On the analysis of induction motor with square wave currents in the rotor via state transition signal flow graph technique

The performance equations of an induction motor are given in the rotor reference frame of two of the three phases. These equations are used to analyse the steady state performance of an induction motor with square wave currents in the rotor and sinusoidal voltages on the stator. A closed form solution for stator flux linkages in the time domain is obtained using state transition signal flow graph technique. It is found that the stator current is essentially sinusoidal superimposed by slip dependent harmonics. The torque developed by the motor has pulsations both at six times and twelve times slip frequency.

---

Stationäres Verhalten eines Asynchronmotors bei rechteckförmigen Läuferströmen auf Signalflußdiagrammbasis

Übersicht Für einen Asynchronmotor werden die Spannungsgleichungen in einem auf zwei Strangachsen bezogenen läuferfesten Koordinatensystem aufgestellt. Diese Gleichungen werden zur Analyse des stationären Verhaltens bei rechteckförmigen Strömen im Läufer und sinusförmigen Spannungen am Ständer angewendet, und führen über Signalflußdiagrammdarstellung zu einer geschlossenen Lösung. Der Ständerstrom hat schlupfabhängigen Schwingungen. Das Drehmoment enthält Schwankungen, die Komponente sechster und zwölfter harmonischen Ordnung des Schlupfes entsprechen.

---

List of symbols i _a,i _b,i _c stator phase currents - i _A,i _B,i _C rotor phase currents - L _m mutual inductance between stator and rotor - L _s self inductance of stator - L _r self inductance of rotor - P pairs of poles - R _s resistance per phase of stator - R _r resistance per phase of rotor - s Laplace operator - T torque developed - _a , _b , _c stator phase flux linkages - _A , _B , _C rotor flux linkages - _a (0), _b(0) stator flux linkages at the beginning of 1/6th cycle - _s , _r synchronous and rotor angular frequencies - Phase difference between stator and rotor phases     

Boolean Operations on n-Dimensional Objects

Computation of the union, intersection, and difference of n-dimensional objects plays a central role in several computer-aided geometric design problems. An algorithm for computing these operations that uses a boundary classification technique is presented here. The algorithm is recursive in structure, with the recursion being on the dimensions of objects dealt with at each stage. The representation treats all entities as objects, making no distinction between faces, edges, or vertices. The objects produced are "regularized"; that is, there are no degenerate boundaries such as dangling edges. The sample application given involves hidden-surface removal.     

Effect of foliar diseases control by chlorothalonil on pod yield and quality characteristics of confectionery groundnuts (Arachis hypogaea L)

Effects of foliar diseases control by chlorothalonil fungicide on pod yield and quality characteristics were studied in 10 confectionery groundnut genotypes at ICRISAT Centre, India, during two rainy seasons. Significant treatment (disease control versus no control), and genotypic effects were observed for pod yield, total biomass, remaining green leaf area, retained leaf area damaged by rust, shelling percentage, 100-seed mass, oil content, fatty acids, and oleic (O)/linoleic (L) acid, and polyunsaturated (P)/saturated (S) fatty acid ratios. A significant increase in pod yield and total oil content was observed due to the control of foliar diseases by chlorothalonil; whereas the protein content remained unaffected by it. The foliar diseases control by chlorothalonil affected four fatty acids; linoleic acid content increased whereas stearic, oleic, and behenic acid contents decreased. Of the seed quality characteristics, a significant decrease in O/L ratio, and a significant increase in P/S ratio were observed under the disease control treatment. Response to disease control for pod yield and quality characteristics was influenced by genotypes and years. Correlations among fatty acid contents, in general, remained unaffected by control of foliar diseases with chlorothalonil whereas those of fatty acid contents with pod yield, seed mass, oil and protein contents changed in their significance and magnitude.     

Local tetra patterns: a new feature descriptor for content-based image retrieval

In this paper, we propose a novel image indexing and retrieval algorithm using local tetra patterns (LTrPs) for content-based image retrieval (CBIR). The standard local binary pattern (LBP) and local ternary pattern (LTP) encode the relationship between the referenced pixel and its surrounding neighbors by computing gray-level difference. The proposed method encodes the relationship between the referenced pixel and its neighbors, based on the directions that are calculated using the first-order derivatives in vertical and horizontal directions. In addition, we propose a generic strategy to compute nth-order LTrP using (n - 1)th-order horizontal and vertical derivatives for efficient CBIR and analyze the effectiveness of our proposed algorithm by combining it with the Gabor transform. The performance of the proposed method is compared with the LBP, the local derivative patterns, and the LTP based on the results obtained using benchmark image databases viz., Corel 1000 database (DB1), Brodatz texture database (DB2), and MIT VisTex database (DB3). Performance analysis shows that the proposed method improves the retrieval result from 70.34%/44.9% to 75.9%/48.7% in terms of average precision/average recall on database DB1, and from 79.97% to 85.30% and 82.23% to 90.02% in terms of average retrieval rate on databases DB2 and DB3, respectively, as compared with the standard LBP.     

