Miracle-dz/UniFAR-FTUs huggingface dataset:
An Application of Hierarchical Linear Modeling to the Estimation of School and Teacher Effect.

AUTHOR Webster, William J.; Mendro, Robert L. ; Orsak, Timothy H. ; Weerasinghe, Dash TITLE An Application of Hierarchical Linear Modeling to the Estimation of School and Teacher Effect. PUB DATE 1998-04-00 NOTE 33p. ; Paper presented at the Annual Meeting of the American Educational Research Association (San Diego, CA, April 13-17, 1998). PUB TYPE Information Analyses (070) Reports Descriptive (141) Speeches/Meeting Papers (150) EDRS PRICE MF01/PCO2 Plus Postage. DESCRIPTORS Elementary Secondary Education; *Estimation (Mathematics); Mathematical Models; *School Effectiveness; *Teacher Effectiveness IDENTIFIERS *Criterion Variables; *Hierarchical Linear Modeling
Farmers' involvement in collective experimental designs in a French region, Rhône-Alpes. How do they contribute to farmers' learning and facilitate the agroecological transition?

Agroecology is a promising concept for designing and managing more sustainable agrosystems, but it deeply questions how farmers learn to implement agroecological practices. The building of generic knowledge by scientists is quite insufficient and has to be completed with learning and innovation dynamics on farms. We assume that experimenting agroecological practices on farms is a way for farmers to simultaneously implement and assess new cropping and livestock farming systems, and that the involvement of peers or supporting actors, either scientists or extensionists, could help the experimenting process and favor agroecological transitions. Based on a French participatory research project, we present a cross-case analysis of seven farmers' networks carrying out experiments on crop production and livestock farming. Some experiments were implemented by the farmers themselves on their farms or within a farm network; others were led by technical advisors, veterinarians or scientists. They varied from very formal to much more informal designs and protocols, from individual to more collective experiments. By experimenting, farmers not only assessed the performances of the experimented practices, they also learned how to manage a complex system and observe animals or plants differently, they gained confidence to move to a trajectory of technical change, and in some cases, the experiments stabilized the network for a period by supporting the exchanges between peers. The synergy between individual and collective dynamics was analyzed. Peer-to-peer exchanges provided new ideas and a greater reflexivity on the experiments realized at the individual level. Complementary, the individual experiments were a way to acquire situated knowledge directly usable by each farmer.
Data-Driven Network-Centric Threat Assessment

Kim, Dae Wook, Ph.D. College of Computer Science & Engineering, Wright State University, 2017. Data-Driven Network-Centric Threat Assessment. As the Internet has grown increasingly popular as a communication and information sharing platform, it has given rise to two major types of Internet security threats related to two primary entities: end-users and network services. First, information leakages from networks can reveal sensitive information about end-users. Second, end-users systems can be compromised through attacks on network services, such as scanning-and-exploit attacks, spamming, drive-by downloads, and fake anti-virus software. Designing threat assessments to detect these threats is, therefore, of great importance, and a number of the detection systems have been proposed. However, these existing threat assessment systems face significant challenges in terms of i) behavioral diversity, ii) data heterogeneity, and iii) large data volume. To address the challenges of the two major threat types, this dissertation offers three unique contributions. First, we built a new system to identify network users via Domain Name System (DNS) traffic, which is one of the most important behavior-based tracking methods for addressing privacy threats. The goal of our system is to boost the effectiveness of existing user identification systems by designing effective fingerprint patterns based on semantically limited DNS queries that are missed by existing tracking efforts. Second, we built a novel system to detect fake anti-virus (AV) attacks, which represent an active trend in the distribution of Internet-based malware. Our system aims to boost the effectiveness of existing fake AV attack detection by detecting fake AV attacks in three challenging scenarios: i) fake AV webpages that require user interaction to install malware, instead of using malicious content to run automatic exploitation without users consent (e.g., shellcode); ii) fake AV webpages designed to impersonate real webpages using a few representative elements, such as the names and icons of anti-virus products from
Effet modérateur dans la relation contexte de programmation & efficacité publicitaire télévisuelle : analyse du rôle de l’âge et l’implication du téléspectateur dans le programme télévisuel

