Miracle-dz/UniFAR-FTUs huggingface dataset:
REDUCTION OF A KINETIC MODEL OF ACTIVE EXPORT OF IMPORTINS

We study a kinetic model of active export of importins. The kinetic model is written as a system of ordinary differential equations. We developed some model reduction techniques to simplify the system. The techniques are: removal of very slow reactions, quasi-steady state approximation and simplification of kinetic equations based on stoichiometric conservation laws. Local sensitivity analysis is used for the identification of critical model parameters. After model reduction, the numbers of reactions and species are reduced from $28$ and $29$ to $20$ and $20$, respectively. The reduced model and original model are compared in numerical simulations using SBedit tools for Matlab, and the methods of further model reduction are discussed. Interestingly, we investigate an iterative algorithm based on the Duhamel iterates to calculate the analytical approximate solutions of the complex non--linear chemical kinetics. This technique plays as an explicit formula that can be studied in detail for wide regions of concentrations for optimization and parameter identification purposes. It seems that the third iterative solution of the suggested method is significantly close to the actual solution of the kinetic models in most cases.
Advanced Microcomputer Simulation for Construction Managers

The concept of simulation allows the analysis of complex and dynamic systems such as those encountered in construction operations. In particular, the technology orientation of construction operations in the field is continually undergoing change. This means that until recently intuitive approaches were the only way to deal with the multi-faceted nature of field construction processes. As computers have become smaller and more mobile, the analytic power of these machines has become more accessible to field engineers and managers. This paper discusses the structure of the CYCLONE concept for construction operation simulation and introduces an extended version of the MicroCYCLONE program. Data bases, standardized construction process networks, sensitivity analysis and interactive graphics enhance the user-friendliness of MicroCYCLONE.
The Effects of Multispecialty Group Practice on Health Care Spending and Use

U.S. physicians are increasingly joining multispecialty group practices. In this paper, we analyze how a primary care physician’s practice type – single (SSP) versus multispecialty practice (MSP) – affects health care spending and use. Focusing on Medicare beneficiaries who change their primary care physician due to a geographic move, we compare changes in practice patterns before and after the move between patients who switch practice types and those who do not. We use instrumental variables to address potential selection by patients into practice types after the move. We find that changing from a single to a multi-specialty primary care group practice decreases annual Medicare-financed per capita expenditures by about $1,600 - a 28% reduction. The effect is driven primarily by changes in hospital expenditures and is concentrated among patients with two or more chronic conditions, suggesting that MSP improves care delivery by reducing hospitalizations among relatively sick patients. The results imply that, while research has shown the potential for physician consolidation to increase prices in some settings, large multispecialty groups also have the potential to lower costs.
Random walks for circuit clustering

The authors introduce a fast, parallelizable approach to circuit clustering based on analysis of random walks in the netlist. The method yields good clustering solutions for classes of 'difficult' inputs in the literature as well as for industry benchmark circuits. The authors characterize their results using a new clustering metric which facilitates comparison with future work. Extensions to a number of other CAD applications are proposed. <<ETX>>
Development and initial testing of a Health Confidence Score (HCS)

Introduction Patients need to feel confident about looking after their own health. This is needed to improve patient outcomes and clinical support. With few suitable tools available to measure self-care health confidence, we developed and validated a short, generic survey instrument for use in evaluation and quality improvement. Methods The Health Confidence Score (HCS) was developed through literature review, patient and expert focus groups and discussions. This paper reports an initial survey (n = 1031, study 1) which identified some issues and a further face-to-face survey (n = 378, study 2) to test the construct and concurrent validity of the final version. Scores were correlated against the My Health Confidence (MHC) rating scale, howRu (health status measure) and relevant demographics. Results The HCS is short (50 words) with good readability (reading age 8). It has four items covering health knowledge, capability to self-manage, access to help and shared decision-making; each has four response options (strongly agree, agree, neutral disagree). Items are reported independently and as a summary score. The mean summary score was 76.7 (SD 20.4) on 0–100 scale. Cronbach’s alpha = 0.82. Exploratory factor analysis suggested that the four items relate to a single dimension. Correlation of the HCS summary score with MHC was high (Spearman r = 0.76). It was also associated with health status (Spearman r = 0.49), negatively with number of medications taken (r=–0.29) and age (r=–0.22) and not with ethnicity, having children or education level. Conclusions The HCS is short, easy to use, with good psychometric properties and construct validity. Each item is meaningful independently and the summary score gives an overall picture of health confidence.
Cell average carrier-to-interference coverage improvement by using DSP interference rejection techniques

