Miracle-dz/UniFAR-FTUs huggingface dataset:
A Multi-phase, Probabilistic Approach ToImage Segmentation In MRI And CT Studies

This paper presents an approach for segmentation of digital medical images using a multi-phase probabilistic approach. The first phase of the approach is enhancement of the image data using an unsharp mask sharpening algorithm. This vastly improved the clarity of the images prior to segmentation. The segmentation of an object within the image is then achieved through two more phases. The first phase is a thresholding process, where each pixel is scored based on a similarity criterion for a chosen seed point. Pixels with a score satisfying a required minimum are selected into the segmented region. A second phase is then instituted for pixels not initially selected. This phase involves a probability selection, based on a Monte Carlo simulation. A probability for each pixel is formulated based on the pixel’s intensity and location. This probability is them compared against a random probability to determine if the pixel is included in the segmented region. To facilitate the processing of multiple image slices, an automated relocation algorithm was developed to move determined seed points from image to image as the shape, size, or location of the object (i.e. organ) changes. The concepts and techniques developed were tested on three separate medical studies with one being shown in this paper. The results showed that the image enhancement process outlined features and details within the data that were not previously apparent. The segmentation process extracted the desired object more completely when compared to other segmentation techniques.
Identifying a Suitable Approach for Measuring and Managing Public Service Productivity

Every public organisation faces the challenge of improving productivity. In this effort, productivity measures are essential managerial tools. However, the task of measuring service productivity has proven to be challenging. A key reason for the challenges seems to be related to the intangibility of services. The objective of this paper is to identify and apply a productivity measurement method satisfying the information requirements of public managers. The study is carried out using a qualitative case study approach. The paper consists of two parts: first, the current knowledge of the issue is examined by reviewing the literature on (service) productivity and performance measurement; second, an action research is carried out in the context of four case services of the City of Helsinki, Finland. A disaggregated approach to productivity measurement is applied. Three different measurement frameworks and methods are evaluated in light of practical criteria for measurement. Finally, a matrix method is chosen and applied in practice. As a result the paper provides more understanding of the process of applying the disaggregated productivity measurement approach in the context of public welfare services.
Enhancement Of Visual Evoked Potentials By Adaptive Processing

Transient evoked potentials (EP) are variations of the on-going electroencephalogram (EEG) in response to the application of sensory stimuli. Since their amplitudes are very small in comparison to the spontaneous EEG, signal extraction methods must be applied to them before their characteristics are measureable. Several signal ex-traction methods which are actually used in EP research are outlined, especially those showing an adaptive characteristic. As a further development, a new method is proposed which considers the on-going EEG preceding the stimulus application for the EP processing. The computational procedure will be described and some preliminary results are given.
TOWARDS USING SUBSEASONAL-TO-SEASONAL ( S 2 S ) EXTREME RAINFALL FORECASTS FOR EXTENDED-RANGE FLOOD PREDICTION

The Arzal dam is located at the mouth of the Vilaine river basin, in Brittany, France, just before the Atlantic Ocean. It creates a 50 Mm3 reservoir of freshwater that supplies the region with drinking water. The dam and its reservoir also play an important role in flood protection, fish migration and touristic activities such as boating. Dam managers have to integrate these multiple uses in their decisions on opening locks and gates. More specifically in summer, they have to guarantee a minimum water volume in the reservoir for water supply, while limiting the entrance of salt water from the ocean when, for instance, allowing boats to leave or enter the reservoir. In periods of low rainfalls and high water demands (May to October), severe low flow situations may occur and uses can become conflictual. A flow forecasting and water management system is essential to provide real-time information to managers and users, supporting decisions and crisis management. The development of this system started in 2013 and comprises two main steps. First, a seasonal forecasting system of inflows upstream the dam was set up and evaluated. Several methods to forecast inflows to the reservoir based on precipitation and streamflow climatology, but also based on seasonal forecasts issued by ECMWF System 4 were analysed. Pre-processing and scenario combination were evaluated for forecast sharpness and reliability. Forecasts of variables of interest to quantify the severity of low flows were incorporated in risk visualisation tools, which were set up with the stakeholders responsible for the management of the dam. In a second step, the management of the reservoir was investigated. Past records of management rules were modelled to reproduce the water levels observed over the summer period. The quality of the seasonal forecasts developed in the previous step was also assessed in this operational context. The main results from the implementation of this low flow forecasting and reservoir water management system will be presented and discussed. The Arzal dam is one of the pilot sites of the Interreg IVB DROP project, which partly funds this research (http://www.dropproject.eu/).
Equalized maximum likelihood receiver in a magnetic recording channel

