This thesis gives a unified framework to formulate and solve resource management problems in radar systems. / As a crucial factor in improving radar performance for multiple target tracking (MTT), resource management problems are analyzed in this thesis with regard to sensor platform path planning, beam scheduling, and burst parameter design. This thesis addresses problems to deploy or adapt radar configurations for multisensor-multitarget tracking, including 1) the path planning of movable receivers and power allocation of transmitted signals, 2) the optimal beam steering of high-precision pencil beams, and 3) the pulsed repetition frequency (PRF) set selection and waveform design. Firstly, the coordinated sensor management on the ends of both receivers and transmitters for a multistatic radar is studied. A multistatic radar system consists of fixed transmitters and movable receivers. To form better transmitter-target-receiver geometry and to establish an effective power allocation scheme to illuminate targets with different priorities, a joint path planning and power allocation problems, which determines the moving trajectories of receivers mounted on unmanned airborne vehicles (UAVs) and the power allocation scheme of transmitted signals over a limited time horizon, is formulated as a weighted-sum optimization. The problem is solved with a genetic algorithm (GA) with a novel pre-selection operator. The pre-selection operator, which takes advantage of the receding horizon control (RHC) framework to improve population structures prior to the next generation, can accelerate the convergence of GA. Secondly, the beam steering strategies for a cooperative phased array radar system with high-precision beams are developed. Pencil beams with narrow beamwidth, which are designated to track targets for a phased array radar, offer efficient performance in an energy-saving design, but can cause partial observations. The novel concept of expected Cramér-Rao lower bound (EPCRLB) is proposed to model partial observations. A formulation based on PCRLB is given and solved with a hierarchical genetic algorithm (HGA). An optimal strategy based on EPCRLB, which is effective in performance and efficient in time, is proposed. Finally, a joint pulsed repetition frequency (PRF) set selection and waveform design is studied. The problem tries to improve blind zone maps while preventing targets from falling into blind zones. Waveform parameters are then optimized for the system to provide better tracking accuracy. The problem is first formulated as a bi-objective optimization problem and solved with a multiple-objective genetic algorithm. Then, a two-step strategy that prioritizes the visibility of targets is developed. Numerical results demonstrate the effectiveness of proposed strategies over simple approaches. / Thesis / Doctor of Philosophy (PhD) / This thesis formulates resource management problems in various radar systems. The problems use PCRLB, a theoretically achievable lower bound for estimators, as a metric to optimize, and help the configuration of radar resources in an efficient manner. Effective strategies and improved algorithms are proposed to solve the problems.

<p> Particle filters are being used in a number of state estimation applications because of their capability to effectively solve nonlinear and non-Gaussian problems. However, they have high computational requirements and this becomes even more so in the case of multitarget tracking, where data association is the bottleneck. In order to perform data association and estimation jointly, typically an augmented state vector, whose dimensions depend on the number of targets, is used in particle filters. As the number of targets increases, the corresponding computational load increases exponentially. In this case, parallelization is a possibility for achieving real-time feasibility in large-scale multitarget tracking applications. In this paper, we present an optimization-based scheduling algorithm that minimizes the total computation time for the bus-connected heterogeneous primary-secondary architecture. This scheduler is capable of selecting the optimal number of processors from a large pool of secondary processors and mapping the particles among the selected ones. A new distributed resampling algorithm suitable for parallel computing is also proposed. Furthermore, a less communication intensive parallel implementation of the particle filter without sacrificing tracking accuracy using an efficient load balancing technique, in which optimal particle migration among secondary processors is ensured, is presented. Simulation results demonstrate the tracking effectiveness of the new parallel particle filter and the speedup achieved using parallelization.</p> / Thesis / Master of Applied Science (MASc)

