Miracle-dz/UniFAR-FTUs huggingface dataset:
User-centred evaluation of an e-learning repository

The aim of this paper is to reflect on the evaluation of DELTA, a distributed learning resources repository. We employed scenarios and claims analysis techniques so as to derive assessable evaluation goals. These goals were related to three quality dimensions: quality of use, pedagogical effectiveness and acceptability for the end-users. We employed a set of six quantitative and qualitative research methods and triangulated the results obtained. The results demonstrate that DELTA met around half of the evaluation goals. This project was an opportunity to reflect on the degree of fitness for purpose of our methods. Two of the qualitative methods employed (user diaries and pedagogy workshop) were particularly effective in the triangulation process.
Development and Validation of AMANDA, a New Algorithm for Selecting Highly Relevant Regions in Molecular Interaction Fields

Descriptors based on Molecular Interaction Fields (MIF) are highly suitable for drug discovery, but their size (thousands of variables) often limits their application in practice. Here we describe a simple and fast computational method that extracts from a MIF a handful of highly informative points (hot spots) which summarize the most relevant information. The method was specifically developed for drug discovery, is fast, and does not require human supervision, being suitable for its application on very large series of compounds. The quality of the results has been tested by running the method on the ligand structure of a large number of ligand-receptor complexes and then comparing the position of the selected hot spots with actual atoms of the receptor. As an additional test, the hot spots obtained with the novel method were used to obtain GRIND-like molecular descriptors which were compared with the original GRIND. In both cases the results show that the novel method is highly suitable for describing ligand-receptor interactions and compares favorably with other state-of-the-art methods.
Heterogeneity of I K 1 in the mouse heart

Panama BK, McLerie M, Lopatin AN. Heterogeneity of IK1 in the mouse heart. Am J Physiol Heart Circ Physiol 293: H3558–H3567, 2007. First published September 21, 2007; doi:10.1152/ajpheart.00419. 2007. — Previous studies have shown that cardiac inward rectifier potassium current (IK1) channels are heteromers of distinct Kir2 subunits and suggested that speciesand tissue-dependent expression of these subunits may underlie variability of IK1. In this study, we investigated the contribution of the slowly activating Kir2.3 subunit and free intracellular polyamines (PAs) to variability of IK1 in the mouse heart. The kinetics of activation was measured in Kir2 concatemeric tetramers with known subunit stoichiometry. Inclusion of only one Kir2.3 subunit to a Kir2.1 channel led to an approximate threefold slowing of activation kinetics, with greater slowing on subsequent additions of Kir2.3 subunits. Activation kinetics of IK1 in both ventricles and both atria was found to correspond to fast-activating Kir2.1/Kir2.2 channels, suggesting no major contribution of Kir2.3 subunits. In contrast, IK1 displayed significant variation in both the current density and inward rectification, suggesting involvement of intracellular PAs. The total levels of PAs were similar across the mouse heart. Measurements of the free intracellular PAs in isolated myocytes, using transgenically expressed Kir2.1 channels as PA sensors, revealed “microheterogeneity” of IK1 rectification as well as lower levels of free PAs in atrial myocytes compared with ventricular cells. These findings provide a quantitative explanation for the regional heterogeneity of IK1.
Attentive Interfaces for Multiple Monitors

The use of multiple monitors is becoming popular but it creates problems for pointer movement, window management, and control of applications. We suggest combining the standard input devices of keyboard and mouse with attentive user interface techniques. A user’s work with conventional input devices will naturally be based around a focal region, but that focus can be rapidly transferred in response to attentive input.
Labor markets in developing countries

This chapter covers selected topics for the 80% of the world's labor force that works in the developing countries. These topics are ones that have: (1) received relatively great attention in developing countries compared to developed economies (i.e., family enterprises, missing labor markets, geographical mobility, health/nutrition effects on productivity) because of their greater importance in developing countries; (2) been considered more extensively for developing than developed labor markets because the nature of institutions, behaviors and available data permit more extensive empirical examination of these topics (i.e., labor adjustments to shocks in the presence of imperfect markets, information problems in labor markets), and (3) been considered extensively for both developing and developed economies but with some different approaches and results for part of the developing country literature (e.g., determinants of and labor market returns to schooling). The discussion is organized around five broad topics: (1) The household enterprise model, surplus labor, disguised employment and unemployment, complete markets and separability, and labor supplies; (2) labor contracts, risks and incentives; (3) determinants of and returns to human capital investments (including health and nutrition in addition to schooling); (4) urban labor markets, labor-market regulations, international trade policies and manufacturing; and (5) distribution and mobility.
Capacity analysis of relay channels for medium voltage powerline access network

