Miracle-dz/UniFAR-FTUs huggingface dataset:
Pinning Down the Moving Target

This article proposes a model for understanding public-private relationships and, specifically, the outcomes sought from them. It was developed from an empirical study for a Ph.D. dissertation on public-private relationships in the Australian government information and communications technology (ICT) outsourcing environment. The study concluded that seven constructs were important in the public-private relationships established in ICT outsourcing, and these are described by the model along a continuum of collaborative outcomes. The article questions the notion that a public-private partnership (PPP) is a distinct and radical form of governance that can achieve otherwise unachievable results. Instead, it suggests, a PPP is just one point on the continuum of collaborative outcomes. The developed model can assist organizations to understand the outcome(s) sought from an organizational relationship and highlights the constructs and characteristics they should consider in achieving these outcomes.
Estimating deep Littlewood-Richardson Coefficients

Littlewood Richardson coefficients are structure constants appearing in the representation theory of the general linear groups $(GL_n)$. The main results of this paper are: 1. A strongly polynomial randomized approximation scheme for Littlewood-Richardson coefficients corresponding to indices sufficiently far from the boundary of the Littlewood Richardson cone. 2. A proof of approximate log-concavity of the above mentioned class of Littlewood-Richardson coefficients.
Generalized belief propagation based TDMR detector and decoder

Two dimensional magnetic recording (TDMR) achieves high areal densities by reducing the size of a bit comparable to the size of the magnetic grains resulting in two dimensional (2D) inter symbol interference (ISI) and very high media noise. Therefore, it is critical to handle the media noise along with the 2D ISI detection. In this paper, we tune the generalized belief propagation (GBP) algorithm to handle the media noise seen in TDMR. We also provide an intuition into the nature of hard decisions provided by the GBP algorithm. The performance of the GBP algorithm is evaluated over a Voronoi based TDMR channel model where the soft outputs from the GBP algorithm are used by a belief propagation (BP) algorithm to decode low-density parity check (LDPC) codes.
Chromium and Ruthenium-Doped Zinc Oxide Thin Films for Propane Sensing Applications

Chromium and ruthenium-doped zinc oxide (ZnO:Cr) and (ZnO:Ru) thin solid films were deposited on soda-lime glass substrates by the sol-gel dip-coating method. A 0.6 M solution of zinc acetate dihydrate dissolved in 2-methoxyethanol and monoethanolamine was used as basic solution. Chromium (III) acetylacetonate and Ruthenium (III) trichloride were used as doping sources. The Ru incorporation and its distribution profile into the films were proved by the SIMS technique. The morphology and structure of the films were studied by SEM microscopy and X-ray diffraction measurements, respectively. The SEM images show porous surfaces covered by small grains with different grain size, depending on the doping element, and the immersions number into the doping solutions. The sensing properties of ZnO:Cr and ZnO:Ru films in a propane (C3H8) atmosphere, as a function of the immersions number in the doping solution, have been studied in the present work. The highest sensitivity values were obtained for films doped from five immersions, 5.8 and 900, for ZnO:Cr and ZnO:Ru films, respectively. In order to evidence the catalytic effect of the chromium (Cr) and ruthenium (Ru), the sensing characteristics of undoped ZnO films are reported as well.
Low Impedance Walking Robots1

Abstract For both historical and technological reasons, most robots, including those meant to mimic animals or operate in natural environments,3 use actuators and control systems that have high (stiff) mechanical impedance. By contrast, most animals exhibit low (soft) impedance. While a robot's stiff joints may be programmed to closely imitate the recorded motion of an animal's soft joints, any unexpected position disturbances will generate reactive forces and torques much higher for the robot than for the animal. The dual of this is also true: while an animal will react to a force disturbance by significantly yielding position, a typical robot will greatly resist. These differences cause three deleterious effects for high impedance robots. First, the higher forces may cause damage to the robot or to its environment (which is particularly important if that environment includes people). Second, the robot must acquire very precise information about its position relative to the environment so as to minimize its velocity upon impact. Third, many of the self-stabilizing effects of natural dynamics are “shorted out”4 by the robot's high impedance, so that stabilization requires more effort from the control system. Over the past 5 yr, our laboratory has designed a series of walking robots based on “Series-Elastic Actuators” and “Virtual Model Control. ” Using these two techniques, we have been able to build low-impedance walking robots that are both safe and robust, that operate blindly without any model of upcoming terrain, and that add minimal control effort in parallel to their self-stabilizing passive dynamics. We have discovered that it is possible to achieve surprisingly effective ambulation from rather simple mechanisms and control systems. After describing the historical and technological motivations for our approach, this paper gives an overview of our methods and shows some of the results we have obtained.
Applying Case-Based Reasoning to Software Quality Management

