Miracle-dz/UniFAR-FTUs huggingface dataset:
Support Vector Machine-Based Classification Scheme for Myoelectric Control Applied to Upper Limb

This paper proposes and evaluates the application of support vector machine (SVM) to classify upper limb motions using myoelectric signals. It explores the optimum configuration of SVM-based myoelectric control, by suggesting an advantageous data segmentation technique, feature set, model selection approach for SVM, and postprocessing methods. This work presents a method to adjust SVM parameters before classification, and examines overlapped segmentation and majority voting as two techniques to improve controller performance. A SVM, as the core of classification in myoelectric control, is compared with two commonly used classifiers: linear discriminant analysis (LDA) and multilayer perceptron (MLP) neural networks. It demonstrates exceptional accuracy, robust performance, and low computational load. The entropy of the output of the classifier is also examined as an online index to evaluate the correctness of classification; this can be used by online training for long-term myoelectric control operations.
Analysis and design of approximate queries over XML documents using statistical techniques

In the last few years several repositories for storing XML documents and languages for querying XML data have been studied and implemented. All the query languages proposed so far allow to obtain exact answers, but when applied to large XML repositories or warehouses, such precise queries may require high response times. To overcome this problem, in traditional relational warehouses fast approximate queries are supported, built on concise data statistics based on histograms or sampling techniques. We believe that the current trend of XML claims for the extension of such approaches also to query massive XML data-sets. In our work we propose a novel approach to summarize an XML document collection using concise data statistics (e.g., histograms), which allows approximate queries on such data using the XQuery standard language.
A New Non-Parametric Matching Method for Covariate Adjustment with Application to Economic Evaluation

In health economic studies that use observational data, a key concern is how to adjust for imbalances in baseline covariates due to the non-random assignment of the programs under evaluation. Traditional methods of covariate adjustment such as regression and propensity score matching are model dependent and often fail to replicate theresults of randomized controlled trials. We demonstrate a new non-parametric matching method, Genetic Matching, which is a generalization of propensity score and Mahalanobis distance matching (Sekhon forthcoming), using two contrasting case studies. In the first, an economic evaluation of a clinical intervention (Pulmonary Artery Catheterization), applying Genetic Matching to observational data replicates the substantive results of a corresponding randomized controlled trial unlike the extant literature. And in the second case study evaluating capitation versus fee-for-service, Genetic Matching radically improves balance on baseline covariates and overturns previous conclusions based on traditional methods.
International Encyclopedia of Rehabilitation Rehabilitation of Locomotor Function after a Central Motor Lesion Generation of Locomotor Activity Physiological Basis of Locomotion in Humans Target for Rehabilitation: Plasticity of the Central Nervous System Locomotor Function after Spinal Cord Injury 

After spinal cord injury (SCI) of the cat or rat neuronal circuits below the level of lesion exhibit plasticity that can be exploited by specific training paradigms. In individuals with complete or incomplete SCI, human spinal locomotor centers can be activated by providing an appropriate afferent input. This includes to facilitate and assist stepping movements of the legs and to provide body weight support (BWS) of SCI subjects standing on a moving treadmill. Individuals with incomplete SCI benefit from such locomotor training such that they improve the ability to walk over ground. Load-and hip-joint-related afferent input seems to be of crucial importance for both the generation of a locomotor pattern and the effectiveness of the training. It appears to be a critical combination of afferent signals that is needed to generate and improve a locomotor pattern after a SCI. Several years of driven gait orthoses can provide a standardized locomotor training. In the future, if regeneration approaches can successfully be applied in human SCI, even individuals with complete SCI may recover walking ability with locomotor training. However, recent studies also indicate that in individuals with a severe SCI, spinal neuronal circuits undergo a degradation of their function 1 year after injury. Neuronal circuits (networks of interneurons) within the spinal cord that interact with specific sensory information under supraspinal control are responsible for locomotion in non-primate mammals (Barbeau and Rossignol 1987). These spinal neuronal circuits are defined as central pattern generators (CPGs) and were identified with experiments that demonstrated self-sustained patterns of locomotor-like neuronal activity generated independently of supraspinal and afferent input (Barbeau and Rossignol 1994, Pearson 2000). The understanding of the basis principles of CPG function is based on research in vertebrates and invertebrates. This research has shown that a significant level of control of locomotion is mediated at the level of the spinal cord. In fact, spinally transected animals can relearn or reexpress hindlimb stepping in the absence of input from the brain There is convincing evidence in spinal animals that use-dependent plasticity of spinal neuronal circuits modifies the sensory-motor function of lumbosacral spinal cord. Regular locomotor training after complete spinal cord transection in adult cats improved the recovery of hindlimb function. Whether these neuronal properties such as the CPG also exist in humans is of crucial importance for the recovery of standing and walking-1-after severe spinal cord injury (SCI). The control of locomotion by spinal centers and activity-dependent …
Neighbor-base similarity matching for graphs

