Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient simulation budget allocation with regression

Simulation can be a very powerful tool to help decision making in many applications; however, exploring multiple courses of actions can be time consuming. Numerous Ranking & Selection (R&S) procedures have been developed to enhance the simulation efficiency of finding the best design. This article explores the potential of further enhancing R&S efficiency by incorporating simulation information from across the domain into a regression metamodel. This article assumes that the underlying function to be optimized is one-dimensional as well as approximately quadratic or piecewise quadratic. Under some common conditions in most regression-based approaches, the proposed method provides approximations of the optimal rules that determine the design locations to conduct simulation runs and the number of samples allocated to each design location. Numerical experiments demonstrate that the proposed approach can dramatically enhance efficiency over existing efficient R&S methods and can obtain significant savings over regression-based methods. In addition to utilizing concepts from the Design Of Experiments (DOE) literature, it introduces the probability of correct selection optimality criterion that underpins our new R&S method to the DOE literature.
3D face detection and face recognition: state of the art and trends

Face detection and recognition are old but rapidly growing research areas due to increasing demands for security in industrial and law enforcement applications. Face recognition based on two-dimensional (2D) images have reached a significant level of maturity with some practical success. However the performance of 2D face recognition may degrade under poor illumination conditions, pose changing or for subjects of various skin colors. 3D face recognition represents a viable alternative to 2D face recognition in the research for a robust and practical identification system. This paper provides a review of research achievement in face recognition from 2007 to present. This survey mainly include three parts: (1) advances in face detections, (2) state of the art of 3D face recognition and (3) face images database and face recognition algorithm evaluation. Recent research has also demonstrated that the fusion of 2D and 3D face recognition can improve the overall performance of face recognition algorithm.
Improvement of Noise Performance in Phased‐Array Receivers

This paper presents a new analytical approach and experimental verification for the improvement of noise performance in phased‐array receivers. For analysis purposes, a multi‐channel array system is converted into an equivalent single‐channel system, such that the two presents the identical signal and noise powers at the output, respectively. We define an effective gain, noise figure, and signal‐to‐noise ratio in the equivalent system. Through the proposed approach, the noise performance of the array receiver is analyzed in a general and straightforward manner and then compared to that of each individual array channel. In addition, the phase noise of the array system is analyzed in a rigorous manner, showing its effective reduction by a factor of the array size. The predicted improvement of the noise performance is experimentally confirmed with a CMOS integrated phased‐array receiver.
Basics and applications of charge pumping in submicron MOSFET's

In this paper a review is made of the principles and the various applications of charge pumping in submicron MOSFETs. The use of the technique for the analysis of MOSFET degradation, energy and both lateral and vertical spatial profiling of the interface traps is discussed. The role and detection of so-called geometric components is illustrated, and the recently discovered ability of the technique to characterise single interface traps in submicron MOSFETs is demonstrated. Finally, the application of charge pumping in other devices, such as SOI-MOSFETs, EEPROM-cells and power transistors is briefly indicated.
CASE tool for object-relational database designs

In 1999, the SQL standard version presented new features to manipulate objects in relational database which has since been called Object-Relational Database (ORDB). Nowadays, many Object-Relational Database Management Systems (ORDBMS) offer resources to manipulate object in database. However, for these resources to become really utilized in corporate environment, it is necessary, among other things, to have CASE tools to aid in object-relational database design. An extension made in ArgoUML tool that permits developers to build graphics schemas to ORDBs is presented. These schemas can be generated using an ORDB profile presented here in. This profile is an extension of the UML class diagram and contains elements to represent the new resources to manipulate object in databases. The tool maps the graphic schema to SQL:2003 code and SQL code to Oracle dialect.
Effects of ship emissions on air quality in the Baltic Sea region simulated with three different chemistry transport models

