Numerous studies on Queueing systems, such as Internet traffic flows, have shown to be bursty, self-similar and/or long-range dependent, because of the heavy (long) tails for the various distributions of interest, including intermittent intervals and queue lengths. Other studies have addressed vacation in no-customers’ queueing system or when the server fails. These patterns are important for capacity planning, performance prediction, and optimization of networks and have a negative impact on their effective functioning. Heavy-tailed distributions have been commonly used by telecommunication engineers to create workloads for simulation studies, which, regrettably, may show peculiar queueing characteristics. To cost-effectively examine the impacts of different network patterns on heavy- tailed queues, new and reliable analytical approaches need to be developed. It is decided to establish a brand-new analytical framework based on optimizing entropy functionals, such as those of Shannon, Rényi, Tsallis, and others that have been suggested within statistical physics and information theory, subject to suitable linear and non-linear system constraints. In both discrete and continuous time domains, new heavy tail analytic performance distributions will be developed, with a focus on those exhibiting the power law behaviour seen in many Internet scenarios. The exposition of two major revolutionary approaches, namely the unification of information geometry and classical queueing systems and unifying information length theory with transient queueing systems. After conclusions, open problems arising from this thesis and limitations are introduced as future work.

<p dir="ltr">Mammalian mesocarnivores contribute greatly to a proper functioning ecosystem by exerting top-down population control on prey species. While many of these species can be legally trapped or hunted in Indiana, given their responsibilities in the ecosystem, continuous monitoring of Gray fox (Urocyon cinereoargenteus) and Long-tailed weasel (Neogale frenata) by researchers is important to identify potential signs of decline and produce specific management plans. Both U. cinereoargenteus and N. frenata populations are suspected to be declining based on reduced frequencies of observations and harvest. However, each species displays cryptic behaviors that can make observation and effective surveying difficult, which may make the development of accurate assessments of population health unfeasible. To enable better monitoring of populations of these species, I developed a model for potential U. cinereoargenteus habitat and build upon camera trapping survey methods for N. frenata in this project. I used community surveying tools in a presence-only software (e.g., MaxEnt) to develop a consensus model for U. cinereoargenteus potential habitat. I identified five landscape-based covariates (distance to mixed and evergreen forest, distance to low urban cover, distance to shrub/scrub cover, and percent total forest cover per km2 ) that contributed the greatest to predicting the presence of the species. The top models in my project indicated a positive relationship between predicted U. cinereoargenteus presence and forested land cover. Additionally, predicted presence was high when the distance to low urban and shrub/scrub cover was low. In the Southern portion of Indiana predicted areas of presence occurred where larger forest patches exist. This differed from the Central and Northern portions of the state where smaller fragmented forest patches exist. In these areas, predicted areas of presence predominantly occurred near shrub/scrub or low urban cover. These findings will allow researchers to target specific areas for effective surveying and develop species conservation strategies. I also evaluated the ability of three enclosed camera trapping systems (AHDriFT system, Mostela system, and MoHDriFT system) to detect N. frenata. These camera systems have been designed to detect N. frenata and potential prey items, doing so successfully in past studies. I deployed trapping systems in three sites throughout Northeast Indiana from February to November 2023. Camera systems collected data during the project period during unbaited and baited (using sardines) survey periods. During my project, I observed three unique detections of N. frenata, all 9 of which were in the AHDriFT system during unbaited survey periods (P = 0.99; Z = -0.005). During these survey periods when N. frenata were detected, the AHDriFT system accounted for greater prey visitation and prey species abundance than the other two trapping systems (P < 0.01; F = 12). The ability to attract large amounts of prey species while successfully detecting N. frenata in this project may point to the AHDriFT