A Three-Point Directional Search Block Matching Algorithm

This paper proposes compact directional asymmetric search patterns, which we have named as three-point directional search (TDS). In most fast search motion estimation algorithms, a symmetric search pattern is usually set at the minimum block distortion point at each step of the search. The design of the symmetrical pattern in these algorithms relies primarily on the assumption that the direction of convergence is equally alike in each direction with respect to the search center. Therefore, the monotonic property of real-world video sequences is not properly used by these algorithms. The strategy of TDS is to keep searching for the minimum block distortion point in the most probable directions, unlike the previous fast search motion estimation algorithms where all the directions are checked. Therefore, the proposed method significantly reduces the number of search points for locating a motion vector. Compared to conventional fast algorithms, the proposed method has the fastest search speed and most satisfactory PSNR values for all test sequences

Fruit Ripeness Assertion Using Deep Learning

The agricultural industry is one of the most important sectors in any country because it contributes to so many different areas. In comparison to other emerging countries, however, farmers and agriculture fields in some countries have limited technology and reach. Agricultural and allied sector operations employ 54.6 percent of the total workforce and contribute for 17.1 percent of the country's Gross Value Added (GVA) in 2017-18, according to India Census 2011. However, Agriculture’s contribution to GVA continues decline.[7] This agricultural field is obviously a challenging field to the digital technology and this “smart fruit ripening assertion” model considerably gives the high-quality and accurate results by utilizing the deep learning techniques such as YoloV3 which is a deep Convolutional Neural Network (CNN). This model's main focus is on the design and implementation of practical tasks, such as predicting the ripening stages of various types of fruits based on form, colour, and texture by combining and comparing various ML methods, OpenCV, and Internet of Things (IoT), thereby providing accurate prediction of ripening stages of fruits with the aid of a computer application which results introduction of large-scale manpower and saves time

Efficient Variable Length Block Switching Mechanism

Most popular and widely used packet switch architecture is the crossbar. Its attractive characteristics are simplicity, non-blocking and support for simultaneous multiple packet transmission across the switch. The special version of crossbar switch is Combined Input Crossbar Queue (CICQ) switch. It overcomes the limitations of un-buffered crossbar by employing buffers at each crosspoint in addition to buffering at each input port. Adoption of Crosspoint Buffer (CB) simplifies the scheduling complexity and adapts the distributed nature of scheduling. As a result, matching operation is not needed. Moreover, it supports variable length packets transmission without segmentation. Native switching of variable length packet transmission results in unfairness. To overcome this unfairness, Fixed Length Block Transfer mechanism has been proposed. It has the following drawbacks: (a) Fragmented packets are reassembled at the Crosspoint Buffer (CB). Hence, minimum buffer requirement at each crosspoint is twice the maximum size of the block. When number of ports are more, existence of such a switch is infeasible, due to the restricted memory available in switch core. (b) Reassembly circuit at each crosspoint adds the cost of the switch. (c) Packet is eligible to transfer from CB to output only when the entire packet arrives at the CB, which increases the latency of the fragmented packet in the switch. To overcome these drawbacks, this paper presents Variable Length Block Transfer mechanism. It does not require internal speedup, segmentation and reassembly circuits. Using simulation it is shown that proposed mechanism is superior to Fixed Length Block Transfer mechanism in terms of delay and throughput

Demonstrating the Feasibility of Line Intensity Mapping Using Mock Data of Galaxy Clustering from Simulations

Visbal & Loeb (2010) have shown that it is possible to measure the clustering of galaxies by cross correlating the cumulative emission from two different spectral lines which originate at the same redshift. Through this cross correlation, one can study galaxies which are too faint to be individually resolved. This technique, known as intensity mapping, is a promising probe of the global properties of high redshift galaxies. Here, we test the feasibility of such measurements with synthetic data generated from cosmological dark matter simulations. We use a simple prescription for associating galaxies with dark matter halos and create a realization of emitted radiation as a function of angular position and wavelength over a patch of the sky. This is then used to create synthetic data for two different hypothetical instruments, one aboard the Space Infrared Telescope for Cosmology and Astrophysics (SPICA) and another consisting of a pair of ground based radio telescopes designed to measure the CO(1-0) and CO(2-1) emission lines. We find that the line cross power spectrum can be measured accurately from the synthetic data with errors consistent with the analytical prediction of Visbal & Loeb (2010). Removal of astronomical backgrounds and masking bright line emission from foreground contaminating galaxies do not prevent accurate cross power spectrum measurements.Comment: 12 pages, 6 figures, Submitted to JCA

