Miracle-dz/UniFAR-FTUs huggingface dataset:
Functional Logic Programming with Distributed Constraint Solving

The main goal of this the thesis is to design efficient calculi that can serve as operational semantics of a higher-order functional logic programming language and their distributed implementation on a network of computers. The main advantages of higher-order logic versus first-order logic are quantification over functions and predicates and its abstraction mechanism. Higher-order programming is standard in functional programming languages, and recent languages such as λ-Prolog illustrate the practical utility of higher-order logic programming. Currently, functional logic programming is mainly restricted to first-order logic, although recent years witnessed a growing interest to extend the operational principles of functional logic programming to higher-order logic. In this thesis we present various lazy narrowing calculi for higher-order logic. We prove that our calculi satisfy essential properties, such as being sound and complete, if the functional logic programs satisfies certain restrictions. In general, the restrictions investigated by us are widely accepted by the functional logic community, or are higher-order generalizations of restrictions which are standard in first-order functional logic programming. We claim that the calculi proposed in the thesis are better choices for an operational semantics of higher-order functional logic programming than what we have found in the literature. Secondly, in order to improve the solving capability of a higher-order functional logic programming language, we aim at integrating the operational principles of higher-order lazy narrowing and of concurrent constraint solving. Concurrent constraint solving is already recognized as a viable approach to integrate the constraint solving capabilities of various constraint solvers in a system that can solve problems that none of the single solvers can handle alone. We define a scheme CFLP(X ,S, C) for constraint logic programming, which describes the integration of a higher-order lazy narrowing calculus C (the functional logic component) with the operational principle of a solver cooperation over a constraint domain X . The solver cooperation is defined
Workforce survey of occupational exposures and health effects in New Zealand : a thesis by publications presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Epidemiology at Massey University, Wellington, New Zealand

CH3. This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Annals of Occupational Hygiene following peer review. The definitive publisher-authenticated version Eng, A. , 'T Mannetje, A. , Cheng, S. , Douwes, J., Ellison-Loschmann, L. , McLean, D. , et al. (2010). The New Zealand workforce survey I: Self-reported occupational exposures. Annals of Occupational Hygiene, 54(2), 144-153 is available online at: http://annhyg.oxfordjournals. org/content/54/2/144.full. CH5. Eng, A. , t Mannetje, A. , Ellison-Loschmann, L. , McLean, D. , Cheng, S. , & Pearce, N. (2011). Ethnic differences in patterns of occupational exposure in New Zealand. American Journal of Industrial Medicine, 54(5), 410-418 The definitive version is available at www3.interscience. wiley.com or http://onlinelibrary.wiley.com/doi/10.1002/ajim.20934/full. CH6. This is a pre-copy-editing, author-produced PDF of an article accepted for publication in The annals of occupational hygiene following peer review. The definitive publisher-authenticated version Eng, A. , ‘T Mannetje, A. , Douwes, J., Cheng, S. , McLean, D. , Ellison-Loschmann, L. , & Pearce, N. (2010). The New Zealand Workforce Survey II: Occupational Risk Factors for Asthma. Annals of Occupational Hygiene, 54(2), 154-164 is available online at: http://annhyg.oxfordjournals. org/content/54/2/154.full.
Localization of Network Nodes for Extra-Terrestrial Deployment

Objectives The topic of sensor networks has received a thorough treatment in academic literature and has even begun to make appearances in the popular press. It has even been suggested that sensor network technology be deployed in spacecraft missions. Once a sensor node has been safely delivered to an extra-terrestrial surface the first thing it must know is its location relative to the rest of the network. Therefore our work will primarily concentrate on localization algorithms. This work can be applied to similarly developed technologies such as sensor webs described in Delin et al. [5, 3, 4]. In this work we will show that the APIT[7] algorithm is mathematically unsound due to a problem with dead spots not characterized in the original work. In addition we will test two of the more popular algorithms including centroid[2] and trilateration [6, 8] using metrics of energy consumed, accuracy of localization and ease of implementation to evaluate each algorithm. We will develop software implementations of these two algorithms and deploy them on test hardware for our experiments.
Parameter estimation for online condition monitoring of robotic machines

This paper proposes a novel learning approach to online condition monitoring of robotic machines. The real-time learning process comprises three stages, domain knowledge defining, random learning and ordinal learning. Domain knowledge defining abstracts the model of a robotic machine; random learning and ordinal learning stages train the parameters of the abstract model with random data selection and ordinal data selection, respectively. Simulation results have proved that the pro-posed method is efficient and feasible for online fault diagnosis of robotic machines.
Application Value of Slider-Crank Mechanism in Pick-and-Place Operation of Delta Robot