An investigation is described into the application of quality function deployment (QFD) and case based reasoning (CBR) to software quality assessment. It is believed that the integration of CBR and QFD may be an effective means of supporting the development of quality software. The main aim in the research is to develop a CBR oriented software quality advisor to support the attainment of quality in software development, by reference to quality case histories using software modules from previous designs. A model linking CBR and QFD mechanisms is presented. Current work is centred on the development of a prototype system in the form of a shell incorporating an interface linking the user requirements, the QFD and CBR mechanisms, and supported by a dynamic library of case histories.
The impact of human resource management practices on the implementation of total quality management

Purpose – The perceived advantages of the implementation of TQM are generating improved quality and efficiency, increasing customer satisfaction, thus improving competitiveness. However, there is a high failure rate in the implementation of TQM. The key issue in this regard is that companies have devoted relatively little attention to human resources management (HRM). Several academics and practitioners have asserted that synergy and congruence among HRM practices are critical to the implementation of TQM. However, there is relatively little empirical evidence to support this contention. The purpose of this research is to conduct an empirical study on high‐tech firms, in order to analyse the impacts of HRM practices on the implementation of TQM.Design/methodology/approach – In this study, a research framework related to HRM practices, TQM practices, and quality performances was developed. Based on the framework, a questionnaire was designed and sent to the HR managers or chief executive officers (CEOs) of.
Shared Data from a Study of Measurement Uncertainty in Fault Injection

Experimental dependability studies usually produce an amount of data substantially greater than what can be presented in a research paper or a technical report. For this reason, authors condensate the results into more succinct forms that allow them to convey their message. Since a large amount of the original data is left unexplored, sharing it allows other teams to discover additional facts (as well as to compare the results to other studies). In a previous paper, we investigated sources of uncertainty in measurement results obtained using three different fault injection techniques. The resulting experimental data was shared in the AMBER raw data repository. This paper gives an overview of the study and makes an attempt at further exploring the shared data.
Untangling the US deficit

As the US current account deficit has expanded to a record level of $811 billion in 2006, debate about the deficit’s causes and consequences has also grown. Is the deficit a product of American profligacy or a ‘glut of savings’ in the rest of the world? Is it a serious problem or essentially benign? Untangling the US Deficit charts a course between the competing explanations in a systematic and rigorous approach, incorporating the latest academic research and market data. Particular attention is given to the China–United States trade imbalance and to the special role of the US dollar and US capital markets in global finance.
Folding and stability of the ligand‐binding domain of the glucocorticoid receptor

A complex pathway involving many molecular chaperones has been proposed for the folding, assembly, and maintenance of a high‐affinity ligand‐binding form of steroid receptors in vivo, including the glucocorticoid receptor. To better understand this intricate folding and assembly process, we studied the folding of the ligand‐binding domain of the glucocorticoid receptor in vitro. We found that this domain can be refolded into a compact, highly structured state in vitro in the absence of chaperones. However, the presence of zwitterionic detergent is required to maintain the domain in a soluble form. In this state, the protein is dimeric and has considerable helical structure as shown by far‐UV circular dichroism. Further investigation of the properties of this in vitro refolded state show that it is stable and resistant to denaturation by heat or low concentrations of chemical denaturants. A detailed analysis of the unfolding equilibria using three different structural probes demonstrated that this state unfolds via a highly populated dimeric intermediate state. Together, these data clearly show that the ligand‐binding domain of the glucocorticoid receptor does not require chaperones for folding per se. However, this in vitro refolded state binds the ligand dexamethasone only weakly (Kd = 45 μM) compared to the in vivo assembled receptor (Kd = 3.4 nM). We suggest that the role of Hsp90 and associated chaperones is to bind to, and stabilize, a specific conformational state of the receptor which binds ligand with high affinity.
BUSINESS PROCESS MANAGEMENT MATURITY MODEL AND SIX SIGMA: AN INTEGRATED APPROACH FOR EASIER NETWORKING

Business process management maturity model enables description of ''as-is'' enterprise’s state, from the perspective of process management maturity. In the hart of this model there are five factors or levers, critical for successful business process management implementation. These factors are: strategic alignment, process management, methods and technology, employees and business culture. Mentioned factors influence the state or the level of enterprise's maturity. The level of process management maturity can be: initial, define, management, quantitative management, continual improvement. When maturity factors or levers are analyzed simultaneously with maturity levels one can formulate two-dimensional business process management maturity model. However, concerning some shortfalls of this model, it is desirable to ennoble it with Six Sigma philosophy and methodology. This model can be very helpful when an enterprise has to make decision concerning different forms of networks, like joint ventures or strategic alliances. However, Business process management maturity model can help managers to make decision concerning franchising, because franchising success depends a great deal on maturity of an enterprise which represents franchisee buyer.
Modern aspects of the management of the newborn undergoing operation.

