252 research outputs found
Transport as a new avenue for CV prevention in city dwellers: how to kill two birds with one stone?
No full textNeven, A (reprint author), Hasselt Univ, Transportat Res Inst IMOB, B-3590 Diepenbeek, Belgium.
[email protected]; [email protected]; [email protected]; [email protected]
Architect Neven Šegvić – Theoretical Works
No full textAutor članka bavi se istraživanjem opusa arhitekta Nevena Šegvića. U trijadi njegova djela – teorijski rad, projektantski rad, pedagoški rad – tekst obrađuje problematiku prvog segmenta. Analizom evidentiranih bibliografskih jedinica autor sagledava vrijednost pojedinačnoga djela unutar duktusa cjelokupnoga znanstveno-publicističkog djela. Verifikacijom i valorizacijom izlučnih radova te uspostavom stratifikacije elaborira se teza o postojanju pet problemsko-razvojnih faza teorijskog opusa arhitekta Nevena Šegvića.Within his work on the oeuvre of the architect Neven Šegvić, the author focuses in this paper on Šegvić’s theoretical work, as one of the three main subject areas of his career, the others being architectural design and teaching. The analysis of Šegvić’s bibliography provides a basis for a critical evaluation of each particular work and its positioning within the entire theoretical oeuvre. The analysis is followed by a stratification in which the author identifies five discrete development phases in Neven Šegvić’s theoretical work
Stratification of Neven Šegvić’s Architecture
No full textAutor članka bavi se istraživanjem opusa arhitekta Nevena Šegvića. U trijadi njegova djela – arhitektonski rad, teorijski rad, pedagoški rad – tekst obrađuje problematiku samo prvog segmenta. Primjenom kronološkoga kriterija očitavanja kataloga autor sagledava vrijednost pojedinačnoga djela unutar duktusa cjelovitoga stvaralačkog opusa. Verifikacijom i valorizacijom radova te uspostavom stratifikacije elaborira se teza o postojanju pet problemsko- -razvojnih faza arhitektonskog opusa Nevena Šegvića.This article is a study of Neven Šegvić’s architecture focusing on his architectural achievements as one of the three main subject areas of his work (along with his theory and teaching). The author evaluates each work within the entire collection through a chronological study of catalogues. Through the analysis and assessment of Šegvić’s works and stratification, the author elaborates his thesis of five development stages in Šegvić’s architectural career
Binary classification with adiabatic quantum optimization
No full textWe study the problem of supervised binary classification from the perspective of deploying adiabatic quantum optimization in training. A vast body of prior academic work consisting of both theoretical and numerical studies has indicated that quantum technology promises to provide computational power that may be fundamentally superior to any classical computing methods. Given the abundance of NP-hard optimization problems that naturally arise in learning, it is clear that machine learning can immensely benefit from such an optimization tool. We describe a series of increasingly complex designs that result in computationally hard training problems of combinatorial nature. In return for accepting classical computational hardness, we retain theoretical properties such as maximal sparsity and robustness to label noise, which are otherwise sacrificed by convex methods for the sake of computational efficiency and sound theoretical footing. In order to be compatible with emerging quantum hardware technology, we formalize the training problem as quadratic unconstrained binary optimization. Our initial investigations focus on a simple training formulation with non-convex regularization that conforms to the architecture of existing quantum hardware and makes frugal use of a limited number of available physical qubits. Next, we extend this baseline formulation to a scalable algorithm, QBoost, which is able to train incrementally large-scale classifiers on data sets of practical interest. Further, we derive another algorithm, TotalQBoost, as a theoretically motivated totally corrective boosting algorithm with cardinality penalization that also makes use of quantum optimization. Both QBoost and TotalQBoost perform explicit cardinality regularization, which is the only known way of achieving maximal sparsity in the trained classifiers. We apply QBoost and TotalQBoost to three different real-world computer vision problems and make use of a quantum processor for solving the sequence of discrete optimization problems generated by one of them. Finally, we study a learning formulation with convex regularization and a non-convex loss function, q-loss, specifically designed for robust supervised learning in the presence of label noise as it occurs in practice. For compatibility with quantum hardware we derive the corresponding quadratic binary problem via variational approximation. For all proposed algorithms we compare results on a variety of popular synthetic and natural data sets against a rich selection of existing rival learning formulations
PHONOLOGICAL LINGUISTIC FEATURES OF UNPUBLISHED POEMS OF THE YOUNG CHAKAVIAN POET AND CHANSONNIER NEVEN BARAC
