Miracle-dz/UniFAR-FTUs huggingface dataset:
TR 11-026 Probabilistic Tensor Factorization for Tensor Completion

Multi-way tensor datasets emerge naturally in a variety of domains, such as recommendation systems, bioinformatics, and retail data analysis. The data in these domains usually contains a large number of missing entries. Therefore, many applications in those domains aim at missing value prediction, which boils down to a tensor completion problem. While tensor factorization algorithms can be a potentially powerful approach to tensor completion, most existing methods have the following limitations: First, some tensor factorization algorithms are unsuitable for tensor completion since they cannot work with incomplete tensors. Second, deterministic tensor factorization algorithms can only generate point estimates for the missing entries, while in some cases, it is desirable to obtain multiple-imputation datasets which are more representative of the joint variability for the predicted missing values. Therefore, we propose probabilistic tensor factorization algorithms, which are naturally applicable to incomplete tensors to provide both point estimate and multiple imputation for the missing entries. In this paper, we mainly focus on the applications to retail sales datasets, but the framework and algorithms are applicable to other domains as well. Through extensive experiments on real-world retail sales data, we show that our models are competitive with state-of-the-art algorithms, both in prediction accuracy and running time.
Gender, Literacy and Empowerment in Rural Colombia

Empowerment, understood as a process by which women increase their capacity to reexamine their own lives and aid those around them, as well as to question their roles as social agents, becomes critical in relation to the complex processes of literacy. This study takes a phenomenological approach to exploring the perceptions of a group of rural Colombian women on the path to literacy via the program Alfabetizacion Virtual Asistida en la Educacion de Jovenes y Adultos (Virtually Assisted Literacy in Youth and Adult Education) and discusses the dynamics of empowerment in the daily lives of these women during and after the program. Using the concepts of critical social theory and critical theory as a theoretical framework, this study demonstrates that programs such as this help women to reveal and reinvent their previously hidden identities; however, they offer only limited opportunities to challenge a stubborn patriarchal culture that insists on placing them in the domestic realm. The importance of this study relies on the fact that it identifies specific issues with regard to constraints in rural women’s education; therefore, there is an urgent need for government, academia, international agencies, and civil society to jointly participate in the implementation and execution of adult literacy programs. These programs must imperatively focus on gender inclusion and continuing education past the elementary stages, as well as on functional literacy that effectively impacts the lives of rural women in terms of decision-making, personal and family health care, reproductive health, and entry into the labor market. Keywords: Adult literacy, Colombia, gender, rural women, empowerment, literacy programs.
Optimization of 2 D Problems Considering the Reduced Basis Method

In the last decade, approximations [1,2] based optimization had received a lot of attention, as they in general, produce very fast computations for the multiple functions/derivatives evaluations required by the optimizers and also eliminate the numerical noise inherent to functions/gradient obtained by numerical procedures. In this work, a model type approximation technique named reduced basis output bound method (RBOBM)[3-5] is used to obtain optimum design of 2D problems. The central idea of RBOBM is the recognition that the field variables depend on a lower solution space dictated by the parametric dependence. To couple efficiency and reliability, the procedure encompass several attributes, namely: dimension reduction; operators separability, a posteriori error estimators and an effective off-line/on-line computational strategy. A Galerkin projection onto lower approximation spaces comprising solutions of the problem of interest at selected points in the parameter/design space is responsible to reduce the order of the system of equations to be solved in order to get the many evaluations of the desired output. A posteriori error estimator procedure is the accuracy checking for the method. This measure of fidelity is in general absent in the approximations methodologies employed in literature. Moreover, a relaxation scheme considered in the error residual equation turns out to be a very efficient computational strategy to compute such estimators. A parameter separability strategy together with the affine decomposition of the linear operators of the governing equations allows the development of an efficient offline/online calculation methodology for the computational implementation of the method. The offline calculations are computed only once and used subsequently in the online stage for each new desired parameter. This provides computational economies of several order of magnitude turning the RBOBM technique into a very attractive tool for optimum design purposes. In this work, the RBOBM rules the structural and sensitivities analysis modules that integrates a conventional structural shape optimization algorithm (SSO) already implemented by the authors [5,6]. As a consequence, during the iterative procedure, functions evaluations, error estimators and sensitivities can be very fast obtained. The sequential quadratic programming algorithm (SQP) is the optimizer [7]. The present article will focus on 2D elasticity applications. This type of application brings about some of the challenging issues inherent to the reduced basis that is a complex parameter dependence related to affine decomposition of the stiffness matrix and load vector. One example will demonstrate the effectiveness/robustness of the method. The importance of considering such scheme for functions/derivatives evaluations in an optimization procedure is highlighted.
Computer-Assisted Analysis and Epidemiological Value of Genotyping Methods for Campylobacter jejuni andCampylobacter coli

