Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of command parameters on efficiency, torque ripple and vibrations for Switched Reluctance motor

This paper deals with the upgrade of MRVSIM, a simulation software for the design assistance of Switched Reluctance Machines with Double Saliency and their electronic converters. This tool is completed with the integration of a vibratory module, in order to evaluate the vibration of the structure, and next to optimize the current command of the machine regarding to such criterion. Motor efficiency, torque ripple and vibrations are then used as optimization criteria to evaluate the impact on the resulting optimized command.
Short-term polynomial phase estimation: Application to radar signal in an electronic warfare context

With the growing electromagnetic traffic, Electronic Warfare (EW) systems need to be accurate or use new characterizing parameters in order to discriminate at best radar pulses. An accurate study of the Instantaneous Frequency Law (IFL) and Rate (IFR) offers some new opportunities. Multi-linear methods such as the High-order Ambiguity Function (HAF) or any General Representation of Phase Derivatives (GRPD) are often used to estimate those parameters but not in an EW context where short pulses and small chirp rates are recurrent. In this article, we first describe conditions for which those modulations can be estimated. Then, HAF and GRPD are studied in an EW context and their performances are compared to Cramer-Rao Bounds (CRB) to find the most appropriate one with industrial specifications.
Higher Frequency and Complexity of Sleep Disturbances in Dementia with Lewy Bodies as Compared to Alzheimer's Disease

Background: Sleep disturbances (SDs) are common in patients with all forms of dementia. However, most studies focus on Alzheimer's disease (AD) and less is known about the prevalence and characteristics of SD in dementia with Lewy bodies (DLB). Objective: The aims of this cross-sectional study were: (1) to examine the frequency of SD in DLB versus AD; (2) to compare patients with and without SD with regard to relevant clinical variables, and (3) to investigate the associations between SD and medication use. Methods: Patients with a first-time diagnosis of probable or possible DLB or AD were selected from the Dementia Study of Western Norway and recruited from clinics for old age psychiatry from 2010 until the end of 2013. Results: In all, 123 (55.7%) subjects with dementia suffered from at least one SD. Insomnia was present in 77 (34.8%), and 34 (20.7%) patients had probable REM-sleep behaviour disorder (RBD). All SDs were also significantly more frequent in patients with DLB than in AD, and DLB patients also more often had several co-occurring SDs. The presence of any SD was associated with more neuropsychiatric symptoms, higher morbidity, more parkinsonian symptoms and excessive daytime sleepiness. Antiparkinsonian medication was used more often in RBD, restless leg syndrome (RLS) and periodic limb movements, and benzodiazepines were also common in RLS. Conclusions: Sleep problems are more common in DLB patients compared to AD, and are associated with more clinical impairment. DLB patients frequently have several sleep problems occurring simultaneously, which suggests a need for screening and accurate assessment of sleep in DLB.
Interaction of Culture-based Learning and Cooperative Co-evolution and its Application to Automatic Behavior-based System Design

Designing an intelligent situated agent is a difficult task because the designer must see the problem from the agent’s viewpoint, considering all its sensors, actuators, and computation systems. In this paper, we introduce a bio-inspired hybridization of reinforcement learning, cooperative coevolution, and a cultural-inspired memetic algorithm for the automatic development of behavior-based agents. Reinforcement learning is responsible for the individual-level adaptation. Cooperative co-evolution performs at the population level and provides basic decision-making modules for the reinforcementlearning procedure. The culture-based memetic algorithm, which is a new computational interpretation of the meme metaphor, increases the lifetime performance of agents by sharing learning experiences between all agents in the society. In this paper, the design problem is decomposed into two different parts: 1) developing a repertoire of behavior modules and 2) organizing them in the agent’s architecture. Our proposed cooperative co-evolutionary approach solves the first problem by evolving behavior modules in their separate genetic pools. We address the problem of relating the fitness of the agent to the fitness of behavior modules by proposing two fitness sharing mechanisms, namely uniform and value-based fitness sharing mechanisms. The organization of behavior modules in the architecture is determined by our structure learning method. A mathematical formulation is provided that shows how to decompose the value of the structure into simpler components. These values are estimated during learning and are used to find the organization of behavior modules during the agent’s lifetime. To accelerate the learning process, we introduce a culturebased method based on our new interpretation of the meme metaphor. Our proposed memetic algorithm is a mechanism for sharing learned structures among agents in the society. Lifetime performance of the agent, which is quite important for real-world applications, increases considerably when the memetic algorithm is in action. Finally, we apply our methods to two benchmark problems, an abstract problem and a decentralized multi-robot objectlifting task, and we achieve human-competitive architecture designs. Index Terms – behavior-based system design, cooperative co-evolution, reinforcement learning, culturebased method, memetic algorithm, structure learning, behavior cooperative co-evolution.
Economic Dispatch of Thermal Units with the Impact of Wind Power Plant