Submitted by Maike Costa (maiksebas@gmail.com) on 2017-07-07T12:56:32Z No. of bitstreams: 1 arquivototal.pdf: 3524208 bytes, checksum: 1dfa6b7ebfd1711a48733025c4052ee9 (MD5) / Made available in DSpace on 2017-07-07T12:56:32Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 3524208 bytes, checksum: 1dfa6b7ebfd1711a48733025c4052ee9 (MD5) Previous issue date: 2017-02-13 / Conselho Nacional de Pesquisa e Desenvolvimento Científico e Tecnológico - CNPq / The human body has a large bacterial flora, but when these bacteria, the principle of commensal character, become part of site other than it's natural, they can cause some severe diseases. Researches that are based either on the search of new drugs from plants or on the improvement of phytotherapics are in prominence and continue to play an important role nowadays. In this perspective, the aim was to carry out a phytochemical study of Solanum capsicoides All. fruits to isolate and characterize the chemical substances of this species and to use in silico studies to carry out investigations of new molecules potentially active for methicillin resistant Staphylococcus aureus (MRSA) and Escherichia coli using a database created with secondary metabolites isolated from Solanum genus. The phytochemical study of Solanum capsicoides All. fruits resulted in the isolation of three substances: carpesterol, acetylated glucose and 4-hydroxybenzaldehyde. A review of the literature led to the creation of a database with 421 different secondary metabolites isolated from the Solanum genus. Two databases from CHEMBL were selected. The first one with activity against MRSA and another against E. coli. The compounds were classified according to the pIC50 values to generate and validate the model using "Random Forest"(RF). The structure of six new target proteins against S. aureus obtained from the PDB (Protein database) were used for virtual screening of the based on the receptor structure using docking studies by the Molegro Virtual Docker, reaching to select Solanum database molecules capable of interacting in the binding sites of proteins. The RF prediction model for MRSA obtained a percent accuracy of 81%, area under the Receiver Operating Characteristic (ROC) curve of 0.885, selecting 8 molecules with an active potential above 60%. The prediction model for Escherichia coli obtained an accuracy rate of 88%, area under ROC curve of 0.932, selecting 4 molecules with potential probability above 84%. The study of the coupling of six target enzymes to S. aureus selected an average of 50 molecules from the bank of 421 isolated molecules of the genus Solanum with an ability to interact with on active site of each enzyme. In addition, it was possible to obtain 1 molecule with active potential and interaction capacity with 5 enzymes studied, 7 molecules interacting with 3 enzymes and 6 with 2 enzymes of S. aureus. The rutin, a molecule potentially active in the in silico study for S. aureus and E. coli, together with carpesterol, were tested in vitro against these bacteria. Microbiological tests have shown that carpesterol has no antimicrobial activity for the studied strains, and that the rutin has activity only for E. coli. An interaction study with strains of S. aureus ATCC 25923, a standard strain sensitive to all antibiotics, and SAM-01, a multidrug resistant strain, was designed. There was interaction only between rutin and oxacillin, one of the three antibiotics studied in the interaction, for a strain SAM- 01, reducing the resistance of this strain. / O ser humano possui uma vasta flora bacteriana que é comensal, mas quando essas bactérias, a princípio de caráter comensal, passam a fazer parte de outro sítio que não o seu natural, podem causar graves patogenias. Pesquisas que se fundamentam na busca por novos medicamentos a partir de plantas ou no melhoramento de fitoterápicos já existentes vem se destacando e continuam a desempenhar um papel importante nos dias de