Search results for: apple leaf disease recognition

Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay

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Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.

Keywords: retail stores, faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition

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Authors: Zahra Bakhtiari

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This article explores the development and evolution of the concept of environmental justice, which has shifted from being dominated by white and middle-class individuals to a civil struggle by marginalized communities against environmental injustices. Environmental justice aims to achieve equity in decision-making and policy-making related to the environment. The concept of justice in this context includes four fundamental aspects: distribution, procedure, recognition, and capabilities. Recent scholars have attempted to broaden the concept of justice to include dimensions of participation, recognition, and capabilities. Focusing on all four dimensions of environmental justice is crucial for effective planning and policy-making to address environmental issues. Ignoring any of these aspects can lead to the failure of efforts and the waste of resources.

Keywords: environmental justice, distribution, procedure, recognition, capabilities

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Authors: Anum Akhter, Sumaira Altaf

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Purpose: To study the effect of low vision devices i.e. telescope and magnifying glasses on distance visual acuity and near visual acuity of children with Stargardt’s disease. Setting: Low vision department, Alshifa Trust Eye Hospital, Rawalpindi, Pakistan. Methods: 52 children having Stargardt’s disease were included in the study. All children were diagnosed by pediatrics ophthalmologists. Comprehensive low vision assessment was done by me in Low vision clinic. Visual acuity was measured using ETDRS chart. Refraction and other supplementary tests were performed. Children with Stargardt’s disease were provided with different telescopes and magnifying glasses for improving far vision and near vision. Results: Out of 52 children, 17 children were males and 35 children were females. Distance visual acuity and near visual acuity improved significantly with low vision aid trial. All children showed visual acuity better than 6/19 with a telescope of higher magnification. Improvement in near visual acuity was also significant with magnifying glasses trial. Conclusions: Low vision aids are useful for improvement in visual acuity in children. Children with Stargardt’s disease who are having a problem in education and daily life activities can get help from low vision aids.

Keywords: Stargardt, s disease, low vision aids, telescope, magnifiers

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Authors: K. Assis, K. P. Chong, A. S. Idris, C. M. Ho

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Oil palm or Elaeis guineensis is considered as the golden crop in Malaysia. But oil palm industry in this country is now facing with the most devastating disease called as Ganoderma Basal Stem Rot disease. The objective of this paper is to analyze the economic loss due to this disease. There were three commercial oil palm sites selected for collecting the required data for economic analysis. Yield parameter used to measure the loss was the total weight of fresh fruit bunch in six months. The predictors include disease severity, change in disease severity, number of infected neighbor palms, age of palm, planting generation, topography, and first order interaction variables. The estimation model of yield loss was identified by using backward elimination based regression method. Diagnostic checking was conducted on the residual of the best yield loss model. The value of mean absolute percentage error (MAPE) was used to measure the forecast performance of the model. The best yield loss model was then used to estimate the economic loss by using the current monthly price of fresh fruit bunch at mill gate.

Keywords: ganoderma, oil palm, regression model, yield loss, economic loss

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Authors: R. O. Anyasi, H. I. Atagana

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In this study, phytoextraction ability of a weed on Aroclor 1254 was studied under greenhouse conditions. Chromolaena odorata plants were transplanted into soil containing 100, 200, and 500 ppm of Aroclor in 1L pots. The experiments were watered daily at 70 % moisture field capacity. Parameters such as fully expanded leaves per plant, shoot length, leaf chlorophyll content as well as root length at harvest were measured. PCB was not phytotoxic to C. odorata growth but plants in the 500 ppm treatment only showed diminished growth at the sixth week. Percentage increases in height of plant were 45.9, 39.4 and 40.0 for 100, 200 and 500 ppm treatments respectively. Such decreases were observed in the leaf numbers, root length and leaf chlorophyll concentration. The control sample showed 48.3 % increase in plant height which was not significant from the treated samples, an indication that C. odorata could survive such PCB concentration and could be used to remediate contaminated soil. Mean total PCB absorbed by C. odorata plant was between 6.40 and 64.60 ppm per kilogram of soil, leading to percentage PCB absorption of 0.03 and 17.03 % per kilogram of contaminated soil. PCBs were found mostly in the root tissues of the plants, and the Bioaccumulation factor were between 0.006-0.38. Total PCB absorbed by the plant increases as the concentration of the compound is increased. With these high BAF ensured, C. odorata could serve as a promising candidate plant in phytoextraction of PCB from a PCB-contaminated soil.