As wind power penetrations increase in current power systems, its impacts to conventional thermal unit should be investigated. Development of better wind-thermal co-ordination economic dispatch is necessary to determine the optimal dispatch scheme that can integrate wind power reliably & efficiently. This paper proposes co-ordination of Synchronous Generator (SG) and Induction Generator (IG) by a simulation method that can fully assess the impacts of large-scale wind power on system operations from cost, reliability & environmental perspectives. But, IG has synchronization and stability problems. Hence, STATCOM is suggested. It is reported that STATCOM can significantly decrease voltage fluctuations of grid connected fixed speed wind generators. Moreover, its reactive power output can also be controlled to keep the wind farm terminal voltage constant. Simulation results clearly show that the STATCOM unit can smooth well the wind-generator output power & also maintain the terminal voltage at rated level. Comprehensive results are presented to assess the performance of the STATCOM connected with IG at steady-state where the simulations have been done by Simulink/MATLAB. Gradient method (Newton-Raphson method) is utilized to co-ordinate the wind & thermal generation dispatch & to minimize the total generation cost in the economic dispatch considering wind power generation. Three conventional thermal units system along with two Non-conventional units is utilized for numerical solution. Different simulation scenarios with & without wind power production are simulated . Simulation results show the effect of wind power generation in reducing total fuel cost. The Simulink/MATLAB software is used for simulation.
Guaranteeing the End-to-End Latency of an IMA System with an Increasing Workload

New features are often added incrementally to avionics systems to minimize the need for redesign and recertification. However, it then becomes necessary to check that the timing constraints of existing as well as new applications are met. We facilitate these checks by introducing a new data switch that bounds the latency of end-to-end communications across a network. This switch runs a clock-driven switching algorithm that is throughput-optimal with a bounded worst-case delay for all feasible traffic. We propose associated heuristics that determine whether the timing constraints of an integrated modular avionics (IMA) system network that uses this switch are met, even if new features have caused traffic to increase, and then search for alternative network configurations if necessary. Virtual integration is used to make a combined analysis of the worst-case delay in the network and the local buses of individual computing modules. This analysis considers the shared network topology, local hardware architectures, and specified IMA configurations. Our approach can be used by a system architect as an effective method for quickly determining which possible system architectures should be pursued to meet timing constraints, and it allows the cascading effects of changes to be tracked and managed. We demonstrate how these heuristics work through an example in which changes are made to an environmental monitoring facility within an avionics system that uses our switch.
Default and Information

In a traditional structural model of default it is implicitly assumed that the information used to calibrate and run the model is publicly available. In reality, model inputs and parameters are unobservable. In this article we analyze the role of information in structural models, which we specify through a model definition of the default time and a model filtration. The model definition relates the default of a firm to its assets and liabilities. The model filtration describes the information of investors relative to the model definition. It parameterizes a family of default models for a given default time. An important situation is when the default is not observable with respect to the model filtration. Examples include models with incomplete information about firm assets and models with incomplete information about the liability-dependent barrier that triggers default. Here the default time is typically totally inaccessible, as in the intensity-based, reduced-form models of default. In this case the model admits generalized reduced-form security pricing formulae in terms of the trend, which is the cumulative intensity. The trend can be explicitly characterized through the conditional default probability given the model filtration. If the trend is absolutely continuous with respect to the Lebesgue measure, then its density is the intensity and our formulae simplify to the classical intensity-based formulae. Not every incomplete information model admits an intensity. A model in which investors cannot observe the default barrier is a first example.
Exploiting Erraticism in Search

High sensitivity to initial conditions is generally viewed as a drawback of tree search methods because it leads to erratic behavior to be mitigated somehow. In this paper we investigate the opposite viewpoint and consider this behavior as an opportunity to exploit. Our working hypothesis is that erraticism is in fact just a consequence of the exponential nature of tree search that acts as a chaotic amplifier, so it is largely unavoidable. We propose a bet-and-run approach to actually turn erraticism to one's advantage. The idea is to make a number of short sample runs with randomized initial conditions, to bet on the “most promising” run selected according to certain simple criteria, and to bring it to completion. Computational results on a large testbed of mixed integer linear programs from the literature are presented, showing the potential of this approach even when embedded in a proof-of-concept implementation.
An algorithm to compute relative cubic fields

