Miracle-dz/UniFAR-FTUs huggingface dataset:
New Opportunities Presented by Novel Work Breakdown Techniques for Distributed Software Development

Research into new techniques for work breakdown and resolution of flow dependencies has shown benefits in improving the coordination among team members in distributed software development projects. While these approaches reduce some risks in distributed project execution, there are other concerns that demand equal attention. Among them, a key concern with distributed project execution is that they take an inordinately longer time for execution. Preliminary analysis shows that coordination and visibility is significantly impaired when operating in the distributed mode adversely affecting the execution time. In addition, the analysis also brings out other contributing factors such as those related to the planning and work breakdown with low granularity inevitably meant low visibility into the progress as well as impact due to delays attributed to sub-optimal coordination. In this paper, we outline a theoretical framework for utilizing and extending work-breakdown and parallelization techniques towards optimizing the execution time.
Indexing a web site with a terminology oriented ontology

This article presents a new approach in order to index a Web site. It uses ontologies and natural language techniques for information retrieval on the Internet. The main goal is to build a structured index of the Web site. This structure is given by a terminology oriented ontology of a domain which is chosen a priori according to the content of the Web site. First, the indexing process uses improved natural language techniques to extract well-formed terms taking into account HTML markers. Second, the use of a thesaurus allows us to associate candidate concepts with each term. It makes it possible to reason at a conceptual level. Next, for each candidate concept, its capacity to represent the page is evaluated by determining its level of representativeness of the page. Then, the structured index itself is built. To each concept of the ontology are attached the pages of the Web site in which they are found. Finally, a number of indicators make it possible to evaluate the indexing process of the Web site by the suggested ontology.
The Relationship between Environment Change and School Board Expectations of Superintendents' Decision Making.

ABSThACT The purpose of this research was to investigate and describe the relationship of environmental change to superintendent-school board decision-making and superintendent turnover. Assuming the resource dependence model of organizational open system theory, researchers hypothesized that the amount of decision-making autonomy boards grant to superintendents and the mobility of superintendents would be related to the amount of turbulence in the community. To gather data for the study, two instruments were developed: (1) a 57-item questionnaire to measure superintendent-board expectations on the relative dependence or independence of the superintendent in various contexts; and (2) a commnity environment questionnaire with 12 questions illustrating im)ortant aspects of the relationship between community characteristics and environmental turbulence. A total of 273 school districts were surveyed with these instruments in 1979 and again in 1983. Data analysis suggests statistically significant relationships between the management process occurring in education (perceptions of superintendents and boards concerning the amount of discretionary authority in decision making that boards should grant to superintendents) and environmental turbulence within the community.
Prostaglandin E2 Reverses Aberrant Production of an Inflammatory Chemokine by Microglia from Sandhoff Disease Model Mice through the cAMP-PKA Pathway

Background Sandhoff disease (SD) is a neurodegenerative lysosomal β-hexosaminidase (Hex) deficiency involving excessive accumulation of undegraded substrates, including terminal GlcNAc-oligosaccharides and GM2 ganglioside. Microglia-mediated neuroinflammation contributes to the pathogenesis and progression of SD. Our previous study demonstrated that MIP-1α, a putative pathogenic factor for SD, is up-regulated in microglial cells derived from SD model mice (SD-Mg) through activation of Akt and JNK. Methodology/Principal Findings In this study, we first demonstrated that prostaglandin E2 (PGE2), which is one of the lipid mediators derived from arachidonic acid and is known to suppress activation of microglia, reduced the aberrant MIP-1α production by SD-Mg to the same level as by WT-Mg. PGE2 also attenuated the activation of Akt and JNK. The inhibition of MIP-1α production and the activation of Akt and JNK occurred through the EP2 and 4/cAMP/PKA signaling pathway in the murine microglia derived from SD model mice. Conclusions/Significance We propose that PGE2 plays a role as a negative regulator of MIP-1α production in the pathogenesis of SD, and that PGE2-EP2 and 4/cAMP/PKA signaling could be a target pathway for therapy for SD.
An Assessment of Metric Contribution in the Construction of a Neural Network-Based Effort Estimator

