An investigation into the learnability of object-oriented case tools for computing education

The use of Computer Aided Software Engineering (CASE) tools for teaching object-oriented systems analysis and design (OOSAD) has many potential benefits, but there are also several problems associated with the usage of these tools. A large portion of these problems relate to the usability and learnability of these tools. Learnability is one of the most important attributes of usability and refers to the capability of the system to enable the user to learn its application. The main research question that this study aims to address is “How can the learnability of OO CASE tools for computing education in South Africa be evaluated?”. In order to answer this question several frameworks for evaluating CASE tool usability and learnability were investigated. One of these frameworks, as proposed by Senapathi, was selected as being the most appropriate for evaluating CASE tool learnability for computing education. This framework maintains that the learnability of a CASE tool is dependent on context of use factors such as the tool used, as well as user characteristics such as gender. The primary aim of this research was thus to validate Senapathi's framework for CASE tool learnability in a South African context. A secondary aim of the research was to extend the implementation of the framework in order to enable the comparison of two CASE tools and to support the inclusion of other user characteristics. An experiment was performed at the Nelson Mandela Metropolitan University (NMMU) in 2006. The participants recruited for this experiment were second year computing students at NMMU. During this experiment, the learnability of two OO CASE tools, namely IBM's Rational Software Modeller and Microsoft's Visio, was evaluated and compared. The quantitative and qualitative results supported Senapathi's results and showed that her framework could be used to evaluate CASE tool learnability and could be adapted to evaluate two CASE tools. The results also showed that the majority of the participants rated the learnability of Microsoft Visio higher for both tasks and that the main reasons participants preferred Visio was due to its simplicity, familiarity and recoverability

Towards a cloud‑based automated surveillance system using wireless technologies

Cloud Computing can bring multiple benefits for Smart Cities. It permits the easy creation of centralized knowledge bases, thus straightforwardly enabling that multiple embedded systems (such as sensor or control devices) can have a collaborative, shared intelligence. In addition to this, thanks to its vast computing power, complex tasks can be done over low-spec devices just by offloading computation to the cloud, with the additional advantage of saving energy. In this work, cloud’s capabilities are exploited to implement and test a cloud-based surveillance system. Using a shared, 3D symbolic world model, different devices have a complete knowledge of all the elements, people and intruders in a certain open area or inside a building. The implementation of a volumetric, 3D, object-oriented, cloud-based world model (including semantic information) is novel as far as we know. Very simple devices (orange Pi) can send RGBD streams (using kinect cameras) to the cloud, where all the processing is distributed and done thanks to its inherent scalability. A proof-of-concept experiment is done in this paper in a testing lab with multiple cameras connected to the cloud with 802.11ac wireless technology. Our results show that this kind of surveillance system is possible currently, and that trends indicate that it can be improved at a short term to produce high performance vigilance system using low-speed devices. In addition, this proof-of-concept claims that many interesting opportunities and challenges arise, for example, when mobile watch robots and fixed cameras would act as a team for carrying out complex collaborative surveillance strategies.Ministerio de Economía y Competitividad TEC2016-77785-PJunta de Andalucía P12-TIC-130

Experimental Study of the Cloud Architecture Selection for Effective Big Data Processing

Big data dictate their requirements to the hardware and software. Simple migration to the cloud data processing, while solving the problem of increasing computational capabilities, however creates some issues: the need to ensure the safety, the need to control the quality during data transmission, the need to optimize requests. Computational cloud does not simply provide scalable resources but also requires network infrastructure, unknown routes and the number of user requests. In addition, during functioning situation can occur, in which you need to change the architecture of the application - part of the data needs to be placed in a private cloud, part in a public cloud, part stays on the client

Four Decades of Computing in Subnuclear Physics - from Bubble Chamber to LHC

This manuscript addresses selected aspects of computing for the reconstruction and simulation of particle interactions in subnuclear physics. Based on personal experience with experiments at DESY and at CERN, I cover the evolution of computing hardware and software from the era of track chambers where interactions were recorded on photographic film up to the LHC experiments with their multi-million electronic channels

A Distributed Sensor Data Search Platform for Internet of Things Environments

Recently, the number of devices has grown increasingly and it is hoped that, between 2015 and 2016, 20 billion devices will be connected to the Internet and this market will move around 91.5 billion dollars. The Internet of Things (IoT) is composed of small sensors and actuators embedded in objects with Internet access and will play a key role in solving many challenges faced in today's society. However, the real capacity of IoT concepts is constrained as the current sensor networks usually do not exchange information with other sources. In this paper, we propose the Visual Search for Internet of Things (ViSIoT) platform to help technical and non-technical users to discover and use sensors as a service for different application purposes. As a proof of concept, a real case study is used to generate weather condition reports to support rheumatism patients. This case study was executed in a working prototype and a performance evaluation is presented.Comment: International Journal of Services Computing (ISSN 2330-4472) Vol. 4, No.1, January - March, 201