Miracle-dz/UniFAR-FTUs huggingface dataset:
Software Simulation of a Self-Organizing Learning Array System

A neural network paradigm named Self-Organizing Learning Array system has been simulated in software. Hardware implementation limitations are considered in this simulation. Simulation is performed based on a benchmark classification problem, the Australian Credit Card problem. The system behavior is observed and the learning algorithm is examined. The correct classification rate has been compared with some existing classification methods. Although not particularly designed for solving this type of classification problem, this system still shows very good performance. The system will be implemented in FPGA and SOC.
Optimal control of switched autonomous linear systems

The paper deals with the optimal control of switched piecewise linear autonomous systems, where the objective is that of minimizing a quadratic performance index over an infinite time horizon. We assume that the switching sequence and the corresponding jump matrix sequence is known, while the unknown switching times are the optimization parameters. The optimal control for this class of systems, assuming a switching sequence of finite length, takes the form of a homogeneous state feedback, i.e., it is possible to identify a homogeneous region of the state space such that an optimal switch should occur if and only if the present state belongs to this region. We show how such a region can be computed with a numerical procedure. As the number of allowed switches goes to infinity, we study the stability of the system and discuss some preliminary results related to the convergence of the state feedback law.
Security Token and Its Derivative in Discrete-Time Models

Aiming at modeling uncertain digital materials in the network society, we de ne the security token, which is abbreviated into a word coinage setok. Each setok has its explicit price, explicit values, and timestamp on it as well as the main contents. The values are uncertain and may cause risks. Several important properties of the setok are de ned. Then, in order to provide risk-hedging opportunities, a derivative written not on the price but on the value is introduced. The derivative investigated is a simple Europeantype call option. We derive option-pricing formulae in a single-period model and in a multiple-period model. These formulae do not require any divisibility of the underlying setok.
An Efficient Approximation for Refining Organ Geographic Distribution in the U.S. Liver Transplantation and Allocation System

Liver transplantation and allocation has been a contentious issue in the United States for decades. Two main challenges in achieving efficient sharing are 1) significant geographic imbalance between donor supply and patient demand, and 2) rapid quality decay of livers. At present, when deciding which immunologically compatible patients should be given higher priorities for donor livers, priorities are given to local patients first, then patients in nearby areas of the procurement site (region), and finally remaining patients from the entire nation. The allowance of allocating livers in nearby areas before making them available to the entire nation ensures that good candidates can receive high-quality liver transplants. In this paper, we present a deterministic sequential matching model to evaluate the impact of allocation region design. We show that the developed model is a good approximation to the real system and it facilitates the numerical analysis of liver geographic distribution. We make recommendations on how geographic configuration of the liver allocation system may be modified to improve post-transplant outcomes.
Optimal Packet Allocation with Airtime Constraint for Multi-Access Links

In next generation wireless networks, a variety of heterogeneous radio access technologies are expected to be available simultaneously within a single wireless terminal. This paper addresses the challenge of link aggregation in multi-access networks, where a key issue is how to optimally aggregate bandwidth offered by the individual radio link. Effective link throughput model is employed as a common resource measure for heterogeneous links. Based on the model, we present a packet allocation technique to optimize link aggregation. The mapping of packets to radio access links is performed to maximize the overall expected system throughput. Airtime constraint is added for an equal load balance. We have conducted extensive simulations with two scenarios. One is at the co-existence of WiMAX and WiFi, and the other includes only WiFi links. The proposed technique adaptively operates to time-varying link resource, and achieves better the aggregated link performance than WRR with fixed distribution ratio.
Experience With Fenestrated Endovascular Repair of Juxtarenal Abdominal Aortic Aneurysms at a Single Center