ABSTRACT For epidemiological tracing of the thermotolerantCampylobacter species C. jejuni and C. coli, reliable and highly discriminatory typing techniques are necessary. In this study the genotyping techniques of flagellin typing (flaA typing), pulsed-field gel electrophoresis (PFGE), automated ribotyping, and amplified fragment length polymorphism (AFLP) fingerprinting were compared. The following aspects were compared: computer-assisted analysis, discriminatory power, and use for epidemiological typing of campylobacters. A set of 50 campylobacter poultry isolates from The Netherlands and neighboring countries was analyzed. Computer-assisted analysis made cluster analysis possible and eased the designation of different genotypes. AFLP fingerprinting was the most discriminatory technique, identifying 41 distinct genotypes, while PFGE identified 38 different types, flaA typing discriminated 31 different types, and ribotyping discriminated 26 different types. Furthermore, AFLP analysis was the most suitable method for computer-assisted data analysis. In some cases combining the results of AFLP fingerprinting, PFGE, and flaA typing increased our ability to differentiate strains that appeared genetically related. We conclude that AFLP is a highly discriminatory typing method and well suited for computer-assisted data analysis; however, for optimal typing of campylobacters, a combination of multiple typing methods is needed.
A History-Based Handover Prediction for LTE Systems

Handover prediction has been considered an effective technology for improvement of LTE Handover performance. Although not a few techniques have been proposed to achieve this goal including handover preparation based on cross-layer optimization and mobility prediction, the fact is that their gains are not usually so high as their cost. To overcome such weaknesses, this paper proposes a simple handover prediction technique which is based on a novel user mobility model to approximate simulation the laws of user mobility actions. We develop a user mobility database to assist the mobility prediction based on the user mobility history records. The simulation results show that the proposed technique minimizes the number of handovers and lower the ping-pang rate in LTE system.
A self-consistent model to estimate NBTI degradation and a comprehensive on-line system lifetime enhancement technique

Lifetime reliability and the resultant temporal performance degradation due to Negative Bias Temperature Instability (NBTI) has emerged as a critical challenge in design and test of integrated circuits in nanometer technology nodes. In this work, we have developed a model that self-consistently estimates the NBTI degradation by considering the impact on the circuit lifetime of inter-dependent parameters such as Vdd and temperature simultaneously. Using the proposed model, we observed that a circuit with lower Vdd can provide better lifetime performance than with higher Vdd. This interesting observation can be attributed to the reduction of electric field in the transistor along with the circuit power/temperature reduction that leads to lesser NBTI degradation. Based on this observation we have developed a on-line detection and mitigation scheme that allows Vdd scaling to enhance system lifetime. The proposed scheme was applied to various arithmetic units and results in 45nm IBM process technology show 18% lifetime improvement with 57% reduction in power compared to conventional mitigation techniques. We also show that by using existing NBTI estimation models, the error in delay estimation can be as large as 7.6%.
Path-complete positivity of switching systems

Abstract The notion of path-complete positivity is introduced as a way to generalize the property of positivity from one LTI system to a family of switched LTI systems whose switching rule is constrained by a finite automaton. The generalization builds upon the analogy between stability and positivity, the former referring to the contraction of a norm, the latter referring to the contraction of a cone (or, equivalently, a projective norm). We motivate and investigate the potential of path-complete positivity and we propose an algorithm for the automatic verification of positivity.
Faculty Perception Of Branding:A Multi-case Qualitative Study

This research explores through the lens of branding practices at universities how professionals in public sector spaces respond to the influence of corporate marketing practices. Specifically, this research addressed the question of how faculty perceive branding activities in higher education and their role in branding activities at the university. It also sought to understand the impact and influence of institutional attributes such as heritage and location on faculty perception of branding. The research was conducted at three Universities in Ontario Canada, which were selected based on differences in heritage and location. Marketing, organizational studies and higher education studies literature were combined highlighting the differences between product and service based marketing and the interplay between organizational identity, image and culture. My research revealed ambiguous and complex responses from faculty and highlighted the unique values and beliefs inherent in academic culture. While most faculty members appreciated the need for branding under current economic conditions, many perceived branding as representing the unwelcome encroachment of business ideology within the university which had the potential of eroding the university’s contribution to the public good. They also perceived branding as leading to changes in both the structure and culture of the university. Many faculty expressed concern that branding tended toward a claim to be everything to everyone resulting in significant gaps in authenticity; in other words between brand representations and actual practices. The findings raise questions about the applicability of existing theories of branding to higher education institutions and an academic service brand model is proposed that captures the complexity of academic responses to branding. The management implications arising from this thesis reveal that faculty members see branding as a complex balancing act combining multiple attributes and one that requires transparent communication, the cultivation of trust, accessible brand leadership and authenticity.
Understanding Revision Planning in Peer-Reviewed Writing

