Ordered Subsets Research Articles

The diagnostics of diabetes mellitus based on ensemble modeling and hair/urine element level analysis

The aim of the present work focuses on exploring the feasibility of analyzing the relationship between diabetes mellitus and several element levels in hair/urine specimens by chemometrics. A dataset involving 211 specimens and eight element concentrations was used. The control group was divided into three age subsets in order to analyze the influence of age. It was found that the most obvious difference was the effect of age on the level of zinc and iron. The decline of iron concentration with age in hair was exactly consistent with the opposite trend in urine. Principal component analysis (PCA) was used as a tool for a preliminary evaluation of the data. Both ensemble and single support vector machine (SVM) algorithms were used as the classification tools. On average, the accuracy, sensitivity and specificity of ensemble SVM models were 99%, 100%, 99% and 97%, 89%, 99% for hair and urine samples, respectively. The findings indicate that hair samples are superior to urine samples. Even so, it can provide more valuable information for prevention, diagnostics, treatment and research of diabetes by simultaneously analyzing the hair and urine samples.

A structured filter for Markovian switching systems

In this work, a new methodology for the structuring of multiple model estimation schemas is developed. The proposed filter is applied to the estimation and detection of active mode in dynamic systems. The discrete-time Markovian switching systems represented by several linear models, associated with a particular operating mode, are studied. Therefore, the main idea of this work is the subdivision of the models set to some subsets in order to improve the detection and estimation performances. Each subset is associated with sub-estimators based on models of the subset. In order to compute the global estimate and subset probabilities, a global estimator is proposed. Theoretical developments based on a hierarchical decision, leading to more efficiency in detection and state estimation, are proposed. Naturally, these results can be used for fault detection and isolation, using the activation probabilities of operating modes. These results are applied to detect switches in the centre of gravity for vehicle roll dynamics.

On Ranking of Intuitionistic Fuzzy Values Based on Dominance Relations

For intuitionistic fuzzy values (IFVs), there are more or less some drawbacks in the existing comparison methods, so it is necessary for us to develop a more proper technique for comparing or ranking IFVs in this paper. To do so, we first formalize an IFV as a fuzzy subset in order to analyze the fuzzy meaning of an IFV, and then according to the basic properties of the fuzzy subset, we determine the dominance relation (order relation) between two IFVs by defining a dominance degree. In order to explain the feasibility of the dominance relations, we validate the monotonicity of intuitionistic fuzzy operational laws, and additionally, we improve and prove the monotonicity of several intuitionistic fuzzy aggregation operators on the basis of the dominance relations. Because it is of importance for some practical problems (e.g., intuitionistic fuzzy multi-attribute decision making) to rank IFVs, we finally develop a method for ranking IFVs by constructing a dominance matrix based on the dominance degrees. A simple example is taken to illustrate the validity of our ranking method.

Evaluation of list-mode ordered subset expectation maximization image reconstruction for pixelated solid-state compton gamma camera with large number of channels

The Voxel Imaging PET (VIP) Pathfinder project intends to show the advantages of using pixelated solid-state technology for nuclear medicine applications. It proposes designs for Positron Emission Tomography (PET), Positron Emission Mammography (PEM) and Compton gamma camera detectors with a large number of signal channels (of the order of 106). For Compton camera, especially with a large number of readout channels, image reconstruction presents a big challenge. In this work, results are presented for the List-Mode Ordered Subset Expectation Maximization (LM-OSEM) image reconstruction algorithm on simulated data with the VIP Compton camera design. For the simulation, all realistic contributions to the spatial resolution are taken into account, including the Doppler broadening effect. The results show that even with a straightforward implementation of LM-OSEM, good images can be obtained for the proposed Compton camera design. Results are shown for various phantoms, including extended sources and with a distance between the field of view and the first detector plane equal to 100 mm which corresponds to a realistic nuclear medicine environment.

STATIC VERSUS DYNAMIC DEA IN FEDERAL HIGHER EDUCATION INSTITUTIONS - IFES

The present study aims to analyze intertemporal changes in productivity at Federal Higher Education Institutions (IFES) from 2004 to 2008. It examines efficient frontiers from each year using slacks-based (SBM-DEA) and dynamic slacks-based measures (DSBM) for data envelopment analysis (DEA). The total set of IFES was divided into two subsets (group A and group B) in order to minimize heterogeneity in the sector. Estimation results show that static frontiers for both groups underestimate the institution efficiency during the study period, indicating that intertemporal frontiers are more accurate when calculating efficiency since they consider a variable link between the inputs and outputs intertemporally.

