Miracle-dz/UniFAR-FTUs huggingface dataset:
On the evaluation of the LTE-advanced proposal within the Canadian evaluation group (CEG) initiative: Preliminary work results

In this paper, we present a preliminary work within the CEG to evaluate the LTE-advanced proposal as a candidate for further improvements of LTE earlier releases. We consider an open-source LTE simulator that implements most of the LTE features. We focus on channel state variations and related link adaptation. We study the performance of channel quality report to the transmitter to track the downlink time-frequency channel variations among users. This process aims at performing link adaptation. To insure this procedure, we implement a CQI feedback scheme to an LTE open-source simulator. SINRs per subcarriers are computed supposing a perfect channel knowledge then mapped into a single SINR value for the whole bandwidth. This SINR is represented by a CQI value that allows for dynamic MCS allocation. CQI mapping is evaluated through different SINR mapping schemes.
The Rebirth of a Medieval Pilgrimage Route: A Study of the Modern-day Via Francigena Pilgrims

iii List of Tables . vi List of Figures . vii Acknowledgments . x Chapter 1: The Via Francigena Rebirth . 1 HISTORY OF THE VIA FRANCIGENA . 3 THE MODERN-DAY VIA FRANCIGENA . 12 THE VIA FRANCIGENA STUDY . 20 Chapter 2: Literature Review . 21 PILGRIMAGES OF THE PAST . 21 STUDY OF CONTEMPORARY PILGRIMAGE . 25 THE NON-RELIGIOUS PILGRIMAGE . 27 Chapter 3: Methods . 32 QUESTIONNAIRE: CRITERIA, RECRUITMENT, AND INSTRUMENT . 32 INTERVIEWS . 36 PERSONAL EXPERIENCE . 37 Chapter 4: Findings . 38 SURVEY RESULTS . 38
RABBIT: An interface for database access

A new kind of user interface for information retrieval has been designed and implemented to aid users in formulating a query. The system, called RABBIT, relies upon a new paradigm for retrieval by reformulation, based on a psychological theory of human remembering. The paradigm actually evolved from an explicit attempt to design a 'natural' interface which imitated human retrieval processes. To make a query in RABBIT, the user interactively refines partial descriptions of his target item(s) by criticizing successive example (and counterexample) instances that satisfy the current partial description. Instances from the database are presented to the user from a perspective inferred from the user's query description and the structure of the knowledge base. Among other things, this constructed perspective reminds users of likely terms to use in their descriptions, enhances their understanding of the meaning of given terms, and prevents them from creating certain classes of semantically improper query descriptions. RABBIT particularily facilitates users who approach a database with only a vague idea of what it is that they want and who thus, need to be guided in the (re)formulation of their queries. RABBIT is also of substantial value to casual users who have limited knowledge of a given database or who must deal with a multitude of databases.
An Analytically Tractable Model for Pricing Multiasset Options with Correlated Jump-Diffusion Equity Processes and a Two-Factor Stochastic Yield Curve

This paper shows how to value multiasset options analytically in a modeling framework that combines both continuous and discontinuous variations in the underlying equity or foreign exchange processes and a stochastic, two-factor yield curve. All correlations are taken into account, between the factors driving the yield curve, between fixed income and equity as asset classes, and between the individual equity assets themselves. The valuation method is applied to three of the most popular two-asset options.
103 Real Estate Ownership by Non-Real Estate Firms: The Impact on Firm Returns

For many years operating companies around the world generally have owned their realestate assets. In the United States alone it is estimated that corporate users own nearly $2 trillion,or roughly half of all commercial property. Companies own not only their production facilities,but frequently their offices, warehouses, and retail outlets. Although many of these properties aresuitable for a broad range of users, these operating companies choose to commit their scarcecapital to the ownership and operation of real estate, rather than re-deploying this capital to theircore operating businesses.
Adaptive motion selection for online hand–eye calibration

SUMMARY While a robot moves, online hand–eye calibration to determine the relative pose between the robot gripper/end-effector and the sensors mounted on it is very important in a vision-guided robot system. During online hand–eye calibration, it is impossible to perform motion planning to avoid degenerate motions and small rotations, which may lead to unreliable calibration results. This paper proposes an adaptive motion selection algorithm for online hand–eye calibration, featured by dynamic threshold determination for motion selection and getting reliable hand–eye calibration results. Simulation and real experiments demonstrate the effectiveness of our method.
Challenges and Solutions in Constructing a Microsimulation Model of the Use and Costs of Medical Services in Australia