As the length of a channel response increases, the complexity of implementing the Maximum Likelihood Sequence Detector (MLSD) grows exponentially. Equalized Maximum Likelihood (EML) has been proposed to approach optimum performance with significantly reduced complexity. In this scheme, the performance degradation due to the colored error sequence is taken into account. A comparison with Partial Response Maximum Likelihood (PRML) is made for a magnetic recording channel. Our results indicate that better performance can be achieved with reduced complexity especially at high recording densities. <<ETX>>
A Novel Feature Selection Method for Process Fault Diagnosis

To increase fault classification performance and reduce computational complexity,the feature selection process has been used for fault diagnosis.In this paper, we proposed a sparse representation based feature selection method and gave detailed procedure of the algorithm. Traditional selecting methods based on wavelet package decomposition and Bhattacharyya distance methods,and sparse methods, including sparse representation classifier, sparsity preserving projection and sparse principal component analysis,were compared to the proposed method.Simulations showed the proposed selecting method gave better performance on fault diagnosis with Tennessee Eastman Process data.
A Eurasian European Union? Relaunching Post-Soviet Economic Integration

In November 2011, the presidents of Belarus, Kazakhstan and Russia agreed to establish a “Eurasian Economic Commission” (EAEK) charged with the development and functioning of the Customs Union and a “Single Economic Space” comprising the three states. Their presidents and other political actors referred to the European Union and its formation to frame these projects and the envisaged creation of a “Eurasian Union” until 2015. The paper studies how these references are emulated in Russian public discourse and the legal regulation of the EAEK. Combining theories of policy transfer and gradual institutional change, the paper conceptualizes different modes of emulation. A weak authority of the EU model and weak powers of integration advocates suggest a “facade emulation” where formal similarities coexist with persisting inherited practices and behavioral patterns. This hypothesis is confirmed by (1) labeling and framing strategies that relate the EU model to familiar ideas in Russian political culture and previous initiatives of post-Soviet integration and (2) a limited emulation of labels and organizational structures from the EU within an essentially intergovernmentalist institutional arrangement.
Visualizing Model-Based Predictive Controllers

One common problem with information displays, particularly in process control, is that relevant data is often scattered across several, separate displays that obscure important relationships and fail to show event information. The current displays used for model-based predictive controllers demonstrate several of the problems that this kind of a design can incur. It is hard to get a good sense of the recent, current and near-future status of the controller (situation awareness), and it is difficult to make informed decision when making changes to the controller (putting data into context). This forces users to navigate around a virtual workspace and attempt to compile the data necessary to make an informed conclusion. We have applied several design principles to show how it is possible to re-represent data into hierarchical data layers that support the cognitive tasks of monitoring, diagnosis, and control. This design forms a coherent, coordinated workspace which helps orient users to problems in the controller, with direct navigation to supporting details.
Control Actions of Hydrodynamic Conditions of Groundwater to Gas Productions of Coal Bed Methane Straight Wells in Fanzhuang Block

This study analyzed the control actions of hydrodynamic conditions of groundwater to gas productions of coal bed methane (CBM) straight wells on the basis of production data and geological data of CBM wells in Fanzhuang Block and hydrogeological characteristics in southern Qinshui basin. Then mechanisms of the control actions were discussed. The results show that groundwater fluid potential in Fanzhuang Block has positive correlation relationships with gas productions of CBM wells in research area. Groundwater fluid potential influences gas productions of CBM wells through drainage and depressurization effects. Coal bed reservoir with high groundwater fluid potential usually has low water content and small water recharging,which is beneficial to the decrease of coal bed pressure and migration and output of CBM. In this condition, CBM wells usually have high daily gas productions. Within a relative large region,the control actions of hydrodynamic conditions of groundwater to gas productions of CBM wells are weak. But the control actions are strong in a relatively small region because of the stronger seepage capability of groundwater. The control actions of hydrodynamic conditions of groundwater to gas productions of CBM wells become weak when groundwater fluid potential is higher than 700 m above sea level,because of the low water content and small water recharging of coal bed reservoir.
Performance evaluation of the non-linear and linear estimation methods for determining kinetic parameters in dynamic FDG-PET study

