138,456 research outputs found

    Programming language trends : an empirical study

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    Predicting the evolution of software engineering technology trends is a dubious proposition. The recent evolution of software technology is a prime example; it is fast paced and affected by many factors, which are themselves driven by a wide range of sources. This dissertation is part of a long term project intended to analyze software engineering technology trends and how they evolve. Basically, the following questions will be answered: How to watch, predict, adapt to, and affect software engineering trends? In this dissertation, one field of software engineering, programming languages, will be discussed. After reviewing the history of a group of programming languages, it shows that two kinds of factors, intrinsic factors and extrinsic factors, could affect the evolution of a programming language. Intrinsic factors are the factors that can be used to describe the general desigu criteria of programming languages. Extrinsic factors are the factors that are not directly related to the general attributes of programming languages, but still can affect their evolution. In order to describe the relationship of these factors and how they affect programming language trends, these factors need to be quantified. A score has been assigued to each factor for every programming language. By collecting historical data, a data warehouse has been established, which stores the value of each factor for every programming language. The programming language trends are described and evaluated by using these data. Empirical research attempts to capture observed behaviors by empirical laws. In this dissertation, statistical methods are used to describe historical programming language trends and predict the evolution of the future trends. Several statistics models are constructed to describe the relationships among these factors. Canonical correlation is used to do the factor analysis. Multivariate multiple regression method has been used to construct the statistics models for programming language trends. After statistics models are constructed to describe the historical programming language trends, they are extended to do tentative prediction for future trends. The models are validated by comparing the predictive data and the actual data

    Software for Wearable Devices: Challenges and Opportunities

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    Wearable devices are a new form of mobile computer system that provides exclusive and user-personalized services. Wearable devices bring new issues and challenges to computer science and technology. This paper summarizes the development process and the categories of wearable devices. In addition, we present new key issues arising in aspects of wearable devices, including operating systems, database management system, network communication protocol, application development platform, privacy and security, energy consumption, human-computer interaction, software engineering, and big data.Comment: 6 pages, 1 figure, for Compsac 201

    Evaluating the development of wearable devices, personal data assistants and the use of other mobile devices in further and higher education institutions

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    This report presents technical evaluation and case studies of the use of wearable and mobile computing mobile devices in further and higher education. The first section provides technical evaluation of the current state of the art in wearable and mobile technologies and reviews several innovative wearable products that have been developed in recent years. The second section examines three scenarios for further and higher education where wearable and mobile devices are currently being used. The three scenarios include: (i) the delivery of lectures over mobile devices, (ii) the augmentation of the physical campus with a virtual and mobile component, and (iii) the use of PDAs and mobile devices in field studies. The first scenario explores the use of web lectures including an evaluation of IBM's Web Lecture Services and 3Com's learning assistant. The second scenario explores models for a campus without walls evaluating the Handsprings to Learning projects at East Carolina University and ActiveCampus at the University of California San Diego . The third scenario explores the use of wearable and mobile devices for field trips examining San Francisco Exploratorium's tool for capturing museum visits and the Cybertracker field computer. The third section of the report explores the uses and purposes for wearable and mobile devices in tertiary education, identifying key trends and issues to be considered when piloting the use of these devices in educational contexts

    A protocol study of novice interaction design behaviour in Botswana: solution-driven interaction design

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    Think aloud studies and protocol analysis are well-known in the field of HCI, but most often these studies focus on usability evaluations, or on the use of technology. Rarely are they used to investigate the behaviour of interaction designers. In this paper, we report on a protocol study with novice interaction designers in Botswana. Participants had just completed the design section of an undergraduate module on Interaction Design that actively promotes a problem-driven approach to the design of interactive products, yet the participants behaved in a way that is closer to a solution-driven approach. The module emphasizes user-centred design, prototyping methods to support design development, and evaluating design detail. Yet participants suggest solutions before exploring the context of use, use prototyping methods to capture, rather than to develop, designs, and do not produce detailed designs. In a problem-solving context, some of these behaviours are typical of novices, but in a design context they are also seen in experienced designers. The results presented here reveal the detail of the approach adopted by these students, and contribute to the wider debate concerning the internationalization of HCI education

    CloudHealth: A Model-Driven Approach to Watch the Health of Cloud Services

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    Cloud systems are complex and large systems where services provided by different operators must coexist and eventually cooperate. In such a complex environment, controlling the health of both the whole environment and the individual services is extremely important to timely and effectively react to misbehaviours, unexpected events, and failures. Although there are solutions to monitor cloud systems at different granularity levels, how to relate the many KPIs that can be collected about the health of the system and how health information can be properly reported to operators are open questions. This paper reports the early results we achieved in the challenge of monitoring the health of cloud systems. In particular we present CloudHealth, a model-based health monitoring approach that can be used by operators to watch specific quality attributes. The CloudHealth Monitoring Model describes how to operationalize high level monitoring goals by dividing them into subgoals, deriving metrics for the subgoals, and using probes to collect the metrics. We use the CloudHealth Monitoring Model to control the probes that must be deployed on the target system, the KPIs that are dynamically collected, and the visualization of the data in dashboards.Comment: 8 pages, 2 figures, 1 tabl

    Learning while Competing -- 3D Modeling & Design

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    The e-Yantra project at IIT Bombay conducts an online competition, e-Yantra Robotics Competition (eYRC) which uses a Project Based Learning (PBL) methodology to train students to implement a robotics project in a step-by-step manner over a five-month period. Participation is absolutely free. The competition provides all resources - robot, accessories, and a problem statement - to a participating team. If selected for the finals, e-Yantra pays for them to come to the finals at IIT Bombay. This makes the competition accessible to resource-poor student teams. In this paper, we describe the methodology used in the 6th edition of eYRC, eYRC-2017 where we experimented with a Theme (projects abstracted into rulebooks) involving an advanced topic - 3D Designing and interfacing with sensors and actuators. We demonstrate that the learning outcomes are consistent with our previous studies [1]. We infer that even 3D designing to create a working model can be effectively learned in a competition mode through PBL

    Experiments of posture estimation on vehicles using wearable acceleration sensors

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    In this paper, we study methods to estimate drivers' posture in vehicles using acceleration data of wearable sensor and conduct a field test. Recently, sensor technologies have been progressed. Solutions of safety management to analyze vital data acquired from wearable sensor and judge work status are proposed. To prevent huge accidents, demands for safety management of bus and taxi are high. However, acceleration of vehicles is added to wearable sensor in vehicles, and there is no guarantee to estimate drivers' posture accurately. Therefore, in this paper, we study methods to estimate driving posture using acceleration data acquired from T-shirt type wearable sensor hitoe, conduct field tests and implement a sample application.Comment: 4 pages, 4 figures, The 3rd IEEE International Conference on Big Data Security on Cloud (BigDataSecurity 2017), pp.14-17, Beijing, May 201
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