By absorbing the advantages of the rotary-driven Delta robot and linear-driven Delta robot, a Delta robot for pick-and-place operation that forms a crank-slider at the drive joint is designed.To take the most common gate shaped curve in Cartesian space as the motion trail of robotic pick-and-place operation, according to the kinematics inverse solution theory of Delta robot, this thesis mainly solves the output angular velocity of robot-driven joint. Establishing the static transfer mathematical model and solving the forced condition of driving joint. The simulation analysis show that after the upper slider-crank mechanism is connected to the driving joint, the angular velocity of the driving joint changes suddenly, which caused a rigid impact on the robot in the picking and releasing operation, though the force of the driving joint can be made smaller.
Laura's Long Winter: Putting the hard winter of 1880-81 into perspective

The winter of 1880-81 was strikingly difficult across much of the Plains and Midwest, so much so that it was featured in the Laura Ingalls Wilder historical fiction account, The Long Winter (Wilder 1940; Fig. 1), as well as in several town histories across the region. The Long Winter takes place in DeSmet, South Dakota, which is 60 km west of Brookings and 53 km east of Huron, South Dakota. While the book, as with the rest of the Little House series by Laura Ingalls Wilder, was a fictionalized account of her childhood experiences, much of the book strongly parallels the experience of the Ingalls family. Both meteorological records and non-meteorological accounts indicate that the winter was particularly long, snowy, and cold.
Development of methodologies for evaluating performance of fault detection and diagnostics protocols applied to unitary air-conditioning equipment

Yuill, David, P. Ph.D., Purdue University, December 2014. Development of Methodologies for Evaluating Performance of Fault Detection and Diagnostics Protocols Applied to Unitary Air-Conditioning Equipment. Major Professor: James E. Braun, Ph.D., School of Mechanical Engineering. This thesis describes the development of standardized methodologies and methods for evaluating the performance of fault detection and diagnostics (FDD) protocols that are intended for air-cooled vapor compression unitary air-conditioners. Although there are currently many FDD protocols available commercially and there are jurisdictions in which the building codes require FDD, there is currently no standardized method to determine how effective the FDD might be at detecting and diagnosing faults. An FDD evaluation method is proposed, in which the evaluator passes data from a large number of scenarios to a candidate FDD protocol, and collects the response from each scenario. The possible results for each scenario are: (a) No Response; (b) Correct; (c) False Alarm; (d) Misdiagnosis; (e) Missed Detection; (f) No Diagnosis. The set of all responses is organized by considering the impact of the fault on the system’s cooling capacity and efficiency for each scenario. This is referred to as fault-impact-based evaluation.
Effect on the mobility of metal atoms on the structure of thin films deposited at oblique incidence

• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.
Comparing tabular parsers for Tree Adjoining Grammars

Most of tabular parsing algorithms for tree adjoining grammars has been demonstrate to attain a theoretical worst-case time complexity of O(n 6), where n is the length of the input string. In this work we study the experimental complexity of a variety of tabular parsers for tree adjoining grammars for the case of formal and natural language grammars.
Automating the meta theory of deductive systems

This thesis describes the design of a meta-logical framework that supports the representation and veri cation of deductive systems, its implementation as an automated theorem prover, and experimental results related to the areas of programming languages, type theory, and logics. Design: The meta-logical framework extends the logical framework LF [HHP93] by a meta-logic M+2 . This design is novel and unique since it allows higher-order encodings of deductive systems and induction principles to coexist. On the one hand, higher-order representation techniques lead to concise and direct encodings of programming languages and logic calculi. Inductive de nitions on the other hand allow the formalization of properties about deductive systems, such as the proof that an operational semantics preserves types or the proof that a logic is consistent. M+2 is a proof calculus whose proof terms are recursive functions that may be de ned by cases and range over dependent higher-order types. The soundness of M+2 follows from a realizability interpretation of proof terms as total recursive functions. Implementation: A proof search algorithm for proof terms inM+2 is implemented in the metatheorem prover that is part of the Twelf system [PS99b]. Its takes full advantage of higher-order encodings while using inductive reasoning. Experiments: Twelf has been used for many experiments. Among others, it proved automatically the Church-Rosser theorem for the simply-typed -calculus and the cut-elimination theorem for intuitionistic rst-order logic. In programming languages, it proved various type preservation theorems for di erent operational semantics and compiler correctness theorems. In logics, it was able to derive the equivalence of various logic calculi, such as the natural deduction calculus, the sequent calculus, and the Hilbert calculus. Twelf also proved that Cartesian closed categories can be embedded into the simply-typed -calculus. In the special domains of programming languages, type theory, and logics, Twelf's reasoning power far exceeds that of any other theorem prover.
AnalyzeFMRI: an R package to perform statistical analysis on FMRI datasets