The performance of a cellular phone system can be evaluated from several perspectives, one of which is the capacity. The capacity of a cellular system can be described by the cell carrier-to-interference ratio coverage (or the percentage of a cell area in which the carrier-to-interference ratio (CIR) is greater than a specific threshold). A theoretical form of the cell carrier-to-interference ratio coverage is derived for both the forward and reverse links. The cell average CIR coverage is also compared to the cell worst case CIR coverage, where the mobile is at the edge of its serving cell but is at the location closest to its interfering cell. The analysis is used to show how the coverage and the capacity can be improved by incorporating digital signal processing (DSP) interference rejection techniques, such as a time-dependent adaptive filter (TDAF). Results indicate that the average CIR coverage can be increased from 90% to 98% for the seven cell reuse pattern assuming an 18 dB threshold. For a three cell frequency reuse pattern, the average CIR coverage is increased from 73% to 96% assuming the same threshold. The improvement is significant, even when a lower frequency reuse pattern is assumed. Thus, the TDAF improves the received signal quality and provides a means to increase the system capacity by using a lower frequency reuse pattern.
Study and Survey of Facilitating Document Annotation Using Content Value and Querying Value.

A many no of organization create and share descriptive and text data of their products, services these type of collection of text data included large amount of structured data, which is saved in unstructured data. extraction algorithms promote the extraction of structured data in costly and incorrect way exclusively when operating on top of data that is not contain any type of exponent of the targeted structure data. There are no of alternative approaches that promotes the creation of the structure metadata by analyzing document that are acceptable to contain information of interest and this type of information is behind useful for querying the database which is relies on the purpose that persons are more likely to add the metadata which is necessary during the generation time. Different types of algorithm that analyze structured attribute that are acceptable to arrive within the document, by jointly utilizing the content value of the text and also query workload.
Ecient Estimation of Variable Order Markov Chains

Variable order markov chains have been applied to a variety of problems in computational biology, from gene annotation to protein domain detection. Particularly, it showed good performance for classifying protein families represented by domains of Pfam. The order L of a markov chain determines the length of the context, that is, the L preceding letters which are taken into account to predict the next symbol. The general idea of variable order markov chains is to remove states from the fixed-order state space, which either cannot be reliably estimated or are redundant according to some estimation process. This estimation process acts recursively on the context comparing the gain in descriptive power for a context and its suffixes, like the context tree of Rissanen or the probabilistic suffix tree (PST)[3, 4]. We used enhanced suffix arrays to implement the linear-time and space algorithm of Apostolico and Bejerano for constructing a PST [1] and show that it is extremely fast in practice and up to three orders of magnitude faster than the previous implementation. The implementation is very general and can be used for model estimation with a variety of estimators, e.g. [3, 4]. Additionally, we consider the class of Parsimonious Markov Models [2], which is now described by ambiguous contexts, allowing for the grouping of characters at each position. Estimation of such models is computationally prohibitive, as it scales exponentially with the size of the alphabet. To tackle this problem we reduce the space of considered contexts according to the biochemical properties of amino acids. Finally, we conduct classification experiments assessing the performance of the various estimation methods.
Supply chain capabilities for facilitating the internationalisation of retailers – a multiple case study of three Swedish retail companies

ABSTRACT Market-oriented aspects of retail internationalisation have received a lot of research attention since the 1990s. However, beyond these aspects lies also supply-chain oriented capabilities that are necessary for retailers to successfully internationalise into foreign sales markets. By using a perspective based on resource-based theories, this paper explores supply-chain oriented capabilities that facilitate retail internationalisation. The research is based on a multiple case study of three Swedish retailers. Through the perspective of research based theories, specifically capabilities, the empirical data is studied in a single-case as well as a cross-case analysis. Findings reveal three supply chain-oriented capability categories (leadership capability, integration capability and learning capability) of importance for retail internationalisation. Resources necessary for the capabilities are to be found internally at the retailer, but also externally at other firms. This research adds to the market-oriented knowledge on retail internationalisation by adding a supply-chain oriented perspective. Further, it provides an understanding of the early phases of retail internationalisation.
INDOOR POSITIONING USING CONVOLUTION NEURAL NETWORK TO REGRESS CAMERA POSE

