Miracle-dz/UniFAR-FTUs huggingface dataset:
An Investigation of IS/ IT Project Risk Analysis and Management Practices in Western Australia

An attachment for a power planer table to support end up board lumber in which the planer table has a pair of parallel extending handles in a plane parallel to and below the upper surface of the table. According to the invention, a pair of parallel extending rails straddle the handles on opposite sides of the planer table and a pair of parallel extending guides are employed to span the upper surface of the planer table. Attaching members are utilized in cooperation with the guides to support the board lumber end up to facilitate planing of the narrow edge.
Interferon Consensus Sequence Binding Protein–deficient Mice Display Impaired Resistance to Intracellular Infection Due to a Primary Defect in Interleukin 12 p40 Induction

Mice lacking the transcription factor interferon consensus sequence binding protein (ICSBP), a member of the interferon regulatory factor family of transcription proteins, were infected with the intracellular protozoan, Toxoplasma gondii. ICSBP-deficient mice exhibited unchecked parasite replication in vivo and rapidly succumbed within 14 d after inoculation with an avirulent Toxoplasma strain. In contrast, few intracellular parasites were observed in wild-type littermates and these animals survived for at least 60 d after infection. Analysis of cytokine synthesis in vitro and in vivo revealed a major deficiency in the expression of both interferon (IFN)-γ and interleukin (IL)-12 p40 in the T. gondii exposed ICSBP−/− animals. In related experiments, macrophages from uninfected ICSBP−/− mice were shown to display a selective impairment in the mRNA expression of IL-12 p40 but not IL-1α, IL-1β, IL-1Ra, IL-6, IL-10, or TNF-α in response to live parasites, parasite antigen, lipopolysaccharide, or Staphylococcus aureus. This selective defect in IL-12 p40 production was observed regardless of whether the macrophages had been primed with IFN-γ. We hypothesize that the impaired synthesis of IL-12 p40 in ICSBP−/− animals is the primary lesion responsible for the loss in resistance to T. gondii because IFN-γ–induced parasite killing was unimpaired in vitro and, more importantly, administration of exogenous IL-12 in vivo significantly prolonged survival of the infected mice. Together these findings implicate ICSBP as a major transcription factor which directly or indirectly regulates IL-12 p40 gene activation and, as a consequence, IFN-γ–dependent host resistance.
Modulating Synchronicity in Computer Mediated Communication

Computer Mediated Communication (CMC) researchers often cite a dichotomy that distinguishes synchronous and asynchronous media. We examine the historical development of this bifurcated classification, as well as present evidence about the manner CMC media is actually used in the field. We speculate about the evolutionary and biological basis for this behavior. We suggest that synchronicity should not be treated as a dichotomy, but rather as a continuum ranging from the highly synchronous, to the highly asynchronous. In addition, we propose that the traditional treatment of synchronicity as an attribute of the medium should be reevaluated. We should treat synchronicity as an attribute of the conversation, not of the medium. These claims have implications on theories in which medium synchronicity plays an important role, and the Media Richness Theory is examined as a test case. Moreover, given that synchronicity is a continuous parameter modulated through decisions of communicators, we examine the way these decisions on synchronicity are taken, propose a theory of synchronicity modulation, and discuss the synchronicity trade-off principle.
Automated Software Deployment

The work users do with an application can be divided into actual work accomplished using the application and overhead performed in order to use the application. The latter can be further partitioned based on the time at which the work is performed: before (application location and delivery), during (installation) and after (upgrade) the installation of the application. This category can be characterized as the software deployment overhead. This thesis presents a component architecture RADIUS (Rapid Application location, Delivery, Installation and Upgrade System) in which applications can be built with no software deployment overhead to the users. An application is deployed automatically by simply giving the user a document produced by the application. Furthermore, the facilities in RADIUS make the applications selfupgrading. In the end, the users perform no deployment overhead work at all. The conventional way of using an application is to install the application first, then start using documents of the application. The object-oriented programming (OOP) paradigm suggests that this order should be reversed: the data should lead to the code. However, almost all software fails to meet this model of design at the persistence level. While modern software often use OOP at the program level, the underlying operating systems do not support OOP at the document/file level. OOP languages use pointers to methods to indicate what operations can be performed on the objects. We extend the idea to include “pointers to applications. ” Each document has an attached application pointer, which is read by RADIUS when the document is opened. This application pointer is then used to locate and deliver the application module necessary for the document. RADIUS is designed to be compatible with existing technologies and requires no extensions to either programming languages or operating systems. It is orthogonal to programming tools, is language-independent and compatible among operating systems, and consequently does not impose limitations on which environments the developers can use. We illustrate the implementations for the two most popular platforms today – C++ on Windows, and Java. RADIUS is also orthogonal to other component systems such as CORBA or COM and is easy to integrate with them.
Filtering of Gaussian filter based embedded enhancement technique for compressively sensed images