hoje. Nessa perspectiva objetivou-se realizar um estudo fitoquímico dos frutos de Solanum capsicoides All. para isolar e caracterizar substâncias químicas desta espécie e, utilizando estudos in silico, realizar investigações de novas moléculas potencialmente ativas para Staphylococcus aureus resistente a meticilina (MRSA) e Escherichia coli, utilizando um banco de dados criado com metabólitos secundários isolados do gênero Solanum. O estudo fitoquímico dos frutos de Solanum capsicoides All. resultou no isolamento de três substancias: carpesterol, glicose acetilada e 4-hidroxi-benzaldeído. A revisão de literatura levou à criação de um banco de dados com 421 diferentes metabólitos secundários isolados do gênero Solanum. Foram selecionados dois bancos de dados obtidos a partir do CHEMBL. O primeiro com atividade contra S. aureus multirresistente (MRSA) e o outro contra E. coli. Os compostos foram classificados de acordo com valores de pIC50 para gerar e validar o modelo utilizando “Random Forest”(RF). A estrutura de seis novas proteínas alvo contra S. aureus obtidas do Protein Data Bank (PDB) foram utilizadas para triagem virtual baseada na estrutura do receptor utilizando estudos de “docking” com o software Molegro Virtual Docker, a fim de selecionar moléculas do banco de dados de Solanum com potencial capacidade de interagir nos sítios de ligação dessas proteínas. O modelo RF de predição para S. aureus multirresistente obteve uma porcentagem de acerto de 81%, área sob a curva Receiver Operating Characteristic (ROC) de 0,885, selecionando 8 moléculas com potencial ativo superior a 60%. O modelo de predição para Escherichia coli obteve taxa de acerto de 88%, área sob curva ROC de 0,932, selecionando 4 moléculas com probabilidade de potencial ativo superior a 84%. O estudo do docking das seis enzimas alvo para S. aureus selecionou uma média de 50 moléculas do banco de 421 moléculas isoladas do gênero Solanum com a capacidade de interagir no sitio ativo de cada enzima. Analisando moléculas multitarget, foi possível obter 1 molécula com potencial ativo e capacidade de interação com 5 das 6 enzimas estudadas, 7 moléculas interagindo com 3 enzimas e 6 com 2 enzimas de S. aureus. A rutina, uma molécula potencialmente ativa no estudo in silico para S. aureus e E. coli, juntamente com o carpesterol, foram testadas in vitro contra essas bactérias. Os testes microbiológicos mostraram que o carpesterol não possui atividade antimicrobiana para as cepas estudadas, e que a rutina possui atividade apenas para a cepa de E. coli. Foi realizado ainda estudo de interação com as cepas de S. aureus ATCC 25923, uma cepa padrão sensível a todos os antibióticos, e SAM-01, uma cepa multirresistente. Houve interação apenas entre a rutina e a oxacilina, um dos três antibióticos estudados na interação, para a cepa SAM-01, diminuindo a resistência dessa cepa.

Abstract Localization and tracking of multiple targets is becoming an essential feature of modern communication services and systems. Although necessary in many contexts, such as surveillance and monitoring applications, low-complexity and reliable solutions capable of coping with different degrees of information are not yet available. This thesis deals with different problems that are encountered in localization and tracking applications and aims to establish a broad understanding of multitarget systems ranging from complete active to incomplete passive solutions in dynamic scenarios. Thereby we start by investigating a fully algebraic framework which is proved to be advantageous in dynamic contexts characterized by no a-priori knowledge. Subsequently we extend the approach to improve its robustness versus corrupted observations. Finally we focus on a Bayesian formulation of the passive multitarget tracking (MTT) problem. The Thesis is based on three parts. The first part focuses on a low complexity mathematical representation of the active problem (i.e manifold-based solution). In particular, the spectrum of the matrices used to represent target locations within an algebraic, multidimensional scaling (MDS) based, solution is characterized statistically. In so doing we propose a novel Jacobi-based eigenspace tracking algorithms for Gramian matrices which is shown to be particularly convenient in a multidimensional scaling formulation of the multitarget tracking problem. The second part deals with