Penalty Dynamic Programming Algorithm for Dim Targets Detection in Sensor Systems

In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD) called penalty DP-TBD (PDP-TBD) is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, the algorithm combines traditional tracking techniques with DP-TBD and it can be applied to simultaneously detect and track maneuvering dim targets. Meanwhile, a reasonable constraint that a sensor measurement can originate from one target or clutter is proposed to minimize track separation. Thus, the algorithm can be used in the multi-target situation with unknown target numbers. The efficiency and advantages of PDP-TBD compared with two existing methods are demonstrated by several simulations

MOTChallenge: A Benchmark for Single-Camera Multiple Target Tracking

Standardized benchmarks have been crucial in pushing the performance of computer vision algorithms, especially since the advent of deep learning. Although leaderboards should not be over-claimed, they often provide the most objective measure of performance and are therefore important guides for research. We present MOTChallenge, a benchmark for single-camera Multiple Object Tracking (MOT) launched in late 2014, to collect existing and new data, and create a framework for the standardized evaluation of multiple object tracking methods. The benchmark is focused on multiple people tracking, since pedestrians are by far the most studied object in the tracking community, with applications ranging from robot navigation to self-driving cars. This paper collects the first three releases of the benchmark: (i) MOT15, along with numerous state-of-the-art results that were submitted in the last years, (ii) MOT16, which contains new challenging videos, and (iii) MOT17, that extends MOT16 sequences with more precise labels and evaluates tracking performance on three different object detectors. The second and third release not only offers a significant increase in the number of labeled boxes but also provide labels for multiple object classes beside pedestrians, as well as the level of visibility for every single object of interest. We finally provide a categorization of state-of-the-art trackers and a broad error analysis. This will help newcomers understand the related work and research trends in the MOT community, and hopefully shed some light on potential future research directions.Comment: Accepted at IJC

Tracking interacting targets in multi-modal sensors

PhDObject tracking is one of the fundamental tasks in various applications such as surveillance, sports, video conferencing and activity recognition. Factors such as occlusions, illumination changes and limited field of observance of the sensor make tracking a challenging task. To overcome these challenges the focus of this thesis is on using multiple modalities such as audio and video for multi-target, multi-modal tracking. Particularly, this thesis presents contributions to four related research topics, namely, pre-processing of input signals to reduce noise, multi-modal tracking, simultaneous detection and tracking, and interaction recognition. To improve the performance of detection algorithms, especially in the presence of noise, this thesis investigate filtering of the input data through spatio-temporal feature analysis as well as through frequency band analysis. The pre-processed data from multiple modalities is then fused within Particle filtering (PF). To further minimise the discrepancy between the real and the estimated positions, we propose a strategy that associates the hypotheses and the measurements with a real target, using a Weighted Probabilistic Data Association (WPDA). Since the filtering involved in the detection process reduces the available information and is inapplicable on low signal-to-noise ratio data, we investigate simultaneous detection and tracking approaches and propose a multi-target track-beforedetect Particle filtering (MT-TBD-PF). The proposed MT-TBD-PF algorithm bypasses the detection step and performs tracking in the raw signal. Finally, we apply the proposed multi-modal tracking to recognise interactions between targets in regions within, as well as outside the cameras’ fields of view. The efficiency of the proposed approaches are demonstrated on large uni-modal, multi-modal and multi-sensor scenarios from real world detections, tracking and event recognition datasets and through participation in evaluation campaigns