system as the best camara trapping system suited for monitoring this cryptic species. The results from my project provide researchers and state agencies with input for monitoring these two cryptic species. With both species in suspected declines, the research conducted in the two chapters can contribute to portions of future species management plans. By targeting specific areas with predicted suitable habitat for U. cinereoargenteus, agencies can better allocate funds and conduct more extensive species research in Indiana. Likewise, by deploying the AHDriFT system, researchers in Indiana can cost-effectively monitor, not only N. frenata populations, but also small mammal and herp communities with ease. The research in this project provides researchers and state agencies in Indiana with new tools and insights in monitoring these cryptic species that are critical mesocarnivores in the state’s ecosystem.</p>

Magnetic fields influence the rate and/or yield of chemical reactions that proceed via spin correlated radical pair intermediates. The field of spin chemistry centres around the study of such magnetic field effects (MFEs). This thesis is particularly concerned with the effects of the weak magnetic fields B₀ ~ 1mT relevant in the ongoing debates on the mechanism by which animals sense the geomagnetic field and on the putative health effects of environmental electromagnetic fields. Relatively few previous studies have dealt with such weak magnetic fields. This thesis presents several new theoretical tools and applies them to interpret experimental measurements. Chapter 1 surveys the development and theory of spin chemistry. Chapter 2 introduces the use of Tikhonov and Maximum Entropy Regularisation methods as a new means of analysing MARY field effect data. These are applied to recover details of the diffusive motion of reacting pyrene and N,N-dimethylaniline radicals. Chapter 3 gives a fresh derivation and appraisal of an approximate, semiclassical approach to MFEs. Monte Carlo calculations allow the elucidation of several "rules of thumb" for interpreting MFE data. Chapter 4 discusses recent optically-detected zero-field EPR measurements, adapting the gamma-COMPUTE algorithm from solid state NMR for their interpretation. Chapter 5 explores the role of RF polarisation in producing MFEs. The breakdown in weak fields of the familiar rotating frame approximation is analysed. Chapter 6 reviews current knowledge and landmark experiments in the area of animal magnetoreception. The origins of the sensitivity of European robins Erithacus rubecula to the Earth’s magnetic field are given particular attention. In Chapter 7, Schulten and Ritz’s hypothesis that avian magnetoreception is founded on a radical pair mechanism (RPM) reaction is appraised through calculations in model systems. Chapter 8 introduces quantitative methods of analysing anisotropic magnetic field effects using spherical harmonics. Chapter 9 considers recent observations that European robins may sometimes be disoriented by minuscule RF fields. These are shown to be consistent with magnetoreception via a radical pair with no (effective) magnetic nuclei in one of the radicals.

No / A review is carried out on the characterisation and algorithmic implementation of an extended product-form approximation, based on the principle of maximum entropy (ME), for a wide class of arbitrary finite capacity open queueing network models (QNMs) with service and space priorities. A single server finite capacity GE/GE/1/N queue with R (R>1) distinct priority classes, compound Poisson arrival processes (CPPs) with geometrically distributed batches and generalised exponential (GE) service times is analysed via entropy maximisation, subject to suitable GE-type queueing theoretic constraints, under preemptive resume (PR) and head-of-line (HOL) scheduling rules combined with complete buffer sharing (CBS) and partial buffer sharing (PBS) management schemes stipulating a sequence of buffer thresholds {N=(N1,¿,NR),0<Ni¿Ni¿1,i=2,¿,R}. The GE/GE/1/N queue is utilised, in conjunction with GE-type first two moment flow approximation formulae, as a cost-effective building block towards the establishment of a generic ME queue-by-queue decomposition algorithm for arbitrary open QNMs with space and service priorities under repetitive service blocking with random destination (RS-RD). Typical numerical results are included to illustrate the credibility of the ME algorithm against simulation for various network topologies and define experimentally pessimistic GE-type performance bounds. Remarks on the extensions of the ME algorithm to other types of blocking mechanisms, such as repetitive service blocking with fixed destination (RS-FD) and blocking-after-service (BAS), are included.