On Finite Groups with Perfect Subgroup Order Subsets

Anite group G is said to be a PSOS-group if for every subgroup H of G the cardinality of the set fK GjjKj =jHjg divides jGj. In this note a rst step in the study of PSOSgroups is made.

Myocardial Defect Detection Using PET-CT: Phantom Studies

It is expected that both noise and activity distribution can have impact on the detectability of a myocardial defect in a cardiac PET study. In this work, we performed phantom studies to investigate the detectability of a defect in the myocardium for different noise levels and activity distributions. We evaluated the performance of three reconstruction schemes: Filtered Back-Projection (FBP), Ordinary Poisson Ordered Subset Expectation Maximization (OP–OSEM), and Point Spread Function corrected OSEM (PSF–OSEM). We used the Channelized Hotelling Observer (CHO) for the task of myocardial defect detection. We found that the detectability of a myocardial defect is almost entirely dependent on the noise level and the contrast between the defect and its surroundings.

Aspect-oriented RTL HW design using SystemC

With the increasing complexity of digital hardware designs, hardware description languages are being pushed to higher levels of abstraction, thus allowing for the use of design artifacts which were previously exclusive to the software domain. In this paper we aim to contribute to this scenario by proposing artifacts and guidelines for hardware design at the register transfer level using object-oriented and aspect-oriented programming concepts. Our methodology is based on features provided by SystemC, a C++-based hardware description language, and leverages on its synthesizable subset in order to produce designs suitable for circuit synthesis. Our experimental results show that the introduction of aspect-oriented design artifacts results in an increased level of flexibility and reusability while yielding a circuit area overhead of only 2.5% when compared to non-aspect-oriented designs.

Optimizing Wait States in the Synthesis of Memory References with Unpredictable Latencies

We consider the problem of synthesizing circuits (from C to Verilog) that are optimized to handle unpredictable latencies of memory operations. Unpredictable memory latencies can occur due to the use of on chip caches, DRAM memory modules, buffers/queues, or multiport memories. Typically, high-level synthesis compilers assume fixed and known memory latencies, and thus are able to schedule the code’s operations efficiently. The operations in the source code are scheduled into states of a state machine whose states will be synthesized to Verilog. The goal is to minimize scheduling length by maximizing the number of operations (and in particular memory operations) that are executed in parallel at the same state. However, with unpredictable latencies, there can be an exponential number of possible orders in which these parallel memory operations can terminate. Thus, in order to minimize the scheduling, we need a different schedule for any such order. This is not practical, and we show a technique of synthesizing a compact state machine that schedules only a small subset of these possible termination orders. Our results show that this compact state machine can improve the execution time compared to a regular scheduling that waits for the termination of all the active memory references in every state.

Acceleration of the EM-like reconstruction method for diffuse optical tomography with ordered-subsets method

Abstract. Diffuse optical tomography (DOT) is an optical imaging modality, which provides the spatial distribution of the optical parameters inside a random medium. A propagation back-propagation method named EM-like reconstruction method for stationary DOT problem has been proposed yet. This method is really time consuming. Hence the ordered-subsets (OS) technique for this reconstruction method is studied in this paper. The boundary measurements of DOT are grouped into nonoverlapping and overlapping ordered sequence of subsets with random partition, sequential partition and periodic partition, respectively. The performance of OS methods is compared with the standard EM-like reconstruction method with two-dimensional and three-dimensional numerical experiments. The numerical experiments indicate that reconstruction of nonoverlapping subsets with periodic partition, overlapping subsets with periodic partition and standard EM-like method provide very similar acceptable reconstruction results. However, reconstruction of nonoverlapping subsets with periodic partition spends a minimum of time to get proper results.

Order acceptance and due-date quotation in low machine rates

In real manufacturing environments, some customer orders include multiple jobs. However, a single due-date should be assigned to each order. Further, machine processing rate is not constant at all times. In effect, in many manufacturing operations, the machine processing rate decreases to a subnormal level during time and needs a special type of maintenance to bring the normal state back. Due to this reduction in capacity, production schedulers may decide to reject some orders. In this paper, the novel extensive problem of selecting a subset of orders, assigning due-dates to selected orders, scheduling the selected orders and jobs within each one, and scheduling the rate-modifying maintenance is studied. The objective function is minimizing total cost of lost-sales of rejected orders together with due-date length and maximum of earliness and tardiness of selected orders. The problem is proved polynomial and an optimal approach is developed.

