Miracle-dz/UniFAR-FTUs huggingface dataset:
A fuzzy self-adaptive PID tracking control of autonomous surface vehicle

Proportional Integral Derivative (PID) controller is a conventional controller, which is widely used in industrial control system. In this paper, a PID control system is used for path tracking of an autonomous surface vehicle (ASV). The PID controller is selected because it is easy to implement as an embedded controller and practically easy to understand compared to other control methods. However, to improve the response of the PID controller, a fuzzy inference system (FIS) is used to tune the controller parameters based on a set of control rules. Three parallel fuzzy self-adaptive PID controllers is used to track the desired position and angular orientation of the ASV along the surge, sway and yaw directions. Through kinematic modeling of the ASV, the desired model for tracking the desired path could be obtained. Simulation results show that the Fuzzy-PID controller performs better compared to the ordinary PID controller in term of improving settling time and reducing overshoot of the control signal.
Shortest Path Estimation for small-world networks using a taxonomy

Can a hierarchy of semantic information of a social graph be used to effectively estimated shortest paths within that graph? The need to compute the shortest paths in social graphs has increased with the rise of social media and the internet before that. This paper attempts to find a way to lower computation cost of the all pairs shortest path problem within social networks. Showing that a hierarchical structure of information on the social graph provides a good basis for path estimation.
A robust linear discrimination fault classification scheme for three phase induction motors

In this article a fault classification algorithm based on a robust linear discrimination scheme, for the case of a squirrel-cage three phase induction motor, will be presented. The suggested scheme is based on a novel feature extraction mechanism from the measured magnitude and phase of current park's vector pattern. The proposed methodology has the merit to diagnose different types of faults such as: (a) broken rotor bar, and (b) short circuit in stator winding. The novel feature generation technique is able to transform the problem of fault detection and diagnosis into a simpler space, where direct robust linear discrimination can be applied for solving the classification problem. Robust linear discrimination has been one of the most widely used fault detection method in real life applications, as this methodology seeks for directions that are efficient for discrimination and at the same time requires a straight forward implementation. The efficacy of the proposed scheme will be evaluated based on multiple simulation results for different fault types.
An energy-efficient, fast FPGA hardware architecture for OpenCV-Compatible object detection

The presence of cameras and powerful computers on modern mobile devices gives rise to the hope that they can perform computer vision tasks as we walk around. However, the computational demand and energy consumption of computer vision tasks such as object detection, recognition and tracking make this challenging. At the same time, a fixed vision hard core on the SoC contained in a mobile chip may not have the flexibility needed to adapt to new situations, or evolve as new algorithms are discovered. This may mean that computer vision on a mobile device is the killer application for FPGAs, and could motivate the inclusion of FPGAs, in some form, within modern smartphones. In this paper we present a novel hardware architecture for object detection, that is bit-for-bit compatible with the object classifiers in the widely-used open source OpenCV computer vision software. The architecture is novel, compared to prior work in this area, in two ways: its memory architecture, and its particular SIMD-type of processing. The implementation, which consists of the full system, not simply the kernel, outperforms a same-generation technology mobile processor by a factor of 59 times, and is 13.5 times more energy-efficient.
A NOVEL METHOD FOR VISUALIZING FUNCTIONAL CONNECTIVITY USING PRINCIPAL COMPONENT ANALYSIS

Functional connectivity is a useful measure of voxel-wise functional magnetic resonance imaging signals that allows for the identification of functionally related brain areas and distributed networks. However, the high dimensionality of functional connectivity makes it difficult to visualize. In most studies, a small percentage of the total functional connectivity is visualized through diagrams that are constructed using individual seed voxels. In the present study describes a new method for visualizing most of the functional connectivity through a single diagram. This method does not rely on seed voxels, but rather employs a reduction of the high-dimensionality of the functional connectivity via a projection onto a three-dimensional color space using principal components analysis. With this new method, most of the information contained in a functional connectivity matrix can be represented through a single color-coded functional connectivity map, thereby facilitating a greater visual appreciation of functional connectivity.
An Agonistic Model of Dialogue

In this article, Schellhammer's statements that learning is only possible in tension and that difference and diversity are prerequisites for tension are discussed in light of a certain event that occurred at a Summer School on Pluralism, Development, and Social Change. The article aims to explore Bildung, and especially learning in tension, through a concrete case study in which cultural diversity is a key issue. Reflecting on the case, psychological, philosophical, and sociopolitical perspectives are presented, each of which casts a different light on what happened. In the final reflection, we turn to the question of what dialogical self theory (DST) can offer when it comes to learning in tension, and how DST can be enriched and challenged by other approaches. We argue that DST facilitates the development of intercultural competence through dialogue with the unknown other in the self. Philosophical notions of cosmopolitanism and Socratic self-examination can shed further light on resistance to and conditions for transformative dialogues. They also place these in a historical and global perspective. We introduce an agonistic model of dialogue, in which the structural power inequalities and privileges people bring into dialogical spaces are explicitly addressed, thereby sowing the seeds of postdialogue transformative action in a personal and professional sense—for example, in transformative justice initiatives.
A demand-based e-government adoption model (DeAM)