Abstract. The Baltic Sea is a highly frequented shipping area with busy shipping lanes close to densely populated regions. Exhaust emissions from ship traffic into the atmosphere do not only enhance air pollution, they also affect the Baltic Sea environment through acidification and eutrophication of marine waters and surrounding terrestrial ecosystems. As part of the European BONUS project SHEBA (Sustainable Shipping and Environment of the Baltic Sea region), the transport, chemical transformation and fate of atmospheric pollutants in the Baltic Sea region were simulated with three regional chemistry transport model (CTM) systems, CMAQ, EMEP/MSC-W and SILAM, with grid resolutions between 4 and 11 km. The main goal was to quantify the effect that shipping emissions have on the regional air quality in the Baltic Sea region when the same shipping emission dataset but different CTMs are used in their typical set-ups. The performance of these models and the shipping contribution to the results of the individual models were evaluated for sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3) and particulate matter (PM2.5). Model results from the three CTMs for total air pollutant concentrations were compared to observations from rural and urban background stations of the AirBase monitoring network in the coastal areas of the Baltic Sea region. Observed PM2.5 in summer was underestimated strongly by CMAQ and to some extent by EMEP/MSC-W. Observed PM2.5 in winter was underestimated by SILAM. In autumn all models were in better agreement with observed PM2.5. The spatial average of the annual mean O3 in the EMEP/MSC-W simulation was ca. 20 % higher compared to the other two simulations, which is mainly the consequence of using a different set of boundary conditions for the European model domain. There are significant differences in the calculated ship contributions to the levels of air pollutants among the three models. EMEP/MSC-W, with the coarsest grid, predicted weaker ozone depletion through NO emissions in the proximity of the main shipping routes than the other two models. The average contribution of ships to PM2.5 levels in coastal land areas is in the range of 3.1 %–5.7 % for the three CTMs. Differences in ship-related PM2.5 between the models are mainly attributed to differences in the schemes for inorganic aerosol formation. Differences in the ship-related elemental carbon (EC) among the CTMs can be explained by differences in the meteorological conditions, atmospheric transport processes and the applied wet-scavenging parameterizations. Overall, results from the present study show the sensitivity of the ship contribution to combined uncertainties in boundary conditions, meteorological data and aerosol formation and deposition schemes. This is an important step towards a more reliable evaluation of policy options regarding emission regulations for ship traffic and the planned introduction of a nitrogen emission control area (NECA) in the Baltic Sea and the North Sea in 2021.
Control of single-degree-of-freedom Hamiltonian systems with impulsive inputs

This paper develops a theory for the feedback control of single degree-of-freedom Hamiltonian systems, utilizing inputs which approximate /spl delta/-functions. The main idea is that by using "spikey" control inputs, it is possible to force the system to jump between energy levels. Since there is a correspondence between energy levels and orbits for Hamiltonian systems, this control of system energy results in control of the system dynamics. Impulsive control has proven useful in simulations and experiments involving the global reconfiguration of mechanical systems. We present application of the control to the cart and pendulum swing-up problem.
Nonparametric Method Using an Alignment Method in a Randomized Block Design with Replications

Mack and Skillings (1980) proposed a typical nonparametric method in a randomized block design with replications. However, this method may lose information because of the use of average observations instead of individual observations. In this paper, we proposed a nonparametric method that employed an aligned method suggested by Hodges and Lehmann (1962) under a randomized block design with replications. In addition, the comparative results of a Monte Carlo power study are presented.
Distributed sensor processing over an ad hoc wireless network: simulation framework and performance criteria

The evaluation of existing and future distributed sensor processing system concepts can be done well using simulation, provided that the simulation is faithful in representing both the medium in which the sensors interface with the phenomena that they measure or detect and the medium in which the sensors interface with each other to achieve a distributed mode of operation. Performance criteria for distributed sensor processing over ad hoc wireless networks are stated and an architecture for analysis and simulation of this kind of system is described.
Michael John Robert Fasham. 29 May 1942 — 7 June 2008

Professor Michael Fasham played a pioneering role in the development of marine ecosystem models for the study of nutrient and carbon cycling in the ocean. He is particularly celebrated for his famous Fasham–Ducklow–McKelvie model, which was the first of its kind to separate new and regenerated forms of nutrient, as well as including microbial recycling pathways. Fasham's models provided key understanding of the links between primary production, carbon cycling and export (of organic matter from the surface to deep ocean) based on both deep and insightful parameterization inspired by his many collaborations with leading experimental and field biologists of the day, and by his expert use of data for model calibration and validation. He had the ability to see the big picture, linking observation and models to achieve a unified understanding of system dynamics. As well as the direct contributions of his own science, Fasham played a pivotal role in steering the international scientific agenda, notably his leadership of the Joint Global Ocean Flux Study which had the aim of understanding ocean carbon cycling and sinks via the coordination of extensive field programmes, synthesis and modelling. He will be remembered by those who knew him for his openness, enthusiasm and modesty, a man who was fun to know and to work with and who loved the thrill of scientific adventure and discovery.
Towards the validation of a method for quantitative mobile usability testing based on desktop eyetracking