Abstract. In recent years, the issue of indoor positioning has become more and more popular and attracted more attention. Under the absence of GNSS, how to more accurately position is one of the challenges on the positioning technology. Camera positioning can be calculated by image and objects. Therefore, this study focuses on locating the user's camera position, but how to calculate the camera position efficiently is a very challenging problem. With the rapid development of neural network in image recognition, computer can not only process images quickly, but also achieve good results. Convolution Neural Network (CNN) can sense the local area of the image and find some high-resolution local features. These basic features are likely to form the basis of human vision and become an effective means to improve the recognition rate. We use a 23-layer convolutional neural network architecture and set different sizes of input images to train the end-to-end task of location recognition to regress the camera's position and direction. We choose the sites where are the underground parking lot for the experiment. Compared with other indoor environments such as chess, office and kitchen, the condition of this place is very severe. Therefore, how to design algorithms to train and exclude dynamic objects using neural networks is very exploratory. The experimental results show that our proposed solution can effectively reduce the error of indoor positioning.
PERFORMANCE OF GNSS CARRIER-TRACKING LOOP BASED ON KALMAN FILTER IN A CHALLENGING ENVIRONMENT

Abstract. The global navigation satellite system (GNSS) recently plays an extremely important role in positioning, navigation, and timing (PNT) applications for the modernized automations and mechanizations, e.g., unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), military aircrafts, etc. Nevertheless, GNSS signals are very vulnerable to the influence of various interferences when they are received on Earth, and the reason why it happens is that the long line-of-sight (LOS) distance between the satellite and the receiver user dramatically reduces the power strength after the signal reaches at the ground. The weak GNSS signal is hard to be handled with traditional phase lock loop (PLL), especially in a dynamic environment. Again, the trade-off among the coherent integration time of tracking loop, received signal power strength, and signal or user receiver dynamics is still a tough and remained problem to be solved. The Kalman filter (KF) is always a promising tool to efficiently decrease the random noise for the tracking process. In our work, we evaluate the performances of the tracking loop modelled with both standard KF and extended Kalman filter (EKF). An adaptive algorithm for the covariance matrix of the process noise is contained in our system to increase the tracking ability in a weak and dynamic environment. Besides, a noise channel is also contained to automatically adjust the priori measurement covariance for the KF tracking loop model. Simulation results demonstrate the performance with the proposed technique.
MAC and routing protocols for AD-HOC cognitive radio networks

Cognitive radio network is a new emerging research area recently. It enhances the existing software-defined radio [1], whose physical layer behaviour is largely defined in software. Cognitive radio has the following characteristics [2]. First, it is aware of its environment and its capabilities. Second, it is able to independently alter its physical layer behaviour based on its previous experience and its current environment. When spectrum environment changes around cognitive user, it is capable of sensing these changes and independently changing its physical layer settings such as transmission power, channel selection and etc to meet some constraints or QOS requirements of the users. In this paper, NS-2 is used to extend it to support cognitive radio network simulation with single radio multichannel and the improved MAC provides efficient spectrum utilisation. And the performance metric is evaluated using AODV routing protocol.
Basic blocks and traces for intermediate representation

The semantic analyses phase of a compiler must translate abstract syntax into abstract machine code. It can do this after type-checking, or at the same time. An intermediate representation is a kind of abstract machine language that can express the target-machine operations without committing to too much machine-specific details. But it is also independent of the details of the source language. The front-end of the compiler does lexical analysis, parsing, semantic analyses, and translation to intermediate representation. The back-end does optimization of the intermediate representation and translation to machine language.
Hands-on digital image processing

This effort presented is the integration of the Khoros 2 system, hypertext (HTML), and network browsers to produce an interactive digital image processing environment to enhance our ability to learn and work together across geographical, temporal, and cultural distances. The paper describes how this new type of course can impact teaching, learning, and research processes, and gives examples of how it is currently being used in several settings. The broad scope of the Khoros system and the communal emphasis on collaboration have contributed to this success. This new interactive toolbox/course is available free of charge via the Internet at http://www.khoros. unm.edu/dipcourse.
Performance of frequency-hopped NPCSMA for broad-band personal communication services (B-PCS) at millimeter waves in an urban mobile radio environment

A millimeter-wave (MMW) propagation model, based on multiray optical theory and the geometrical theory of diffraction (GTD), is used to statistically study the delay spread and coherence bandwidth (B/sub c/) for broad-band personal communication services (B-PCSs) in urban mobile radio environments. The results of the statistical model are compared with outdoor measurements near the street level with B/sub c/ varying over a range of frequencies (14-100 MHz). It is shown that the distribution of B/sub c/ depends on antenna heights, street layout, and frequency. The signal level statistics are evaluated and found to agree with the measurements. In general, these statistics are non-Rayleigh distributed. The additive thermal Gaussian noise (AGN) is calculated for such channels to evaluate the signal-to noise ratio (SNR). The performance of the medium-access control (MAC) sublayer is studied by first evaluating the probability of packet retransmission and then the performance of the FH-NPCSPMA protocol. The FH-NPCSMA protocol is the combination of frequency hopping spread spectrum (FH-SS) and nonpersistent carrier-sense multiple access (NPCSMA) that is proposed to improve the system throughput and average packet delay for both high traffic and multipath channels at MMW. The main advantage of the PH-NPCSMA protocol is to improve the performance over fading channels.
Applications of variational partial differential equation models in medical image processing

