Miracle-dz/UniFAR-FTUs huggingface dataset:
Recommendation systems: a joint analysis of technical aspects with marketing implications

In 2010, Web users ordered, only in Amazon, 73 items per second and massively contribute reviews about their consuming experience. As the Web matures and becomes social and participatory, collaborative filters are the basic complement in searching online information about people, events and products. In Web 2.0, what connected consumers create is not simply content (e.g. reviews) but context. This new contextual framework of consumption emerges through the aggregation and collaborative filtering of personal preferences about goods in the Web in massive scale. More importantly, facilitates connected consumers to search and navigate the complex Web more effectively and amplifies incentives for quality. The objective of the present article is to jointly review the basic stylized facts of relevant research in recommendation systems in computer and marketing studies in order to share some common insights. After providing a comprehensive definition of goods and Users in the Web, we describe a classification of recommendation systems based on two families of criteria: how recommendations are formed and input data availability. The classification is presented under a common minimal matrix notation and is used as a bridge to related issues in the business and marketing literature. We focus our analysis in the fields of one-to-one marketing, network-based marketing Web merchandising and atmospherics and their implications in the processes of personalization and adaptation in the Web. Market basket analysis is investigated in context of recommendation systems. Discussion on further research refers to the business implications and technological challenges of recommendation systems.
Rain Streaks Removal from Single Image

: Rain Removal from Video is a challenging problem and has been recently investigated extensively. In this paper, we propose a single-image-based rain removal framework via properly formulating rain removal as an image decomposition problem based on morphological component analysis (MCA). Instead of directly applying conventional image decomposition technique, we first decompose an image into the low-frequency and high-frequency parts using a bilateral filter. The high-frequency part is then decomposed into “rain component” and “non-rain component” by performing dictionary learning and sparse coding. As a result, the rain component can be successfully removed from the image while preserving most original image details. Experimental results demonstrate the efficacy of the proposed algorithm. Rain introduces sharp intensity variations in images, which degrade the quality or performance of outdoor vision systems. These intensity variations depend on various factors, such as the brightness of the scene, the properties of rain, and the camera parameters. The detection and removal of rain streaks in an image is done by image decomposition which depends on Morphological Component Analysis (MCA) by performing dictionary learning and sparse coding.
Do wireless data signals exhibit spectral autocorrelation?

Signal spectra of wireless data systems are well known to be uncorrelated provided the communicated data sequence itself is white. However, multiplicative processes in wireless transmission systems and multipath fading channels produce spectral correlation. This paper shows that, where spectrum sensing opportunities are short in duration, the sample vector spectrum covariance matrix typically remains purely diagonal. It is also shown that signal spectra may be somewhat correlated in instances where the channel Doppler spread is severe, or where the measurement system has resolution bandwidth smaller than that of the wireless data system.
6 X 6 Playfair Cipher using LFSR based Unique Random Number Generator

Playfair cipher is the well-known multiple letter encryption cipher. Here the digraphs in the plaintext are treated as single units and converted into corresponding cipher text digraphs. However because of the drawbacks inherent in the 5 X 5 Playfair cipher which adversely affects the security we proposed a 6 X 6 Playfair cipher and then coupled it with Linear Feedback Shift Register based Unique Random Number Generator [1]. 6 X 6 Playfair cipher supports all 26 alphabets (A-Z) and 10 digits (0-9) which eliminate the limitation of 5 X 5 Playfair in which “i” and “j” both character could not appear at the same time [2, 3]. LFSR not only enhances the security up to a considerable level by generating random sequences but also provides a much faster rate of encryption and decryption [1], that’s why LFSR based Unique Random Number Generator is chosen for the consideration. This paper deals in with the security issues of the new proposed system. Various types of cryptography attacks have been taken under consideration for original Playfair cipher but not vulnerable for this proposed cipher.
Adaptive reverberation cancelation for multizone soundfield reproduction using sparse methods

The necessity of a large number of loudspeaker-microphone channels for the existing sound rendering systems complicates the application of multizone soundfield reproduction in reverberant environments. We introduce an adaptive reverberation cancelation method for multizone soundfield reproduction using sparse methods. The reproduced soundfield is described as a weighted series of orthonormal basis functions over the desired reproduction region, which is then used to adaptively equalize the desired multizone soundfield in terms of the basis function coefficients. The sparse methods result in a significantly reduced number of the required microphones for the measuring process of the reproduced soundfield. Simulation results verify the efficient room reverberation compensation for desired multizone soundfield reproduction. The proposed method also facilitates reproduction over a wide frequency range.
Performance Analysis of Counter-Based Broadcast Scheme for Mobile Ad Hoc Networks

