Target differentiation with simple infrared sensors using statistical pattern recognition techniques

This study compares the performances of various statistical pattern recognition techniques for the differentiation of commonly encountered features in indoor environments, possibly with different surface properties, using simple infrared (IR) sensors. The intensity measurements obtained from such sensors are highly dependent on the location, geometry, and surface properties of the reflecting feature in a way that cannot be represented by a simple analytical relationship, therefore complicating the differentiation process. We construct feature vectors based on the parameters of angular IR intensity scans from different targets to determine their geometry and/or surface type. Mixture of normals classifier with three components correctly differentiates three types of geometries with different surface properties, resulting in the best performance (100%) in geometry differentiation. Parametric differentiation correctly identifies six different surface types of the same planar geometry, resulting in the best surface differentiation rate (100%). However, this rate is not maintained with the inclusion of more surfaces. The results indicate that the geometrical properties of the targets are more distinctive than their surface properties, and surface recognition is the limiting factor in differentiation. The results demonstrate that simple IR sensors, when coupled with appropriate processing and recognition techniques, can be used to extract substantially more information than such devices are commonly employed for.     

Comparative analysis of different approaches to target differentiation and localization with sonar

This study compares the performances of different methods for the differentiation and localization of commonly encountered features in indoor environments. Differentiation of such features is of interest for intelligent systems in a variety of applications such as system control based on acoustic signal detection and identification, map building, navigation, obstacle avoidance, and target tracking. Different representations of amplitude and time-of-flight measurement patterns experimentally acquired from a real sonar system are processed. The approaches compared in this study include the target differentiation algorithm, Dempster-Shafer evidential reasoning, different kinds of voting schemes, statistical pattern recognition techniques (k-nearest neighbor classifier, kernel estimator, parameterized density estimator, linear discriminant analysis, and fuzzy c-means clustering algorithm), and artificial neural networks. The neural networks are trained with different input signal representations obtained using pre-processing techniques such as discrete ordinary and fractional Fourier, Hartley and wavelet transforms, and Kohonen's self-organizing feature map. The use of neural networks trained with the back-propagation algorithm, usually with fractional Fourier transform or wavelet pre-processing results in near perfect differentiation, around 85% correct range estimation and around 95% correct azimuth estimation, which would be satisfactory in a wide range of applications.     

Metal hydride materials for solid hydrogen storage: A review

Hydrogen is an ideal energy carrier which is considered for future transport, such as automotive applications. In this context storage of hydrogen is one of the key challenges in developing hydrogen economy. The relatively advanced storage methods such as high-pressure gas or liquid cannot fulfill future storage goals. Chemical or physically combined storage of hydrogen in other materials has potential advantages over other storage methods. Intensive research has been done on metal hydrides recently for improvement of hydrogenation properties. The present review reports recent developments of metal hydrides on properties including hydrogen-storage capacity, kinetics, cyclic behavior, toxicity, pressure and thermal response. A group of Mg-based hydrides stand as promising candidate for competitive hydrogen storage with reversible hydrogen capacity up to 7.6 wt% for on-board applications. Efforts have been devoted to these materials to decrease their desorption temperature, enhance the kinetics and cycle life. The kinetics has been improved by adding an appropriate catalyst into the system and as well as by ball-milling that introduces defects with improved surface properties. The studies reported promising results, such as improved kinetics and lower decomposition temperatures, however, the state-of-the-art materials are still far from meeting the aimed target for their transport applications. Therefore, further research work is needed to achieve the goal by improving development on hydrogenation, thermal and cyclic behavior of metal hydrides.     

Designing carbon-supported Fe2O3 anodes for lithium ion batteries

Journal of Applied Electrochemistry - In this study, within the defined orthogonal array of Taguchi design, the hydrothermal process parameters have been optimized for fabricating the smallest...     

Transient protein-protein interactions

Transient complexes are crucial for diverse biological processes such as biochemical pathways and signaling cascades in the cell. Here, we give an overview of the transient interactions; the importance of transient interactions as drug targets; and the structural characterization of transient protein-protein complexes based on the geometrical and physicochemical features of the transient complexes' interfaces. To better understand and eventually design transient protein-protein interactions (TPPIs), a molecular perspective of the protein-protein interfaces is necessary. Obtaining high-quality structures of protein-protein interactions could be one way of achieving this goal. After introducing the association kinetics of TPPIs, we elaborate on the experimental techniques detecting TPPIs in combination with the computational methods which classify transient and/or non-obligate complexes. In this review, currently available databases and servers that can be used to identify and predict TPPIs are also compiled.     

