Discovering the best web service: A neural network-based solution

Differentiating between Web services that share similar functionalities is becoming a major challenge into the discovery of Web services. In this paper we propose a framework for enabling the efficient discovery of Web services using Artificial Neural Networks (ANN) best known for their generalization capabilities. The core of this framework is applying a novel neural network model to Web services to determine suitable Web services based on the notion of the Quality of Web Service (QWS). The main concept of QWS is to assess a Web service\u27s behaviour and ability to deliver the requested functionality. Through the aggregation of QWS for Web services, the neural network is capable of identifying those services that belong to a variety of class objects. The overall performance of the proposed method shows a 95% success rate for discovering Web services of interest. To test the robustness and effectiveness of the neural network algorithm, some of the QWS features were excluded from the training set and results showed a significant impact in the overall performance of the system. Hence, discovering Web services through a wide selection of quality attributes can considerably be influenced with the selection of QWS features used to provide an overall assessment of Web services. ©2009 IEEE

A practical system for hands-off computer interaction based on electromyogram (EMG)/eye gaze tracking (EGT)

Effective interaction with personal computers is a basic requirement for many of the functions that are performed in our daily lives. With the rapid emergence of the Internet and the World Wide Web, computers have become one of the premier means of communication in our society. Unfortunately, these advances have not become equally accessible to physically handicapped individuals. In reality, a significant number of individuals with severe motor disabilities, due to a variety of causes such as Spinal Cord Injury (SCI), Amyothrophic Lateral Sclerosis (ALS), etc., may not be able to utilize the computer mouse as a vital input device for computer interaction. The purpose of this research was to further develop and improve an existing alternative input device for computer cursor control to be used by individuals with severe motor disabilities. This thesis describes the development and the underlying principle for a practical hands-off human-computer interface based on Electromyogram (EMG) signals and Eye Gaze Tracking (EGT) technology compatible with the Microsoft Windows operating system (OS). Results of the software developed in this thesis show a significant improvement in the performance and usability of the EMG/EGT cursor control HCI

Detecting Heart Rate Variability Using Millimeter-Wave Radar Technology

Identifying cardiac abnormalities has mainly been determined by the observation of electrocardiogram (ECG) signals. To collect ECG signals, it is often necessary to place ECG electrodes on the body for critical analysis of ECG data transmitted by such electrodes. By analyzing this collected data, it is then possible, for example, to examine the intervals between the heartbeats (or R-R intervals) to measure the heart rate variability (HRV). However, this process requires a multilayered setup for both hardware and software which can be costly and time consuming. To overcome these challenges, we introduce in this paper a real-time millimeter-wave radar-based, non-contact vital sign monitoring system that is capable of detecting the heart variability rate without the use of any heart rate sensors or wires required. Through this system, it is then possible to detect any heart rate abnormalities by analyzing the collected data. Throughout the paper, we present results for three individuals and compare our approach to heart rate monitoring devices and Apple Watch

A User-Centered Handoff Procedure in 5G Cellular Networks

The 5G cellular network is being deployed across many countries and is becoming an integral technology for mobile communication. The ubiquity of the 5G services, however, will require the dissemination of a large number of base stations which translates into a significant number of handoff operations compared to ear-lier generations (e.g. 4G/LTE). Furthermore, Narrowband Internet of Things (NB-IoT) is a 3GPP specification designed for enabling the wireless communication of low powered IoT devices. However, NB-IoT does not provide complete support for handoff operations and is intended for fixed IoT devices. In this paper, we investigate critical handoff attributes that may affect the end-to-end service inNB-IoT and present a user-centered handoff optimization model.Results show that our proposed user-centered model significantly outperforms the generic uniform preferences across 96% of tested handoff operations

WWW 2007 / Poster Paper Topic: Services Crawling Multiple UDDI Business Registries