Revision is a core writing skill that presents challenges to both novice and expert writers. Within the context of peer review, peer feedback has the potential to provide rich guidance for revision, especially when making content-level changes. However, authors must review and evaluate each piece of feedback for meaningful critiques that can be applied to further drafts. In this work, we analyzed several factors that influenced students’ decisions to fix or ignore comments they received. We found that feedback on content dimensions, as well as critical remarks by both the reviewers, and by the authors regarding papers they reviewed, were correlated with the amount of revisions made between drafts.
Artery: A Data-Centric Architecture for Wireless Sensor Networks

Sensor networks, composed of large amount of micro-sensors, are considered promising, both in academic research and in real life applications. To ensure highly efficient communications between event observers and sensor network users, new infrastructures and algorithms are being developed. This paper describes Artery, a novel architecture that delivers queries and data between multiple observers and multiple mobile users. Simulation results show that Artery outperforms some major data dissemination algorithms.
Rab3D Is Critical for Secretory Granule Maturation in PC12 Cells

Neuropeptide- and hormone-containing secretory granules (SGs) are synthesized at the trans-Golgi network (TGN) as immature secretory granules (ISGs) and complete their maturation in the F-actin-rich cell cortex. This maturation process is characterized by acidification-dependent processing of cargo proteins, condensation of the SG matrix and removal of membrane and proteins not destined to mature secretory granules (MSGs). Here we addressed a potential role of Rab3 isoforms in these maturation steps by expressing their nucleotide-binding deficient mutants in PC12 cells. Our data show that the presence of Rab3D(N135I) decreases the restriction of maturing SGs to the F-actin-rich cell cortex, blocks the removal of the endoprotease furin from SGs and impedes the processing of the luminal SG protein secretogranin II. This strongly suggests that Rab3D is implicated in the subcellular localization and maturation of ISGs.
An Auditory Inspired Amplitude Modulation Filter Bank for Robust Feature Extraction in Automatic Speech Recognition

The human ability to classify acoustic sounds is still unmatched compared to recent methods in machine learning. Psychoacoustic and physiological studies indicate that the auditory system of mammals decomposes audio signals into their acoustic and modulation frequency components prior to further analysis. Since it is known that most linguistic information is coded in amplitude fluctuations, mimicking temporal processing strategies of the auditory system in automatic speech recognition (ASR) promises to increase recognition accuracies. We present an amplitude modulation filter bank (AMFB) that is used as a feature extraction scheme in ASR systems. The time-frequency resolution of the employed FIR filters, i.e., bandwidth and modulation frequency settings, are adopted from a psychophysically inspired model of Dau (1997) that was originally proposed to describe data from human psychoacoustics. Investigations on modulation phase indicate the need for preserving such information in amplitude modulation features. We show that the filter symmetry has an important impact on ASR performance. The proposed feature extraction scheme exhibits significant word error rate (WER) reductions using the Aurora-2, Aurora-4, and REVERB ASR tasks compared to other recent feature extraction methods, such as MFCC, FDLP, and PNCC features. Thereby, AMFB features reveal high robustness against additive noise, different transmission channel characteristics, and room reverberation. Using the Aurora-4 benchmark, for instance, an average WER of 12.33% with raw and 11.31% with bottleneck transformed features is attained, which constitutes a relative improvement of 19.6% and 29.2% over raw MFCC features, respectively.
Dynamic Workload Balancing for Hadoop MapReduce

Hadoop has two components which are HDFS and MapReduce. HDFS is a distributed file system for storing data for users of Hadoop and MapReduce is the framework that executes jobs from users. Hadoop stores user data based on space utilization of data nodes on the cluster rather than the processing capability of the data nodes. Furthermore Hadoop runs in a heterogeneous environment as all data nodes may not be homogeneous. For these reasons, workload imbalances will occur when Hadoop runs resulting in poor performance. In this paper, we propose a dynamic algorithm to balance the workload between different racks on a Hadoop cluster based on information obtained from analyzing the log files of Hadoop. Moving tasks from the busiest rack to another rack improves the performance of Hadoop MapReduce by reducing the running time of jobs. Our simulations indicate that using our algorithm, we can decrease by more than 50% the remaining time of the tasks belonged to a job running on the busiest rack.
Pseudo Rotation Curve Connecting the Galaxy, Dark Halo, and Local Group