[ES] La creciente preocupación sobre el efecto de la emisión de gases nocivos provenientes de motores de combustión interna alternativos (ICE) a la atmósfera ha llevado a los gobiernos a lo ancho del planeta a limitar la cantidad de dichas emisiones, particularmente en Europa a través de las normas EURO. La dificultad en cumplir dichas limitaciones ha llevado a la industria automovilística a cambiar el foco de motores de encendido por compresión (CI) o provocado (SI) hacia la electrificación o los combustibles libres de carbono. Sin embargo, esta transición no se puede llevar a cabo de manera sencilla en el corto y medio plazo, mientras que combustibles libres de carbono como el Hidrógeno (H2 ) o el Amoniaco (NH3 ) siguen produciendo algunos contaminantes como los Óxidos de Nitrógeno (NOx ), con los cuales hay que lidiar. Estas emisiones pueden ser particularmente dañinas para el ser humano ya que incrementan el riesgo de cáncer de pulmón. La Reducción Catalítica Selectiva (SCR) ha demostrado ser una tecnología eficaz para la reducción de este contaminante en particular. A través de una inyección de una Solución de Urea-Agua, junto con la energía térmica de los gases de escape, se genera una cantidad suficiente de NH 3 capaz de neutralizar los indeseados NOx en un catalizador de reducción. Con la inclusión de los SCR en automóviles ligeros además de su presencia tradicional en automóviles pesados, los SCR han sido el foco de la comunidad científica para mejorar el entendimiento de su principio de actuación, y mejorar su eficiencia en un entorno legislativo en el que los limites de emisión se han estrechado enormemente. Esta Tesis intenta ser parte de ese esfuerzo científico en caracterizar el proceso de inyección de UWS en su totalidad a través de un entorno computacional. El presente estudio tiene como objetivo proveer de un mejor entendimiento del proceso de atomización y degradación sufrido por los chorros de UWS. Las dinámicas no estacionarias que se dan lugar en la zonas cercana del chorro, añadido a la gran influencia de las características internas del inyector sobre el desarrollo del spray hacen que los métodos experimentales sean complicados para poder entender dicho proceso. Por otro lado, la Mecánica de Fluidos Computacional (CFD) presenta una alternativa. Para el propósito de esta Tesis, el CFD ha sido utilizado para caracterizar los sprays de SCR. Se intenta desarrollar y seleccionar los modelos más apropiados a chorros de baja velocidad, y establecer un conocimiento Una vez adquiridos dichos métodos, los mecanismos principales de rotura del chorro y de degradación de la urea se han analizan. En ese sentido, el uso de técnicas experimentales podrían ser sustituídos en el futuro para esta aplicación. Los métodos CFD son validados tanto en el campo cercano como en el lejano. Para el campo cercano, el tratamiento multi-fase se lleva a cabo a través de métodos de Modelo de Mezclas, o el método Volume-Of-Fluid. A través de ellos, la caracterización hidráulica de dos reconstrucciones del inyector de UWS se lleva a cabo. Subsiguientes análisis se llevan a cabo sobre las dinámicas de rotura de la vena líquida, descubriendo que mecanismos rigen el proceso. El estudio de campo lejano usa un Discrete Droplet Model (DDM) para lidiar con las fases líquidas y gaseosas. En él, la evaporación del agua y el proceso de termólisis de la urea han sido considerados y comparados con resultados experimentales con el fin de obtener una metodología fiel para su caracterización. Todo el conocimiento adquirido se aplica más tarde a un Close-Coupled SCR, en el cual condiciones de trabajo realista han sido consideradas. Además, una herramienta llamada Maximum Entropy Principle (MEP) es presentada. Por tanto, esta Tesis aporta una metodología valiosa capaz de predecir tanto el campo cercano como el lejano de chorros de UWS de una manera precisa. / [CA] La creixent preocupació sobre el efecte de l'emissió de gasos nocius provenients the motors de Combustió Interna Alternatius (ICE) a l'atmosfera ha dut als governs de tot el planeta a limitar la quantitat d'aquestes emisions, particularment a Europa mitjant les normes EURO. La dificultat de complir aquestes limitacions ha portat a l'industria automovilística a cambiar el focus de motors d'encedut per compresió (CI) o provocat (SI) cap a la electrificació o els combustibles lliures de carbó. No obstant això, aquesta transició no es pot dur a terme de manera senzilla , mentres que els combustibles lliures de carbó como l'Hidrogen (H2 ) o l'Amoniac (NH3 ) seguirien produint contaminants como els Óxids de Nitrogen (NOx ), amb els quals n'hi ha que bregar. Estes emissions poden ser particularment nocives per a l'esser humà ja que incrementen el risc de càncer de pulmó. La Reducció Catalítica Selectiva (SCR) ha demostrat ser una tecnología eficaç per a la reducció d'este contaminant en particular. Mitjançant una injecció d'una Solució D'Urea i Aigua, junt a l'energía térmica dels gasos d'fuita, es pot generar una quantitat suficiente de NH 3 capaç de neutralitzar els indesitjats NO x a un catalitzador de reducció. Amb l'inclusió dels SCR en automòvils lleugers a més de la seua tradicional presència en automòvils pesats, els SCR han segut el foc per a mijorar l'enteniment del seu principi d'actuació, i mijorar la seua eficiencia. Este estudi té como a objectiu proveir d'un mijor entenement del procés d'atomizació y degradació patit pels dolls de UWS. Les dinàmiques no estacionaries que es donen lloc en la zona propenca al doll, afegit a la gran influència de les característiques