scholarly journals Agricultural harvesting using integrated robot system

2022 ◽  
Vol 25 (1) ◽  
pp. 152
Author(s):  
Vikram Raja ◽  
Bindu Bhaskaran ◽  
Koushik Karan Geetha Nagaraj ◽  
Jai Gowtham Sampathkumar ◽  
Shri Ram Senthilkumar
Keyword(s):  
Deep Learning ◽  
Fruits And Vegetables ◽  
Cost Effective ◽  
Robotic Manipulators ◽  
Manual Labor ◽  
Improve Quality ◽  
Robot System ◽  
Image Detection ◽  
Viable Solution ◽  
Manual Methods

In today's competitive world, robot designs are developed to simplify and improve quality wherever necessary. The rise in technology and modernization has led people from the unskilled sector to shift to the skilled sector. The agricultural sector's solution for harvesting fruits and vegetables is manual labor and a few other agro bots that are expensive and have various limitations when it comes to harvesting. Although robots present may achieve harvesting, the affordability of such designs may not be possible by small and medium-scale producers. The integrated robot system is designed to solve this problem, and when compared with the existing manual methods, this seems to be the most cost-effective, efficient, and viable solution. The robot uses deep learning for image detection, and the object is acquired using robotic manipulators. The robot uses a Cartesian and articulated configuration to perform the picking action. In the end, the robot is operated where carrots and cantaloupes were harvested. The data of the harvested crops are used to arrive at the conclusion of the robot's accuracy.

Deep-n-Cheap: An Automated Efficient and Extensible Search Framework for Cost-Effective Deep Learning

2021 ◽  
Vol 2 (4) ◽  
Author(s):  
Sourya Dey ◽  
Sara Babakniya ◽  
Saikrishna C. Kanala ◽  
Marco Paolieri ◽  
Leana Golubchik ◽  
...  
Keyword(s):  
Deep Learning ◽  
Cost Effective

scholarly journals Management of Hypertension: A Bangladeshi Perspective

1970 ◽  
Vol 39 (1) ◽  
pp. 40-43
Author(s):  
SM Mustafa Zaman ◽  
Mohammad Salman ◽  
Kaniz Fatema
Keyword(s):  
Cardiovascular Disease ◽  
Fruits And Vegetables ◽  
Lifestyle Modification ◽  
Clinical Care ◽  
Cost Effective ◽  
Developed Countries ◽  
Population Based ◽  
Lifestyle Changes ◽  
Optimum Level ◽  
Lifestyle Modifications

Hypertension is a silent killer. Bangladeshis are racially predisposed to cardiovascular disease, and the increasing burden of hypertension has only added to the problem. Economic constraints and the allure of additional benefits without adverse effects have made lifestyle modifications an attractive proposition in developing and developed countries alike. Blood pressure is a continuum and any increase above optimum level confers additional independent risk of cardiovascular disease. We review screening, diagnosis and management using lifestyle measures and pharmacotherapy. We then discuss the barriers and challenges to implementing this approach and what can be done regarding prevention, screening, lifestyle modification and pharmacotherapy in our country. By adopting a comprehensive population based approach including policy level interventions directed at promoting lifestyle changes; a healthy diet (appropriate calories, low in saturated fats and salt and rich in fruits and vegetables), increased physical activity, and a smoking free society, properly balanced with a high risk approach of cost effective clinical care, Bangladesh can effectively control hypertension and improve public health. DOI: 10.3329/bmj.v39i1.6232 Bangladesh Medical Journal 2010; 39(1): 40-43

scholarly journals Fabric Defect Detection System Using Stacked Convolutional Denoising Auto-Encoders Trained with Synthetic Defect Data

2020 ◽  
Vol 10 (7) ◽  
pp. 2511
Author(s):  
Young-Joo Han ◽  
Ha-Jin Yu
Keyword(s):  
Image Segmentation ◽  
Deep Learning ◽  
Machine Vision ◽  
Image Classification ◽  
Defect Detection ◽  
Detection System ◽  
Image Detection ◽  
Fabric Defect Detection ◽  
Fabric Defect ◽  
Segmentation Image

As defect detection using machine vision is diversifying and expanding, approaches using deep learning are increasing. Recently, there have been much research for detecting and classifying defects using image segmentation, image detection, and image classification. These methods are effective but require a large number of actual defect data. However, it is very difficult to get a large amount of actual defect data in industrial areas. To overcome this problem, we propose a method for defect detection using stacked convolutional autoencoders. The autoencoders we proposed are trained by using only non-defect data and synthetic defect data generated by using the characteristics of defect based on the knowledge of the experts. A key advantage of our approach is that actual defect data is not required, and we verified that the performance is comparable to the systems trained using real defect data.

scholarly journals A Cost-Effective Person-Following System for Assistive Unmanned Vehicles with Deep Learning at the Edge