As Web services proliferate, size and magnitude of UDDI Business Registries (UBRs) are likely to increase. The ability to discover Web services of interest then across multiple UBRs becomes a major challenge specially when using primitive search methods provided by existing UDDI APIs. Clients do not have the time to endlessly search accessible UBRs for finding appropriate services particularly when operating via mobile devices. Finding services of interest should be time effective and highly productive. This paper addresses issues relating to the efficient access and discovery of Web services across multiple UBRs and introduces a novel exploration engine, the Web Service Crawler Engine (WSCE). WSCE is capable of crawling multiple UBRs, and enables for the establishment of a centralized Web services repository that can be used for discovering Web services much more efficiently. The paper presents experimental validation, results, and analysis of the proposed ideas. Categories and Subject Descriptors D.2.12 [Software Engineering]: Interoperability – data mapping, distributed objects, interface definition languages; H.3.

Tutorial chairs\u27 welcome

It is our great pleasure to welcome you to the WWW2017 Tutorials that are held in conjunction with the 26th International World Wide Web Conference, April 3 – April 7, 2017, Perth, Australia. The tutorials of WWW2017 provide a high quality learning experience to conference attendees and local participants on current and emergent topics related to the World Wide Web. The call for papers attracted nineteen submissions from all around the world covering a broad range of topics. We evaluated them regarding relevance, quality, and novelty selecting three full-day tutorials and ten half-day tutorials. We also took into account the coverage of the different areas related to WWW as well as the potential audience, to schedule them in two consecutive days with the minimal audience interest overlap

Emerging Hardware Prototyping Technologies as Tools for Learning

Integrating hardware prototyping platforms such as Arduino, Raspberry Pi or BeagleBone Board in education is becoming more prevalent as the number of courses utilizing such platforms is continuously increasing. In this work, we conduct an analytical investigation on the plurality of courses that utilize or integrate hardware prototyping platforms. We examine curriculum and instructional material (e.g. course syllabi or outlines) through publicly available web informational resources (e.g. search engines). We use this data to determine the degree to which these platforms are used as effective learning technologies in existing courses. We further use this data to determine hardware platforms integration statistics and distribution based on the number of courses, types of platforms employed and institutions using them as learning technologies. This statistical data can be used to help determine the current status of the utilization and adoption rate of hardware prototyping platforms into courses. In this paper, we present evidence that hardware prototyping technologies are employed as tools for teaching and learning. Based on examining forty five universities worldwide, we determine that there are on average nine unique courses per university which utilize or integrate a variety of these platforms into courses. We also determine that 75% of these courses are Science, Technology, Engineering, and Math- (STEM-) based while 25% are Non-STEM. We further use our findings to provide insights on the extent to which educational institutions are utilizing these platforms as learning technologies and applying project-based or experiential learning approaches as part of their curriculum development

A Fog-Based Digital Forensics Investigation Framework for IoT Systems

The increasing number of IoT devices is prompting the need to investigate digital forensic techniques that can be efficiently applied to solve computer-related crimes involving IoT devices. In digital forensics, it is common for forensic investigators to consider computing hardware and operating systems for forensic data acquisition. However, applying current forensic data acquisition techniques for further digital evidence analysis may not be applicable to some IoT devices. It is becoming increasingly challenging to determine what type of data should be collected from IoT devices and how traces from such devices can be leveraged by forensic investigators. In this paper, we introduce a fog-based IoT forensic framework (FoBI) that attempts to address the key challenges associated with digital IoT forensics. Throughout this paper, we discuss the overall architecture, use cases and implementation details of FoBI. We further use our FoBI framework to provide insights on improving the digital forensics processes involving IoT systems. © 2018 IEEE

Edgify: Resource Allocation Optimization for Edge Clouds Using Stable Matching

As more Internet of Things (IoT) devices become increasingly ubiquitous, dynamic resource allocation for edge computing environments becomes extremely time consuming and challenging task.To overcome these challenges, edge computing environments need to dynamically scale based on the availability of accessible edge clouds within existing IoT infrastructure. In this paper, we introduce Edgify: a dynamic resource provisioning model that can effciently allocate resources across a distributed edge computing environment. We evaluate Edgify through a number of experiments that demonstrate usefulness and effectiveness of the proposed approach