Organizational maintenance manual including repair parts and special tools lists : mounting kit, chemical agent automatic alarm, low profile, M182 (FSN 6665-110-9492) and mounting kit, chemical agent automatic alarm, high profile, M228 (FSN 6665-859-2212) for alarm, chemical agent, automatic, portable, for truck, 2-1/2 ton, M13 ...

"October 1973."

Organizational maintenance manual including repair parts and special tools lists : installation kits for alarm, chemical agent, automatic, portable, for truck, 2-1/2 ton, M13 (FSN 6665-479-2718) ... w/power supply for truck, utility, 1/4 ton, M16 (FSN 6665-479-2716).

Includes index.

Direct support and general support maintenance repair parts and special tools lists (including depot maintenance repair parts and special tools) : detector unit, chemical agent automatic alarm, M43 (FSN 6665-859-2201), alarm unit, chemical agent automatic alarm, M42 (FSN 6665-859-2215).

Includes index.

Organizational, direct and general support, and depot maintenance repair parts and special tools lists : heater, duct type, portable gasoline, 400,000 BTU/hr, gasoline engine and electric motor driven blowers, w/6 and 12 inch diameter ducts, automatic temperature control, trailer mounted (American Air Filter Co. Inc model BT400-40) FSN 4520-792-8257 (American Air Filter Co, Inc model BT400-40-1) FSN 4520-930-9474.

Includes index.

DS, GS, and depot maintenance manual including repair parts and special tools lists : rifle caliber .30, automatic, Browning, M1918A2, W/E (1005-674-1309).

Includes index.

Organizational maintenance repair parts and special tools list for azimuth laying set, guided missile AN/TSQ-110(XO-1), 1430-00-399-5318, optical link, automatic (in container), 1430-01-035-0831, weather shield assembly, missile window, 1430-01-011-0819, diagnostic prism set, 4935-01-010-6017, (Pershing 1A Field Artillery Missile System).

Includes index.

Direct support and general support maintenance repair parts and special tools list (including depot repair parts and special tools list) for automatic telephone central offices AN/TTC-38(V)1 (NSN 5805-00-186-0681) and AN/TTC-38(V)2 (NSN 5805-00-186-0640).

"17 September 1982"--[Vol.] 2.

Direct support and general support maintenance repair parts and special tools list (including depot maintenance repair parts and special tools) for central office, telephone, automatic, AN/TTC-41(V)1 (NSN 5805-01-028-8393), AN/TTC-41(V)2 (NSN 5805-01-028-8394), AN/TTC-41(V)3 (NSN 5805-01-028-8392), and AN/TTC-41(V)4 (NSN 5805-01-044-8869).

Includes index.

Direct support, general support, and depot maintenance repair parts and special tools list for transmission, automatic, with container, assembly model TX 200-2A ... transmission, automatic ... assembly model TX 200-2B ... transmission, automatic ... assembly model TX 200-6, Allison Division, GM 2520-133-9635.

Includes index.

Timed Probabilistic Automaton : a bridge between Raven and Song Scope for automatic species recognition

Raven and Song Scope are two automated sound anal-ysis tools based on machine learning technique for en-vironmental monitoring. Many research works have been conducted upon them, however, no or rare explo-ration mentions about the performance and comparison between them. This paper investigates the comparisons from six aspects: theory, software interface, ease of use, detection targets, detection accuracy, and potential application. Through deep exploration one critical gap is identified that there is a lack of approach to detect both syllables and call structures, since Raven only aims to detect syllables while Song Scope targets call structures. Therefore, a Timed Probabilistic Automata (TPA) system is proposed which separates syllables first and clusters them into complex structures after.

Towards robust automatic affective classification of images using facial expressions for practical applications

Affect is an important feature of multimedia content and conveys valuable information for multimedia indexing and retrieval. Most existing studies for affective content analysis are limited to low-level features or mid-level representations, and are generally criticized for their incapacity to address the gap between low-level features and high-level human affective perception. The facial expressions of subjects in images carry important semantic information that can substantially influence human affective perception, but have been seldom investigated for affective classification of facial images towards practical applications. This paper presents an automatic image emotion detector (IED) for affective classification of practical (or non-laboratory) data using facial expressions, where a lot of “real-world” challenges are present, including pose, illumination, and size variations etc. The proposed method is novel, with its framework designed specifically to overcome these challenges using multi-view versions of face and fiducial point detectors, and a combination of point-based texture and geometry. Performance comparisons of several key parameters of relevant algorithms are conducted to explore the optimum parameters for high accuracy and fast computation speed. A comprehensive set of experiments with existing and new datasets, shows that the method is effective despite pose variations, fast, and appropriate for large-scale data, and as accurate as the method with state-of-the-art performance on laboratory-based data. The proposed method was also applied to affective classification of images from the British Broadcast Corporation (BBC) in a task typical for a practical application providing some valuable insights.

