FollowMe: A Bigraphical Approach

In this paper we illustrate the use of modelling techniques using bigraphs to specify and refine elementary aspects of the FollowMe framework. This framework provides the seamless migration of bi-directional user interfaces for users as they navigate between zones within an intelligent environment

Predictive dynamic resource allocation for web hosting environments

E-Business applications are subject to significant variations in workload and this can cause exceptionally long response times for users, the timing out of client requests and/or the dropping of connections. One solution is to host these applications in virtualised server pools, and to dynamically reassign compute servers between pools to meet the demands on the hosted applications. Switching servers between pools is not without cost, and this must therefore be weighed against possible system gain. This work is concerned with dynamic resource allocation for multi-tiered, clusterbased web hosting environments. Dynamic resource allocation is reactive, that is, when overloading occurs in one resource pool, servers are moved from another (quieter) pool to meet this demand. Switching servers comes with some overhead, so it is important to weigh up the costs of the switch against possible system gains. In this thesis we combine the reactive behaviour of two server switching policies – the Proportional Switching Policy (PSP) and the Bottleneck Aware Switching Policy (BSP) – with the proactive properties of several workload forecasting models. We evaluate the behaviour of the two switching policies and compare them against static resource allocation under a range of reallocation intervals (the time it takes to switch a server from one resource pool to another) and observe that larger reallocation intervals have a negative impact on revenue. We also construct model- and simulation-based environments in which the combination of workload prediction and dynamic server switching can be explored. Several different (but common) predictors – Last Observation (LO), Simple Average (SA), Sample Moving Average (SMA) and Exponential Moving Average (EMA), Low Pass Filter (LPF), and an AutoRegressive Integrated Moving Average (ARIMA) – have been applied alongside the switching policies. As each of the forecasting schemes has its own bias, we also develop a number of meta-forecasting algorithms – the Active Window Model (AWM), the Voting Model (VM), the Selective Model (SM), the Dynamic Active Window Model (DAWM), and a method based on Workload Pattern Analysis (WPA). The schemes are tested with real-world workload traces from several sources to ensure consistent and improved results. We also investigate the effectiveness of these schemes on workloads containing extreme events (e.g. flash crowds). The results show that workload forecasting can be very effective when applied alongside dynamic resource allocation strategies

Towards FollowMe User Profiles for Macro Intelligent Environments

We envision an Ambient Intelligent Environment as an environment with technology embedded within the framework of that environment to help enhance an users experience in that environment. Existing implementations , while working effectively, are themselves an expensive and time consuming investment. Applying the same expertise to an environment on a monolithic scale is very inefficient, and thus, will require a different approach. In this paper, we present this problem, propose theoretical solutions that would solve this problem, with the guise of experimentally verifying and comparing these approaches, as well as a formal method to model the entire scenario

Asthma diagnosis and treatment - 1012. The efficacy of budesonide in the treatmetn of acute asthma in children: a double-blind, randomized, controlled trial.

