Miracle-dz/UniFAR-FTUs huggingface dataset:
A 3D wavelet fusion approach for the reconstruction of isotropic‐resolution MR images from orthogonal anisotropic‐resolution scans

Hardware constraints, scanning time limitations, patient movement, and signal‐to‐noise ratio (SNR) considerations, restrict the slice‐selection and the in‐plane resolutions of MRI differently, generally resulting in anisotropic voxels. This nonuniform sampling can be problematic, especially in image segmentation and clinical examination. To alleviate this, the acquisition is divided into (two or) three separate scans, with higher in‐plane resolutions and thick slices, yet orthogonal slice‐selection directions. In this work, a noniterative wavelet‐based approach for combining the three orthogonal scans is adopted, and its advantages compared with other existing methods, such as Fourier techniques, are discussed, including the consideration of the actual pulse response of the MRI scanner, and its lower computational complexity. Experimental results are shown on simulated and real 7 T MRI data. Magn Reson Med, 2011. © 2011 Wiley‐Liss, Inc.
Identification of roofs perimeter from aerial and satellite images

The computer-driven extraction of roofs perimeter is a very vimportant step in 3D reconstruction of buildings as it allows vto reduce human interactions. In this context, very high vresolution optical images, from airborne surveys or from vsatellites, were used in this paper with the aim of extracting vsuch information.
Automated quantification of one-dimensional nanostructure alignment on surfaces

A method for automated quantification of the alignment of one-dimensional (1D) nanostructures from microscopy imaging is presented. Nanostructure alignment metrics are formulated and shown to be able to rigorously quantify the orientational order of nanostructures within a two-dimensional domain (surface). A complementary image processing method is also presented which enables robust processing of microscopy images where overlapping nanostructures might be present. Scanning electron microscopy (SEM) images of nanowire-covered surfaces are analyzed using the presented methods and it is shown that past single parameter alignment metrics are insufficient for highly aligned domains. Through the use of multiple parameter alignment metrics, automated quantitative analysis of SEM images is shown to be possible and the alignment characteristics of different samples are able to be quantitatively compared using a similarity metric. The results of this work provide researchers in nanoscience and nanotechnology with a rigorous method for the determination of structure/property relationships, where alignment of 1D nanostructures is significant.
The use of mind mapping to develop writing skills in UAE schools

Purpose – The purpose of this paper is to study the effectiveness of using mind mapping as a methodology to help students to plan effectively for a writing task under an assessment situation.Design/methodology/approach – The methodology included a variety of qualitative data collection techniques such as interviews, mind map analysis, observation checklist and reflective journal.Findings – Evidence and research outcomes suggested that mind mapping did help students to plan and organize their ideas for writing tasks under exam conditions.Research limitations/implications – A major limitation of the research was that the duration of the research was very short. The turnaround time between the introduction of mind mapping, the implementation of the author's teaching strategies and the final mock examination was just a matter of weeks. The results may be more significant if the same students were retested in six months and again in one year, and this would help the author's research to be more reliable.Origin.
Continuous asr for flexible incremental dialogue

Spoken dialogue systems provide a convenient way for users to interact with a machine using only speech. However, they often rely on a rigid turn taking regime in which a voice activity detection (VAD) module is used to determine when the user is speaking and decide when is an appropriate time for the system to respond. This paper investigates replacing the VAD and discrete utterance recogniser of a conventional turn-taking system with a continuously operating recogniser that is always listening, and using the recogniser 1-best path to guide turn taking. In this way, a flexible framework for incremental dialogue management is possible. Experimental results show that it is possible to remove the VAD component and successfully use the recogniser best path to identify user speech, with more robustness to noise, potentially smaller latency times, and a reduction in overall recognition error rate compared to using the conventional approach.
Identification of BLyS (B Lymphocyte Stimulator), a Non-Myelin-Associated Protein, as a Functional Ligand for Nogo-66 Receptor

B lymphocyte stimulator (BLyS), a tumor necrosis factor family protein essential for B cell development, was previously shown to be expressed at an elevated level in the CNS of multiple sclerosis patients. Although it may be involved in CNS diseases, its exact functions in CNS remain unknown. We hypothesize that BLyS may be a negative regulator for neuronal functions. Here Nogo-66 receptor (NgR) is identified as a high affinity receptor for BLyS, which inhibits dorsal root ganglion outgrowth in culture. The inhibition by BLyS can be reversed by a truncated NgR or by removal of glycosylphosphatidylinositol-linked proteins from neurons. More importantly, the inhibitory effect by BLyS is significantly diminished for neurons isolated from NgR−/− mice. Furthermore, expressions of BLyS and NgR are also found to be associated with astrocytes and macrophages/microglial cells at spinal cord injury sites. Thus, BLyS can function independently of myelin-associated inhibitors and likely serves as a redundant NgR ligand that negatively influences axonal outgrowth in CNS.
On imitating Connect-4 game trajectories using an approximate n-tuple evaluation function

