In recent years the use of smart mobile devices has become an integral part of everyday life leading to the expansion of applications development for the various mobile platforms. Each of these platforms requires sepa...
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In recent years the use of smart mobile devices has become an integral part of everyday life leading to the expansion of applications development for the various mobile platforms. Each of these platforms requires separate software development process, which subsequently increases dramatically the corresponding effort. With the emergence of HTML5 these issues can be addressed efficiently since application development is allowed in a cross-platform manner. An additional important benefit is that users can access the application immediately without any need for installation. In this paper, we investigate the potentials of mobile application development with web technologies and we present a development framework that utilizes the most important state-of-art web technologies for the support of mobile devices. This framework can be used for the implementation of mobile web applications and also for the investigation and experimentation on the main features that HTML5 offers for this specific type of devices.
Interactive dynamic simulators are an accelerator for developing novel robotic control algorithms and complex systems involving humans and robots. In user training and synthetic data generation applications, high-fide...
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ISBN:
(数字)9798331521554
ISBN:
(纸本)9798331521561
Interactive dynamic simulators are an accelerator for developing novel robotic control algorithms and complex systems involving humans and robots. In user training and synthetic data generation applications, high-fidelity visualizations from the simulation are essential. Yet, robotic simulators often limit their rendering algorithms to preserve real-time interaction with the simulation. Advancements in Graphics Processing Units (GPU) enable improved visualization without compromising performance. However, these advancements cannot be fully leveraged in simulation frameworks that use legacy graphics application programming interfaces (API) to interface with the GPU. This paper presents a performance-focused and lightweight rendering engine supporting the modern Vulkan graphics API that can be easily integrated with other simulation frameworks to enhance visualizations. To illustrate the proposed method, our engine is used to modernize the legacy rendering pipeline of the Asynchronous Multi-Body Framework (AMBF), a dynamic simulation framework used extensively for interactive robotics simulation development. This new rendering engine implements graphical features such as physically based rendering (PBR), anti-aliasing, and ray-traced shadows, significantly improving the image fidelity of AMBF. Computational experiments show that the engine can render a simulated scene with over seven million triangles while maintaining GPU computation times within two milliseconds.
The increasing complexity of network traffic resulting from internet-based services and data exchanges presents formidable obstacles to real-time analysis and decision-making in the field of network security. A real-t...
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ISBN:
(数字)9798331529635
ISBN:
(纸本)9798331529642
The increasing complexity of network traffic resulting from internet-based services and data exchanges presents formidable obstacles to real-time analysis and decision-making in the field of network security. A real-time network traffic analysis system was created using Kafka, Redpanda, and machine learning to overcome these difficulties. Flow-based values were collected from CICFlowmeter. To efficiently classify network traffic, these attributes are subsequently examined using a machine learning model that has already been trained. Our integration of a Flask applicationprogramming Interface (API) with Kafka guarantees efficient, real-time data handling and processing. Efficient deployment is made possible via Docker, which also makes the system compatible with any existing server infrastructure. Performance analysis was conducted to assess how well the system handles real-time traffic and its accuracy in classifying network data, an accuracy of 99.4% is achieved using the Random Forest Classifier algorithm. The findings show that using Redpanda for Kafka, alongside machine learning, greatly improves the speed and effectiveness of data processing and classification. This approach provides a solid and adaptable solution for enhancing network security.
With the development of the Internet, a large number of computer applications have emerged, and the quantity is still growing rapidly. These applications contain a lot of useful data and functions, however, as most of...
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ISBN:
(纸本)9781728112787
With the development of the Internet, a large number of computer applications have emerged, and the quantity is still growing rapidly. These applications contain a lot of useful data and functions, however, as most of them are not available and couldn't interact with each other, so the data and functions are difficult to shared and reused, resulting in a huge waste of resources. In order to solve this problem, secondary development is needed on the basis of the source system. For example, it is necessary to collect data from client applications or integrate their functions. Therefore, a framework of automatic encapsulation API based on the client system is proposed in this paper. Firstly, using a design pattern to reconstruct the runtime software architecture. Secondly, an algorithm is proposed for parameter matching to automatically construct API template. Thirdly, a framework is implemented to support design patterns and matching algorithms. In conclusion, we experimented with a real client system, and the results show that in most cases our method can effectively encapsulate and reduce the execution time of the functions.
IP based Live Broadcast production is almost here and a production-ready system requires more than basic management of media flows. A production-ready system must have orchestration, security, diagnostics, scale, and ...