Photocatalytic, antibacterial and electrochemical properties of novel rare earth metal oxides-based nanohybrids

Mixed metal oxide nanocomposites (rare earth-based) have become irreplaceable and tend to display great functioning in all kinds of arenas like as photocatalytic, electrochemical, and biological. NiO-CGSO [NiO-Ce0.8Gd0.2O2-??Ce0.8Sm0.2O2-?] nanomaterial was produced by the wet-chemical route for numerous purposes. The development of (FCC) face-centered cubic structure confirmed and there was no derivative phase was observed by XRD. Metal-Oxygen bond was revealed by FTIR analysis. The morphology and elemental composition of the sample were carried out using SEM with EDAX. The optical bandgap of prepared nanocomposite was studied using UV?Vis spectroscopy. Electrochemical behaviour was observed at conditions, voltage (1.3 V), and the frequency (42 Hz?5 kHz). Photocatalytic and antibacterial behavior of prepared NiO-CGSO nanocomposites also investigated. It was found that this novel composite catalyst decomposed 92% of toxic pollutants from wastewater. Further, NiO-CGSO composites showed superior antibacterial performance against aeromonas hydrophila, E. coli, and S. epidermis bacterial pathogens.Scopu

CSH 22SS – an improved sweet sorghum hybrid

Parentage: ICSA 38 x SSV 84 Medium duration hybrid: 120 days;Days to 50% fl owering: 80 to 88 days;Plant height: 280–350 cm;High stalk yield (44–52 t ha-1): 29% higher than SSV 84 and CSV 19SS. ; High ethanol yield (1250–1320 L ha-1):43% higher than SSV 84 and 34% 8% higher than CSV 19SS. High CCS (3.2–4.0 t ha-1): 33% higher than SSV 84

A critical review on modelling formalisms and simulation tools in computational biosystems

Integration of different kinds of biological processes is an ultimate goal for whole-cell modelling. We briefly review modelling formalisms that have been used in Systems Biology and identify the criteria that must be addressed by an integrating framework capable of modelling, analysing and simulating different biological networks. Aware that no formalism can fit all purposes we realize Petri nets as a suitable model for Metabolic Engineering and take a deeper perspective on the role of this formalism as an integrating framework for regulatory and metabolic networks.Research supported by PhD grant SFRH/BD/35215/2007 from the Fundacao para a Ciencia e a Tecnologia (FCT) and the MIT-Portugal program

Socio-Demographic Patterning of Physical Activity across Migrant Groups in India: Results from the Indian Migration Study

OBJECTIVE: To investigate the relationship between rural to urban migration and physical activity (PA) in India. METHODS: 6,447 (42% women) participants comprising 2077 rural, 2,094 migrants and 2,276 urban were recruited. Total activity (MET hr/day), activity intensity (min/day), PA Level (PAL) television viewing and sleeping (min/day) were estimated and associations with migrant status examined, adjusting for the sib-pair design, age, site, occupation, education, and socio-economic position (SEP). RESULTS: Total activity was highest in rural men whereas migrant and urban men had broadly similar activity levels (p<0.001). Women showed similar patterns, but slightly lower levels of total activity. Sedentary behaviour and television viewing were lower in rural residents and similar in migrant and urban groups. Sleep duration was highest in the rural group and lowest in urban non-migrants. Migrant men had considerably lower odds of being in the highest quartile of total activity than rural men, a finding that persisted after adjustment for age, SEP and education (OR 0.53, 95% CI 0.37, 0.74). For women, odds ratios attenuated and associations were removed after adjusting for age, SEP and education. CONCLUSION: Our findings suggest that migrants have already acquired PA levels that closely resemble long-term urban residents. Effective public health interventions to increase PA are needed