139585 research outputs found
Sort by
N-Sum Box : An Abstraction for Linear Computation over Many-to-one Quantum Networks
No full textLinear computations over quantum many-to-one communication networks offer opportunities for communication cost improvements through schemes that exploit quantum entanglement among transmitters to achieve superdense coding gains, combined with classical techniques such as interference alignment. The problem becomes much more broadly accessible if suitable abstractions can be found for the underlying quantum functionality via classical black box models. This work formalizes such an abstraction in the form of an “ N -sum box”, a black box generalization of a two-sum protocol of Song et al . with recent applications to N -server private information retrieval. The N -sum box has a communication cost of N qudits and classical output of a vector of N q -ary digits linearly dependent (via an N × 2 N transfer matrix) on 2 N classical inputs distributed among N transmitters. We characterize which transfer matrices are feasible by our construction, both with and without the possibility of additional locally invertible classical operations at the transmitters and receivers. Furthermore, we provide a sample application to Cross-Subspace Alignment (CSA) schemes to obtain efficient instances of Quantum Private Information Retrieval (QPIR) and Quantum Secure Distributed Batch Matrix Multiplication (QSDBMM). We first describe N -sum boxes based on maximal stabilizers and we then consider non-maximal-stabilizer-based constructions to obtain an instance of Quantum Symmetric Private Information Retrieval.Peer reviewe
Supervised Learning of the Optimal Objective Function Value in Chemical Production Scheduling
No full textPublisher Copyright: © 2025 The Authors. Published by American Chemical Society.Mixed-integer programming (MIP) can be used to formulate and solve complex production scheduling problems in the field of process systems engineering. However, the solution of MIP models may require a long computing time due to the combinatorial complexity of the problems. In this work, we propose supervised learning models to predict the optimal objective function value on four classes of scheduling problems, which can be useful in a number of settings. To improve the accuracy of the prediction models, we device a number of machine learning features based on the instance parameters. The studied objective functions are cost and makespan minimization. Based on the results, the prediction accuracy is high─the coefficients of determination with the best prediction models are r2 > 0.97 on the four classes of problems. These predictions allow us to predict how different problem features (e.g., new orders or disturbances) affect the optimal objective function value.Peer reviewe
Euclid preparation. LIX. Angular power spectra from discrete observations
No full textPublisher Copyright: © The Authors 2025.In this paper we present the framework for measuring angular power spectra in the Euclid mission. The observables in galaxy surveys, such as galaxy clustering and cosmic shear, are not continuous fields, but discrete sets of data, obtained only at the positions of galaxies. We show how to compute the angular power spectra of such discrete data sets, without treating observations as maps of an underlying continuous field that is overlaid with a noise component. This formalism allows us to compute the exact theoretical expectations for our measured spectra, under a number of assumptions that we track explicitly. In particular, we obtain exact expressions for the additive biases ('shot noise') in angular galaxy clustering and cosmic shear. For efficient practical computations, we introduce a spin-weighted spherical convolution with a well-defined convolution theorem, which allows us to apply exact theoretical predictions to finite-resolution maps, including HEALPix. When validating our methodology, we find that our measurements are biased by less than 1% of their statistical uncertainty in simulations of Euclid's first data release.Peer reviewe
Dual-Polarized Wideband Filtering Antenna Array Based on Stacked-PCB Structure
No full textPublisher Copyright: © 2020 IEEE.This paper investigates a thin low-pass filtering antenna array based on dual-polarized Vivaldi elements. The low-pass filtering in the antenna elements reduces the requirement for the front-end filtering between the antenna and the microwave electronics, resulting in improved overall out-of-band suppression, size reduction, and lower cost. The array employs a novel stacked-PCB structure, where simple two-sided PCBs are stacked on top of each other. The via-connected metal layers of all PCBs form a tapered slotline along the surface normal of the PCBs. The filtering effect is realized by corrugating the tapered slotlines, which provides effective, space-saving integration of the filters that fit into a half-wavelength lattice. According to unit-cell simulations, the proposed antenna array operates at 6-18.5 GHz, and the stopband extends from 21 GHz to 37 GHz. The antenna array provides a -10-dB active reflection coefficient (ARC) with beam-steering angles within ±60° in E- and D-planes, and -6 dB within ±55° in the H-plane. At stopband frequencies, the attenuation with respect to simulated total efficiency is at least 20 dB. The operation of the proposed antenna array is confirmed by measurements of an 11× 12 antenna array prototype, which show that the gain suppression level in the stopband is more than 30 dB up to 37 GHz, and more than 20 dB up to 40 GHz.Peer reviewe