We construct a Galacto-Local Group rotation curve, combining the Galactic rotation curve with a diagram, where galacto-centric radial velocities of outer globular clusters and member galaxies of the Local Group are plotted against their galacto-centric distances. The high-velocity ends of this pseudo rotation curve within a radius R ~ 150 kpc are well traced by a rotation curve calculated for the NFW (Navaro, Frenk, White) and Burkert dark halo models. The NFW model indicates that the Galaxy's mass within 385 kpc, half distance to M31, is ~ 4 x 10^{11}M_{sun}. High-velocity ends of the pseudo rotation curve for the entire Local Group up to 1.5 Mpc indicate isothermal nature with a terminal velocity of ~ 200 km/s. In order for the Local Group to be gravitationally bound, an order of magnitude larger mass than those of the Galaxy and M31 is required. This fact indicates that the Local Group contains dark matter of mass ~ 5 x 10^{12}M_{sun} filling the space between the Galaxy and M31. The mass density of the Galactic dark halo becomes equal to that of the Local Group's dark matter at R ~ 100 kpc, beyond which the intracluster dark matter dominates. If we define the Galaxy's radius at this distance, the enclosed Galactic mass is ~ 3 x 10^{11}M_{sun}. We comment on the barionic matter fraction of galaxies in the Local Group.
Computer-Assisted Resection and Reconstruction of Pelvic Tumor Sarcoma

Pelvic sarcoma is associated with a relatively poor prognosis, due to the difficulty in obtaining an adequate surgical margin given the complex pelvic anatomy. Magnetic resonance imaging and computerized tomography allow valuable surgical resection planning, but intraoperative localization remains hazardous. Surgical navigation systems could be of great benefit in surgical oncology, especially in difficult tumor location; however, no commercial surgical oncology software is currently available. A customized navigation software was developed and used to perform a synovial sarcoma resection and allograft reconstruction. The software permitted preoperative planning with defined target planes and intraoperative navigation with a free-hand saw blade. The allograft was cut according to the same planes. Histological examination revealed tumor-free resection margins. Allograft fitting to the pelvis of the patient was excellent and allowed stable osteosynthesis. We believe this to be the first case of combined computer-assisted tumor resection and reconstruction with an allograft.
In vitro characterization and delivery of chitosan-DNA microparticles into mammalian cells.

PURPOSE Chitosan has a high potential for transferring DNA molecules into mammalian cells because of its cationic properties. In the present study, we have investigated DNA encapsulation efficiency and loading capacity of chitosan microparticles prepared in different conditions, as well as in vitro DNA release from microparticles, and transfection of different cell lines with chitosan-DNA microparticles, which may be employed in future in vivo studies. METHODS Plasmid DNAs were amplified in Escherichia coli DH5alpha and isolated by the alkali SDS-lysis method. Chitosan-DNA microparticles were prepared by the coacervation method by using different concentrations of chitosan and plasmid DNAs. In vitro release experiments were performed in PBS at 37 degrees C and DNA release was monitored spectrophotometrically. Transfection efficiency of chitosan-DNA microparticles into mammalian cells was determined by measuring the beta-galactosidase activity in cell lysates. RESULTS DNA encapsulation efficiency and loading capacity of microparticles was altered depending on the chitosan and DNA concentrations. Approximately 75-85% of DNA was encapsulated into the chitosan-DNA microparticles. The average size of microparticles was found to be approximately 2 microm. In vitro studies revealed that the release of DNA from chitosan microparticles could be controlled by changing the formulation conditions. Although the transfection efficiency of chitosan-DNA microparticles was typically lower than that of DNA complexed with lipid-based reagents, in vitro transfection results indicated that HEK293 cells take up chitosan-DNA microparticles more efficiently compared to HeLa and mouse fibroblastic 3T3 cell lines. CONCLUSION Chitosan microparticles provide a sustained release of plasmid DNA for a long period and they have a potential for DNA transfer into the mammalian cells. However, transfection efficiency of chitosan-DNA microparticles is low and dependent on the cell type.
Harmonic Guidance for Surface Deformation

We present an interactive method for applying deformations to a surface mesh while preserving its global shape and local properties. Two surface editing scenarios are discussed, which conceptually differ in the speci(cid:2)cation of deformations: Either interpolation constraints are imposed explicitly, e.g., by dragging a subset of vertices, or, deformation of a reference surface is mimicked. The contribution of this paper is a novel approach for interpolation of local deformations over the manifold and for ef(cid:2)ciently establishing correspondence to a reference surface from only few pairs of markers. As a general tool for both scenarios, a harmonic (cid:2)eld is constructed to guide the interpolation of constraints and to (cid:2)nd correspondence required for deformation transfer. We show that our approach (cid:2)ts nicely in a uni(cid:2)ed mathematical framework, where the same type of linear operator is applied in all phases, and how this approach can be used to create an intuitive and interactive editing tool.