Search results for "hinta"
showing 10 items of 114 documents
Application of a Knowledge Discovery Process to Study Instances of Capacitated Vehicle Routing Problems
2020
Vehicle Routing Problems (VRP) are computationally challenging, constrained optimization problems, which have central role in logistics management. Usually different solvers are being developed and applied for different kind of problems. However, if descriptive and general features could be extracted to describe such problems and their solution attempts, then one could apply data mining and machine learning methods in order to discover general knowledge on such problems. The aim then would be to improve understanding of the most important characteristics of VRPs from both efficient solution and utilization points of view. The purpose of this article is to address these challenges by proposi…
Data-driven value creation in digitalizing public service
2022
Data has become an important asset in value creation. Organizations are dealing with a huge amount of data generated on different platforms. In dynamic environments, public organizations have an opportunity to make innovations by applying innovative technologies, implementing big data, and enabling data analytics capabilities that can create value. Evidence from the literature shows that organizations need data analytics capabilities to achieve data-driven value creation. In this chapter, based on a literature review and case example, the aim is to present the factors enabling public innovations from the big data analytics perspective; a theoretical framework for data-driven value creation …
Eettiset ongelmat massadatan ja tiedonlouhinnan hyödyntämisessä
2016
Niin julkiset kuin yksityisetkin organisaatiot keräävät ja hyödyntävät yhä enemmän dataa osana toimintaansa. Big data eli massadata on keskeinen teknologia suurten datamäärien hallitsemiseksi. Massadataa analysoidaan puolestaan usein tiedonlouhinnan menetelmin. Molempien innovaatioiden suosio on kasvanut trendinomaisesti ja niiden käytön ennustetaan yleistyvän jatkossakin. Massadataa ja tiedonlouhintaa on hyödynnetty myös arveluttaviin tarkoituksiin. Julkisuudessa on ollut esillä tapauksia, joissa yritykset ovat kohdentaneet markkinointiaan selvittämällä arkaluonteista tietoa asiakkaistaan. Tämä yhdistettynä ajatukseen uusiin teknologioihin liittyvistä käytäntötyhjiöistä toimii motiivina ai…
Incentive Mechanism for Edge-Computing-Based Blockchain
2020
Blockchain has been gradually applied to different Internet of Things (IoT) platforms. As the efficiency of the blockchain mainly depends on the network computing capability, how to make sure the acquisition of the computational resources and participation of the devices would be the driving force. In this work, we focus on investigating incentive mechanism for rational miners to purchase the computational resources. A edge computing-based blockchain network is considered, where the edge service provider (ESP) can provide computational resources for the miners. Accordingly, we formulate a two-stage Stackelberg game between the miners and ESP. The aim is to investigate Stackelberg equilibriu…
Semantic place recognition for context aware services
2012
Extracting the meaning of the most significant places, which are frequently visited by a mobile user, is a relevant problem in mobile computing. Predicting semantic meaning of such places is useful in many areas. The problem of place semantic annotation of a user location can be challenging for service providers. Awareness of user activities is very important for development of personalized applications, which can be used in health care systems, living systems, etc. Predicting location of mobile users not only enables development of high quality location-based services and applications, but also improves resource reservation in wireless networks. In this research several solutions for seman…
Incentive Mechanism for Edge Computing-Based Blockchain: A Sequential Game Approach
2022
The development of the blockchain framework is able to provide feasible solutions for a wide range of Industrial Internet of Things (IIoT) applications. While the IIoT devices are usually resource-limited, how to make sure the acquisition of computational resources and participation of the devices will be the driving force to realize blockchain. In this work, an edge computing-based blockchain framework is considered, where multiple edge service providers (ESPs) can provide computational resources to the IIoT devices. We focus on investigating the trading between the devices and ESPs, where ESPs are the sellers and devices are the buyers. A sequential game is formulated and by exploring the…
Dimensionality reduction framework for detecting anomalies from network logs
2012
Dynamic web services are vulnerable to multitude of intrusions that could be previously unknown. Server logs contain vast amounts of information about network traffic, and finding attacks from these logs improves the security of the services. In this research features are extracted from HTTP query parameters using 2-grams. We propose a framework that uses dimensionality reduction and clustering to identify anomalous behavior. The framework detects intrusions from log data gathered from a real network service. This approach is adaptive, works on the application layer and reduces the number of log lines that needs to be inspected. Furthermore, the traffic can be visualized. peerReviewed
Mining Maximal Frequent Patterns in Transactional Databases and Dynamic Data Streams: A Spark-based Approach
2018
Mining maximal frequent patterns (MFPs) in transactional databases (TDBs) and dynamic data streams (DDSs) is substantially important for business intelligence. MFPs, as the smallest set of patterns, help to reveal customers’ purchase rules and market basket analysis (MBA). Although, numerous studies have been carried out in this area, most of them extend the main-memory based Apriori or FP-growth algorithms. Therefore, these approaches are not only unscalable but also lack parallelism. Consequently, ever increasing big data sources requirements cannot be met. In addition, mining performance in some existing approaches degrade drastically due to the presence of null transactions. We, therefo…
Anomaly-based online intrusion detection system as a sensor for cyber security situational awareness system
2016
Almost all the organisations and even individuals rely on complex structures of data networks and networked computer systems. That complex data ensemble, the cyber domain, provides great opportunities, but at the same time it offers many possible attack vectors that can be abused for cyber vandalism, cyber crime, cyber espionage or cyber terrorism. Those threats produce requirements for cyber security situational awareness and intrusion detection capability. This dissertation concentrates on research and development of anomaly-based network intrusion detection system as a sensor for a situational awareness system. In this dissertation, several models of intrusion detection systems are devel…
Propaganda Barometer : A Supportive Tool to Improve Media Literacy Towards Building a Critically Thinking Society
2018
To smartly consume a huge and constantly growing volume of information, to identify fake news and resist propaganda in the context of Information Warfare, to improve personal critical thinking capabilities and increase media literacy, people require supportive environment with sophisticated technology facilitated tools. With rapid development of media, widespread popularity of social networks and fast growing amount of information distribution channels, propaganda and information warfare enter an absolutely new digital technology supported cyber era. Propaganda mining is not a trivial and very time consuming process for human. And, as with any new technology, human need certain time to unde…