Genetics of Primary Immunodeficiency in Finland

Primary Immunodeficiency (PIDs) categorize a broad and heterogeneous group of inborn immunity errors. Despite being generally quite rare, PIDs collectively account for consistent morbidity and mortality. Currently, more than 350 monogenic PIDs have been recognised to embody clinical phenotypes ranging from life-threatening infections to autoimmune/inflammatory diseases, allergies and/or malignancy. Many PIDs display genetic and allelic heterogeneity with an overlap of symptoms among different syndromes, often making diagnoses challenging. In the past few years, advancements in genomic technologies have revolutionised the world of genetic testing, and currently, next-generation sequencing (NGS)-based approaches are widely applied to routine genetic diagnostics of human disorders. Among the different methods, whole-exome sequencing (WES) proved highly efficient in revealing the genetic variants behind rare disorders. To further depict the genetics of PIDs, a WES-based approach was carried out, targeting the possible disease-causing variants in Finnish subjects lacking a clinical diagnosis. The cohort included patients with a clinical suspicion of immune or/and haematological disorders (n= 212). In the first study, a Finnish founder mutation in the AICDA gene was identified in patients affected by hyper-IgM syndrome type 2 (HIGM2). The disease is a primary antibody deficiency characterised by early-onset recurrent infections, autoimmunity and an absence/low levels of IgG, IgA and IgE but elevated/normal levels of IgM. The retrieved ancestral founder allele is significantly enriched in Finns compared to other European populations (38.56-fold) and has accounted for all HIGM2 cases diagnosed in Finns thus far. In the second study, biallelic ADA2 mutations that cause a deficiency of adenosine deaminase 2 (DADA2) were identified in seven PID patients, all sharing one of the causal variants, which were significantly enriched in Finns (3.31-fold). DADA2 was originally associated with systemic autoinflammation, polyarteritis nodosa-type vasculitis and mild immunodeficiency. Only a fraction of the identified DADA2 patients presented with vasculopathies. In addition, recurrent haematological manifestations are noted, and for the first time, the occurrence of lymphoproliferation is described for some of the patients, expanding the phenotypic spectrum of DADA2. Finally, novel causal variants in telomere biology disorders (TBDs)-associated genes were identified in three families with heterogeneous phenotypes that lacked the classic clinical pathognomonic signs of telomeropathies. The phenotypes ranged from mild signs of Dyskeratosis congenita (DKC) to SCID. The genetic diagnosis was confirmed by an assessment of shortened telomere lengths in patients. In addition, the spectrum of TBD-associated phenotypes was enlarged, showing variable degrees of cytopenia in some patients. This work attests to the validity of clinical WES testing to identify rare disease-causing variants despite the heterogeneous and/or atypical clinical presentations of PIDs. The achievement of a genetic diagnosis allowed for updating the spectrum of reported phenotypes as well as including atypical clinical presentations that might have otherwise remained undiagnosed. In addition, the enrichment of some rare PID-causing mutations in Finland has been depicted, highlighting the correlation of the population history with the distribution of rare deleterious variants of clinical relevance.Primary Immunodeficiency (PIDs) categorize a broad and heterogeneous group of inborn immunity errors. Despite being generally quite rare, PIDs collectively account for consistent morbidity and mortality. Currently, more than 350 monogenic PIDs have been recognised to embody clinical phenotypes ranging from life-threatening infections to autoimmune/inflammatory diseases, allergies and/or malignancy. Many PIDs display genetic and allelic heterogeneity with an overlap of symptoms among different syndromes, often making diagnoses challenging. In the past few years, advancements in genomic technologies have revolutionised the world of genetic testing, and currently, next-generation sequencing (NGS)-based approaches are widely applied to routine genetic diagnostics of human disorders. Among the different methods, whole-exome sequencing (WES) proved highly efficient in revealing the genetic variants behind rare disorders. To further depict the genetics of PIDs, a WES-based approach was carried out, targeting the possible disease-causing variants in Finnish subjects lacking a clinical diagnosis. The cohort included patients with a clinical suspicion of immune or/and haematological disorders (n= 212). In the first study, a Finnish founder mutation in the AICDA gene was identified in patients affected by hyper-IgM syndrome type 2 (HIGM2). The disease is a primary antibody deficiency characterised by early-onset recurrent infections, autoimmunity and an absence/low levels of IgG, IgA and IgE but elevated/normal levels of IgM. The retrieved ancestral founder allele is significantly enriched in Finns compared to other European populations (38.56-fold) and has accounted for all HIGM2 cases diagnosed in Finns thus far. In the second study, biallelic ADA2 mutations that cause a deficiency of adenosine deaminase 2 (DADA2) were identified in seven PID patients, all sharing one of the causal variants, which were significantly enriched in Finns (3.31-fold). DADA2 was originally associated with systemic autoinflammation, polyarteritis nodosa-type vasculitis and mild immunodeficiency. Only a fraction of the identified DADA2 patients presented with vasculopathies. In addition, recurrent haematological manifestations are noted, and for the first time, the occurrence of lymphoproliferation is described for some of the patients, expanding the phenotypic spectrum of DADA2. Finally, novel causal variants in telomere biology disorders (TBDs)-associated genes were identified in three families with heterogeneous phenotypes that lacked the classic clinical pathognomonic signs of telomeropathies. The phenotypes ranged from mild signs of Dyskeratosis congenita (DKC) to SCID. The genetic diagnosis was confirmed by an assessment of shortened telomere lengths in patients. In addition, the spectrum of TBD-associated phenotypes was enlarged, showing variable degrees of cytopenia in some patients. This work attests to the validity of clinical WES testing to identify rare disease-causing variants despite the heterogeneous and/or atypical clinical presentations of PIDs. The achievement of a genetic diagnosis allowed for updating the spectrum of reported phenotypes as well as including atypical clinical presentations that might have otherwise remained undiagnosed. In addition, the enrichment of some rare PID-causing mutations in Finland has been depicted, highlighting the correlation of the population history with the distribution of rare deleterious variants of clinical relevance

