Search results for "algoritmit"
showing 10 items of 118 documents
Peer-to-peer cooperative GNSS-based localization for stationary reference nodes in wireless sensor networks
2017
Most localization algorithms in wireless sensor networks rely on a few reference nodes with known locations to estimate the locations of unknown nodes. The locations of reference nodes can be either manually configured or, more practically, obtained by means of some satellite-based positioning system(s). However, satellite-based locations may be inaccurate and imprecise, which results in reduced location accuracy of localization algorithms. This paper proposes a peer-to-peer cooperative GNSS-based localization algorithm for stationary reference nodes to improve their relative location accuracy and precision. The algorithm applies simple statistical methods and GNSS-based information from mu…
Do Randomized Algorithms Improve the Efficiency of Minimal Learning Machine?
2020
Minimal Learning Machine (MLM) is a recently popularized supervised learning method, which is composed of distance-regression and multilateration steps. The computational complexity of MLM is dominated by the solution of an ordinary least-squares problem. Several different solvers can be applied to the resulting linear problem. In this paper, a thorough comparison of possible and recently proposed, especially randomized, algorithms is carried out for this problem with a representative set of regression datasets. In addition, we compare MLM with shallow and deep feedforward neural network models and study the effects of the number of observations and the number of features with a special dat…
A New Paradigm in Interactive Evolutionary Multiobjective Optimization
2020
Over the years, scalarization functions have been used to solve multiobjective optimization problems by converting them to one or more single objective optimization problem(s). This study proposes a novel idea of solving multiobjective optimization problems in an interactive manner by using multiple scalarization functions to map vectors in the objective space to a new, so-called preference incorporated space (PIS). In this way, the original problem is converted into a new multiobjective optimization problem with typically fewer objectives in the PIS. This mapping enables a modular incorporation of decision maker’s preferences to convert any evolutionary algorithm to an interactive one, whe…
Dataa näkyvissä: Läpinäkyvyys algoritmien ja datan journalistisessa hyödyntämisessä
2021
Läpinäkyvyyden käsite on noussut keskeiseksi viestinnän, median ja politiikan tutkimuksessa sekä viestinnän ja politiikan käytäntöjen eettisessä arvioinnissa. Läpinäkyvyyttä on esitetty keinoksi ylläpitää ja kasvattaa luottamusta journalistista työtä ja sen tuotteita kohtaan interaktiivisessa media- ja viestintäympäristössä. Tiedontuotannon ja päätöksenteon perustuessa yhä enemmän dataan ja sen prosessointiin läpinäkyvyys on noussut keskeiseksi käsitteeksi myös algoritmisen päätöksenteon kohdalla. Tässä artikkelissa tarkastelemme läpinäkyvyyden roolia dataa ja algoritmeja sekä journalismia koskevassa keskustelussa ja esitämme mahdollisuuksia dataan ja algoritmeihin tukeutuvan journalismin l…
Decoding Musical Training from Dynamic Processing of Musical Features in the Brain
2018
AbstractPattern recognition on neural activations from naturalistic music listening has been successful at predicting neural responses of listeners from musical features, and vice versa. Inter-subject differences in the decoding accuracies have arisen partly from musical training that has widely recognized structural and functional effects on the brain. We propose and evaluate a decoding approach aimed at predicting the musicianship class of an individual listener from dynamic neural processing of musical features. Whole brain functional magnetic resonance imaging (fMRI) data was acquired from musicians and nonmusicians during listening of three musical pieces from different genres. Six mus…
Alkulukutesteistä
2016
Tämän tutkielman tavoitteena on esittää tunnetuimmat alkulukutestit niin matemaattiselta perustoiltaan kuin käytännön toteutuksiltaan ohjelmakoodin muodossa. Alkulukutestit jaotellaan yleisesti deterministisiin ja probabilistisiin testeihin; deterministiset testit antavat täysin varman vastauksen, mutta ovat suurille luvuille huomattavasti probabilistia testejä hitaampia. Probabilistiset testit ovat nopeita tehdä, mutta saattavat antaa väärän vastauksen. Testien suoritusaikaa mitataan karkeasti niiden suorittamiseksi vaadittavien laskutoimitusten lukumääarällä. Tutkielmassa käsitellään deterministisistä testeistä jakolaskumenetelmä, Wilsonin lause, Prothin testi, Lucasin ja Lehmerin testi j…
Evolutionary Algorithms and Metaheuristics : Applications in Engineering Design and Optimization
2018
The Datafication of Hate: Expectations and Challenges in Automated Hate Speech Monitoring.
2020
Laaksonen, S-M.; Haapoja, J.; Kinnunen, T., Nelimarkka, M. & Pöyhtäri, R. (2020, accepted). . Frontiers in Big Data: Data Mining and Management / Critical Data and Algorithm Studies. doi:10.3389/fdata.2020.00003 Hate speech has been identified as a pressing problem in society and several automated approaches have been designed to detect and prevent it. This paper reports and reflects upon an action research setting consisting of multi-organizational collaboration conducted during Finnish municipal elections in 2017, wherein a technical infrastructure was designed to automatically monitor candidates' social media updates for hate speech. The setting allowed us to engage in a 2-fold investiga…
Impact of chaotic dynamics on the performance of metaheuristic optimization algorithms : An experimental analysis
2022
Random mechanisms including mutations are an internal part of evolutionary algorithms, which are based on the fundamental ideas of Darwin's theory of evolution as well as Mendel's theory of genetic heritage. In this paper, we debate whether pseudo-random processes are needed for evolutionary algorithms or whether deterministic chaos, which is not a random process, can be suitably used instead. Specifically, we compare the performance of 10 evolutionary algorithms driven by chaotic dynamics and pseudo-random number generators using chaotic processes as a comparative study. In this study, the logistic equation is employed for generating periodical sequences of different lengths, which are use…
On optimal deployment of low power nodes for high frequency next generation wireless systems
2018
Recent development of wireless communication systems and standards is characterized by constant increase of allocated spectrum resources. Since lower frequency ranges cannot provide sufficient amount of bandwidth, new bands are allocated at higher frequencies, for which operators resort to deploy more base stations to ensure the same coverage and to utilize more efficiently higher frequencies spectrum. Striving for deployment flexibility, mobile operators can consider deploying low power nodes that could be either small cells connected via the wired backhaul or relays that utilize the same spectrum and the wireless access technology. However, even though low power nodes provide a greater fl…