High quality ordered subset expectation maximization reconstruction algorithm based on multi-resolution for PET images

In Positron Emission Tomography(PET) imaging,Maximum Likelihood Expectation Maximization(MLEM) algorithm cannot be directly applied to clinical diagnosis due to suppressing noise ineffectively and converging slowly.Although Ordered Subset Expectation Maximization(OSEM) algorithm converges fast,it will lead to a significant decline in the quality of the reconstructed image.To address this problem,multi-resolution technology was introduced into the subset of the OSEM reconstruction algorithm to suppress noise and stabilize solving process.The experimental results indicate that the new algorithm overcomes the drawback of the traditional algorithm on degrading the reconstructed image and has the advantage of fast convergence.The proposed reconstruction algorithm can obtain a higher Signal-to-Noise Ratio(SNR) and a superior visual effect.

Radio interferometric calibration via ordered-subsets algorithms: OS–LS and OS–SAGE calibrations

The main objective of this work is to accelerate the Maximum-Likelihood (ML) estimation procedure in radio interferometric calibration. We introduce the OS-LS and the OS-SAGE radio interferometric calibration methods, as a combination of the Ordered-Subsets (OS) method with the Least-Squares (LS) and Space Alternating Generalized Expectation maximization (SAGE) calibration techniques, respectively. The OS algorithm speeds up the ML estimation and achieves nearly the same level of accuracy of solutions as the one obtained by the non-OS methods. We apply the OS-LS and OS-SAGE calibration methods to simulated observations and show that these methods have a much higher convergence rate relative to the conventional LS and SAGE techniques. Moreover, the obtained results show that the OS-SAGE calibration technique has a superior performance compared to the OS-LS calibration method in the sense of achieving more accurate results while having significantly less computational cost.

The perfect order subset conjecture for simple groups

This paper verifies the Perfect Order Subset Conjecture for Simple Groups for all but one family of finite simple groups. Specifically, for each nonabelian finite simple group G there is some N such that the cardinality of the nonempty subset of all elements of order N in G does not divide the order of G, unless G is an orthogonal group of plus type in dimension 4n, for some n⩾2.

Accelerating ordered subsets image reconstruction for X-ray CT using spatially nonuniform optimization transfer.

Statistical image reconstruction algorithms in X-ray computed tomography (CT) provide improved image quality for reduced dose levels but require substantial computation time. Iterative algorithms that converge in few iterations and that are amenable to massive parallelization are favorable in multiprocessor implementations. The separable quadratic surrogate (SQS) algorithm is desirable as it is simple and updates all voxels simultaneously. However, the standard SQS algorithm requires many iterations to converge. This paper proposes an extension of the SQS algorithm that leads to spatially nonuniform updates. The nonuniform (NU) SQS encourages larger step sizes for the voxels that are expected to change more between the current and the final image, accelerating convergence, while the derivation of NU-SQS guarantees monotonic descent. Ordered subsets (OS) algorithms can also accelerate SQS, provided suitable "subset balance" conditions hold. These conditions can fail in 3-D helical cone-beam CT due to incomplete sampling outside the axial region-of-interest (ROI). This paper proposes a modified OS algorithm that is more stable outside the ROI in helical CT. We use CT scans to demonstrate that the proposed NU-OS-SQS algorithm handles the helical geometry better than the conventional OS methods and "converges" in less than half the time of ordinary OS-SQS.

Specifications of a continual reassessment method design for phase I trials of combined drugs

In studies of combinations of agents in phase I oncology trials, the dose-toxicity relationship may not be monotone for all combinations, in which case the toxicity probabilities follow a partial order. The continual reassessment method for partial orders (PO-CRM) is a design for phase I trials of combinations that leans upon identifying possible complete orders associated with the partial order. This article addresses some practical design considerations not previously undertaken when describing the PO-CRM. We describe an approach in choosing a proper subset of possible orderings, formulated according to the known toxicity relationships within a matrix of combination therapies. Other design issues, such as working model selection and stopping rules, are also discussed. We demonstrate the practical ability of PO-CRM as a phase I design for combinations through its use in a recent trial designed at the University of Virginia Cancer Center.