L’objectif de ce papier est d’analyser dans un contexte d’exposition a une publicite televisuelle, l’effet moderateur de l’âge du telespectateur sur l’interaction de son implication a l’egard du programme televisuel sur la relation entre le contexte de programmation et efficacite publicitaire televisuelle. D’abord, l’effet du contexte violent, drole et neutre sur l’efficacite publicitaire a ete analyse par la methode des equations structurelles. Ensuite, cet article a analyse le role moderateur de l’âge du telespectateur sur l’interaction de son implication a l’egard du programme televisuel sur l’ensemble des liens du modele a travers la demarche de Haye (2013). Les resultats obtenus dans cet article montrent que l’exposition du telespectateur a un programme violent, drole ou neutre, probablement par l’activation qu’elle provoque chez le sujet, facilite la memorisation publicitaire, favorise l’attitude envers la publicite et facilite l’intention de comportement. Ces relations sont renforcees par l’âge et l’implication du telespectateur envers le programme.
Avaliação da função muscular de indivíduos com indicação de reconstrução combinada do ligamento cruzado anterior e ligamento anterolateral do joelho

Silva ACG. Muscular function evaluation of individuals with indication of combined reconstruction of the anterior cruciate ligament and anterolateral knee ligament [dissertation]. São Paulo: “Faculdade de Medicina, Universidade de São Paulo”; 2018. Introduction: The main function of the anterolateral ligament (ALL) is the secondary restriction of tibial medial rotation, resulting in a change on the Pivot shift test. Studies show a worse rotational stability when there is an ALL lesion associated with an anterior cruciate ligament (ACL) lesion, which is improved after the combined reconstruction of these ligaments. Regarding the alterations on muscle function, there is no understanding in the literature on how these individuals behave. Purpose: To analyze if there is a difference in the muscle function (knee flexor and extensor and hip abductor) between the groups with indication for combined ACL and ALL reconstruction (ACL+ALL group) and isolated ACL reconstruction (ACL group). Secondarily, to do a clinical and functional evaluation. Methods: Isokinetic dynamometry for the primary objective using 60o/s angular velocities for the hip and 60 and 120o/s for the knee. Secondarily, the use of the Lysholm scale and functional tests, such as Single Hop Test and Cross Over Hop Test and clinical evaluation of pain by visual analogue scale; anterior translation of the tibia, with the arthrometer (KT-1000) and perimetry of the knee and thigh (tape measure). Results: No differences were found regarding hip and knee muscle function in the affected limb when the ACL+ALL and ACL groups were compared. However, there was a lower total extensor work at 60o/s in the limb contralateral to the lesion observed in the ACL+ALL group in relation to the ACL group. Evaluating the difference between the members there was a greater difference between them in the ACL group (peak torque, total work and agonist/antagonist ratio) at 60o/s, which also occurred at 120o/s for total extensor work and knee agonist / antagonist relation for this group. Regarding the secondary variables, 68.9% of the ACL+ALL group reported knee pain and 61.9% in the ACL group, and there was a significant increase in anterior tibial translation in the ACL+ALL group in relation to the ACL group. Conclusion: There is no difference between ACL+ALL and ACL groups regarding hip and knee muscle function and functionality. The ACL+ALL group presented a greater anterior translation of the tibia in relation to the ACL group. Descriptors: knee Injuries; anterolateral ligament; anterior cruciate ligament; muscle strength; muscle strength dynamometer.
The Halo Effect and Social Evaluation: How Organizational Status Shapes Audience Perceptions on Corporate Environmental Reputation

Although firms generally strive to enhance social evaluations, scholars have noted that such evaluations may not completely reflect actual performance of the firms. Extending this approach to the domain of environmental sustainability, we focus on the importance of social evaluation heuristics and explore how a firm’s status, or generalized evaluation not directly linked to environmental performance, plays a key role in shaping audience perceptions on its environmental reputation. Using multiple sources of data on 178 global companies’ green reputation, status, and environmental performance, our study shows that a firm’s status significantly enhances its environmental reputation assessed by general consumers and that the status effect varies significantly according to media frames. These findings illuminate the richness and complexity in the relations between status, reputation, and media-provided information in the area of environmental sustainability.
Big Data Problem, Technologies and Solutions

Big data challenge is about how to process and analysis terabytes and petabytes of data from multiple sources like social media interactions, real-time sensory data feeds and others as well as extract meaningful value of it. Big data describes a situation where the volume, velocity and variety of data exceed an organization’s storage or compute capacity for timely and accurate decision making (Sagiroglu & Sinanc, 2013; Bertolucci, 2013; SAS, 2012). IDC (International Data Corporation) defined big data as a “big data technologies describe a new generation of technologies and architectures, designed to economically extract value from very large volumes of a wide variety of data, by enabling high-velocity capture, discovery, and/or analysis”. Big data can include transactional data, warehoused data, metadata, healthcare, video and media/entertainment, in addition to social media solutions such as Facebook and Twitter (Gantz and Reinsel, 2011). Another definition is: big data means data that is too big (means that organizations must deal with petabyte-scale collections of data), too fast (it must be processed quickly-for example, to perform fraud detection at a point of sale), or too hard (means that is difficult to process or needs some kind of analysis) for existing tools to process (Wielki, 2013; Madden, 2012). When big data is distilled and analyzed in combination with traditional data, organizations can develop insightful understanding of their business. Therefore, new technologies (such as Hadoop and MapReduce) are emerging that enable organizations to handle large amounts of unstructured data, making the prospect of gaining insight both feasible and cost-effective (Wielki, 2013; Oracle, 2012 a)
TERNATE SOCIETY DEVELOPMENT DILEMMA IN FACING ATTRACTIONS BETWEEN TRADITION AND MODERNITY

