Miracle-dz/UniFAR-FTUs huggingface dataset:
Cosmic Backgrounds from Miniquasars

A large population of Intermediate Mass Black Holes (IMBHs) might be produced at early cosmic times as a left over of the evolution of the very massive first stars. Accretion onto IMBHs provides a source of (re)ionizing radiation. We show that the baryon mass fraction locked into IMBHs and their growth is strongly constrained by the observed residual Soft X-ray Background (SXRB) intensity. Thus, unless they are extremely X-ray quiet, miniquasars must be quite rare and/or have a short shining phase. As a byproduct, we find that miniquasars can not be the only source of reionization and that their alleged contribution to the near infrared bands is completely negligible.
The classification of tilting modules over Harada algebras

In the 1980s, Harada introduced a new class of algebras now called Harada algebras. Harada algebras provides us with a rich source of Auslander's 1-Gorenstein algebras. In this paper, we have two main results about Harada algebras. The first is the classification of modules over Harada algebras whose projective dimension is at most one. The second is the classification of tilting modules over Harada algebras, which is shown by giving a bijection between tilting modules over Harada algebras and tilting modules over direct products of upper triangular matrix algebras over $K$. A combinatorial description of tilting modules over upper triangular matrix algebras over $K$ is known. These facts allow us to classify tilting modules over a given Harada algebra.
Assessing the Cost-Benefits of Using Type Inference Algorithms to Improve the Representation of Exceptional Control Flow in Java

Accurate representations of program control flow are important to the soundness and efficiency of program analysis and testing techniques. The Java programming language has introduced structured exception handling features that complicate the task of constructing safe and precise representations of the possible control flow in Java programs. Prior work has considered applying various type inference algorithms to exceptions, but has not yet investigated whether the use of higher cost algorithms is necessarily justified. It is important to understand and assess the tradeoffs associated with the use of more powerful yet costly algorithms, thus we conducted an empirical study to evaluate the relative performance of several such algorithms. We find that applying type inference to exceptions may improve representations of control flow, but that these improvements do not necessarily translate into benefits for practical techniques that use them. Thus we argue that type inference should not be blindly applied, but rather the tradeoffs of applying them must be assessed with respect to particular program analyses and techniques.
Sub-Word Indexing and Blind Relevance Feedback for English, Bengali, Hindi, and Marathi IR

The Forum for Information Retrieval Evaluation (FIRE) provides document collections, topics, and relevance assessments for information retrieval (IR) experiments on Indian languages. Several research questions are explored in this article: 1) How to create create a simple, language-independent corpus-based stemmer, 2) How to identify sub-words and which types of sub-words are suitable as indexing units, and 3) How to apply blind relevance feedback on sub-words and how feedback term selection is affected by the type of the indexing unit. More than 140 IR experiments are conducted using the BM25 retrieval model on the topic titles and descriptions (TD) for the FIRE 2008 English, Bengali, Hindi, and Marathi document collections. The major findings are: The corpus-based stemming approach is effective as a knowledge-light term conflation step and useful in the case of few language-specific resources. For English, the corpus-based stemmer performs nearly as well as the Porter stemmer and significantly better than the baseline of indexing words when combined with query expansion. In combination with blind relevance feedback, it also performs significantly better than the baseline for Bengali and Marathi IR. Sub-words such as consonant-vowel sequences and word prefixes can yield similar or better performance in comparison to word indexing. There is no best performing method for all languages. For English, indexing using the Porter stemmer performs best, for Bengali and Marathi, overlapping 3-grams obtain the best result, and for Hindi, 4-prefixes yield the highest MAP. However, in combination with blind relevance feedback using 10 documents and 20 terms, 6-prefixes for English and 4-prefixes for Bengali, Hindi, and Marathi IR yield the highest MAP. Sub-word identification is a general case of decompounding. It results in one or more index terms for a single word form and increases the number of index terms but decreases their average length. The corresponding retrieval experiments show that relevance feedback on sub-words benefits from selecting a larger number of index terms in comparison with retrieval on word forms. Similarly, selecting the number of relevance feedback terms depending on the ratio of word vocabulary size to sub-word vocabulary size almost always slightly increases information retrieval effectiveness compared to using a fixed number of terms for different languages.
Fault diagnosis via structural support vector machines

Discriminative methods are becoming more and more popular on fault diagnosis systems, while they need additional strategies or multiple models to cope with the multiple classification problems. In this paper, we introduce the structural Support Vector Machines (structural SVMs) to fault diagnosis, which can indentify multiple kinds of faults with only one uniform discriminative model. We define error penalty function and select a proper kernel to make structural SVMs be appropriate for non-linear problem. Tennessee Eastman Process (TEP), a benchmark chemical engineering problem, is used to generate datasets to evaluate the performance of the propose method. Experiments show that the structural SVM reports a state-of-the-art performance on overlapping fault data and different fault type data.
Fast Marching farthest point sampling for implicit surfaces and point clouds