internes del injector sobre el desentroll de l'esprai, fan que els métods experimentals siguen complicats d'aplicar per entendre dit procés. Per un altre costat, la Mecànica de Fluïts Computacional (CFD) supon una alternativa que té certes avantatges. Per al propòsit d'esta Tesi, el CFD ha sigut utilitzat com la principal metodología per a caracteritzar elsesprais de SCR. Per mitjà de dits métodes, la Tesi vol desentrollar i seleccionar els models més apropiats que mitjos s'adapten a sprays de baixa velocitat, i establir un coneiximent per a posteriors estudis desentrollats sobre la mateixa temàtica. Una volta adquirits dits métodes, els mecanismes principals de trencament del doll, així com els de degradació de l'urea en amoníac s'analitzaran. En aquest sentit, l'us de técniques experimentals podría no ser utilitzat més en el futur per aquesta aplicació.Els métods CFD son aplicats i validats tant el el camp propenc com en el llunyà. Per al camp propenc, el tractament multi-component es porta a terme a través de métodes Eulerians-Eulerians, com el Model de Mescles, o el métode Volume-Of-Fluid. La caracterització hidràulica de dos reconstruccions de l'injector es porta a terme, els resultats del qual són comparats amb resultats experimentals. Subsegüents anàlisis es porten a terme sobre les dinàmiques de trencament de la vena líquida, descobrint qué mecanismes regeixen el procés. L'estudi de camp llunyà usa un Discrete Droplet Model (DDM) per a bregar en la fase líquida i gaseosa. En ell, l'evaporació del aigua y el procés de termòlisis de l'urea han sigut considerats i comparats amb el resultats experimentals amb la finalitat d'obtindre una metodología fidel per a la seua caracterització. Tot el coneixement obtingut s'aplica més tard a un Close-Coupled SCR, en el qual condicions de treball realistes han sigut considerades. Dels resultats obtinguts dels distints estudis, una ferramenta adicional anomenada Maximum Entropy Principle (MEP),capaç de predir el fenomen d'atomització dels doll de UWS sense la necessitat de realitzar simulacions del camp propenc, es presentat. Per tant, esta Tesi aporta una metodología capaç de predir tant el camp proper como el llunyà d'una manera precisa. / [EN] The increasing awareness of the effect of emitting harmful gases from Internal Combustion Engines (ICE) into the atmosphere has driven the governments across the globe to limit the amount of these emissions, par ticularly in Europe through the EURO norms. The difficulty to meet such limitations has driven the automotive industry to shift from traditional Compression Ignited (CI) or Spark Ignited (SI) engines toward electrification or carbon-free fuels. Nonetheless, this transition will not be easily done in the short and medium time frames, while carbon-free fuels such as Hydrogen (H2 ) and Ammonia (NH3 ) will keep producing certain pollutants such as Nitrogen Oxides (NOx ) which need taking care of. These emissions can be particularly hazardous for humans, increasing the risk of developing lung cancer. Selective Catalytic Reduction (SCR) is an effective technology for reducing this specific ICE contaminant. An injection of a Urea-Water Solution (UWS), together with the thermal energy of the combustion gases can generate a sufficient amount of NH 3 capable of neutralizing the unwanted NO x in a catalyst. With the fitting of SCR systems within light-duty applications, in addition to their traditional presence on heavy-duty usage, SCR has been on the focus to understand their working principle and improve their efficiency . This Thesis tries to become part of that scientific ensemble by characterizing the whole UWS injection process within a computational framework. The present research aims to provide a better understanding of the atomizing and degradation processes undergone by the UWS sprays. The transient dynamics taking place in the near-field region, added to the great influence of the inner-injector characteristics on the development of the spray make experimental approaches on such sprays challenging in providing such knowledge. Computational Fluid Dynamics (CFD) provide an alternative that has certain advantages. For this Thesis they have been adopted as the main methodology on characterizing SCR sprays. The Thesis tries to develop and select the appropriate models that best suit low-velocity sprays. With the suitable methods that best predict these sprays, the main jet breakup mechanisms, together with the urea-to-ammonia transformation will have their behavior analyzed. In that way, experimental techniques could be avoided for such applications. CFD is applied and validated both in the near-field and far-field regions. For the near-field, multi-component flows are treated through Eulerian-Eulerian such as the Mixture Model or the Volume-Of-Fluid method. Through them, a hydraulic characterization on two recon structions of the UWS injector is performed, with results compared with experimental data. Further analysis is done on the jet-to-droplet dynamics, assessing which mechanisms drove the process. The far-field analy sis uses a Discrete Droplet Model (DDM) for dealing with the gas and liquid phases. In it, the evaporation of water and the thermolysis process of the urea have been considered and again compared with experimental results to have a faithful methodology for its characterization. All the acquired knowledge has been later applied to a commercial Close-Coupled SCR, in which real-working conditions have been considered. From the results obtained from several studies, an additional tool called