16 research outputs found

    Design of an Autonomous Agriculture Robot for Real Time Weed Detection using CNN

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    Agriculture has always remained an integral part of the world. As the human population keeps on rising, the demand for food also increases, and so is the dependency on the agriculture industry. But in today's scenario, because of low yield, less rainfall, etc., a dearth of manpower is created in this agricultural sector, and people are moving to live in the cities, and villages are becoming more and more urbanized. On the other hand, the field of robotics has seen tremendous development in the past few years. The concepts like Deep Learning (DL), Artificial Intelligence (AI), and Machine Learning (ML) are being incorporated with robotics to create autonomous systems for various sectors like automotive, agriculture, assembly line management, etc. Deploying such autonomous systems in the agricultural sector help in many aspects like reducing manpower, better yield, and nutritional quality of crops. So, in this paper, the system design of an autonomous agricultural robot which primarily focuses on weed detection is described. A modified deep-learning model for the purpose of weed detection is also proposed. The primary objective of this robot is the detection of weed on a real-time basis without any human involvement, but it can also be extended to design robots in various other applications involved in farming like weed removal, plowing, harvesting, etc., in turn making the farming industry more efficient. Source code and other details can be found at https://github.com/Dhruv2012/Autonomous-Farm-RobotComment: Published at the AVES 2021 conference. Source code and other details can be found at https://github.com/Dhruv2012/Autonomous-Farm-Robo

    Electronic Toll Collection (ETC) System Using Wi-Fi Technology

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    A toll system is one in which a fee (or toll) is assessed for passage of a vehicle from the tollway. In the existing toll tax system, we observe limitations like mismanagement of time, long queue for the payment of toll tax, the payment in cash. Our aim in this paper is user need to pay toll electronically. Wi-Fi toll collection stations allow the traffic to flow continuously, and vehicle being stopping and starting again. This, in combination with reduced fuel consumption has positive effect on environment. By introducing the Wi-Fi technology, we can make this system automatic and easier. The Android phone need to be included in each vehicle and the details of the vehicle owner must be stored in the database of toll tax system. Wi-Fi technology will leverage the existing payment systems used in ETC and will influence the future of toll collection modes in India. DOI: 10.17762/ijritcc2321-8169.16046

    Machine Vision Using Cellphone Camera: A Comparison of deep networks for classifying three challenging denominations of Indian Coins

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    Indian currency coins come in a variety of denominations. Off all the varieties Rs.1, RS.2, and Rs.5 have similar diameters. Majority of the coin styles in market circulation for denominations of Rs.1 and Rs.2 coins are nearly the same except for numerals on its reverse side. If a coin is resting on its obverse side, the correct denomination is not distinguishable by humans. Therefore, it was hypothesized that a digital image of a coin resting on its either size could be classified into its correct denomination by training a deep neural network model. The digital images were generated by using cheap cell phone cameras. To find the most suitable deep neural network architecture, four were selected based on the preliminary analysis carried out for comparison. The results confirm that two of the four deep neural network models can classify the correct denomination from either side of a coin with an accuracy of 97%.Comment: 6 Pages, 4 Figures, 6 Tables, Conference pape

    A case report on generalized pemphigus vulgaris treated with rituximaba

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    Background: Pemphigus vulgaris has an obscure etiology; the presence of autoantibodies is coherent with an autoimmune disease. Rituximab a monoclonal antibody that specifically targets the CD20 antigen of B lymphocytes, has arisen as a novel treatment approach for pemphigus vulgaris.  Case presentation: A 39-year-old male patient presented with a three-month history of mouth ulcers, poor oral hygiene accompanied with heavy tobacco smoking and alcohol consumption. He was diagnosed with pemphigus vulgaris. The disease gradually progressed to involve other body parts. The patient had shown partial improvement after conventional therapy (oral cefuroxime, oral prednisolone with azathioprine) and was later on successfully treated with rituximab. After 90 days of follow-up, no future recurrence was observed. Conclusion: With this case, the authors would like to aware other clinicians of the potential use of rituximab in treating pemphigus vulgaris, especially when the conventional therapy fails