Broadcasting is a technique used for distributing of control packets in mobile ad hoc networks (MANETs), where source node diffuses a message to all other nodes in the network. Flooding is the simplest mechanism used for broadcasting in MANETs. Despite its simplicity, it can result in high redundant retransmission, contention and collision, a phenomenon called broadcast storm problem. In view of this, several schemes where proposed with aim to mitigate this problem, among which is the counter based scheme. It relies on counter threshold value for rebroadcast decision. The selection of an appropriate counter is crucial to the performance of the scheme. How, previous studies have focused on the choice of optimal counter threshold-value using network setting with very low traffic load. In this paper, we focus on the effect of the counter threshold value on the performance of counter-based scheme in terms of number saved rebroadcast nodes and reachability using Ns-2 simulation under varying condition of network density and traffic load. The results have shown that an optimal counter threshold is network density dependent.
Are Cash Earnings Disclosures Valuable?

In this paper, we examine the relative information content of two cash earnings measures (earnings with amortization of intangibles added back and earnings before interest, taxes, depreciation, and amortization), one traditional accrual accounting earnings measure (earnings before extraordinary items), and one traditional cash flow measure (cash flow from operations). Our research is motivated by the increasing use of these cash earnings disclsoures and the perceived additional value they provide. Overall, we find results consistent with previous research that nothing beats accrual earnings in its ability to explain market-adjusted returns. In addition, and again consistent with prior literature, we find that as each measure moves further away from accrual accounting earnings and closer to cash flows, the explanatory power of the measure decreases. We do find, however, that the information content rank ordering of our four measures reverse when we perform our tests on only firms' loss-year observations, although there is no statistical significance between the measures in their relative information content. We further explore the loss-year sub-sample by examining cases in which the loss includes a large amortization charge. Within this sub-sample, the cash flow measures dominate. In fact, each of the two cash earnings measures provides significantly greater information content than does accounting earnings. The provides evidence that these disclosures may have value in certain settings.
WCET-Aware Optimization of Shared Cache Partition and Bus Arbitration for Hard Real-Time Multicore Systems

In recent years, multicore processors have been receiving a significant amount of attention from avionic and automotive industries as the demand for high-end real-time applications drastically increases. However, the unpredictable worst-case timing behavior that mainly arises from shared resource contention in current multicore architectures has been the biggest stumbling block for a widespread use of multicores in hard real-time systems. A great deal of research efforts have been devoted to address the issue. Among others, the development of a new multicore architecture has emerged as an attractive solution because it is possible to eliminate the sources of unpredictable interferences in the first place, or at least to turn them into predictable ones. Accordingly, this opens a new possibility of system-level optimizations with multicore-based hard real-time systems. To address this issue, this study proposes a new perspective of WCET model called tunable WCET, in which the WCET of a task is partitioned into fixed execution time and tunable delay. Our tunable WCET model enables WCET-aware shared resource allocation/arbitration by elastically deforming the tunable delays of tasks. For this, we also propose novel shared bus arbitration and cache partitioning methods called harmonic round-robin bus scheduling and two-level cache partitioning. We present a mixed integer linear programming (MILP) formulation as the solution to the optimization problem of tunable WCETs. Our experimental results show that the proposed methods can significantly lower overall system utilization.
Estimation of boreal forest biomass using spaceborne SAR systems

The authors report on the use of a semi-empirical algorithm derived from a two layer radar backscatter model for forest canopies. The model stratifies the forest canopy into crown and stem layers, separates the structural and biometric attributes of the canopy. The structural parameters are estimated by training the model with polarimetric SAR (synthetic aperture radar) data acquired over homogeneous stands with known above ground biomass. Given the structural parameters, the semi-empirical algorithm has four remaining parameters, crown biomass, stem biomass, surface soil moisture, and surface rms height that can be estimated by at least four independent SAR measurements. The algorithm has been used to generate biomass maps over the entire images acquired by JPL AIRSAR and SIR-C SAR systems. The semi-empirical algorithms are then modified to be used by single frequency radar systems such as ERS-1, JERS-1, and Radarsat. The accuracy of biomass estimation from single channel radars is compared with the case when the channels are used together in synergism or in a polarimetric system.
Integrating Low-Cost Rapid Usability Testing into Agile System Development of Healthcare IT: A Methodological Perspective