To ensure the reliable data communication and increase the efficiency of resources which is an essential requirement for the future smart grid services, this paper describes a cooperative relaying scheme for the medium voltage (MV) powerline access network. We analyze the capacity of cooperative relaying protocol over the MV powerline channel model. Numerical results show that the cooperative relaying protocol introduces a notable capacity increase compared with conventional schemes.
Abstract of Thesis Object Matching in Disjoint Cameras Using a Color Transfer Approach Object Matching in Disjoint Cameras Using a Color Transfer Approach Name Date Thesis Object Matching in Disjoint Cameras Using a Color Transfer Approach Thesis

OF THESIS OBJECT MATCHING IN DISJOINT CAMERAS USING A COLOR TRANSFER APPROACH Object appearance models are a consequence of illumination, viewing direction, camera intrinsics, and other conditions that are specific to a particular camera. As a result, a model acquired in one view is often inappropriate for use in other viewpoints. In this work we treat this appearance model distortion between two non-overlapping cameras as one in which some unknown color transfer function warps a known appearance model from one view to another. We demonstrate how to recover this function in the case where the distortion function is approximated as general affine and object appearance is represented as a mixture of Gaussians. Appearance models are brought into correspondence by searching for a bijection function that best minimizes an entropic metric for model dissimilarity. These correspondences lead to a solution for the transfer function that brings the parameters of the models into alignment in the UV chromaticity plane. Finally, a set of these transfer functions acquired from a collection of object pairs are generalized to a single camera-pair-specific transfer function via robust fitting. We demonstrate the method in the context of a video surveillance network and show that recognition of subjects in disjoint views can be significantly improved using the new color transfer approach.
Fast speech decoding through phone confusion networks

We present a two stage automatic speech recognition architecture suited for applications, such as spoken document retrieval, where large scale language models can be used and very low out-of-vocabulary rates need to be reached. The proposed system couples a weakly constrained phone-recognizer with a phone-to-word decoder that was originally developed for phrase-based statistical machine translation. The decoder permits to efficiently decode confusion networks in input, and to exploit large scale unpruned language models. Preliminary experiments are reported on the transcription of speeches of the Italian parliament. The use of phone confusion networks as interface between the two decoding steps permits to reduce the WER by 28%, thus making the system perform relatively close to a state-of-the-art baseline using a comparable language model.
Inactivation of the ATMIN/ATM pathway protects against glioblastoma formation

Glioblastoma multiforme (GBM) is the most aggressive human primary brain cancer. Using a Trp53-deficient mouse model of GBM, we show that genetic inactivation of the Atm cofactor Atmin, which is dispensable for embryonic and adult neural development, strongly suppresses GBM formation. Mechanistically, expression of several GBM-associated genes, including Pdgfra, was normalized by Atmin deletion in the Trp53-null background. Pharmacological ATM inhibition also reduced Pdgfra expression, and reduced the proliferation of Trp53-deficient primary glioma cells from murine and human tumors, while normal neural stem cells were unaffected. Analysis of GBM datasets showed that PDGFRA expression is also significantly increased in human TP53-mutant compared with TP53-wild-type tumors. Moreover, combined treatment with ATM and PDGFRA inhibitors efficiently killed TP53-mutant primary human GBM cells, but not untransformed neural stem cells. These results reveal a new requirement for ATMIN-dependent ATM signaling in TP53-deficient GBM, indicating a pro-tumorigenic role for ATM in the context of these tumors. DOI: http://dx.doi. org/10.7554/eLife.08711. 001
Process Communication on Clusters

Clusters of computers promise to be the supercomputers of the future. Traditional mechanisms (in particular communication support) are not suitable anymore. Recent research was directed towards developing thin communication layers that exploit the new features of the hardware and that provides to the upper level up to 90% from the underlying hardware capability. Common mechanisms to di erent approaches include kernel bypassing and \0 copies" memory transfers. Several projects dealing with associated problems exists. We survey four of them.
Text Recognition with k-means Clustering

A thesaurus is a reference work that lists words grouped together according to similarity of meaning (containing synonyms and sometimes antonyms), in contrast to a dictionary, which contains definitions and pronunciations. This paper proposes an innovative approach to improve the classification performance of Persian texts considering a very large thesaurus. The paper proposes a flexible method to recognize and categorize the Persian texts employing a thesaurus as a helpful knowledge. In the corpus, when utilizing the thesaurus the method obtains a more representative set of word- frequencies comparing to those obtained when the method disables the thesaurus. Two types of word relationships are considered in our used thesaurus. This is the first attempt to use a Persian thesaurus in the field of Persian information retrieval. The k-nearest neighbor classifier, decision tree classifier and k-means clustering algorithm are employed as classifier over the frequency based features. Experimental results indicate enabling thesaurus causes the method significantly outperforms in text classification and clustering.
Duration of Displacement Unemployment : Evidence from the GSOEP