With the fast evolution in the development of applications for mobile devices, the study and adequacy of usability evaluation methodologies in this context is becoming an increasingly demand. Current techniques and equipment particularly adapted to these types of interfaces, such as specific eyetracking equipment for mobile devices, are trying to offer a solution to contexts related to mobility. However, due to known physical restrictions, especially the limited size of displays, data registered by this kind of equipment is limited to qualitative data. These restrictions are especially strong when collecting data from eyetracking techniques. Further study is needed to assess usability in mobile interfaces quickly and comprehensively. This paper shows a state of the art review on the mobile usability evaluation field, specifically focused on the application of eyetracking techniques in usability testing for mobile interfaces. Once related handicaps and awkwardness's are identified, an agile method for exploiting desktop eyetracker equipment in combination with mobile devices is proposed. The point is coming into play the same facilities used in traditional usability testing in order to obtain qualitative and quantitative data. An experimental study of the proposed method has been carried out for two purposes. The first one is to prove the efficiency and applicability of the method, in comparison to existing options. The second one is to deeply analyse quantitative data extracted from the experiment related not only to the gaze, but also to the visual cognition issue in the exploration of the interface. Initial findings from this study are presented.
Review of Sensor-based Activity Recognition Systems

Abstract Activity recognition (AR) has become a hot research topic due to its strength in providing personalized sup port for many diverse applications such as healthcare and security. Due to its importance, a considerable amount of AR systems have been developed. In general, these systems utilize diverse sensors to obtain the activity related information, which are then used by machine learning techniques to infer human’s ongoing activity. According to the types of sensors used, existing AR systems can be roughly divided into two catego ries: 1. Video sensor based AR. It remotely observes human activity using video sensors; 2. Physical sensor based AR (PSAR). It attaches physical sensors to the body of human or objects (appliances) to infer human activity. Based on the location of attached sensors, PSAR consists of two subcategories: Wearable sensor based AR and object usage based AR. In this work, different types of AR are reviewed. We think this review is significant because no existing review papers include all the different types of AR as a whole. For each type of AR, its main techniques, characteristics, strengths and limitations are discussed and summarized. We also make a comparative analysis for them. Finally the main research challenges in AR are pointed out.
Effects of Mild and Severe Knee Joint Pain on the Frequency of Falls and Fall Risk in Elderly Females

This study aimed to examine differences in the frequency of falls during the past year and fall risk among 392 elderly females was categorized into five groups on the basis of the knee pain expe-rienced: no knee pain, mild unilateral knee pain, mild bilateral knee pain, severe unilateral knee pain, and severe bilateral knee pain. The subjects participated in a fall risk survey comprising 50 items representing five risk factors: “symptoms of falling”, “disease and physical symptoms”, “en-vironment”, “behavior and character”, and “physical function”. The frequency of falls during the past year, score for each risk factor, and the total fall risk score were not significantly different between the mild unilateral and mild bilateral knee pain groups, and between the severe unilateral and severe bilateral knee pain groups. Therefore, these groups were pooled to form a mild knee pain group and a severe knee pain group and analyzed. The severe knee pain group had experienced a significantly greater number of falls during the past year compared with the no knee pain group. Furthermore, the symptom of falling score was significantly higher in the severe knee pain group than in the no knee pain group, while the disease and physical symptoms score was significantly higher in the mild and severe knee pain groups than in the no knee pain group. The physical function score and total fall risk score were significantly higher in the following order: the severe knee pain group, the mild knee pain group, and the no knee pain group. Our results indicate that for elderly females who can achieve ADL independently, the degree of knee pain (mild or severe) has a marked effect on fall risk, irrespective of laterality of the pain (unilateral or bilateral). Factors such as symptoms of falling, disease and physical symptoms, and physical function are also related to fall risk in this population. Furthermore, elderly individuals with severe knee pain experience frequent falls.
Design of a Computer Code To Evaluate the Influence of the Harmonics in the Electrical Networks

This paper aims to present the design of a computer code (HPFCODE), for calculate a power flow and power losses in power systems under the influence of harmonics, using the GUI in MATLAB. After described the program was run for two networks IEEE 6 nodes and IEEE 14 nodes. The power flow by Newton-Raphson method was calculated as the losses of active and reactive power in the lines, respectively, where the loads are linear and nonlinear (Static Var Compensator(SVC), Thyristor controlled Reactor(TCR), and Unified Power Flow Controller ((UPFC)), The results were almost consistent and show the influence of higher harmonics on power losses in electrical networks. DOI: http://dx.doi. org/10.11591/ijece.v2i5. 1465 Full Text: PDF
Zirconium-Based Metal–Organic Framework Nanocarrier for the Controlled Release of Ibuprofen