Background Current evidence suggests that inhaled glucocorticoids (IGC) have a more profound topical none genomic effect on bronchial airways as compared to systemic glucocorticoids. The value of adding IGC to current therapy of acute asthma is not well established. Methods We conducted a double-blind, randomized, two-arm, parallel groups, controlled clinical trial to compare the addition of budesonide 1500 mcg or placebo (normal saline) to standard acute asthma treatment (albuterol and ipratropium bromide) administered in 3 divided mixed doses within 1 hour in the emergency department (ED). Children 2-12 years of age with moderate or severe acute asthma, scoring 8-15/15 on a well-validated scoring system were included. Both groups received a single dose of prednisone 2 mg/kg/day (max. 60 mg) at the beginning of therapy. The primary outcome was admission rate within 2-4 hours from starting therapy. Results A total of 723 children were enrolled in the study over 17 months duration, of whom 139 were allowed to re-enroll and be randomized to constitute 906 randomization assignments (458 on the treatment group and 448 on the control group); with baseline mean + SD asthma score of 10.63 + 1.73; age 5.52 + 2.76 years; 35% girls; 30.8% (16.5%) with baseline severe asthma score of ≥12 (≥ 13). Statistical Analysis plan allowed for the potential dependency in response due to reenrollments of a subset of children, using Generalized Linear Mixed Modeling (GLMM) techniques. Baseline demographic and clinical characteristics were not significantly different between the two randomized groups. Seventy-five out of 458 (16.4%) of the treatment group vs. 82/448 (18.3%) of the control group were admitted, (OR 0.85, CI: 0.59-1.23, p-value=0.39). Among the severe asthmatics with baseline score ≥13, treatment vs. placebo group, GLMM adjusted admission rate was 30% vs. 47%, indicating a 17% difference in admission rate in favor of the treatment group (adjusted OR of 0.49, CI: 0.25-0.95; p-value= 0.035) that indicated a 51% reduction in the risk of admission for the treatment vs. control group. Conclusions Children with baseline severe asthma score ≥13 who were treated with budesonide had a significant reduction in their admission rate

Electrochemical determination of rosiglitazone by square-wave adsorptive stripping voltammetry method

AbstractSquare-wave adsorptive stripping voltammetry technique was used to determine rosiglitazone (ROS) on the hanging mercury dropping electrode (HMDE) surface, in Britton Robinson buffer, pH=5. The voltammetric cathodic peak was observed at −1520mV vs. Ag/AgCl reference electrode. The voltammetric peak response was characterized with respect to pH, supporting electrolyte, accumulation potential, preconcentration time, scan rate, frequency, pulse amplitude, surface area of the working electrode and the convection rate. Under optimal conditions, the voltammetric current is proportional to the concentration of ROS over the concentration range of 5×10−8–8×10−7moll−1 (r=0.9899) with a detection limit of 3.2×10−11moll−1 using 120s accumulation time. The developed SW-AdSV procedure showed a good reproducibility, the relative standard deviation RSD% (n=10) at a concentration level of 5×10−7moll−1 was 0.33%, whereas the accuracy was 101%±1.0. The proposed method was successfully applied to assay the drug in the human urine and plasma samples with mean recoveries of 90±0.71% and 86±1.0%, respectively

Spectroscopic ellipsometry study of barrier width effect in self-organized InGaAs/GaAs QDs laser diodes

Molecular beam epitaxy (MBE) is used to grow InGaAs/GaAs quantum dots (QDs) laser diodes (LDs) with different barrier widths (5, 10 and 15 nm) at 580 ºC on GaAs substrates. Optical properties of the InGaAs/GaAs QDs LDs have been investigated by using the spectroscopic ellipsometry (SE) technique. A general oscillator optical model has been utilized to fit the experimental data in order to obtain the LD layer thicknesses, refractive index and absorption coefficient. The dielectric function, the energy band gap and the surface and volume energy loss functions are computed in the energy range 1-6 eV. The optical properties of the deposited InGaAs/GaAs QDs LDs are found to be affected by the barrier width, which give more insight into carriers dynamics and optical parameters in these devices. The refractive indices, the extinction coefficients and the dielectric constants of the LDs with barrier widths 15 and 10 nm are relatively larger than those of the LD with barrier width 5 nm. These indicate that optical properties of LDs with larger barrier widths (15 and 10 nm) will be improved. The interband transition energies in the three devices have calculated and identified. Two energy gaps at 1.04 and ~1.37 eV are obtained for all the heterostructures which indicates that fabricated LDs may be operating for a wavelength of 1.23 m at room temperature

Robustness, redundancy, inclusivity, and integration of built environment systems: resilience quantification from stakeholders’ perspectives

