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Abstract: Konkurenca med restavracijami in destinacijami se povečuje skupaj s hitro spreminjajočimi se preferencami potrošnikov. Hrana ni več zgolj sredstvo za zadovoljevanje osnovnih človekovih potreb; že dolgo časa nazaj je postala glavna motivacija za potovanje. Turiste, katerih sila potega na destinacijo je gastronomija, imenujemo gastronomski turisti ali s tujko foodie-ji. Čeprav je primarna funkcija restavracij zagotavljanje visokokakovostne gastronomske ponudbe, samo vidik kakovosti ne zadostuje; zahtevni sodobni gostje nenehno iščejo inovativnost, kreativnost in pristnost, kar zagotavlja edinstveno kulinarično izkušnjo. Restavracije morajo zato nenehno uvajati novosti in biti kreativne, da pritegnejo pozornost gostov in tako pridobijo konkurenčno prednost. Poskrbeti morajo za ustrezen ambient (fizični izgled) restavracije, kakor tudi za nesnovne elemente, kot so zagotavljanje visokokakovostne strežbe, prijetnega vzdušja z razsvetljavo in glasbo, ali z organiziranjem posebnih dogodkov in razvedrila. Ker se je v zadnjem času povečala tudi okoljska ozaveščenost potrošnikov, je le-ta prisilila ponudnike gastronomije, da se prilagodijo trajnostnim vzorcem delovanja. Vse omenjene značilnosti so restavracijske kompetence, ki ustvarjajo zaznano kakovost ponudbe in iz nje izvirajočo zaznano vrednost; vse zgoraj navedene kompetence vplivajo tako na konkurenčnost restavracij kot gastronomskih destinacij. V teoretičnem delu te doktorske disertacije smo opredelili koncept konkurenčnosti destinacije in njene modele, koncept kakovosti storitev in njene modele in koncept destinacijskih kompetenc. Sledila je opredelitev gastronomskega turizma kot kreativnega dela kulturnega turizma. V nadaljevanju se teoretična raziskava osredotoča na motivacijo gastronomskih turistov, njihovo tiplogijo in ključne značilnosti. Govorimo tudi o imidžu gastronomske destinacije skupaj s prihodnjimi trendi, tako na strani povpraševanja kot na strani ponudbe. Pri razvoju modela smo se najprej osredotočili na restavracijsko (podjetniško) raven, ki je povezana z različnimi kompetencami, in sicer s kakovostjo, inovativnostjo, kreativnostjo, trajnostjo in lokalnimi značilnostmi. Predpostavili smo, če ponudniki gastronomije (t. j. restavracije) razvijejo kompetence, bodo gostje restavracij zaznali višjo kakovost storitev, s tem pa tudi višjo zaznano vrednost teh restavracij in tako izboljšali svojo konkurenčnost, kakor tudi konkurenčnost celotne destinacije. Kar zadeva destinacije, samo prizadevanja restavracij kot ponudnikov gastronomije, ki se nahajajo v destinaciji, niso dovolj. Poleg gastronomske ponudbe morajo destinacije zagotavljati pestro, a hkrati celostno ponudbo, ki bo zadovoljila potrebe turističnega trga kot celote. To vključuje učinkovito upravljanje destinacije, infrastrukturo, nastanitve, prostočasne dejavnosti znotraj destinacije itd. Gostom, ki prihajajo v destinacijo, je namreč vseeno, kdo so lastniki edinstvenih objektov – želijo le dobiti celostno ponudbo in preživeti odlične počitnice. Da bi destinacijam poiskali način, kako delovati kot enoten (meta) ponudnik, smo kompetence in znanje prenesli z ravni restavracije na raven destinacije. Pri tem smo celotno destinacijo obravnavali kot virtualno podjetje, kar je bilo v skladu z našo trditvijo, da mora destinacija delovati holistično in kot celota. Če je gastronomija osrednji vir destinacije in glavni motiv za obisk destinacije, lahko takšno destinacijo imenujemo gastronomska destinacija in mora, seveda, odražati kompetence gastronomske destinacije: kakovost, inovativnost, kreativnost, trajnostnost in lokalne značilnosti. Tako smo razvili teoretični model GADECOMP (GAstronomic DEstination COMPetitiveness, konkurenčnost gastronomske destinacije) za merjenje konkurenčnosti izbranih gastronomskih destinacij.
Keywords: gastronomski turizem, gastronomija višjega ranga, kompetence (gastronomske) destinacije, konkurenčnost (gastronomske) destinacije, GADECOMP model.