Local maximum edge binary patterns: A new descriptor for image retrieval and object tracking

A new algorithm meant for content based image retrieval (CBIR) and object tracking applications is presented in this paper. The local region of image is represented by local maximum edge binary patterns (LMEBP), which are evaluated by taking into consideration the magnitude of local difference between the center pixel and its neighbors. This LMEBP differs from the existing LBP in a manner that it extracts the information based on distribution of edges in an image. Further, the effectiveness of our algorithm is confirmed by combining it with Gabor transform. Four experiments have been carried out for proving the worth of our algorithm. Out of which three are meant for CBIR and one for object tracking. It is further mentioned that the database considered for first three experiments are Brodatz texture database (DB1), MIT VisTex database (DB2), rotated Brodatz database (DB3) and the fourth contains three observations. The results after being investigated show a significant improvement in terms of their evaluation measures as compared to LBP and other existing transform domain techniques.     

Hydroxyapatite-supported Ag-TiO2 as Escherichia coli disinfection photocatalyst

A series of hydroxyapatite (HAP), 1wt% Ag-TiO(2) (AT1), 1wt% Ag-HAP and 5wt% AT1/HAP composite catalysts were prepared by incipient wetness and mechanical mixing methods. They were characterized by X-ray diffraction (XRD), FT-IR, SEM and ESCA analyses and their photocatalytic bactericidal activities were measured in suspension using Escherichia coli (E. coli), a water pollutant indicator. The surface analysis revealed that the Ag/Ti ratio is found to be ca. 0.0273 and also it indicated that the titania is present in the form of Ti(4+) and Ag is present as metallic silver. Both the XRD and ESCA analyses confirmed the phase of metallic Ag particles, which played a significant role on the bactericidal activity of the Ag doped TiO(2) catalysts. The FT-IR analysis of HAP revealed that the peak intensity is due to the absorbance of surface PO(4)(3-) group centered at wave number 1030cm(-1) and is drastically decreased upon exposure to UV for 1h. The HAP displayed high amount of bacteria adsorption, ca. 80% during the dark experiments compared to other catalytic systems tested. The cumulative photocatalytic properties of AT1/HAP catalytic system resulted in 100% E. coli bacteria reduction within 2min.     

Cautious optimism for the future [codesign research]

The expectations, experimental results, and open issues relating to codesign research are discussed. Codesign refers to the integrated design of systems implemented using both hardware and software components. It is argued that the renewed interest in codesign is largely explained by the increasing diversity and complexity of applications employing embedded systems; the need to decrease the cost of designing and testing such systems; and advances in some key enabling technologies     

Degradation-resistant TiO2@Sn anodes for high-capacity lithium-ion batteries

Journal of Materials Science - As the demand for higher-performance batteries has increased, so has the body of research on theoretical high-capacity anode materials. However, the research has been...     

SABOS-Net: Self-supervised attention based network for automatic organ segmentation of head and neck CT images

The segmentation of Organs At Risk (OAR) in Computed Tomography (CT) images is an essential part of the planning phase of radiation treatment to avoid the adverse effects of cancer radiotherapy treatment. Accurate segmentation is a tedious task in the head and neck region due to a large number of small and sensitive organs and the low contrast of CT images. Deep learning-based automatic contouring algorithms can ease this task even when the organs have irregular shapes and size variations. This paper proposes a fully automatic deep learning-based self-supervised 3D Residual UNet architecture with CBAM(Convolution Block Attention Mechanism) for the organ segmentation in head and neck CT images. The Model Genesis structure and image context restoration techniques are used for self-supervision, which can help the network learn image features from unlabeled data, hence solving the annotated medical data scarcity problem in deep networks. A new loss function is applied for training by integrating Focal loss, Tversky loss, and Cross-entropy loss. The proposed model outperforms the state-of-the-art methods in terms of dice similarity coefficient in segmenting the organs. Our self-supervised model could achieve a 4% increase in the dice score of Chiasm, which is a small organ that is present only in a very few CT slices. The proposed model exhibited better accuracy for 5 out of 7 OARs than the recent state-of-the-art models. The proposed model could simultaneously segment all seven organs in an average time of 0.02 s. The source code of this work is made available at https://github.com/seeniafrancis/SABOSNet .