The principles of neonatal anaesthesia have been described by a number of eminent paediatric anaesthetists (Rees, 1958; Smith, 1959; Wilton and Wilson, 1965; Stead and Nightingale, 1969). Since then important advances have been made in the preparation of the infant for surgery, in the increased use of ventilator therapy, in the better understanding of fluid, electrolyte and metabolic disturbances and in the use of improved equipment and therapeutic agents, all of which have contributed to lowering the mortality and morbidity of neonatal surgery. The purpose of this paper is to describe some of these recent advances and to re-emphasize some of the important aspects of neonatal anaesthesia.
Towards Quantifying Limits of Automated Curation of Geospatial Data

Workflow systems are an increasingly popular eScience tool for executing complex sequences of tasks. The large volumes of data created during the course of these computationally intense and datadriven scientific investigations drives research in techniques to automate metadata capture to relieve the burden on the user of manual annotation. In this paper we describe our experience to date in quantifying the limits of automated metadata collection in e-Science workflow systems.
AutoParSe: An Automatic Paradigm Selector For Nouns in Konkani

In this paper, we discuss a rule based method which automatically assigns paradigms to Konkani nouns using morphophonemic rules, stem formation rules and relevance score of the paradigms. The first contribution is computation of relevance score of a paradigm, which is computed using a corpus and paradigm differentiating measure assigned to inflectional suffixes in the paradigm. Relevance score helps assign multiple paradigms to the input word wherever appropriate. The other contribution is a method for computing paradigm differentiating measure for inflectional suffixes. We have proposed a pruning technique based on derivational suffixes to further improve the precision. The experimental study has been carried out using the Konkani WordNet and the Asmitai Corpus. The proposed method successfully assigned relevant paradigms to 10,068 nouns with F-Score of 0.93.
A Hysteretic Source Rate Control Scheme for a Finite Buffer in a Wireless Environment

In this paper, we consider a source rate control scheme for a finite buffer of size C in a medium access control layer of a wireless system over a Markovian channel. Our rate control scheme can reduce the mean number of packets produced by a source when the queue length exceed K (K<C), and increase again (by recovering the original source rate) when the queue length drops below L (L<K). In order to obtain the stationary state probability vector of the system which is no longer a typical M/G/1 type queue, we propose an algorithm consisting of two phases. During the backward reduction phase, we obtain a minimal finite M/G/1 queue with an invariant probability vector called the minimal solution vector. This is followed by a forward expansion phase on the minimal solution vector. Numerical results are presented in terms of cumulative queue length distribution, by varying source and channel parameters and the hysteresis levels, L and K.
Robust and efficient people detection with 3-D range data using shape matching

Information about the location of a person is a necessity for Human-Robot Interaction (HRI) as it enables the robot to make human aware decisions and facilitates the extraction of further useful information; such as low-level gestures and gaze. This paper presents a robust method for person detection with 3-D range data using shape matching. Projections of the 3-D data onto 2-D planes are exploited to effectively and efficiently represent the data for scene segmentation and shape extraction. Fourier descriptors (FD) are used to describe the shapes and are subsequently classified with a Support Vector Machine (SVM). A database of 25 people was collected and used to test this approach. The results show that the computationally efficient shape features can be used to robustly detect the location of people.
Hexagonal dielectric loaded nantenna for optical ITU-T C-band communication

Antennas designed with nano scale technologies, at optical frequencies, will be a corner stone in next generation nano communication links and networks. These optical antennas, operating in the THz regime of electromagnetic spectrum, will be applicable to fields including biomedical, environmental, military, and civilian communications. In this paper, authors propose and explore the potential benefits of designing a hexagonal dielectric loaded nantenna (HDLN) at a center frequency of 193.5 THz using CST Microwave Studio. The nantenna consists of Silver `Ag' as partial ground plane, a top and bottom `SiO2' substrate and a `Si' hexagon as dielectric fed by a `Ag' nanostrip transmission line. The simulated nantenna achieves a wide impedance bandwidth of 3.7% from 190.9 THz to 198.1 THz and an end-fire directivity of 8 dBi, covering all the standard optical transmission window at the ITU-T optical communication 1550 nm C-band.
Adaptive Fuzzy Evidential Reasoning for Automated Brain Tissue Segmentation

This paper presents an adaptive fuzzy evidential reasoning approach, for segmenting multi-modality MR brain images. A novel fuzzy evidence structure model is proposed under the assumption that each information source provides two types of evidence: probabilistic evidence and fuzzy evidence. A new information measure, called hybrid entropy, is employed for evaluating the overall uncertainty contained in a fuzzy evidence structure. For adaptive reasoning, two discounting strategies are included. To handle conflict between the probabilistic evidence and the fuzzy evidence, local discounting takes into account Kullback-Leibler distance between the two types of evidence. Global discounting takes into account source quality, in terms of Shannon entropy and hybrid entropy, for dealing with conflict of sources. To demonstrate its effectiveness, the approach is applied to segmenting multi-modality MR brain images. It is concluded that the proposed approach performs better than Kmean clustering, majority voting, fuzzy set operators, and Bayesian approach.
Design of Waveguide Short-Slot Two-Plane Couplers for One-Body 2-D Beam-Switching Butler Matrix Application