This paper proposes a new conceptual model that explains factors that influence the uptake of e-government services in a developing country context. The development of the conceptual model was guided by qualitative data collected from a range of e-government potential adopters using semi-structured interviews informed by prior e-government literature. The paper starts by describing the research methods used, followed by a description of the environment in which the interviews took place and the analytical method used. Then, a detailed description of the domain analysis technique used to analyze the qualitative data is provided. This is followed by presenting the findings of the study and highlighting the main domains that emerged from the data which led to the development of the conceptual Demand-based e-government Adoption Model (DeAM).
Monte Carlo Pricing of American Options Using Nonparametric Regression

This paper provides an introduction to Monte Carlo algorithms for pricing American options written on multiple assets, with special emphasis on methods that can be applied in a multi-dimensional setting. Simulated paths can be used to estimate by nonparametric regression the continuation value of the option or the optimal exercise policy and the value functions can then be computed by backward induction. The flexibility of nonparametric regression allows to obtain accurate price estimates with remarkable speed. For illustrative purposes we price one- and two-dimensional American options.
A load of cobbler's children: beyond the model designing processor

HCI has developed rich understandings of people at work and at play with technology, moving beyond users' minds to their moods, buddies and bodies. However, understandings of designers remain trapped within the information processing paradigm of first wave HCI, remaining focused on minds that execute design methods as if they were computer programs, and producing the same results on a range of architectures and hardware. Designers are people too, with minds, moods, buddies and bodies, which all interfere substantially (generally to good effects) with the 'code' of design methods. We need to take full account of designers' humanity when assessing design and evaluation methods. This juried alt.chi paper moves from critique to a logocentric proposal based on resource function vocabularies as a more appropriate basis for understanding and assessing methods.
Key-based Blocking of Duplicates in Entity-Independent Probabilistic Data

Currently, in many application areas the demand on probabilistic data grows. Duplicate entity representations are an essential problem of data quality, for certain databases as well as for probabilistic databases. Traditional duplicate detection approaches are based on pairwise comparisons. For dealing with large data sets, however, a comparison of all entity representation pairs is impractical and the search space is usually reduced by blocking techniques. The majority of blocking techniques is based on the usage of keys created from the original representations. These techniques, however, are only designed to deal with certain keys and hence cannot be used for probabilistic data without any adaptation. In this paper, we propose an adaptation of existing blocking techniques to data uncertainty based on the creation of certain keys from the probabilistic data. Moreover, we discuss some approaches for adapting the techniques' core functionalities to handle probabilistic keys. A final set of experiments evaluates the quality of our certain key based approaches in terms of pairs completeness and pairs quality.
A Study of Techno-Economic Feasibility Analysis of Solar Photovoltaic (PV) Power Generation in the Province of Adana in Turkey

In this study, the examination of techno-economic feasibility analysis of a solar photovoltaic (PV) power generation were carried out by taken into account a PV power plant that has the capacity of 100 kWe as an example, in the province of Adana, Turkey. For this purpose, the technical characteristics of the PV array, the amount of electricity production, the cost of electricity production, investment and operating costs, payback periods and the amount of CO2 emissions reduction were determined for the solar PV plant. By using the total area of 653.4 m2 PV cell, total 135,403 MWh of electricity was produced in the power plant. To this end, total 5 units of PV arrays were required with the surface area of 130.7 m2 each. In this case, the system efficiency was determined as 12.2%, the annual specific efficiency of the system was 1,352 kWh/kW and the amount of CO2 emissions reduction was obtained as 119,830 Mg/year. The payback period of the system was 7.8 years and the electricity production cost was 0.1400 TL (Turkish Liras)/kWh, respectively.
Tracking and Size Estimation of Objects in Motion

Detection and tracking of moving objects in video is emerging in computer vision and robotics. Classification of objects in addition to the detection and tracking can lead to better understanding of the scene and helps in taking certain decisions in various applications. Classifying the objects based on the features like color, shape, size, speed, direction of objects in motion has numerous applications. In this paper, we consider the size of an object in motion. We present a model to estimate the size of an object in motion using optical flow technique, and present some applications in watermarking, steganography and in robotics where the size of an object in motion is an important parameter to be considered.
A complexity theory-based management framework for virtual organisations