Hydrolysis of freshly prepared wheat starch fractions and commercial wheat starch using α-amylase

The enzymic hydrolysis of commercial wheat starch and freshly prepared wheat starch fractions was studied in batch and flow systems. Fresh starch was prepared by wet separation of wheat flour into starch milk and gluten, followed by processing the starch milk using a serially connected hydrocyclone system to produce underflow and overflow streams. The underflow stream consisted mainly of the larger (> 30 w m) granules, while the overflow stream contained only the smaller (< 10 w m) granules. In batch system, the hydrolysis behavior of wheat starch fractions was investigated under the action of Sigma f -amylase ( Bacillus licheniformis ), either as soon as they were prepared or after spray drying. The two fractions of fresh wheat starch showed different hydrolysis behavior, the difference getting larger as the separation improves. Underflow streams were found to be much more susceptible to hydrolysis than overflow streams, regardless of whether the hydrolysis was carried out right away or on dried samples, and also regardless of whether rinsing was applied. In flow system, dried underflow stream and commercialwheat starch were hydrolyzed using Orbamil-T ( Bacillus licheniformis ), Orbamil-BHT ( Bacillus stearothermophilus ), and Sigma f -amylase ( Bacillus licheniformis ). Hydrolysis of fresh starch was found to be significantly faster than commercial wheat starch. Commercial f -amylase Orbamil-T was found to be almost as effective as the purified Sigma f -amylase.     

Automated evaluation of physical therapy exercises using multi-template dynamic time warping on wearable sensor signals

We develop an autonomous system to detect and evaluate physical therapy exercises using wearable motion sensors. We propose the multi-template multi-match dynamic time warping (MTMM-DTW) algorithm as a natural extension of DTW to detect multiple occurrences of more than one exercise type in the recording of a physical therapy session. While allowing some distortion (warping) in time, the algorithm provides a quantitative measure of similarity between an exercise execution and previously recorded templates, based on DTW distance. It can detect and classify the exercise types, and count and evaluate the exercises as correctly/incorrectly performed, identifying the error type, if any. To evaluate the algorithm's performance, we record a data set consisting of one reference template and 10 test executions of three execution types of eight exercises performed by five subjects. We thus record a total of 120 and 1200 exercise executions in the reference and test sets, respectively. The test sequences also contain idle time intervals. The accuracy of the proposed algorithm is 93.46% for exercise classification only and 88.65% for simultaneous exercise and execution type classification. The algorithm misses 8.58% of the exercise executions and demonstrates a false alarm rate of 4.91%, caused by some idle time intervals being incorrectly recognized as exercise executions. To test the robustness of the system to unknown exercises, we employ leave-one-exercise-out cross validation. This results in a false alarm rate lower than 1%, demonstrating the robustness of the system to unknown movements. The proposed system can be used for assessing the effectiveness of a physical therapy session and for providing feedback to the patient.     

Representing and evaluating ultrasonic maps using active snake contours and Kohonen’s self-organizing feature maps

Active snake contours and Kohonen’s self-organizing feature maps (SOMs) are employed for representing and evaluating discrete point maps of indoor environments efficiently and compactly. A generic error criterion is developed for comparing two different sets of points based on the Euclidean distance measure. The point sets can be chosen as (i) two different sets of map points acquired with different mapping techniques or different sensing modalities, (ii) two sets of fitted curve points to maps extracted by different mapping techniques or sensing modalities, or (iii) a set of extracted map points and a set of fitted curve points. The error criterion makes it possible to compare the accuracy of maps obtained with different techniques among themselves, as well as with an absolute reference. Guidelines for selecting and optimizing the parameters of active snake contours and SOMs are provided using uniform sampling of the parameter space and particle swarm optimization (PSO). A demonstrative example from ultrasonic mapping is given based on experimental data and compared with a very accurate laser map, considered an absolute reference. Both techniques can fill the erroneous gaps in discrete point maps. Snake curve fitting results in more accurate maps than SOMs because it is more robust to outliers. The two methods and the error criterion are sufficiently general that they can also be applied to discrete point maps acquired with other mapping techniques and other sensing modalities.     

Copolymers possessing dithienothiophene and boron for optoelectronic applications

In this work, copolymers of dithienothiophenes (DTT) and DTT‐4,4‐dioxide (DTT‐S,S‐O₂) with mesitylboron were prepared for optoelectronic applications. Optical and electrochemical investigations were performed giving rise to the band gaps of 2.46–3.21 and 2.18–2.88 eV, respectively. Copolymers possessing DTT‐S,S‐O₂ units demonstrated the lower band gaps. Density functional theory investigations of the model compounds revealed the presence of an intramolecular charge transfer transition between the donor DTT units and the boron acceptor atoms. POLYM. ENG. SCI., 56:1390–1398, 2016. © 2016 Society of Plastics Engineers     

The dependence of tool overhang on surface quality and tool wear in the turning process

In the turning process, the importance of machining parameter choice is increased, as it controls the surface quality required. Tool overhang is a cutting tool parameter that has not been investigated in as much detail as some of the better known ones. It is appropriate to keep the tool overhang as short as possible; however, a longer tool overhang may be required depending on the geometry of the workpiece and when using the hole-turning process in particular. In this study, we investigate the effects of changes in the tool overhang in the external turning process on both the surface quality of the workpiece and tool wear. For this purpose, we used workpieces of AISI 1050 material with diameters of 20, 30, and 40 mm; and the surface roughness of the workpiece and tool wear were determined through experiments using constant cutting speed and feed rates with different depth of cuts (DOCs) and tool overhangs. We observed that the effect of the DOC on the surface roughness is negligible, but tool overhang is more important. The deflection of the cutting tool increases with tool overhang. Two different analytical methods were compared to determine the dependence of tool deflection on the tool overhang. Also, the real tool deflection values were determined using a comparator. We observed that the tool deflection values were quite compatible with the tool deflection results obtained using the second analytical method.