A Multilinear Johnson–Lindenstrauss Transform
No full textThe Johnson-Lindenstrauss family of transforms constitutes a key algorithmic tool for reducing the dimensionality of a Euclidean space with low distortion of distances. Rephrased from geometry to linear algebra, one seeks to reduce the dimension of a vector space while approximately preserving inner products. We present a multilinear generalization of this bilinear (inner product) setting that admits both an elementary randomized algorithm as well as a short proof of correctness using Orlicz quasinorms.Peer reviewe
The growth in the gamification of digital consumer application services: a case analysis of Duolingo, Fitbit and Starbucks
No full textThe main objectives of this research project were to look at the impact that gamification has had on digital consumer application services thus far, and the direction which gamification as a business tool is likely to take in the future. For this paper, an examination of the already available academic and non-academic literature related to gamified features in the representative case studies of Duolingo, Fitbit and Starbucks, was completed, making use of primarily secondary qualitative data in doing so. The conclusions drawn from the case analysis of the representative case studies largely shaped the focus of this paper. From this paper, it can be seen that the use of gamified features has in the case studies focused on, generally been advantageous in increasing user engagement and user retention, with the case digital consumer application services examined all being relatively successful in their respective industries. The use of gamification is generally aimed at fulfilling the three primary consumer psychological needs of autonomy, competence and relatedness, as outlined in the SSMMD framework, a key part of the conceptual framework for this research project. Gamified features within digital consumer application services are geared in most cases, toward achieving one or more of these psychological consumer needs, with notable examples being the use of inservice rewards systems, medals, achievements and streaks, along with streamlined UI features
Application of 3D Convolutional Neural Networks in the Analysis of Wafer Data
No full textMEMS-piikiekkojen manuaalinen laadunvalvonta on työlästä ja altista ihmisen tekemille virheille. Lähes jokaisessa teollisessa prosessissa valmistetussa piikiekossa havaitaan ainakin muutama neliömikrometrien kokoinen vika. Piikiekossa on yli 3300 anturia, jotka sahataan erilleen vasta valmistuksen jälkeen, joten satunnaiset anturikohtaiset viat eivät vielä tarkoita, että koko komponentti olisi viallinen.
Tämän kandidaatintutkielman tavoitteena on luoda Murata Electronics Oy:n toimeksiannosta pohjaa ratkaisulle, jossa piikiekot esitetään kaksi- tai kolmiulotteisina vektoreina niiden pääpiirteet säilyttäen. Piikiekkoaineiston ulottuvuuden alentaminen tehdään pääkomponenttianalyysillä (PCA) sekä 3D konvoluutioneuroverkosta (CNN) eristetyllä enkooderilla, ja saatuja tuloksia vertaillaan. Alempiulotteinen esitys mahdollistaa piikiekkojen vertailun tulkitsemalla kuvaa, jossa samankaltaiset piikiekot ryhmittyvät. Tutkielmassa halutaan myös selvittää, kuinka teollista aineistoa tulee esikäsitellä parhaan tuloksen saamiseksi. Aineiston esitys alemmassa ulottuvuu dessa pyritään klusteroimaan todenmukaisesti, eli ryhmittelemään ohjaamattomasti piikiekkojen kategorioihin.
Kun laadunvalvonta saa tuekseen piikiekon pääpiirteitä kuvaavan vektorin, piikiekkoa voidaan arvioida tukeutuen menneisyydessä valmistettujen piikiekkojen vektoritietokantaan. Tarkka viantunnistus johtaa nopeampiin jatkotoimenpiteisiin, jotka tukevat koko tuotantolinjaa.
Tulosten perusteella molemmat mallit ulottuvuuden alentamiseen hukkasivat paljon tietoa. Pääkomponenttianalyysin lineaarinen piirteiden muunnos todettiin epätarkaksi ja metodi hylättiin. Enkooderi löysi aineistosta epälineaarisia riippuvuuksia ja onnistui erottelemaan joitakin piikiekkojen valmistusvaiheen yleisvikoja. Enkooderin todettiin olevan herkkä, sillä sen tekemässä muunnoksessa oli selkeitä eroja konvoluutioneuroverkon koulutuskertojen välillä. Stabiilimman mallin saavuttamiseksi tarvitaan merkittävästi enemmän dataa CNN:n koulutusvaiheeseen. Klusterointi oli liian yleistävää, mutta sen tulos on hyödyllinen todellisten ryhmittymien manuaalisessa etsinnässä.Manual quality control of MEMS wafers is labor-intensive and prone to human error. In almost every industrially manufactured wafer, at least a few square-micrometer sized defects are observed. A wafer contains over 3300 sensors, which are only separated after production, meaning that random sensor-specific defects do not necessarily render the entire component faulty.