This article describes a complexity theory-based management framework for virtual organisations. Specific focus is on a South African virtual organisation as a complex adaptive system. A case study strategy was followed, and multiple data sources used to generate theory. The findings describe the management of an organisation where technology replaces conventional face-to-face contexts for integration and assimilation. The article showed how managers create a virtual context for sharing meaning and interaction through synergy, empowerment, participation and an accountable, committed workforce. Key words: Complexity theory, management, post-modern organisation forms, virtual organisations.
UT-OCL: an OpenCL framework for embedded systems using xilinx FPGAs

FPGA vendors now include hardened IPs to form a system-on-chip (SoC) making it easier to build embedded systems. However programming and integrating hardware accelerators (devices) into these systems present a challenge. The OpenCL standard has become accepted as a good programming model for managing devices, or hardware accelerators in the context of embedded systems on FPGAs, due to its rich set of constructs. OpenCL has also caught the attention of FPGA vendors for use in high-level systhesis (HLS). While commercial OpenCL frameworks are now emerging, there is a need for an open-source OpenCL framework that facilitates the exploration of the overall system architecture and software, as well as the implementation and architectures of the task-level parallel devices. This would enable exploration of concepts that can improve current architectures as well as allow the study of features that are not within the current standard. This paper presents UT-OCL, an OpenCL framework for embedded systems using FPGAs. The framework is composed of a hardware system and its necessary software counterparts, which together form an embedded Linux system augmented to run OpenCL applications within a single FPGA. This paper describes the challenges with implementing an OpenCL framework for embedded systems on FPGAs, and presents an OpenCL implementation that is compliant with OpenCL 2.0. This framework is intended for use as a platform to explore architectures for hosting OpenCL applications, implemetations of OpenCL features and to study potential new features for OpenCL. Although the current trend is to use OpenCL in high-level synthesis targeting FPGAs, it is not the focus of this paper.
Optimization of Contrast Material Dose for Abdominal Multi-Detector Row CT: Predicting Patient Lean Body Weight by Using Preliminary Transverse CT Images

Estimated LBW could be used to determine the contrast material dose and rate during MDCT. The aim of this study is to test the accuracy of a technique for estimation of lean body weight (LBW) from a single multi-detector row computed tomographic (MDCT) abdominal image, using a bioelectrical body composition analyzer scale as the reference standard. CT images of 21 patients with previously measured LBW (mLBW) were processed using computer-assisted, vendor-specific software (Advantage Windows 4.2; GE Healthcare, Inc). For each transverse image, a fat-fraction was automatically measured as the number of fat pixels (-200 to -50 HU) divided by the total number of pixels having an attenuation value ≥-200 HU. Estimated LBW (eLBW) of five single contiguous sections was calculated in each of three abdominal regions (upper abdomen, mid abdomen and pelvis) by multiplying TBW by (1 – fat-fraction). Bland-Altman plot with limits of agreement was used to assess agreement between mLBW and eLBW. The mean mLBW for all patients was 56 kg (range, 39 - 75 kg). Mean differences and limits of agreement between mLBW and eLBW measurements for the upper abdomen, mid abdomen and pelvis reported were -8.9 kg (-25.6 kg, +7.5 kg), -10.6 kg (-27.7 kg, +6.4 kg), and +0.5 kg (-12.8 kg, +13.8 kg) respectively. eLBW deriving directly from a transverse CT image of the pelvis can accurately predict mLBW.
The contact dynamics method for granular media

In this paper we review the simulation method of the non-smooth contact dynamics. This technique was designed to solve the unilateral and frictional contact problem for a large number of rigid bodies and has proved to be especially valuable in research of dense granular materials during the last decade. We present here the basic principles compared to other methods and the detailed description of a 3D algorithm. We point out an artifact manifesting itself in spurious sound waves and discuss the applicability of the method.
QuickPup: A Heuristic Backtracking Algorithm for the Partner Units Configuration Problem

The Partner Units Problem (PUP) constitutes a challenging real-world configuration problem with diverse application domains such as railway safety, security monitoring, electrical engineering, or distributed systems. Although using the latest problem-solving methods including Constraint Programming, SAT Solving, Integer Programming, and Answer Set Programming, current methods fail to generate solutions for midsized real-world problems in acceptable time. This paper presents the QuickPup algorithm based on backtrack search combined with smart variable orderings and restarts. QuickPup outperforms the available methods by orders of magnitude and thus makes it possible to automatically solve problems which couldn’t be solved without human expertise before. Furthermore, the runtimes of QuickPup are typically below one second for real-world problem instances.
An Empirical Study on the Selection of Good Metamorphic Relations