Maximum Entropy Principle (MEP), capable of predicting the UWS spray atomization phenomenon without the need to perform near-field simulations, has been provided. Accordingly, this Thesis provides a valuable methodology capable of predicting the near-field and far-field dynamics accurately thanks to its validation against experimental results from literature. Additionally, the MEP tool can be used independently for computational and experimental works to predict the performance of UWS atomizers.The work carried out presents a significant leap in the application of CFD tools in predicting low-velocity sprays. / Javier Marco Gimeno has been founded through a grant from the Government of Generalitat Valenciana with reference ACIF/2020/259 and financial support from the European Union. These same institutions, Government of Generalitat Valenciana and The European Union, supported through a grant for pre-doctoral stays out of the Comunitat Valenciana with reference CIBEFP/2021/11 the research carried out during the stay at Energy Systems, Argonne National Laboratory, United States of America. / Marco Gimeno, J. (2023). Computational study of Formation and Development of Liquid Jets in Low Injection Pressure Conditions. Focus on urea-water solution injection for exhaust gas aftertreatment [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/198699

Cette thèse se penche sur les modèles de choix, des distributions sur des ensembles d'alternatives. Les modèles de choix sur les processus décisionnels de Markov (MDP) peuvent décomposer de très grands espaces alternatifs en procédures étape par étape conçues pour non seulement combattre la malédiction de la dimensionnalité mais aussi pour mieux refléter la dynamique sous-jacente. La première partie est consacrée à l'estimation du temps de trajet dans le cadre de la modélisation du choix de chemin. Les modèles de choix de chemin sont des modèles de choix sur l'ensemble des chemins utilisés pour modéliser le flux de circulation. Intuitivement, le temps de trajet est l'une des caractéristiques les plus importantes lors du choix des chemins, mais les temps de trajet ne sont pas toujours connus. En revanche, le cadre classique suppose que ces deux étapes sont séquentielles, car les temps de trajet des arcs font partie de l'entrée du processus d'estimation du choix de chemin. Pourtant, les interdépendances complexes signifient que ce modèle de choix de chemin peut complémenter toute observation lors de l'estimation des temps de trajet. Nous construisons un modèle statistique pour l'estimation du temps de trajet et proposons de marginaliser les caractéristiques non observées. En utilisant ces idées, nous montrons que nous sommes capables d'apprendre des modèles de choix de chemin sans observer de chemins réels et à différentes granularités. La deuxième partie se concentre sur les échecs des MDP régularisés et comment la régularisation peut avoir des effets secondaires inattendus, tels que la divergence dans les chemins stochastiques les plus courts ou des fonctions de valeur déraisonnablement grandes. Les MDP régularisés ne sont rien d'autre qu'une application des modèles de choix aux MDP. Ils sont utilisés dans l'apprentissage par renforcement (RL) pour obtenir, entre autres choses, un modèle de choix sur les trajectoires possibles pour l'apprentissage par renforcement inverse, transférer des connaissances préalables au modèle, ou obtenir des politiques qui exploitent tous les objectifs dans l'environnement. Ces effets secondaires sont exacerbés dans les espaces d'action dépendants de l'état. Comme mesure d'atténuation, nous introduisons deux transformations potentielles, et nous évaluons leur performance sur un problème de conception de médicaments. / This thesis delves on choice models, distributions on sets of alternatives. Choice models on Markov decision processes (MDPs) can break down very large alternative spaces into step-by-step procedures designed to not only tackle the curse of dimensionality but also to reflect the underlying dynamics better. The first part is devoted to travel time estimation as part of path choice modeling. Path choice models are choice models on the set of paths used to model traffic flow. Intuitively, travel time is one of the more important features when choosing paths, yet travel times are not always known. In contrast, the classical setting assumes that these two steps are sequential, as arc travel times are part of the input of the path choice estimation process. Yet the intricate interdependences mean that that path choice model can complement any observation when estimating travel times. We build a statistical model for travel time estimation and propose marginalizing the unobserved features. Using these ideas, we show that we are able to learn path choice models without observing actual paths and at different granularity. The second part focuses on the failings of regularized MDPs and how regularization may have unexpected side effects, such as divergence in stochastic shortest paths or unreasonably large value functions. Regularized MDPs are nothing but an application of choice models to MDPs. They are used in reinforcement learning (RL) to get, among other things, a choice model on possible trajectories for inverse reinforcement learning, transfer prior knowledge to the model, or to get policies that exploit all goals in the environment. These side effects are exacerbated in state-dependent action spaces. As a mitigation, we introduce two potential transformations, and we benchmark their performance on a drug design problem.