Keywords: phytoremediation, bioremediation, soil restoration, polychlorinated biphenyls (PCB), biological treatment, aroclor

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Authors: Ali Farzan

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Classification of data objects or patterns is a major part in most of Decision making systems. One of the popular and commonly used classification methods is Decision Tree (DT). It is a hierarchical decision making system by which a binary tree is constructed and starting from root, at each node some of the classes is rejected until reaching the leaf nods. Each leaf node is a representative of one specific class. Finding the splitting criteria in each node for constructing or training the tree is a major problem. Particle Swarm Optimization (PSO) has been adopted as a metaheuristic searching method for finding the best splitting criteria. Result of evaluating the proposed method over benchmark datasets indicates the higher accuracy of the new PSO based decision tree.

Keywords: decision tree, particle swarm optimization, splitting criteria, metaheuristic

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Authors: Temosho Promise Chuene, T. Chitura

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Background: Foot and mouth disease is a real challenge in South Africa. The disease is a serious threat to the viability of livestock farming initiatives and affects local and international livestock trade. In Limpopo Province, the Kruger National Park and other game reserves are home to the African buffalo (Syncerus caffer), a notorious reservoir of the picornavirus, which causes foot and mouth disease. Out of the virus’s seven (7) distinct serotypes, Southern African Territories (SAT) 1, 2, and 3 are commonly endemic in South Africa. The broad objective of the study was to establish the trend of foot and mouth disease in Limpopo Province over a seven-year period (2014-2020), as well as the adoption and comprehensive reporting of the measures that are taken to contain disease outbreaks in the study area. Methods: The study used secondary data from the World Organization for Animal Health (WOAH) on reported cases of foot and mouth disease in South Africa. Descriptive analysis (frequencies and percentages) and Analysis of variance (ANOVA) were used to present and analyse the data. Result: The year 2020 had the highest prevalence of foot and mouth disease (3.72%), while 2016 had the lowest prevalence (0.05%). Serotype SAT 2 was the most endemic, followed by SAT 1. Findings from the study demonstrated the seasonal nature of foot and mouth disease in the study area, as most disease cases were reported in the summer seasons. Slaughter of diseased and at-risk animals was the only documented disease control strategy, and information was missing for some of the years. Conclusion: The study identified serious underreporting of the adopted control strategies following disease outbreaks. Adoption of comprehensive disease control strategies coupled with thorough reporting can help to reduce outbreaks of foot and mouth disease and prevent losses to the livestock farming sector of South Africa and Limpopo Province in particular.

Keywords: livestock farming, African buffalo, prevalence, serotype, slaughter

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Authors: T. Alghamdi, G. Alaghband

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In this paper we develop a model that couples Two Concurrent Convolution Neural Network with different filters (TC*CNN) for face recognition and compare its performance to an existing sequential CNN (base model). We also test and compare the quality and performance of the models on three datasets with various levels of complexity (easy, moderate, and difficult) and show that for the most complex datasets, edges will produce the most accurate and efficient results. We further show that in such cases while Support Vector Machine (SVM) models are fast, they do not produce accurate results.

Keywords: Convolution Neural Network, Edges, Face Recognition , Support Vector Machine.