The purpose of this research is to find information about the Ternatenese and Ternate aristocracy in facing the attraction between tradition and modernity as an effort to formulate a conceptual frame of the local society. Interview and documentary is used to gather data. Several informants that were chosen purposively were interviewed in this research. Documentary study was done of the primary and secondary sources. The result of this research is (1) Ternate aristocracy has a responsive reaction toward modernization. This means, they are not only accepting new values, but also conserving traditional values that is relevance to the society life development and; (2) Tradition and modernization attractions in Ternate aristocracy, in the political access, is improving. Some aristocrats are often used by the local politicians for their political purpose.
Elements Of Episodic Memory

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Korean Transition-based Dependency Parsing with Recurrent Neural Network

Transition-based dependency parsing requires much time and efforts to design and select features from a very large number of possible combinations. Recent studies have successfully applied Multi-Layer Perceptrons (MLP) to find solutions to this problem and to reduce the data sparseness. However, most of these methods have adopted greedy search and can only consider a limited amount of information from the context window. In this study, we use a Recurrent Neural Network to handle long dependencies between sub dependency trees of current state and current transition action. The results indicate that our method provided a higher accuracy (UAS) than an MLP based model.
Investigating Critical Thinking in Prospective Teachers: Metacognitive Skills, Problem Solving Skills and Academic Self-Efficacy

The aim of this study is to determine the extent to which prospective teachers' metacognitive skills, problem solving skills and academic self-efficacy explain their critical thinking tendencies. This study, designed as correlational survey method, was conducted with 229 prospective teachers studying at Van Yuzuncu Yil University, Faculty of Education. “Critical Thinking Disposition Scale”, “Metacognitive Skills Scale”, “Problem Solving Inventory” and “Academic Self-efficacy Scale” were used for data collection. Data were analyzed using descriptive statistics, Pearson Product-Moment Correlation Coefficient and stepwise regression analysis. As a result of the study, a positive, moderate level and significant relationship was found between prospective teachers’ critical thinking tendencies and metacognitive skills, problem solving skills, academic self-efficacy perceptions. This study concluded that prospective teachers' metacognitive skills, problem solving skills and academic self-efficacy perceptions together can explain about half of the variance (39.5%) in their critical thinking tendencies. However, this study revealed that problem solving skills doesn't make a meaningful contribution to the total variance and cannot explain prospective teachers' critical thinking tendencies to a significant extent.
Enhancing international students’ experiences: An imperative agenda for universities in the UK

The role of international students as catalysts for internationalization and related reforms in the UK higher education sector is increasing. With the growing number of international students, administrators and academics are identifying ways to enable international students to adapt to the UK environment and enhance their experiences as students. This article examines the academic and other social problems that international students who pursue programmes offered by the universities in the UK encounter. It also suggests mechanisms that universities may adopt so that international students have a smooth academic progression and a comfortable social life. Describing the roles of different stakeholders in supporting international students, and the need to create a university-wide awareness of the importance of the presence of the international students in the university campus, the article suggests how universities may track the performance of drivers that foster the experiences of international students.
ON AN APPROACH TO THE DERIVATION OF CONSTITUTIVE EQUATIONS OF PHOTOCHROMIC MATERIALS

The paper presents constitutive equations of deformed solids, the state parameters of which, apart from the displacement vector, include concentrations of photochromic compounds. Equilibrium equations are completed with chemical kinetic equations, which are a system of, in a general case, nonlinear ordinary differential equations or parabolic-type equations accounting for the diffusion of products of photochromic reactions. Coefficients of such equations (for example, quantum reaction yield, reaction rate) can be assumed to depend on the stressed state. Several versions of the dependence of coefficients of chemical kinetic equations on the stressed-strained state are introduced. Also, in the assumption of electrostatics, possible effects of electric fields are taken into account. In analogy with mechanics of semiconductors and conductors, related equations of state are proposed. The introduced model of a coupled photo-electro-mechanical effect is a strongly nonlinear boundary-value problem, the equations of which contain a large number of material constants that must be determined experimentally. For conducting potential mechanical experiments, a simplified one-dimensional model is proposed, which is analogous to problems of tension-compression and bending in mechanics of bars and beams. In the framework thereof, solutions of related one-dimensional problems are constructed, which make it principally possible to define dimensionless complexes containing unknown material constants.
An approach to sentence-selection-based text summarization

