Human Machine Collaboration for Multiple Object Tracking in Videos

While modern computer vision solutions have achieved impressive strides, the level of accuracy for many complicated tasks is still not on par with human intelligence. In particular, humans are incredibly adept at generalizing to novel scenarios. Yet, humans need automation to minimize mundane tasks and improve efficiency. This inter-dependency of humans and algorithms warrants collaborative work to leverage each other&rsquo;s strengths towards a shared goal, via human-machine collaboration, also referred to as hybrid solutions. One such complicated task that has the potential of benefiting from hybrid solutions is Multi-Object Tracking or MOT. For this task, the aim is to detect and track every single object in videos. Annotating every single object at a frame level is an inefficient use of human time and effort, yet automated trackers are still struggling to adapt to novel domains with challenging scenarios (e.g., occlusions, tiny or similar looking objects). In this thesis, I explore hybrid solutions to support tracking of a diverse categories of objects in videos. To do so, I first explore a human computation based approach, i.e., crowdsourcing with new strategies to establish a scalable approach to tracking objects. Next, I explore state-of-the-art algorithmic capabilities to highlight their strengths and weaknesses, with an emphasis on their generalization capabilities in tracking domain-specific objects (i.e., biological cells), and proposea new cell tracking dataset that is larger and more diverse than prior datasets to support model development. Finally, I explore hybrid solutions and propose an approach to track novel objects in videos without the need of large human-labeled datasets.</p

VEGAWES: variational segmentation on whole exome sequencing for copy number detection

Background Copy number variations are important in the detection and progression of significant tumors and diseases. Recently, Whole Exome Sequencing is gaining popularity with copy number variations detection due to low cost and better efficiency. In this work, we developed VEGAWES for accurate and robust detection of copy number variations on WES data. VEGAWES is an extension to a variational based segmentation algorithm, VEGA: Variational estimator for genomic aberrations, which has previously outperformed several algorithms on segmenting array comparative genomic hybridization data. Results We tested this algorithm on synthetic data and 100 Glioblastoma Multiforme primary tumor samples. The results on the real data were analyzed with segmentation obtained from Single-nucleotide polymorphism data as ground truth. We compared our results with two other segmentation algorithms and assessed the performance based on accuracy and time. Conclusions In terms of both accuracy and time, VEGAWES provided better results on the synthetic data and tumor samples demonstrating its potential in robust detection of aberrant regions in the genome

Microbial Fuel Cell Formulation from Nano-Composites

Petroleum and oil industry is a rich source of nonrenewable energy that ultimately results in threatening of ecosystem due to emission of greenhouse gases into the environment. In the current panorama of the energy demand, industries focus on alternate and renewable energy resources to meet energy gaps. Thus, an expedient fuel cell based on microbes can be valued as an economical and ecofriendly substitute of energy generator. These microbial fuel cells have commercialized platinum electrodes to generate cost-effective energy after oxidation of organic wastes catalyzed by biocatalyst. Nowadays, conventional carbon electrode as an anode is taking popularity in microbial fuel cell but displays poor performance. So, to improve the chemistry of electrodes, nano-composites fabricated from polar polymeric material as well as cost-effective oxides of metals are the raw material. In this chapter, green synthesis of nano-composites from conducting polymers and oxides of transition metals has been discussed. Anode modification by composite to treat wastewater as well as its role to generate electricity has been discussed briefly

Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma

Therapy development for adult diffuse glioma is hindered by incomplete knowledge of somatic glioma driving alterations and suboptimal disease classification. We defined the complete set of genes associated with 1,122 diffuse grade II-III-IV gliomas from The Cancer Genome Atlas and used molecular profiles to improve disease classification, identify molecular correlations, and provide insights into the progression from low- to high-grade disease. Whole-genome sequencing data analysis determined that ATRX but not TERT promoter mutations are associated with increased telomere length. Recent advances in glioma classification based on IDH mutation and 1p/19q co-deletion status were recapitulated through analysis of DNA methylation profiles, which identified clinically relevant molecular subsets. A subtype of IDH mutant glioma was associated with DNA demethylation and poor outcome; a group of IDH-wild-type diffuse glioma showed molecular similarity to pilocytic astrocytoma and relatively favorable survival. Understanding of cohesive disease groups may aid improved clinical outcomes