Dynamic positron emission tomography (PET) is a promising diagnostic tool to quantitatively predict biological and physiological changes in vivo through estimation of kinetic parameters. In this work, several popular linear and non-linear estimation methods for determining kinetic parameters using PET imaging with Fluorine-18 fluorodeoxyglucose ([18F]FDG) are compared and evaluated. The simulation studies are presented. The linear estimation methods include linear least squares (LLS), generalized linear least squares (GLLS) and total least squares (TLS), while the non-linear estimation methods include non-linear least squares (NLS), weighted nonlinear least squares using noisy tissue time activity data (WNLS-N), weighted non-linear least squares using noise-free tissue time activity data (WNLS-NF) and iteratively re-weighted non-linear least squares (IRWNLS). There are several findings: 1. Compared with non-linear estimation methods, GLLS performs well when noise level is low, but worse especially in determining k3 and k4 when noise level is high. What's more, GLLS does not show obvious advantage in running time. 2. The choice of weights plays an important role in nonlinear estimation methods. Weighting using noisy data should be avoided. WNLS-NF and IRWNLS perform best. Since the noise-free data can not be obtained in clinical and IRWNLS is time-consuming, NLS is most recommended. 3. Non-linear estimation methods are prone to produce lower-biased, higher-precision parameter estimates, however, also more easily affected by noise. Linear estimation methods are prone to be more biased, however, much more computational efficient and noise robust.
An empirical comparison of copresent and technologically-mediated interaction based on communicative breakdown

Within the area of Computer-Supported Cooperative Work (CSCW), there has been an explosion of interest in how recently developed network technologies might be applied to support the collaborative endeavors of widely distributed participants. Increasingly powerful systems for desktop conferencing, group meeting, and distributed design have been developed. Though the technologies applied in such systems vary widely, their underlying design goal is essentially the same: to support interactions that are functionally equivalent to face-to-face interaction. This dissertation evaluates the extent to which currently available technologies achieve this goal by comparing the amount of communicative breakdown experienced by pairs of participants interacting in three communications environments: copresent, audio-mediated and audio/video-mediated. In all three environments, participants had access to a shared workspace, in which they used a graphical computer simulation to collaboratively explore the behavior of a simple cardiovascular system. Videotaped interactions were analyzed in a series of three studies, intertwining the qualitative techniques of Conversation and Interaction Analysis with more traditional quantitative techniques to progressively refine understanding of the functional differences that exist between environments. Four categories of communicative breakdown were identified: failure to maintain shared conceptions of current topic, failure to establish shared reference, failure to regulate access to the verbal channel and to a shared cursor. Statistical results showed that copresent interactions were significantly less prone to breakdown than interactions in either of the two technologically-mediated environments; no significant differences in the incidence of breakdown were found between audio-only and audio-video interactions. A subsequent qualitative analysis showed that breakdowns in technologically-mediated interactions were related to a profound insensitivity to nonverbal displays like direction of gaze, deictic gesture and manipulation of objects in the task context. This result demonstrates that, though visual access to a partner is clearly vital for avoiding breakdown, the visual access afforded by a video image is fundamentally unequal to that afforded by physical copresence. More generally, there is a great deal of difference between technically making more communicative resources available in an environment and the practical utility of such upgrades to participants.
The Blackboard Learning System: The Be All and End All in Educational Instruction?

Blackboard Inc. provides powerful and easy-to-use systems for educational instruction, communication, and assessment. In the last three years, Blackboard Inc. has marketed two major product lines: the Blackboard Commerce Suite and the Blackboard Academic Suite. The core of the Academic suite is the Blackboard Learning System, the course management system for classroom and online educational assistance. Other course management systems and learning management systems exist, including Angel/LMS, eCollege, GNU General Public License/Linux, and LearningSpace, as well as open-source learning systems such as The Sakai Project, Open SourcePortfolio Initiative, Moodle, and uPortal. Despite the drive toward new portal commodities, the Blackboard Learning System has become the dominant e-learning software company. Is this necessarily good for higher educational learning? Members of the United University Professions Technology Issues Committee debate the issue as well as present specific applications of the Blackboard Learning System in distance learning, hybrid courses, and as didactic supplements to other electronic environment enhancement systems.
N A ] 1 8 Ju l 2 01 8 DD-DA PinT-based model : A Domain Decomposition approach in space and time , based on Parareal , for solving the 4 D-Var Data Assimilation model

We present the mathematical framework of a Domain Decomposition (DD) aproach based on Parallel-in-Time methods (PinT-based approach) for solving the 4D-Var Data Assimilation (DA) model. The main outcome of the proposed DD PinT-based approach is: 1. DA acts as coarse/predictor for the local PDE-based forecasting model, increasing the accuracy of the local solution. 2. The fine and coarse solvers can be used in parallel, increasing the efficiency of the algorithm. 3. Data locality is preserved and data movement is reduced, increasing the software scalability. We provide the mathematical framework including convergence analysis and error propagation.
Personalized Food Recommendations Exploring Content-Based Methods