incomplete-active multitarget scenarios as well as eventual disturbances on the ranging measurements such as bias due to non-line-of-sight conditions. In particular the aforementioned algebraic solution is extended to cope with heterogeneous information and to incorporate eventual knowledge on the confidence of the measurement information. To do so we solve the classical multidimensional scaling (C-MDS) over a novel kernel matrix and show how the intrinsic nature of this formulation allows to deal with heterogeneous information, specifically angle and distance measurements. Finally, the third part focuses on the random finite sets formulation of Bayesian multisensor MTT problem for passive scenarios. In this area a new gating strategy is proposed to lower the computational complexity of the algorithms without compromising their performance. / Tiivistelmä Useiden kohteiden yhtäaikaisesta paikannuksesta ja seurannasta on tulossa olennainen osa nykyaikaisia viestinnän palveluita ja järjestelmiä. Huolimatta siitä, että yhtäaikainen paikannus on erittäin tarpeellinen osa monissa yhteyksissä, kuten valvonnan ja kontrolloinnin sovelluksissa, siihen ei ole olemassa kompleksisuudeltaan alhaista ratkaisua, joka ottaisi huomioon kaiken saatavilla olevan informaation. Väitöskirja käsittelee useiden kohteiden paikannukseen ja seurantaan liittyviä ongelmia, ja se keskittyy antamaan laajan ymmärryksen aktiivisista täydellisistä menetelmistä passiivisiin epätäydellisiin menetelmiin dynaamisissa ympäristöissä. Saavuttaakseen tavoitteen väitöskirjassa esitetään algebrallinen kehys, jonka todistetaan olevan edistyksellinen dynaamisissa ympäristöissä, joissa ei ole ennakkoinformaatiota saatavilla. Seuraavaksi väitöskirja laajentaa esitettyä lähestymistapaa parantamalla sen vakautta vääriä havaintoja vastaan. Lopuksi esitetään bayesialainen formulointi passiiviselle usean kohteen seuranta -ongelmalle (MTT). Väitöskirja on jaettu kolmeen on osaan. Ensimmäinen osa käsittelee aktiivisen ongelman kuvaamista matemaattisesti säilyttäen alhaisen kompleksisuuden. Erityisesti tässä osassa karakterisoidaan tilastollisesti matriisien spektrin käyttäminen kohteiden paikan esittämiseen moniulotteiseen skaalaukseen (MDS) pohjautuvassa menetelmässä. Saavuttaakseen tämän väitöskirja esittää Jacobin ominaisavaruuksiin perustuvan seuranta-algoritmin Gramian matriiseille, joiden osoitetaan olevan erityisen soveltuvia usean kohteen seuraamisongelman kuvaamiseen MDS-menetelmän avulla. Toinen osa käsittelee epätäydellistä aktiivista usean kohteen skenaariota, kuten myös mittausten lopullisia häiriötä, esim. ei-näköyhteyskanavasta johtuvaa harhaa. Edellä mainittu algebrallinen ratkaisu on laajennettu ottamaan huomioon heterogeeninen informaatio sekä tieto mittausdatan luotettavuudesta. Lisäksi tässä osassa esitetään ratkaisu klassiseen moniulotteiseen skaalausongelmaan (C-MDS) esittelemällä uudenlainen ydinmatriisi ja osoitetaan, kuinka tämä mahdollistaa heterogeenisen informaation, tässä tapauksessa kulma-ja etäisyysmittauksien, huomioon ottamisen. Viimeisessä osassa käsitellään äärellisten satunnaisten joukkojen soveltuvuutta bayesialaisen MTT-ongelman ratkaisuun passiivisissa skenaarioissa. Väitöskirja esittää uuden porttistrategian algoritmien kompleksisuuksien pienentämiseksi säilyttäen kuitenkin samalla niiden suorituskyvyn.

Data association problem for multitarget tracking is determination of the relationship between targets and the incoming measurements from sensors of the target tracking system. Performance of a multitarget tracking system is strongly related to the chosen method for data association and target tracking algorithm. Incorrect data association effects state estimation of targets. In this thesis, we propose a new multi-scan data association algorithm for multitarget tracking systems. This algorithm was implemented by using MATLAB programming tool. Performances of the new algorithm and JPDA method for multiple targets tracking are compared. During simulations linear models are used and the uncertainties in the sensor and motion models are modeled by Gaussian density. Simulation results are presented. Results show that the new algorithm&#039 / s performance is better than that of JPDA method. Moreover, a survey over target tracking literature is presented including basics of multitarget tracking systems and existing data association methods.