The development of more usable and effective healthcare information systems has become a critical issue. In the software industry methodologies such as agile and iterative development processes have emerged to lead to more effective and usable systems. These approaches highlight focusing on user needs and promoting iterative and flexible development practices. Evaluation and testing of iterative agile development cycles is considered an important part of the agile methodology and iterative processes for system design and re-design. However, the issue of how to effectively integrate usability testing methods into rapid and flexible agile design cycles has remained to be fully explored. In this paper we describe our application of an approach known as low-cost rapid usability testing as it has been applied within agile system development in healthcare. The advantages of the integrative approach are described, along with current methodological considerations.
The Role of Climatic Change in the Evolution of Mammals

ABSTRACT The paleontological record of mammals offers many examples of evolutionary change, which are well documented at many levels of the biological hierarchy—at the level of species (and above), populations, morphology, and, in ideal cases, even genes. The evolutionary changes developed against a backdrop of climatic change that took place on different scales, from rapid shifts in climate state that took only a few decades, to those that occurred over a millennial scale, to regular glacial–interglacial transitions with cycles of roughly a hundred thousand years, to long-term warming or cooling trends over hundreds of thousands to millions of years. Are there certain scales of climatic change that accelerate evolution? And what will the current global warming event do to evolutionary rates? Here we use paleontology—the study of fossils—to illustrate the scientific method behind answering such complex questions, and to suggest that current rates of global warming are far too fast to influence evolution much and instead are likely to accelerate extinctions.
Genetic Adaptation to Optimal Membership Functions for Modelling with B -Splines

This paper proposes a comprehensive approach on automatic optimisation of B-spline based neuro-fuzzy models. The underlying structure of a system decided by the displacements of the membership functions is an important factor for its generalisation ability and output accuracy. Therefore a genetic algorithm is introduced which is used to find a suitable model for an arbritrary given problem. Approximation of benchmark test functions shows that our approach beats the models using other set functions.
Model Photospheres for Late-Type Stars from the Inversion of High-Resolution Spectroscopic Observations: The Sun

An inversion technique has been developed to recover LTE, one-dimensional, model photospheres for late-type stars from very high resolution, high signal-to-noise ratio stellar line profiles. It is successfully applied to the Sun by using a set of clean Ti I, Ca I, Cr I, and Fe I normalized line profiles with accurate transition probabilities, taking advantage of the well-understood collisional enhancement of the wings of the Ca I line at 6162 A. Line and continuum center-to-limb variations, continuum flux, and wings of strong metal lines are synthesized by means of the model obtained and are compared with solar observations, as well as with predictions from other well-known theoretical and empirical solar models, showing the reliability of the inversion procedure. The prospects for and limitations of the application of this method to other late-type stars are discussed.
Accelerating IEEE 1857 Deblocking Filter on GPU Using CUDA

In IEEE 1857/AVS decoder, the deblocking filter is one of the most time consuming tasks and it accounts for nearly 30% of the decoder complexity. Due to data dependence in the process of filtering, it is a big challenge to execute deblocking filter in parallel efficiently. In this paper, a parallel algorithm is proposed, which hides the data dependence by dividing a frame into several 8 × 8 Intersection-blocks. The proposed parallel deblocking filter algorithm is implemented on GPU using CUDA. Experimental results of processing 1920 × 1080 video streams show that the proposed CUDA deblocking filter implementation accelerates traditional CPU implementation by 6~8 times.
Market Segmentation in the Tourism Industry and Consumers' Spending

Abstract Despite the unabated pace of globalisation and the incessant flow of tourists to multiple tourist destinations, there is little attention paid by tourist operators and hospitality managers to the segmentation of holiday makers based on their distinctive spending habits for revenue maximization. Segmenting holiday makers according to their levels of expenditure is an important factor in developing comprehensive marketing strategies since travellers who decide to spend a vacation in the same area and in the same period might spend their money in very different ways. This paper uses the CHAID technique to examine direct as well as daily tourist expenditures of holiday makers in Hong Kong to define market segments (particularly, the big spenders). The results obtained confirm that CHAID is a relatively flexible technique to use and can be employed as a precursor to a more parametric approach.
Localization of Alagille Syndrome to 2 0 P Ll.2 -p L2 by Linkage Analysis of a Three-generation Family