Images of various kinds are increasingly important to medical diagnostic processes. Difficult problems are encountered in selecting both the most appropriate image reconstruction methods and post-processing methods. Reconstruction methods involve producing optimal quality images from raw data. Post-processing methods involve acquiring the highest quality information from these images. Medical image processing (i.e., reconstruction and post processing) has created tremendous opportunities for mathematical modeling, analysis, and computation. I examined various applications of the variational partial differential equation (PDE) method. This method is one of the most recent and successful approaches to medical image processing. I worked on the following important medical image processing problems: clustering, denoising, segmentation, registration, tomography, inpainting, and field tracking. Novel PDE based models and corresponding numerical methods are introduced for each of these problems. We proposed an original framework for segmentation that may incorporate various forms of prior information. This information can include shape, key points, or intensity profiles. We also proposed the level set formulation and a numerical algorithm for the model. We proposed a novel inpainting model and applied it to magnetic resonance imaging (MRI). This novel inpainting model considers the automatic choice of diffusion type. A specific modification of this model for sensitivity maps was produced. We also introduced a new framework (the modified mumford-shad model by level set) for tomography problems with extremely noisy and limited data. This algorithm is flexible, it can be used for any geometry with or without prior information. This model is very easy to modify for various cases. Finally, we proposed a novel tracking algorithm. The proposed method solves multi-diffusion-direction and branch problems existing in fiber tracking. We applied those models on segmentation of ultrasound cardiac images, MRI brain images, noise tomography, inpainting of sensitivity maps for MRI surface coils, and fiber tracking. Experimental results and computational costs were compared with conventional methods.
Current Status of Bio-medical Imaging Technology and Method in China: A Review

Biomedical image processing is a new interdisciplinary field that combines mathematics, computer science, medical imaging and many other areas. It takes advantage of mathematical theory, and with the help of the recent highly-developed information technology, biomedical image processing technique is gaining much attention. The medical science relies much more heavily on medical images produced by different advanced equipment nowadays to acquire information in order to make accurate diagnosis and offer appropriate diagnosis. Since medical images can reflect the condition of a patient more directly, thus increasing the accuracy of diagnosis. It’s estimated that more than 70% of information is acquired through those images. And because of its importance, we focus our attention on medical image processing to gain a look of the development in
Social Comparison facilitates Value Exchange in Collaborative Scenario Generation

Chance Discovery has considered the two components of data analysis and collaborative scenario generation. The data analysis results in a graphical presentation, which is then used by members of an expert team to generate scenarios for decision making. Trust and the exchange of values have previously been identified as prerequisites for creative scenarios. The current study has addressed the question whether social comparison of group-induced self-esteem is the underlying mechanism for increasing trust and value exchange. Three software design groups have tackled the same design task. The two experimental groups were individually asked to increase and decreased self-esteem respectively by respectful or disrespectful treatment of the group members, whereas the members of the control group received no instructions. The result showed an increase in references to trust and value exchange if self-esteem was increased and a decrease with reduced self-esteem. This result is important for collaborative scenario generation because it clarifies the link between trust and value exchange in work groups.
Modeling thermal effects on MESFET I-V characteristics

In this paper a new thermal DC I-V empirical model of GaAs MESFETs is proposed. The model is rather simple, suitable for implementation in software for circuit simulations and allows to simulate very well both the internal thermal effects, due to heating of device, for dissipation of electrical power, and the external thermal effects, due to particular environmental temperatures. Moreover it is valid for different MESFET types. The agreement between simulated and measured curves obtained for MESFETs with different gate lengths is excellent, so that accuracy and usefulness of the proposed model are confirmed.
BAKAL A RSK A PR ACE

The work will provide students of the Economically Administrative Faculty of the University of Pardubice the manual that describes in the brief summary the technical instruments of the basic element of a personal computer. The range of the work comes out from the range of education in the subjects of the bachelor studies. The manual is completed with the informative wall posters that are placed in the rooms of the Institution of the Systemic Engineering and Informatics and with CD with the used photographs in higher resolution.