Miracle-dz/UniFAR-FTUs huggingface dataset:
The design revolution of logarithmic number system architecture

Logarithmic number system (LNS) has been a trend in digital signal processing (DSP) for recent years, particularly digital image processing. LNS was been implemented in DSP processors and even as an enhancer tool in image improvements. The selection of LNS is due to the ease of operation for multiplication, division, square and square-root which been replaced by fixed-point addition, subtraction, and left- and right-shift operations, respectively. Current researches have found that LNS is possible to be a competitor and a potential replacement of floating point (FP) system in near future, as it provides comparable strength towards the latter. The other arithmetic operations, which is the addition and subtraction, however, have to face great challenges in implementations as it requires complex procedures and circuitry. As LNS potential to be a substitution of FP, there is a significant need for LNS to improve the performance. Hence, this paper outlines the evolution of the LNS architecture design and highlights the potential areas for further improvements. These enhancements will then be implemented and verified in a specific digital image processing system.
Financial Valuation and Risk Management Working Paper No . 825 Large Liquidity Expansion of Super-Hedging Costs

We consider a financial market with liquidity cost as in Çetin, Jarrow and Protter [3] where the supply function S(s, ν) depends on a parameter ε ≥ 0 with S(s, ν) = s corresponding to the perfect liquid situation. Using the PDE characterization of Çetin, Soner and Touzi [6] of the super-hedging cost of an option written on such a stock, we provide a Taylor expansion of the super-hedging cost in powers of ε. In particular, we explicitly compute the first term in the expansion for a European Call option and give bounds for the order of the expansion for a European Digital Option.
Stroke Survivors Scoring Zero on the NIH Stroke Scale Score Still Exhibit Significant Motor Impairment and Functional Limitation

Objective. To determine the National Institutes of Health Stroke Scale's (NIHSS's) association with upper extremity (UE) impairment and functional outcomes. Design. Secondary, retrospective analysis of randomized controlled trial data. Setting. Not applicable. Participants. 146 subjects with stable, chronic stroke-induced hemiparesis. Intervention. The NIHSS, the UE Fugl-Meyer (FM), and the Arm Motor Ability Test (AMAT) were administered prior to their participation in a multicenter randomized controlled trial. Main Outcome Measures. The NIHSS, FM, and AMAT. Results. The association between the NIHSS and UE impairment was statistically significant (P = −0.204; p = 0.014) but explained less than 4% of the variance among UE FM scores. The association between NIHSS total score and function as measured by the AMAT was not statistically significant (P = −0.141; p = 0.089). Subjects scoring a “zero” on the NIHSS exhibited discernible UE motor deficits and varied scores on the UE FM and AMAT. Conclusion. While being used in stroke trials, the NIHSS may have limited ability to discriminate between treatment responses, even when only a relatively narrow array of impairment levels exists among patients. Given these findings, NIHSS use should be restricted to acute stroke studies and clinical settings with the goal of reporting stroke severity.
Two-dimensional clustering algorithms for image segmentation

This paper introduces modified versions of the K-Means (KM) and Moving K-Means (MKM) clustering algorithms, called the Two-Dimensional K-Means (2D-KM) and Two-Dimensional Moving K-Means (2D-MKM) algorithms respectively. The performances of these two proposed algorithms are compared with three of the commonly used conventional clustering algorithms, namely K-Means (KM), Fuzzy C-Means (FCM), and Moving K-Means (MKM). The new algorithms incorporate the median value of considered pixel intensity with its neighboring pixel; together with the pixel's own intensity for the assigning process of the pixel to the nearest cluster. From the observed qualitative and quantitative results, it is proven that 2D-KM and 2D-MKM perform better than KM, FCM, and MKM in terms of producing more homogeneous segmentation results, while taking shorter time in executing the process as compared to FCM.
Search space pruning and global optimization of multiple gravity assist trajectories with deep space manoeuvres