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Authors: Qian Liu, Steve Furber

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To explore how the brain may recognize objects in its general,accurate and energy-efficient manner, this paper proposes the use of a neuromorphic hardware system formed from a Dynamic Video Sensor~(DVS) silicon retina in concert with the SpiNNaker real-time Spiking Neural Network~(SNN) simulator. As a first step in the exploration on this platform a recognition system for dynamic hand postures is developed, enabling the study of the methods used in the visual pathways of the brain. Inspired by the behaviours of the primary visual cortex, Convolutional Neural Networks (CNNs) are modeled using both linear perceptrons and spiking Leaky Integrate-and-Fire (LIF) neurons. In this study's largest configuration using these approaches, a network of 74,210 neurons and 15,216,512 synapses is created and operated in real-time using 290 SpiNNaker processor cores in parallel and with 93.0% accuracy. A smaller network using only 1/10th of the resources is also created, again operating in real-time, and it is able to recognize the postures with an accuracy of around 86.4% -only 6.6% lower than the much larger system. The recognition rate of the smaller network developed on this neuromorphic system is sufficient for a successful hand posture recognition system, and demonstrates a much-improved cost to performance trade-off in its approach.

Keywords: spiking neural network (SNN), convolutional neural network (CNN), posture recognition, neuromorphic system

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Authors: Shahpar Yilmaz, Yasir Nadeem, Syed A. Mehdi

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Searching for a record in a dataset is always a frequent task for any data structure-related application. Hence, a fast and efficient algorithm for the approach has its importance in yielding the quickest results and enhancing the overall productivity of the company. Interpolation search is one such technique used to search through a sorted set of elements. This paper proposes a new algorithm, an advancement over interpolation search for the application of search over a sorted array. Pattern Recognition Search or PR Search (PRS), like interpolation search, is a pattern-based divide and conquer algorithm whose objective is to reduce the sample size in order to quicken the process and it does so by treating the array as a perfect arithmetic progression series and thereby deducing the key element’s position. We look to highlight some of the key drawbacks of interpolation search, which are accounted for in the Pattern Recognition Search.

Keywords: array, complexity, index, sorting, space, time

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Authors: Nermeen El Kashef, Yasser Fouad, Khaled Mahar

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No AI-complete system can model the human brain or behavior, without looking at the totality of the whole situation and incorporating a combination of senses. This paper proposes a Pattern Recognition model based on Simulation of Chemical Senses (SCS) for separation and classification of sign language. The model based on human taste controlling strategy. The main idea of the introduced model is motivated by the facts that the tongue cluster input substance into its basic tastes first, and then the brain recognizes its flavor. To implement this strategy, two level architecture is proposed (this is inspired from taste system). The separation-level of the architecture focuses on hand posture cluster, while the classification-level of the architecture to recognizes the sign language. The efficiency of proposed model is demonstrated experimentally by recognizing American Sign Language (ASL) data set. The recognition accuracy obtained for numbers of ASL is 92.9 percent.

Keywords: artificial intelligence, biocybernetics, gustatory system, sign language recognition, taste sense

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Authors: Ali Reza Tahavvor, Saeed Hosseini, Nazli Jowkar, Behnam Amiri

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Heat transfer of leaves is a crucial factor in optimal operation of metabolic functions in plants. In order to quantify this phenomenon in different leaves and investigate the influence of leaf shape on heat transfer, natural convection for pine, orange and olive leaves was simulated as representatives of different groups of leaf shapes. CFD techniques were used in this simulation with the purpose to calculate heat transfer of leaves in similar environmental conditions. The problem was simulated for steady state and three-dimensional conditions. From obtained results, it was concluded that heat fluxes of all three different leaves are almost identical, however, total rate of heat transfer have highest and lowest values for orange leaves and pine leaves, respectively.