The effect of game trajectories on learning after-state evaluation functions for the game Connect-4 is investigated. The evaluation function is approximated using a linear function of n-tuple features. The learning is supervised by an AI game engine, called Velena, within a preference learning framework. A different distribution of game trajectories will be generated when applying the learned approximated evaluation function, which may degrade the performance of the player. A technique known as the Dagger method will be used to address this problem. Furthermore, the opponent playing strategy is a source for new game trajectories. Random play will be introduced to the game to model this behaviour. The method of introducing random play to the game will again form different game trajectories and result in various strengths of play learned. An empirical study of a number of techniques for the generation of game trajectories is presented and evaluated.
Test case prioritization for regression testing based on fault dependency

Test case prioritization techniques involve scheduling test cases for regression testing in an order that increases their effectiveness at meeting some performance goal. This is inefficient to re execute all the test cases in regression testing following the software modifications. Using information obtained from previous test case execution, prioritization techniques order the test cases for regression testing so that most beneficial are executed first thus allows an improved effectiveness of testing. One performance goal, rate of dependency detected among faults, measures how quickly dependency among faults are detected within the regression testing process. An improved rate of fault dependency can provide faster feedback on software and let developers start debugging on the severe faults that cause other faults to appear later. This paper presents the new metric for assessing rate of fault dependency detection and an algorithm to prioritize test cases. Using the new metric the effectiveness of this prioritization is shown comparing it with non-prioritized test case. Analysis proves that prioritized test cases are more effective in detecting dependency among faults.
Illumination invariant and rotational insensitive textural representation

We propose an illumination invariant and rotation insensitive texture representation based on a Markovian textural model. A texture is aligned with its dominant orientation and textural features are derived from fast analytical estimates of Markovian statistics. We do not require any knowledge of illumination direction or spectrum. This makes our method suitable for computer analysis of real scenes, where appearance of materials depends on their orientation towards the illumination source. Our method is tested on the most realistic visual representation of natural materials - the bidirectional texture function (BTF), using data from the CUReT database, where it outperforms the alternative leading illumination invariant Local Binary Patterns (LBP) and texton MR8 methods, respectively.
The Role of TRP Proteins in Mast Cells

Transient receptor potential (TRP) proteins form cation channels that are regulated through strikingly diverse mechanisms including multiple cell surface receptors, changes in temperature, in pH and osmolarity, in cytosolic free Ca2+ concentration ([Ca2+]i), and by phosphoinositides which makes them polymodal sensors for fine tuning of many cellular and systemic processes in the body. The 28 TRP proteins identified in mammals are classified into six subfamilies: TRPC, TRPV, TRPM, TRPA, TRPML, and TRPP. When activated, they contribute to cell depolarization and Ca2+ entry. In mast cells, the increase of [Ca2+]i is fundamental for their biological activity, and several entry pathways for Ca2+ and other cations were described including Ca2+ release activated Ca2+ (CRAC) channels. Like in other non-excitable cells, TRP channels could directly contribute to Ca2+ influx via the plasma membrane as constituents of Ca2+ conducting channel complexes or indirectly by shifting the membrane potential and regulation of the driving force for Ca2+ entry through independent Ca2+ entry channels. Here, we summarize the current knowledge about the expression of individual Trp genes with the majority of the 28 members being yet identified in different mast cell models, and we highlight mechanisms how they can regulate mast cell functions. Since specific agonists or blockers are still lacking for most members of the TRP family, studies to unravel their function and activation mode still rely on experiments using genetic approaches and transgenic animals. RNAi approaches suggest a functional role for TRPC1, TRPC5, and TRPM7 in mast cell derived cell lines or primary mast cells, and studies using Trp gene knock-out mice reveal a critical role for TRPM4 in mast cell activation and for mast cell mediated cutaneous anaphylaxis, whereas a direct role of cold- and menthol-activated TRPM8 channels seems to be unlikely for the development of cold urticaria at least in mice.
The Work of Endre Szemerédi

