Miracle-dz/UniFAR-FTUs huggingface dataset:
A Node Mobile Handoff Model Based on Resource Allocation in Wireless Mobile Networks

The technology on network interconnection handoff with the QoS guarantee is becoming an important research issue in wireless mobile networks. Most of the current researches focus on the cell mobile networks, the schemes of which are comparatively complex in solving the QoS guarantee in mobile node handoff and the utilization rate of resource is lower. In order to reduce these disadvantages to the minimal extent, the model (HDBRA) on the mobile node handoff with service guarantee applied in the wireless mobile networks is presented in the paper based on the dynamic network bandwidth resource allocation in the real-time detection on the data flow state and network traffic-load in interconnection gateway nodes. And according to the state of the applications data in mobile node handoff, the model describes and analyzes in detail the dynamic resource allocation and reservation, and the release of the reserved resource as well. In the scheme, the real-time adjustment on resource allocation is achieved based on the real-time measurement on network traffic-load in interconnection gateway nodes and the method also achieves the balance on network traffic-load. Theoretic analysis and simulation test the correctness and validity of the model in the paper.
Analyzing Sequence Data

In this article we discuss optimal matching (OM), an invaluable yet underutilized tool in the analysis of sequence data. Initially developed in biology to identify and study patterns in DNA sequences, OM subsequently migrated over to sociology, where it has been used to examine career patterns in life course research. It involves the computation of the number of insertions, deletions, and substitutions of sequence elements that are needed to transform one sequence into another and the costs associated with such transformations. The goal is to identify similarities across sequences, which can then be used for pattern identification. Along with a discussion of the logic underlying OM analysis, we provide an illustration of its use in the examination of careers of deans at U.S. business schools. In addition, we use Monte Carlo simulation to compare OM and cluster analysis and highlight the superiority of OM analysis in the analysis of sequence data. Also discussed are recent methodological advances that have been made in OM and our recommendations and guidelines for future applications of OM in management research.
Effects of the Transcranial Direct Current Stimulation on Prevention of Postoperative Cognitive Dysfunction after Cardiac Surgery: Prospective, Randomized, Double-Blind Study

Introduction: Postoperative cognitive dysfunction (POCD) is a contrary event observed between 20 to 83%, especially in elderly and after cardiac surgery. Prevention and rehabilitation on cases of POCD may improve the quality of life. The neuromodulator effect of the noninvasive cerebral stimulation has been used in the treatment of brain injuries, depression, and also in the cognitive rehabilitation. The hypothesis is that the use of the transcranial direct current stimulation (tDCS) technique can decrease the occurrence of POCD and cognitively rehabilitate patients submitted to cardiac surgeries. The objective of this study will be to evaluate the tDCS effect over the occurrence of POCD in patients on cardiac surgeries. Methods: After approval the institutional ethics committee, will be included in the study 138 adult submitted a cardiac surgery. After assigned the consent form patients will be randomly allocated in two groups. tDCS GROUP: Submitted to 2 daily sessions of cerebral stimulation, starting from the first day after surgery during 4 consecutive days, with each session having 20 minutes. Will be applied a direct current stimulus of 2mA in the right anode and in the left cathode on the prefrontal right region. SHAM GROUP: The same equipment used in tDCS as simulated stimulus similar to the active one. Will also be summited to neuropsychological tests to evaluate memory, attention, and executive functions as well as data relative of surgery, cognitive evolution and quality of life in the postoperative period. The neuropsychological test will be describes according groups and the moments of application, with mean and standard deviation (SD) and compared to results of normative tables with Z-score (±1,96). The data will be expressed in means, medians, confidence intervals (CI-95%) and SD and analyzed by Generalized Estimating Equation (GEE), to comparison of the results between the two groups. P<0,05 will be considered significant.
GPU Accelerated Dissipative Particle Dynamics with Parallel Cell-list Updating

A general purpose DPD simulation entirely implemented on GPU is presented in this paper, including cell-list updating, force calculation and integrating forward. The algorithm and optimization needed to obtain best performance of GPU is discussed. The performance benchmarks show that our implementation running on single GPU can be more than 20x faster than conventional implementation running on single CPU core and 10x faster than that running on 5 CPU cores.
Studies on techniques and application of numerical simulation oriented 3-dimensional reconstruction for medical images

Software of 3D reconstructions for medical images is basically focused on the application of visualization. Few people have studied the techniques and software about numerical simulation oriented 3D reconstructions for medical images that mainly solve the problems such as visualization for 3D reconstructions, model modifying and mesh generation for finite element analysis. These issues were reviewed and analyzed, the development toolkits were introduced, and some attentive questions and their corresponding solutions as well as some new perspectives were proposed.
On the role(s) of modelling in cognitive science

