A novel optical flow-based representation for temporal video segmentation

Temporal video segmentation is a field of multimedia research enabling us to temporally split video data into semantically coherent scenes. In order to develop methods challenging temporal video segmentation, detecting scene boundaries is one of the more widely used approaches. As a result, representation of temporal information becomes important. We propose a new temporal video segment representation to formalize video scenes as a sequence of temporal motion change information. The idea here is that some sort of change in the optical flow character determines motion change and cuts between consecutive scenes. The problem is eventually reduced to an optical flow-based cut detection problem from which the average motion vector concept is put forward. This concept is used for proposing a pixel-based representation enriched with a novel motion-based approach. Temporal video segment points are classified as cuts and noncuts according to the proposed video segment representation. Consequently, the proposed method and representation is applied to benchmark data sets and the results are compared to other state-of-the art methods

Dynamics of collaborative work in global software development environment.

This study aims to explore the dynamics of collaborative work in global software development projects. The study explored the nature of collaboration, the patterns of collaborative behaviors in different tasks in computer science, and the impact of the tasks to the collaboration among students. Four different collaborative software development tasks were assigned to the globally distributes teams. The study used data from 230 students from five universities, namely Atilim University (Turkey), Middle East Technical University (Turkey), Universidad Tecnológica de Panamá (Panama), University of North Texas (US), and Middlesex University (UK). The findings involve the recommendations for building effective collaborative working environments and guidelines for building collaborative virtual communities

Exploring collaboration patterns among global software development teams.

This study examines communication behaviors in global software student teams. The authors of the paper characterize the types of communication behaviors that occur when student teams are engaged in a software development project. The authors present findings from a one-semester study that examined factors contributing to successful distributed programming interactions among students enrolled at the University of Atilim (Turkey), Universidad Tecnológica de Panamá, University of North Texas, and Middlesex University (UK). Using content and cluster analyses techniques, we identified distinct patterns of collaboration and examined how these patterns were associated with task, culture, GPA, and performance of collaborative teams. Our results suggest that communication patterns among global software learners may be related to task type, culture and GPA. It is hoped that these findings will lead to the development of new strategies for improving communication among global software teams

Using data analytics for collaboration patterns in distributed software team simulations: the role of dashboards in visualizing global software development patterns

This paper discusses how previous work on global software development learning teams is extended with the introduction of data analytics. The work is based on several years of studying student teams working in distributed software team simulations. The scope of this paper is twofold. First it demonstrates how data analytics can be used for the analysis of collaboration between members of distributed software teams. Second it describes the development of a dashboard to be used for the visualization of various types of information in relation to Global Software Development (GSD). Due to the nature of this work, and the need for continuous pilot studies, simulations of distributed software teams have been created with the participation of learners from a number of institutions. This paper discusses two pilot studies with the participation of six institutions from two different countries

Creating smarter teaching and training environments: innovative set-up for collaborative hybrid learning

This paper brings together previous work from a number of research projects and teaching initiatives in an effort to introduce good practice in setting up supportive environments for collaborative learning. The paper discusses prior use of social media in learning support, the role of dashboards for learning analytics in Global Software Development training, the use of optical head-mounted displays for feedback and the use of NodeXl visualization in managing distributed teams. The scope of the paper is to provide a structured approach in organizing the creation of smarter teaching and training environments and explore ways to coordinate learning scenarios with the use of various techniques. The paper also discusses challenges from integrating multiple innovative features in educational contexts. Finally the paper attempts to investigate the use of smart laboratories in establishing additional learning support and gather primary data from blended and hybrid learning pilot studies

