Improving the Writing Proficiency of Engineering Students by Strategic Integration of Technology

This paper aims to provide an academic analysis of the user's text and rewrite it in a proficient way. In contemporary engineering education, the cultivation of proficient writing abilities holds significant importance. This article explores the impact of incorporating technology on the improvement of English language writing abilities among engineering students. In the dynamic and ever-changing realm of technology and education, there exists a pressing demand for engineers to proficiently articulate their concepts, remedies, and proposals. The importance of discoveries has never been more crucial. This article examines the importance of effective written communication in the field of engineering and the common difficulties encountered by students in developing this competency.  By strategically incorporating technology, students have the potential to overcome these problems and enhance their writing skills. The article examines a range of technology resources that can be utilized to facilitate this process. The educational platform aims to facilitate student empowerment through the utilization of interactive learning modules, provision of tailored feedback, and the opportunity for individualized growth. Real-life case studies provide concrete evidence of the effective utilization of these tools, demonstrating noticeable enhancements in students' writing abilities. This article provides pragmatic advice on how educators might effectively integrate technology into their instructional approaches. Furthermore, it also takes into consideration probable obstacles, therefore guaranteeing that the utilization of technology in writing development remains accessible and fair to all students

A Machine Learning Framework for Generating Photorealistic Photos of Real Time Objects using Adam Optimizer by a Generative Adversarial Network (GAN)

Photographic training can result in new photographs that, to human observers, appear to be at least superficially authentic, with many realistic features. will discuss a number of intriguing GAN applications in order to help you develop an understanding of the types of problems where GANs can be used and useful. It is not an exhaustive list, but it includes numerous examples of GAN applications that have garnered media attention. This Paper Proposes a Framework for Generating Photorealistic Photos of real time objects (FGPPO) using Adam Optimizer by Generative Adversarial Networks

Increased chickpea yield and economic benefits by improved crop production technology in rainfed areas of Kurnool District of Andhra Pradesh, India

Sixteen on-farm trials in 2002 and 9 trials in 2003 were conducted in Nandavaram and Jillella villages of Banaganapalle mandal in Kurnool district, Andhra Pradesh, India, during the post-rainy season to evaluate the performance of improved production technologies (T1) and farmers' practice (T2) for chickpea production. T1 consisted of improved cultivar (ICCC 37), sowing rate of 60 kg/ha, seed treatment with thiram (3 g/kg), inoculation with Rhizobium, 20 kg N, 50 kg P2O5/ha, basal application of micronutrient mixture (5 kg borax, 0.5 kg B/ha; 50 kg zinc sulfate, 10 kg Zn/ha; and 200 kg gypsum, 30 kg S/ha), and need-based pest and disease control measures. Inter-cultivation was conducted at 25 and 50 days after sowing to control weeds. One insecticide spray was given at the pod formation stage to control pod borers. T2 consisted of a local cultivar, sowing rate of 50 kg/ha, 14 kg N/ha, and 35 kg P2O5/ha. T1 gave higher grain yields and recorded a mean yield of 2.09 t/ha, which was 53% higher than that obtained with T2 (1.37 t/ha). The increased grain yield under T1 was mainly because of greater total dry matter, 100-grain weight and harvest index. T1 also resulted in increased mean income of US$190 and a cost-benefit ratio of 2.9

Effect of improved crop production technology on pigeonpea yield in resource poor rainfed areas.

Twelve on-farm trials were conducted in Nandavaram village of Banaganapalle mandal in Kurnool district, Andhra Pradesh, India, during the 2002/03 rainy season to study the effects of improved production technologies (T1) and farmers' practice (T2) on pigeon pea yield. T1 consisted of a medium-duration high-yielding cultivar (ICPL 87119), sowing rate of 12 kg/ha, seed treatment with thiram (3 g/kg), inoculation with Rhizobium, 20 kg N, 50 kg P2O5/ha, basal application of micronutrient mixture (5 kg borax, 0.5 kg B/ha; 50 kg zinc sulfate, 10 kg Zn/ha; and 200 kg gypsum, 30 kg S/ha), and need-based pest and disease control measures. Inter-cultivation was conducted at 25 and 50 days after sowing to control weeds. One insecticide spray was given at the pod formation stage to control pod borers. T2 included a sowing rate of 10 kg/ha, 12 kg N/ha, and 30 kg P2O5/ha. T1 gave higher yields than T2 and recorded a mean grain yield of 1.61 t/ha, which was 204% higher than that obtained with T2 (0.53 t/ha). T1 also resulted in higher stalk yield (2.93 t/ha) than T2 (1.10 t/ha). The increased grain and stalk yields under were mainly because of increased total dry matter, pod weight, shelling percentage, 100-grain weight and harvest index. T1 recorded a higher mean income (US$290) and a cost-benefit ratio of 2.4

Improved production technology in rainfed groundnut helps reap rich benefits by resource-poor farmers of Andhra Pradesh.

