or assets must be kept private. Providing location privacy for such an asset is tantamount to protecting the location of a source node from an attacker who is attempting to locate it. Although no solution exists to provide source location privacy over an extended period, it has been shown that attackers can be sufficiently inhibited by prominent approaches that use either a phantom node, via which protocol messages are routed, or nodes assigned to be fake sources, each of which then broadcast fake messages. However, the applicability of fake source approaches to networks where location privacy must be maintained for multiple sources has yet to be considered. This paper addresses this issue by analysing a representative fake source algorithm in the context of multiple sources, presenting simulation results that demonstrate the shortcomings of the approach and identifying the underlying limitations to pave the way for the development of algorithms capable of accounting for multiple sources.
Cyber Security Situational Awareness
Venue: 2016 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)

Situational awareness in the context of cyber security has been well recognized. In a time cyber attacks getting increasingly sophisticated and making potentially disruptive impacts, it becomes apparent that a holistic approach is fundamentally needed to handling security data effectively. Cyber Security Situational Awareness (CSSA) emerges timely. In this paper, after revisiting the concept of CSSA, we have aligned the process of CSSA with security data lifecycle and analyzed the requirements of CSSA. Then, we have put forward a multi level analysis framework for CSSA.