Artemisinin-based combination therapies (ACTs) are the gold standard for the treatment of malaria, but the efficacy is threatened by the development of parasite resistance. Histone deacetylase inhibitors (HDACis) are an emerging new class of potential antiplasmodial drugs. In this work, we present the design, synthesis, and biological evaluation of a mini library of dihydroartemisinin– HDACi hybrid molecules. The screening of the hybrid molecules for their activity against selected human HDAC isoforms, asexual blood stage P. falciparum parasites, and a panel of leukemia cell lines delivered important structure–activity relationships. All synthesized compounds demonstrated potent activity against the 3D7 and Dd2 line of P. falciparum with IC50 values in the single-digit nanomolar range. Furthermore, the hybrid ()-7c displayed improved activity against artemisininresistant parasites compared to dihydroartemisinin. The screening of the compounds against five cell lines from different leukemia entities revealed that all hydroxamate-based hybrids (7a–e) and the ortho-aminoanilide 8 exceeded the antiproliferative activity of dihydroartemisinin in four out of five cell lines. Taken together, this series of hybrid molecules represents an excellent starting point toward the development of antimalarial and antileukemia drug leads.

Autonomous driving systems are rapidly improving and may have the ability to change society in the coming decade. One important part of these systems is the interpretation of sensor information into trajectories of objects. In this master’s thesis, we study an energy minimisation method with radar and camera measurements as inputs. An energy is associated with the trajectories; this takes the measurements, the objects’ dynamics and more factors into consideration. The trajectories are chosen to minimise this energy, using a gradient descent method. The lower the energy, the better the trajectories are expected to match the real world. The processing is performed offline, as opposed to in real time. Offline tracking can be used in the evaluation of the sensors’ and the real time tracker’s performance. Offline processing allows for the use of more computer power. It also gives the possibility to use data that was collected after the considered point in time. A study of the parameters of the used energy minimisation method is presented, along with variations of the initial method. The results of the method is an improvement over the individual inputs, as well as over the real time processing used in the cars currently. In the parameter study it is shown which components of the energy function are improving the results. / Mycket resurser läggs på utveckling av självkörande bilsystem. Dessa kan komma att förändra samhället under det kommande decenniet. En viktig del av dessa system är behandling och tolkning av sensordata och skapande av banor för objekt i omgivningen. I detta examensarbete studeras en energiminimeringsmetod tillsammans med radar- och kameramätningar. En energi beräknas för banorna. Denna tar mätningarna, objektets dynamik och fler faktorer i beaktande. Banorna väljs för att minimera denna energi med hjälp av gradientmetoden. Ju lägre energi, desto bättre förväntas banorna att matcha verkligheten. Bearbetning sker offline i motsats till i realtid; offline-bearbetning kan användas då prestandan för sensorer och realtidsbehandlingen utvärderas. Detta möjliggör användning av mer datorkraft och ger möjlighet att använda data som samlats in efter den aktuella tidpunkten. En studie av de ingående parametrarna i den använda energiminimeringsmetoden presenteras, tillsammans med justeringar av den ursprungliga metoden. Metoden ger ett förbättrat resultat jämfört med de enskilda sensormätningarna, och även jämfört med den realtidsmetod som används i bilarna för närvarande. I parameterstudien visas vilka komponenter i energifunktionen som förbättrar metodens prestanda.