We introduced a newly developed text summarization system. It supports both Chinese and English, while this paper focuses on Chinese processing. We apply 6 word level features and 3 sentence level features to weigh each word and sentence. We also describe two new techniques, one is for processing the topic sensitive word feature and another is for processing the sentence length feature. Primary subjective evaluation shows that these approaches are effective and efficient, and performance of the system is promising.
Firm Behavior and Pollution in Small Geographies

We consider the relationship between the location choices of potentially polluting firms and local income. Unlike previous research in the area of economic justice, we distinguish between pollution potential and actual releases of toxic substances in the locality. We explore the relationship between profit maximizing behavior of potentially polluting firms in their choice of both location and expenditures to influence the likelihood of toxic releases and their expected financial costs. We proxy the expenditures on prudential behavior by observing the co-localization of waste remediation activities. Evidence supports the conclusion that firms behave rationally in managing risk of toxic release.
Semi‐supervised approaches to efficient evaluation of model prediction performance

In many modern machine learning applications, the outcome is expensive or time consuming to collect whereas the predictor information is easy to obtain. Semi‐supervised (SS) learning aims at utilizing large amounts of ‘unlabelled’ data along with small amounts of ‘labelled’ data to improve the efficiency of a classical supervised approach. Though numerous SS learning classification and prediction procedures have been proposed in recent years, no methods currently exist to evaluate the prediction performance of a working regression model. In the context of developing phenotyping algorithms derived from electronic medical records, we present an efficient two‐step estimation procedure for evaluating a binary classifier based on various prediction performance measures in the SS setting. In step I, the labelled data are used to obtain a non‐parametrically calibrated estimate of the conditional risk function. In step II, SS estimates of the prediction accuracy parameters are constructed based on the estimated conditional risk function and the unlabelled data. We demonstrate that, under mild regularity conditions, the estimators proposed are consistent and asymptotically normal. Importantly, the asymptotic variance of the SS estimators is always smaller than that of the supervised counterparts under correct model specification. We also correct for potential overfitting bias in the SS estimators in finite samples with cross‐validation and we develop a perturbation resampling procedure to approximate their distributions. Our proposals are evaluated through extensive simulation studies and illustrated with two real electronic medical record studies aiming to develop phenotyping algorithms for rheumatoid arthritis and multiple sclerosis.
Public Key Encryption algorithms Enabling Efficiency Using SaaS in Cloud Computing

— The Most great challenging in Cloud computing is Security. Here Security plays key role in this paper proposed concept mainly deals with security at the end user access. While coming to the end user access that are connected through the public networks. Here the end user wants to access his application or services protected by the unauthorized persons. In this area if we want to apply encryption or decryption methods such as RSA, 3DES, MD5, Blow fish. Etc., Whereas we can utilize these services at the end user access in cloud computing. Here there is problem of encryption and decryption of the messages, services and applications. They are is lot of time to take encrypt as well as decrypt and more number of processing capabilities are needed to use the mechanism. For that problem we are introducing to use of cloud computing in SaaS model. i.e., scalable is applicable in this area so whenever it requires we can utilize the SaaS model. In Cloud computing use of computing resources (hardware and software) that are delivered as a service over Internet network. In advance earlier there is problem of using key size in various algorithm like 64 bit it take some long period to encrypt the data.
Sentiment and Topic Analysis

The IDEAL (Integrated Digital Event Archiving and Library) and Global Event and Trend Archive Research (GETAR) projects have collected over 1.5 billion tweets, and webpages from social media and the World Wide Web and indexed them to be easily retrieved and analyzed. This gives researchers an extensive library of documents that reflect the interests and sentiments of the public in reaction to an event. By applying topic analysis to collections of tweets, researchers can learn the topics of most interest or concern to the general public. Adding a layer of sentiment analysis to those topics will illustrate how the public felt in relation to the topics that were found. The Sentiment and Topic Analysis team has designed a system that joins topic analysis and sentiment analysis for researchers who are interested in learning more about public reaction to global events. The tool runs topic analysis on a collection of tweets, and the user can select a topic of interest and assess the sentiments with regard to that topic (i.e., positive vs. negative). This report covers the background, requirements, design and implementation of our contributions to this project. Furthermore, we include a user manual and a developer manual to assist in any future work.