Miracle-dz/UniFAR-FTUs huggingface dataset:
Global modelling studies of composition and decadal trends of the Asian Tropopause Aerosol Layer

Abstract. The Asian Summer Monsoon (ASM) traps convectively-lifted boundary layer pollutants inside its upper-tropospheric lower-stratospheric Asian monsoon anticyclone (AMA). It is associated with a seasonal and spatially-confined enhanced aerosol layer, called the Asian Tropopause Aerosol Layer (ATAL). The knowledge of the ATAL properties in terms of aerosol budget, chemical composition, as well as its variability and temporal trend is still largely uncertain, due to the dynamical variability of the AMA, the dearth of in situ observations in this region, the complex transport pathways of pollutants and its atmospheric chemical processes. In this work, we use the Community Earth System Model (CESM 1.2 version) based on the coupling of the Community Atmosphere Model (CAM5) and the MAM7 (Modal Aerosol Model) aerosol module to simulate the composition of the ATAL and its decadal trends. Our simulations cover a long-term period of 16 years from 2000 to 2015. We identify a double-peak aerosols vertical profile for the ATAL. We attribute the upper peak (around 100 hPa, predominant during early ATAL in June) to dry aerosols, possibly from nucleation processes and the lower peak (around 250 hPa, predominant for a well-developed and late ATAL, in July and August) to cloud-borne aerosols associated with convective clouds. We find that mineral dust is the dominant aerosol by mass in the ATAL showing a large interannual variability, but no long-term trend, due to its natural variation. The results between 120–80 hPa (dry aerosol peak) suggest that for aerosols other than dust the ATAL is composed of around 40 % of sulfate, 30% of secondary and 15 % of primary organic aerosols, 14 % of ammonium aerosols and less than 3 % of black carbon. The analysis of the anthropogenic and biomass burning aerosols shows a positive trend for all aerosols simulated by CESM-MAM7.
From centralized to dsitributed mobility management. A contribution to future mobile networks: Gestión de la movilidad centralizada y distribuida. Una contribución para las redes móviles de próxima generación

Over the last few years, IP-based mobility management in the Internet has been one of the most active research fields in communications. Existing IP mobility support protocols are all based on a centralized mobility anchor that manages the traffic and signaling of the mobile nodes. However, centralized mobility management protocols need to be redesigned in order to cope with the recent trends in mobile Internet and current increasing mobile data traffic demand. In order to address these limitations which inherently occur in Centralized Mobility Management (CMM) protocols, Distributed Mobility Management (DMM) solutions are being developed to efficiently handle the current mobile traffic explosion. In DMM, the core idea is that the mobility anchors are distributed within the network, topologically closer to the users, with the aim to provide an almost optimal routing support and an efficient use of network resources to improve the scalability required for next generation mobile networks. To cope with this evolution, the thesis concerns analysing, designing, and evaluating IPv6 mobility management protocols. Specifically, we propose three novel approaches which cover each of this evolutionary stage. Our first scheme, LinkWork Mobile MPLS is a centralized solution. The second proposal called DM3 is based on the distributed paradigm. Finally, the third proposal is a Hybrid DMM solution, suitable to tackle future mobile network architectures. In order to evaluate the proposed schemes, we carry out analysis and simulations to measure the performance of the protocols in terms of mobility cost and handover latency.
Verification of aero‐elastic offshore wind turbine design codes under IEA Wind Task XXIII

This work presents the results of a benchmark study on aero-servo-hydro-elastic codes for offshore wind turbine dynamic simulation. The codes verified herein account for the coupled dynamic systems including the wind inflow, aerodynamics, elasticity and controls of the turbine, along with the incident waves, sea current, hydrodynamics and foundation dynamics of the support structure. A large set of time series simulation results such as turbine operational characteristics, external conditions, and load and displacement outputs was compared and interpreted. Load cases were defined and run with increasing complexity to trace back differences in simulation results to the underlying error sources. This led to a deeper understanding of the underlying physical systems. In four subsequent phases—dealing with a 5-MW turbine on a monopile with a fixed foundation, a monopile with a flexible foundation, a tripod and a floating spar buoy—the latest support structure developments in the offshore wind energy industry are covered, and an adaptation of the codes to those developments was initiated. The comparisons, in general, agreed quite well. Differences existed among the predictions were traced back to differences in the model fidelity, aerodynamic implementation, hydrodynamic load discretization and numerical difficulties within the codes. The comparisons resulted in a more thorough understanding of the modeling techniques and better knowledge of when various approximations are not valid. More importantly, the lessons learned from this exercise have been used to further develop and improve the codes of the participants and increase the confidence in the codes’ accuracy and the correctness of the results, hence improving the standard of offshore wind turbine modeling and simulation. One purpose of this paper is to summarize the lessons learned and present results that code developers can compare to. The set of benchmark load cases defined and simulated during the course of this project—the raw data for this paper—is available to the offshore wind turbine simulation community and is already being used for testing newly developed software tools. Despite that no measurements are included, the large number of participants and the—in general—very fine level of agreement indicate high trustworthy results within the physical assumptions of the codes and the simulation cases chosen. Other cases, such as large prebend flexible blades, large wind shear, large yaw error or transient maneuvers, may not show the same level of agreement. These cases were deliberately left out because the focus is on the specific offshore application. Further on, this benchmark study includes participating codes and organizations by name (contrary to several previous benchmark studies) that gives the reader a chance to find results from one particular code of interest.Copyright © 2013 John Wiley & Sons, Ltd.
Development Status and Multilevel Classification Strategy of Medical Robots

