Effect of Nickel Nitrate Concentration on the Size of Nickel Oxide Nanoparticles Bio-synthesized by Artemisia herba-alba Aqueous Leaves Extract and Improving Their Antioxidant Activities

Journal of Inorganic and Organometallic Polymers and Materials - This work aims to investigate the effect of nickel nitrate concentration on the size and antioxidant activity of nickel oxide...     

Simultaneous reconstruction of the time-dependent Robin coefficient and heat flux in heat conduction problems

This paper aims to solve an inverse heat conduction problem in two-dimensional space under transient regime, which consists of the estimation of multiple time-dependent heat sources placed at the boundaries. Robin boundary condition (third type boundary condition) is considered at the working domain boundary. The simultaneous identification problem is formulated as a constrained minimization problem using the output least squares method with Tikhonov regularization. The properties of the continuous and discrete optimization problem are studied. Differentiability results and the adjoint problems are established. The numerical estimation is investigated using a modified conjugate gradient method. Furthermore, to verify the performance of the proposed algorithm, obtained results are compared with results obtained from the well-known finite-element software COMSOL Multiphysics under the same conditions. The numerical results show that the proposed algorithm is accurate, robust and capable of simultaneously representing the time effects on reconstructing the time-dependent Robin coefficient and heat flux.     

Low-temperature processing and characterization of single-phase PZT powders by sol-gel method

A new sol-gel system using acetoin was developed and employed for the fabrication of PZT powders and films with compositions near the morphotropic phase boundary Pb(Zr_0.52Ti_0.48)O₃. Acetoin was used as chelating agent to replace the highly toxic methoxyethanol used in previous formulations. This route simplified the chemical processing of PZT-based solutions. Powders were completely crystallized by about 450 °C and contained the ferroelectric perovskite single phase. The firing temperature and time were to be the most important variables. Metallic lead formed only when excess Pb was incorporated. The precursor and the heat-treated powders have been characterized by using thermal analysis and X-ray diffractometry (XRD) studies. The average particle size, as measured from X-ray line broadening, was ∼35 nm.     

Psychosocial Factors and Musculoskeletal Disorders in the Construction Industry

Musculoskeletal disorders (MSDs) constitute more than half of the total injuries and illnesses within the construction industry. The aim of this study was to assess the prevalence of MSD among construction workers and identify the psychosocial and physical risk factors associated with their occurrence using an on-site survey instrument. One hundred forty seven construction workers (representing three trades) participated in the study. The 1-year prevalence of MSD was high with 61.2% reporting severe symptoms and 39.7% having some functional impairment due to MSD. Physical task requirement was the most important factor associated with MSD reflecting the physical nature of construction work. Economic and performance factors were the most stressful psychosocial factors reported and significantly increased the risk of reporting MSD. The findings of this research underscore the independent role that psychosocial factors play in the health and safety of construction workers. Understanding this role is imperative for practitioners and academics alike in the quest to make construction a safer work environment for all workers.     

Physiological Demands during Construction Work

Notwithstanding the use of earthmoving equipment, cranes, and other machinery, physically strenuous and demanding tasks remain endemic to the construction industry. This research was motivated by the need to investigate the physical demands of construction work and to evaluate whether these physical demands are excessive. Physiological measures of energy expenditure, including oxygen consumption and heart rate data, were collected for 100 construction workers performing typical construction work. The average oxygen uptake for the measured construction activities was 0.82 L?min?1 (±0.22 L?min?1), and the average heart rate for the measured construction activities was 108 beats ?min?1 (±17 beats ?min?1). The measured data were evaluated against published guidelines for acceptable levels of physical performance in industrial settings indicating that a significant number of craft workers (20 to 40%) routinely exceed these physiological thresholds. The results clearly point to the need to promote and apply concepts of work physiology at the workplace to better the occupational health and safety of the construction workforce. This paper developed the foundation for further applied research regarding the physical demands of construction work.     