This paper deals with the design of optimal multiple gravity assist trajectories with deep space manoeuvres. A pruning method which considers the sequential nature of the problem is presented. The method locates feasible vectors using local optimization and applies a clustering algorithm to find reduced bounding boxes which can be used in a subsequent optimization step. Since multiple local minima remain within the pruned search space, the use of a global optimization method, such as Differential Evolution, is suggested for finding solutions which are likely to be close to the global optimum. Two case studies are presented.
Brushless doubly-fed induction machines: Torque ripple

The brushless Doubly-Fed Induction Machine (DFIM) without its brush-gear and slip-rings seems interesting as successor of the normal DFIG in wind turbine drivetrains. However, the brushless DFIM magnetic field has a rich space-harmonic spectrum, which causes additional torque ripple. This paper focuses on torque ripple in the brushless DFIM. The causes and origin of torque ripple are discussed and an analytical model is developed that derives the torque ripple from the air-gap magnetic field distribution. Further, a finite element method for torque ripple calculation is presented. Both methods are used to calculate the torque response of a case study machine. Results are compared and the accuracy of the analytical model is validated with good result. The analytical model is then used to further analyse the torque ripple, resulting in exact torque ripple frequencies and additional insight in the cause of the torque ripple.
The Transit Light Curve Project. VII. The Not-So-Bloated Exoplanet HAT-P-1b

We present photometry of the G0 star HAT-P-1 during six transits of its close-in giant planet, and we refine the estimates of the system parameters. Relative to Jupiter's properties, HAT-P-1b is 1.20 ± 0.05 times larger, and its surface gravity is 2.7 ± 0.2 times weaker. Although it remains the case that HAT-P-1b is among the least dense of the known sample of transiting exoplanets, its properties are in accord with previously published models of strongly irradiated, coreless, solar-composition giant planets. The times of the transits have a typical accuracy of 1 minute and do not depart significantly from a constant period.
Combining Process and Sensor Ontologies to Support Geo-Sensor Data Retrieval

The Sensor Web Enablement (SWE) framework specifies how to access web-enabled sensors and sensor data on a syntactical level. Nevertheless, it is difficult to discover a sensor that fulfills certain criteria from a huge set of available sensors; effort is required to retrieve, interpret, and combine sensor data based on heterogeneous schemas. Semantics-based approaches promise to overcome these challenges (Bermudez and Piasecki 2004, Babitski et al. 2009, Kuhn 2009, Janowicz et al. 2010), but so far most work has focused on ontologies for sensors and their observations. We propose a combined approach which relates a sensor ontology to a process-centric domain ontology and hence takes into account how observation data was created and what types of features it relates refers to. In accordance with the OGC specifications and related work (Compton et al. 2009, Kuhn 2009, Stasch et al. 2009), our sensor network ontology is not limited to physical devices but is constructed such that any entity (e.g., physical sensors, computational process) observing a phenomenon can be represented as a sensor. In contrast to existing hydrology ontologies (Bermudez and Piasecki 2004, Beran 2007, OrdnanceSurvey 2007, Vilches-Blázquez et al. 2009), we focus on a process-centric ontological approach. Process-centric means that the domain ontology is developed by first identifying geo-processes, entities (i.e., objects and matters), and their properties, followed by the relations between them. These relations are used as basis to handle naming heterogeneities and hence support sensor data retrieval. The following sections of the paper describe our ontologies. We will use the concept of Evapotranspiration (ET) as running example as it is a key component is in the Hydrological Sensor Web research by the CSIRO Water for a Healthy Country Flagship initiative. For details, see (Guru et al. 2008).
Subjective Health Measures, Reporting Errors and Endogeneity in the Relationship between Health and Work