Although work on computational and robotic modelling of cognition is highly diverse, as an empirical method it can be roughly divided into at least two clearly different, though non-exclusive branches, motivated to evaluate the sufficiency or the necessity of theories when it comes to accounting for data and/or other observations. With the rising profile of theories of situated/embodied cognition, a third non-exclusive avenue for investigation has also gained in popularity, the investigation of agent-environment embedding or more generally, exploration. Still in its infancy, and often confused with sufficiency testing, this relatively new kind of modelling, which is theory- rather than data-driven, investigates the role of the environment in shaping the ontogenetic and/or phylogenetic development of situated agency. Each of these three approaches presents many issues that modellers must be sensitive to, both in the design of experiments, and in the conclusions that can be drawn from them. This paper highlights some of these issues, provides examples, and addresses the contribution of computational/robotic modelling to cognitive science, as well as some of its limitations.
Iso-precision scaling of digitized mammograms to facilitate image analysis

A 12 bit CCD camera equipped with a linear sensor of 4096 photodiodes is used to digitize conventional mammographic films. An iso-precision conversion of the pixel values is performed to transform the image data to a scale on which the image noise is equal at each level. For this purpose film noise and digitization noise have been determined as a function of optical density and pixel size. It appears that only at high optical densities digitization noise is comparable to or larger than film noise. The quantization error caused by compression of images recorded with 12 bits per pixel to 8 bit images by an iso-precision conversion has been calculated as a function of the number of quantization levels. For mammograms digitized in a 40962 matrix the additional error caused by such a scale transform is only about 1.5 percent. An iso-precision scale transform can be advantageous when automated procedures for quantitative image analysis are developed. Especially when detection of signals in noise is aimed at, a constant noise level over the whole pixel value range is very convenient. This is demonstrated by applying local thresholding to detect small microcalcifications. Results are compared to those obtained by using logarithmic or linearized scales.
Proximity warning and terrain modelling system based on Delaunay triangulation and surface spline interpolation

A three-dimensional real time proximity warning system (PWS) has been developed using a combination of object oriented programming techniques, open graphics library (OpenGL), global positioning system (GPS) and wireless communications networking. The main purpose of this research is to probe the application of information technologies in preventing the run-over incidents that occur frequently in large mobile equipment operations in open pit mining. The system provides three major functions: first, the system has the ability to display three-dimensional drawing exchange format (DXF) maps and has the basic map operation functions such as zoom in, zoom out, move, rotate, etc. Second, the system can show the real time positions of the trucks on the laptop installed on the truck and generate warming information when the clients are too close to each other, and then send the warming information to the client trucks. Third, the system has the ability to record the GPS positions and regenerate the surface of the mine based on the new recorded positions. So the surface maps of the mine can be updated timely. The whole system can be divided into two parts: server and clients. The clients can be any moving utilities with a GPS device installed. The server is responsible for the communication between the clients, monitors the behaviour of the clients and computes the distance between the clients in real time. Whenever the distance between two clients is less than the safe distance, warning messages will be sent to the clients and shown on the computer screens installed on the clients. The hardware of the system contains the wireless network, GPS receivers and computers installed on trucks. The system can also be applied to other industrial applications to monitor the activities of moving utilities and improve operational safety. This paper will explain the development of the system and display the field test results.
Probability, Scale of Delicacy and Proximity

This paper discusses the semantic constraints of English News probability, scale of delicacy and relationship between proximity and semantic proximity and its measurement method as well as the semantic constraints of the three factors on lexical information. Article introduces "semantic proximity" concept from the mandarin information processing and computer applications. By combing the algorithm of semantic proximity and semantic distance, the summary is obtained: the proposal algorithm of scale of delicacy in second language testing; semantic distance value and the measurement methods of the "semantic proximity".
Prosodic Breaks and Attachment Decisions in Sentence Parsing.