In a recent paper [13], the Fast Marching farthest point sampling strategy (FastFPS) for planar domains and curved manifolds was introduced. The version of FastFPS for curved manifolds discussed in the paper [13] deals with surface domains in triangulated form only. Due to a restriction of the underlying Fast Marching method, the algorithm further requires the splitting of any obtuse into acute triangles to ensure the consistency of the Fast Marching approximation. In this paper, we overcome these restrictions by using Memoli and Sapiro’s [11, 12] extension of the Fast Marching method to the handling of implicit surfaces and point clouds. We find that the extended FastFPS algorithm can be applied to surfaces in implicit or point cloud form without the loss of the original algorithm’s computational optimality and without the need for any preprocessing.
Waveform interpolation coding with pitch-spaced subbands

We present new waveform-interpolation coding procedures which allow perfect reconstruction of the speech signal from the un-quantized parameter set. Instead of using adaptive parameter extraction methods, we combine a time warping of the original signal with nonadaptive parameter extraction methods. The new coding structure has good performance at low bit rates and provides convergence to the original waveform with increasing rate.
Establishment of Security Levels in Trusted Cloud Computing Platforms

Cloud computing, which provides online resources as a service to users, brings a technology revolution in IT world. However, the data security and privacy on cloud is an important issue, becoming the biggest barrier of cloud computing development. A Trusted Cloud Computing Platform (TCCP) based on remote attestation build a trusted cloud for tenant. The critical section is centralized Trusted Coordinator, taking the place of tenants to authenticate nodes individually in cloud computing platform. But, when a lot of tenants apply for nodes at the same time, Trusted Coordinator (TC) maybe can't deal with these requests quickly. To address this problem, we propose the establishment of security-level for different applications in TCCPs, which divides Trusted Coordinator into three, each responsible for authenticating different application kind. TC would implement different authentication policies, such as user password comparison, image hash verification and trusted chain measurement, according to different security levels.
Exploring EFL Teachers’ Perception of Pedagogical Task

Pedagogic competence is one of the competences that should be owned, comprehended, and mastered by teachers and lecturers to conducting professional job in Indonesian context and Bintan Regency particularly. It can be seen from their ability to help students to practice target language through pedagogical task. Therefore, the purpose is to explore the cognition, beliefs, and practice of state junior high school of English as a foreign language (EFL) teachers of pedagogical tasks in the classroom. The focus is on the cognition of the EFL teachers of pedagogical task in their classroom; the beliefs of EFL teachers of pedagogical task in the classroom; the practices of EFL teachers of pedagogical tasks in the classroom. The study is descriptive quantitative with survey method. The data will be collected through questionnaires for pedagogical task. The data will be analyzed with Likert scale through interpreting the data of cognition, beliefs, and practice of pedagogical task gathered from questionnaires. The findings showed that the teachers had good enough cognition, positive point of view and reasons to or not to use the pedagogical task in their EFL classroom. The teachers have had awareness of pedagogical task to try this in their teaching practice. Keywords—EFL teacher; pedagogical task; teacher’s competence
Hedonic Model with Discrete Consumer Heterogeneity and Horizontal Differentiated Housing

This paper investigates how the hedonic equilibrium is modified when discrete consumer heterogeneity with horizontal differentiated housing supply is assumed. Our results are threefold. First, discrete consumer heterogeneity leads to a segmentation of the hedonic price function at equilibrium and the discontinuity of the implicit price of environmental quality on the borders of the segments. Second, we demonstrate that horizontal differentiation can lead to a partial sorting of consumer demand for housing attributes at hedonic equilibrium. Finally, we show that according to model specification, the groupwise heterogeneity with horizontal differentiation can lead to modification of welfare assessment related to changes in environmental quality.
Cumulativity as Inductive Bias

An important di erence in inductive bias between machine learning approaches is whether they assume the e ects of di erent properties on a target variable to be cumulative or not. We believe this di erence may have an important in uence on the performance of machine learning or data mining techniques, and hence should be taken into account when deciding which techniques to use. We illustrate this point with some practical cases. We furthermore point out that in Inductive Logic Programming, most algoritms belong to the class that does not assume cumulativity. We argue for the use and/or development of ILP systems that do make this assumption.
Institute for Computing R 12 methods , Gaussian geminals

c © 2000 by John von Neumann Institute for Computing Permission to make digital or hard copies of portions of this work for personal or classroom use is granted provided that the copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise requires prior specific permission by the publisher mentioned above.
Phylogeography of Libanotis buchtormensis (Umbelliferae) in Disjunct Populations along the Deserts in Northwest China