Parameter optimization of relaxed Ordered Subsets Pre-computed Back Projection (BP) based Penalized-Likelihood (OS-PPL) reconstruction in limited-angle X-ray tomography

This paper presents a two-step strategy to provide a quality-predictable image reconstruction. A Pre-computed Back Projection based Penalized-Likelihood (PPL) method is proposed in the strategy to generate consistent image quality. To solve PPL efficiently, relaxed Ordered Subsets (OS) is applied. A training sets based evaluation is performed to quantify the effect of the undetermined parameters in OS, which lets the results as consistent as possible with the theoretical one.

Automatic Passenger Detection in Safety Critical Mass Transit Environments

Enhancing user safety constitutes a major issue in railway transport. In this paper, a novel solution for detection and identification of objects falling on railway tracks is proposed. This solution is based on a system using a set of consecutive ultra wideband (UWB) monostatic radars fed by a common transmission line. The main objective of this work is to study the different radiofrequency and signal processing subsets in order to evaluate and validate the full system. A slotted waveguide operating in its fundamental mode is used as the common transmission line. Slots are periodically perforated in the waveguide to constitute the radars. An optimal bandwidth and constant radiation coverage along the track are then optimized. The singularity Expansion Method (SEM) is used to characterize the objects falling on railway tracks. Complex Natural Resonances are then computed or measured and stored in a library. They are used in a specific discrimination process. Using both numerical simulations and experimental results, the discrimination process shows that human bodies are well detected and distinguished as well as other objects typically found on platform (suitcases, bottles…).

T cell depletion in paediatric stem cell transplantation

Haematopoietic stem cell transplantation (HSCT) can be a curative procedure for a growing number of paediatric diseases, but as the indications for HSCT grow, so does the need to find suitable stem cell donors. When the preferred option of a genoidentical sibling donor is not available alternative donors, including unrelated adult or umbilical cord blood donors, or haploidentical related donors may be considered. Outcome following alternative donor HSCT has improved over the past 20 years but graft-versus-host disease (GvHD) remains a significant obstacle. T cell depletion (TCD) for non-genoidentical grafts aims to reduce the morbidity and mortality associated with GvHD, but this intervention has not led directly to improved survival due to delayed immune reconstitution and increased infections, graft rejection and increased rates of disease relapse. Limited data from the paediatric population, however, suggest some encouraging results for children undergoing haploidentical HSCT: a move from positive selection of CD34(+) haematopoietic stem cells towards negative depletion of specific cell subsets in order to retain useful accessory cells within the graft appears to enhance immune reconstitution and improve disease-free survival. Here we review recent paediatric outcome data for T cell-depleted HSCT, explore the role of serotherapy in conditioning regimens and look at future possibilities to improve outcome, including novel allodepletion techniques, suicide gene therapy and pathogen-specific immunotherapy.

Assessing the impact of mobile technology on order verification during pharmacist participation in patient rounds

Pharmacists' use of mobile technology (MT) to verify medication orders placed during their participation in medical rounds is investigated. A retrospective observational study was conducted at a large academic medical center to assess the impact of MT on the average time to pharmacist verification of medication orders written by general medicine staff during pharmacist participation in patient rounds. A total of 260 medication orders for 129 patients were evaluated: 146 orders processed over a one-month period during which rounding pharmacists verified orders using stationary computer terminals on patient care units and 114 orders processed using an MT device. The primary endpoint was the average time to pharmacist verification for all medication orders; average verification times for orders for specific medication classes (analgesics, antibiotics, antidiabetes drugs, and antihypertensives) were also evaluated. Overall, the average time to order verification was significantly lower with the use of the MT device compared with non-MT-assisted order verification (7.5 minutes versus 38.9 minutes, p < 0.001), with significant (p < 0.001) time benefits favoring MT-assisted verification for all order subsets within the evaluated medication classes. Challenges posed by the use of MT-assisted order verification included the selected device's relatively small keyboard and the frequent loss of network connections as the pharmacist moved from floor to floor within the hospital. Clinical pharmacists' use of an MT device to verify medication orders written during patient care rounds can significantly decrease the average time required for order verification relative to the use of stationary computer terminals.