Compressed sensing (CS) is the technique used in signal processing for acquiring and reconstructing a signal efficiently, by finding solutions to undetermined linear systems. In compressed sensing, the data is compressed and converted into fewer measurements at the transmitter end and are transmitted through the wireless channel. The transmitted information is reconstructed in the receiver end. Since only few samples are used here to reconstruct the original image, there may be the possibilities of degraded quality in reconstruction. In such cases image enhancement is carried out with traditional enhancement techniques after reconstruction. Such enhancements can now be done using the developing technique of compressed sensing by incorporating the various image processing techniques like edge detection, histogram, filtering etc. which increase the perceptual quality of the image. This paper proposes an embedded image enhancement technique inbuilt along with the compressed sensing process which provide better quality of reconstructed images. There is nearly 1dB increase in PSNR of the reconstructed image provided, the complexity remains unaltered.
Exploring the Resolution Limit for In-Air Synthetic-Aperture Audio Imaging

SONAR imaging can detect reflecting objects in the dark and around corners, however many SONAR systems require large phased-arrays and immobile equipment. In order to enable sound imaging with a mobile device, one can move a microphone and speaker in the air to form a large synthetic aperture. We demonstrate resolution limited audio images using a moving microphone and speaker of a mannequin in free-space and a mannequin located around a corner. This paper also explores the 2D resolution limit due to aperture size as well as the time resolution limit due to bandwidth, and proposes Continuous Basis Pursuits (CBP) to super-resolve.
Adding Constraints to Logic-based Formalisms

Constraints are predeened relations with a special implementation mechanism. Logic formalisms provide speciic reasoning facilities. We look at the eeect of adding constraints to existing logic-based executable formalisms, focussing on the semantics of the combined formalisms. We nd that in cases where this has been successful the operations of the formalism can be formulated logically and then extended easily to constraints. In many cases a disjunctive property of the constraints is reeected in the combined formalism, to the detriment of eeciency.
A sensitivity analysis of microarray feature selection and classification under measurement noise

Microarray experiments typically generate data with a fairly high level of technical noise. Whereas this noise information is sometimes used in tests for differential expression and in clustering tasks, its effect on classification has remained underexposed. In this paper we assess the stability of microarray feature selection and classification under measurement noise. We do so by repeating the experiments many times, using perturbed expression measurements, based on reported uncertainty information. For a well-known study from the literature, the experiments show that the feature selection outcome can vary considerably, and that classification is quite unstable for 7 out of the 106 validation samples, in the sense that over 25% of the perturbations are not assigned to their original class. We also show that classification stability decreases when fewer genes are selected.
Identity Fusion

Identity fusion is a visceral sense of “oneness” with a group and its individual members that motivates personally costly, pro-group behaviors. Past approaches, most notably social identity theory, have assumed that when people align with groups, the group category eclipses both the personal self and the relationships among individual group members. Also, social identity researchers have focused on intergroup processes. In contrast, fusion theory emphasizes the role of the personal self and intragroup relationships in extreme pro-group action. Strongly fused persons are especially inclined to endorse pro-group action when either the personal or the social self is salient, when physiological arousal is high, or when they perceive that group members share essential qualities (e.g., genes, core values) with one another. Moreover, feelings of personal agency, perceptions of family-like ties to other group members, and a sense of group-related invulnerability mediate the link between identity fusion and pro-group behaviors. All of these effects emerged while controlling for identification, which predicted the effects weakly if at all. By specifying some of the key antecedents of extreme pro-group behavior as well as the role of the personal self and familial ties in such behavior, the identity-fusion approach fills an important explanatory gap left largely unaddressed by earlier perspectives.
USING QUALITY FUNCTION DEPLOYMENT IN SOFTWARE REQUIREMENTS SPECIFICATION

We present in this paper an approach to requirements specification based on quality function deployment (QFD). We discuss how techniques like QFD with accompanying tool-support can contribute to the development of high quality requirements models that are the basis for information systems that are perceived as valuable by the stakeholders of the systems. Based on the practical application of this technique on a number of information systems projects, including both traditional development projects and the implementation of packaged solutions, it is our experience that the quality of requirements specifications can be improved by using this technique, in particular when used together with groupware tools supporting the overall process. Especially, what we term semantic, pragmatic, and social quality are often affected positively. On the other hand, the QFD-technique is not sufficient alone, but needs to be combined with other RE-techniques such as prototyping, observations, and more traditional conceptual modeling to be able to cover and analyze all types of systems requirements.
Comprehensive indoor remote tracking system

