Low Bit-rate Color Video Compression using Multiwavelets in Three Dimensions

In recent years, wavelet-based video compressions have become a major focus of research because of the advantages that it provides. More recently, a growing thrust of studies explored the use of multiple scaling functions and multiple wavelets with desirable properties in various fields, from image de-noising to compression. In term of data compression, multiple scaling functions and wavelets offer a greater flexibility in coefficient quantization at high compression ratio than a comparable single wavelet. The purpose of this research is to investigate the possible improvement of scalable wavelet-based color video compression at low bit-rates by using three-dimensional multiwavelets. The first part of this work included the development of the spatio-temporal decomposition process for multiwavelets and the implementation of an efficient 3-D SPIHT encoder/decoder as a common platform for performance evaluation of two well-known multiwavelet systems against a comparable single wavelet in low bitrate color video compression. The second part involved the development of a motion-compensated 3-D compression codec and a modified SPIHT algorithm designed specifically for this codec by incorporating an advantage in the design of 2D SPIHT into the 3D SPIHT coder. In an experiment that compared their performances, the 3D motion-compensated codec with unmodified 3D SPIHT had gains of 0.3dB to 4.88dB over regular 2D wavelet-based motion-compensated codec using 2D SPIHT in the coding of 19 endoscopy sequences at 1/40 compression ratio. The effectiveness of the modified SPIHT algorithm was verified by the results of a second experiment in which it was used to re-encode 4 of the 19 sequences with lowest performance gains and improved them by 0.5dB to 1.0dB. The last part of the investigation examined the effect of multiwavelet packet on 3-D video compression as well as the effects of coding multiwavelet packets based on the frequency order and energy content of individual subbands

Computational analysis of a novel mutation in ETFDH gene highlights its long-range effects on the FAD-binding motif

<p>Abstract</p> <p>Background</p> <p>Multiple acyl-coenzyme A dehydrogenase deficiency (MADD) is an autosomal recessive disease caused by the defects in the mitochondrial electron transfer system and the metabolism of fatty acids. Recently, mutations in electron transfer flavoprotein dehydrogenase (<it>ETFDH</it>) gene, encoding electron transfer flavoprotein:ubiquinone oxidoreductase (ETF:QO) have been reported to be the major causes of riboflavin-responsive MADD. To date, no studies have been performed to explore the functional impact of these mutations or their mechanism of disrupting enzyme activity.</p> <p>Results</p> <p>High resolution melting (HRM) analysis and sequencing of the entire <it>ETFDH </it>gene revealed a novel mutation (p.Phe128Ser) and the hotspot mutation (p.Ala84Thr) from a patient with MADD. According to the predicted 3D structure of ETF:QO, the two mutations are located within the flavin adenine dinucleotide (FAD) binding domain; however, the two residues do not have direct interactions with the FAD ligand. Using molecular dynamics (MD) simulations and normal mode analysis (NMA), we found that the p.Ala84Thr and p.Phe128Ser mutations are most likely to alter the protein structure near the FAD binding site as well as disrupt the stability of the FAD binding required for the activation of ETF:QO. Intriguingly, NMA revealed that several reported disease-causing mutations in the ETF:QO protein show highly correlated motions with the FAD-binding site.</p> <p>Conclusions</p> <p>Based on the present findings, we conclude that the changes made to the amino acids in ETF:QO are likely to influence the FAD-binding stability.</p

The Role of Age in Predicting the Outcome of Caustic Ingestion in Adults: A Retrospective Analysis

<p>Abstract</p> <p>Background</p> <p>Although the outcomes of caustic ingestion differ between children and adults, it is unclear whether such outcomes differ among adults as a function of their age. This retrospective study was performed to ascertain whether the clinical outcomes of caustic ingestion differ significantly between elderly and non-elderly adults.</p> <p>Methods</p> <p>Medical records of patients hospitalized for caustic ingestion between June 1999 and July 2009 were reviewed retrospectively. Three hundred eighty nine patients between the ages of 17 and 107 years were divided into two groups: non-elderly (< 65 years) and elderly (≥ 65 years). Mucosal damage was graded using esophagogastroduodenoscopy (EGD). Parameters examined in this study included gender, intent of ingestion, substance ingested, systemic and gastrointestinal complications, psychological and systemic comorbidities, severity of mucosal injury, and time to expiration.</p> <p>Results</p> <p>The incidence of psychological comorbidities was higher for the non-elderly group. By contrast, the incidence of systemic comorbidities, the grade of severity of mucosal damage, and the incidence of systemic complications were higher for the elderly group. The percentages of ICU admissions and deaths in the ICU were higher and the cumulative survival rate was lower for the elderly group. Elderly subjects, those with systemic complications had the greatest mortality risk due to caustic ingestion.</p> <p>Conclusions</p> <p>Caustic ingestion by subjects ≥65 years of age is associated with poorer clinical outcomes as compared to subjects < 65 years of age; elderly subjects with systemic complications have the poorest clinical outcomes. The severity of gastrointestinal tract injury appears to have no impact on the survival of elderly subjects.</p