<p>In this thesis, the problem of estimating the clutter spatial intensity function for the multitarget tracking algorithms has been considered. In many scenarios, after the signal detection process, measurement points provided by the sensor (e.g., sonar, infrared sensor, radar) are not distributed uniformly in the surveillance region as assumed by most tracking algorithms. On the other hand, in order to obtain accurate results, the multitarget tracking algorithm requires information about clutter’s spatial intensity. Thus, non-homogeneous clutter spatial intensity has to be estimated from the measurement set and the tracking filter’s output. Also, in order to take advantage of existing tracking algorithms, it is desirable for the clutter estimation method to be integrated into the tracker itself. In this thesis, the clutter is modeled by a non-homogeneous Poisson point (NHPP) process with a spatial intensity function g(z). To calculate the value of the clutter spatial intensity, all we need to do is estimating g(z). First, two new methods for joint spatial clutter intensity estimation and multitarget tracking using the Probability Hypothesis Density (PHD) Filter are presented. Then, based on NHPP process, multitarget multi-Bernoulli processes and set calculus, the approximated Bayesian method is extended to joint the non–homogeneous clutter background estimation and multitarget tracking with standard multitarget tracking algorithms, like the Multiple Hypothesis Tracking (MHT) and the Joint Integrated Probabilistic Data Association (JIPDA) tracker. Finally, a kernel density method is proposed for the clutter spatial intensity estimation problem. Simulation results illustrate the performance of the above algorithms, both in terms of the false track number and the true track initialization speed. All proposed algorithms show the ability to improve the performance of the multitarget tracker in the presence of slowly time varying non–homogeneous clutter background.</p> / Doctor of Philosophy (PhD)

This dissertation addresses two fundamental problems in computer vision—namely, multitarget tracking and event recognition in videos. These problems are challenging because uncertainty may arise from a host of sources, including motion blur, occlusions, and dynamic cluttered backgrounds. We show that these challenges can be successfully addressed by using a multiscale, volumetric video representation, and taking into account various constraints between events offered by domain knowledge. The dissertation presents our two alternative approaches to multitarget tracking. The first approach seeks to transitively link object detections across consecutive video frames by finding the maximum independent set of a graph of all object detections. Two maximum-independent-set algorithms are specified, and their convergence properties theoretically analyzed. The second approach hierarchically partitions the space-time volume of a video into tracks of objects, producing a segmentation graph of that video. The resulting tracks encode rich contextual cues between salient video parts in space and time, and thus facilitate event recognition, and segmentation in space and time. We also describe our two alternative approaches to event recognition. The first approach seeks to learn a structural probabilistic model of an event class from training videos represented by hierarchical segmentation graphs. The graph model is then used for inference of event occurrences in new videos. Learning and inference algorithms are formulated within the same framework, and their convergence rates theoretically analyzed. The second approach to event recognition uses probabilistic first-order logic for reasoning over continuous time intervals. We specify the syntax, learning, and inference algorithms of this probabilistic event logic. Qualitative and quantitative results on benchmark video datasets are also presented. The results demonstrate that our approaches provide consistent video interpretation with respect to acquired domain knowledge. We outperform most of the state-of-the-art approaches on benchmark datasets. We also present our new basketball dataset that complements existing benchmarks with new challenges. / Graduation date: 2011 / Access restricted to the OSU Community at author's request from May 12, 2011 - May 12, 2012

In this thesis study, single target tracking algorithms including IMM-PDA and IMM-IPDA algorithms / Optimal approaches in multitarget tracking including IMM-JPDA, IMM-IJPDA and IMM-JIPDA algorithms and an example of Linear Multi-target approaches in multitarget tracking including IMM-LMIPDA algorithm have been studied and implemented in MATLAB for comparison. Simulations were carried out in various realistic test scenarios including single target tracking, tracking of multiple targets moving in convoy fashion, two targets merging in a junction, two targets merging-departing in junctions and multitarget tracking under isolated tracks situations. RMSE performance, track loss and computational load evaluations were done for these algorithms under the test scenarios dealing with these situations. Benchmarkings are presented relying on these outcomes.