The role of prosodic breaks (PB) in the parsing of locally ambiguous NP+ V + NP + PP French sentences was examined in four word monitoring experiments. The presence of a PB after the verb was shown to hinder the VP-attachment interpretation (# The spies inform # the guards of the conspiracy #), whereas the presence of a second PB in front of the PP seemed to neutralise the effect of the first break (# The spies inform # the guards # of the conspiracy #). Moreover, the second PB apparently produced a greater effect when the verb's argument structure conflicted with the actual attachment of the PP (i.e. when the sequence of words used in the sentence required an NP-attachment in the case of a ditransitive verb like “to inform”, and a VP-attachment in the case of a monotransitive verb like “to choose”). These results clearly indicate that PBs can influence sentence parsing. Possible mechanisms are discussed in the framework of Frazier's (1987) garden-path model and Perfetti's (1990) restricted interactive model.
Distributed model predictive control based on a cooperative game

In this work we propose a distributed model predictive control scheme based on a cooperative game in which two different agents communicate in order to find a solution to the problem of controlling two constrained linear systems coupled through the inputs. We assume that each agent only has partial information of the model and the state of the system. In the proposed scheme, the agents communicate twice each sampling time in order to share enough information to take a cooperative decision. We provide sufficient conditions that guarantee practical stability of the closed‐loop system as well as an optimization‐based procedure to design the controller so that these conditions are satisfied. The theoretical results and the design procedure are illustrated using two different examples. Copyright © 2010 John Wiley & Sons, Ltd.
Comparison of VAAC atmospheric dispersion models using the 1 November 2004 Grimsvötn eruption

The robustness of the Numerical Atmospheric‐dispersion Modelling Environment (NAME) for forecasting the dispersion of volcanic ash clouds is investigated by comparing the output from different Volcanic Ash Advisory Centre (VAAC) models initialised using the parameters for the 2004 Grimsvötn, Iceland, volcanic eruption. London, Darwin, Washington, Montreal and Toulouse VAAC dispersion models are all run operationally as if responding to the eruption. Comparison of the model set‐ups reveals differing approaches between the VAACs for model averaging times, ash release rates, and thresholds for defining the ash cloud, amongst others. The importance of these factors is considered in detail. Despite using different weather conditions and having different structures, the models all demonstrate strong similarities for forecasting regional ash cloud transport. The dispersal of volcanic ash is simulated over Scandinavia and as far as Eastern Europe in all cases. Greater variations are seen between the forecast ash concentrations for different aircraft flight levels. The model forecasts are highly dependent on the amount of eruption information available at the time. Copyright © 2007 Royal Meteorological Society
Computer-based creativity enhanced conceptual design model for non-routine design of mechanical systems

Computer-based conceptual design for routine design has made great strides, yet non-routine design has not been given due attention, and it is still poorly automated. Considering that the function-behavior-structure(FBS) model is widely used for modeling the conceptual design process, a computer-based creativity enhanced conceptual design model(CECD) for non-routine design of mechanical systems is presented. In the model, the leaf functions in the FBS model are decomposed into and represented with fine-grain basic operation actions(BOA), and the corresponding BOA set in the function domain is then constructed. Choosing building blocks from the database, and expressing their multiple functions with BOAs, the BOA set in the structure domain is formed. Through rule-based dynamic partition of the BOA set in the function domain, many variants of regenerated functional schemes are generated. For enhancing the capability to introduce new design variables into the conceptual design process, and dig out more innovative physical structure schemes, the indirect function-structure matching strategy based on reconstructing the combined structure schemes is adopted. By adjusting the tightness of the partition rules and the granularity of the divided BOA subsets, and making full use of the main function and secondary functions of each basic structure in the process of reconstructing of the physical structures, new design variables and variants are introduced into the physical structure scheme reconstructing process, and a great number of simpler physical structure schemes to accomplish the overall function organically are figured out. The creativity enhanced conceptual design model presented has a dominant capability in introducing new deign variables in function domain and digging out simpler physical structures to accomplish the overall function, therefore it can be utilized to solve non-routine conceptual design problem.
Integrated Mechanistic-Empirical Modeling of Cellular Response Based on Intracellular Signaling Dynamics

A hybrid modeling framework integrating a highly specific mechanistic model with highly abstract empirical model is presented. With the growing interest in the scientific and medical community for identification of therapeutic targets in treatment of disease, it is necessary to develop predictive models that can describe cellular behavior in response to environmental cues. Intracellular signaling pathways form complex networks that regulate cellular response in both health and disease. Mechanistic (or white-box) models of biochemical networks are often unable to explain comprehensive cellular response due to lack of knowledge and/or intractable complexity (especially in events distal from the cell membrane). Empirical (or black-box) models may provide a less than accurate representation of cellular response due to data deficiency and/or loss of mechanistic detail. In the proposed framework, we use a mechanistic model to capture early signaling events and apply the resulting generated internal signals (along with external inputs) to a downstream empirical sub-model. The key construct in the approach is the treatment of a cell’s biochemical network as an encoder that creates a functional internal representation of external environmental cues. The signals derived from this representation are then used to inform downstream behaviors. Using this idea, we are able to create a comprehensive framework that describes important mechanisms with sufficient detail, while representing complex or unknown mechanisms in a more abstract form. The model is verified using published biological data describing T-Cells in immune response.Copyright © 2013 by ASME
Video Copy Detection Based on Principal Component Analysis