Endre Szemerédi is famous for his work in combinatorics and theoretical computer science. He has published a very large number of papers, often involving extraordinarily intricate arguments, so it will not be possible in an article such as this to do justice to either the breadth or the depth of his work. Instead, therefore, I shall describe a representative sample of his best known theorems, and attempt to convey in an informal way some of the ideas that go into their proofs. The sample will consist of the following results. (The dates given below and throughout the paper are the dates of publication rather than the dates that the results were actually proved.)
Performance evaluation of the 6LoWPAN protocol on MICAz and TelosB motes

For wireless sensor networks to reach their full potential they need to be able to interoperate with external IPv6 based networks. This can be achieved using the light-weight 6LoWPAN (IPv6 over Low power Wireless Personal Area Networks) communications protocol that has been designed to operate within the limited processing, memory and energy power constraints associated with Wireless Sensor Networks. In this paper the TinyOS Berkeley 6LoWPAN implementation is configured, deployed and tested on both the MICAz and the TelosB sensor architectures. A performance evaluation of point-to-point communications from a computer to a sensor mote is then carried out over an IPv6/6LoWPAN network.
Modelling the market for bandwidth.

This paper investigates methods for describing pricing and agent behaviour in the burgeoning market for bandwidth capacity on networks. Two contrasting views of this market are examined. Initially the application of traditional methods of mathematical finance are explored, to model prices for the actual physical infrastructure over which data is transmitted. Secondly the existence of an instantaneous market for bandwidth is discussed, and optimisation methods are used to obtain prices for forward bandwidth contracts. Possible extensions and current problems with both methodologies are discussed.
A comparison of front-end configurations for robust speech recognition

This paper presents a comparative analysis of the processing stages involved in feature extraction for speech recognition. Feature extraction is considered as comprising three different processing stages; namely static feature extraction, normalisation and inclusion of temporal information. In each stage a comparison of techniques is made, both theoretically and in terms of their comparative performance. The analysis shows that while some techniques may appear significantly different, upon analysis the effect they have on the signal can be similar. Comparative studies include MFCC and PLP analysis, RASTA filtering and cepstral mean normalisation, and temporal derivatives and cepstral-time matrices. Experimental results, on an unconstrained monophone task, compare recognition performance using different front-end configurations.
Secured architecture for inter-VM traffic in a Cloud environment

Cloud Computing (CC) is a large-scale distributed computing paradigm that is driven by economies of scale, in which a pool of abstracted, virtualized, dynamically-scalable, managed computing power, storage, platforms, and services are delivered on demand to external customers over the Internet. On the other hand, one of the key enablers for building Cloud environments is Virtualization. It offers a great level of efficiency and scalability that makes the complex processing of the Cloud possible. However, with these advantages come certain limitations, especially in relation to security. Virtualization vulnerabilities and more specifically isolation, creates new targets for intrusion due to the complexity of access and difficulty in monitoring all interconnection points between systems, applications, and data sets. Hence, without strict controls put in place within the Cloud, guests could violate and bypass security policies, intercept unauthorized client data, and initiate or become the target of security attacks. This article discusses the security and the visibility issues of inter-VM traffic, by proposing a solution for it within the Cloud context. The proposed approach provides Virtual Machines (VMs) authentication, communication integrity, and enforces trusted transactions, through security mechanisms, structures, policies, and various intrusion detection techniques.
The Open Government Data Policy as a Strategic Use of Information to Entrench Neoliberalism? The Case of Italy

The philosophy of Open Government provides a new paradigm of innovation in public admin-istration built around three key words: transparency, participation and collaboration. Greater transparency of information about the PA and its way of working should help to regain public confidence in the institu-tions, motivating people to take a more active part in decision making processes. It should also encourage them to support the institutions by inputting their own knowledge and abilities, consequently engendering a widespread spirit of collaboration between different public authorities and between them and the pub-lic, businesses and non profit organisations, in order to relaunching the economic value of the Public Sec-tor Information (Huijboom, Van den Broek, 2011). The hypothesis behind this contribution, starting from an approach based on an interpretation of significant elements in public action (Moini 2013) and of their conceptual framework (Fischer 2003), is that through which open government, open data, social media, collective intelligence, and connectivity are key words in a new rhetoric of administrative innovation - summed up in the label ‘’government 2.0’’ - which refers to a form of public action easily seen to be drawn from the neoliberal paradigm (Jessop, 2002), even though subject to some variegated form at na-tional level
Grants versus Loans for Development Banks

