An orchestrator for networked control systems and its application to collision avoidance in multiple mobile robots.

Networked Control System (NCS) consists of controlled distributed nodes while an Orchestrator functions as a central coordinator for controlling the distributed tasks. The NCSs have challenges of coordination and right execution sequencing of operations. This paper proposes a framework named Controlled Orchestrator (COrch) for coordinating and sequencing the tasks of NCSs. An experiment was performed with three robotic vehicles that are considered as individual control system. Furthermore, the proposed orchestrator COrch decided the sequencing of operations of the robots while performing obstacle avoidance task for spatially distributed robots in parallel. COrch is used to control this task by utilizing the concept of Remote Method Invocation (RMI) and multithreading. RMI is used to prepare the software for controlling the robots at remote end while multithreading is used to perform parallel and synchronize execution of multiple robots. The remote end software generates signals for sequential, parallel and hybrid mode execution

Cloud-based bug tracking software defects analysis using deep learning

Cloud technology is not immune to bugs and issue tracking. A dedicated system is required that will extremely error prone and less cumbersome and must command a high degree of collaboration, flexibility of operations and smart decision making. One of the primary goals of software engineering is to provide high-quality software within a specified budget and period for cloud-based technology. However, defects found in Cloud-Based Bug Tracking software's can result in quality reduction as well as delay in the delivery process. Therefore, software testing plays a vital role in ensuring the quality of software in the cloud, but software testing requires higher time and cost with the increase of complexity of user requirements. This issue is even cumbersome in the embedded software design. Early detection of defect-prone components in general and embedded software helps to recognize which components require higher attention during testing and thereby allocate the available resources effectively and efficiently. This research was motivated by the demand of minimizing the time and cost required for Cloud-Based Bug Tracking Software testing for both embedded and general-purpose software while ensuring the delivery of high-quality software products without any delays emanating from the cloud. Not withstanding that several machine learning techniques have been widely applied for building software defect prediction models in general, achieving higher prediction accuracy is still a challenging task. Thus, the primary aim of this research is to investigate how deep learning methods can be used for Cloud-Based Bug Tracking Software defect detection with a higher accuracy. The research conducted an experiment with four different configurations of Multi-Layer Perceptron neural network using five publicly available software defect datasets. Results of the experiments show that the best possible network configuration for software defect detection model using Multi-Layer Perceptron can be the prediction model with two hidden layers having 25 neurons in the first hidden layer and 5 neurons in the second hidden layer

ASIRI : an ocean–atmosphere initiative for Bay of Bengal

Author Posting. © American Meteorological Society, 2016. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 97 (2016): 1859–1884, doi:10.1175/BAMS-D-14-00197.1.Air–Sea Interactions in the Northern Indian Ocean (ASIRI) is an international research effort (2013–17) aimed at understanding and quantifying coupled atmosphere–ocean dynamics of the Bay of Bengal (BoB) with relevance to Indian Ocean monsoons. Working collaboratively, more than 20 research institutions are acquiring field observations coupled with operational and high-resolution models to address scientific issues that have stymied the monsoon predictability. ASIRI combines new and mature observational technologies to resolve submesoscale to regional-scale currents and hydrophysical fields. These data reveal BoB’s sharp frontal features, submesoscale variability, low-salinity lenses and filaments, and shallow mixed layers, with relatively weak turbulent mixing. Observed physical features include energetic high-frequency internal waves in the southern BoB, energetic mesoscale and submesoscale features including an intrathermocline eddy in the central BoB, and a high-resolution view of the exchange along the periphery of Sri Lanka, which includes the 100-km-wide East India Coastal Current (EICC) carrying low-salinity water out of the BoB and an adjacent, broad northward flow (∼300 km wide) that carries high-salinity water into BoB during the northeast monsoon. Atmospheric boundary layer (ABL) observations during the decaying phase of the Madden–Julian oscillation (MJO) permit the study of multiscale atmospheric processes associated with non-MJO phenomena and their impacts on the marine boundary layer. Underway analyses that integrate observations and numerical simulations shed light on how air–sea interactions control the ABL and upper-ocean processes.This work was sponsored by the U.S. Office of Naval Research (ONR) in an ONR Departmental Research Initiative (DRI), Air–Sea Interactions in Northern Indian Ocean (ASIRI), and in a Naval Research Laboratory project, Effects of Bay of Bengal Freshwater Flux on Indian Ocean Monsoon (EBOB). ASIRI–RAWI was funded under the NASCar DRI of the ONR. The Indian component of the program, Ocean Mixing and Monsoons (OMM), was supported by the Ministry of Earth Sciences of India.2017-04-2

Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

As mortality rates decline, life expectancy increases, and populations age, non-fatal outcomes of diseases and injuries are becoming a larger component of the global burden of disease. The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016

A novel technique to recanalize the nasolacrimal duct with endodiathermy bipolar probe

Aims: To evaluate a new approach for recanalization (RC) of nasolacrimal duct obstruction in the treatment of the symptomatic nasolacrimal duct obstruction (NLDO). Materials and Methods: A prospective, interventional, comparative study in 302 eyes of 209 patients of symptomatic nontraumatic NLDO. Eyes with previous failed surgery were excluded. One hundred and fifty-one eyes underwent RC with 20 G endodiathermy bipolar probe connected to a 7 W diathermy followed by bicanalicular intubation under direct visualization. One hundred and fifty-one eyes underwent standard external dacryocystorhinostomy (DCR). Follow-up was for 24 months and evaluation was done on basis of change in symptoms and lacrimal syringing. Data was analyzed by Chi-square test and unpaired t-test. P value 0.05). Two eyes in RC and one in DCR group had complications. Conclusions: RC with 20 G endodiathermy bipolar probe is a quick, simple, and effective alternative to standard external DCR

Evaluating a new surgical dosage calculation method for esotropia

Purpose: To evaluate a simplified method for correction of ocular deviation in patients of infantile and acquired basic esotropia. Materials and Methods: Thirty-six consecutive patients of infantile and acquired basic esotropia were selected for this study. Patients underwent unilateral recession-resection surgery as per the new norm gram. Patients underwent 3.5-7 mm recession of medial rectus (MR) in one eye depending on the pre-operative deviation and patient′s age. Together they also underwent 6 or 7 mm resection of the lateral rectus (LR) in the same eye depending on patient′s age (6 mm for 3 years and below and 7 mm for older age). In patients 3 years and below, a correction of 6, 7, or 8 PD/mm of recession of MR was expected when the pre-operative deviation was lesser than 30 PD, between 30 and 60 PD, or above 60 PD, respectively. Similarly, these values were 5, 6, and 7 PD/mm of MR recession in patients above 3 years. A ratio between achieved and expected correction was calculated and the calculation was deemed successful for a patient if this ratio fell between 0.9 and 1.1. Results: The calculation procedure was successful in 33 out of 36 patients (91%). The two-tailed probability on paired Wilcoxon test was 0.187. Conclusions: This simplified method of surgical dosage calculation using MR recession as basis is predictable in patients of infantile and basic Esotropia. It may serve as a useful tool for minimizing variability of surgical results

Monitoring, Surveillance and Technostress-An Enterprise Application Case

There has been an increasing reliance of organizations on workflow systems to maintain quality and to manage people. The use of enterprise workflow applications like ERP, CRM or customized workflow applications provides ample opportunities for computer-mediated control and monitoring. The employees are subjected to constant surveillance that often starts negatively affecting their health and mental wellbeing. The knowledge of constantly being watched puts tremendous pressure on people. This Technostress experienced by employees is caused due to lack of social interactions with peers and supervisors, change in their job description and information overload. They often face role conflict and are constrained by the system. The system drives the business instead of the other way around. The managers have increased workload as now they spend time and energy in micromanaging their teams. This paper examines the impact of monitoring and surveillance due to Enterprise Workflow applications on employee stress