This paper describes the development of a microsimulation model =HealthModÂ‘ which simulates the use and costs of medical and related services by Australian families. Australia has a universal social insurance scheme known as =MedicareÂ‘ which provides all Australians with access to free or low-cost essential medical services. These services are provided primarily by general practitioners as well as specialist doctors but also include diagnostic and imaging services. Individuals may pay a direct out-of pocket contribution if fees charged for services are higher than the reimbursement schedule set by government. HealthMod is based on the Australian 2001 National Health Survey. This survey had a number of deficiencies in terms of modelling the national medical benefits scheme. The article outlines three major methodological steps that had to be taken in the model construction: the imputation of synthetic families, the imputation of short-term health conditions, and the annualisation of doctor visits and costs. Some preliminary results on the use of doctor services subsidised through AustraliaÂ‘s Medicare are presented.
Groupwise image registration of multimodal head-and-neck images

Fusion of multimodal medical images using deformable registration is of high interest for head-and-neck tumour treatment planning. In this context, more than two images often have to be aligned for a given patient. The conventional, pairwise way to register multiple images is to select one of them as fixed reference and independently align each remaining image with it. An alternative method would be to simultaneously register the images using a groupwise registration scheme, thus eliminating the need to select a reference image and avoiding any bias due to this arbitrary choice. In this study, we propose a novel groupwise image registration technique, combining a principal component analysis (PCA) based similarity metric and modality independent neighbourhood descriptors (MIND). Results on 16 patients show that the images are slightly better aligned when using the proposed registration method than when using pairwise registration.
Forecasting North Dakota Fuel Tax Revenue and License and Registration Fee Revenue

A literature review was conducted to determine the level and methods of forecasting used by states for fuel tax revenue collections and license and registration fees. The literature revealed that most state Departments of Transportation use statistical or econometric models to forecast revenue of fuel tax and license and registration fee revenue. A survey was conducted to ask states about their models. All states responding to the survey use a statistical or econometric model to forecast. It was also found that most states have some problem with forecasting error in times of economic recession or other economic shock. The survey revealed results similar to the literature review and also revealed that states model cash flow in an attempt to estimate cash balances. Models were fit to the North Dakota data to estimate fuel tax and license and registration fees. The models provide reasonable forecasts, however the model for the license and registration fees does not seem to be as good a fit as the fuel model because of variations in the data.
Learning Discriminative and Transformation Covariant Local Feature Detectors

Robust covariant local feature detectors are important for detecting local features that are (1) discriminative of the image content and (2) can be repeatably detected at consistent locations when the image undergoes diverse transformations. Such detectors are critical for applications such as image search and scene reconstruction. Many learning-based local feature detectors address one of these two problems while overlooking the other. In this work, we propose a novel learning-based method to simultaneously address both issues. Specifically, we extend the covariant constraint proposed by Lenc and Vedaldi [8] by defining the concepts of standard patch and canonical feature and leverage these to train a novel robust covariant detector. We show that the introduction of these concepts greatly simplifies the learning stage of the covariant detector, and also makes the detector much more robust. Extensive experiments show that our method outperforms previous hand-crafted and learning-based detectors by large margins in terms of repeatability.
Privatization of Welfare Services: A Review of the Literature

The use of private organizations to perform social service functions has increased greatly in the past few years, although little is known about the privatization of welfare services. This report reviews the literature to set the stage for a study looking at the experiences of six agencies that privatized TANF case management. In addition to describing the current extent of privatization, the report looks at organizations that are doing it, arguments for using it, and challenges it presents.
Corporate Governance and Financial Crises

This paper focuses on answering the three following questions: (1) Does corporate governance matter in financial crisis? And how does it matter? (2) Does the effect of corporate governance level on crisis in developing countries differ from that in developed countries? Why? (3). Does weak corporate governance make countries more vulnerable during global financial crisis? Theoretically, the contribution of corporate governance to financial crises is through two channels. The first channel is that weak corporate governance increases aggressive risk taking of financial institutions’ managers (Tarraf (2011)) and may cause a rise in the probability of crisis. The second explanation is proposed by Johnson and all (2000) that managerial agency problems can make countries with weak legal systems vulnerable to the effects of sudden loss of investor confidence. When the country experiences even a small loss in confidence, weak corporate governance can cause a sharp increase in net outflow of capital since the foreign investors think they will be stolen more. As a result, exchange rate increases. Using the macroeconomic data and Worldwide Governance Indicators of 14 countries from 1996-2014, I find that besides economic fundamentals, better corporate governance reduces significantly the probability of financial crises, especially in Asian countries and in developed ones. This effect is consistent in the global crisis period for the Asian ones while it seems to be smaller for the developed ones. Similarly, corporate governance reduces the depreciation of the exchange rate. However, corporate governance indicators only influence the exchange rate in developing countries during the global financial crisis. Fulbright Scholar at Ross School of Business, The University of Michigan Associate professor at Department of Finance, DaNang University of Economics, DaNang University
Formalizing Data Quality and its Influence on Business Performance