The built environment faces a growing number of challenges due to changing climates. A resilient built environment system (BES) can withstand disruptions and shocks, and resilient design allows communities to bounce back quickly. Considering present and future needs, BESs can be oriented to adapt to new uses or modified to handle changing climates. This study examines the resilience qualities (RQs) of built environment systems (BESs) in responding to and recovering from climate change disruptions effectively. A survey was designed to capture the views of various stakeholders about the different indicators to assess the four RQs: robustness (Rb), redundancy (Rd), inclusivity (Ic), and integration (It). Regulatory and engineering stakeholders participated in the survey, and the results were analyzed using statistical methods. Stakeholders generally agree on the need to enhance transformative capacity for addressing uncertainties and climate challenges. While stakeholders trust the role of BESs’ robustness against climate impacts, some suggest improving standards for better resilience. There is consensus on the importance of regulatory measures mandating emergency resources in BESs. The study highlights the need to enhance adaptive capacities and tools within BESs. Incorporating reconfigurability and spare capacity in BESs is crucial to prevent disruptions. Participants tend to think promoting good practices at the community level is essential to address climate impacts effectively. The analysis highlights the importance of inclusive community consultation and involvement in fostering a shared responsibility for enhancing urban ecosystems against climate change impacts. This involves aligning processes across various city systems to support cohesive decision-making and strategic investments. The study suggests developing objective engineering techniques to establish a standardized approach for evaluating the RQs of BESs

The Multi-dimensional Problem of Quantifying Cartographic Generalization Uncertainty: Linear Features as an Example.

This paper highlights cartographic considerations relevant during the process of quantification of generalization uncertainties, defined here as Generalization Factor (GF). The paper adds to current research on map or spatial database errors and uncertainties, but focuses on the complex nature of the quantification process of generalization uncertainties. Three main cartographic aspects or contexts are discussed in this paper: namely, feature complexity, map sources, and map purposes. The paper discusses the difficulties in producing a universal index as GF that accounts satisfactorily for generalization uncertainty. As a result, there is a need for a thorough study to account for all types of generalization uncertainty for each feature according to the cartographic consideration discussed in this study, although such contexts are not exhaustive. The study suggests that the uncertainty measures should result in a form of value that can be attached to each feature in the database, especially for those detailed databases that are designed for analysis purposes. The study suggests that it might well be possible to quantify generalization uncertainty more easily once the process of generalization is performed automatically or even semi-automatically, especially with the advent of new generalization tools

First Order Phase Transformation in Amorphous Ge25Se75 – xSbx Glasses

Non-isothermal Differential scanning calorimetry (DSC) technique was used to study the kinetics of first order phase transformation in Ge25Se75 – xSbx glasses. The X-ray diffraction (XRD) technique was employed to investigate the amorphous and crystalline phases in Ge25Se75 – xSbx glasses. From the heating rate dependences of crystallization temperature; the activation energy for crystallization and other kinetics parameters were derived. The temperature difference (Tc – Tg) and Tc is highest for the samples with 6 % of Sb. Hence, Ge25Se69Sb6 glass is most stable. The enthalpy released is found to be less for Ge25Se69Sb6 glass which further confirms its maximum stability. The activation energy of crystallization (Ec) is found to vary with compositions indicating a structural change due to the addition of Sb. The crystallization data are interpreted in terms of recent analyses developed for non-isothermal conditions. The present investigation indicates that both the glass transition and the crystallization processes occur in a single stage. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3101

Graph-based correlated topic model for trajectory clustering in crowded videos

This paper presents a graph-based correlated topic model (GCTM) to analyse various motion patterns by trajectory clustering in a highly cluttered and crowded environment. Unlike the existing methods that address trajectory clustering and crowd motion modelling using local motion features such as optical flow, it builds on trajectory segments extracted from crowded scenes. Correlated topic models have been previously applied to handle mid-level features learning in crowded scenes. However it depends on scene priors in the learning process. GCTM addresses this issue by using a spatio-temporal graph and manifold-based clustering as initialization and iterative statistical inference as optimization. The output of GCTM is mid-level features used later as an input to the final step that generates trajectory clusters. Experiments on two different datasets show the effectiveness of the approach in trajectory clustering and crowd motion modelling