The combination of artificial intelligence technology and medical science has inspired the emergence of medical robots with novel functions that use new materials and have a neoteric appearance. However, the diversity of medical robots causes confusion regarding their classification. In this paper, we review the concepts pertinent to major classification methods and development status of medical robots. We survey the classification methods according to the appearance, function, and application of medical robots. The difficulties surrounding classification methods that arose are discussed, for example, (1) it is difficult to make a simple distinction among existing types of medical robots; (2) classification is important to provide sufficient applicability to the existing and upcoming medical robots; (3) future medical robots may destroy the stability of the classification framework. To solve these problems, we proposed an innovative multilevel classification strategy for medical robots. According to the main classification method, the medical robots were divided into four major categories—surgical, rehabilitation, medical assistant, and hospital service robots—and personalized classifications for each major category were proposed in secondary classifications. The technologies currently available or in development for surgical robots and rehabilitation robots are discussed with great emphasis. The technical preferences of surgical robots in the different departments and the rehabilitation robots in the variant application scenes are perceived, by which the necessity of further classification of the surgical robots and the rehabilitation robots is shown and the secondary classification strategy for surgical robots and rehabilitation robots is provided. Our results show that the distinctive features of surgical robots and rehabilitation robots can be highlighted and that the communication between professionals in the same and other fields can be improved.
Critical factors analysis and its ranking for implementation of GSCM in Indian dairy industry

Purpose – Sustainability in food sector is the need of the hour. It has been revealed that Green supply chain management (GSCM) is an emerging new and effective approach to improve the productivity, efficiency of any enterprises and to achieve sustainability. The purpose of this paper is to rank the key performance indicators which are responsible for implementation of GSCM in Indian dairy sector. Ranking is done by giving weightage to them based on survey reports. The study includes literature review, personal interviews and surveys using the detailed questionnaire. Since food processing industry, e.g. dairy industry is the major energy user and directly affecting the health of public is being chosen for implementing GSCM practices. The approach is to form an effective framework for successful implementation of GSCM in dairy sector. Grouping of key performance indicators has been done using factor analysis and thereafter Analytic hierarchy process (AHP) method has been applied to determine the suitable f.
Accuracy of automatic QT measurement techniques

The aim of this study was to compare, against manual measurement, 3 algorithms for automatic QT interval measurement using eight 4 lead ECGs recorded from normal subjects. The algorithms investigated determined T wave end from (a) the intercept of the isoelectric line and maximum T wave slope, thresholds applied to (b) the T wave and (c) the differential of the T wave. Mean manual-automatic QT measurement differences of 27 to 29 ms for algorithm a, -2 to 20 ms for b and -5 to 4 ms for c were found. The standard deviations (SD) of the manual-automatic differences varied from 9 to 30 ms. Failure to measure the QT interval (1 to 12 cases) occurred with only algorithm b. Each algorithm performed differently with the mean and SD of the differences, and failure rate for b, dependent on threshold and isoelectric levels used. <<ETX>>
Autonomous littoral warfare systems evaluator-engineering simulation (ALWSE-ES)