Let k be an imaginary quadratic number field (with class number 1). We describe a new, essentially linear-time algorithm, to list all isomorphism classes of cubic extensions L/k up to a bound X on the norm of the relative discriminant ideal. The main tools are Taniguchi's generalization of Davenport-Heilbronn parametrisation of cubic extensions, and reduction theory for binary cubic forms over imaginary quadratic fields. Finally, we give numerical data for k=Q(i), and we compare our results with ray class field algorithm ones, and with asymptotic heuristics, based on a generalization of Roberts' conjecture.
New information seeking behaviours of academics in the Nelson R. Mandela School of Medicine at the University of KwaZulu- Natal

This study examines the information needs and information searching behaviour of medical academics at the University of KwaZulu-Natal. An online web-based survey generated 72 responses to 286 invitations to academics. The responses provided information on various aspects of information seeking. The results of this study showed that medical academics display behaviour similar to that found in several other studies. The results do suggest however that the constraints of time result in non-optimal use of services. This finding has some consequences for the marketing of library services and training and development of medical academics.
Accuracy analysis of data aggregation for network monitoring

The quality of computing certain aggregation functions based on incomplete measurements for the purpose of distributed network monitoring is considered. Network monitoring plays a fundamental role in network management systems by providing timely information on the network status, which is crucial for administration purposes. To reduce network overhead and for easier assimilation, this information is usually presented by calculating a few key aggregate metrics. The aggregates are periodically computed from a large number of detailed events collected continuously during the course of the network operations. Under errors induced by network delays, the accuracy of typical aggregation functions used in network management systems is evaluated both analytically and by simulations. The results provide a quantifiable trade-off between accuracy and timeliness of the information acquired, which can then be used to design and optimize network management systems.
Approximating Higher-Order Distances Using Random Projections

We provide a simple method and relevant theoretical analysis for efficiently estimating higher-order lp distances. While the analysis mainly focuses on l4, our methodology extends naturally to p = 6,8,10. , (i.e., when p is even). Distance-based methods are popular in machine learning. In large-scale applications, storing, computing, and retrieving the distances can be both space and time prohibitive. Efficient algorithms exist for estimating lp distances if 0 2 is known to be difficult. Our work partially fills this gap.
Mixed-Valent Diruthenium Long-Chain Carboxylates. 2. Magnetic Properties.

The magnetic properties of several mixed-valent diruthenium long-chain carboxylates of general formula Ru(2)(RCO(2))(4)X (X = Cl, DOS, or RCO(2), DOS = dodecyl sulfate, and RCO(2) = linear aliphatic carboxylate or dialkoxy- or trialkoxybenzoate) were studied in the temperature range 6-400 K. All of the compounds exhibit a strong zero-field splitting (D = ca. 75 cm(-)(1)), independent of the nature of the axial anion X or of the equatorial substituent R. In the X = RCO(2) series an intermolecular antiferromagnetic (AF) interaction zJ = ca. -2 cm(-)(1) was found, whereas in the case of an X = DOS analogue, this interaction is very weak (-0.2 cm(-)(1)). The X = Cl series shows three distinct types of interdimer magnetic exchange: very weak, moderate (|zJ| approximately 2 cm(-)(1)), or strong (|zJ| > 10 cm(-)(1)). One representative complex in this series, Ru(2)(C(4)H(9)CO(2))(4)Cl, has been structurally characterized by X-ray crystallography. Crystal data: tetragonal system, space group I&fourmacr;2d, a = 14.137(3) Å, c = 26.246(5) Å, and Z = 8. Examination of the structures and magnetic behaviors suggests that the AF exchange in this series correlates with the Ru-Cl-Ru intermolecular angle; a qualitative explanation in terms of overlap of magnetic orbitals is proposed. Magnetic susceptibility measurements in the columnar mesophase of the mesomorphic congeners indicate that no significant structural change occurs at the crystal-liquid crystal transition.
A Dispute Arbitration Protocol Based on a Peer-to-Peer Service Contract Management Scheme

Cloud computing has provided an attractive model for business service delivery. However, accountability aspects, mainly the monitoring of the execution of a service contract, liability assignment and dispute arbitration are still lacking. On the one hand, the traditional centralized monitoring and the trusted-third party (TTP) based arbitration solutions are not suitable for the distributed cloud environment. On the other hand, a decentralized solution also faces challenges in guaranteeing fairness, accuracy and sustainability. To address this issue, this paper firstly proposes an innovative service contract management scheme that facilitates the monitoring of the execution of a service contract in a peer-to-peer environment, inspired by the concept of blockchain in Bitcoin. Secondly, on top of the scheme it presents a novel dispute resolution protocol based on the Byzantine agreement and the commitment scheme. Thirdly, it identifies the optimal settings of the key parameters of the protocol through a set of experiments and scenario analysis, aiming to strike the balance of fairness, accuracy, incentive maximization for the honest arbiters and cost minimization for the overall arbitration process. With this approach, service participants can be held accountable in a truly distributed environment without the presence of a central authority, which increases businesses confidence on adopting cloud services.
DTNC: A New Server-side Data Cleansing Framework for Cellular Trajectory Services