The rapid development of internet and data centers has made cloud data management a major issue in database management system. Various cloud data management related applications require the basic operation of graph pattern matching. Exact matching method for graph pattern matching is too restrictive and it incurs very high computational cost as an NP-complete problem. Thus, it cannot be applied to most cloud applications. So several approximate notions are proposed. However, traditional approximate matching methods are still too restrictive in some situations, and some of them may neglect important nodes in the pattern. To address these problems, we propose a novel notion for graph pattern matching, and show that it can be processed in polynomial time. In addition, our method is flexible, free of thresholds and does not leave out any node in the pattern.
Global Localization and Position Tracking of Automatic Guided Vehicles using passive RFID Technology

Automated Guided Vehicles (AGVs) are used in warehouses, distribution centers and manufacturing plants in order to automate the internal material flow. Usually AGVs are designed to transport large and heavy transport units such as Euro-pallets or mesh pallets. Just-in-time inventory management and lean production requires small transportation units to enable one-piece-flow. A solution to meet these demands are small automatic vehicles for material transport, which can replace conventional conveyor systems or large AGVs. This paper presents an inexpensive solution for localization and tracking of small AGVs. Global localization is realized by detection of RFID transponders, which are integrated in the floor. The measurements of the RFID reader are fused with data from wheel encoders using Quantized Kalman filtering. The paper presents results from experiments with a NaviFloor ® installation. The experiments show, that the proposed Quantized Kalman Filter provides a similar localization accuracy compared to a Monte Carlo Particle Filter, but with much lower computational expense.
SIMILARITY MEASURES FOR NOMINAL VARIABLE CLUSTERING Zdeněk Šulc

The paper deals with selected similarity measures which can be used for hierarchical clustering of nominal variables. These variables are commonly used in questionnaire surveys. Cluster analysis can be applied in case a reduction of a dataset size is welcomed. In this paper, there are examined several similarity measures for nominal variable clustering, which have been introduced in recent years. On the contrary to the simple matching coefficient, which is considered to be a basic similarity measure, they take into account more characteristics regarding the dataset, such as distribution of frequencies of categories. Therefore, they should provide better results in a comparison to the simple matching coefficient. The performance of clustering with selected similarity measures is examined on two real datasets. For cluster quality evaluation, indices based on the within-cluster variability have been chosen. All computations have been performed in the statistical systems Matlab, IBM SPSS Statistics and MS Excel.
Application layer versus cross-layer service discovery protocols in MANETs

Service discovery in mobile ad hoc networks is challenging because of the absence of any central intelligence in the network. Traditional solutions as used in the Internet are hence not well suited for mobile ad hoc networks. This paper focuses on traditional application layer service discovery protocols (SDP) shortcomings by presenting a fair comparison between application layer and cross-layer protocols. We present and examine our simulation results for both BF-SD-ZRP and SLPManet protocols in order to demonstrate their efficiency and shortcomings in terms of overhead, energy consumption and service discoverability using the scalable network simulator Jist/Swans.
Studying Impact of Organizational Factors in Information Technology Acceptance in Accounting Occupation by Use of Tam Model (Iranian Case Study)

Nowadays, information technology attitudes as the beneficial part of industry, economic and culture. Accounting posits as profession that provide information for decision- making of users and in the complex world, organizations must use information technology to present information for users in time. This research is by purpose of studying impact of organizational factors in information technology acceptance by use of TAM model in study descriptive- surveying method that researcher has used to reach research objectives of descriptive and inferential statistics and research results is indicated lack of perceived ease of use by accountants.
Comment-guided Learning: Bridging the Knowledge Gap between Expert Assessor and Feature Engineer

As more and more natural language processing systems utilize human assessment on system responses, it becomes beneficial to discover some hidden privileged knowledge (such as comments) from assessors. We present a simple, low-cost but effective comment- guided learning approach to exploit such knowledge declaratively in an automatic assessor. Our approach only requires a small set of training data, together with comments which are naturally available from human assessment. To demonstrate the power and generality of this approach, we apply the method in two very different applications: name translation and residence slot filling. Our approach achieved significant absolute improvement (15% for name translation and 8% for slot filling) over state-of-the-art systems. It also outperformed previous methods such as Recognizing Textual Entailment (RTE) based fact validation. Furthermore, it can be used as feedback to significantly speed up human assessment. Keywords-comment-guided learning; assessment; feature engineering.
LIFT-UP : Lifted First-Order Planning Under Uncertainty