The aim of this bachelor’s thesis is to lay the groundwork for a solution assigned by Murata Electronics, where wafers are represented as two- or three-dimensional vectors while preserving their key features. Dimension reduction of the wafer data is done using principal component analysis (PCA), and an encoder extracted from a 3D convolutional neural network (CNN). The results obtained are compared. The lower-dimensional representation enables the comparison of wafers by interpreting a visualization where similar wafers are grouped together. The thesis also seeks to determine how the industrial wafer data should be preprocessed to achieve the best results. One goal is also to cluster the data in the lower-dimensional representation accurately, that is grouping the wafers into categories in an unsupervised manner. When quality control is supported by a vector representing the key features of a wafer, the wafer can be categorized by comparing it to a vector database of previously manufactured wafers. Accurate defect detection enables faster follow-up actions, which benefit the entire production line.
The results showed that both models for dimension reduction lost a significant amount of information. The linear feature transformation of principal component analysis was found to be inaccurate, leading to the method being discarded. The encoder identified nonlinear dependencies in the data and succeeded in distinguishing some common manufacturing defects in the wafers. However, the encoder was found to be sensitive, as the transformations it produced showed noticeable variations between different training iterations of the convolutional neural network. Achieving a more stable model will require significantly more data for CNN training. The clustering was found to be overly generalizing, but its output is helpful in the manual identification of actual grouping
From Waste to New Fiber: Knowledge and Material Flows in a Circular Textile Ecosystem
No full text| openaire: EC/H2020/101000559/EU//New CottonIt is now known that transitioning from a linear to a circular economy is vital for achieving sustainability in the textile and fashion industries. This transition involves not only closing material loops and incorporating waste into business models but also establishing circular ecosystems characterized by flows of material, knowledge, and economic value. Circular ecosystems involve actors from previously disconnected industries and sectors, which presents new challenges in terms of knowledge exchange and collaboration. This chapter investigates the knowledge and material flows in a European ecosystem that produces circular garments from a chemically regenerated cellulosic fiber. Our findings highlight the interdependence of material and knowledge flows in the ecosystem, with the textile material itself serving as an important carrier of knowledge. We examine knowledge flows related to learning and ecosystemic collaboration, as well as to the material, technological, and business knowledge in circular innovation. We found that knowledge flows across ecosystem boundaries were essential for promoting a broader circular transition among both industry and consumers and for facilitating a dialogue with European policymakers. Understanding knowledge and material flows in circular textile ecosystems is crucial for the further development of circular ecosystems and the planning of the related policy and support measures.Peer reviewe
The declining price anomaly: A study on Finnish art auctions
No full textThis thesis studies a phenomenon called the declining price anomaly, and whether there is any evidence of such anomaly in a sample of Finnish art auctions. I start the thesis by examining prior studies in which the prices of auctioned items have been reported to systematically decline as the auction progresses; the observation has been deemed anomalous, as auction theory predicts that the prices should, on average, remain constant throughout the auction. The anomaly has been identified in auctions of both homogeneous and heterogeneous goods. I proceed by presenting explanations that have been suggested to explain the anomaly. Some explanations provide a theoretical framework in which rational and predictable behaviour causes the prices to decline, whereas other theories seek explanation from factors such as the way auctions are organized or non-optimal and irrational behaviour of the par- ticipants.
I proceed by examining literature focusing on measuring the implicit prices of any measurable attributes of pieces of art. Such studies are carried out by utilizing the hedonic regression method, in which the art prices are explained with the measurable characteristics of the piece in question, such as the measurements and technique. These studies typically utilize data from auctions, as in such settings the prices and measurable attributes are easily observable. Despite various samples and settings, there are certain regularities in the findings: for example, the prices appear to be typically increasing with the size of the artwork.