Nowadays, the number of indoor areas which are multi-layered, complex and spread to large areas is increasing. Because of that, location-based tracking systems have become an important place in the indoor areas. In our country, there isn't any system and service which provides tracking for indoor locations. In this study, indoor positioning system for remote tracking (U-TAKİP) has been developed. Using sensor network which will be set in the area and K-NN algorithm on the central server remote tracking (people / objects) system has been developed. As signal resource wearable or portable Bluetooth Low Energy tags was used. Use areas of the application is defined as personnel tracking, patient tracking, child tracking, logistics tracking.
Microeconomic Models for Long Memory in the Volatility of Financial Time Series

We show that a class of microeconomic behavioral models with interacting agents, derived from Kirman (1991) and Kirman (1993), can replicate the empirical long-memory properties of the two first-conditional moments of financial time series. The essence of these models is that the forecasts and thus the desired trades of the individuals in the markets are influenced, directly or indirectly, by those of the other participants. These "field effects" generate "herding" behavior that affects the structure of the asset price dynamics. The series of returns generated by these models display the same empirical properties as financial returns: returns are I (0), the series of absolute and squared returns display strong dependence, and the series of absolute returns do not display a trend. Furthermore, this class of models is able to replicate the common long-memory properties in the volatility and covolatility of financial time series revealed by Teyssière (1997, 1998a). These properties are investigated by using various model-independent tests and estimators, that is, semiparametric and nonparametric, introduced by Lo (1991), Kwiatkowski et al. (1992), Robinson (1995), Lobato and Robinson (1998), and Giraitis et al. (2000, forthcoming). The relative performance of these tests and estimators for long memory in a nonstandard data-generating process is then assessed.
Mirror-Like Gabor Features for Face Recognition under Varying Illumination Conditions

As is well known, face recognition under varying illumination conditions remains one of the most challenging tasks. How to achieve illumination invariant features is the key issue of face recognition. This paper provides a novel face recognition method using mirror-like Gabor features (MGF). The paper first presents the process of even/odd MGF extraction. It then demonstrates that the even MGF are superior to the odd ones in terms of robustness and efficient matching, providing relevant theoretical analysis from the point of view of the Fisher criterion and statistics. Finally, it describes comparison experiments on the YaleB face database and offers valuable conclusions.
Job Creation by Company Size Class: Concentration and Persistence of Job Gains and Losses in Canadian Companies

The statistical observation that small firms have created the majority of new jobs during the 1980s has had a tremendous influence on public policy. Governmentshave looked to the small firm sector for employment growth, and have promoted policies to augment this expansion. However, recent research in the US suggeststhat net job creation in the small firm sector may have been overestimated, relative to that in large firms. The first part of this paper addresses various measurement issues raised in the recent research, and uses a very unique Canadian longitudinal data set thatencompasses all companies in the Canadian economy to reassess the issue of job creation by firm size. We conclude that over the 1978-92 period, for both theentire Canadian economy and the manufacturing sector, the growth rate of net and gross employment decreases monotonically as the size of firm increases, no matterwhich method of sizing firms is used. Measurement does matter, however, as the magnitude of the difference in the growth rates of small and large firms is verysensitive to the measurement approaches used. Part one of the paper also produces results for various industrial sectors, and examines employment growth inexisting small and large firms (i.e., excluding births). It is found that employment growth in the population of existing small and large firms is very similar. Finallyattempts are made to introduce a job quality aspect to the numbers by using payroll distributions rather than employment. The net and gross rates of increase anddecrease in payrolls by firm size are found to be only marginally different than those of employment. The second part of the paper looks at concentration of employment creation and destruction within size classes. This is relevant because if growth is highlyconcentrated, knowing that a firm is small will provide little information about its prospects for growth. Most small firms would grow relatively little, or decline, whilea few expanded a lot. It is found that both job creation and destruction is highly concentrated among relatively few firms in all size groups, but it is greater amongsmall and mid-sized companies than large. Finally attempts are made to correlate the performance of businesses over two three-year periods. It is found thatknowing that a firm is a high performer (in terms of jobs created) over one period is of only limited value in determining growth in the second period. This isparticularly true among small firms. These results suggest that firms which expand rapidly during one period are replaced to some considerable degree by others inthe subsequent period.
Improved Image Thresholding Based on 2-D Tsallis Entropy