Food recommendation is a relatively new area, with few systems that focus on analysing user preferences being deployed in real settings. In my M.Sc. dissertation, the applicability of content-based methods in personalized food recommendation is explored. Variations of popular approaches used in other areas, such as Rocchio’s algorithm for document classification, can be adapted to provide personalized food recommendations. With the objective of exploring content-based methods in this area, a system platform was developed to evaluate a variation of the Rocchio algorithm adapted to this domain.
Using borehole flowmeter data to optimize hydraulic conductivity characterization in heterogeneous unconsolidated aquifers

Borehole flowmeter measurements obtained during pumping can be effective in determining profiles of hydraulic conductivity (K). Few tests have been reported on flowmeter in full-screened wells that penetrate unconsolidated aquifers. In this paper, we demonstrate the utility of the flowmeter technique in quantifying the spatial variability of K and in distinguishing hydrofacies in an unconsolidated heterogeneous aquifer that exhibits low to moderate K. Results indicate that: (1) comparison of K values obtained from flowmeter measurements and multilevel slug tests shows differences consistently below 10%, and (2) individual hydrofacies can be delineated based upon K contrasts. RÉSUMÉ Le débitmètre dans un puits en pompage peut efficacement définir des profils de conductivité hydraulique (K). Peu d’essais ont été faits avec le débitmètre dans des puits crépinés dans les dépôts meubles. Dans cet article, nous démontrons l’applicabilité du débitmètre pour quantifier la variabilité spatiale de K et identifier les hydrofaciès dans un aquifère granulaire hétérogène avec des valeurs de K faibles à moyennes. Les résultats montrent que : (1) les différences de K obtenues par débitmètre et essais de perméabilité multi-niveaux sont inférieures à 10% et (2) les hydrofaciès peuvent être identifiés sur la base des contrastes de K mesurés.
Distributed Computing in Molecular Modeling : Practical Experience on the Joint ISMA-ISC Cluster

The experience of using a set of molecular modeling programs on the Joint ISMA-ISC computer cluster is discussed. The main attention is paid to the computational efficiency and the scalability of the tasks in different applied program packages. Hardware issues limiting the efficiency are pointed out. Specific features of some quantum chemical modeling programs are mentioned briefly.
Text Mining Perspectives in Microarray Data Mining

Current microarray data mining methods such as clustering, classification, and association analysis heavily rely on statistical and machine learning algorithms for analysis of large sets of gene expression data. In recent years, there has been a growing interest in methods that attempt to discover patterns based on multiple but related data sources. Gene expression data and the corresponding literature data are one such example. This paper suggests a new approach to microarray data mining as a combination of text mining (TM) and information extraction (IE). TM is concerned with identifying patterns in natural language text and IE is concerned with locating specific entities, relations, and facts in text. The present paper surveys the state of the art of data mining methods for microarray data analysis. We show the limitations of current microarray data mining methods and outline how text mining could address these limitations.
Fast Correlation Attacks on Grain-like Small State Stream Ciphers and Cryptanalysis of Plantlet, Fruit-v2 and Fruit-80

The fast correlation attack (FCA) is one of the most important cryptanalytic techniques against LFSR-based stream ciphers. In CRYPTO 2018, Todo et al. found a new property for the FCA and proposed a novel algorithm which was successfully applied to the Grain family of stream ciphers. Nevertheless, these techniques can not be directly applied to Grain-like small state stream ciphers with keyed update, such as Plantlet, Fruit-v2, and Fruit80. In this paper, we study the security of Grain-like small state stream ciphers by the fast correlation attack. We first observe that the number of required parity-check equations can be reduced when there are multiple different parity-check equations. With exploiting the Skellam distribution, we introduce a sufficient condition to identify the correct LFSR initial state and derive a new relationship between the number and bias of the required parity-check equations. Then a modified algorithm is presented based on this new relationship, which can recover the LFSR initial state no matter what the round key bits are. Under the condition that the LFSR initial state is known, an algorithm is given against the degraded system and to recover the NFSR state at some time instant, along with the round key bits. As cases study, we apply our cryptanalytic techniques to Plantlet, Fruit-v2 and Fruit-80. As a result, for Plantlet our attack takes 2 time complexity and 2 keystream bits to recover the full 80-bit key. Regarding Fruit-v2, 2 time complexity and 2 keystream bits are token to determine the secret key. As for Fruit-80, 2 time complexity and 2 keystream bits are required to recover the secret key. More flexible attacks can be obtained with lower data complexity at cost of increasing attack time. Especially, for Fruit-v2 a key recovery attack can be launched with data complexity of 2 and time complexity of 2. Moreover, we have implemented our attack methods on a toy version of Fruit-v2. The attack matches the expected complexities predicted by our theoretical analysis quite well, which proves the validity of our cryptanalytic techniques.