In Northwest China, aridification and desert expansion play significant roles in promoting desert plant diversification and speciation. However, to date, little is known about the effects of the desert barrier on the population structure of montane, non-desert species in the area. In this study, we sequenced chloroplast DNA regions (trnL–trnF and trnS–trnG) and a nuclear gene (rpb2) to investigate the population differentiation and phylogeographical history of Libanotis buchtormensis, a perennial montane species possessing a disjunct distribution at the periphery of the central desert. In total, 23 chloroplast haplotypes and 24 nuclear haplotypes were recovered from the 21 natural populations and six hebarium specimens. Phylogenetic analysis based on the combined plastid and nuclear dataset revealed two distinct lineages of L. buchtormensis, which inhabit the disjunct areas on both sides of the desert zone. The molecular dating analysis indicated that the divergence between the southeastern and the northwestern populations occurred in the middle Pleistocene, concomitantly with the desert expansion. The geographical vicariance likely contributed to the present disjunct distribution of L. buchtormensis across the deserts in Northwest China. Populations in the southeastern region may have migrated from the northwestern region, and seem to be a peripheral distribution of L. buchtormensis.
Representations of Multiple-Output Functions Using Binary Decision Diagrams for Characteristic Functions (Special Section on VLSI Design and CAD Algorithms)

This paper proposes a method to construct smaller binary decision diagrams for characteristic functions (BDDs for CFs). A BDD for CF represents an n-input m-output function, and evaluates all the outputs in O(n+m) time. We derive an upper bound on the number of nodes of the BDD for CF of n-bit adders (adrn). We also compare complexities of BDDs for CFs with those of shared binary decision diagrams (SBDDs) and multi-terminal binary decision diagrams (MTBDDs). Our experimental results show: 1) BDDs for CFs are usually much smaller than MTBDDs; 2) for adrn and for some benchmark circuits, BDDs for CFs are the smallest among the three types of BDDs; and 3) the proposed method often produces smaller BDDs for CFs than an existing method. key words: binary decision diagram (BDD), characteristic function (CF), multiple-output function, variable ordering, logic simulation, adder, bit-counting function, multiplier
Dynamic Modeling and Identification of Par4, A Very High Speed Parallel Manipulator

This paper introduces the dynamic modeling and the identification of Par4, a four-degree-of-freedom parallel manipulator producing Schonflies motions (three translations and one rotation about a fixed axis). First of all, this paper presents how this robot is developed with the goal of reaching very high speed. Indeed, it is an evolution of Delta, H4 and I4 robots architectures: it keeps their advantages while overcoming their drawbacks. Experimentations done with the prototype prove that the robot is able to reach very high accelerations (15 G) and to perform an adept cycle in 0.25 s. In order to improve its dynamic accuracy, a dynamic control could be necessary. Thus, this paper presents the dynamic modeling of the manipulator using a simplified Newton-Euler approach. The originality of this computation is to model the traveling as two separated parts and to determine the dynamic effects applied on each of them. Finally, since a dynamic control requires a good evaluation of dynamic parameters, an experimental dynamic identification is presented
Test harness and script design principles for automated testing of non-GUI or web based applications

Scarcity of commercially available testing tools that could support all native or application specific message formats as well as those that cater to non GUI or non web based backend applications leads to creating your own customized traffic generators or scripts. Also the test environment setup may differ from one system to another -- some may use simulators or mocks to stub out complex software, others may just be a scaled down (in terms of number of servers) replica of the production environment. So what are the factors that need to be considered when creating scripts that can be used for native request formats and for non GUI or web based applications? How do we design a script that is easy to maintain and extend when new test scenarios are added to accurately assess the performance of an application? This paper provides (1) the general design principles for a test script that can be used to generate traffic for any request format as well as (2) specific factors to keep in mind when creating a script that will work in a test environment that uses a mock. In addition to this the core activities of testing include not only traffic generation but also setting up the environment, verifying that both the hardware and software configurations are accurate prior to sending traffic and creating a report at the end of the test. Therefore the test script needs to be part of a complete harness that accomplishes these tasks. The paper will address the (3) design and properties of such a harness. It provides a simple framework that can be easily used to complete an end to end testing process -pre test, traffic generation and post test activities.
Primal-dual interior-point methods solver based on kernel functions for Linear Optimization