Keywords: computational fluid dynamic, heat flux, heat transfer, natural convection

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Authors: Priya Arora, Ashutosh Mishra

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Gene identification, towards the pursuit of mutated genes, leading to Parkinson’s disease, puts forward a challenge towards proactive cure of the disorder itself. Computational analysis is an effective technique for exploring genes in the form of protein sequences, as the theoretical and manual analysis is infeasible. The limitations and effectiveness of a particular computational method are entirely dependent on the previous data that is available for disease identification. The article presents a sequence-based classification method for the identification of genes responsible for Parkinson’s disease. During the initiation phase, the physicochemical properties of amino acids transform protein sequences into a feature vector. The second phase of the method employs Jaccard distances to select negative genes from the candidate population. The third phase involves artificial neural networks for making final predictions. The proposed approach is compared with the state of art methods on the basis of F-measure. The results confirm and estimate the efficiency of the method.

Keywords: disease gene identification, Parkinson’s disease, physicochemical properties of amino acid, protein sequences

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Authors: Manaranjan Pradhan, Shailaja Grover, U. Dinesh Kumar

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Farming community in India, as well as other parts of the world, is one of the highly stressed communities due to reasons such as increasing input costs (cost of seeds, fertilizers, pesticide), droughts, reduced revenue leading to farmer suicides. Lack of integrated farm advisory system in India adds to the farmers problems. Farmers need right information during the early stages of crop’s lifecycle to prevent damage and loss in revenue. In this paper, we use deep learning techniques to develop an early warning system for detection of crop diseases using images taken by farmers using their smart phone. The research work leads to building a smart assistant using analytics and big data which could help the farmers with early diagnosis of the crop diseases and corrective actions. The classical approach for crop disease management has been to identify diseases at crop level. Recently, ImageNet Classification using the convolutional neural network (CNN) has been successfully used to identify diseases at individual plant level. Our model uses convolution filters, max pooling, dense layers and dropouts (to avoid overfitting). The models are built for binary classification (healthy or not healthy) and multi class classification (identifying which disease). Transfer learning is used to modify the weights of parameters learnt through ImageNet dataset and apply them on crop diseases, which reduces number of epochs to learn. One shot learning is used to learn from very few images, while data augmentation techniques are used to improve accuracy with images taken from farms by using techniques such as rotation, zoom, shift and blurred images. Models built using combination of these techniques are more robust for deploying in the real world. Our model is validated using tomato crop. In India, tomato is affected by 10 different diseases. Our model achieves an accuracy of more than 95% in correctly classifying the diseases. The main contribution of our research is to create a personal assistant for farmers for managing plant disease, although the model was validated using tomato crop, it can be easily extended to other crops. The advancement of technology in computing and availability of large data has made possible the success of deep learning applications in computer vision, natural language processing, image recognition, etc. With these robust models and huge smartphone penetration, feasibility of implementation of these models is high resulting in timely advise to the farmers and thus increasing the farmers' income and reducing the input costs.

Keywords: analytics in agriculture, CNN, crop disease detection, data augmentation, image recognition, one shot learning, transfer learning

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Authors: Lebogang Jane Msiza, Felix Dapare Dakora