AbstractTo present the early and mid-term results of fenestrated endovascular aneurysm repair (FEVAR) using the Zenith fenestrated device for juxtarenal abdominal aortic aneurysms (JAAAs) at our center in China.Design: Retrospective study.The study included 15 male patients with JAAAs, who underwent FEVAR using the Zenith fenestrated device at our center between February 2011 and June 2015.All custom-made Zenith fenestrated devices were designed according to computed tomography angiography (CTA) images obtained preoperatively. The patients with renal insufficiency underwent duplex ultrasonography, while the patients with normal renal function underwent 3 CT data acquisitions including nonenhanced CT, arterial phase, and venous phase. These examinations and blood examinations were completed at 3, 6, and 12 months after discharge, and annually thereafter.The mean age of the patients was 73.13 ± 9.06 years (range, 57–86 years), and the median follow-up period was 30 months (8–52 months). Small fenestrations were used in 27 renal arteries, scallops were used in 7 superior mesenteric arteries (SMAs) and 2 renal arteries, and large fenestrations were used in 2 SMAs. Conversion to an open procedure was not required in any of the patients, and the technical success rate was 100%. The mean length of hospital stay was 11.33 ± 2.02 days (7–15 days). No patient died within the 1st 30 days after the operation. One patient had a type Ia endoleak, which disappeared at 6 months after the operation, 1 patient had a type Ib endoleak, which was detected at 17 months after the operation, and 2 patients had type II endoleaks. One patient died at 17 months and another patient died at 30 months after the operation. Therefore, the all-cause mortality rate was 13.33% (2/15). The target vessel patency rate was 100% without occlusion.The early and mid-term results of FEVAR using the Zenith fenestrated device were good, demonstrating that this procedure is effective for the treatment of JAAAs.
Dynamic and Adaptive Bandwidth Defragmentation in Spectrum-Sliced Elastic Optical Networks With Time-Varying Traffic

Elastic optical networks (EONs) enable network operators to have agile bandwidth management in the optical layer. In this paper, we investigate dynamic and adaptive bandwidth defragmentation (DF) in EONs with time-varying traffic using connection reconfigurations. We consider how to design DF procedure in a systematic way, and study the problems that have not been fully explored so far. Basically, we divide the procedure design into four subproblems: “How to reconfigure? ,” “ How to migrate traffic? ,” “When to reconfigure? ,” and “What to reconfigure? ,” and solve them sequentially. For “How to reconfigure? ,” we investigate the combination of routing and spectrum assignment (RSA) algorithms for DF, i.e., the RSA algorithm that the connections are originally served with and the algorithm that they are re-optimized with. For “ How to migrate traffic? ,” we propose to construct a dependency graph to represent the relations among the selected connections and to use it to assist the best-effort traffic migration. A move-to-vacancy method is also proposed to further reduce the traffic disruptions. For “When to reconfigure? ” and “ What to reconfigure? ,” we propose intelligent timing selection and adaptive DF ratio selection methods to tackle the tradeoff between the bandwidth blocking probability (BBP) performance and operational complexity. Simulation results show that the algorithm with both methods implemented (DF-AT-AR) achieves better tradeoff between BBP performance and operational complexity, when compared with existing algorithms.
Digital Image Stabilization for Cameras on Moving Platform

Digital image stabilization is an important technique including three parts: global motion estimation, motion filtering and motion compensation. To ensure the visual quality of the whole video, the accuracy of global motion estimation and smooth motion vectors over long images sequence are emphasized. In this paper, we propose a novel stabilization algorithm based on particle filtering. Firstly, Harris point detection is improved by grid sampling to select evenly distributed points. The points are initially matched by feature window matching and further validated by distance criterion to get global motion matrix. Then particle filter is employed to obtain smooth scanning motion vector from original motion curves. The performance of the proposed algorithm is demonstrated through computer simulated experiments. It is shown experimentally that particle filtering can reduce the error variance compared to Kalman filtering.
Where Are the Niches? Dynamic Fitness Sharing

The problem of locating all the optima within a multimodal fitness landscape has been widely addressed in evolutionary computation, and many solutions, based on a large variety of different techniques, have been proposed in the literature. Among them, fitness sharing (FS) is probably the best known and the most widely used. The main criticisms to FS concern both the lack of an explicit mechanism for identifying or providing any information about the location of the peaks in the fitness landscape, and the definition of species implicitly assumed by FS. We present a mechanism of FS, i.e., dynamic fitness sharing, which has been devised in order to overcome these limitations. The proposed method allows an explicit, dynamic identification of the species discovered at each generation, their localization on the fitness landscape, the application of the sharing mechanism to each species separately, and a species elitist strategy. The proposed method has been tested on a set of standard functions largely adopted in the literature to assess the performance of evolutionary algorithms on multimodal functions. Experimental results confirm that our method performs significantly better than FS and other methods proposed in the literature without requiring any further assumption on the fitness landscape than those assumed by the FS itself.
KDE Paring and a Faster Mean Shift Algorithm