Machines ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 49
Author(s):  
Anna Boschi ◽  
Francesco Salvetti ◽  
Vittorio Mazzia ◽  
Marcello Chiaberge
Keyword(s):  
Deep Learning ◽  
Cost Effective ◽  
Vital Statistics ◽  
Unmanned Vehicles ◽  
Optimization Techniques ◽  
World Population ◽  
Service Robotics ◽  
Power Efficient ◽  
Person Following ◽  
The World

The vital statistics of the last century highlight a sharp increment of the average age of the world population with a consequent growth of the number of older people. Service robotics applications have the potentiality to provide systems and tools to support the autonomous and self-sufficient older adults in their houses in everyday life, thereby avoiding the task of monitoring them with third parties. In this context, we propose a cost-effective modular solution to detect and follow a person in an indoor, domestic environment. We exploited the latest advancements in deep learning optimization techniques, and we compared different neural network accelerators to provide a robust and flexible person-following system at the edge. Our proposed cost-effective and power-efficient solution is fully-integrable with pre-existing navigation stacks and creates the foundations for the development of fully-autonomous and self-contained service robotics applications.

Passive Diffusion through Polymeric Membranes: A Novel Cleanup Procedure for Analysis of Azinphos-Methyl and Azinphos-Ethyl Residues in Fruits and Vegetables

1995 ◽  
Vol 78 (6) ◽  
pp. 1450-1454 ◽  
Author(s):  
Nazir Ahmad ◽  
Lin Guo ◽  
Peter Mandarakas ◽  
Sbmeone Appleby ◽  
George Bugueno
Keyword(s):  
Fruits And Vegetables ◽  
Residue Analysis ◽  
Cost Effective ◽  
Field Evaluation ◽  
Polymeric Membrane ◽  
Gas Liquid Chromatography ◽  
Final Volume ◽  
High Lipid ◽  
Azinphos Methyl ◽  
Cleanup Procedure

Abstract A novel procedure is described for simple removal of coextractives prior to analysis of fruits and vegetables for azinphos-methyl and azinphos-ethyl residues. The solvent extract is concentrated, placed in a polymeric membrane tube, and then dialyzed in cyclohexane. Both azinphos-methyl and azinphos- ethyl diffuse into the surrounding solvent while coextractants remain inside the membrane. The dialyzing solvent is exchanged during concentration with n-hexane and analyzed without further cleanup by gas-liquid chromatography with a specific thermionic detector. The detection limit for a 25 g grape sample with final volume of extract made to 15 mL was 0.01 mg/kg. Recoveries of both residues from grapes averaged 107% (spike levels of 0.3 to 2.0 mg/kg). From a 20 g spinach sample, recoveries averaged 82% for azinphos-methyl and 72% for azinphos-ethyl when final volume of extract was made to 5 mL (spike levels of 0.1 to 1.0 mg/kg). Recoveries from 20 types of fruits and vegetables (20 g sample spiked at 1 mg/kg for both azinphos-methyl and azinphos-ethyl) were consistently greater than 70%, except for strawberries (61–67%) and avocado (28–34%). The high lipid content of avocado may impede diffusion of azinphosmethyl and azinphos-ethyl through the polymeric membrane. A field evaluation of the procedure showed a strong correlation (r = 0.957) between azinphos-methyl residues on grapes and treatments with 2 spray formulations. The membrane cleanup procedure is a simple and cost-effective alternative to other column or liquid–liquid partitioning procedures for azinphos-methyl and azinphosethyl residue analysis.

Great Plains Interactive Distance Education Alliance (Great Plains IDEA)

2010 ◽  
pp. 110-130 ◽  
Author(s):  
Virginia Moxley ◽  
Sue Maes ◽  
Dawn Anderson
Keyword(s):  
Higher Education ◽  
Distance Education ◽  
Great Plains ◽  
Effective Means ◽  
Cost Effective ◽  
Lessons Learned ◽  
Academic Programs ◽  
Award Winning ◽  
Viable Solution ◽  
Higher Education Leaders

This chapter will examine the organizational and technological challenges encountered by the highly successful Great Plains Interactive Distance Education Alliance (Great Plains IDEA) since its members began offering multi-university online academic programs in 2000. Members include the following universities: Colorado State, Iowa State, Kansas State, Texas Tech, Michigan State, Missouri, Montana State, Nebraska, North Dakota State, Oklahoma State, and South Dakota State. Inter-institutional online academic programs are a cost-effective means of rapidly increasing access and addressing emerging educational needs. The chapter explains how the Great Plains IDEA began, operates and has evolved, as well as the mistakes made, lessons learned, and upcoming challenges. A major technological challenge was identifying a secure multi-institution enrollment system for sharing student data between enrolling and teaching institutions the award-winning ExpanSIS system. The authors hope that higher education leaders will be convinced that inter-institutional collaboration is a viable solution to many higher education challenges.

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