AnalyzeFMRI is a developing package, initiated by J. Marchini, for the processing and analysis of large structural Magnetic Resonance Imaging (MRI) and Functional MRI (FMRI) datasets. In this presentation, we first introduce MRI and fMRI to enlight the data specificities and the main image processing steps. We then describe the current package version and the functionnalities we have recently added, mainly NFTI format management, cross-platform visualization based on Tcl/TK components and temporal and spatial IC analysis. We illustrate our presentation with examples coming from human visual experiments [1,2], especially demonstrating the interest of spatial and temporal IC analysis [3] compared to standard general linear model [4]. We conclude about the interest of the AnalyzeFMRI package for the exploration of MRI data and outline our plans for future extensions
Empirical Analysis of Traditional Link Prediction Methods

Online Social Networks are growing exponentially due to which a lot of researchers are working on Social Network analysis. Link Prediction is a task of predicting new links that may occur in future in the social network. The link prediction problem has generated a lot of interest due its widespread applicability across many domains. We conducted a study on the different methods that have been developed for link prediction. In most of these methods, the social network is modeled as a graph, and the links are predicted based on the similarities between two nodes. We have chosen seven widely used similarity methods in our study. We found that on the simulated data sets, Sorenson index method and Jaccard coefficient method performed well when compared to other methods.
Suppression of blocking artifact in compressed image

Image compression is actually major content for certain perspectives in the area of interactive media communication. Image processing is the mechanism for handling different kinds of images, processed images can be stored routinely and conveyance of such kind of images from one place to another place becomes simple to the user. By using image compression technique we are able to represent the image with lesser number of data bits. image compression execution can cut down the bandwidth and the volume of the data to be transmitted. (BDCT) block-based discrete cosine transform is long establish used transform for the two static and uninterrupted images. While we compress any kind of image by lossy type of image compression technique then there will be loss of data bits, we have to confrontation unwanted artifacts ringing and blocking artifacts and when we want to restore such kind of image then we face problem of blurring of images, which is sometimes called as the annoying artifacts problem near the block of the image. The recovered images from jpeg compression create blocking artifact near block boundaries of the image in high compression. Artifacts take on several forms in images. We are going to focus on blocking artifacts at medium and high level compression. Various types of images can be processed and we can diminish blocking artifacts up to tolerable level. Some standard techniques MPEG and JPEG are used in video and image processing field respectively for the compression. Lossy image compression technique is used in photographic images because loss of bits is tolerable, Since last few decades, image compression in real time applications has been a provocative field for image processing professionals. To recover original image decompression succeed by the different post processing techniques. High quality image communication with low-bit rate.
Factors affecting source of family planning services in India

This report analyzes the relative importance of the public and private sectors in the provision of family planning services in India. The analysis is based on data from Indias National Family Health Survey (NFHS) conducted in 1992-93. The NFHS collected socioeconomic demographic and health information from the nationally representative sample of 88562 households comprising 541827 individuals. The unit analysis was undertaken on the 30741 women in the sample who were current users of modern contraceptive methods. Seven predictor variables were included in the regression analyses (womans age residence level of educational attainment religion level of exposure to electronic mass media and region). These variables were included because they were known to have substantial effects on contraceptive use and also because they were likely to affect how women chose family planning services. Supporting data are clearly presented in tables and graphs. The results of this study imply that contrary to expectations the proportion of women in different states of India who obtain family planning services from the private sectors bears little relation to state-level fertility rates. The correlation between the total fertility rate and the percentage relying on private sector sources of family planning was only 0.11% which further suggests that increased use of the private sector is clearly not a prerequisite for achieving low fertility. Overall 18% of women who used modern contraception obtained their method most recently from the private sector and among the 7 demographic and socioeconomic variables only urban versus rural residence and education consistently affected the use of private-sector family planning services.
• AN ENHANCED ALGORITHM FOR IMPROVING THE EFFICIENCY OF K-MEANS AND K-MEDOID CLUSTERING USING NORMAL DISTRIBUTION DATA POINTS

