Miracle-dz/UniFAR-FTUs huggingface dataset:
Relational model vs. dimensional model-further experimentation on understandability of the twoschemas

Data warehouse (DW) has been commonly accepted as a solution to support organization’s decision support. Despite technical aspects of DW implementation, one of the most important tasks that need to be considered is its data modeling. Data modeling is important as it deals with structuring the data so that users can easily access for decision support process. The two predominant data models in data warehouse project are dimensional model (i.e. Star Schema Diagram (SSD)) and relational model (i.e. Entity-Relationship Diagram (ERD)). The decision whether to build a data warehouse using either model has created controversy among practitioners. Semantic network theory support that SSD is better than ERD in terms of its understanding measures. However, previous studies have produced conflicting result regarding the support and claim. Thus, the objective of this study is to further explore whether one schema is better than another in terms of its understandability. This study aims to design and conduct an experiment that test the understandability of the SSD and ERD with schema complexity factor.
Modelling the development and growth of bacterial biofilms

When bacteria attach to a solid surface they form biofilms, which increases their chances of survival. These biofilms can be very useful for example in soil and water treatment; however they can also cause serious illness. In this thesis we study and model biofilms in both one and two dimensions, to increase our understanding of their growth and development. These models use a continuum approach where we ssume that the biofilm is a viscous fluid that is free to grow, whilst sitting on a solid impermeable surface. The esulting equations where solved using various numerical techniques, including finite difference, level sets, conjugate gradient solvers and parallelised code. Comparisons between one and two dimensions are made, to understand whether predictions from one remain true in higher dimensions. A variety of anti-biofilm agents are also investigated to see what effects each of these have on biofilms and whether it is better to use a combination of these treatments.
Run-time support for parallel object-oriented computing : the NIP lazy task creation technique and the NIP object-based software distributed shared memory

Advances in hardware technologies combined with decreased costs have started a trend towards massively parallel architectures that utilise commodity components. It is thought unreasonable to expect software developers to manage the high degree of parallelism that is made available by these architectures. This thesis argues that a new programming model is essential for the development of parallel applications and presents a model which embraces the notions of object-orientation and implicit identification of parallelism. The new model allows software engineers to concentrate on development issues, using the object-oriented paradigm, whilst being freed from the burden of explicitly managing parallel activity. To support the programming model, the semantics of an execution model are defined and implemented as part of a run-time support system for objectoriented parallel applications. Details of the novel techniques from the run-time system, in the areas of lazy task creation and objectbased, distributed shared memory, are presented. The tasklet construct for representing potentially parallel computation is introduced and further developed by this thesis. Three caching techniques that take advantage of memory access patterns exhibited in object-oriented applications are explored. Finally, the performance characteristics of the introduced run-time techniques are analysed through a number of benchmark applications. © 2001 University of Newcastle upon Tyne. Printed and published by the University of Newcastle upon Tyne, Computing Science, Claremont Tower, Claremont Road, Newcastle upon Tyne, NE1 7RU, England. Bibliographical details
Galaxy luminosity functions in WINGS clusters

Aims. Using V band photometry of the WINGS survey, we derive galaxy luminosity functions (LF) in nearby clusters. This sample is complete down to MV =−15.15, and it is homogeneous, thus allowing the study of an unbiased sample of clusters with different characteristics. Methods. We constructed the photometric LF for 72 out of the original 76 WINGS clusters, excluding only those without a velocity dispersion estimate. For each cluster we obtained the LF for galaxies in a region of radius=0.5× r200, and fitted them with single and double Schechter’s functions. We also derive the composite LF for the entire sample, and those pertaining to different morphological classes. Finally we derive the spectroscopic cumulative LF for 2009 galaxies that are cluster members. Results. The double Schechter fit parameters are neither correlated w ith the cluster velocity dispersion, nor with the X‐ray lumi nosity. Our median values of the Schechter’s fit slope are, on average , in agreement with measurements of nearby clusters, but are less steep that those derived from large surveys, such as the SDSS. Early‐type galaxies outnumber late‐types at all magnitudes, but both early and late types contribute equally to the faint end of the LF. F inally, the spectroscopic LF is in excellent agreement with the ones derived for A2199, A85 and Virgo, and with the photometric one at the bright magnitudes (where both are available). Conclusions. There is a large spread in the LF of different clusters. However, this spread is not caused by correl ation of the LF shape with cluster characteristics such as X‐ray luminosity or velocity dispersions. The faint end is flatter than what previo usly derived (α f =−1.7) at odds with what predicted from numerical simulations.
The treatment of metaphorical and idiomatic expressions in learners’ dictionaries