The kernel density estimate (KDE) is a nonparametric density estimate which has broad application in computer vision and pattern recognition. In particular, the mean shift procedure uses the KDE structure to cluster or segment data, including images and video. The usefulness of these twin techniques—KDE and mean shift—on large data sets is hampered by the large space or description complexity of the KDE, which in turn leads to a large time complexity of the mean shift procedure that is superlinear in the number of points. In this paper, we propose a sampling technique for KDE paring, i.e., the construction of a compactly represented KDE with much smaller description complexity. We prove that this technique has good properties in that the pared-down KDE so constructed is close to the original KDE in a precise mathematical sense. We then show how to use this pared-down KDE to devise a considerably faster mean shift algorithm, whose time complexity we analyze formally. Experiments show that image and video segmentation results of the proposed fast mean shift method are similar to those based on the standard mean shift procedure, with the typical speed-up several orders of magnitude for large data sets. Finally, we present an application of the fast mean shift method to the efficient construction of multiscale graph structures for images, which can be used as a preprocessing step for more sophisticated segmentation algorithms.
Exchange of Indivisible Objects with Asymmetry

In this paper we study the exchange of indivisible objects where agents' possible preferences over the objects are strict and share a common structure among all of them, which represents a certain level of asymmetry among objects. A typical example of such an exchange model is a re-scheduling of tasks over several processors, since all task owners are naturally assumed to prefer that their tasks are assigned to fast processors rather than slow ones. We focus on designing exchange rules (a.k.a. mechanisms) that simultaneously satisfy strategy-proofness, individual rationality, and Pareto efficiency. We first provide a general impossibility result for agents' preferences that are determined in an additive manner, and then show an existence of such an exchange rule for further restricted lexicographic preferences. We finally find that for the restricted case, a previously known equivalence between the single-valuedness of the strict core and the existence of such an exchange rule does not carry over.
Using JITT in a database course

This paper describes our experience using the Just-in-Time Teaching (JiTT) technique in an undergraduate database course for computer science majors during two semesters. JiTT was implemented by giving the students reading assignments and asking them to complete web-based reading tests the day before class, so that the teacher could detect weaknesses in students' understanding of the material and adjust the lesson plan just in time for the next day class. Based on surveys as well as on exams and course grades, we found a significant improvement on the students' interest in the course and learning of the material.
An internally and externally validated prognostic score for metastatic breast cancer: analysis of 2269 patients.

BACKGROUND The prognosis of metastatic breast cancer (MBC) is extremely heterogeneous. Although patients with MBC will uniformly die to their disease, survival may range from a few months to several years. This underscores the importance of defining prognostic factors to develop risk-adopted treatment strategies. Our aim has been to use simple measures to judge a patient's prognosis when metastatic disease is diagnosed. PATIENTS AND METHODS We retrospectively analyzed 2269 patients from four clinical cancer registries. The prognostic score was calculated from the regression coefficients found in the Cox regression analysis. Based on the score, patients were classified into high-, intermediate-, and low-risk groups. Bootstrapping and time-dependent receiver operating characteristic curves were used for internal validation. Two independent datasets were used for external validation. RESULTS Metastatic-free interval, localization of metastases, and hormone receptor status were identified as significant prognostic factors in the multivariate analysis. The three prognostic groups showed highly significant differences regarding overall survival from the time of metastasis [intermediate compared with low risk: hazard ratio (HR) 1.76, 95% confidence interval (CI) 1.36-2.27, P < 0.001; high compared with low risk: HR 3.54, 95% CI 2.81-4.45, P < 0.001). The median overall survival in these three groups were 61, 38, and 22 months, respectively. The external validation showed congruent results. CONCLUSIONS We developed a prognostic score, based on routine parameters easily accessible in daily clinical care. Although major progress has been made, the optimal therapeutic management of the individual patient is still unknown. Besides elaborative molecular classification of tumors, simple clinical measures such as our model may be helpful to further individualize optimal breast cancer care.
Enhancing testability of system on chips using network management protocols

This paper shows how to adapt the P1500 design-for-test standard through network management protocols to make the testing problem of system-on-chips (SoCs) easier and cost-effective. For this purpose, a SoC is analyzed as a distributed system in which its own basic components or IP cores (intellectual properties) are considered as network agents according to SNMP (simple network management protocol) protocol. An experimental study was carried out to show the effectiveness of such an approach.
Improved cascaded delta-sigma architecture with high signal to noise ratio and reduced distortion

