Miracle-dz/UniFAR-FTUs huggingface dataset:
Policies on sovereign debt

This paper seeks to convey four main messages. Because sovereign debt in advanced countries has reached unprecedented levels, there is more uncertainty than before on its future dynamics, and its impact on growth. As with any debt, it also creates the potential for increased financial fragility. However, uncertainty does not translate into unsustainability. A “yes or no” approach to the question of sustainability will only lead to misapprehension and mistakes. In most cases, sustainability is fully endogenous to the set of policies implemented by governments themselves. Policy frameworks, therefore, are even more important than before to anchor expectations and ensure financial and monetary stability. There should be no doubt or ambiguity about the willingness of the governments of advanced countries to pay their debts. And nor should there be any ambiguity on the preservation of monetary policies aimed at price stability. Clarity of purpose is especially important when central banks are still implementing exceptional non-standard measures and taking broader responsibility for fi nancial stability. Finally, there is an international dimension to public debt sustainability. Improving the international financial architecture will help the world reach a high growth equilibrium despite asymmetries in public debt levels and financial development. This should be a major priority on the international agenda.
Adaptive fuzzy-neural-network control of robot manipulator using T-S Fuzzy model design

This study focuses on the development of an adaptive fuzzy-neural-network control (AFNNC) scheme for an n-link robot manipulator to achieve high-precision position tracking. In general, it is difficult to adopt a model-based design to achieve this control objective due to the uncertainties in practical applications, such as friction forces, external disturbances and parameter variations. In order to cope with this problem, an AFNNC system is investigated without the requirement of prior system information. In this model-free control scheme, a continuous-time Takagi-Sugeno (T-S) dynamic fuzzy model with on-line learning ability is constructed for representing the system dynamics of an n-link robot manipulator. Then, a four-layer fuzzy-neural-network (FNN) is utilized for estimating nonlinear dynamic functions in this fuzzy model. Moreover, the AFNNC law and adaptive tuning algorithms for FNN weights are established in the sense of Lyapunov stability analyses to ensure the network convergence as well as stable control performance. Numerical simulations of a two-link robot manipulator actuated by DC servomotors are given to verify the effectiveness and robustness of the proposed AFNNC methodology. In addition, the superiority of the proposed control scheme is indicated in comparison with proportional-differential control (PDC), Takagi-Sugeno-Kang (TSK) type fuzzy-neural-network control (T-FNNC), robust-neural-fuzzy-network control (RNFNC), and fuzzy-model-based control (FMBC) systems.
Thai sign language translation system using upright speed-up robust feature and dynamic time warping

Sign language is an important communication tool for the deaf. There are two types of Thai sign language, i.e., Thai finger spelling (a signer spells each character using their fingers) and Thai sign language (a signer uses hand gesture and face expression to represent each word). In this paper, we build a dynamic hand gesture translation system with video caption without prior hand region segmentation. In particular, we utilize the upright speed-up robust feature (U-SURF) and the dynamic time warping (DTW) to find a matched word. This Thai sign language translation system was tested on 42 words. The total number of video sequences used in the experiment is 1470. The best correct classification rate for blind test set of signer-dependent is approximately 98% whereas that of signer-semi-independent is around 76 to 79%. The best blind test result for the signer-independent is around 62 to 68%.
Open Source Framework-Based New Generation Network Application Construction and Testing

Framework technology, as an important approach to develop new generation network application provides various and flexible design models for professionals. Based on open source framework this paper presents a solution on the construction and testing for the new generation network application. This solution shows a high quality software platform (Struts+Spring+Hibernate) and reveals the testing strategies of the software in detail. The testing is processed as follows, data persistence layer, business logic layer, presentation layer, then function and performance. Finally, a case study is illustrated to verify the validity of this solution. Keywords-new generation network; framework; Internet; load; performance
Ensuring Stable and Inclusive Growth in Pakistan