We present a new approach for solving first-order Markov decision processes combining first-order state abstraction and heuristic search. In contrast to existing systems, which start with propositionalizing the decision process and then perform state abstraction on its propositionalized version we apply state abstraction directly on the decision process avoiding propositionalization. Secondly, guided by an admissible heuristic, the search is restricted to those states that are reachable from the initial state. We demonstrate the usefulness of the above techniques for solving first-order Markov decision processes within a domain dependent system called FluCaP which participated in the probabilistic track of the 2004 International Planning Competition. Working toward a domain independent implementation we present novel approaches to θ-subsumption involving literal and object contexts.
Spliceosomal protein E regulates neoplastic cell growth by modulating expression of Cyclin E/CDK2 and G2/M checkpoint proteins

Small nuclear ribonucleoproteins are essential splicing factors. We previously identified the spliceosomal protein E (SmE) as a downstream effector of E2F1 in p53‐deficient human carcinoma cells. Here, we investigated the biological relevance of SmE in determining the fate of cancer and non‐tumourigenic cells. Adenovirus‐mediated expression of SmE selectively reduces growth of cancerous cells due to decreased cell proliferation but not apoptosis. A similar growth inhibitory effect for SmD1 suggests that this is a general function of Sm‐family members. Deletion of Sm‐motifs reveals the importance of the Sm‐1 domain for growth suppression. Consistently, SmE overexpression leads to inhibition of DNA synthesis and G2 arrest as shown by BrdU‐incorporation and MPM2‐staining. Real‐time RT‐PCR and immunoblotting showed that growth arrest by SmE directly correlates with the reduction of cyclin E, CDK2, CDC25C and CDC2 expression, and up‐regulation of p27Kip. Importantly, SmE activity was not associated with enhanced expression of other spliceosome components such as U1 SnRNP70, suggesting that the growth inhibitory effect of SmE is distinct from its pre‐mRNA splicing function. Furthermore, specific inactivation of SmE by shRNA significantly increased the percentage of cells in S phase, whereas the amount of G2/M arrested cells was reduced. Our data provide evidence that Sm proteins function as suppressors of tumour cell growth and may have major implications as cancer therapeutics.
The Subtle Micro-Effects of Peacekeeping: Evidence from Liberia

We use original survey data and administrative data from post-war Liberia to test a theory of the micro-level impacts of peacekeeping. The theory proposes that through the creation of local security bubbles and also through direct assistance, peacekeeping deployments contribute to economic and social revitalization that may contribute to more durable peace. This theory guides the design of current United Nations peacekeeping operations, and has been proposed as one of the explanations for peacekeeping’s well-documented association with more durable peace. We identify local impacts of deployment bases by exploiting the fact that peacekeepers had limited information when selecting base localities, using coarsened exact matching to identify sets of communities that should have been equally likely to receive bases, and then using regression to clean up residual imbalances. Our evidence paint a complex picture that deviates substantially from the theory. We do not find evidence for local security bubbles around deployment base areas, and we do not find that deployments were substantial contributors to local social infrastructure. In addition, we find a negative relationship between deployment basing locations and NGO contributions to social infrastructure. Nonetheless, we find that deployments do seem to stimulate local markets, leading to better employment possibilities and substantially higher incomes. The result is something of a puzzle, suggesting that more work needs to be done on other types of direct assistance by peacekeeping contingents—e.g. the impact of mission procurement and routine spending by those associated with the mission. Also, the findings with respect to NGO activities suggest that this is an important factor that past case studies and cross-national studies have not taken into account sufficiently.
Predictors of systolic augmentation from left ventricular preexcitation in patients with dilated cardiomyopathy and intraventricular conduction delay.

BACKGROUND VDD pacing can enhance systolic function in patients with dilated cardiomyopathy and discoordinate contraction; however, identification of patients likely to benefit is unclear. We tested predictors of systolic responsiveness on the basis of global parameters as well as directly assessed mechanical dyssynchrony. METHODS AND RESULTS Twenty-two DCM patients with conduction delay were studied by cardiac catheterization with a dual-sensor micromanometer to measure LV and aortic pressures during sinus rhythm and LV free-wall pacing. Pacing enhanced isovolumetric (dP/dt(max)) and ejection-phase (pulse pressure, PP) systolic function by 35+/-21% and 16.4+/-11%, respectively, and these changes correlated directly (r=0.7, P=0.001). %DeltadP/dt(max) was weakly predicted by baseline QRS (r=0.6, P<0.02), more strongly by baseline dP/dt(max) (r=0.7, P=0.001), and best by bidiscriminate analysis combining baseline dP/dt(max) < or =700 mm Hg/s and QRS > or =155 ms to predict %DeltadP/dt(max) > or =25% and %DeltaPP > or =10% (P<0.0005, chi(2)), with no false-positives. Benefit could not be predicted by %DeltaQRS. To test whether basal mechanical dyssynchrony predicted responsiveness to LV pacing, circumferential strains were determined at approximately 80 sites throughout the LV by tagged MRI in 8 DCM patients and 7 additional control subjects. Strain variance at time of maximal shortening indexed dyssynchrony, averaging 28.0+/-7.1% in normal subjects versus 201.4+/-84.3% in DCM patients (P=0.001). Mechanical dyssynchrony also correlated directly with %DeltadP/dt(max) (r=0.85, P=0.008). Conclusions-These results show that although mechanical dyssynchrony is a key predictor for pacing efficacy in DCM patients with conduction delay, combining information about QRS and basal dP/dt(max) provides an excellent tool to identify maximal responders.
Closed Symbolic Execution for Verifying Program Termination