This paper explores the interrelation between health and work decisions of older workers. For this, two issues are of relevance. Firstly, health and work may be endogenously related because of direct effects of health on work and vice versa, and because of unobservables that may relate observed health and work outcomes. Secondly, social surveys usually contain self-assessed health measures and research indicates that these may be affected by endogenous, state-dependent, reporting behavior. A solution to the 'Health and Retirement Nexus' requires an integrated model for work decisions, health production and health-reporting mechanisms. We formulate such a model and estimate it on a longitudinal dataset of Dutch elderly.
Estimating User Affect and Focus of Attention from Physiological Signals in Life-Like Character Based Interaction Scenarios

This paper abstract highlights some of our recent research efforts in designing and evaluating lifelike characters that are capable of entertaining affective and social communication with users. The key novelty of our approach is the use of human physiological information: first, as a method to evaluate the effect of life-like character behavior on a moment-to-moment basis, and second, as an input modality for a new generation of interface agents that we call ‘physiologically perceptive’ characters. By exploiting the stream of primarily involuntary human responses, such as biometric signals and eye movements, those characters are expected to respond to users’ affective and social needs in a truly sensitive, and hence effective, friendly, and beneficial way.
Naturalism, Explanation, and Identity

Some people believe that there is an “explanatory gap” between the facts of physics and certain other facts about the world—for example, facts about consciousness. The gap is presented as a challenge to any thoroughgoing naturalism or physicalism. We believe that advocates of the explanatory gap have some reasonable expectations that cannot be merely dismissed. We also believe that naturalistic thinkers have the resources to close the explanatory gap, but that they have not adequately explained how and why these resources work. In this paper we isolate the legitimate explanatory demands in the gap reasoning, as it is defended by Chalmers and Jackson (2001). We then argue that these demands can be met. Our solution involves a novel proposal for understanding the relationship between theories, explanations, and scientific identities.
Enhanced real-time ECG coder for packetized telecardiology applications

A new real-time compression method for electrocardiogram (ECG) signals has been developed based on the wavelet transform approach. The method is specifically adaptable for packetized telecardiology applications. The signal is segmented into beats and a beat template is subtracted from them, producing a residual signal. Beat templates and residual signals are coded with a wavelet expansion. Compression is achieved by selecting a subset of wavelet coefficients. The number of selected coefficients depends on a threshold which has different definitions depending on the operational mode of the coder. Compression performance has been tested using a subset of ECG records from MIT-BIH Arrhythmia database. This method has been designed for real-time packetized telecardiology scenarios both in wired and wireless environments
A single-cell view on the ecophysiology of anaerobic phototrophic bacteria

Quantitative information on the ecophysiology of individual microorganisms is generally limited because it is difficult to assign specific metabolic activities to identified single cells. Here, we develop and apply a method, Halogen In Situ Hybridization-Secondary Ion Mass Spectroscopy (HISH-SIMS), and show that it allows simultaneous phylogenetic identification and quantitation of metabolic activities of single microbial cells in the environment. Using HISH-SIMS, individual cells of the anaerobic, phototropic bacteria Chromatium okenii, Lamprocystis purpurea, and Chlorobium clathratiforme inhabiting the oligotrophic, meromictic Lake Cadagno were analyzed with respect to H13CO3− and 15NH4+ assimilation. Metabolic rates were found to vary greatly between individual cells of the same species, showing that microbial populations in the environment are heterogeneous, being comprised of physiologically distinct individuals. Furthermore, C. okenii, the least abundant species representing ≈0.3% of the total cell number, contributed more than 40% of the total uptake of ammonium and 70% of the total uptake of carbon in the system, thereby emphasizing that numerically inconspicuous microbes can play a significant role in the nitrogen and carbon cycles in the environment. By introducing this quantification method for the ecophysiological roles of individual cells, our study opens a variety of possibilities of research in environmental microbiology, especially by increasing the ability to examine the ecophysiological roles of individual cells, including those of less abundant and less active microbes, and by the capacity to track not only nitrogen and carbon but also phosphorus, sulfur, and other biological element flows within microbial communities.
A Decision Model for Berth Allocation Under Uncertainty Considering Service Level Using an Adaptive Differential Evolution Algorithm

