AN EXPERIMENTAL INVESTIGATION INTO THE EFFECT OF PARTICULATE MATTER ON NOx REDUCTION IN A SCR CATALYST ON A DPF

The study of NOx reduction across the SCRF® is presented in this report to understand the inlet and outlet NO, NO2, NH3 species from the SCRF®. The SCRF® is a prototype SCR catalyst on a Diesel Particulate Filter (DPF) that reduces NOx and PM at the downstream location. The SCRF® reduces the packaging volume of the aftertreatment components in order to reduce the cost, volume and weight of the aftertreatment system. A total of 12 experiments were performed on a Cummins ISB 2013 280 hp engine and the aftertreatment system. The tests were performed to investigate the NOx reduction performance of the SCRF® under various Particulate Matter loading. The loading phase has been divided into two stages: Stage 1 and Stage 2. Stage 1 begins after all the PM has been removed from the SCRF®, which is then followed by Stage 2 loading. The engine is run at 2400 rpm and 200 Nm load with different fuel rail pressures for a duration to achieve PM loadings of 0, 2, and 4 g/L (grams of PM per volume of the SCRF®) in the SCRF®. For the testing of the SCRF® without PM loading, a Catalyzed Particulate Filter (CPF) was placed before the SCRF®. After the loading phase, NOx reduction stage was run at different engine conditions. The engine speed and load conditions were selected for the NOx reduction stage, named as test points 1, 3, 6, and 8, in order to attain a wide range in space velocities, inlet temperatures and NO2/NOx ratios in the SCRF®, which are the major parameters determining NOx reduction efficiency in the SCRF®. The exhaust temperature varied from 206 to 443 °C, inlet NO2/ NOx ratio varied from 0.22 to 0.46, and space velocity varied from 13.5 to 48.2 k/hr. Urea was dosed in the decomposition tube before the SCRF® to determine the NOx conversion efficiency at different ammonia to NOx ratio (ANR) values. The ANR values considered for the NOx reduction and NH3 slip were 0, 0.8, 1, 1.2, and 1.2 repeat. The ANR of 1.2 was repeated in the urea dosing cycle. It was found that the NOx conversion efficiency across the SCRF® is maximum for test points 3 and 6 i.e. for the temperature range of 300-350 °C. The NO2/NOx ratio at those points was around 0.42-0.46. It is observed that the loading in the SCRF® does not affect the NOx conversion efficiency at low (205 °C) and high (440 °C) temperature points but affects in between. The NOx conversion efficiency improved with PM loading until 300°C SCRF® inlet temperature and decreased (with PM loading) after 350 °C. There is noticeable ammonia oxidation at temperatures above 400 °C in the SCRF® that affects NOx conversion efficiency [1]. At higher temperature of about 440 °C, NH3 slip is observed varying with PM loading in the SCRF®. With PM loading, NO2 assisted oxidation increases the concentration of NO [2] and affects the NOx conversion efficiency. It is concluded from the results that the NO2 concentration across the SCRF® decreased with PM loading and SCRF® temperature due to NO2 assisted PM oxidation. The impact of PM loading on NOx reduction in the SCRF® was insignificant below 300 °C. NOx conversion decreased by 3 – 5 % above 350 °C with increase in PM loading from 0 to 2 and 4 g/L, due to consumption of NO2 via passive oxidation of PM. The NOx concentration is not completely converted across the SCRF® at temperatures above 350 °C even if dosed with an ANR value of 1.2

Dynamic Motion Planning for Aerial Surveillance on a Fixed-Wing UAV

We present an efficient path planning algorithm for an Unmanned Aerial Vehicle surveying a cluttered urban landscape. A special emphasis is on maximizing area surveyed while adhering to constraints of the UAV and partially known and updating environment. A Voronoi bias is introduced in the probabilistic roadmap building phase to identify certain critical milestones for maximal surveillance of the search space. A kinematically feasible but coarse tour connecting these milestones is generated by the global path planner. A local path planner then generates smooth motion primitives between consecutive nodes of the global path based on UAV as a Dubins vehicle and taking into account any impending obstacles. A Markov Decision Process (MDP) models the control policy for the UAV and determines the optimal action to be undertaken for evading the obstacles in the vicinity with minimal deviation from current path. The efficacy of the proposed algorithm is evaluated in an updating simulation environment with dynamic and static obstacles.Comment: Accepted at International Conference on Unmanned Aircraft Systems 201

Teaching Matters: Investigating the Role of Supervision in Vision Transformers

Vision Transformers (ViTs) have gained significant popularity in recent years and have proliferated into many applications. However, their behavior under different learning paradigms is not well explored. We compare ViTs trained through different methods of supervision, and show that they learn a diverse range of behaviors in terms of their attention, representations, and downstream performance. We also discover ViT behaviors that are consistent across supervision, including the emergence of Offset Local Attention Heads. These are self-attention heads that attend to a token adjacent to the current token with a fixed directional offset, a phenomenon that to the best of our knowledge has not been highlighted in any prior work. Our analysis shows that ViTs are highly flexible and learn to process local and global information in different orders depending on their training method. We find that contrastive self-supervised methods learn features that are competitive with explicitly supervised features, and they can even be superior for part-level tasks. We also find that the representations of reconstruction-based models show non-trivial similarity to contrastive self-supervised models. Project website (https://www.cs.umd.edu/~sakshams/vit_analysis) and code (https://www.github.com/mwalmer-umd/vit_analysis) are publicly available.Comment: Website: see https://www.cs.umd.edu/~sakshams/vit_analysis. Code: see https://www.github.com/mwalmer-umd/vit_analysis. The first two authors contributed equally. Accepted to CVPR 2023 as conference pape