Finally, I conduct my own study in which I examine a sample of Finnish art auctions to study if there is any trace of the declining price anomaly. No trace of the anomaly is found; furthermore, it seems that the regularities typically found in earlier studies are not present in my sample
Kohti digitaalista vesivarojen hallintoa – Digitalisaation rooli vesivarojen alalla Suomessa
No full textDigitalization is expected to address many pressing challenges in the water resources field including climate change, pollution, and overexploitation. However, limited research has been conducted on the actual role of digitalization and its possibilities and threats in relation to water resources management and governance.
The aim of this thesis was to explore the state of digitalization in the water field through the following research questions: 1) How is digitalization understood in the water field, 2) How are the positive and negative effects of digitalization considered, and 3) How should digitalization be developed in the water resources field. The research methods included a literature review, interviews with three water field professionals, and a policy analysis of digitalization and water resource policies. Possibilities and threats of digitalization were identified through the interviews and categorized.
The findings indicate that digitalization lacks a universally accepted definition. The term is interpreted differently by individuals and is used rather inconsistently in literature and policy documents. Therefore, it is essential to clearly define digitalization to ensure a shared understanding of its desired outcomes. Developing a definition suitable for water field should also be considered.
Based on the interview results, the key possibilities of digitalization included data gathering, technological methods, availability, and efficiency. The key threats of digitalization, based on the interviews, were security, accessibility, data accuracy, usability, and continuity. Comparing these results to the key possibilities and threats found from the literature, the major differences were that sustainability as a threat was emphasized more in the literature while interviewees emphasised more also data gathering and technological methods as possibilities and data accuracy and continuity as potential threats.
Digitalization should be developed considering both the possibilities and threats, that the development is intentional towards a desired direction but also considers the threats. Further research is needed to understand digitalization’s affects in the water sector context comprehensively.Digitalisaation odotetaan vastaavan moniin keskeisiin haasteisiin vesialalla, kuten ilmastonmuutokseen, saastumiseen sekä resurssien ylikäyttöön. Digitalisaation roolista tai sen uhista ja mahdollisuuksista ei kuitenkaan ole juurikaan tehty tutkimusta vesialalla. Tämän tutkielman tavoitteena oli tarkastella digitalisaation nykytilaa vesialalla seuraavien tutkimuskysymysten avulla: 1) Miten digitalisaatio ymmärretään vesialalla, 2) Miten digitalisaation positiivisia ja negatiivisia vaikutuksia huomioidaan, ja 3) Miten digitalisaatiota tulisi kehittää vesialalla. Tutkimusmenetelminä oli kirjallisuuskatsaus, haastattelut kolmen vesialan ammattilaisen kanssa sekä politiikka-analyysi digitalisaatioon ja vesivaroihin liittyvistä laeista, strategioista ja säädöksistä. Haastattelujen perusteella tunnistettiin digitalisaation mahdollisuuksia ja uhkia.
Tulokset osoittivat, että digitalisaatiolle ei ole yhtä yleisesti hyväksyttyä määritelmää. Termiä tulkitaan eri tavoin ja sitä käytetään epäjohdonmukaisesti kirjallisuudessa sekä politiikkatoimissa. Olisi siis tärkeää määritellä digitalisaatio selkeästi, jotta varmistetaan yhteinen ymmärrys halutuista lopputuloksista. Myös vesialalle sopivan määritelmän luomista tulisi harkita.
Haastattelujen perusteella keskeiset mahdollisuudet ovat datan keruu, teknologiset menetelmät, saatavuus ja tehokkuus. Keskeisiksi uhiksi tunnistettiin turvallisuus, saavutettavuus, datan oikeellisuus, käytettävyys sekä jatkuvuus. Näitä tuloksia verratessa kirjallisuudesta löydettyihin mahdollisuuksiin ja uhkiin huomattiin, että kestävyys uhkana korostui kirjallisuudessa huomattavasti haastatteluja enemmän, kun taas haastatteluissa datan keruu ja teknologiset metodit painottuivat mahdollisuuksina sekä datan oikeellisuus ja jatkuvuus uhkina kirjallisuutta enemmän.
Digitalisaation kehityksessä tulisi ottaa huomioon sekä sen mahdollisuudet että uhat, jotta kehityksen suunta on tarkoituksenmukainen huomioiden, että uhat eivät toteudu. Lisätutkimusta tarvitaan, jotta digitalisaation vaikutuksia vesialalla voidaan ymmärtää kokonaisvaltaisemmin