This paper focuses on the berth allocation problem, which is to determine where and when the vessels to be loaded and unloaded at a terminal within a given planning horizon, with consideration of uncertain factors, mainly including the arrival and operation time of the calling vessels. Based on the concept of service level which is commonly used in the inventory system, a decision model is constructed to minimize the cost of baseline schedule, which includes delay cost and nonoptimal berthing location cost. According to the specific characteristics of the model, the upper and lower bounds are found. And due to the NP-hardness of the constructed model, an adaptive differential evolution is employed to solve the problem. Finally, extensive numerical experiments are conducted to test the performance of the proposed models and solution approaches.
Validation of CFS classification with different data sources

The difference between patients with CFS patient and healthy ones could, in principle, be detected by examining a variety of data. We systematically used the CAMDA 2006 available data sets in order to assess the patients’ discrimination using supervised and unsupervised techniques. Our results suggest that data sets that are predictive are the clinical as well as the microarray data sets. On the other hand, our analysis of the proteomics data suggests that subjects with diseases different from CFS could be among the healthy ones. Finally, we indicate a set of genes extracted from the microarray data and validate then with an automatic comparison with Gene Ontology information. A set of these genes with high GO proximity may contribute to CFS.
Estimation of equivalent circuit parameters of transformer and induction motor using PSO

In this paper a simple and robust parameter estimation methodology for single phase transformer and three phase induction motor is proposed using particle swarm optimization (PSO) technique. Here the equivalent circuit parameters and losses of a single phase transformer and a three phase induction motor are obtained using PSO technique. The obtained results from PSO are verified by comparing it with a 15 kVA transformer as mentioned in [8] and validated with the results obtained from laboratory test performed on a 3kVA single phase transformer as well as a 2 HP three phase slip ring induction motor. From the test it can be seen that the results obtained from PSO can track the test results quite accurately in estimation of equivalent circuit parameters. This scheme can be extended to estimate the parameters of three phase transformers as well as three phase squirrel cage induction motors and single phase induction motor with proper modification.
Robust text-independent speaker identification using Gaussian mixture speaker models

This paper introduces and motivates the use of Gaussian mixture models (GMM) for robust text-independent speaker identification. The individual Gaussian components of a GMM are shown to represent some general speaker-dependent spectral shapes that are effective for modeling speaker identity. The focus of this work is on applications which require high identification rates using short utterance from unconstrained conversational speech and robustness to degradations produced by transmission over a telephone channel. A complete experimental evaluation of the Gaussian mixture speaker model is conducted on a 49 speaker, conversational telephone speech database. The experiments examine algorithmic issues (initialization, variance limiting, model order selection), spectral variability robustness techniques, large population performance, and comparisons to other speaker modeling techniques (uni-modal Gaussian, VQ codebook, tied Gaussian mixture, and radial basis functions). The Gaussian mixture speaker model attains 96.8% identification accuracy using 5 second clean speech utterances and 80.8% accuracy using 15 second telephone speech utterances with a 49 speaker population and is shown to outperform the other speaker modeling techniques on an identical 16 speaker telephone speech task. >
Spatiotemporal Variation of Driving Forces for Settlement Expansion in Different Types of Counties