Electrospray-differential mobility analysis coupled with aerosol particle mass analysis (ES-DMA/APM) was demonstrated for the development of a metal–organic framework (MOF) nanocarrier system. A successful quantification of ibuprofen loading in UiO-66-NH2 (i.e., the representative drug molecule and MOF, respectively) achieved based on the aerosol particle mass of MOF measured by ES-DMA/APM (≈55 mg of ibuprofen/g of UiO-66-NH2). The structural stability of UiO-66-NH2 versus ibuprofen release was successfully quantified over a 7-day period in an acidic phosphate buffer solution. The methodology provides a proof-of-concept scheme for controlled release studies of different types of active pharmaceutical ingredients from a variety of MOF-based nanocarrier systems.
A Traffic Matrix Recovery Algorithm via Low-Dimension Nature in Smart Grid

In this literature, we explore the solution of network traffic recovery in smart grid. Taking account of dimensionality of network traffic in smart grid, we propose a novel reconstruction model via network tomography. In our algorithm, we use the low-dimension nature of traffic matrix and the greedy adaptive dictionary algorithm to convert the network tomography into the problem of sparse reconstruction at first. Then we solve network traffic by an iterative greedy algorithm. Simulation results indicate that proposed algorithm exhibits noticeably improvement in estimation error comparing with previous work.
A fast nearest-neighbor search algorithm

A fast nearest-neighbor search algorithm is developed which incorporates prior information about input vectors. The prior information comes in the form of a vector from the codebook which is known to be near the input vector, though it may not be the nearest codebook vector. A number of applications are described for which such prior information is available. The algorithm has a very simple structure and can be designed to have very low memory requirements. The new algorithm requires much less computation for constructing precomputed tables than previously proposed algorithms with comparable performance. Simulations show dramatic saving over conventional full search methods. <<ETX>>
The linguistic annotation of corpora: The TOSCA analysis system

The article discusses the role of linguistic annotation in corpus linguistics as opposed to annotation in natural language processing. In corpus linguistics, annotation is an integral part of the process of linguistic interpretation and description of the data. Tagging and parsing are discussed as the automatic counterparts of, respectively, the paradigmatic and the syntagmatic description of corpus data. The requirements for a corpus linguistic annotation system are considered. An account is given of the TOSCA analysis system as representative of such an annotation system. Performance results of the system are given, and an evaluation is made.
Using Unlabeled Data to Improve Author Identification

Authorship attribution may be considered as a text categorization problem. Text categorization requires a large number of training examples which are particularly difficult to obtain in the case of authorship attribution task. In this paper, we investigate the possibility of using Web-based text-mining methods for the identification of the author of a given poem. In particular, we propose a semi-supervised method that is specially suited to work with just few training examples in order to tackle the problem of the lack of data with the same writing style. The results obtained on poem categorization show that this method may significantly improve the classification accuracy and it is appropriate to handle the attribution of short documents.
Technical solutions for a full-resolution autostereoscopic 2D/3D display technology

Auto-stereoscopic 3D displays capable of high quality, full-resolution images for multiple users can only be created with time-sequential systems incorporating eye tracking and a dedicated optical design. The availability of high speed displays with 120Hz and faster eliminated one of the major hurdles for commercial solutions. Results of alternative display solutions from SeeReal show the impact of optical design on system performance and product features. Depending on the manufacturer's capabilities, system complexity can be shifted from optics to SLM with an impact on viewing angle, number of users and energy efficiency, but also on manufacturing processes. A proprietary solution for eye tracking from SeeReal demonstrates that the required key features can be achieved and implemented in commercial systems in a reasonably short time.
Multi-frequency polarimetric SAR interferometry for vegetation structure extraction

The authors compare the relative information content of single baseline polarimetric interferometry at C-, L- and P-bands and conclude as to the best frequency range for vegetation structure estimation. They present an inversion algorithm for vegetated terrain based on a coherent polarimetric scattering model of volume and surface scattering. They point out some general aspects of using multi-frequency interferometric techniques for vegetation studies and use L- and P-band data from the DLR E-SAR system to verify the theoretical models.
The Analysis and Improvement about Word Similarity Computing Method Based on HowNet

Word similarity computing is widely used in many fields, such as question answer,text clustering and so on. This paper synthesizes previous research achievement and proposes an improved word similarity computing method based on Hownet. The improvement is mainly shown in the following aspects: We make a difference between the antonym and common words ,and define the value range of sememe similarity as [-1, 1]; what’s more we not only consider the hyponymy, but the depth and density as we compute the sememe similarity, then makes the result more distinctly; besides we introduce the concepts of weak and supplement sememes, and lower the effect of the weak and supplement sememes by reducing the weight of weak and supplement as we compute the concept similarity. Experiment shows that the improved method makes the word similarity more practically.