Fuzzy classification in dynamic environments

The persistence and evolution of systems essentially depend on their adaptivity to new situations. As an expression of intelligence, adaptivity is a distinguishing quality of any system that is able to learn and to adjust itself in a flexible manner to new environmental conditions and such ability ensures self-correction over time as new events happen, new input becomes available, or new operational conditions occur. This requires self-monitoring of the performance in an ever-changing environment. The relevance of adaptivity is established in numerous domains and by versatile real-world applications. The present paper presents an incremental fuzzy rule-based system for classification purposes. Relying on fuzzy min–max neural networks, the paper explains how fuzzy rules can be continuously online generated to meet the requirements of non-stationary dynamic environments, where data arrives over long periods of time. The approach proposed to deal with an ambient intelligence application. The simulation results show its effectiveness in dealing with dynamic situations and its performance when compared with existing approaches.     

Experimental and numerical investigation of using waste glass aggregates in asphalt pavement to mitigate urban heat islands

Clean Technologies and Environmental Policy - In this study, the experimental and numerical effects of using waste glass as aggregates of asphalt pavement are evaluated. The main reason for using...     

Dipper Throated Algorithm for Feature Selection and Classification in Electrocardiogram

Arrhythmia has been classified using a variety of methods. Because of the dynamic nature of electrocardiogram (ECG) data, traditional handcrafted approaches are difficult to execute, making the machine learning (ML) solutions more appealing. Patients with cardiac arrhythmias can benefit from competent monitoring to save their lives. Cardiac arrhythmia classification and prediction have greatly improved in recent years. Arrhythmias are a category of conditions in which the heart's electrical activity is abnormally rapid or sluggish. Every year, it is one of the main reasons of mortality for both men and women, worldwide. For the classification of arrhythmias, this work proposes a novel technique based on optimized feature selection and optimized K-nearest neighbors (KNN) classifier. The proposed method makes advantage of the UCI repository, which has a 279-attribute high-dimensional cardiac arrhythmia dataset. The proposed approach is based on dividing cardiac arrhythmia patients into 16 groups based on the electrocardiography dataset’s features. The purpose is to design an efficient intelligent system employing the dipper throated optimization method to categorize cardiac arrhythmia patients. This method of comprehensive arrhythmia classification outperforms earlier methods presented in the literature. The achieved classification accuracy using the proposed approach is 99.8%.     

A survey of multidisciplinary design optimization methods in launch vehicle design

Optimal design of launch vehicles is a complex problem which requires the use of specific techniques called Multidisciplinary Design Optimization (MDO) methods. MDO methodologies are applied in various domains and are an interesting strategy to solve such an optimization problem. This paper surveys the different MDO methods and their applications to launch vehicle design. The paper is focused on the analysis of the launch vehicle design problem and brings out the advantages and the drawbacks of the main MDO methods in this specific problem. Some characteristics such as the robustness, the calculation costs, the flexibility, the convergence speed or the implementation difficulty are considered in order to determine the methods which are the most appropriate in the launch vehicle design framework. From this analysis, several ways of improvement of the MDO methods are proposed to take into account the specificities of the launch vehicle design problem in order to improve the efficiency of the optimization process.     

Joint loss pattern characterization and unequal interleaved FEC protection for robust H.264 video distribution over wireless LAN

The recently adopted H.264 standard achieves efficient video encoding and bandwidth savings. Thus, designing communication protocols and QoS control mechanisms for H.264 video distribution over wireless IP networks is a topic of intense research interest. Delivering video streams to terminals via a wireless last hop is indeed a challenging task due to the varying nature of the wireless link. While a common approach suggests exploiting the variations of the wireless channel, an alternative is to exploit characteristics of the video stream to improve the transmission. In this paper, we combine both approaches through an efficient wireless loss characterization and a low-delay unequal interleaved FEC protection. Besides deriving new QoS metrics for FEC block allocation, the wireless loss characterization is as well used to adjust the interleaving level depending on the loss correlation exhibited by the wireless channel. This novel unequal interleaved FEC (UI-FEC) protocol allows graceful video quality degradation over error-prone wireless links while minimizing the overall bandwidth consumption and the end-to-end latency.