An architecture of cascaded delta-sigma modulator is presented. It attains a significant improvement in achievable SNR, dynamic range and has the additional advantage of reduced sensitivity to switch and op-amp nonlinearities. The design consists of approximating quantizer-gain by functional simulation of the modulator and then keeping this value in view while conceiving digital filters. Digital filters designed this way are more efficient in cancelling quantization error and provide better results. This architecture can be used at low oversampling ratios for wideband applications, as well as for high-resolution audio applications.
Site-directed Mutagenesis of the Rat ml Muscarinic Acetylcholine Receptor

An electromagnetically actuatable valve, in particular a fuel injection valve for fuel injection systems, which serves to supply fuel to internal combustion engines. The fuel injection valve comprises a valve chamber and a core upon which a magnet coil is wound by use of a carrier body. A flat armature is constructed in such a manner at its side facing core that it partially overlaps the front surface of a ferromagnetic valve chamber with its outer range of action so that the magnet circuit is guided to the flat armature via valve chamber and the front face and so that magnetic coil, when actuated, simultaneously serves as a detent for the flat armature.
Black rings in (Anti)-de Sitter space

We construct solutions for thin black rings in Anti-deSitter and deSitter spacetimes using approximate methods. Black rings in AdS exist with arbitrarily large radius and satisfy a bound |J| ≤ LM, which they saturate as their radius becomes infinitely large. For angular momentum near the maximum, they have larger area than rotating AdS black holes. Thin black rings also exist in deSitter space, with rotation velocities varying between zero and a maximum, and with a radius that is always strictly below the Hubble radius. Our general analysis allows us to include black Saturns as well, which we discuss briefly. We present a simple physical argument why supersymmetric AdS black rings must not be expected: they do not possess the necessary pressure to balance the AdS potential. We discuss the possible existence or absence of `large AdS black rings' and their implications for a dual hydrodynamic description. An analysis of the physical properties of rotating AdS black holes is also included.
The effects of 2012 tuition fee reform on choices made by further education students contemplating participation in higher education : a case study

This study examines the educational choices made by some of the first cohort of further education students at an art college to face fees of up to £9,000 per annum for higher education study. Focusing on lower socio-economic status students, potentially most easily deterred by increased fees and debt, it explores the influences on their decisionmaking and considers the adequacy of the theoretical models underpinning their choice processes. It is a case study essentially concerned with why students make the choices that they do, what processes are involved and what influences shape student choice. The study was undertaken in the case study college – which delivers undergraduate programmes of study – partly as a result of the potential impact on the college of reduced FE to HE progression. Semi-structured individual interviews were conducted with 16 students on three occasions during the 2011-12 academic year, to coincide with particular points during their decision-making process. An interpretivist paradigm was adopted as the literature shows that many aspects of higher education choice relate to socially constructed realities which could only become fully apparent during qualitative inquiry, with a close relationship between the researcher and what is studied. The study found that students were not deterred unduly by the prospect of increased tuition fee debt on graduation, but that their choices of where to study were strongly influenced by concerns about living costs whilst studying and other considerations such as proximity to home that are already documented in the literature on higher education choice, largely from the theoretical perspective set out by Pierre Bourdieu (1974). The need for ontological security (Giddens, 1991) was clearly evident in many participants’ comments and was a strong underlying theme. Fieldwork demonstrated that at the point of decision-making, actors sought to make pragmatically rational decisions, within limits conditioned by their social capital, and therefore argues for a two-stage model of decision-making similar to that espoused by Raymond Boudon (1974). Glaesser and Cooper (2014) have argued convincingly for a combination of Bourdieu and Boudon’s work in this manner. Whilst this has merit, this thesis notes Hodkinson’s (2008) concerns regarding the explanatory capability of existing theoretical models in simultaneously addressing key aspects of HE choice at both macro and micro levels, rather than merely severally. It argues that at a micro level Herbert Simon’s 1957 model of bounded rationality best explains decision–making, and uniquely that the boundaries of actors’ choices are limited by their habitus. It concludes that actors’ boundedly-rational decisions and levels of satisficing are conditioned by their habitus, such that higher education choice is best characterised as ‘conditioned bounded rationality’.
Face Recognition using DCT - DWT Interleaved Coefficient Vectors with NN and SVM Classifier

---------------------------------------------------------------Abstract------------------------------------------------------------Face recognition applications are continuously gaining demands because of their requirements person authentication, access control and surveillance systems. The researchers are continuously working for making the system more accurate and faster in the part of that research this paper presents a face recognition system which uses DWT, DCT interleaved component for feature vector formation & tested the Support Vector Machine and ANN for classification. Finally the proposed technique is implemented and comprehensively analyzes to test its efficiency we also compared these two classification method.