It is essential for the cellular network operators to provide cellular location services to meet the needs of their users and mobile applications. However, cellular locations, estimated by network-based methods at the server-side, bear with {\it high spatial errors} and {\it arbitrary missing locations}. Moreover, auxiliary sensor data at the client-side are not available to the operators. In this paper, we study the {\em cellular trajectory cleansing problem} and propose an innovative data cleansing framework, namely \underline{D}ynamic \underline{T}ransportation \underline{N}etwork based \underline{C}leansing (DTNC) to improve the quality of cellular locations delivered in online cellular trajectory services. We maintain a dynamic transportation network (DTN), which associates a network edge with a probabilistic distribution of travel times updated continuously. In addition, we devise an object motion model, namely, {\em travel-time-aware hidden semi-Markov model} ({\em TT-HsMM}), which is used to infer the most probable traveled edge sequences on DTN. To validate our ideas, we conduct a comprehensive evaluation using real-world cellular data provided by a major cellular network operator and a GPS dataset collected by smartphones as the ground truth. In the experiments, DTNC displays significant advantages over six state-of-the-art techniques.
ETISEO, performance evaluation for video surveillance systems

This paper presents the results of ETISEO, a performance evaluation project for video surveillance systems. Many other projects have already evaluated the performance of video surveillance systems, but more on an end-user point of view. ETISEO aims at studying the dependency between algorithms and the video characteristics. Firstly we describe ETISEO methodology which consists in addressing each video processing problem separately. Secondly, we present the main evaluation metrics of ETISEO as well as their benefits, limitations and conditions of use. Finally, we discuss about the contributions of ETISEO to the evaluation community.
A Best Practice Guide to Resource Forecasting for Computing Systems

Recently, measurement-based studies of software systems have proliferated, reflecting an increasingly empirical focus on system availability, reliability, aging, and fault tolerance. However, it is a nontrivial, error-prone, arduous, and time-consuming task even for experienced system administrators, and statistical analysts to know what a reasonable set of steps should include to model, and successfully predict performance variables, or system failures of a complex software system. Reported results are fragmented, and focus on applying statistical regression techniques to monitored numerical system data. In this paper, we propose a best practice guide for building empirical models based on our experience with forecasting Apache web server performance variables, and forecasting call availability of a real-world telecommunication system. To substantiate the presented guide, and to demonstrate our approach in a step by step manner, we model, and predict the response time, and the amount of free physical memory of an Apache web server system, as well as the call availability of an industrial telecommunication system. Additionally, we present concrete results for a) variable selection where we cross benchmark three procedures, b) empirical model building where we cross benchmark four techniques, and c) sensitivity analysis. This best practice guide intends to assist in configuring modeling approaches systematically for best estimation, and prediction results.
A case series of flow-through free anterolateral thigh flap to augment the vascularity of ischaemic limbs with soft tissue defect

Introduction: In a world of fast moving vehicles, heavy machinery and industries crush injury to limbs with vascular compromise and soft tissue defect is common. The traditional treatment is a 2 step one dealing with vascular repair and soft tissue cover separately, in the same operation. We report a series of single step vascular repair and soft tissue cover with flow through anterolateral thigh flap (ALT) flap for limb salvage. Materials and Methods: Ten patients with soft tissue defect and vascular injury were included in this study. A two team approach was used to minimise operative time, team one prepared the vessels and team 2 harvested the flap. Observations and Results: Of the ten patients operated (8 males), eight flaps were done for upper limb and two for lower limb salvage. Six anastomosis were done with ulnar vessels, two with radial and two with posterior tibial vessels. Nine extremities could be salvaged while one patient developed progressive thrombosis leading to amputation. Conclusion: The ALT flow-through flap is a versatile single step procedure that can be used to salvage an ischemic limb with soft tissue loss avoiding the need for interpositional vein graft.
The Role of Website Quality on PAD, Attitude and Intentions to Visit and Recommend Island Destination

This study investigates the effect of website stimuli on positive attitude and intentions to visit and recommend, through three emotional responses (pleasure, arousal and dominance). The model was tested regarding three island-related websites. Findings show the role of emotions as mediators between website quality attitude and intentions. Arousal and dominance are revealed to be more important in the formation of a positive attitude than pleasure. Visual appeal and ease of use, followed by information, seem to be the most important components in forming a perception of the islands’ website quality. Copyright © 2014 John Wiley & Sons, Ltd. Received 04 October 2013; Revised 21 March 2014; Accepted 23 July 2014