The 2-D maximum Tsallis entropy (2DMTE) method not only considers the distribution of the gray information and the spatial neighbor information with using the 2-D histogram of the image, as a global threshold method, but also it often gets better segmentation results and flexibility owing to a parameter than other 2-D entropy methods. However, its performance is sensitive to its parameter. How to choose the parameter is often an obstacle in real time application systems. In this paper, improved image segmentation based on two-dimensional Tsallis entropy is presented. Firstly, the parameter of Tsallis entropy’s method is changed into two parameters, then, the middle value of the image probability distribution is obtained, finally, according to it, the parameters are selected adaptively. Experimental results show the proposed approach can get much better segmentation result than the previous 2-D thresholding methods.
Coherent Inference on Optimal Play in Game Trees

Round-based games are an instance of discrete planning problems. Some of the best contemporary game tree search algorithms use random roll-outs as data. Relying on a good policy, they learn on-policy values by propagating information upwards in the tree, but not between sibling nodes. Here, we present a generative model and a corresponding approximate message passing scheme for inference on the optimal, o-policy value of nodes in smooth and/or trees, given random roll-outs. The crucial insight is that the distribution of values in game trees is not completely arbitrary. We dene a generative model of the on-policy values using a latent score for each state, representing the value under the random roll-out policy. Inference on the values under the optimal policy separates into an inductive, pre-data step and a deductive, post-data part. Both can be solved approximately with Expectation Propagation, allowing o-policy value inference for any node in the (exponentially big) tree in linear time.
Prevalence of Nonclassic Congenital Adrenal Hyperplasia in Turkish Children Presenting with Premature Pubarche, Hirsutism, or Oligomenorrhoea

Background. Nonclassic congenital adrenal hyperplasia (NCAH), caused by mutations in the gene encoding 21-hydroxylase, is a common autosomal recessive disorder. In the present work, our aim was to determine the prevalence of NCAH presenting as premature pubarche (PP), hirsutism, or polycystic ovarian syndrome (PCOS) and to evaluate the molecular spectrum of CYP21A2 mutations in NCAH patients. Methods. A total of 126 patients (122 females, 4 males) with PP, hirsutism, or PCOS were included in the present study. All patients underwent an ACTH stimulation test. NCAH was considered to be present when the stimulated 17-hydroxyprogesterone plasma level was >10 ng/mL. Results. Seventy-one of the 126 patients (56%) presented with PP, 29 (23%) with PCOS, and 26 (21%) with hirsutism. Six patients (4,7%) were diagnosed with NCAH based on mutational analysis. Four different mutations (Q318X, P30L, V281L, and P453S) were found in six NCAH patients. One patient with NCAH was a compound heterozygote for this mutation, and five were heterozygous. Conclusion. NCAH should be considered as a differential diagnosis in patients presenting with PP, hirsutism, and PCOS, especially in countries in which consanguineous marriages are prevalent.
A new approach based on the serological tests and the Delayed Hyper Sensitivity Tests for the diagnosis of canine leishmaniasis

Several responses in the form of serological tests ELISA (Enzyme Linked Immuno Sorbent Assay), IIF (Indirect Immuno Fluoresence) and DHST (Delayed Hyper Sensitivity Tests) can be used to detect leishmania parasite infection in dogs. In this paper, we propose a new method to select the most discriminative tests based on determinant criterion. So, the diagnosis of canine leishmaniasis (CanL) can be improved by reducing the number of features. Moreover, an artificial neural networks (the Multilayer Preceptron neural network) is applied to classify subjects into two groups: positive (sick) and negative (not sick). The correlation between the physical and the pathological state of subjects is specified with multiple attempts. These methods are obtained with considering chain of experiences that allow for fairly reliable and highly effective results which enable us to develop an efficient way to estimate the diagnosis of this disease. After many experiments, we notice that the best combination of the three studied tests is the DHST and IIF tests.
Towards predictive structure-based models of evolved drug resistance

The evolution of drug resistance in malaria continues to be a widespread concern. Many of these drugs target key proteins such as dihydrofolate reductase (DHFR). However in malaria, the structural plasticity of DHFR allows it to maintain its active site and catalytic activity, while resisting drug binding. One way to better understand this process is through the appreciation of DHFR structural evolution in general, and then use in silico evolution to model both the drug docking and the likely amino acid changes in DHFR that will occur as a result. Using a comprehensive phylogenetic analysis of DHFR, we have generated a method that generates variant DHFR proteins and sequentially scores the docking of the natural cofactor NADPH and the known anti-malarial drug pyrimethamine in order to determine fitness. Iteration of this process allows the opportunity to model the coevolutionary processes involved with drug resistance and to predict responses to pharmaceuticals in advance of their use in the field.