Published in DKUM: 20.01.2025; Views: 0; Downloads: 5
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Abstract: Classic enhanced self-correcting battery equivalent models require proper model parameters and initial conditions such as the initial state of charge for its unbiased functioning. Obtaining parameters is often conducted by optimization using evolutionary algorithms. Obtaining the initial state of charge is often conducted by measurements, which can be burdensome in practice. Incorrect initial conditions can introduce bias, leading to long-term drift and inaccurate state of charge readings. To address this, we propose two simple and efficient equivalent model frameworks that are optimized by a genetic algorithm and are able to determine the initial conditions autonomously. The first framework applies the feedback loop mechanism that gradually with time corrects the externally given initial condition that is originally a biased arbitrary value within a certain domain. The second framework applies the genetic algorithm to search for an unbiased estimate of the initial condition. Long-term experiments have demonstrated that these frameworks do not deviate from controlled benchmarks with known initial conditions. Additionally, our experiments have shown that all implemented models significantly outperformed the well-known ampere-hour coulomb counter integration method, which is prone to drift over time and the extended Kalman filter, that acted with bias.
Keywords: enhanced self-correcting model, state of charge estimation, lithium-ion cell parameter identification
Published in DKUM: 08.01.2025; Views: 0; Downloads: 2
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Abstract: The synchronization of chaotic systems has garnered considerable attention across various fields, including neuroscience and physics. Particularly in these domains, synchronizing physical systems such as laser models is crucial for secure and rapid information transmission. Consequently, numerous studies investigate the synchronizability of different laser networks by establishing logical network frameworks. In this study, we employed a minimal universal laser (MUL) model designed to capture the essential dynamics of an actual laser model within just three dimensions. Within the network model of MUL systems, we introduced the linear diffusive function of neighboring nodes' fast variables into the feedback term of the lasers, with models arranged in a global network structure. Our examination of synchronization within the constructed MUL network utilized master stability functions and the time-averaged synchronization error index. The findings suggest that while the network fails to achieve complete synchrony, it exhibits various synchronization phenomena, including cluster synchronization, chimera states, extreme events, and multistability. These results shed light on the complex dynamics underlying the synchronization of chaotic systems in networked environments, offering insights relevant to numerous applications across diverse fields.
Keywords: minimal universal laser model, synchronization, extreme events
Published in DKUM: 16.12.2024; Views: 0; Downloads: 3
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Abstract: Within the islets of Langerhans, beta cells orchestrate synchronized insulin secretion, a pivotal aspect of metabolic homeostasis. Despite the inherent heterogeneity and multimodal activity of individual cells, intercellular coupling acts as a homogenizing force, enabling coordinated responses through the propagation of intercellular waves. Disruptions in this coordination are implicated in irregular insulin secretion, a hallmark of diabetes. Recently, innovative approaches, such as integrating multicellular calcium imaging with network analysis, have emerged for a quantitative assessment of the cellular activity in islets. However, different groups use distinct experimental preparations, microscopic techniques, apply different methods to process the measured signals and use various methods to derive functional connectivity patterns. This makes comparisons between findings and their integration into a bigger picture difficult and has led to disputes in functional connectivity interpretations. To address these issues, we present here a systematic analysis of how different approaches influence the network representation of islet activity. Our findings show that the choice of methods used to construct networks is not crucial, although care is needed when combining data from different islets. Conversely, the conclusions drawn from network analysis can be heavily affected by the pre-processing of the time series, the type of the oscillatory component in the signals, and by the experimental preparation. Our tutorial-like investigation aims to resolve interpretational issues, reconcile conflicting views, advance functional implications, and encourage researchers to adopt connectivity analysis. As we conclude, we outline challenges for future research, emphasizing the broader applicability of our conclusions to other tissues exhibiting complex multicellular dynamics.
Keywords: islets of Langerhans, beta cells, calcium signaling, intercellular communication, functional networks, myosin model
Published in DKUM: 09.12.2024; Views: 0; Downloads: 3
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Abstract: This article aims to provide an accurate mathematical model with the minimum number of degrees of freedom for describing the floating sleeper phenomenon. This was accomplished using mathematical modeling supported by extensive field measurements of the railway track. Although the observed phenomenon is very complex, the simplified single degree of freedom (SDOF) mathematical model proved accurate enough for its characterization. The progression of the deterioration of the railway track was successfully correlated to changes in the maximal dynamic factor for different types of pulse loading. The results of the presented study might enable the enhanced construction and maintenance of railroads, particularly in karst areas.
Keywords: floating sleepers, dynamic factor, pulse loading, field measurements, SDOF mathematical model
Published in DKUM: 28.11.2024; Views: 0; Downloads: 4
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