A waveguide short-slot two-plane coupler is proposed as a component of 2-D beam-switching Butler matrix. The hybrid and cross coupler operations are designed by including the 2-D polarity symmetry, the propagation constant, and the coupling with the ports of the modes in the coupled region. Their designs are confirmed by experiments. The achieved bandwidth is approximately 2%, restricted by the frequency characteristic of the modes in the coupled region. Since the short-slot two-plane hybrid coupler itself acts as the 2 ×2-way 2-D beam-switching Butler matrix, the beam switching is also verified by measurements. The general configuration of the 2-D beam-switching Butler matrix is also proposed by using the short-slot two-plane couplers.
An Exploration of Designing for Playfulness in a Business Context

The Playful Experiences (PLEX) framework is a categorization of 22 experiences that has been used to design for and evaluate aspects of playfulness. The design activities performed using PLEX have been conducted mostly within an academic research context. This paper investigates through three studies how to design for and evaluate playful user experiences in business at three stages of the design process: idea generation, conceptualization, and evaluation. Based on the findings, opportunities and challenges of designing for playfulness within business are discussed.
Distributed, predictive perception of actions: a biologically inspired robotics architecture for imitation and learning

One of the most important abilities for an agent's cognitive development in a social environment is the ability to recognize and imitate actions of others. In this paper we describe a cognitive architecture for action recognition and imitation, and present experiments demonstrating its implementation in robots. Inspired by neuroscientific and psychological data, and adopting a ‘simulation theory of mind’ approach, the architecture uses the motor systems of the imitator in a dual role, both for generating actions, and for understanding actions when performed by others. It consists of a distributed system of inverse and forward models that uses prediction accuracy as a means to classify demonstrated actions. The architecture is also shown to be capable of learning new composite actions from demonstration. *email: y.demiris@imperial.ac. uk †email: matthew.johnson@imperial.ac. uk
Fully automated recognition of spontaneous facial expressions in videos using random forest classifiers

This paper discusses the design and implementation of a fully automated comprehensive facial expression detection and classification framework. It uses a proprietary face detector (PittPatt) and a novel classifier consisting of a set of Random Forests paired with support vector machine labellers. The system performs at real-time rates under imaging conditions, with no intermediate human intervention. The acted still-image Binghamton University 3D Facial Expression database was used for training purposes, while a number of spontaneous expression-labelled video databases were used for testing. Quantitative evidence for qualitative and intuitive facial expression recognition constitutes the main theoretical contribution to the field.
Mining Short‐Rule Covers in Relational Databases

An implication rule Q→R is a statement of the form “for all objects in the database, if an object has the attribute–value pairs Q then it has also the attribute–value pairs R. ” This simple type of rule is theoretically interesting, because it supports reasoning, similar to functional dependencies in database theory, and it may be of practical significance because the size of the set of implication rules that hold in a relation can remain substantially high even when mining real data and considering only most general covers; i.e., covers containing rules with unredundant right and left sizes. Motivated by these observations, we focus on the extraction of short‐rule covers, which cannot be efficiently mined by standard rule miners. We present an algorithm driven by “negative examples” (i.e., satisfy Q but not R) to prune the rule‐candidate lattice associated with each “positive example” (i.e., satisfies both Q and R). The algorithm scales up quite well with respect to the number of objects and it is particularly suitable for databases with attributes described by large domains. Furthermore, a perfect hash function ensures extraction of short‐rule covers even from databases containing a large number of attributes.
Technology Challenges for Silicon Nanophotonics and Beyond

The development of Si-based photonics has been far behind the development of electronics for long time. There are two reasons for that. As silicon is an indirect band gap semiconductor, achieving light emission and gain is quite difficult. On the other hand, for using silicon as a light guiding material for passive devices, the main constrains until recently were relatively high propagation losses and high fiber-to-waveguide incoupling losses. The general trend towards more compact photonic devices together with progress in fabrication techniques resulted in the development of two nano-photonic technologies for next generation optical devices: photonic crystals and nanowire waveguides-based devices. To drastically increase the integration density and achieve subwavelength confinement of light along the propagation direction, plasmonic waveguides have been proposed. Surface plasmons are electromagnetic modes constituted on the interface between a metal and a dielectric. The tradeoff between the light confinement and propagation loss has here a vital importance.