Symbolic execution, originally introduced as a method for program testing and debugging, is usually incomplete because of infinite symbolic execution paths. In this work, we adapt some well-known notions from partial evaluation in order to have a complete symbolic execution scheme which can then be used to check liveness properties like program termination. We also introduce a representation of the symbolic transitions as a term rewrite system so that existing termination provers for these systems can be used to verify the termination of the original program.
Face detection and tracking algorithm in video images with complex background

The problem in accurate and fast face detection and tracking in video images with complex background is studied in this paper. In order to meet both of speed and accuracy, a face detection method integrating the skin color segmentation and Split up Sparse Network of Winnows (SNoW) is presented. This kind of method can not only utilize the advantage of skin color segmentation to remove the interference of complex background, but also has the advantage of Split up SNoW in accurately classifying feathers. More importantly, this method can inherit their common advantage of fast speed. Based on these advantages, the method is used to detect human face areas and then use the way of Continuously Adaptive Mean Shift (CAMShift) to track human face areas. The experimental results show that the proposed method integrating the skin color segmentation and Split up SNoW is superior to each single method. Through this method we can achieve higher recognition accuracy and faster speed in face detection and tracking.
International Journal of Farming and Allied Sciences Detection of Empty Hazelnuts from Fully Nuts Using Artificial Neural Network Techniques

Hazelnut is native to Europe and Asia Minor and one of the products is important that the nuts are grown in over 20 countries worldwide. Major problem in Iran Hazelnut empty farmers before it is complete Overcoming this problem by examining the growth and development, but has not gone completely nuts osteoporosis and the need for new methods are needed to resolve these is important. One of the main reasons may be lack of suitable technology for classification of the quality. In this paper an intelligent separation system is presented based on artificial neural networks (ANNs) for separating empty hazelnuts without breaking them. The components of signal processing system include signal production and recording of its reflections. The produced sounds should be due to twirling of the hazelnuts and not slipping, therefore the spiral surface of the produced sounds has been designed in a way that hazelnut can rotate in all direction on its axis. After running the recorded sounds in MATLAB software, the results are investigated by Neural Network toolbox. The optimal model is selected after several evaluations based on minimizing of mean square error (MSE). A 12-12-1 multi-layer perceptron neural network was used for separation of empty hazelnuts.
Abstract 12916: Elevation of Fatty Acid-Binding Protein 4 is Predisposed by Family History of Hypertension and Contributes to Blood Pressure Elevation

[Background] Fatty acid-binding protein 4 (FABP4/A-FABP/aP2), a lipid chaperone, is expressed in both adipocytes and macrophages. Recent studies have shown secretion of FABP4 from adipocytes and association of elevated serum FABP4 level with obesity, insulin resistance, and atherosclerosis. However, little is known about the role of FABP4 in essential hypertension. [Methods] First, using blood samples in 296 subjects on no medication of our cohort, the Tanno-Sobetsu study cohort, correlation between serum FABP4 level and blood pressure was examined. Second, we next examined difference between serum FABP4 concentrations in 18 normotensives (NT) and 30 non-treated essential hypertensives (EHT). The EHT were divided into 18 insulin-sensitive EHT (EHT-S) and 12 insulin-resistant EHT (EHT-R) based on their insulin sensitivity index, the M value, determined by the hyperinsulinemic-euglycemic clamp technique. We lastly determined FABP4 levels in 30 young normotensive men with or without a family history of hyper.
A model-driven joint source and channel coder for MPEG-2 video transmission

This paper proposes a joint source and channel coding (JSCC) method for MPEG-2 video transmission. Based on the current channel status, this JSCC method finds the best source and channel code rate distribution. Due to the different bit error sensitivity of the source code. we apply unequal error protection (UEP) for the source bits by using so-called rate compatible punctured convolution (RCPC) channel coder for efficient protection during channel transmission. In the simulations. we illustrate that under the conditions of the same channel status and total bit rate. our method provides the minimal overall distortion of the MPEG-2 video compared to the equal error protection(EEP) coding.