Metaphorical and idiomatic expressions constitute an area of difficulty for (Italian) learners o f English as a foreign language not only, as easily expected, for productive purposes, but also in decoding activities, in particular in the field o f reading comprehension. It is therefore useful to see i f and how metaphorical and idiomatic expressions are treated in the O X F O R D ADVANCED LEARNER'S DICTIONARY OF CURRENT ENGLISH (OALD) and in the LONGMAN DIC­ TIONARY OF CONTEMPORARY ENGLISH (LDOCE), the two Learners' Dic­ tionaries (LD's) on which Italian learners most heavily rely and from which they expect help in decoding written texts, as no use o f the language can be effective and communicative i f metaphors and idioms are not decoded by the addressee. "Language", as L . Urdang says (1979 : 5 1 ) , "is metaphor". I f one agrees with him and realizes what pedagogic implications are involved in his concept in the field o f E F L learning, one cannot but adhere to his "frank plea to lexicographers to include metaphor in dictionaries" ( 1 9 7 9 : 4 7 ) . In order to support the plea and to draw attention to certain characteristics o f idioms, in the first part o f this pa­ per I shall analyse, among the definitions that the concept o f metaphor and the concept o f idiom have been given, those that, in my opinion, are more relevant to find acceptable lines along which certain metaphorical and idiomatic expres­ sions could be included and/or better treated in LD's , and to provide a theoreti­ cal framework against which the examples given in the second part o f this paper can be aptly illustrated.
Analyzing Impact of Formally Taught Life Skills’ Curriculum on Self Esteem and Thinking Skills of Early School Children

There is a rapidly developing trend of anxiety and depressive disorders; the level of prevalence of such disorders is at 34% in urban Pakistan. Given this alarming level of anxiety and depressive disorders and the evidence that intervention is mandatory for prevention, we have analyzed the role, if any, that educational institutions can play in providing preventive tools that will facilitate in coping with diverse situations that pose challenges leading to disorders. Our study is an attempt to investigate: (a) the impact of structured, taught and activity based curriculum for life skills with focus on self-esteem and thinking skills; (b) the differences in impact, if any, by gender. Out of total population of 3000 students, 220 students of Grade 1 (age 6-7 years) participated in the study. Five sample sets were taken, with identical numbers for both genders. Experimental design was pre tests, followed by 30-week program intervention and subsequent post tests in order to measure the changes in the selfesteem and thinking skills of early school children. The instruments used were Rosenberg Self-Esteem Test and Drawing and Conservation Tests for assessment of thinking skills. T-Test and ANOVA were used to evaluate the significance of impact of intervention. Based on this research: (a) it is conclusively clear that structured intervention enhances thinking skills (40.2%) and self-esteem (31.6%); (b) it can be reasonably deduced that improvement level is not directly correlated with the base level skill; (c) it can be intuitively determined that while prolonged intervention is expected to lead to a continuous improvement, the skill development over time is not likely to be linear. Based on our findings, it is deemed necessary and recommended that: (a) more targeted research be conducted to determine the level of intervention, on self-esteem and thinking skills, at which a significant correlation exists to treat this intervention as a prevention tool against developing mental disorders; (b) on concluding such research, it may be used to form the basis of prescriptive policy and law making for changing the early education curriculum to include mandatory life skills education as one preventive intervention against avoidable mental disorders caused by inability to manage stress and frustration.
An elliptic semilinear equation with source term involving boundary measures: the subcritical case

We study the boundary behaviour of the nonnegative solutions of the semilinear elliptic equation in a bounded regular domain O of RN (N = 2), i ? u + uq = 0, in O i i u = µ, on ? O where 1 < q < (N + 1)/(N - 1) and µ is a Radon measure on ? O. We give a priori estimates and existence results. The lie on the study of superharmonic functions in some weighted Marcinkiewicz spaces.
Photometric properties of Mars soils analogs

We have measured the bidirectional reflectance of analogs of dry, wet, and frozen Martian soils over a wide range of phase angles in the visible spectral range. All samples were produced from two geologic samples: the standard JSC Mars‐1 soil simulant and Hawaiian basaltic sand. In a first step, experiments were conducted with the dry samples to investigate the effects of surface texture. Comparisons with results independently obtained by different teams with similar samples showed a satisfying reproducibility of the photometric measurements as well as a noticeable influence of surface textures resulting from different sample preparation procedures. In a second step, water was introduced to produce wet and frozen samples and their photometry investigated. Optical microscope images of the samples provided information about their microtexture. Liquid water, even in relatively low amount, resulted in the disappearance of the backscattering peak and the appearance of a forward‐scattering peak whose intensity increases with the amount of water. Specular reflections only appeared when water was present in an amount large enough to allow water to form a film at the surface of the sample. Icy samples showed a wide variability of photometric properties depending on the physical properties of the water ice. We discuss the implications of these measurements in terms of the expected photometric behavior of the Martian surface, from equatorial to circum‐polar regions. In particular, we propose some simple photometric criteria to improve the identification of wet and/or icy soils from multiple observations under different geometries.
Multiple Access in the Delay-Doppler Domain using OTFS modulation