In recent years, economists have increasingly debated whether multilateral development banks, such as the World Bank, should switch from making subsidized loans to giving outright grants. It is no small question. The combined loans of the World Bank Group and brethren regional entities such as the Asian and Inter-American Development Banks, approach $300 billion. Their funds constitute a main channel through which rich country governments provide assistance to developing country governments. In Bulow and Rogoff (1990), we first developed the case for a shift to outright grants. We argued that under the status quo, a vastly disproportionate share of aid goes to middle income countries via disguised interest subsidies, rather than to the poorest countries. We also argued that a shift to grants would protect donor banks from sometimes having to play a “bad cop” role when trying to collect net repayments rather than fully rolling over loans. The “Meltzer Commission” (International Financial Institution Advisory Commission, 2000) report on government sponsored international lending institutions famously took a similar view. Supporters of the status quo often argue that development bank loans to middle income countries are in fact highly profitable, and are essential for allowing institutions like the World Bank to subsidize aid to poor countries. We shall argue that the Bank’s profitability is an accounting artifice that greatly underestimates the risks of the Bank’s portfolio. Another argument for loans is that multilateral development banks have a superior enforcement technology that helps international debt markets to function more efficiently. Thus loans allow financially strapped governments, including in middle-income countries, to borrow more than they could otherwise. We will argue that this benefit, too, is an illusion. In those cases when official lending does expand a developing country government’s borrowing capacity, it effectively enables the government to commit the country to repayment levels beyond that supported by domestic political consensus, creating moral hazard for shortsighted rulers. In theory, better credit access to finance, say, public infrastructure projects can be highly beneficial. In practice, however, the increased risk of debt crisis all too often outweighs any gain ordinary citizens might enjoy from the loans. Furthermore, moral hazard on the part of lenders, who may be able to induce rich countries into subsidizing the bailout of troubled middle-income borrowers, may mean that aggregate lending is excessive even if multilaterals merely displace equivalent private debt. We do not argue for eliminating assistance to middle-income countries. On the contrary, we would favor expanding aid in general, albeit in far greater proportion to the world’s poorest countries. Note that in principle, any country with market access could use grant flows to help defray interest rate costs on loans if it so chose, but development banks would never need to assume a “bad cop” role in enforcing debt.
Compression-based document length prior for language models

The inclusion of document length factors has been a major topic in the development of retrieval models. We believe that current models can be further improved by more refined estimations of the document's scope. In this poster we present a new document length prior that uses the size of the compressed document. This new prior is introduced in the context of Language Modeling with Dirichlet smoothing. The evaluation performed on several collections shows significant improvements in effectiveness.
Analyzing the Device Discovery Phase of Bluetooth Scatternet Formation Algorithms

we study in this paper the impact of the modifications introduced in version 1.2 of the Bluetooth specifications on Bluetooth Scatter net Formation (BSF) algorithms. Up to now, the effect of these modifications on BSF algorithms had not been analyzed. We show that: 1) Bluetooth ver1.2 and upward have a major positive effect on static BSF algorithms (i.e. those which require an external device discovery phase). We conducted some experiments on a common device discovery technique for static BSF algorithms and compared its performance using Ver1.2 and Ver1.1 (the latter is used in most BSF studies). We found that this technique, using ver1.2, generates a connected topology about 3.5 times faster than it does using ver1.1. It also discovers about 20% more edges. 2) Dynamic algorithms, on the other hand, are not affected by these modifications. This will be proven using some experiments and some analytical arguments. These results give more applicability to static BSF algorithms and call for more research on dynamic BSF algorithms.
Unknown place name detection base on YamCha for Japanese guidance QA system

We perform a research about Japanese sightseeing guidance question answering (QA) system. In this domain web information retrieval approach is always being used. However for the web information retrieval, Japanese unknown place word detection needs to be considered. Some famous places are known very well, such as "Kinkaku-ji", it can be recognized by morphological analysis. However, the recognition rate of Japanese complex place is so poor. Therefore, we proposed an approach of the Japanese unknown place word detection. We use YamCha, a tool based on Support Vector Machines (SVMs). The goal is that we want to recognize the unknown sightseeing spots word from user's question. In the experiment of Japanese place word detection we have got excellent precision and recalling rates.
Improved weak labels using contextual cues for person identification in videos

Fully automatic person identification in TV series has been achieved by obtaining weak labels from subtitles and transcripts [11]. In this paper, we revisit the problem of matching subtitles with face tracks to obtain more assignments and more accurate weak labels. We perform a detailed analysis of the state-of-the-art showing the types of errors during the assignment and providing insights into their cause. We then propose to model the problem of assigning names to face tracks as a joint optimization problem. Using negative constraints between co-occurring pairs of tracks and positive constraints from track threads, we are able to significantly improve the speaker assignment performance. This directly influences the identification performance on all face tracks. We also propose a new feature to determine whether a tracked face is speaking and show further improvements in performance while being computationally more efficient.