A bstract Alagille syndrome (AGS) or arteriohepatic dysplasia is a rare but well-defined clinical entity that is usually inherited as an autosomal dominant trait. A lim­ ited number of patients carry a deletion in chromosome 20p, with 20p 11.23— pi 2.2 as the area of minimal overlap. Recently, a family has been identified in which a balanced translocation with a breakpoint in 20p l 2 co-segregates with the AGS phenotype. Here, we report a three-genera­ tion family with AGS and in which the affected members have a normal karyotype. Linkage analysis was perfozTned with markers from the 20p candidate region. A lod score of Z=2.96 was obtained with D20S27 at no recombina­ tion. Combining D20S27 and D20S61 to a single highly informative locus resulted in a maximum lod score of Z-+ 3.56 at 0=0.0. Haplotype analysis positioned AGS between D20S59 and D20S65, markers that define an in­ terval of about 40 cM. Allelic loss was not observed for the tested markers and no abnormalities in the PAX1 can­ didate gene were detected. These findings demonstrate that the locus on chromosome 20p could be responsible for AGS in cytogenetically normal patients and argues for a general role of this locus in the aetiology of AGS.
Analysing the 'biodiversity' of open source ecosystems: the GitHub case

In nature the diversity of species and genes in ecological communities affects the functioning of these communities. Biologists have found out that more diverse communities appear to be more productive than less diverse communities. Moreover such communities appear to be more stable in the face of perturbations. In this paper, we draw the analogy between ecological communities and Open Source Software (OSS) ecosystems, and we investigate the diversity and structure of OSS communities. To address this question we use the MSR 2014 challenge dataset, which includes data from the top-10 software projects for the top programming languages on GitHub. Our findings show that OSS communities on GitHub consist of 3 types of users (core developers, active users, passive users). Moreover, we show that the percentage of core developers and active users does not change as the project grows and that the majority of members of large projects are passive users.
Arterial transit time imaging with flow encoding arterial spin tagging (FEAST)

Arterial spin labeling (ASL) perfusion imaging provides direct and absolute measurement of cerebral blood flow (CBF). Arterial transit time is a related physiological parameter reflecting the duration for the labeled spins to reach the brain region of interest. Most of the existing ASL approaches to assess arterial transit time rely on multiple measurements at various postlabeling delay times, and thus are vulnerable to motion artifact as well as computational error. We describe the use of flow encoding arterial spin tagging (FEAST) technique to measure tissue transit time, which can be derived from the ratio between the ASL signals measured with and without appropriate bipolar gradients. In the present study, we provided a theoretical framework and carried out an experimental validation during steady‐state imaging. The global mean tissue transit time was ∼1100 and 1400 ms for two conditions of bipolar gradients with specific encoding velocity (Venc) of 29 and 8 mm/sec, respectively. The mean tissue transit time measured within cerebral vascular territories was shortest in the deep middle cerebral artery (MCA) territory. Application of the FEAST technique in two patients with cerebrovascular disease demonstrated prolonged tissue transit times in the affected vascular territories which were consistent with results from other MR imaging modalities. Magn Reson Med 50:599–607, 2003. © 2003 Wiley‐Liss, Inc.
urCF : User Review Enhanced Collaborative Filtering Completed Research Paper

Despite of success in both research and industry, traditional collaborative filtering (CF) based recommender systems suffer from a fundamental problem, which lies in its dependence on users’ numeric ratings as its sole source of user preference information. User ratings are often unable to fully represent user preferences. As a result, it is difficult and error prone to identify genuinely similar users based on ratings only. On the other hand, online consumer product reviews have become a common source for consumers to share and acquire information about products, but there have been very few studies on how those text reviews can be analyzed and integrated with traditional CF approaches to improve the prediction of consumers’ preferences. We propose a novel approach to memory-based collaborative filtering called urCF (User Review enhanced Collaborative Filtering) that integrates user text reviews and user numeric ratings in order to model users’ preferences better and in turn improve the performance of CF-based recommender systems. This research extracts user opinions on individual item features from online reviews, and proposes a new weighting scheme by following the general idea of TF-IDF to measure the priority of item features in influencing users’ overall opinions on different items. This study also explores and compares two different methods for integrating user opinion into user similarity measurement. The proposed urCF system is evaluated against existing approaches using a dataset collected from Yahoo! Movies. The results show that urCF significantly improves the performance of memory-based CF systems.
Rapid octree construction from image sequences

Abstract The construction of a three-dimensional object model from a set of images taken from different viewpoints is an important problem in computer vision. One of the simplest ways to do this is to use the silhouettes of the object (the binary classification of images into object and background) to construct a bounding volume for the object. To efficiently represent this volume, we use an octree, which represents the object as a tree of recursively subdivided cubes. We develop a new algorithm for computing the octree bounding volume from multiple silhouettes and apply it to an object rotating on a turntable in front of a stationary camera. The algorithm performs a limited amount of processing for each viewpoint and incrementally builds the volumetric model. The resulting algorithm requires less total computation than previous algorithms, runs in close to real-time, and builds a model whose resolution improves over time.