Surveying human habit modeling and mining techniques in smart spaces

A smart space is an environment, mainly equipped with Internet-of-Things (IoT) technologies, able to provide services to humans, helping them to perform daily tasks by monitoring the space and autonomously executing actions, giving suggestions and sending alarms. Approaches suggested in the literature may differ in terms of required facilities, possible applications, amount of human intervention required, ability to support multiple users at the same time adapting to changing needs. In this paper, we propose a Systematic Literature Review (SLR) that classifies most influential approaches in the area of smart spaces according to a set of dimensions identified by answering a set of research questions. These dimensions allow to choose a specific method or approach according to available sensors, amount of labeled data, need for visual analysis, requirements in terms of enactment and decision-making on the environment. Additionally, the paper identifies a set of challenges to be addressed by future research in the field

Current State of Information Security Research In IS

The importance of information security in a pervasive networked environment is undeniable, yet there is a lack of research in this area. In this study we conduct a comprehensive survey of the information security articles published in leading IS journals. We then compared the research themes with those of the IBM Information Security Capability Reference Model

The complexity of extracting knowledge in Big Data / Rozianiwati Yusof...[et al.]

Big data is extremely large data set data in the range of exabytes and the volume of data cannot be processed efficiently with the traditional technology in term of storing, manage and process. With the technologies appear, big data has attracted many researchers to extract knowledge from it. The knowledge can be produced in making a decision. However, there are some issues existed in extracting the important knowledge such as in storing the data, managing the data and processing the data in extracting useful information since its relate with volume, velocity and variety. Therefore, this paper is attempting to list all the possible knowledge that can be extracted from big data as well as discuss the previous researches in knowledge extraction from the huge amount of data. The problem in extracting importantknowledge will be examined thoroughly and by identifying the significant problems in knowledge extraction the best knowledge from big data could be revealed. The techniques in analysing big data will be also discussed in the next sectio

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Design and Verification of Association Rules Application Solution for Determination of the Relationship between Product Groups

Import 04/11/2015Téma diplomové práce se týká techniky dolování dat – dolování asociačních pravidel v hierarchické struktuře pro potřeby analýzy nákupního košíku a je prakticky zaměřena na návrh vylepšení zavedeného procesu dolování dat. V úvodní části práce jsou rozebírána teoretická východiska potřebná pro praktickou část. Praktická část zahrnuje v první řadě analýzu existujícího procesu dolování a návrhy na zlepšení tohoto procesu. Část návrhu je také ověřena na reálných datech. Závěr práce patří zhodnocení navrhovaných řešení a uvedení námětu pro další práci.Diploma thesis is about a certain data mining technique – multilevel association rules mining for market basket analysis and the topic is focused on proposal for improvements of the established data mining process. In the introductory part, the theoretical basics needed for the practical part are discussed. Practical part contains analysis of the existing data mining process and proposals for the improvements of this process. Part of the proposal is also verified on a real data set. Conclusion of the thesis is devoted to the review of proposed improvements and motives for further work.157 - Katedra systémového inženýrstvívýborn

Multilevel Object Tracking in Wireless Multimedia Sensor Networks for Surveillance Applications Using Graph-Based Big Data

https://ieeexplore.ieee.org/document/8721634/keywords#keywordsWireless Multimedia Sensor Networks (WMSN), for object tracking, have been used as an emerging technology in different application areas, such as health care, surveillance, and traffic control. In surveillance applications, sensor nodes produce data almost in real-time while tracking the objects in a critical area or monitoring border activities. The generated data is generally treated as big data and stored in NoSQL databases. In this paper, we present a new object tracking approach for surveillance applications developed using a big data model based on graphs and a multilevel fusion. Our approach consists of three main steps: intra-node fusion, inter-node fusion, and object trajectory construction. Intra-node fusion exploits the detection and tracking of objects in each sensor, while inter-node fusion uses spatio-temporal data and neighboring sensors. Then, the fused data of all sensor nodes are combined to construct global trajectories of the detected objects in the monitored area on the WMSN. We implemented a prototype system and evaluated the performance of the proposed approach with both a real dataset and a synthetic dataset. The results of our experiments on the two datasets show that the use of third-level fusion in addition to inter-node and intra-node fusions provides significantly better performance for object tracking in the WMSN applications