Performing surveillance, reconnaissance, mapping, reacquisition, identification, and neutralization of mines in the littoral environment presents a very complex and difficult problem to solve. The natural environment of this area is extremely dynamic and energetic, creating a formidable challenge for any appointed system. Evaluating system performance and interoperability are also very difficult in this environment. The complex nature of the littoral area's environmental interactions requires the use of systems that rely increasingly on complicated tactics, high-resolution peripheral components, and sophisticated processing algorithms. In addition, the availability and flexibility of autonomous platforms have resulted in thousands of concept permutations which can be used to address missions in the littorals. Evaluating the effectiveness of these concepts in an orderly, structured, and consistent way requires the use of an effective engineering-simulation based analysis approach. The Coastal Systems Station (CSS) is utilizing such an approach by developing a high fidelity, engineering level simulation tool named the Autonomous Littoral Warfare Systems Evaluator-Engineering Simulation (ALWSE-ES). ALWSE-ES is closely related to the higher level stochastic tool, ALWSE-MC, and will serve as a foundational tool supporting an overall systems engineering toolset. ALWSE-ES allows the detailed characterization of environmental effects on systems under test, providing a synthetic environment in which to evaluate an engineering concept or design. This paper describes the approach and implementation of ALWSE-ES. ALWSE-ES is being developed in support of the Very Shallow Water/Surf Zone Mine Countermeasures Reconnaissance Program.
An efficient adaptive structure for interference rejection and PN correlation simultaneously in DS spread-spectrum system

The author propose an efficient interference rejection filter structure for direct-sequence spread-spectrum systems. Unlike the existing structures, the proposed adaptive filter performs interference rejection and pseudorandom sequence correlation simultaneously. The number of arithmetic operations required to implement the structure is reduced significantly as compared to existing algorithms. Compared with the performance of the system proposed by Li and Milstein (1982) the proposed system yields improved mean-square error (MSE), especially in the high range of the signal-to-Gaussian noise ratio.
Analysis of reliability improvement possibilities of thermoelectric cooling devices

The methods of reliability improvement of single- and multi-stage thermoelectric devices (TED) were considered. It is shown that in the range of modes from the maximum cooling capacity to the minimum failure rate, there are intermediate modes, in which the influence of the parameters of thermoelements (electric conductivity, thermoEMF, efficiency etc.) is different, which suggests that selecting the combinations of parameters allows to improve reliability indicators of the product. The methods of reliability improvement in the design of thermoelectric devices when changing the ratio of height to the cross-sectional area of the thermoelement, which reduces the required number of thermoelements and TED failure rate were analyzed. Within the constructive method, the possibility of choosing the optimal current operating modes of cooling thermoelements for various operating conditions using a criteria-based approach was shown. Possibilities of a parametric method due to: improving the quality of starting thermoelectric materials and enhancing their effectiveness; using various combinations of starting materials at the same efficiency were defined. According to the results of the comparative analysis of the basic reliability parameters and indicators for various combinations of parameters of starting materials, analytical relations for calculating the basic parameters for various operating modes and temperature fluctuations were obtained. It is shown that using the combined method allows to significantly increase the reliability of the device. The above methods of reliability improvement of cascaded TED are a tool in the design of highly reliable thermally loaded equipment using thermoelectric cooling.
Antecedents and Impacts of Service Operations Flexibility: A Multiple Regression Approach

This study investigates the antecedents of service operations flexibility (SOF) in the forms of structural and infrastructural elements. Additionally, it examines the SOF’s impacts on company performances. Structural elements decisions are grouped as capacity, location, integration/networking, and technology while infrastructural elements decisions encompass worker empowerment, quality leadership, and team management. Service operations flexibility is divided into internal robustness and external flexibility while company performances are categorized as financial and non-financial. An instrument to measure all the factors was designed and pre-tested on 30 MBA students. Subsequently, a pilot study was conducted to check the reliability of the instrument. The exercise involved 23 Malaysian service organizations. Respondents were operations managers involved in the decision making process. All items used to measure the studied factors were found to be reliable. The preliminary study was followed by a large scale survey that involved architect and accountant firms, considered as professional groups in Schmenner’s service typology. For the international inputs, we engaged researchers who are attached to the local universities of the respected countries. A total of 224 valid responses were received from Malaysia, Indonesia, India and South Africa. Using factor analysis, the antecedents were regrouped into quality leadership, technology, integration, training and motivation, team management, capacity, location, and worker involvement. Separate factor analysis was done on the measures associated with flexibility that resulted in external flexibility and internal robustness. The third factor analysis was done on the measures of company performances which resulted in clear distinction of financial and non-financial performance. Finally, the relationships were tested using multiple regression analysis. The first analysis was done to test the relationship between the antecedents and the SOF. We found that all antecedents except worker involvement significantly are influencing the external flexibility dimension, but only two factors; technology and worker involvement affecting internal robustness. Another multiple regression test was done to test the impacts of the SOF on performances. We found that non-financial performances were affected by external flexibility.
Machine learning in exploitation (Invited Paper)