No full textU radu se donosi pregled fonoloških jezičnih značajki neobjavljenih pjesama mladoga vinodolskog pjesnika i šansonijera Nevena Barca. Njegove su pjesme pisane na griškome idiomu koji pripada srednjočakavskomu ili ikavsko-ekavskomu čakavskom dijalektu. S jedne smo se strane u jezičnome proučavanju služili njegovom neobjavljenom zbirkom pjesama, a s druge strane do danas objavljenim dijalektološkim opisima govora Grižana te vlastitim zapažanjima s terena. Jezična je analiza potvdila da je mladi autor u jeziku pjesama ostao dosljedan svojemu mjesnom govoru.This paper provides an overview of the phonological linguistic features of the unreleased songs by the young poet and chansonnier Neven Barac. His poems are written in the Grižane idiom that belongs to the Chakavian ikavian-ekavian dialect. Linguistic analysis has confirmed that the young author has remained consistent to his local idiom linguistic features in the language of the songs
Efficient Population Transfer via Non-Ergodic Extended States in Quantum Spin Glass
No full textQuantum tunneling has been proposed as a physical mechanism for solving binary optimization problems on a quantum computer because it provides an alternative to simulated annealing by directly connecting deep local minima of the energy landscape separated by large Hamming distances. However, classical simulations using Quantum Monte Carlo (QMC) were found to efficiently simulate tunneling transitions away from local minima if the tunneling is effectively dominated by a single path. We analyze a new computational role of coherent multi-qubit tunneling that gives rise to bands of non-ergodic extended (NEE) quantum states each formed by a superposition of a large number of deep local minima with similar energies. NEE provide a coherent pathway for population transfer (PT) between computational states with similar energies. In this regime, PT cannot be efficiently simulated by QMC. PT can serve as a new quantum subroutine for quantum search, quantum parallel tempering and reverse annealing optimization algorithms. We study PT resulting from quantum evolution under a transverse field of an n-spin system that encodes the energy function E(z) of an optimization problem over the set of bit configurations z. Transverse field is rapidly switched on in the beginning of algorithm, kept constant for sufficiently long time and switched off at the end. Given an energy function of a binary optimization problem and an initial bit-string with atypically low energy, PT protocol searches for other bitstrings at energies within a narrow window around the initial one. We provide an analytical solution for PT in a simple yet nontrivial model: M randomly chosen marked bit-strings are assigned energies E(z) within a narrow strip [-n -W/2, n + W/2], while the rest of the states are assigned energy 0. The PT starts at a marked state and ends up in a superposition of L marked states inside the narrow energy window whose width is smaller than W. The best known classical algorithm for finding another marked state is the exhaustive search. We find that the scaling of a typical PT runtime with n and L is the same as that in the multi-target Grover's quantum search algorithm, except for a factor that is equal to exp(n /(2B^2)) for finite transverse field B >>1. Unlike the Hamiltonians used in analog quantum unstructured search algorithms known so far, the model we consider is non-integrable and the transverse field delocalizes the marked states. As a result, our PT protocol is not exponentially sensitive in n to the weight of the driver Hamiltonian and may be initialized with a computational basis state. We develop the microscopic theory of PT by constructing a down-folded dense Hamiltonian acting in the space of marked states of dimension M. It belongs to the class of preferred basis Levy matrices (PBLM) with heavy-tailed distribution of the off-diagonal matrix elements. Under certain conditions, the band of the marked states splits into minibands of non-ergodic delocalized states. We obtain an explicit form of the heavy-tailed distribution of PT times by solving cavity equations for the ensemble of down-folded Hamiltonians. We study numerically the PT subroutine as a part of quantum parallel tempering algorithm for a number of examples of binary optimization problems on fully connected graphs
Protection and Retrieval of Encrypted Multimedia Content: When Cryptography Meets Signal Processing
No full textThe processing and encryption of multimedia content are generally considered sequential and independent operations. In certain multimedia content processing scenarios, it is, however, desirable to carry out processing directly on encrypted signals. The field of secure signal processing poses significant challenges for both signal processing and cryptography research; only few ready-to-go fully integrated solutions are available. This study first concisely summarizes cryptographic primitives used in existing solutions to processing of encrypted signals, and discusses implications of the security requirements on these solutions. The study then continues to describe two domains in which secure signal processing has been taken up as a challenge, namely, analysis and retrieval of multimedia content, as well as multimedia content protection. In each domain, state-of-the-art algorithms are described. Finally, the study discusses the challenges and open issues in the field of secure signal processing.Electrical Engineering, Mathematics and Computer Scienc
Neural dynamics parametrically controlled by image correlations organize robot navigation
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