Impact of automatic region-of-interest coding on perceived quality in mobile video

At present, the most reliable method to obtain end-user perceived quality is through subjective tests. In this paper, the impact of automatic region-of-interest (ROI) coding on perceived quality of mobile video is investigated. The evidence, which is based on perceptual comparison analysis, shows that the coding strategy improves perceptual quality. This is particularly true in low bit rate situations. The ROI detection method used in this paper is based on two approaches: - (1) automatic ROI by analyzing the visual contents automatically, and; - (2) eye-tracking based ROI by aggregating eye-tracking data across many users, used to both evaluate the accuracy of automatic ROI detection and the subjective quality of automatic ROI encoded video. The perceptual comparison analysis is based on subjective assessments with 54 participants, across different content types, screen resolutions, and target bit rates while comparing the two ROI detection methods. The results from the user study demonstrate that ROI-based video encoding has higher perceived quality compared to normal video encoded at a similar bit rate, particularly in the lower bit rate range.

Construction of a global map of human gene expression : the process, tools and analysis

This thesis studies human gene expression space using high throughput gene expression data from DNA microarrays. In molecular biology, high throughput techniques allow numerical measurements of expression of tens of thousands of genes simultaneously. In a single study, this data is traditionally obtained from a limited number of sample types with a small number of replicates. For organism-wide analysis, this data has been largely unavailable and the global structure of human transcriptome has remained unknown. This thesis introduces a human transcriptome map of different biological entities and analysis of its general structure. The map is constructed from gene expression data from the two largest public microarray data repositories, GEO and ArrayExpress. The creation of this map contributed to the development of ArrayExpress by identifying and retrofitting the previously unusable and missing data and by improving the access to its data. It also contributed to creation of several new tools for microarray data manipulation and establishment of data exchange between GEO and ArrayExpress. The data integration for the global map required creation of a new large ontology of human cell types, disease states, organism parts and cell lines. The ontology was used in a new text mining and decision tree based method for automatic conversion of human readable free text microarray data annotations into categorised format. The data comparability and minimisation of the systematic measurement errors that are characteristic to each lab- oratory in this large cross-laboratories integrated dataset, was ensured by computation of a range of microarray data quality metrics and exclusion of incomparable data. The structure of a global map of human gene expression was then explored by principal component analysis and hierarchical clustering using heuristics and help from another purpose built sample ontology. A preface and motivation to the construction and analysis of a global map of human gene expression is given by analysis of two microarray datasets of human malignant melanoma. The analysis of these sets incorporate indirect comparison of statistical methods for finding differentially expressed genes and point to the need to study gene expression on a global level.

Automatic Recognition of Facial Features and Landmarking of Digital Human Head

Ergonomic design of products demands accurate human dimensions-anthropometric data. Manual measurement over live subjects, has several limitations like long time, required presence of subjects for every new measurement, physical contact etc. Hence the data currently available is limited and anthropometric data related to facial features is difficult to obtain. In this paper, we discuss a methodology to automatically detect facial features and landmarks from scanned human head models. Segmentation of face into meaningful patches corresponding to facial features is achieved by Watershed algorithms and Mathematical Morphology tools. Many Important physiognomical landmarks are identified heuristically.

CLAP: A web-server for automatic classification of proteins with special reference to multi-domain proteins

Background: The function of a protein can be deciphered with higher accuracy from its structure than from its amino acid sequence. Due to the huge gap in the available protein sequence and structural space, tools that can generate functionally homogeneous clusters using only the sequence information, hold great importance. For this, traditional alignment-based tools work well in most cases and clustering is performed on the basis of sequence similarity. But, in the case of multi-domain proteins, the alignment quality might be poor due to varied lengths of the proteins, domain shuffling or circular permutations. Multi-domain proteins are ubiquitous in nature, hence alignment-free tools, which overcome the shortcomings of alignment-based protein comparison methods, are required. Further, existing tools classify proteins using only domain-level information and hence miss out on the information encoded in the tethered regions or accessory domains. Our method, on the other hand, takes into account the full-length sequence of a protein, consolidating the complete sequence information to understand a given protein better. Results: Our web-server, CLAP (Classification of Proteins), is one such alignment-free software for automatic classification of protein sequences. It utilizes a pattern-matching algorithm that assigns local matching scores (LMS) to residues that are a part of the matched patterns between two sequences being compared. CLAP works on full-length sequences and does not require prior domain definitions. Pilot studies undertaken previously on protein kinases and immunoglobulins have shown that CLAP yields clusters, which have high functional and domain architectural similarity. Moreover, parsing at a statistically determined cut-off resulted in clusters that corroborated with the sub-family level classification of that particular domain family. Conclusions: CLAP is a useful protein-clustering tool, independent of domain assignment, domain order, sequence length and domain diversity. Our method can be used for any set of protein sequences, yielding functionally relevant clusters with high domain architectural homogeneity. The CLAP web server is freely available for academic use at http://nslab.mbu.iisc.ernet.in/clap/.