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Photosynthesis is a process by which plants convert light energy to chemical energy for metabolic processes. Plants are known for converting inorganic CO₂ in the atmosphere to organic C by photosynthesis. A decrease in stomatal conductance causes a decrease in the transpiration rate of leaves, thus increasing the water-use efficiency of plants. Water-use efficiency in plants is conditioned by soil moisture availability and is enhanced under conditions of water deficit. This study evaluated leaf photosynthesis and water-use efficiency in 12 legume species inoculated with 26 rhizobial isolates from soybean, 15 from common bean, 10 from cowpea, 15 from Bambara groundnut, 7 from lessertia and 10 from Kersting bean. Gas-exchange studies were used to measure photosynthesis and water-use efficiency. The results revealed a much higher photosynthetic rate (20.95µmol CO₂ m-2s-1) induced by isolated tutpres to a lower rate (7.06 µmol CO₂ m-2s-1) by isolate mgsa 88. Stomatal conductance ranged from to 0.01 mmol m-2.s-1 by mgsa 88 to 0.12 mmol m-2.s-1 by isolate da-pua 128. Transpiration rate also ranged from 0.09 mmol m-2.s-1 induced by da-pua B2 to 3.28 mmol m-2.s-1 by da-pua 3, while water-use efficiency ranged from 91.32 µmol CO₂ m-1 H₂O elicited by mgsa 106 to 4655.50 µmol CO₂ m-1 H₂O by isolate tutswz 13. The results revealed the highest photosynthetic rate in soybean and the lowest in common bean, and also with higher stomatal conductance and transpiration rates in jack bean and Bambara groundnut. Pigeonpea exhibited much higher water-use efficiency than all the tested legumes. The findings showed significant differences between and among the test legume/rhizobia combinations. Leaf photosynthetic rates are reported to be higher in legumes with high stomatal conductance, which suggests that legume productivity can be improved by manipulating leaf stomatal conductance.

Keywords: legumes, photosynthetic rate, stomatal conductance, water-use efficiency

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Authors: Shabnam Alizadeh, Hatice Dumanoglu

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Plant tissue culture is a substantial plant propagation technique for mass clonal production throughout the year, regardless of time in fruit species. However, the rooting achievement must be enhanced in the difficult-to-root genotypes. Classical auxin applications in clonal propagation of these genotypes are inadequate to solve the rooting problem. Nanoparticles having different physical and chemical properties from bulk material could enhance the rooting success of controlled release of these substances when loaded with auxin due to their ability to reach the active substance up to the target cells as a carrier system.The purpose of this study is to investigate the effects of zinc oxide nanoparticles loaded with indole-3-acetic acid (IAA-nZnO) and indole-3-butyric acid (IBA-nZnO) on in vitro rooting of microcuttings in a difficult-to-root apple genotype (Malus domestica Borkh.). Rooting treatments consisted of IBA or IAA at concentrations of 0.5, 1.0, 2.0, 3.0 mg/L; nZnO, IAA-nZnO and IBA-nZnO at doses of 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 mg/L were used. All components were added to the Murashige and Skoog (MS) basal medium at strength ½ with 2% sucrose and 0.7% agar before autoclaving. In the study, no rooting occurred in control and nZnO applications. Especially, 1.0 mg/L and 2.0 mg/L IBA-nZnO nanoparticle applications (containing 0.5 mg/L and 0.9 mg/L IBA), respectively with rooting rates of 40.3% and 70.4%, rooting levels of 2.0±0.4 and 2.3±0.4, 2.6±0.7 and 2.5±0.6 average root numbers and 20.4±1.6 mm and 20.2±3.4 mm average root lengths put forward as effective applications.

Keywords: Auxin, Malus, nanotechnology, zinc oxide nanoparticles

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Authors: Javad Khaligh, Aghileh Heydari, Ali Akbar Heydari

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Mathematical epidemiological models for the spread of disease through a population are used to predict the prevalence of a disease or to study the impacts of treatment or prevention measures. Initial conditions for these models are measured from statistical data collected from a population since these initial conditions can never be exact, the presence of chaos in mathematical models has serious implications for the accuracy of the models as well as how epidemiologists interpret their findings. This paper confirms the chaotic behavior of a model for dengue fever and SI by investigating sensitive dependence, bifurcation, and 0-1 test under a variety of initial conditions.