Development and Characterization of a Filter-Based Bioaerosol Sampler Capable of Integration into Small Unmanned Aerial Systems

In developing functional SUAS, performance characteristics that indicate system capability should be developed prior to initiating initial system design. Key performance parameters should be developed involving all system elements (including vehicle body, operator, ground station, sensor, and algorithm or processing module). A bioaerosol sampler designed specifically for the use in SUAS was characterized based on designated performance measures to determine overall effectiveness compared to traditional bioaerosol samplers. For a system with a goal of accurately identifying and quantifying areas of airborne biological contamination or surveying background levels for longitudinal studies, performance parameters such as weight of the vehicle with payload and sampler specific parameters will be quantitatively evaluated. These sampler-specific parameters include operational noise levels, power demand compared to performance, and sampling fraction. These were evaluated in a series of lab-based tests to determine if the developed model of bioaerosol sampler could be deployed for use in military environments. Overall, it was found that the developed EOS inlet oversampled for the background concentrations compared to the modeled performance for the inlet, and oversampled compared to the closed face cassette filter. This may be due to ground effects acting on the system—as the bottom placement for the sampler performed worse than expected based on previous research in comparison to the sampler closer to the rotors

Knowledge-Based Analysis of Genomic Expression Data by Using Different Machine Learning Algorithms for the Purpose of Diagnostic, Prognostic or Therapeutic Application

With more and more biological information generated, the most pressing task of bioinformatics has become to analyze and interpret various types of data, including nucleotide and amino acid sequences, protein structures, gene expression profiling and so on. In this dissertation, we apply the data mining techniques of feature generation, feature selection, and feature integration with learning algorithms to tackle the problems of disease phenotype classification, clinical outcome and patient survival prediction from gene expression profiles. We analyzed the effect of batch noise in microarray data on the performance of classification. Batchmatch, a batch adjusting algorithm based on double scaling method is advantageous over Combat, another batch correcting algorithm based on the empirical bayes frame work. In order to identify genes associated with disease phenotype classification or patient survival prediction from gene expression data, we compared and analyzed the performance of five feature selection algorithms. Our observations from these studies indicated that Gainratio algorithm performs better and more consistently over the other algorithms studied. When it comes to performance metric to choose the best classifiers, MCC gives unbiased performance results over accuracy in some endpoints, where class imbalance is more. In the aspect of classification algorithms, no single algorithm is absolutely superior to all others, though SVM achieved fairly good results in most endpoints. Naive bayes algorithm also performed well in some endpoints. Overall, from the total 65 models we reported (5 top models for 13 end points) SVM and SMO (a variant of SVM) dominate mostly, also the linear kernel performed well over RBF in our binary classifications

A review on the eco-epidemiology and clinical management of human granulocytic anaplasmosis and its agent in Europe

Anaplasma phagocytophilum is the agent of tick-borne fever, equine, canine and human granulocytic anaplasmosis. The common route of A. phagocytophilum transmission is through a tick bite, the main vector in Europe being Ixodes ricinus. Despite the apparently ubiquitous presence of the pathogen A. phagocytophilum in ticks and various wild and domestic animals from Europe, up to date published clinical cases of human granulocytic anaplasmosis (HGA) remain rare compared to the worldwide status. It is unclear if this reflects the epidemiological dynamics of the human infection in Europe or if the disease is underdiagnosed or underreported. Epidemiologic studies in Europe have suggested an increased occupational risk of infection for forestry workers, hunters, veterinarians, and farmers with a tick-bite history and living in endemic areas. Although the overall genetic diversity of A. phagocytophilum in Europe is higher than in the USA, the strains responsible for the human infections are related on both continents. However, the study of the genetic variability and assessment of the difference of pathogenicity and infectivity between strains to various hosts has been insufficiently explored to date. Most of the European HGA cases presented as a mild infection, common clinical signs being pyrexia, headache, myalgia and arthralgia. The diagnosis of HGA in the USA was recommended to be based on clinical signs and the patient’s history and later confirmed using specialized laboratory tests. However, in Europe since the majority of cases are presenting as mild infection, laboratory tests may be performed before the treatment in order to avoid antibiotic overuse. The drug of choice for HGA is doxycycline and because of potential for serious complication the treatment should be instituted on clinical suspicion alone