Thirty on-farm trials were conducted during the rainy seasons of 2002 and 2003 in the drought-prone districts of Andhra Pradesh, India, to demonstrate the beneficial effects of improved groundnut production technologies. Improved production technologies gave higher yields at all the locations. The pod yield was 1.22 t/ha in 2002 and 1.64 t/ha in 2003 compared to 0.77 t/ha and 1.02 t/ha, respectively, with farmers' practice. The additional mean cost incurred in the improved package was US$25 (1 US$=Rs 45) compared to an increased mean income of US$158 with a benefit-cost ratio of 1.6

Food-Fodder Traits in Groundnut

Groundnut (Arachis hypogaea) is one of the key crops of the semi-arid tropics. It is commonly cultivated as a foodfeed crop that provides pods for human food and haulms for livestock feeding (Larbi et al. 1999, Omokanye et al. 2001). From farmer participatory studies in the Deccan plateau of India, Rama Devi et al. (2000) concluded that food from grain/pods and fodder from the crop residues almost equally contribute to livelihoods in mixed-crop livestock systems. It was because of this important dualpurpose usage of groundnut that the groundnut improvement group of the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) and livestock nutrition group of the International Livestock Research Institute (ILRI), Patancheru, India started to explore collaboratively the potential for improving pod yield and haulm quantity and quality. Successful inclusion of haulm fodder traits into groundnut improvement has three prerequisites

Participatory selection of groundnut genotypes under rainfed conditions in Kurnool District of Andhra Pradesh.

The performance of 3 drought-tolerant groundnut cultivars (ICGS 11, ICGS 76 and ICGV 86590) and TMV 2 as control was evaluated under rainfed conditions in on-farm participatory trials conducted in Kurnool district, Andhra Pradesh, India, during the rainy season of 2002. The pod yields of the improved cultivars (1.8-2.4 t/ha) were higher by 40-85% than the pod yield of TMV 2 (1.3 t/ha). Among the improved cultivars, ICGS 76 had the highest pod yield (2.4 t/ha), harvest index (0.46), 100-seed weight (39.2 g) and number of developed pods per plant (18.8). This cultivar was the most preferred by farmers based on drought tolerance and high yield potential, followed by ICGS 11

Forage yield and quality in pigeonpea germplasm lines

The forage yield and quality traits and their heritability estimates over 2003 and 2004 in India were observed. Two hundred pigeonpea (Cajanus cajan) germplasm lines were planted at ICRISAT, Patancheru, Andhra Pradesh, India during kharif (rainy) season of 2003 and 2004, with 157 lines grown in both years. The lines were evaluated in a randomized block design with three replications, and harvested at 50% flowering by cutting the plants about 2 feet aboveground. The tested pigeonpea lines showed large genetic variability for forage dry matter yield, nitrogen content, in vitro organic matter digestibility and condensed tannins content in 2003 and 2004. The five best lines for forage yield in rainy season 2003 (8.8-10.5 tonnes/ha) and 2004 (7.0 to 7.8 tonnes/ha) with forage nitrogen content, in vitro organic matter digestibility and condensed tannins content are presented. ICP 2098 was the most promising for forage yield with relatively superior quality in both years. Forage dry matter yield and forage quality traits were unrelated in the 2003 rainy season. However, in the 2004 rainy season, forage yield was positively associated with forage nitrogen content (r = 0.32) and negatively with condensed tannins content (r=-0.18). Estimates of broad sense heritability (h2) for forage yield, nitrogen, condensed tannins and in vitro digestibility were 0.27, 0.51, 0.70 and 0.34, respectively. Mean nitrogen content in the pigeonpea forage was 3.4 and 3.6% in 2003 and 2004, respectively, suggesting that pigeonpea forage can serve as an effective supplement to nitrogen deficient feedstuffs

Observations on Livestock Productivity in Sheep Fed Exclusively on Haulms from Ten Different Genotypes of Groundnut

Haulms from 10 different genotypes of groundnut were tested with growing male sheep for digestibility, intake, nitrogen retention and live weight gains. Very high daily intake levels of > 4% of sheep bodyweight were observed in all haulms. Nitrogen retention (range: 6.7 to 11.4 g/d) and live weight gains (range: 65 to 137 g/d) varied about two fold among genotypes suggesting that the choice of groundnut genotype can have a very significant effect on livestock productivity in feeding systems based on groundnut haulms. Haulm fodder quality difference were well reflected by acid detergent lignin (ADL), which accounted for 58, 39 and 72% of the variation in haulm in vivo digestibility, nitrogen retention and live weight gains, respectively. Using stepwise multiple regression procedures, combinations of haulm ADL content and in vitro digestibility and of haulm ADL content and in vitro metabolisable energy content accounted for 84% and 92% of the variation in in vivo digestibility and live weight gain, respectively. The combination of haulm nitrogen and ADL content accounted for 80% of the variation in nitrogen retention. Among the genotypes, ICGV 89104), ICGV 91114), TMV 2 and ICGV 92093 promoted highest productivity in shee