Kinetic characterization of glucose aerodehydrogenase from Aspergillus niger EMS-150-F after optimizing the dose of mutagen for enhanced production of enzyme

In the present study enhanced production of glucose aerodehydrogenase from Aspergillus niger has been achieved after optimizing the dose of chemical mutagen ethyl methane sulfonate (EMS) that has not been reported earlier. Different doses of mutagen were applied and a strain was developed basing upon the best production. The selected strain Aspergillus niger EMS-150-F was optimized for nutrient requirements in order to produce enzyme through fermentation and the results showed the best yield at 2% corn steep liquor (CSL), 36 hours fermentation time, pH 5, 30°C temperature, 0.3% KH2PO4, 0.3% urea and 0.06% CaCO3. The enzyme was then purified and resulted in 57.88 fold purification with 52.12% recovery. On kinetic characterization, the enzyme showed optimum activity at pH 6 and temperature 30°C. The Michaelis-Menton constants (Km, Vmax, Kcat and Kcat/Km) were 20 mM, 45.87 U mL-1, 1118.81 s-1 and 55.94 s-1 mM-1, respectively. The enzyme was found to be thermaly stable and the enthalpy and free energy showed an increase with increase in temperature and &#916;S* was highly negative proving the enzyme from A. niger EMS-150-F resistant to temperature and showing a very little disorderliness

Evaluation of Antimicrobial Activity of Glucose Oxidase from Aspergillus niger EBL-A and Penicillium notatum

This work aimed to study the production and purification of glucose oxidase by Aspergillus niger and Penicillium notatum using corn steep liquor as the substrate and evaluate its antimicrobial activity for use in pharmaceutical and food industries. The enzyme was purified by ammonium sulfate precipitation (60-85%), DEAE-cellulose ion exchange and Sephadex G-200 size exclusion chromatography. The crude enzyme extracts of A. niger and P. notatum showed 2.32 and 5.53 U mg-1 specific activities, respectively, which after desalting was 15.52 and 12.05 U mg-1, and after ion exchange and gel filtration chromatography was 29.09 - 62 and 25.72 - 59.37 U mg-1 for A. niger and P. notatum, respectively. The antimicrobial activity was determined by disc diffusion method against selected microbial strains where glucose oxidase from A. niger showed anti-bacterial activity, while no fungicidal effects were shown by both A. niger and P. notatum glucose oxidases

Remote Sensing for Precise Nutrient Management in Agriculture

Agricultural sustainability and food security are adversely affected by nutrient deficiency in the soil that in turn reduces crop yield. To restore soil fertility, precision agriculture (PA) techniques are highly encouraged. The PA techniques include the use of integrated sensors, information systems, better-quality machinery, and informed management to improve productivity. The quality and quantity of agricultural products can be improved by precision farming. The use of remote sensing is a nondestructive technique that facilitates the application of PA. The nutrient use efficiency of crops can be improved by using PA technology. In this regard, various remote sensing techniques including hyperspectral remote sensing, visible light remote sensing, and the back-propagation neural network (BPNN) model combined with ordinary kriging (OK) known as BPNKOK are currently being employed to improve soil nutrients management. These techniques assist in non-destructive monitoring of plant growth and hence aid in sustaining crop yields

MAQSA: A System for Social Analytics on News

Demonstration session: social- or user-centeredInternational audienceWe present MAQSA, a system for social analytics on news. MAQSA provides an interactive topic-centric dashboard that summarizes news articles and social activity (e.g., comments and tweets) around them. MAQSA helps editors and publishers in newsrooms understand user engagement and audience sentiment evolution on various topics of interest. It also helps news consumers explore public reaction on articles relevant to a topic and refine their exploration via related entities, topics, articles and tweets. Given a topic, e.g., "Gulf Oil Spill," or "The Arab Spring", MAQSA combines three key dimensions: time, geographic location, and topic to generate a detailed activity dashboard around relevant articles. The dashboard contains an annotated comment timeline and a social graph of comments. It utilizes commenters' locations to build maps of comment sentiment and topics by region of the world. Finally, to facilitate exploration, MAQSA provides listings of related entities, articles, and tweets. It algorithmically processes large collections of articles and tweets, and enables the dynamic specification of topics and dates for exploration. In this demo, participants will be invited to explore the social dynamics around articles on oil spills, the Libyan revolution, and the Arab Spring. In addition, participants will be able to define and explore their own topics dynamically