The article provides an overview of the Pakistani economy and addresses various sectoral issues currently being faced by the economy. The first and the most critical problem highlighted concerns the protection of the poor. Other issues highlighted relate to education, healthcare, housing, taxation and energy. This paper discusses how the current account deficit needs to be tackled by higher tariffs, exchange rate adjustments, and possible export duties. The paper also discusses the need to reduce the cost of production for industry and upgrade governance through an emphasis on the local government system. Regarding public sector investments, the paper explains how the government needs to be transparent about the Public Sector Development Programme, and allow projects to be executed by the provinces.
Extraction and Relation in Instant Messaging

The task of topic extraction and relation attempts to first identify important topics in a corpus and then draw relationships between them. Some research has explored topic segmentation—simply dividing the corpus according to when the topic changes. Additional research has tried to extract positive and negative sentiment from product reviews and discussion comments. However, the idea of relating extracted topics in a corpus is also interesting. One could imagine a question and answer system that benefits from the ability to associate different keywords that may not necessarily be associated by a simple thesaurus. For example, in a conversation about Stanford, the words “school” and “California” may be strongly related to one another; if someone was talking about Terminator, then “movie” and “robot” might be related. This is semantic information that can only be decided by examining the language itself. Such knowledge could also conceivably be useful in spam filtering or other situations in which the computer needs a deeper understanding of important words and their relevance to one another.
Plücker forms and the theta map

Let ${\rm SU}_X(r,0)$ be the moduli space of semistable vector bundles of rank r and trivial determinant over a smooth, irreducible, complex projective curve $X$. The theta map $\theta_r: {\rm SU}_X(r,0) \rightarrow \Bbb{P}^N$ is the rational map defined by the ample generator of ${\rm Pic}{\rm SU}_X(r,0)$. The main result of the paper is that $\theta_r$ is generically injective if $g \gg r$ and $X$ is general. This partially answers the following conjecture proposed by Beauville: $\theta_r$ is generically injective if $X$ is not hyperelliptic. The proof relies on the study of the injectivity of the determinant map $d_E: {\wedge}^r H^0(E) \rightarrow H^0(\det E)$, for a vector bundle $E$ on $X$, and on the reconstruction of the Grassmannian $G(r,rm)$ from a natural multilinear form associated to it, defined in the paper as the Pl\"ucker form. The method applies to other moduli spaces of vector bundles on a projective variety $X$.
A Shape Grammar Study: Form Generation with Geometric Islamic Patterns

The aim of this research is to present the features of geometric patterns in Islam, to use rules-sets for two and three dimensional form generation and to indicate the potential of mathematics of symmetry and geometry. The study focused on parametrically defined shape grammars of Islamic patterns to generate three dimensional forms in CAAD. The information offered in this paper can be used to generate innovative depictions and to add fresh perspective to architecture. Throughout the history, some simple repetitive patterns were used as a starting point for architectural layouts, landscape designs or urban planning. In this research, Islamic patterns are used as a basis for three dimensional form generation explorations. This study can be accepted as a preliminary step of more complicated forward studies for innovative designs with historical patterns.
Topological Descriptor for CAD Models with Inner Cavities

The current work introduces an algorithm for constructing Reeb graph for CAD models and their inner cavities. The nodes of the graph represent areas of the manifold of the model where topological changes occur. Edges of the graph encode information about connections between such areas. The outline for the topological graph matching is given for detection of graph (sub)isomorphism. The proposed Reeb graph structure can be used as a descriptor of CAD models in the retrieval process
Predicting popularity of articles on bulletin board system