    Job creation for youth in Africa : assessing the potential of industries without smokestacks

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    There is emerging evidence that some industries, including tourism, agro-industry, horticulture, transport, and information technology-enabled services are generating opportunities for job creation and more rapid structural transformation in Africa. This paper assesses the job creation potential of these “industries without smokestacks” (IWOSS) by estimating employment-to-output elasticities. Both transport and telecom (T-T) and tourism have employment elasticities similar to manufacturing and near the ideal 0.7 identified in the literature, suggesting that growth in the sector could enhance productivity and generate employment

    Micromagnet arrays for on-chip focusing, switching, and separation of superparamagnetic beads and single cells

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    Nonlinear magnetophoresis (NLM) is a powerful approach for on-chip transport and separation of superparamagnetic (SPM) beads, based on a travelling magnetic field wave generated by the combination of a micromagnet array (MMA) and an applied rotating magnetic field. Here, we present two novel MMA designs that allow SPM beads to be focused, sorted, and separated on-chip. Converging MMAs were used to rapidly collect the SPM beads from a large region of the chip and focus them into synchronized lines. We characterise the collection efficiency of the devices and demonstrate that they can facilitate on-chip analysis of populations of SPM beads using a single-point optical detector. The diverging MMAs were used to control the transport of the beads and to separate them based on their size. The separation efficiency of these devices was determined by the orientation of the magnetisation of the micromagnets relative to the external magnetic field and the size of the beads relative to that of micromagnets. By controlling these parameters and the rotation of the external magnetic field we demonstrated the controlled transport of SPM bead-labelled single MDA-MB-231 cells. The use of these novel MMAs promises to allow magnetically-labelled cells to be efficiently isolated and then manipulated on-chip for analysis with high-resolution chemical and physical techniques.European Commission - European Regional Development FundIrish Research CouncilScience Foundation IrelandNanoremedies ProgrammeProgramme for Research in Third-Level Institution

    Nonsuicidal self-injury and identity formation in Indian clinical and nonclinical samples: A comparative study

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    Background: Nonsuicidal self-injury (NSSI) is being increasingly identified as an important emerging mental health issue in the West. Yet, NSSI has not been adequately studied in clinical and nonclinical contexts in countries like India. Aim: The aim of this study was to compare different features of NSSI between clinical and nonclinical samples in India. We also explored if the strength of the association between NSSI and disturbances in identity formation – a risk factor that can increase vulnerability to NSSI – was similar in the two samples mentioned above. Method: For the clinical sample, data regarding NSSI and identity formation were collected from 100 psychiatric patients (47.0% females, mean age = 34.76 years, SD = 12.76, 17–70 years) from an outpatient/inpatient psychiatric department of a large tertiary hospital in Mumbai, India. Nonclinical data were collected from 120 young adults studying in a medical college in Mumbai, India (51.7% females, mean age = 19.7 years, SD = 2.16, 17–28 years). Information regarding NSSI and identity were collected using self-report questionnaires. Results: Lifetime prevalence of NSSI in the clinical and nonclinical samples was found to be around 17% and 21%, respectively. Although the prevalence of NSSI did not significantly differ between the two samples, some features of NSSI did differ between the two groups. Finally, multigroup Bayesian structural equation modeling indicated that irrespective of the type of the sample (i.e. clinical or nonclinical), consolidated and disturbed identity significantly (negative and positive, respectively) predicted lifetime NSSI. Additionally, the association between the aforementioned identity variables and NSSI did not significantly differ between the two samples. Conclusion: The findings of these studies highlight the need for exploring issues related to identity formation in individuals who engage in NSSI irrespective of whether they suffer from a psychiatric disorder or not.status: Published onlin
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