A Methodology for Engineering Collaborative and ad-hoc Mobile Applications using SyD Middleware

Today’s web applications are more collaborative and utilize standard and ubiquitous Internet protocols. We have earlier developed System on Mobile Devices (SyD) middleware to rapidly develop and deploy collaborative applications over heterogeneous and possibly mobile devices hosting web objects. In this paper, we present the software engineering methodology for developing SyD-enabled web applications and illustrate it through a case study on two representative applications: (i) a calendar of meeting application, which is a collaborative application and (ii) a travel application which is an ad-hoc collaborative application. SyD-enabled web objects allow us to create a collaborative application rapidly with limited coding effort. In this case study, the modular software architecture allowed us to hide the inherent heterogeneity among devices, data stores, and networks by presenting a uniform and persistent object view of mobile objects interacting through XML/SOAP requests and responses. The performance results we obtained show that the application scales well as we increase the group size and adapts well within the constraints of mobile devices

Outcomes Considered Most Important by Emergency Physicians When Determining Disposition of Patients with Pulmonary Embolism

Purpose: Clinical decision rules for the disposition of patients with pulmonary embolism (PE) are typically validated against an outcome of 30-day mortality or disease recurrence. There is little justification for this time frame, nor is it clear whether this outcome reflects emergency department (ED) decision making. Aims: To determine which outcomes emergency physicians (EP) consider most relevant to disposition decisions. Methods: Survey of attending EPs in geographically diverse US states using acute PE as the diagnostic framework. Responses required single-answer multiple choice, a numerical percentage, rank-ordered responses, or a five-point Likert scale. We distributed the survey via e-mail to 608 EPs. Results: We received responses from 292 (48%) EPs: 88% board certified, 91% trained in emergency medicine, and 70% work in academics. Respondents reported discharging 1% of patients with PE from the ED, but 21% reported being asked to do so by an admitting service. EPs were more interested in knowing 5-day (in hospital) outcomes [192/265, 72% (95% exact CI=66%–78%)] than 30-day outcomes [39/261, 15% (95% exact CI=11%–20%)] or 90-day outcomes [29/263, 11% (95% exact CI=8%–15%)]. On a Likert scale, 212/241 (88%, 95% exact CI=83%–92%) agreed or strongly agreed that they considered 5-day (in hospital) clinical deterioration when making a decision to admit or discharge a patient from the ED compared to 184/242 (76%, 95% exact CI=70%–81%) and 73/242 (30%, 95% exact CI=24%–36%) for 30 and 90 days, respectively. A wide variety of clinical outcomes beyond death or recurrent PE were considered indicative of clinical deterioration. Conclusions: Five-day (in hospital) outcomes that incorporate a variety of clinical deterioration events are of interest to EPs when determining the disposition of ED patients with PE. Researchers should consider this when developing and validating clinical decision rules

Time Series Traffic Flow Prediction with Hyper-Parameter Optimized ARIMA Models for Intelligent Transportation System

408-415Intelligent Transportation System (ITS) has become the need of the day to manage heavy traffic problems due to the exponential growth of road transportation. This is also very much essential for building the smart cities and to improve the comfort of the vehicle drivers. The electric and autonomous vehicles are going to be the future transport systems for which we need an intelligent traffic management system. This requires a lot of growth in infrastructure. The integration of technologies such as Sensors, Internet of Things (IoT), Cloud Computing, etc. has to be done for this. The traffic prediction is one of thekey requirement for establishing the ITS. In this paper we present our study on ARIMA model with optimized hyper-parameter using grid search technique for traffic flow predictions. The model validation is done on the whole day traffic flow, morning and evening peak time traffic flow datasets. The prediction results show good performance metrics with RMSE of 8.953, 11.007 and 11.837 for those three datasets

Intelligent transportation system and smart traffic flow with IOT

64-67There has been an increase in vehicles across the globe. Also, the congestion due to traffic has leapfrogged in India. The traffic flow information has been required to find out the route with minimum congestion and forecast the traffic. And this has been a part of the Intelligent Transportation System (ITS) which would help build smart cities. A lot of work has been done on the traffic measurement system. But the integration of emerging techniques such as the Internet of Things (IoT) and cloud computing has provided a lot of research scope in ITS. This paper has proposed an IoT-based method to determine the real-time traffic flow in a road section with ultrasonic sensors, Arduino, ESP8266 Wi-Fi module, and an open-source cloud. There has been an average traffic flow every five minutes to be displayed in the cloud platform. This method can be very much cost-effective with less power consumption and improved accuracy. Hence, the proposed IoT-based technique has provided the traffic flow data, and this data shall further be used for traffic predictions using machine learning algorithms

SyD: A Middleware Testbed for Collaborative Applications over Small Heterogeneous Devices and Data Stores

Abstract. Currently, it is possible to develop a collaborative application running on a collection of heterogeneous, possibly mobile, devices, each potentially hosting data stores, using existing middleware technologies such as JXTA, BREW, compact.NET and J2ME. However, they require too many ad-hoc techniques as well as cumbersome and time-consuming programming. Our System on Mobile Devices (SyD) middleware, on the other hand, has a modular architecture that makes such application de-velopment very systematic and streamlined. The architecture supports transactions over mobile data stores, with a range of remote group invo-cation options and embedded interdependencies among such data store objects. The architecture further provides a persistent uniform object view, group transaction with Quality of Service (QoS) speci¯cations, and XML vocabulary for inter-device communication. This paper presents the basic SyD concepts, introduces the architecture and the design of the SyD middleware and its components. We also provide guidelines fo

Time Series Traffic Flow Prediction with Hyper-Parameter Optimized ARIMA Models for Intelligent Transportation System

Intelligent Transportation System (ITS) has become the need of the day to manage heavy traffic problems due to the exponential growth of road transportation. This is also very much essential for building the smart cities and to improve the comfort of the vehicle drivers. The electric and autonomous vehicles are going to be the future transport systems for which we need an intelligent traffic management system. This requires a lot of growth in infrastructure. The integration of technologies such as Sensors, Internet of Things (IoT), Cloud Computing, etc. has to be done for this. The traffic prediction is one of thekey requirement for establishing the ITS. In this paper we present our study on ARIMA model with optimized hyper-parameter using grid search technique for traffic flow predictions. The model validation is done on the whole day traffic flow, morning and evening peak time traffic flow datasets. The prediction results show good performance metrics with RMSE of 8.953, 11.007 and 11.837 for those three datasets