Content-based video hashing was proposed for the purpose of video copy detection. Conventional video copy detection algorithms apply image hashing algorithm to either every frame or key frame which is sensitive to video variation. In our proposed algorithm, key frames including temporal and spatial information are used to video copy detection, Discrete cosine transform (DCT) is done for video key frame and feature vector is extracted by principal component analysis ( PCA ). An average true positive rate of 99.31% and false positive rate of 0.37% demonstrate the robustness and uniqueness of the proposed algorithm. Experiments indicate that it is easy to implement and more efficient than other video copy detection algorithms.
An outlook on intranet management

The growing trend of corporate organizations to embrace intranet technology is accelerating the computing paradigm shift from a desktop-centric model to a network-centric one. Intranet revamps the enterprise LAN and WAN by adorning them with the glaze of Internet attire. As with any kind of network, intranet reliability is subordinate to the attention and effort put into its management. Since what characterizes an intranet is not only its network infrastructure but also its information content and the way it is created, shared, and stored, intranet management must extend beyond typical network management issues and encompass service management. The authors elaborate on intranet management and reflect on the challenges it poses.
Traffic Classification based on Adjustable Convex-hull Support Vector Machines

Traffic classification plays an important role in traffic management. To traditional methods, P2P and encryption traffic may become a problem. Support Vector Machine (SVM) is a useful classification tool which is able to overcome the traditional bottleneck. The main disadvantage of SVM algorithms is that it`s time-consuming to train large data set because of the quadratic programming (QP) problem. However, the useful support vectors are only a small part of the whole data. If we can discard the useless vectors before training, we are able to save time and keep accuracy. In this article, we discussed the feasibility to remove the useless vectors through a sequential method to accelerate training speed when dealing with large scale data.
Patient-reported experiences with hospitals: comparison of proxy and patient scores using propensity-score matching.

OBJECTIVE The objective of this study was to compare patient-experience scores between patients with a proxy response and without a proxy response, using propensity-score matching to maximize the comparability between these two groups. DESIGN Cross-sectional survey. SETTING Hospital inpatient services in Norway. PARTICIPANTS Patients were randomly selected from each of the 61 hospitals in Norway during spring 2011. Postal questionnaires were mailed to 23 420 patients after their discharge from hospital. INTERVENTION No intervention. MAIN OUTCOME MEASURES All of the patient respondents (n = 8744) and the matched cases (n = 734) were compared with patients with a proxy response (n = 734) on 12 patient-experience indicators using t-tests. RESULTS Compared with patient respondents, patients with a proxy response had poorer health, were older and were more often discharged from the hospital to another health-care institution (P < 0.001). Patients with a proxy response yielded significantly lower patient-experience scores than those without a proxy response for 9 of the 12 indicators. Compared with the matched patient group, patients with a proxy response had significantly lower scores for 3 of the 12 indicators and a significantly higher score for one indicator. Differences in scores between patients with a proxy response and the matched patient sample were small, with the largest difference being 4 on a scale of 0-100. CONCLUSIONS Patients with a proxy response report somewhat poorer experiences than those without a proxy response; however, proxies represent a different patient group than the patient group as a whole, and the results were very similar after controlling for these differences.
GPU Computation for Online Realtime Multi-Pattern Matching

Most applications of traditional full-text search, e.g., webpage search, are offline which exploit text search engine to preview the texts and set up related index. However, applications of online realtime full-text search, e.g., network Intrusion detection and prevention systems (IDPS) are too hard to implementation by using commodity hardware. They are expensive and inflexible for more and more occurrences of new virus patterns and the text cannot be previewed and the search must be complete realtime online. Additionally, IDPS needs multi-pattern matching, and then malicious packets can be removed immediately from normal ones without degrading the network performance. Considering the problem of realtime multi-pattern matching, we implement two sequential algorithms, Wu-Manber and Aho-Corasick, respectively over GPU parallel computation platform. Both pattern matching algorithms are quite suitable for the cases with a large amount of patterns. In addition, they are also easier extendable over GPU parallel computation platform to satisfy realtime requirement. Our experimental results show that the throughput of GPU implementation is about five to seven times faster than CPU. Therefore, pattern matching over GPU offers an attractive solution of IDPS to speed up malicious packets detection among the normal traffic by considering the lower cost, easy expansion and better performance.