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L'analyse de séries temporelles biomédicales chaotiques tirées de systèmes dynamiques non-linéaires est toujours un challenge difficile à relever puisque dans certains cas bien spécifiques les techniques existantes basées sur les multi-fractales, les entropies et les graphes de récurrence échouent. Pour contourner les limitations des invariants précédents, de nouveaux descripteurs peuvent être proposés. Dans ce travail de recherche nos contributions ont porté à la fois sur l’amélioration d’indicateurs multifractaux (basés sur une fonction de structure) et entropiques (approchées) mais aussi sur des indicateurs de récurrences (non biaisés). Ces différents indicateurs ont été développés avec pour objectif majeur d’améliorer la discrimination entre des signaux de complexité différente ou d’améliorer la détection de transitions ou de changements de régime du système étudié. Ces changements agissant directement sur l’irrégularité du signal, des mouvements browniens fractionnaires et des signaux tirés du système du Lorenz ont été testés. Ces nouveaux descripteurs ont aussi été validés pour discriminer des fœtus en souffrance de fœtus sains durant le troisième trimestre de grossesse. Des mesures statistiques telles que l’erreur relative, l’écart type, la spécificité, la sensibilité ou la précision ont été utilisées pour évaluer les performances de la détection ou de la classification. Le fort potentiel de ces nouveaux invariants nous laisse penser qu’ils pourraient constituer une forte valeur ajoutée dans l’aide au diagnostic s’ils étaient implémentés dans des logiciels de post-traitement ou dans des dispositifs biomédicaux. Enfin, bien que ces différentes méthodes aient été validées exclusivement sur des signaux fœtaux, une future étude incluant des signaux tirés d’autres systèmes dynamiques nonlinéaires sera réalisée pour confirmer leurs bonnes performances. / The analysis of biomedical time series derived from nonlinear dynamic systems is challenging due to the chaotic nature of these time series. Only few classical parameters can be detected by clinicians to opt the state of patients and fetuses. Though there exist valuable complexity invariants such as multi-fractal parameters, entropies and recurrence plot, they were unsatisfactory in certain cases. To overcome this limitation, we propose in this dissertation new entropy invariants, we contributed to multi-fractal analysis and we developed signal-based (unbiased) recurrence plots based on the dynamic transitions of time series. Principally, we aim to improve the discrimination between healthy and distressed biomedical systems, particularly fetuses by processing the time series using our techniques. These techniques were either validated on Lorenz system, logistic maps or fractional Brownian motions modeling chaotic and random time series. Then the techniques were applied to real fetus heart rate signals recorded in the third trimester of pregnancy. Statistical measures comprising the relative errors, standard deviation, sensitivity, specificity, precision or accuracy were employed to evaluate the performance of detection. Elevated discernment outcomes were realized by the high-order entropy invariants. Multi-fractal analysis using a structure function enhances the detection of medical fetal states. Unbiased cross-determinism invariant amended the discrimination process. The significance of our techniques lies behind their post-processing codes which could build up cutting-edge portable machines offering advanced discrimination and detection of Intrauterine Growth Restriction prior to fetal death. This work was devoted to Fetal Heart Rates but time series generated by alternative nonlinear dynamic systems should be further considered.