Understanding the process of settlement expansion and the spatiotemporal variation of driving forces is the foundation of rational and specific planning for sustainable development. However, little attention has been paid to the spatiotemporal differences of driving forces among different counties, especially when they are representatives of different development types. This study used Guanyun, Kunshan and Changshu as case studies, and binary logistic regression was employed. The results showed that the expansion rates of Kunshan and Changshu were 5.55 and 3.93 times higher than that of Guanyun. The combinations and relative importance of drivers varied with counties and periods. The change in the number of driving forces can be divided into three stages: increasing stage, decreasing stage, and stable stage. In the relatively developed counties, Kunshan and Changshu, the importance of population is decreased, while it remain an important factor in the less developed county, Guanyun. In addition, the effect of GDP stays the same in Kunshan while it becomes the most important factor in Changshu. The distance to the main road and the distance to town are increasingly important in Kunshan and Guanyun, and distance to town has been the only common factor in the last period, indicating the discrepancy is increased. The relative importance of distance to a lake in Kunshan and Changshu increased, reflecting the role of increasing tourism in accelerating settlement expansion.
A Hybrid Hierarchical Schema-Based Architecture for Distributed Autonomous Agents

The advent of inexpensive computers has spurred interest in distributed architectures, in which a cluster of low-cost cornpeters can achieve performance on the same scale as expensive super-computers. The goal of research in distributed systems is to take a highly decomposable problem solution, and put that solution into a framework that allows the system to take full advantage of the sohition’s decomposability. An architecture that allows additional processors to be taken advantage of with little or no manual reconfigurafion would be ideal. Artificial Intelligence (AI) algorithms for planning in nontrivial domains am typically resource-inteasive. We believe that a framework for developing planning algorithms that allows an arbitrary level of decomposition and provides the means for distributing the computation would be a valuable contribution to the Al community. We propose a general, flexible, and scalable hierarchical architecture for designing multi-agent distributed systems. We developed this architecture to facilitate the development of software for soccer-playing robots. These robots will compete in the international robot soccer competition RoboCup. All of our software, from the high-level team strategy planning down to the control loop for the motors on our robots fits into this architecture. We build on the notion of deliberative and reactive agents, forming a hierarchy of hybrid agents. The hierarchy covers the entire continuum of hybrid agents: agents near the root of the hierarchy are mostly deliberative, while agents near the leaves are almost purely reactive.
MASA: a multithreaded processor architecture for parallel symbolic computing

Multiple architecture for symbolic applications (MASA) is a first cut at a processor architecture intended as a building block for a multiprocessor that can execute parallel Lisp programs efficiently. MASA features a tagged architecture, multiple contexts, fast-trap handling, and a synchronization bit in every memory word. MASA's principal novelty is its use of multiple contexts both to support multithreaded execution-interleaved execution from separate instruction streams-and to speed up procedure calls and trap handling in the same manner as register windows. A project is underway to evaluate MASA-like architectures for executing programs written in Multilisp. <<ETX>>
Single nucleotide polymorphism analysis of corticotropin-releasing factor-binding protein gene in bipolar disorder

Corticotropin-releasing factor-binding protein regulates the availability of free corticotropin-releasing factor and is a functional candidate gene for affective disorders. The aim of this study was to examine the association between polymorphisms in CRF-BP gene and bipolar disorder in an isolated Swedish population. One hundred and eighty-two patients with bipolar I disorder and 333 controls from Northern Sweden were included in the study. Five single nucleotide polymorphisms and a deletion polymorphism in the CRF-BP gene were genotyped. The haplotype block structure of the gene was considered and the expectation maximization algorithm was adopted to estimate the haplotype frequencies. As a result, there were no significant associations of the different polymorphisms in the CRF-BP gene with bipolar disorder. In conclusion, this study in an isolated Swedish population does not support a role for the CRF-BP gene in the vulnerability for bipolar disorder.
Expressive global protocols via logic-based electronic institutions

We propose a notation to specify and reason about an expressive class of protocols. Our notation is logic-based, employing a restricted form of first-order constructs added with sets. We formally associate the syntax of our constructs with a precise semantics. The semantics enables us to automatically build explicit models which can be used to restrict the possible executions of a given Multi-Agent System. Our notation has been incorporated to a variant of electronic institutions -- an encompassing and flexible approach to specify open agent organisations -- and we have implemented a proof-of-concept platform to enact arbitrary protocols using our notation.