Orthogonal time frequency space (OTFS) modulation is a recent modulation scheme designed in the delay-Doppler domain. It has been shown to achieve superior performance compared to conventional multicarrier modulation schemes designed in the time-frequency domain. In this paper, we consider OTFS based multiple access (OTFS-MA), where delay-Doppler bins serve as the resource blocks for multiple access. Different delay-Doppler resource blocks (DDRBs) in the delay-Doppler grid are allocated to different users for multiple access. We consider three different DDRB allocation schemes. While Scheme 1 multiplexes the users along the delay axis, Scheme 2 multiplexes them along the Doppler axis. In both these schemes, each user's signal spans the entire time-frequency plane. Scheme 3 allocates the DDRBs in such a way that each user's signal is limited to span only over a subset of the time-frequency plane. We study the performance of OTFS-MA in high mobility environments on the uplink and compare it with those of OFDMA and SC-FDMA. Our results show that OTFS-MA (with maximum-likelihood detection in small dimension systems and with a message passing based detection in large dimension systems) achieves better performance compared to OFDMA and SC-FDMA. We also present the performance of a multiuser channel estimation scheme using pilot symbols placed in the delay-Doppler grid.
Venn GAN: Discovering Commonalities and Particularities of Multiple Distributions

We propose a GAN design which models multiple distributions effectively and discovers their commonalities and particularities. Each data distribution is modeled with a mixture of $K$ generator distributions. As the generators are partially shared between the modeling of different true data distributions, shared ones captures the commonality of the distributions, while non-shared ones capture unique aspects of them. We show the effectiveness of our method on various datasets (MNIST, Fashion MNIST, CIFAR-10, Omniglot, CelebA) with compelling results.
Worst-Case Guarantees for Remote Estimation of an Uncertain Source

Consider a remote estimation problem where a sensor wants to communicate the state of an uncertain source to a remote estimator over a finite-time horizon. The uncertain source is modeled as an autoregressive process with bounded noise. Given that the sensor has a limited communication budget, the sensor must decide when to transmit the state to the estimator who has to produce real-time estimates of the source state. In this article, we consider the problem of finding a scheduling strategy for the sensor and an estimation strategy for the estimator to jointly minimize the worst-case maximum instantaneous estimation error over the time horizon. This leads to a decentralized minimax decision-making problem. We obtain a complete characterization of optimal strategies for this decentralized minimax problem. In particular, we show that an open-loop communication scheduling strategy is optimal and the optimal estimate depends only on the most recently received sensor observation.
Revisiting hash table design for phase change memory

Phase Change Memory (PCM) is emerging as an attractive alternative to Dynamic Random Access Memory (DRAM) in building data-intensive computing systems. PCM offers read/write performance asymmetry that makes it necessary to revisit the design of in-memory applications. In this paper, we focus on in-memory hash tables, a family of data structures with wide applicability. We evaluate several popular hash-table designs to understand their performance under PCM. We find that for write-heavy workloads the designs that achieve best performance for PCMdiffer from the ones that are best for DRAM, and that designs achieving a high load factor also cause a high number of memory writes. Finally, we propose PFHT, a PCM-Friendly Hash Table which presents a cuckoo hashing variant that is tailored to PCM characteristics, and offers a better trade-off between performance, the amount of writes generated, and the expected load factor than any of the existing DRAM-based implementations.
Fast Evaluation of Low-Thrust Transfers via Deep Neural Networks

The design of low-thrust-based multitarget interplanetary missions requires a method to quickly and accurately evaluate the low-thrust transfer between any two visiting targets. Complete evaluation of the low-thrust transfer includes not only the estimation of the optimal fuel consumption but also the judgment of transfer feasibility. In this paper, a deep neural network (DNN)-based method is proposed for quickly evaluating low-thrust transfer. An efficient database generation method is developed for obtaining both the infeasible and optimal transfers. A classification DNN and a regression DNN are trained based on the infeasible and optimal transfers to judge the transfer feasibility and estimate the optimal fuel consumption, respectively. The simulation results show that the well-trained DNNs are capable of quickly determining the transfer feasibility with a correct rate of greater than 98% and approximating the optimal transfer fuel consumption with a relative estimation error of less than 0.4%. The tests on two asteroid chains further show the superiority of the DNN-based method for application to the design of low-thrust-based multitarget interplanetary missions
A Motion Free Approach to Dense Depth Estimation in Complex Dynamic Scene