The research literature contains various models for estimating programming effort. Traditional, well understood, mature approaches include Putnam’s SLIM [15], Albrect’s function point method of estimation [2], as well as COCOMO [3] and COCOMO II [1, 4]. Besides these traditional approaches, various machine learning techniques, including neural networks, [16, 17, 12] have evolved. At the foundation of these models is a set of cost drivers based upon process (e.g. process maturity), project (e.g., reuse, platform), personnel (e.g. team cohesion, personnel experience), and/or product measures (e.g. size and interface). Historically, SLOC (Source Lines of Code) metric is the most popular product metric used in the formulation of the various models. It is simple to calculate and provides a quick answer. However, it is an oversimplification of the product measure contribution to what characterizes programming effort. Using only SLOC ignores the contribution of other internal product metrics, such as complexity and vocabulary, in determining programming effort. What is needed is a more representative product metric which is both simple to calculate and provides a quick answer. This paper describes a neural network approach for characterizing programming effort based on internal product measures. Over thirty-three thousand different neural network experiments were performed upon data derived from a corporate repository. Four different simple metrics (size, vocabulary, complexity, and object) are assessed in terms of their individual contribution to programming effort. Afterwards these simple metrics are combined and assessed to determine the synergistic impact of each of the combinations. Finally, a cross-validation is performed on a second corporate repository.
Robust stabilization of infinite-dimensional systems using sliding-mode output feedback control

Sliding mode based feedback control has long been recognized as a powerful, yet easy-to-implement, control method to counteract non-vanishing external disturbances and unmodelled dynamics. Recently, research attention has focused on the development of sliding mode feedback control methods for various classes of infinite-dimensional systems. However, the existing methods are based on the assumption that distributed sensing and actuation is available, which significantly restricts their applicability to distributed process control applications. In this work, a sliding mode output feedback control method is developed for a class of linear infinite-dimensional systems with finite-dimensional unstable part using finite-dimensional sensing and actuation. Modal decomposition is initially used to decompose the original infinite-dimensional system into an interconnection of a finite-dimensional (possibly unstable) system and an infinite-dimensional stable system. Then, a sliding mode-based stabilizing state feedback controller is constructed on the basis of the finite-dimensional system. Subsequently, an infinite-dimensional Luenberger state observer, which utilizes a finite number of measurements, is constructed to provide estimates of the state of the infinite-dimensional system. Finally, an output feedback controller design is completed by coupling the infinite-dimensional Luenberger state observer and the sliding mode-based state feedback controller. Implementation, performance and robustness issues of the sliding-mode output feedback controller are illustrated in a simulation study of a distributed parameter system governed by the linearization around the spatially-uniform steady-state solution of the Kuramoto–Sivashinsky partial differential equation with periodic boundary conditions.
Stroke outcomes in Croatian and Bulgarian patients measured by modified Rankin scale

The purpose of the study was to measure functional outcomes of stroke patients undergoing rehabilitation in Croatia and Bulgaria using modified Rankin scale (mRS) as a clinician-reported measure of global disability. Fewer days are allowed for rehabilitation in Bulgaria than in Croatia according to the payers’ rules, and the aim of the study was to assess the impact of length of stay to the progress of patients. Data on 50 stroke patients from each of two countries were analyzed that were matched by gender, age at stroke, days from stroke to the onset of rehabilitation, type, side and severity of stroke, co-morbidity and the programme of rehabilitation. Initial and final mRS results and the change (progress) of patients` functional abilities and lengths of stay of both groups were recorded. Both groups presented with lower mRS results at rehabilitation onset (4.06±1.02 in Croatian and 3.88±0.96 in Bulgarian patients) indicating high dependency and the need for thorough approach and engagement of the whole rehabilitation team. There were significant changes of mRS (improvement) in both groups, but the progress was statistically better in Croatian with change of mRS of 0.96±0.67, than in Bulgarian patients (0.42±0.50), whereas the length of stay was significantly longer in Croatian patients (33±15 days) than in Bulgarian (8±2 days). The change in Strucni rad Professional article ISSN 1846-1867
Walking to the Beat of Their Own Drum: How Children and Adults Meet Timing Constraints

Walking requires adapting to meet task constraints. Between 5- and 7-years old, children’s walking approximates adult walking without constraints. To examine how children and adults adapt to meet timing constraints, 57 5- to 7-year olds and 20 adults walked to slow and fast audio metronome paces. Both children and adults modified their walking. However, at the slow pace, children had more trouble matching the metronome compared to adults. The youngest children’s walking patterns deviated most from the slow metronome pace, and practice improved their performance. Five-year olds were the only group that did not display carryover effects to the metronome paces. Findings are discussed in relation to what contributes to the development of adaptation in children.
A Biological Signals and Medical Images Lossless Compressor IP-Core Design

The present work shows the design flow of the BSMILC (Biological Signals and Medical Images Lossless Compressor) IPCore. During all design flow, since conception phase until layout phase, it was used the ipPROCESS [1] as the IP-Core development process. Both FPGA prototyping and ASIC experimental evaluation were made using the electrocardiogram (ECG) records from the MIT-BIH Arrhythmia Database and reached a compression ratio average of 2.32:1 and 2.57:1, respectively, with low memory requirements.
Design of Fuzzy-based autonomous car control system