In this work, we study how to predict the popularity of an article in the largest terminal-based bulletin board system (BBS) and also one of the most major social media, PTT (ptt.cc), in Taiwan. Given a specified article and a duration time after it is published, we want to predict the number of unique users that have ever commented the article and the degree of popularity based on the total number of comments of this article compared to other historical articles in the system. We first introduce the ecology of PTT and show our observations of the user posting behaviors. Since PTT has quite a different style compared to other commonly-known social media such as Facebook and Twitter, we show how to extract and integrate four sets of important and useful features, including the textual, author-wise, social and temporal ones, from the large-scale BBS data for predicting the article popularity with different classification models. Experiment results show the effectiveness of all these four types of features we extracted. Specifically, the temporal and social features help improve the prediction qualities most.
The Mindpool hybrid: theorising a new angle on EBS and suggestion systems

Traditional suggestion systems, despite their shortcomings, have been used to promote creativity in industry for over a century. Independently, brainstorming has also been applied for almost fifty years as a method to increase idea generation. However, the two have never met. In this argumentative paper it is theorised that by adding computer support and applying lessons from the realm of electronic brainstorming (EBS) to traditional suggestion systems useful improvements may be achieved. A hybrid intranet prototype mimicking the attributes of an EBS system and at the same time serving as a complement to the suggestion system was therefore devised and evaluated using a theoretical framework. The implications suggest novel ideas for both suggestion systems and EBS research.
Privacy Policy Preferences Enforced by SPARQL Query Rewriting

When specifying privacy preferences, the data owner can control who may access its personal data, for which purpose and under which accuracy. In this paper we present an approach that enforces the privacy policy preferences by query transformation. We present also how to instrument this rewriting query algorithm using a privacy-aware model like PrivOrBAC. We take into account various dimensions of privacy preferences through the concepts of consent, accuracy, purpose and recipient.
An approach of constructing ECOC adaptively based on confusion matrix

Error correcting output codes(ECOC) is an effective frame that can decompose a multiclass problem into a set of complementary two-class problems, and the research of encoding based on data especially attracts attentions. In this paper, we propose a new encoding method CMECOC for constructing ECOC adaptively based on confusion matrix, first, we obtain the separability measure between each pair of patterns with the help of confusion matrix, then abide by Fisher's rule, the most favorable combination of patterns for classification can be found, at last, we get binary partitions based on the way of pattern combination, and a data driven coding matrix can be achieved. Experimental results on UCI datasets with support vector machine(SVM) as the binary classifier show that our approach can provide a better performance and robustness of classification with a little longer but acceptable coding length.
Neuroprotective Effect of Transplanted Human Embryonic Stem Cell-Derived Neural Precursors in an Animal Model of Multiple Sclerosis

Background Multiple sclerosis (MS) is an immune mediated demyelinating disease of the central nervous system (CNS). A potential new therapeutic approach for MS is cell transplantation which may promote remyelination and suppress the inflammatory process. Methods We transplanted human embryonic stem cells (hESC)-derived early multipotent neural precursors (NPs) into the brain ventricles of mice induced with experimental autoimmune encephalomyelitis (EAE), the animal model of MS. We studied the effect of the transplanted NPs on the functional and pathological manifestations of the disease. Results Transplanted hESC-derived NPs significantly reduced the clinical signs of EAE. Histological examination showed migration of the transplanted NPs to the host white matter, however, differentiation to mature oligodendrocytes and remyelination were negligible. Time course analysis of the evolution and progression of CNS inflammation and tissue injury showed an attenuation of the inflammatory process in transplanted animals, which was correlated with the reduction of both axonal damage and demyelination. Co-culture experiments showed that hESC-derived NPs inhibited the activation and proliferation of lymph node–derived T cells in response to nonspecific polyclonal stimuli. Conclusions The therapeutic effect of transplantation was not related to graft or host remyelination but was mediated by an immunosuppressive neuroprotective mechanism. The attenuation of EAE by hESC-derived NPs, demonstrated here, may serve as the first step towards further developments of hESC for cell therapy in MS.
Research on Purchase Intentions of Residential Product Based on Structural Equation Model