A research thesis into how to determine the influence of data quality on business performance using methodologies form the field of data uncertainty and data quality. A model is explained and validated which uses principles of probabilistic databases to show the uncertainty of information used in decisions. This uncertainty is based on the data quality of the source data. Finally the thesis shows how this influences business performance.
Immune Activation of NF-κB and JNK Requires Drosophila TAK1*

Stimulation of the Drosophila immune response activates NF-κB and JNK signaling pathways. For example, infection by Gram-negative bacteria induces the Imd signaling pathway, leading to the activation of the NF-κB-like transcription factor Relish and the expression of a battery of genes encoding antimicrobial peptides. Bacterial infection also activates the JNK pathway, but the role of this pathway in the immune response has not yet been established. Genetic experiments suggest that the Drosophila homolog of the mammalian MAPK kinase kinase, TAK1 (transforming growth factor β-activated kinase 1), activates both the JNK and NF-κB pathways following immune stimulation. In this report, we demonstrate that Drosophila TAK1 functions as both the Drosophila IκB kinase-activating kinase and the JNK kinase-activating kinase. However, we found that JNK signaling is not required for antimicrobial peptide gene expression but is required for the activation of other immune inducible genes, including Punch, sulfated, and malvolio. Thus, JNK signaling appears to play an important role in the cellular immune response and the stress response.
What Does Volume Reveal: A Study of the Indian Single Stock Futures Market

A single stock future is a relatively new type of exchange-traded derivative that has become popular in some of the emerging financial markets. In order to uncover any information effect of trading volume, a cogent question to ask is whether a relationship exists between the volume of trade on the underlying stock and the number of its single stock futures contracts traded. In this paper, we have explored the bi-variate relationship between trading volume of some of the most liquid individual stocks, as well as the single stock futures traded on those stocks in the fast emerging Indian market. Our findings indicate that a significant relationship exists between the trading volumes of the straight stocks and the single stock futures on them.
A journey through early augmentative communication and computer access.

When asked to write an account of the early days of augmentative communication and computer access, I first set out to create a documented history of all the early work and workers. I soon found that the task was beyond the time and resources I had available. For much of the very early work that I could remember, I soon realized I was unable to accurately date or document it, and the principals have died or are dispersed. After a couple of attempts I chose another approach, a personal narrative, which allowed me to both capture some important behind-the-scenes observations and to acknowledge some of those who were critical to this pioneer’s entry, survival, and credited accomplishments. This narrative consists of three parts, and each part tells a different dimension of the story. The first deals with my entry into the field and early support from others. Part 2 discusses the three different fields that converged to form the field of Augmentative Communication. Part 3 touches on some of the early aspects of Computer Access, particularly those that grew out of Augmentative Communication. Although the narrative does capture some of the early history in these areas, its primary purpose is to show the role of individual action or initiative. Although many advances came from organized programs over an extended period of time, much of what has happened is the result of decisions by individuals who in turn caused things to move forward or allowed others to move forward. Often progress has been a chain of such individual events. This narrative seeks to highlight the importance of such individual decisions and action, often by people outside of this field. Without those decisions, actions, or commitments— including those by people unrelated to the field—the field would not have progressed as rapidly, and in some cases would perhaps have developed quite differently.
Political Economy of the Mining Sector in Ghana

With a focus on the institutional set-up and the political environment as central to understanding and rectifying the poor impact of mining on Ghana's economic development, this paper highlights the vulnerabilities in mining sector governance along the industry value chain. The authors explain why it has been difficult to implement policies that would have improved social welfare. They find that incentive problems in institutions directly or peripherally involved in mining governance are a major factor, as are an excessively centralized policy-making process, a powerful executive president, strong party loyalty, a system of political patronage, lack of transparency, and weak institutional capacity at the political and regulatory levels. The paper argues that the net impact of mining on economic development is likely to be enhanced with appropriate reforms in governance. Most importantly, there should be a greater awareness of incentive problems at the political level and their possible implications for sector performance and the economy at large. The set of checks and balances, as stipulated by the Constitution, have to be reinforced. Furthermore, capacity building at different levels and institutions is needed and should be combined with efforts to enhance incentives for institutional performance.
Rhizobia inoculation and liming increase cowpea productivity in Maranhão State