Since the 20th century industrial revolution era, automobiles started playing a key and important role in our daily life activities. But, unfortunately, at the same time, an automobiles related accidents, and problems are representing an increasing source of danger on Human's life. In this paper a design of an autonomous (self-driving) car control system is presented to reduce automobiles-related problems. System's design is done by using Fuzzy Logic Control technology in addition to artificial intelligence algorithms. The achieved results demonstrates that proposed design has shown a reliable and efficient performance; all of the main driving control tasks (speed, brakes, steering wheel) were done effectively; it acts just same as a professional human driver.
Scalable Machine Translation in Memory Constrained Environments

Machine translation is the discipline concerned with developing automated tools for translating from one human language to another. Statistical machine translation (SMT) is the dominant paradigm in this field. In SMT, translations are generated by means of statistical models whose parameters are learned from bilingual data. Scalability is a key concern in SMT, as one would like to make use of as much data as possible to train better translation systems. In recent years, mobile devices with adequate computing power have become widely available. Despite being very successful, mobile applications relying on NLP systems continue to follow a client-server architecture, which is of limited use because access to internet is often limited and expensive. The goal of this dissertation is to show how to construct a scalable machine translation system that can operate with the limited resources available on a mobile device. The main challenge for porting translation systems on mobile devices is memory usage. The amount of memory available on a mobile device is far less than what is typically available on the server side of a client-server application. In this thesis, we investigate alternatives for the two components which prevent standard translation systems from working on mobile devices due to high memory usage. We show that once these standard components are replaced with our proposed alternatives, we obtain a scalable translation system that can work on a device with limited memory.
The Outsourcing Bogeyman

WHEN a presidential election year coincides with an uncertain economy, campaigning politicians invariably invoke an international economic issue as a dire threat to the well-being of Americans. Speechwriters denounce the chosen scapegoat, the media provides blanket coverage of the alleged threat, and legislators scurry to introduce supposed remedies. The cause of this year's commotion is offshore outsourcing-the alleged migration of American jobs overseas. The depth of alarm was strikingly illustrated by the firestorm of reaction to recent testimony by N. Gregory Mankiw, the head of President George W. Bush's Council of Economic Advisers. No economist really disputed Mankiw's observation that "outsourcing is just a new way of doing international trade," which makes it "a good thing. " But in the political arena, Mankiw's comments sparked a furor on both sides of the aisle. Democratic presidential candidate John Kerry accused the Bush administration of wanting "to export more of our jobs overseas, and Senate Minority Leader Tom Daschle quipped, "If this is the administration's position, I think they owe an apology to every worker in America. " Speaker of the House Dennis Hastert, meanwhile, warned that "outsourcing can be a problem for American workers and the American economy. " Critics charge that the information revolution (especially the Internet) has accelerated the decimation of U.S. manufacturing and facilitated the outsourcing of service-sector jobs once considered safe, from backroom call centers to high-level software programming.
Quality Estimation of English-Hindi Machine Translation Systems

Quality Estimation is a new research area in natural language processing where machine learning techniques are used to estimate the quality of machine translation outputs. In this paper we have discussed our experience of performing quality estimation for English-Hindi language pair. We have shown the use of some seventeen language independent features and then added some linguistic features to the feature set and analyzed the performance of the system by training two different classifiers on distinct sets. The results of these classifiers are compared with the results of human evaluators. Moreover we have also compared the results of these classifiers with some of the popular evaluation metrics.
Downlink System Throughput Statistics for Various MEA Configurations

The advent of applications that need higher throughputs motivates wireless service providers and cellular operators to embrace newer technologies that can meet these demands. Multiple-input-multiple-output (MIMO) systems have shown promise in their ability to deliver high throughput per bandwidth with reasonable constellation sizes. Adding antennas at the base station (BS) is practical due to reasons of size and cost amortization over users. However, adding antennas at the mobile station (MS), which does not have similar advantages, needs to be carefully evaluated. We therefore consider the more general class of techniques involving a multiple-element antenna (MEA) at one or both ends of the link (MIMO corresponding to the case of both). From a commercial standpoint, one needs to address the following questions: (i) What is the benefit of a second antenna at the BS or the MS relative to the single-input-single-output (SISO) case? (ii) What is the added value of a second antenna at both ends? (iii) If a second antenna is indeed used at both ends, which mode of operation --- spatial multiplexing (SM) or diversity (Div) --- is the preferred one? Using $(n, m)$ to denote a link with $n$ BS transmit elements and $m$ MS receive elements, we compare the downlink throughput performance of the SISO link with that of four MEA configurations: $(1, 2)$, \mbox{$(2, 1)$}, $(2, 2)$ with Div and $(2, 2)$ with SM. Our results indicate that, in the context of adaptive modulation with practical limits on constellation size, $(1, 2)$ is the preferred configuration. We also show this finding to be robust to assumptions used in the study.
Virtual Reality Software and Technology

