Research of dynamic processes at cutting forest materials on horizontal band saw equipment

For processing small-scale wood, as well as wood from logging and sanitary logging, small enterprises are created that use fairly large and expensive band saws of various foreign firms and domestic production, which have a high energy intensity of the technological process. In this regard, the development of a resource-saving band saw machine that improves the quality of saw products and reduces the energy intensity of the technological process is an urgent task for the timber processing industry. To study the dynamics of the process of sawing wood on a horizontal band saw, it is necessary to create its dynamic model, which is a mathematical description of the interaction of the cutting process and the equivalent elastic system of the machine. The problem of the quality of wood sawing is both the accuracy of processing and the roughness of the surface to be processed. To assess the accuracy of wood sawing, two indicators were used: average and maximum undulation. As a result of the research, a new design of the band saw was developed using a dynamic model, which ensures resource saving, reducing the energy intensity of the technological process and improving the quality of the resulting saw products.

A Residual Analysis for the Removal of Biological Oxygen Demand through Rotating Biological Contactor

Regression is a statistical method that is generally used for forecasting and prediction. It helps us to estimate the relationship between a dependent variable and one or more independent variables. This is the most widely used technique that best approximates the individual data points. It has found numerous successful applications in Engineering, Science, business and other fields. Getting average removal % of Biological Oxygen Demand (BOD5) from greywater through Rotating Biological Contactor (RBC), following experiment was conducted in Sindh University hostels using different parameters such as Hydraulic Retention Time (HRT) i.e. 2 hours (0.42 liter per min), 2.5 hours (0.33 l/min) and 3 hours (0.28 l/min) and multiple number of discs i.e. 40, 42, 44, 46, 48, 50 and 52. Consequences reveal that linear estimate of HRTs and numbers of disc are considerable whereas linear and quadratic estimates of number of discs are highly significant, which evidence the significance of time and discs. However, as p-value is greater than 0.05, hence quadratic estimate of HRT is not significant. By using coefficients of the table the regression equation is Removal = - 79.995 + 6.88 time + 2.90 disc, where the sample standard deviation is 7.151, coefficient of correlation is 0.86 and coefficient of determination is 0.742. Distributions of errors are approximately normal as probability plot of the residuals is approximately linear. Residual analysis shows that against each predicted variable, residuals plot falls approximately in a horizontal band symmetric and centered about the horizontal axis and against predicted y-values. Moreover, Residual plot shows the constant standard deviations and linearity assumptions appear to be met.

A Critical Reanalysis of Uncontrollable Washboarding Phenomenon in Metal Band Sawing

The article analyzes the cutting process of hard bars. Investigations conducted in industrial conditions demonstrated the presence of surface errors in the machined workpieces in the form of washboard patterns. The purpose of this study was to analyze the results of cutting on band sawing machines with different band saw blades. The cutting processes were conducted on three different horizontal band sawing machine types. Analyzed material was an alloy steel Ø40 mm rod with a hardened surface covered with a thin layer of chromium. The hardness of the outer layer was 547 HV with a core hardness of 180 HV. The surface topography measurements of the processed workpieces were carried out with the 3D Optical Profiler, which supplied information on the irregularities of the processed material texture. In each of the analyzed cases, a corrugated surface was obtained after sawing, which is the effect of the occurrence of the washboarding phenomenon, despite the fact that the teeth of each band saw had variable pitches. The washboarding phenomenon when cutting rods with hard surfaces is caused by the phenomenon of wave regeneration. Despite the use of variable pitch saw blades, the cutting process results in rippling of the sawn surface, which is caused by the high hardness of the outer layer of the workpiece, as well as by the type of tool with spring setting of teeth.

CIS Band Noise Prediction Methodology Using Co-Simulation of Camera Module

This paper describes a CMOS image sensor (CIS) horizontal band noise reduction methodology considering on-chip and offchip camera module PCB design parameters. The horizontal band noise is a crucial issue for high quality camera of modern smartphone applications. This paper discusses CIS horizontal band noise mechanism and proposes the solution by optimization of design factors in CIS and camera module. Analog ground impedance value and bias voltage condition of pixel array transfer gate have been found to be effective optimization parameters. Through the real experimental data, we proved that proposed solution is instrumental in reducing the horizontal band noise.

Location of Eyes in Images of Human Faces through Analysis Variance Shine Intensity

Extraction of facial features is an important step in automatic visual interpretation and recognition of human faces. Among the facial features, the eyes play a major role in the recognition process. In this article, we present an approach to detect and locate the eyes in frontal face images. Eye regions are identified using the technique of voucher detection based on mathematical morphology. After this identification is made a comparison between the variances of three different portions of each candidate region to eye (set of pixels belonging to the candidate region as a whole, set of pixels contained in a minimum rectangle circumscribed to the candidate region and set of pixels of the candidate region belonging to a horizontal band that crosses the center of mass of this region). The calculation of these variances also considers the R, G, and B channels, as well as the gray version of the input image.

Design and Development of a Guide Bracket for Horizontal band Sawing Machine by Geometrical Optimization

All modern manufacturing units are striving to develop a cost effective product with optimized reduced weight by using CAE driven design process. In this scenario the product design is stimulated by structural optimization tools like geometrical (topology) optimization, shape optimization or size optimization. For conservation of natural resources and optimum energy utilization, weight reduction has been the main focus of machine tool manufacturers in the present scenario. Weight reduction can be achieved by the introduction of better material, better manufacturing processes and design optimization. In automobile and aircraft sector, geometrical optimization has become an integral tool of product design and development. Geometry (topology) assisted design model gives optimized results which are better and innovative in terms of product design with enhanced structural performance and stability. In other words, simulation saves time, reduces costs, and strengthens the competitiveness of companies, thus strengthened market position.

A Wavelet-Domain Local Dominant Feature Selection Scheme for Face Recognition

A multiresolution feature extraction algorithm for face recognition is proposed based on two-dimensional discrete wavelet transform (2D-DWT), which efficiently exploits the local spatial variations in a face image. For feature extraction, instead of considering the entire face image, an entropy-based local band selection criterion is developed, which selects high-informative horizontal segments from the face image. In order to capture the local spatial variations within these bands precisely, the horizontal band is segmented into several small spatial modules. The effect of modularization in terms of the entropy content of the face images has been investigated. Dominant wavelet coefficients corresponding to each module residing inside those bands are selected as features. A histogram-based threshold criterion is proposed to select dominant coefficients, which drastically reduces the feature dimension and provides high within-class compactness and high between-class separability. The effect of using different mother wavelets for the purpose of feature extraction has been also investigated. PCA is performed to further reduce the dimensionality of the feature space. Extensive experimentation is carried out upon standard face databases, and a very high degree of recognition accuracy is achieved by the proposed method in comparison to those obtained by some of the existing methods.

Devario xyrops, a new species of danionine fish from south-western Myanmar (Teleostei: Cyprinidae)

Devario xyrops is described from small rivers on the western slope of the Rakhine Yoma in south-western Myanmar. It is distinguished from all other species in the genus except D. anomalus by its colour pattern including a dark blotch or condensed series of vertical bars anteriorly on the side, separate from a posterior dark horizontal band; and distinguished from D. anomalus in particular by deeper body (29.9–35.8% SL, vs. 25.0–26.8 % SL) and fewer lateral line scales (31–33, modally 32 vs. 33–35, modally 34).