LOW BIT-RATE COLOR VIDEO COMPRESS USING MULTIWAVELETS IN THREE DIMENSIONS

This dissertation was presented by Jong-Chih Chien It was defended o

Inspection and Classification of Semiconductor Wafer Surface Defects Using CNN Deep Learning Networks

Due to advances in semiconductor processing technologies, each slice of a semiconductor is becoming denser and more complex, which can increase the number of surface defects. These defects should be caught early and correctly classified in order help identify the causes of these defects in the process and eventually help to improve the yield. In today&rsquo;s semiconductor industry, visible surface defects are still being inspected manually, which may result in erroneous classification when the inspectors become tired or lose objectivity. This paper presents a vision-based machine-learning-based method to classify visible surface defects on semiconductor wafers. The proposed method uses deep learning convolutional neural networks to identify and classify four types of surface defects: center, local, random, and scrape. Experiments were performed to determine its accuracy. The experimental results showed that this method alone, without additional refinement, could reach a top accuracy in the range of 98% to 99%. Its performance in wafer-defect classification shows superior performance compared to other machine-learning methods investigated in the experiments

A Fuzzy Rules-Based Driver Assistance System

A vision-based driver assistance system using fuzzy rules to determine whether warnings are necessary is presented. This system is comprised of four cameras, one of which focuses on the driver for estimating the driver’s viewing angle, another focuses on the road ahead for the detection of road condition ahead, and the last two cameras are on both sides of the vehicle, facing backward, for the purpose of determining whether neighboring lanes are occupied by vehicles hidden in the blind-spots. The system uses fuzzy-rules for the analysis of interactions between the driver’s gaze, whether there are vehicles ahead, and in the neighboring lanes to determine whether the current driving condition should be of concern to the driver and issues one of three levels of warnings, from safe to dangerous

Characteristics and Diagnostic Yield of Pediatric Colonoscopy in Taiwan

BackgroundColonoscopy of the lower gastrointestinal tract has diagnostic and therapeutic value. This retrospective study aimed to investigate the indications, complications, and diagnostic yield of diagnostic colonoscopy among Taiwanese children.MethodsThe application of colonoscopy performed on children aged < 18 years between 1998 and 2010 in a referral tertiary center in Southern Taiwan was reviewed. Data on age, gender, indications, complications, and colonoscopic and final diagnoses were collected and analyzed.ResultsOne hundred and ninety-two children with 201 colonoscopies and 27 sigmoidoscopies were enrolled. The rate of successful ileocecal approach was 77.5%. The most common indication was lower gastrointestinal bleeding (LGIB; 53.5%), followed by chronic abdominal pain (20.6%), iron deficiency anemia (IDA; 11.8%), and chronic diarrhea (11.4%). There were 144 patients (75%) with a conclusive diagnosis in their first colonoscopy, including nonspecific colitis (23.4%), polyp (20.4%), and inflammatory bowel disease (8.3%). The diagnostic yields of colonoscopy according to the major indications were 77.3% in LGIB, 68.1% in chronic abdominal pain, 66.7% in IDA, and 79.2% in chronic diarrhea. Among the patients with LGIB, juvenile polyp (26.4%) was the most common etiology. There were no major procedure-related complications.ConclusionLGIB is the most common indication for pediatric colonoscopy. Pediatric colonoscopy is most effective in diagnosing pediatric LGIB and chronic diarrhea

Improving Night Time Driving Safety Using Vision-Based Classification Techniques

The risks involved in nighttime driving include drowsy drivers and dangerous vehicles. Prominent among the more dangerous vehicles around at night are the larger vehicles which are usually moving faster at night on a highway. In addition, the risk level of driving around larger vehicles rises significantly when the driver’s attention becomes distracted, even for a short period of time. For the purpose of alerting the driver and elevating his or her safety, in this paper we propose two components for any modern vision-based Advanced Drivers Assistance System (ADAS). These two components work separately for the single purpose of alerting the driver in dangerous situations. The purpose of the first component is to ascertain that the driver would be in a sufficiently wakeful state to receive and process warnings; this is the driver drowsiness detection component. The driver drowsiness detection component uses infrared images of the driver to analyze his eyes’ movements using a MSR plus a simple heuristic. This component issues alerts to the driver when the driver’s eyes show distraction and are closed for a longer than usual duration. Experimental results show that this component can detect closed eyes with an accuracy of 94.26% on average, which is comparable to previous results using more sophisticated methods. The purpose of the second component is to alert the driver when the driver’s vehicle is moving around larger vehicles at dusk or night time. The large vehicle detection component accepts images from a regular video driving recorder as input. A bi-level system of classifiers, which included a novel MSR-enhanced KAZE-base Bag-of-Features classifier, is proposed to avoid false negatives. In both components, we propose an improved version of the Multi-Scale Retinex (MSR) algorithm to augment the contrast of the input. Several experiments were performed to test the effects of the MSR and each classifier, and the results are presented in experimental results section of this paper