The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Exploratory learning environments (ELEs) promote a view of learning that encourages students to construct and/or explore models and observe the effects of modifying their parameters. The freedom given to learners in this exploration context leads to a variety of learner approaches for constructing models and makes modelling of learner behavior a challenging task. To address this issue, we propose...
Attack propagation models within honeypot systems aim at providing insights about attack strategies that target multiple honeypots, rather than analyzing attacks on each honeypot separately. Traditional attack propagation models focus on building a single probabilistic model. This modeling approach may be misleading, since it does not take into consideration contextual information such as the country...
Being a complex topic Internet of Things (IoT) involves multiple disciplines and approaches. In this paper an initial overview of the modeling techniques within the IoT by the Information Systems researchers is provided. These descriptive results offer a basis for discussion about the research topics that are important in IoT for the Information Systems Research community as well as the first overview...
For image retrieval and caption generation, this paper considers a multimodal representation that associates image with its text description (caption) by defining a neural language model as the conditional probability of the next word given both n past words in a caption and the image that the caption describes. To address the data sparsity problem, the use of the Kneser-Ney smoothing and skip-gram...
Software Testing is an approach to ensuring the quality of software systems. Testing of safety-critical systems often requires conformance to certain code coverage criteria, including for example, in aviation, Modified Condition/Decision Coverage (MC/DC). In some situations, however, access to the actual code may be restricted with black Box approaches, and testers may only be able to use models of...
Efficient query processing over a large amount of business process models is important for managing the business process model repository. The structural similarity between two process models is considered as the main measurement for ranking the process models for a given search model. Current business process query methods are inefficient since too many expensive computations of the graph edit distance...
Today's Enterprises exist in highly dynamic environment. While enterprise-architecture (EA) based models help in holistic treatment of enterprise aspects, they are static in nature and do not represent the complex dynamic behavior of enterprise as it evolves over time. Instead of relying on guideline for simulating EA models as in other approaches, we propose a comprehensive metamodel of system dynamics...
Few years ago, retailers started to employ self-service checkout terminals providing customers a choice to scan the barcodes on their own items and complete the purchase process without an interaction with retailer's staff. This study aimed to investigate factors which can have a significant impact on user's decision about how and when they will use the self-checkout unit. To understand customers'...
Individuals working as a team introduce team related issues such as interpersonal coordination, supervision, time, and task management which are influenced by nontechnical, cognitive and social skills of team members. In control room of complex systems and under high task load situations, teams of operators are solely responsible for the ultimate decision making and control; but incomplete information,...
Rating and recommendation systems have become a popular application area for applying a suite of machine learning techniques. Current approaches rely primarily on probabilistic interpretations and extensions of matrix factorization, which factorizes a user-item ratings matrix into latent user and item vectors. Most of these methods fail to model significant variations in item ratings from otherwise...
Although there is significant research and development into information security areas such as confidentiality and availability, scope remains for attention to the third fundamental security property: integrity. The Biba and Clark-Wilson models are still the most recognised for managing integrity of data in systems. After identifying several desirable extensions to the original ideas in these models,...
One of the main challenges in the development of traffic systems is to assure safety for all road users. Hence, especially expensive vehicles are equipped with advanced driver assistance systems (ADAS) that use data about the vehicle and information about objects in the proximity of the vehicle to execute the assistance function. These objects have to be detected by sensors and they have to be tracked...
Affective computing systems with situated or ambient intelligence could be extremely effective in various application scenarios. However, majority of the proposed systems have limited utility since either they are strictly context-sensitive or otherwise too general. In this paper, we report on building and evaluating a context-aware yet situation-adaptive Bayesian inference framework that predicts...
This paper is part of a research project which aims at developing a generic model specification on a conceptual layer in order to reduce the empirically observed high error rate of model-driven Decision Support Systems (DSS), typically based on multi-dimensional, spreadsheet-oriented models. Following the framework of Wand and Weber for conceptual modeling, this paper firstly presents basic elements...
Reliable recognition of activities from cluttered sensory data is challenging and important for a smart home to enable various activity-aware applications. In addition, understanding a user's preferences and then providing corresponding services is substantial in a smart home environment. Traditionally, activity recognition and preference learning were dealt with separately. In this work, we aim to...
Many applications such as telecommunication and commercial video broadcasting streams, computer systems logs, and web clicks are categorical or mixed-value data streams that exhibit context-dependency. Models that try to capture this context-dependency tend not to be scalable. This paper offers a solution to the scalability problem of these models by providing a method for generating them around relevant...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.