In this paper we present the theory and practical aspects of implementing the path following interior point methods for linear optimization, based on kernel functions. We will investigate the influence of the choice of the kernel function on the computational behavior of the generic primal-dual algorithm for Linear Optimization. We find that the finite kernel function gives the best results for more than 50 % of the tested problems compared to the standard log-barrier method.
Identi ® cation and interpretation of clinical and quality of life prognostic factors for survival and response to treatment in ® rst-line chemotherapy in advanced breast cancer

The aim of the project was to identify clinical and quality of life (QL) factors that together predict survival and response to chemotherapy in advanced breast cancer. Potential prognostic factors were studied in 187 women with baseline QL data from a trial of paclitaxel versus doxorubicin as ®rst-line chemotherapy. Demographic and clinical factors studied were age, performance status, dominant site of disease and preceding disease-free interval (DFI). Factors from the EORTC QLQ-C30 were all function scales, fatigue, nausea/vomiting, pain, dyspnoea, insomnia, loss of appetite and global QL. The proportional hazards regression model with strati®cation for treatment, and the logistic regression model adjusting for treatment arm were used for univariate and multivariate analyses of survival and response to treatment, respectively. For survival, multiple sites of visceral disease, pain, global QL and fatigue were signi®cant prognostic factors in the univariate analysis. The ®nal multivariate model predicted poor survival with multiple sites of visceral disease (P=0.003), DFI 42 years (P=0.026) and pain (P=0.003). For response, age, dyspnoea, fatigue and global QL were signi®cant predictive factors in the univariate analysis. The ®nal multivariate model for response selected DFI (P=0.009), multiple sites of visceral disease (P=0.037) and dyspnoea (P=<0.001) using forward selection, but model instability was indicated by the inclusion of fatigue and emotional function in the ®nal model when backward selection was used. In addition to known clinical factors, patient-assessed QL variables appear to be prognostic for survival and response to chemotherapy in women with advanced breast cancer. However, identi®cation of prognostic factors from responses to questionnaires may be unstable, and their reliability and clinical utility should be tested prospectively. # 2000 Elsevier Science Ltd. All rights reserved.
Usage of public key infrastructures in automation networks

Due to the use of standardized information technology from the office world in industrial automation networks, threats concerning such networks become relevant for automation systems. Communication protocols used in automation networks typically provide no security functionalities. In this paper, a public key infrastructure (PKI) for automation networks is proposed that supports the establishment of secured connections between automation components and also supports protective measures against product piracy.
A Combined Fuzzy Decision Making Approach to Supply Chain Risk Assessment

0F � Abstract—Many firms implemented various initiatives such as outsourced manufacturing which could make a supply chain (SC) more vulnerable to various types of disruptions. So managing risk has become a critical component of SC management. Different types of SC vulnerability management methodologies have been proposed for managing SC risk, most offer only point-based solutions that deal with a limited set of risks. This research aims to reinforce SC risk management by proposing an integrated approach. SC risks are identified and a risk index classification structure is created. Then we develop a SC risk assessment approach based on the analytic network process (ANP) and the VIKOR methods under the fuzzy environment where the vagueness and subjectivity are handled with linguistic terms parameterized by triangular fuzzy numbers. By using FANP, risks weights are calculated and then inserted to the FVIKOR to rank the SC members and find the most risky partner. Keywords—Analytic network process (ANP), Fuzzy sets, Supply chain risk management (SCRM), VIsekriterijumsko KOmpromisno Rangiranje (VIKOR) I. INTRODUCTION ANAGING risk in supply chains has emerged as an important topic in supply chain management. The topic derives its importance due to several industry trends currently in place: increase in strategic outsourcing by firms, globalizations of markets, increasing reliance on suppliers for specialized capabilities and innovation, reliance on supply networks for competitive advantage, and emergence of information technologies that make it possible to control and coordinate extended supply chains. These trends have manifested themselves in an increase in outsourcing and off- shoring of manufacturing and R&D activities, low cost country (LCC) sourcing, and collaboration with international supplier partners (20)-(32). While these increase the strategic options for firms, they also increase the probability of experiencing adverse events in supply chains that significantly threaten normal business operations of firms in the supply chains. Along with the increase in these initiatives, there has been an increase in the potential and magnitude of supply chain risks (4). Recent events involving food supply chains (for example, Melamine in infant formula and powdered milk
Privacy preserving multimedia content identification for cloud based bag-of-feature architectures

In this paper we consider privacy-preserving multimedia content identification for a cloud based Bag-of-Feature (BoF) framework. We analytically model how geometric information can be used as a shared secret and derive the tradeoff between identification capability, privacy and computational load. In addition we suggest a descriptor ambiguization method that introduces uncertainty to the server with respect to the true interest of the data users.