Effective Gesture Based Framework for Capturing User Input

Computers today aren't just confined to laptops and desktops. Mobile gadgets like mobile phones and laptops also make use of it. However, one input device that hasn't changed in the last 50 years is the QWERTY keyboard. Users of virtual keyboards can type on any surface as if it were a keyboard thanks to sensor technology and artificial intelligence. In this research, we use the idea of image processing to create an application for seeing a computer keyboard using a novel framework which can detect hand gestures with precise accuracy while also being sustainable and financially viable. A camera is used to capture keyboard images and finger movements which subsequently acts as a virtual keyboard. In addition, a visible virtual mouse that accepts finger coordinates as input is also described in this study. This system has a direct benefit of reducing peripheral cost, reducing electronics waste generated due to external devices and providing accessibility to people who cannot use the traditional keyboard and mouse

On designing light-weight object trackers through network pruning: Use CNNs or transformers?

Object trackers deployed on low-power devices need to be light-weight, however, most of the current state-of-the-art (SOTA) methods rely on using compute-heavy backbones built using CNNs or transformers. Large sizes of such models do not allow their deployment in low-power conditions and designing compressed variants of large tracking models is of great importance. This paper demonstrates how highly compressed light-weight object trackers can be designed using neural architectural pruning of large CNN and transformer based trackers. Further, a comparative study on architectural choices best suited to design light-weight trackers is provided. A comparison between SOTA trackers using CNNs, transformers as well as the combination of the two is presented to study their stability at various compression ratios. Finally results for extreme pruning scenarios going as low as 1% in some cases are shown to study the limits of network pruning in object tracking. This work provides deeper insights into designing highly efficient trackers from existing SOTA methods.Comment: Submitted at IEEE ICASSP 202

The Epigenomics of Pituitary Adenoma

Background: The vast majority of pituitary tumors are benign and behave accordingly; however, a fraction are invasive and are more aggressive, with a very small fraction being frankly malignant. The cellular pathways that drive transformation in pituitary neoplasms are poorly characterized, and current classification methods are not reliable correlates of clinical behavior. Novel techniques in epigenetics, the study of alterations in gene expression without changes to the genetic code, provide a new dimension to characterize tumors, and may hold implications for prognostication and management.Methods: We conducted a review of primary epigenetic studies of pituitary tumors with a focus on histone modification, DNA methylation, and transcript modification.Results: High levels of methylation have been identified in invasive and large pituitary tumors. DNA methyltransferase overexpression has been detected in pituitary tumors, especially in macroadenomas. Methylation differences at CpG sites in promoter regions may distinguish several types of tumors from normal pituitary tissue. Histone modifications have been linked to increased p53 expression and longer progression-free survival in pituitary tumors; sirtuins are expressed at higher values in GH-expressing compared to nonfunctional adenomas and correlate inversely with size in somatotrophs. Upregulation in citrullinating enzymes may be an early pathogenic marker of prolactinomas. Numerous genes involved with cell growth and signaling show altered methylation status for pituitary tumors, including cell cycle regulators, components of signal transduction pathways, apoptotic regulators, and pituitary developmental signals.Conclusions: The limited clinical predictive capacity of the current pituitary tumor classification system suggests that tumor subclasses likely remain to be discovered. Ongoing epigenetic studies could provide a basis for adding methylation and/or acetylation screening to standard pituitary tumor workups. Identifying robust correlations between tumor epigenetics and corresponding histological, radiographic, and clinical course information could ultimately inform clinical decision-making

QTL mapping for resistance against cereal cyst nematode (Heterodera avenae Woll.) in wheat (Triticum aestivum L.)

The resistance to cereal cyst nematode (Heterodera avenae Woll.) in wheat (Triticum aestivum L.) was studied using 114 doubled haploid lines from a novel ITMI mapping population. These lines were screened for nematode infestation in a controlled environment for two years. QTL-mapping analyses were performed across two years (Y1 and Y2) as well as combining two years (CY) data. On the 114 lines that were screened, a total of 2,736 data points (genotype, batch or years, and replication combinations) were acquired. For QTL analysis, 12,093 markers (11,678 SNPs and 415 SSRs markers) were used, after filtering the genotypic data, for the QTL mapping. Composite interval mapping, using Haley-Knott regression (hk) method in R/QTL, was used for QTL analysis. In total, 19 QTLs were detected out of which 13 were novel and six were found to be colocalized or nearby to previously reported Cre genes, QTLs or MTAs for H. avenae or H. filipjevi. Nine QTLs were detected across all three groups (Y1, Y2 and CY) including a significant QTL "QCcn.ha-2D" on chromosome 2D that explains 23% of the variance. This QTL colocalized with a previously identified Cre3 locus. Novel QTL, QCcn.ha-2A, detected in the present study could be the possible unreported homeoloci to QCcn.ha-2D, QCcn.ha-2B.1 and QCcn.ha-2B.2. Six significant digenic epistatic interactions were also observed. In addition, 26 candidate genes were also identified including genes known for their involvement in PPNs (plant parasitic nematodes) resistance in different plant species. In-silico expression of putative candidate genes showed differential expression in roots during specific developmental stages. Results obtained in the present study are useful for wheat breeding to generate resistant genetic resources against H. avenae