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IP based Live Broadcast production is almost here and a production-ready system requires more than basic management of media flows. A production-ready system must have orchestration, security, diagnostics, scale, and redundancy capabilities. A richer integration between the broadcast systems and the network is required to achieve these capabilities. There needs to be an interoperable interface between the Broadcast Controller and the Network to permit an open, flexible, and multi-vendor environment. This paper explores architectural aspects of the interface (Network Control API) between the Broadcast and the Network Controller. The presentation will describe how Network Control delivers the above-mentioned capabilities and extends the interactions of the Broadcast systems.
Wildland fire simulation is a useful tool for studying wildland fires and for developing new technologies to help wildland fire management. This paper presents an effort of developing wildland fire simulation as a ser...
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ISBN:
(数字)9798331539580
ISBN:
(纸本)9798331539597
Wildland fire simulation is a useful tool for studying wildland fires and for developing new technologies to help wildland fire management. This paper presents an effort of developing wildland fire simulation as a service that is accessible to broader users. The developed simulation service supports fire spread simulation, fire suppression simulation, and prescribed fire simulation with dynamic ignitions, and is accessible through a graphic user interface and an applicationprogramming interface (API). We present the underlying DEVS-FIRE simulation model, the design of the cloud-based wildland fire simulation service, and some preliminary results.
Social media data have been shown to be a useful resource for the recognition of novel drug use practices and trends. In a random sample collected using Twitter applicationprogramming Interface (API), “dabs” relate...
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ISBN:
(数字)9781728106663
ISBN:
(纸本)9781728106670
Social media data have been shown to be a useful resource for the recognition of novel drug use practices and trends. In a random sample collected using Twitter applicationprogramming Interface (API), “dabs” related tweets produced high volume data than other keywords related to marijuana concentrate in all the states that have legalized for recreational use or for medical use. The key objectives of this research are: 1-Describing a development model of a Machine Learning (ML) classifier to identify “dabs“ that are related to marijuana concentrates and evaluate its performance. 2-Examining dabs-related data between March 2016 and June 2017 after application of the ML classifier model. 3-Analyzing the trends on the number of relevant tweets, number of tweets with retweets, and unique users.
Sensor networks have recently been attracting the interest of both researchers and developers alike. Due to the advances in sensor and wireless device miniaturisation through MEMS technology, it is now possible to obt...
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ISBN:
(纸本)9784907764319
Sensor networks have recently been attracting the interest of both researchers and developers alike. Due to the advances in sensor and wireless device miniaturisation through MEMS technology, it is now possible to obtain environment information from difficult to reach places and expectations are high as to how this technology will be applied. When we considered sensor network applications, difficulties were forecast with respect to gathering the enourmous amounts of data from the monitored environment. However, we designed and developed a Web API for obtaining sensor data from sensor networks and, using a version of the Web API tailored for mobile phones, we developed a navigation system aimed at pedestrians. The system uses temperature sensor data to determine the most comfortable route for the user. All edges are weighted using the temperature sensor data and then an optimal route is computed using Dijkstra's algorithm. In this paper we describe both the Web API and the navigation system.
The diversity of platforms on the smart phones market, make the mobile applications development quite difficult and very expensive. Platform development could be a good solution for this problem. We'll start by de...
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The diversity of platforms on the smart phones market, make the mobile applications development quite difficult and very expensive. Platform development could be a good solution for this problem. We'll start by defining cross-platform development, and define the different types of mobile applications, and then define and explain the different approaches used in cross-platform development in order to achieve a comparison between these approaches allowing us to identify the strong points, and weaknesses of each approach. We present our results in a comparative table taking into consideration several criteria. These benchmarks have shown that the choice of a cross-platform development approach depends mainly on two things: to know what type of mobile application should be directed, and or targeted platforms. And adding the fact that multiplatform tools based on these approaches are limited in some point (access to different API platforms, performance compared to native applications ...), this work shows with certainty that more research is needed to go further than the current approaches.
In this paper we explore the relation between different groups of tweets using complex network analysis and link prediction. The tweets were collected via the Twitter API depending on their textual content. That is, w...
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ISBN:
(纸本)9781509025435
In this paper we explore the relation between different groups of tweets using complex network analysis and link prediction. The tweets were collected via the Twitter API depending on their textual content. That is, we searched for the tweets in English language containing specific predefined keywords from different domains. From the gathered tweets a complex network of words was formed as a weighted network. Nodes represent words and a link between two nodes exists if these two words co-occur in the same tweet, while weight denotes the co-occurrence frequency. The Twitter search was repeated for four different search criteria (API queries based on different tweet keywords), thus resulting in four networks with different nodes and links. The resulting networks were subjects to further network analysis, as comparison of numerical properties for different networks and link prediction for individual networks. This paper shows the tweet scraping process, our approach to building the networks, the measures we calculated for them, the differences and similarities between different networks we built and our success in predicting future links.
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