Clustering is one of the unsupervised learning method in which a set of essentials is separated into uniform groups. The K-Means method is one of the most widely used clustering techniques for various applications. paper proposes a method for making the K-Means algorithm more effective and Efficient, so as to get better clustering with reduced complexity. In this research, the most representative algorithms K-Means and K-Medoids and proposed K-Means were examined and analyzed based on their basic approach. The best algorithm in each category was found out based on their performance using Normal Distribution data points. The accuracy of the algorithm was investigated during different execution of the program using Normal Distribution input data points. colors and the execution time is calculated in milliseconds. This paper deals with a method for improving efficiency of the K-Means algorithm and analyze the elapsed time is taken by Efficient K-Means is less than K-Means and K-Medoid algorithm.
Modèles, primitives et méthodes de suivi pour la segmentation vasculaire. Application aux coronaires en imagerie tomodensitométrique 3D.

The segmentation of vascular structures is a fundamental step for diagnosis assistance and treatment. In this context, image processing techniques aim at easing and speeding up reviewing tasks by medical professionals, reducing the amount of manual interaction and lowering inter-operator variability. We first present an extensive bibliographical review of existing methods for 3D vascular segmentation following three axes of study: geometric and appearance models, image features and extraction schemes. In this work, we focus on a particularly challenging problem, the delineation of coronary arteries from 3D cardiac Computed Tomography Angiographic (CTA) data. We first detail our medial-based geometric model, which we evaluate on the image thanks to a fast, oriented, gradient flux-based medialness feature. We then formulate a recursive Bayesian model, which is learned in a non-parametric fashion from a ground-truth database of manually segmented datasets. We propose two separate extraction schemes to perform the actual segmentation. Our first strategy performs a discrete, graph-based optimization propagating minimal paths on a 4D (position+radius) graph. It exploits a new cumulative cost metric derived from our seminal Bayesian formulation. Our second strategy employs a sequential, stochastic Monte-Carlo tracking approach which successively estimates the posterior distribution of our Bayesian model through a population of random samples. For both approaches, particular attention is given to robustness and computational efficiency. Qualitative and quantitative evaluation is presented on a varied database of clinical data.
Constructing Retinal Fundus Photomontages

Methods. Patients with retinal degeneration underwent fundus photography with a 45° fieldof-view fundus camera. Individual photographic slides were digitized for creating fundus montages. Background variations in individual 45° images were modeled to first- or secondorder two-dimensional polynomial functions to generate a background image. The background image was subtracted from the original image to obtain background corrected image. Background corrected images were registered and spatially transformed using a first- or second-order two-dimensional polynomial warp model to reconstruct a composite retinal fundus montage. Results. The authors successfully reconstructed 24-bit color, 100° field-of-view, composite retinal fundus images. The computer-reconstructed montages are an improvement over manually generated montages because computer analysis can be performed on the computer-based montages. In addition, background variations and discontinuities between individual photographs observed in manually generated montages are reduced gready in computer-generated montages. Most important, the computer-generated montages are better aligned than the manually generated photomontages. Conclusions. This method of reconstructing a wide-angle composite retinal fundus image from a set of adjacent small- and wide-angle fundus slides is a new tool for creating montages as large as 100° field of view. The computer-generated montages may be used for documenting and quantifying retinal findings. This can gready assist studies of retinal manifestations of diseases, such as gyrate atrophy, retinitis pigmentosa, sickle cell disease, and acquired immune deficiency syndrome. Invest Ophthalmol Vis Sci. 1996; 37:1675-1683. -Tundus imaging has been used to document and monitor retinal changes in persons with diseases such as age-related macular degeneration, diabetic retinopathy, retinitis pigmentosa, acquired immune deficiency syndrome, and gyrate atrophy. With the development of image processing equipment and tech
A multiprocessor data flow accelerator module

Real-time controllers often need to minimize the latency between the arrival of a stimulus and the delivery of a control signal. Using multiprocessors to compute the control algorithm is appealing for these applications, but problem decomposition and load leveling are not straightforward. The data flow model of computation offers a solution which can be implemented for shared memory, parallel processors by the addition of a single circuit board. A typical parallel processor, the data flow model, and several versions of the Data flow Accelerator Module (DFAM) are presented together with some preliminary results. 15 refs., 12 figs.