Virtual Reality (VR) refers to a technology which is capable of shifting a subject into a different environment without physically moving him/her. To this end the inputs into the subject's sensory organs are manipulated in such a way, that the perceived environment is associated with the desired Virtual Environment (VE) and not with the physical one. The manipulation process is controlled by a computer model that is based on the physical description of the VE. Consequently, the technology is able to create almost arbitrarily perceived environments.
Combined Descriptors in Spatial Pyramid Domain for Image Classification

Recently spatial pyramid matching (SPM) with scale invariant feature transform (SIFT) descriptor has been successfully used in image classification. Unfortunately, the codebook generation and feature quantization procedures using SIFT feature have the high complexity both in time and space. To address this problem, in this paper, we propose an approach which combines local binary patterns (LBP) and three-patch local binary patterns (TPLBP) in spatial pyramid domain. The proposed method does not need to learn the codebook and feature quantization processing, hence it becomes very efficient. Experiments on two popular benchmark datasets demonstrate that the proposed method always significantly outperforms the very popular SPM based SIFT descriptor method both in time and classification accuracy.
Felicity and Presupposition Triggers

Many current pragmatic approaches to presupposition, beginning at least with Stalnaker (1974), are based on a notion of felicity. Presuppositions are requirements a sentence places upon a context for an utterance of that sentence to be felicitous. These requirements in turn are induced by the presence of certain presupposition triggers, such as lexical items like factive verbs, or constructions like clefts. In this framework, the notion of felicity is left unanalyzed, relying upon speakers’ abilities to provide felicity judgments. Likewise the mechanisms by which presupposition triggers lead to requirements on context are left largely unexplored (as most attention has been focused on the study of presupposition projection). In this paper, I shall begin to explore the notion of felicity and how it relates to presupposition triggers. My discussion will center around the observation that the kind of felicity relevant to presupposition is not an entirely uniform phenomenon. I shall argue this by a closer examination of infelicity. Two important subcategories of infelicity will emerge, distinguished by their discourse status. Generally, infelicity induces an opportunity for conversational repair. In some cases, we will see, the repair is obligatory, while in others, it is merely optional. I shall argue that this distinction correlates to a division among presupposition triggers. One category, which we may call strong presupposition, leads to obligatory repair upon failure. The other, which we may call weak presupposition, leads only to repair optional status. I shall then attempt to explain the distinction between strong and weak presuppositions, by offering an analysis of presupposition triggers in a framework of dynamic intensional logic. I shall argue that a systematic treatment of a wide range of triggers can be given in terms of a single dynamic operator. I shall also show how the dynamic properties of this operator can help to explain the different discourse properties of presuppositions. In dynamic logics, two sorts of failure can be distinguished. Update instructions can fail by resulting in a fail state; but instructions can also fail by being undefined for a given input. I shall propose that weak presuppositions result in the former kind of failure, while
Multifocus Image Fusion and Restoration With Sparse Representation

To obtain an image with every object in focus, we always need to fuse images taken from the same view point with different focal settings. Multiresolution transforms, such as pyramid decomposition and wavelet, are usually used to solve this problem. In this paper, a sparse representation-based multifocus image fusion method is proposed. In the method, first, the source image is represented with sparse coefficients using an overcomplete dictionary. Second, the coefficients are combined with the choose-max fusion rule. Finally, the fused image is reconstructed from the combined sparse coefficients and the dictionary. Furthermore, the proposed fusion scheme can simultaneously resolve the image restoration and fusion problem by changing the approximate criterion in the sparse representation algorithm. The proposed method is compared with spatial gradient (SG)-, morphological wavelet transform (MWT)-, discrete wavelet transform (DWT)-, stationary wavelet transform (SWT)-, curvelet transform (CVT)-, and nonsubsampling contourlet transform (NSCT)-based methods on several pairs of multifocus images. The experimental results demonstrate that the proposed approach performs better in both subjective and objective qualities.
Defining Functional Requirements for a Lightweight GNSS Support Protocol (LGSP)

Monash University is developing a lightweight GNSS (global navigation satellite system) support protocol (LGSP). This protocol aims to comprehensively address limitations in the traditional GNSS model, such as low signal availability in urban environments, receiver initialisation delays and bandwidth restrictions, by offering an alternative secure distribution channel for GNSS data. This gives compatible receivers an alternate means for acquiring GNSS data, resulting in enhanced robustness, efficiency and availability of GNSS systems. Development of LGSP has progressed, and a protocol specification is being prepared for release as an Internet draft to the IETF. This paper discusses motivations for the creation of LGSP, and presents key constraints and aims in the development of the protocol.