All corporations' activities must surround consumer behavior directly or indirectly, take consumer as activity's start and ultimate aim, and provide satisfying product or service to consumer. It is the key of transforming profit successfully which is how can we deliver the value of the residential product by using suited mode, route and marketing mix, and how can we inspire the consumer's purchase intentions. This paper chooses the consumer's purchase intentions as the dependent variable. By reviewing researches on antecedents of purchase intention, the paper finds out three pivotal antecedents variables: perceived value, perceived quality and perceived risk, and chooses product knowledge, perceived price, consumption scene, brand perception, advertising perception and reference group as the independent variables. By Cronbach's analysis of coefficient alpha analysis, factor analysis, analysis of variances, correlation analysis and structural equations modeling etc., we testified the hypothesis proposed in the study. Results indicate perceived value is the most direct antecedent of the purchase intentions, both of the other two antecedents perform via perceived value. The marketing strategies' influence weights on perceived quality and perceived risk are quite distinct.
Best Practices for Data Centers: Lessons Learned from Benchmarking 22 Data Centers

Over the past few years, the authors benchmarked 22 data center buildings. From this effort, we have determined that data centers can be over 40 times as energy intensive as conventional office buildings. Studying the more efficient of these facilities enabled us to compile a set of “best-practice” technologies for energy efficiency. These best practices include: improved air management, emphasizing control and isolation of hot and cold air streams; rightsizing central plants and ventilation systems to operate efficiently both at inception and as the data center load increases over time; optimized central chiller plants, designed and controlled to maximize overall cooling plant efficiency, central air-handling units, in lieu of distributed units; “free cooling” from either air-side or water-side economizers; alternative humidity control, including elimination of control conflicts and the use of direct evaporative cooling; improved uninterruptible power supplies; high-efficiency computer power supplies; on-site generation combined with special chillers for cooling using the waste heat; direct liquid cooling of racks or computers; and lowering the standby losses of standby generation systems. Other benchmarking findings include power densities from 5 to nearly 100 Watts per square foot; though lower than originally predicted, these densities are growing. A 5:1 variation in cooling effectiveness index (ratio of cooling power to computer power) was found, as well as large variations in power distribution efficiency and overall center performance (ratio of computer power to total building power). These observed variations indicate the potential of energy savings achievable through the implementation of best practices in the design and operation of data centers.
Raking the governmental organizations in cyberspace environment

E-government as a subsection of e-government influenced in organizations for enhancing the service delivery to citizens, businesses, and other governments. Therefore, it is critical for organizations to assess their investigations in e-government development for improvement of their future plans. In this paper, the required criteria are extracted with a modified BSC framework and performance evaluation is done by fuzzy ranking method.
THE INTERNATIONAL COMPETITIVENESS OF EUROPEAN UNION COUNTRIES AND STRATEGIES FOR ITS ENHANCEMENT: A TAXONOMIC ANALYSIS

: The aim of this article is to identify clusters of countries with similar levels of competitiveness among the EU-27 countries and to identify for each of the 27 EU countries the path of competitiveness growth. The cluster analysis conducted confirms the hypothesis that the European Union is an area with a high differentiation in terms of levels of competitiveness. The analysis shows that the strategy to increase competitiveness should be significantly different for each EU country. It is suggested that in order to increase its international competitiveness each EU country should follow the pattern of the country which stands above it in terms of competitiveness ranking, but at the same time is most similar.
Structure-Activity Determinants in Antifungal Plant Defensins MsDef1 and MtDef4 with Different Modes of Action against Fusarium graminearum