Exploitation has largely focused on single look, single modality platform collections exploited by a variety of classification algorithms over the last several decades. But multi look, multi modality exploitation is the evolving paradigm for threat classification given the evolution and cost of near term unmanned vehicle system sensor platforms. This paper presents an overview of machine learning algorithms that have previously been applied to automatic target recognition, discusses the evolution of target recognition to the 2010 paradigm of multi look, multi modality valid target identification, and explores how advanced machine learning algorithms can be applied to address the exploitation problems of the next decade.
High frequency inductor design concepts

The trend towards planar shapes for electromagnetic components in high-frequency power converters presents difficulties for the design of inductors that operate at frequencies in the megahertz range. Two existing and two improved inductor design concepts are studied, and it is shown how the internal and external leakage fields are affected by them. Flux plots are presented to illustrate the patterns of these fields and theoretical and experimental results for winding losses are given. <<ETX>>
Research on Modeling High-Mix and Variable-Batch Flow Manufacturing System

For the problem of modeling high-mix and variable-batch flow manufacturing system, the thesis focus on method of mixed processing task and mechanism of constructing manufacture unit. First, decompose the processing task into Manufacturing Task Tree (MTT for short) according to the level of ‘orders-products-components-fittings-parts’. Then decompose each level node of the MTT to task cell. Then on the basis of processing task, we construct the framework of processing tasks management for group mixed flow manufacturing and analyze the mechanisms of building manufacturing unit for high-mix and variable-batch flow manufacturing system. Finally, we established the model of high-mix and variable-batch flow manufacturing system.
Theoretical and experimental power from large horizontal-axis wind turbines

A method for calculating the output power from large horizontal-axis wind turbines is presented. Modifications to the airfoil characteristics and the momentum portion of classical blade element-momentum theory are given that improve correlation with measured data. Improvement is particularly evident at low tip speed ratios where aerodynamic stall can occur as the blade experiences high angles of attack. Output power calculated using the modified theory is compared with measured data for several large wind turbines. These wind turbines range in size from the DOE/NASA 100 kW Mod-O (38 m rotor diameter) to the 2000 kW Mod-1 (61 m rotor diameter). The calculated results are in good agreement with measured data from these machines.
Implications of fundamental threshold voltage variations for high-density SRAM and logic circuits

As the number of transistors integrated on a circuit continues to increase, roughly doubling every 18 months, the impact of transistor variations on circuit performance becomes more significant. Even in the absence of systematic variations (implant nonuniformities, Leff and Weff variations), there exists a fundamental variability in the threshold voltage V/sub T/ due to the finite number of dopant atoms in the extremely small MOSFET channel area. This work presents for the first time the impact of these fundamental V/sub T/ variations on SRAM cell stability and CMOS logic performance. We also analyze the impact of device scaling on these V/sub T/ variations and propose guidelines for future SRAM cell design. <<ETX>>
AUTOMATED CLASSIFICATION OF CONSTRUCTION PROJECT DOCUMENTS

The number of documents generated in a construction project and stored in interorganizational information systems is significant. Since a large percentage of these project documents are generated in text format, methods for organizing and improving access to the information contained in these types of documents become essential to construction information management. Information classification schemes can be used for this purpose. They provide a common framework to enact document organization and information exchange among project members. Current systems for document management rely on manual classification methods controlled by human experts. Due to the widespread use of information technologies for construction, the increasing availability of electronic documents, and the development of systems based on project object models, manual classification becomes unfeasible. This paper presents a unique way to improve information organization and access in interorganizational systems based on automated classification of construction project documents according to their related project components. Machine-learning methods were used for this purpose. A prototype of a document classification system was developed to provide easy deployment and scalability to the classification process.
Effect of Device Variables on Surface Potential and Threshold Voltage in DG-GNRFET

In this paper we present four simple analytical threshold voltage model for short- channel and length of saturation velocity region (LVSR) effect that takes into account the built – in potential of the source and drain channel junction, the surface potential and the surface electric field effect on double – gate graphene nanoribbon transistors. Four established models for surface potential, lateral electric field, LVSR and threshold voltage are presented. These models are based on the easy analytical solution of the two dimensional potential distribution in the graphene and Poisson equation which can be used to obtain surface potential, lateral electric field, LVSR and threshold voltage. These models give a closed form solution of the surface potential and electrical field distribution as a function of structural parameters and drain bias. Most of analytical outcomes are shown to correlate with outcomes acquired by Matlab simulation and the end model applicability to the published silicon base devices is demonstrated.