The objetives of the study were to evaluate the agronomic efficiency of strains approved as inoculants for cowpea and of three new strains under selection, as well as to evaluate the influence of liming on the symbiosis and productivity. Two field experiments were conducted using cowpea (BRS Guariba) from June to September 2013. In the first experiment, a completely randomized block experimental design was used, with four replicates and seven treatments (INPA03-11B, UFLA03-84, UFLA03-153, UFLA03-154, UFLA03-164 and two controls). In the second experiment, a 7 x 2 factorial design was used, with the above described treatments being the first factor and liming as the second factor. Parameters evaluated were: nodule dry matter, shoot dry matter, shoot N content and accumulation, number of pods per plant, number of seeds per pod, weight of 100 seeds, grain yield and grain N content and accumulation. Strains UFLA03-153 and UFLA03-164 were more efficient for cowpea inoculation than the strains approved as inoculants, UFLA03-84 and INPA03-11B. Although the tested rhizobia strains and cultivar BRS Guariba are tolerant to soil acidity, productivity washigher when soil was limed. Yields obtained with fertilized and inoculated treatments were well above Maranhao state average.
Improved reproducibility in measuring the laminar thickness on enhanced depth imaging SD-OCT images using maximum intensity projection.

PURPOSE To investigate whether the thin-slab maximum intensity projection (MIP) image improves the reproducibility of the measurement of spectral domain optical coherence tomography (SD-OCT) based lamina cribrosa thickness (LCT). METHODS Optic discs of 63 open angle glaucoma patients or glaucoma suspects were scanned with enhanced depth imaging spectral domain optical coherence tomography (SD-OCT). The B-scan images were constructed three-dimensionally using maximum intensity projection (MIP). The whole mip volume was then cut into thin slabs of two scan-line distance width (approximately 64 μm) at three 3 locations: mid-horizontal, and superior and inferior mid-peripheral regions of the optic nerve head. The LCT was measured in the thin-slab MIP images (LCT-MIP) and the three B-scans corresponding to each thin-slab MIP image (LCT-Bscan) at the three regions in each eye. The interobserver and intraobserver reproducibility of measuring the LCT-MIP and LCT-Bscan were evaluated by calculating the intraclass correlation coefficient (ICC), coefficient of variation (CV), and coefficient of repeatability (CR). The agreement between the LCT-MIP and the LCT-Bscan was assessed by Bland-Altman analysis. RESULTS The thin-slab MIP images provided better image contrast with more distinct borders of the lamina cribrosa compared to the B-scan images. Both intraobserver and interobserver ICCs were higher for LCT-MIP than for LCT-Bscan in all areas. The 95% limit of agreement of measurement differences between LCT-Bscan and LCT-MIP ranged from -29.43 to 32.55 μm. CONCLUSIONS The thin-slab MIP images provided a higher reproducibility in measuring the LCT using SD-OCT than the B-scan images. With thin-slab MIP images, the detection of the laminar borders was more straightforward. This technique should facilitate the evaluation of the lamina cribrosa.
Human activity prediction based on Sub-volume Relationship Descriptor

In this paper, we address the problem of recognizing unfinished human activity from partially observed videos. Specifically, we propose a novel human activity descriptor, which can represent pairwise relationships among human activities in a compact manner using pre-trained Convolutional Neural Networks (CNNs) by capturing the discriminative sub-volume. The potentially important relationship among all pairwise sub-volumes, called key-volumes, is automatically captured using global and local motion activation and the ratio of the participant. The captured key-volumes without prior knowledge hold discriminative information related to the unfinished activity. The key-volume information is considered in the descriptor construction procedure. Training a CNN model for a particular purpose requires a lot of resources, such as large amount of labeled data and computing power, despite its representational power. Thus, we develop a method to utilize pre-trained CNN without any additional model training procedure. The low-level features can be extracted through existing CNN toolkits. For a real application, the proposed method may be more cost-effective while implementing a smart surveillance system to understand human activity. In our experiments, we compare the performances of the proposed method with other state-of-the-art human activity prediction methods for two public datasets; the results of the experiments show that the proposed method outperforms these competing methods.
A robust hair segmentation and removal approach for clinical images of skin lesions

Artifacts such as hair are major obstacles to automatic segmentation of pigmented skin lesion images for computer-aided diagnosis systems. It is even more challenging to process clinical images taken by a regular digital camera, where the shadows of the skin texture may mimic hair-like curvilinear structures. In this study, we examined the popular DullRazor software with a dataset of 20 clinical images. The software, specifically designed for dermoscopic images, was unable to remove fine hairs or hairs in the shade. Alternatively, we proposed using conventional matched filters to enhance curvilinear structures. The more complicate hair intersection patterns, which were known to generate low matched filtering responses, were recovered by using region growing algorithms from nearby detected hair segments with linear discriminant analysis (LDA) based on a color similarity criterion. The preliminary results indicated the proposed method was able to remove more fine hairs and hairs in the shade, and lower false hair detection rate by 58% (from 0.438 to 0.183) as compared to the DullRazor's approach.