Plant defensins are small cysteine-rich antimicrobial proteins. Their three-dimensional structures are similar in that they consist of an α-helix and three anti-parallel β-strands stabilized by four disulfide bonds. Plant defensins MsDef1 and MtDef4 are potent inhibitors of the growth of several filamentous fungi including Fusarium graminearum. However, they differ markedly in their antifungal properties as well as modes of antifungal action. MsDef1 induces prolific hyperbranching of fungal hyphae, whereas MtDef4 does not. Both defensins contain a highly conserved γ-core motif (GXCX3–9C), a hallmark signature present in the disulfide-stabilized antimicrobial peptides, composed of β2 and β3 strands and the interposed loop. The γ-core motifs of these two defensins differ significantly in their primary amino acid sequences and in their net charge. In this study, we have found that the major determinants of the antifungal activity and morphogenicity of these defensins reside in their γ-core motifs. The MsDef1-γ4 variant in which the γ-core motif of MsDef1 was replaced by that of MtDef4 was almost as potent as MtDef4 and also failed to induce hyperbranching of fungal hyphae. Importantly, the γ-core motif of MtDef4 alone was capable of inhibiting fungal growth, but that of MsDef1 was not. The analysis of synthetic γ-core variants of MtDef4 indicated that the cationic and hydrophobic amino acids were important for antifungal activity. Both MsDef1 and MtDef4 induced plasma membrane permeabilization; however, kinetic studies revealed that MtDef4 was more efficient in permeabilizing fungal plasma membrane than MsDef1. Furthermore, the in vitro antifungal activity of MsDef1, MsDef1-γ4, MtDef4 and peptides derived from the γ-core motif of each defensin was not solely dependent on their ability to permeabilize the fungal plasma membrane. The data reported here indicate that the γ-core motif defines the unique antifungal properties of each defensin and may facilitate de novo design of more potent antifungal peptides.
An Improved Implementation of Brain Tumor Detection Using Segmentation Based on Neuro Fuzzy Technique

Implementation of a neuro-fuzzy segmentation process of the MRI data is presented in this study to detect various tissues like white matter, gray matter, csf and tumor. The advantage of hierarchical self organizing map and fuzzy c means algorithms are used to classify the image layer by layer. The lowest level weight vector is achieved by the abstraction level. We have also achieved a higher value of tumor pixels by this neuro-fuzzy approach. The computation speed of the proposed method is also studied. The multilayer segmentation results of the neuro fuzzy are shown to have interesting consequences from the viewpoint of clinical diagnosis. Neuro fuzzy technique shows that MRI brain tumor segmentation using HSOM-FCM also perform more accurate one.
Land Reform in Developing Countries: Property Rights and Property Wrongs

Introducing Land Reform 1. Goals 2. Output, Efficiency and Growth 3. Land Reforms: The Types, and the Classic Paradigm 4. Tenurialism: Tenancy Reform, Titling, Patrialisation 5. The Terrible Detour: Collectivisation and Decollectivisation 6. Alternatives, Complements, Diversions, 'New Wave' Land Reform 7. The Death of Land Reform?
Learning Contextualized Music Semantics from Tags Via a Siamese Neural Network

Music information retrieval faces a challenge in modeling contextualized musical concepts formulated by a set of co-occurring tags. In this article, we investigate the suitability of our recently proposed approach based on a Siamese neural network in fighting off this challenge. By means of tag features and probabilistic topic models, the network captures contextualized semantics from tags via unsupervised learning. This leads to a distributed semantics space and a potential solution to the out of vocabulary problem, which has yet to be sufficiently addressed. We explore the nature of the resultant music-based semantics and address computational needs. We conduct experiments on three public music tag collections—namely, CAL500, MagTag5K and Million Song Dataset—and compare our approach to a number of state-of-the-art semantics learning approaches. Comparative results suggest that this approach outperforms previous approaches in terms of semantic priming and music tag completion.
Survey of Different Types of CAPTCHA

CAPTCHA is an acronym for Completely Automated Public Turning Test to tell Computers and Humans Apart [1]. CAPTCHA is basically used as a protection from these malicious programs like Bot. Now a day’s for web security we are using different type of captcha. In this paper we describe all type of captcha and also describe their drawbacks all type of captcha. We also describe application of captcha. And review paper of different types of Captcha.