This study investigates the duration of unemployment following job displacement. It uses data from the first fourteen sweeps of the German Socio-Economic Panel (GSOEP) survey for the purpose. The paper employs both parametric and non-parametric discretetime models to study the duration of displacement unemployment spells. Alternative mixing distributions have also been used to account for unobserved heterogeneity. Results from single and competing risks models show that the average hazard rate of exit via re-employment declines with the duration of time in unemployment. On the other hand, the average hazard rate of exit via inactivity increases as the duration of unemployment lengthens. Accounting for unobserved heterogeneity does make a difference. Nevertheless, the crux of the results in terms of duration dependence remains unchanged. Comparing displacement and overall unemployment spells, the displaced unemployed have a higher hazard of re-employment and a lower hazard of exit to inactivity. In terms of covariate effects, those at the lower end of the skills ladder, those who had been working in the manufacturing industry and those with previous experience of inactivity are found to have lower hazard of exit via re-employment. That those at the lower end of the skills ladder and those with previous experience of inactivity, who are likely to be dominated by women, have difficulty exiting unemployment calls for appropriate intervention to ameliorate the lot of the ‘disadvantaged’. Theme: Microeconomics of unemployment
Colony-RAN architecture for future cellular network

Mobile data traffic has been increasing at a rapid pace over the past few years due to the rise of both smartphones and tablets. To accommodate such a huge traffic volume in cellular systems, it is imperative to reduce cell size to increase system capacity. To reduce cell size, the main issue confronting mobile network operators is system cost to provide coverage areas with small cells. Therefore, we propose a suitable RAN architecture for deploying small cells. First, a base band is physically separated into one baseband unit (BBU) and remote radio heads (RRHs). The BBUs are centralized in some locations. One BBU can connect to one or more RRHs. Such a network architecture, which we call Colony-RAN due to its ability to flexibly change cell layout, can dynamically change the connections of BBUs and RRHs in respect to traffic demand. As a result, because traffic distribution is non-uniform, Colony-RAN can drastically reduce the number of BBUs due to the statistical multiplexing effect. As a rough estimation based on the population of the Tokyo metropolitan area, we confirmed that the number of BBUs can be reduced by 75% with the co-located BBU and RRHs compared with conventional cellular systems. Another characteristic of Colony-RAN is its ability to reduce inter-cell interference and increase link quality by accommodating several RRHs in the same BBU taking user mobility and/or user distributions into consideration.
Robust technique for the detection of Acute Lymphoblastic Leukemia

The counting and classification of blood cells helps in diagnosing a vast number of blood diseases. One type of hematological neoplasia which is most common among those blood diseases is Acute Lymphoblastic Leukemia (ALL) and it mostly occurs in the age group of 3-7. The characterization of ALL is done by rapid and uncontrolled growth of immature leukemic cells (also named as blast cells) mainly in bone marrow and lymphoid organs. The primary step in the diagnosis of ALL is the morphological analysis of the bone marrow and blood smear under the microscope. Valuable information is provided by the features extracted from the blood cells for the confirmation of the diagnosis. Nowadays, this is performed manually by experienced operators. The process have numerous drawbacks, such as non-standard accuracy, dependency on the operator skills and time consuming too. A computerized system will be helpful for the analysis of stained microscopic images of the blood cells for quantitative examination. This paper demonstrates a method using morphological operations in MATLAB to segment images and compare between different classifiers to perfectly diagnose the presence of ALL in blood smear.
Techniques for computing on encrypted data in a practical system

In this document, we survey various techniques for computing on encrypted data that might be useful when designing a practical security system. These tools or methods provide an interesting spectrum over three coordinates: functionality, security, and performance. Unfortunately, none of these tools alone suffices to enable running the systems we have today over encrypted data. They typically fail to achieve a desired goal with respect to at least one of these three coordinates. Nevertheless, understanding the tradeoffs these tools provide in functionality, security, and performance, coupled with an understanding of the targeted system, has enabled building systems that are practical for a class of applications and provide a meaningful level of security. Some examples of such systems are [PRZB11, PSV+14, ABE+13, AEK+13, TKMZ13, TLMM13, KGM+14, SSSE14, TSCS13, HHCW12, KKM+13]. Hence, below we describe each tool or method from a functionality, security and performance standpoint, describing the tradeoff it strikes in this space, and the settings in which it might be practical. Since our focus is this tradeoff, we keep the cryptographic presentation of each tool informal, and instead reference outside formal presentations. We divide these tools and methods in two categories: tools that leak (virtually) nothing about the data and tools that reveal a well-defined function of the data. Many times, the information revealed in the second category helps improve performance drastically.
Clustering for collaborative filtering applications

