Thinning-free Polygonal Approximation of Thick Digital Curves Using Cellular Envelope

Since the inception of successful rasterization of curves and objects in the digital space, several algorithms have been proposed for approximating a given digital curve. All these algorithms, however, resort to thinning as preprocessing before approximating a digital curve with changing thickness. Described in this paper is a novel thinning-free algorithm for polygonal approximation of an arbitrarily thick digital curve, using the concept of "cellular envelope", which is newly introduced in this paper. The cellular envelope, defined as the smallest set of cells containing the given curve, and hence bounded by two tightest (inner and outer) isothetic polygons, is constructed using a combinatorial technique. This envelope, in turn, is analyzed to determine a polygonal approximation of the curve as a sequence of cells using certain attributes of digital straightness. Since a real-world curve=curve-shaped object with varying thickness, unexpected disconnectedness, noisy information, etc., is unsuitable for the existing algorithms on polygonal approximation, the curve is encapsulated by the cellular envelope to enable the polygonal approximation. Owing to the implicit Euclidean-free metrics and combinatorial properties prevailing in the cellular plane, implementation of the proposed algorithm involves primitive integer operations only, leading to fast execution of the algorithm. Experimental results that include output polygons for different values of the approximation parameter corresponding to several real-world digital curves, a couple of measures on the quality of approximation, comparative results related with two other well-referred algorithms, and CPU times, have been presented to demonstrate the elegance and efficacy of the proposed algorithm

Generation of Highlights from Research Papers Using Pointer-Generator Networks and SciBERT Embeddings

Nowadays many research articles are prefaced with research highlights to summarize the main findings of the paper. Highlights not only help researchers precisely and quickly identify the contributions of a paper, they also enhance the discoverability of the article via search engines. We aim to automatically construct research highlights given certain segments of the research paper. We use a pointer-generator network with coverage mechanism and a contextual embedding layer at the input that encodes the input tokens into SciBERT embeddings. We test our model on a benchmark dataset, CSPubSum and also present MixSub, a new multi-disciplinary corpus of papers for automatic research highlight generation. For both CSPubSum and MixSub, we have observed that the proposed model achieves the best performance compared to related variants and other models proposed in the literature. On the CSPubSum data set, our model achieves the best performance when the input is only the abstract of a paper as opposed to other segments of the paper. It produces ROUGE-1, ROUGE-2 and ROUGE-L F1-scores of 38.26, 14.26 and 35.51, respectively, METEOR F1-score of 32.62, and BERTScore F1 of 86.65 which outperform all other baselines. On the new MixSub data set, where only the abstract is the input, our proposed model (when trained on the whole training corpus without distinguishing between the subject categories) achieves ROUGE-1, ROUGE-2 and ROUGE-L F1-scores of 31.78, 9.76 and 29.3, respectively, METEOR F1-score of 24.00, and BERTScore F1 of 85.25, outperforming other models.Comment: 18 pages, 7 figures, 7 table

Multilayered and Chemiresistive Thin and Thick Film Gas Sensors for Air Quality Monitoring

Selective detection of gases such as nitrogen dioxide (NO2), carbon monoxide (CO), carbon dioxide (CO2), and various volatile organic components (VOCs) is necessary for air quality monitoring. Detection of hydrogen (H2) is equally important as it is a flammable gas and poses serious threat of explosion when exposed to oxygen gas. We have studied the sensing characteristics of these gases using thin film deposited by chemical solution deposition as well as relatively thicker films deposited by atmospheric plasma spray (APS) process. The chapter starts with the sensing mechanism of chemiresistive sensors followed by the definition of gas sensing parameters. Subsequently, we have demonstrated selective NO2 sensing characteristics of zinc oxide-graphene (ZnO-G) multilayered thin film followed by CO and H2 sensing characteristics of ZnO thin film and SnO2 thick film. Cross-sensitivity among CO and H2 gases has been addressed through the analysis of conductance transients with the determination of activation energy, Ea, and heat of adsorption, Q. The concepts of reversible and irreversible sensing have also been discussed in relation to CO and H2 gases. CO2 sensing characteristics of LaFe0.8Co0.2O3 (LFCO)-ZnO thin film have been elucidated. Interference from CO has been addressed with principal component analyses and the ascertaining of Ea and Q values. Additionally, the variation of response with temperature for each gas was simulated to determine distinct parameters for the individual gases. Further, VOC sensing characteristics of copper oxide (CuO) thin film and WO3-SnO2 thick film were investigated. Principal component analysis was performed to discriminate the gases in CuO thin film. The interaction of WO3-SnO2 thick film with various VOCs was found to obey the Freundlich adsorption isotherm based on which Ea and Q values were determined

Leaching behaviour of pendimethalin causes toxicity towards different cultivars of Brassica juncea and Brassica campestris in sandy loam soil

An experiment was conducted at the farm of Zonal Adaptive Research Station, Uttar Banga Krishi Viswavidhyalaya, Pundibari, Cooch Behar, West Bengal to evaluate the effect of pendimethalin on the yield, weed density and phytotoxicity in different varieties of rai (Brassica juncea) and yellow sarson (B. campestris var. yellow sarson) under higher soil moisture regime in Terai region of West Bengal. Pre-emergence application of pendimethalin at higher dose i.e. 1.0 kg/ha recorded higher plant mortality (30.92%) due to the presence of higher concentration of pendimethalin residue (0.292 µg/g) till the tenth day of crop age and consequently had the reduced yield (12.59 q/ha) than the dose of 0.7 kg/ha (13.33 q/ha) where plant mortality was only 12.62% due to comparatively lower level of pendimethalin residue (0.192 µg/g). Although the application of pendimethalin at the rate of 1.0 kg/ha was able to control weed more efficiently (18.96/m2) than the dose of 0.7 kg/ha (30.41/m2) and subsequent lower doses. The herbicide leached down to the root zone resulting in phytotoxicity towards crop. Yellow sarson group (Brassica campestris) showed more susceptibility than rai (Brassica juncea) group against pendimethalin application at higher doses