Full software test automation requires automated test input generation, execution, and output evaluation. The latter task is non-trivial and usually referred to as the oracle problem in software testing. The present paper describes an empirical study on metamorphic testing, an approach to the oracle problem. This study was conducted with common Java implementations of determinant computation in order to evaluate the usefulness of the metamorphic testing approach and to establish general criteria that can be used to quickly assess metamorphic relations with respect to their suitability. The latter is very important, since metamorphic testing is based on so-called metamorphic relations on input-output tuples, which can easily be found. It is, however, crucial to evaluate these relations according to their usefulness. The empirical study enables us to derive general rules that can be used to quickly assess metamorphic relations and identify those that should be considered and studied in more detail with other methods (e.g. with mutation analysis)
Quality of Service in Web Services Discovery

The ability to discover required Web services and select the most proper one is becoming critical in Service-Oriented applications. Many techniques have been proposed to optimize the selections of Web Services by calculating quality of service (QoS). In this paper, we incorporate QoS advertisements of service providers into WSDL documents. The Quality Manager is introduced to discover Web services, collect quality ratings from users, and calculate QoS when a quality assessment is required. We calculate and compare user-concerned quality attributes using exception-based method. When all concerned quality attributes are retrieved, the ratings of web services are then calculated and the most suitable one is selected.
Effects of dexmedetomidine on oxygenation and lung mechanics in patients with moderate chronic obstructive pulmonary disease undergoing lung cancer surgery

BACKGROUND Chronic obstructive pulmonary disease (COPD) is a risk factor that increases the incidence of postoperative cardiopulmonary morbidity and mortality after lung resection. Dexmedetomidine, a selective &agr;2-adrenoreceptor agonist, has been reported previously to attenuate intrapulmonary shunt during one-lung ventilation (OLV) and to alleviate bronchoconstriction. OBJECTIVE The objective is to determine whether dexmedetomidine improves oxygenation and lung mechanics in patients with moderate COPD during lung cancer surgery. DESIGN A randomised, double-blinded, placebo-controlled study. SETTING Single university hospital. PARTICIPANTS Fifty patients scheduled for video-assisted thoracoscopic surgery who had moderate COPD. Patients were randomly allocated to a control group or a Dex group (n = 25 each). INTERVENTIONS In the Dex group, dexmedetomidine was given as an initial loading dose of 1.0 &mgr;g kg−1 over 10 min followed by a maintenance dose of 0.5 &mgr;g kg−1 h−1 during OLV while the control group was administered a comparable volume of 0.9% saline. Data were measured at 30 min (DEX-30) and 60 min (DEX-60) after dexmedetomidine or saline administration during OLV. MAIN OUTCOME MEASURES The primary outcome was the effect of dexmedetomidine on oxygenation. The secondary outcome was the effect of dexmedetomidine administration on postoperative pulmonary complications. RESULTS Patients in the Dex group had a significantly higher PaO2/FIO2 ratio (27.9 ± 5.8 vs. 22.5 ± 8.4 and 28.6 ± 5.9 vs. 21.0 ± 9.9 kPa, P < 0.05), significantly lower dead space ventilation (19.2 ± 8.5 vs. 24.1 ± 8.1 and 19.6 ± 6.7 vs. 25.3 ± 7.8%, P < 0.05) and higher dynamic compliance at DEX-30 and DEX-60 (P = 0.0001 and P = 0.0184) compared with the control group. In the Dex group, the PaO2/FIO2 ratio in the postoperative period was significantly higher (P = 0.022) and the incidence of ICU admission was lower than in the control group. CONCLUSION Dexmedetomidine administration may provide clinically relevant benefits by improving oxygenation and lung mechanics in patients with moderate COPD undergoing lung cancer surgery. TRIAL REGISTRATION ClinicalTrial.gov identifier: NCT 02185430.
A theoretical framework for ontology evaluation and validation

The need for evaluation-methodologies emerged very early in the field of ontology development and reuse and it has grown steadily. Yet, no comprehensive and global approach to this problem has been proposed to date. This situation may become a serious obstacle for the success of ontology-based Knowledge Technology, especially in the industrial and commercial sectors. In this paper we look at existing ontology-evaluation methods from the perspective of their integration in one single framework. Based on a catalogue of qualitative and quantitative measures for ontologies, we set up a formal model for ontology. The proposed formal model consists of a meta-ontology Othat characterizes ontologies as semiotic objects. The meta-ontology is complemented with an ontology of ontology evaluation and validation oQual. Based on O and oQual, we identify three main types of measures for ontology evaluation: structural measures, that are typical of ontologies represented as graphs; functional measures, that are related to the intended use of an ontology and of its components, i.e. their function; usability-related measures, that depend on the level of annotation of the considered ontology.