Collaborative (cid:12)ltering systems assist users to identify items of interest by providing predictions based on ratings of other users. The quality of the predictions depends strongly on the amount of available ratings and collaborative (cid:12)ltering algorithms perform poorly when only few ratings are available. In this paper we identify two important situations with sparse ratings: Bootstrapping a collaborative (cid:12)ltering system with few users and providing recommendations for new users, who rated only few items. Further, we present a novel algorithm for collaborative (cid:12)ltering, based on hierarchical clustering, which tries to balance robustness and accuracy of predictions, and experimentally show that it is especially e(cid:14)cient in dealing with the previous situations.
An architectural framework for web information retrieval based on user's navigational pattern

As the popularity of WWW explodes, a massive amount of data is gathered by Web servers in the form of Web access logs which are rich source of information for understanding the Web user's surfing behavior. Web Usage Mining is an application of data mining algorithms to Web access logs to find trends and regularities in Web users' traversal pattern. Web page prediction technique is an important research area in web technologies. Mining is useful for web path traversal pattern from web logs. Web traversal pattern mining discovers most of the users' access patterns from web logs. This information can provide the routing suggestions for web users such that suitable actions can be adopted. However, the web data will grow speedily in the short time, and some of the web data may be out of date. The user behaviors may change when old web data in web logs is replaced by new data. Therefore, we must re-discover the user behavior from the updated web logs but, it is very time-consuming. In this work we present efficient algorithms for web page prediction from large web logs visited by a user. We assign a significant weight to each page based on time spent by user on each page and visiting frequency on each page.
Experimental Analysis of a Class of Approximation Algorithms for Belief Network Inference

The exact inference on probabilistic networks is finding posterior marginal probabilities conditioned on evidence. This problem is known to be NP-Hard. There are a myriad of approximation algorithms for the same problem. Randomized algorithms are one class of such approximation algorithms. Randomized algorithms also fail in computational efficiency particularly when there are extreme probability values in the network. We take up a particular stochastic sampling algorithm, called the AA algorithm and scrutinize on it in an experimental setting. The AA algorithm has already been shown to guarantee polynomial convergence for a larger class of networks than other randomized algorithms. The approximation has been proved to be “optimal” using a constant c. This universal constant is dependent on network properties. In this paper, we aim to find the optimal value of c depending on the network properties. The constant c linearly affects the computational effort of the algorithm. We describe a procedure to obtain a reasonable c value for any given network.
Soft Information Relaying for Wireless Networks with Error- Prone Source-Relay Link

Relays in wireless networks can be used to decrease transmit power while additionally increasing diversity. Distributed turbo coding as a special case of decode-and-forward is very powerful in relay networks when assuming error free decoding in the relay. In practical wireless networks, however, this assumption is only justifiable if an ARQ protocol is applied which leads to lower throughput. Soft-reencoding and transmission of the reliability of reencoded bits helps the destination to decode the message. Reencoding in the relay with a recursive convolutional code as used for turbo-codes, can lead to error propagation. In this paper the effects of error propagation in relay networks are investigated and more suitable distributed coding schemes are presented for soft-reencoding. As the often used assumption of Gaussian distributed disturbance at the destination is not valid for the considered system setup, the calculation of Log-Likelihood-Ratios (LLR) for the received noisy reliability information is derived analytically.
Handling of Incident , Challenges , Risks , Vulnerability and Implementing Detection approaches inside the Cloud

: In a malicious cloud system, handling of incident, challenges and risks, is an integral part of security management. In this paper we discuss various detection and analysis of security incidents as well as the subsequent response (i.e., containment, eradication, and recovery.) On side of existing processes and methods for incident and risk handling is geared towards infrastructures and operational models that will be increasingly outdated by cloud computing. So to update these systems on time to time, we need to discuss some risks and incident inside the cloud. Cloud computing is a computing paradigm which provides services and data from a shared resources from scalable data centers, and the services and data are accessible by any authenticated device over the Internet. Hence this paper discusses how to handle the changes in a cloud computing environment which is influenced via various incident, risks and challenges. It identifies problems that cloud customers encounter in each of the incident and risks handling steps and provides possible approaches and corresponding challenges to get the reliable service from cloud provider. The identified approaches provide guidance for cloud customers and cloud service providers towards handling of incidents and risks in the cloud; the identified challenges may serve as basis for a research agenda in cloud incident handling in future.