Realistic applications of action languages for worklow management

TÜBİTAK EEEAG Proje01.05.2003Bu projenin iki amacı vardır. Bunlardan ilki, kendi geliştirdiğimiz iş akışı tanımlama dilini kullanarak tanımlanan iş akışlarını C eylem dilinde yazılmış program haline getiren bir çevirmen sisteminin geliştirilmesi, C eylem dilindeki bu programlar için model(ler) bulma, ve bu programların nasıl çalıştığını görmek için geçiş şemalarını çizen bir araç geliştirmedir. Projenin diğer bir amacı ise, iş akışı konusunda elde ettiğimiz bilgi ve deneyimlerle başka problemlerin çözümü için C eylem dilini ve onun getirdiği altyapıyı kullanmaktır. Bu amaçla, bir ön çalışma olarak, gerçek hayattan alınma bir trafik problemini C dilini kullanarak çözmüş bulunmaktayız. İş akışı yönetimi sistemleri kurumların otomasyon işlemleri için ümit vaad eden bir çözümdür. İş akışını modellemek ve çalıştırmak için pek çok ticari ürün mevcuttur. Ancak, iş akışı yönetim sistemlerinin kuramsal temelleri eksiktir. Diğer bir yandan, eylem dilleri, eylem sistemlerini tanımlama problemine en son yaklaşımlardan biridir. C dili, nedenselliğin açıklanması kuramını temel alan, bir yüksek düzey eylem tanımlama dilidir.İş akışı süreçlerinin biçimselleştirilmesi için yapılan pek çok öneriden biri eylem tanımlama dili C'nin kullanılmasıdır. Bu projede, iş akışı süreçlerinin eylem tanımlama dili C kullanılarak biçimselleştirilmesinde kullanılması amacı ile bir yüksek düzey iş akışı tanımlama dili olan WoDeL tasarlanmıştır ve WoDeL dilinden C diline bir çevirim tanımlanmıştır. Ayrıca, çevirim işinin otomatik olarak yapılabilmesini sağlamak için bir çevirim aracı geliştirilmiştir. Bu biçimselleştirme, iş akışı süreç tanımları üzerinden akıl yürütme işlemlerinin yapılabilmesine olanak sağlayan bir zemin oluşturmaktadır. Ayrıca, önerilen biçimselleştirme geliştirilerek iş akışı süreçlerinin doğrulanması ve en iyilenmesi amaçları için kullanılabilir. Ayrıca iş akışı sürecini görsel olarak izlemeye yarayan bir araç geliştirilmiştir. C diline çevrilen programları farklı model bulucularla denemek mümkündür

Temporal neuro-fuzzy MAR Algorithm for time series data in rule-based systems

This paper introduces a new neuro-fuzzy model for constructing a knowledge-base of temporal fuzzy rules obtained by MAR (Multivariate Autoregressive) Algorithm. The model described contains two main parts which are fuzzy-rule extraction and storage of them. The fuzzy rules are obtained from time series data using MAR Algorithm. Fuzzy linear function with fuzzy number coefficients are used. The extracted rules are fed into the temporal fuzzy multilayer feedforward neural network

Hierarchical behavior categorization using correlation based adaptive resonance theory

This paper introduces a new model for robot behavior categorization. Correlation based adaptive resonance theory (CobART) networks are integrated hierarchically in order to develop an adequate categorization, and to elicit various behaviors performed by the robot. The proposed model is developed by adding a second layer CobART network which receives first layer CobART network categories as an input, and back-propagates the matching information to the first layer networks. The first layer CobART networks categorize self-behavior data of a robot or an object in the environment while the second layer CobART network categorizes the robot's behavior with respect to its effect on the object. Experiments show that the proposed model generates reasonable categorization of behaviors being tested. Moreover, it can learn different forms of the behaviors, and it can detect the relations between them. In essence, the model has an expandable architecture and it contains reusable parts. The first layer CobART networks can be integrated with other CobART networks for another categorization task. Hence, the model presents a way to reveal all behaviors performed by the robot at the same time

Supervised Learning in Football Game Environments Using Artificial Neural Networks

Game industry has become one of the sectors that commonly use artificial intelligence. Today, most of the game environments include artificial intelligence agents to offer more challenging and entertaining gameplay experience. Since it gets harder to develop good agents as games become more complex, machine learning methods have started to be used in some notable games to shorten the development process of agents and to improve their quality. Popularity of machine learning applications in game environments has increased in the last decades. Supervised learning methods are applied to develop artificial intelligence agents that play a game like human players by imitating them. The imitating agents can either play the role of opponents or play on behalf of the real players when they are absent. The purpose of this study is to develop imitating agents fir a popular online game, namely HaxBall. ilaxBall is a two dimensional football game with fully observable, continuous, and real-time game environment