Despite the recent success in per-frame monocular dense depth estimation of rigid scenes using deep learning methods, they fail to achieve similar success for complex dynamic scenes, such as MPI Sintel [4]. Moreover, conventional geometric methods to address this problem using a piece-wise rigid scene model requires a reliable estimation of motion parameters for each local model, which is difficult to obtain and validate. In this work, we show that, given per-pixel optical flow correspondences between two consecutive frames and the sparse depth prior for the reference frame, we can recover the dense depth map for the successive frames without solving for motion parameters. By assigning the locally rigid structure to the piece-wise planar approximation of a dynamic scene which transforms as-rigid-as-possible over frames, we demonstrate that we can bypass the motion estimation step. In essence, our formulation provides a new way to think and recover dense depth map of a complex dynamic scene which is recursive, incremental and motion free in nature and therefore, it can also be integrated with the modern neural network frameworks for large-scale depth-estimation applications. Our proposed method does not make any prior assumption about the rigidity of a dynamic scene, as a result, it is applicable to a wide range of scenarios. Experimental results show that our method can effectively provide dense depth maps for the successive/multiple frames of a dynamic scene without using any motion parameters.
Semantic Hierarchical Priors for Intrinsic Image Decomposition

Intrinsic Image Decomposition (IID) is a challenging and interesting computer vision problem with various applications in several fields. We present novel semantic priors and an integrated approach for single image IID that involves analyzing image at three hierarchical context levels. Local context priors capture scene properties at each pixel within a small neighbourhood. Mid-level context priors encode object level semantics. Global context priors establish correspondences at the scene level. Our semantic priors are designed on both fixed and flexible regions, using selective search method and Convolutional Neural Network features. Our IID method is an iterative multistage optimization scheme and consists of two complementary formulations: $L_2$ smoothing for shading and $L_1$ sparsity for reflectance. Experiments and analysis of our method indicate the utility of our semantic priors and structured hierarchical analysis in an IID framework. We compare our method with other contemporary IID solutions and show results with lesser artifacts. Finally, we highlight that proper choice and encoding of prior knowledge can produce competitive results even when compared to end-to-end deep learning IID methods, signifying the importance of such priors. We believe that the insights and techniques presented in this paper would be useful in the future IID research.
Color Image and Multispectral Image Denoising Using Block Diagonal Representation

Filtering images of more than one channel are challenging in terms of both efficiency and effectiveness. By grouping similar patches to utilize the self-similarity and sparse linear approximation of natural images, recent nonlocal and transform-domain methods have been widely used in color and multispectral image (MSI) denoising. Many related methods focus on the modeling of group level correlation to enhance sparsity, which often resorts to a recursive strategy with a large number of similar patches. The importance of the patch level representation is understated. In this paper, we mainly investigate the influence and potential of representation at patch level by considering a general formulation with a block diagonal matrix. We further show that by training a proper global patch basis, along with a local principal component analysis transform in the grouping dimension, a simple transform-threshold-inverse method could produce very competitive results. Fast implementation is also developed to reduce the computational complexity. The extensive experiments on both the simulated and real datasets demonstrate its robustness, effectiveness, and efficiency.
Magneto-Inductive Powering and Uplink of In-Body Microsensors: Feasibility and High-Density Effects

This paper studies magnetic induction for wireless powering and the data uplink of microsensors, in particular for future medical in-body applications. We consider an external massive coil array as power source (1 W) and data sink. For sensor devices at 12cm distance from the array, e.g. beneath the human skin, we compute a minimum coil size of 150µm assuming 50nW required chip activation power and operation at 750 MHz. A 275µm coil at the sensor allows for 1 Mbit/s uplink rate. Moreover, we study resonant sensor nodes in dense swarms, a key aspect of envisioned biomedical applications. In particular, we investigate the occurring passive relaying effect and cooperative transmit beamforming in the uplink. We show that the frequency- and location-dependent signal fluctuations in such swarms allow for significant performance gains when utilized with adaptive matching, spectrally-aware signaling and node cooperation. The work is based on a general magneto-inductive MIMO system model, which is introduced first.