Keywords: epidemiological models, SEIR disease model, bifurcation, chaotic behavior, 0-1 test

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Authors: Abdolreza Esmaeilzadeh, Mehri Mirzaei

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Objective: Rheumatic disease is a chronic disease that causes pain, stiffness, swelling and limited motion and function of many joints. RA is the most common form of autoimmune arthritis, affecting more than 1.3 million Americans. Of these, about 75% are women. Materials and Methods: This study was formed due to the misconception about ANA test, which is frequently performed with methods based upon solid phase as ELISA. This experiment was conducted on 430 patients, with clinical symptoms that are likely affected with rheumatic diseases, simultaneously by means of ANA and FANA. Results: 36 cases (8.37%) of patients, despite positive ANA, have demonstrated negative results via Indirect Immunofluorescence Assay (IIFA), (false positive). 116 cases (27%) have demonstrated negative ANA results, by means of the ELISA technique, although they had positive IIFA results. Conclusion: Other advantages of IIFA are antibody titration and specific pattern detection that have the capability of distinguishing positive dsDNA results. According to the restrictions and false negative cases, in patients, IIFA test is highly recommended for these disease's diagnosis.

Keywords: autoimmune disease, IIFA, EIA, rheumatic disease

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Authors: Bharti Chogtu Magazine, Dhanya Soodana Mohan, Shruti Nair, Tanwi Trushna

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The study was undertaken to analyse the cardiovascular drugs being prescribed in patients with concomitant reactive airway disease and hypertension or ischemic heart diseases (IHD). Also, the effect of beta-blockers on respiratory symptoms in these patients was recorded. Data was collected from medical records of patients with reactive airway disease and concomitant hypertension and IHD. It included demographic details of the patients, diagnosis, drugs prescribed and the patient outcome regarding the exacerbation of asthma symptoms with intake of beta blockers. Medical records of 250 patients were analysed.13% of patients were prescribed beta-blockers. 12% of hypertensive patients, 16.6% of IHD patients and 20% of patients with concomitant hypertension and IHD were prescribed beta blockers. Of the 33 (13%) patients who were on beta-blockers, only 3 patients had an exacerbation of bronchial asthma symptoms. Cardioselective beta-blockers under supervision appear to be safe in patients with reactive airway disease and concomitant hypertension and IHD.

Keywords: beta blockers, hypertension, ischemic heart disease, asthma

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Authors: Qiang Wang, Hongyang Yu, MingRong Lai, Miao Luo

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This paper presents a method for accurately localizing and interacting with known surface defects by overlaying patterns onto real-world surfaces using a projection system. Given the world coordinates of the defects, we project corresponding patterns onto the surfaces, providing an intuitive visualization of the specific defect locations. To enable users to interact with and retrieve more information about individual defects, we implement a gesture recognition system based on a pruned and optimized version of YOLOv6. This lightweight model achieves an accuracy of 82.8% and is suitable for deployment on low-performance devices. Our approach demonstrates the potential for enhancing defect identification, inspection processes, and user interaction in various applications.

Keywords: defect localization, projection mapping, gesture recognition, YOLOv6

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Authors: Mehmet Bulent Ozdemir, Sultan Çagirici, Sahika Pinar Akyer, Fikri Turk

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Neuroanatomical appearance can be correlated with clinical or other characteristics of illness. With the introduction of diagnostic imaging machines, producing 3D images of anatomic structures, calculating the correlation between subjects and pattern of the structures have become possible. The aim of this study is to examine the 3D structure of hippocampus in cases with Alzheimer disease in different dementia severity. For this purpose, 62 female and 38 male- 68 patients’s (age range between 52 and 88) MR scanning were imported to the computer. 3D model of each right and left hippocampus were developed by a computer aided propramme-Surf Driver 3.5. Every reconstruction was taken by the same investigator. There were different apperance of hippocampus from normal to abnormal. In conclusion, These results might improve the understanding of the correlation between the morphological changes in hippocampus and clinical staging in Alzheimer disease.

Keywords: Alzheimer disease, hippocampus, computer-assisted anatomy, 3D

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Authors: Hermalina Sinay, Estri L. Arumingtyas

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The research objective was to determine the expression level of dehydration responsive element binding/DREB gene of local corn cultivars from Kisar Island Maluku. The study design was a randomized block design with single factor consist of six local corn cultivars obtained from farmers in Kisar Island and one reference varieties wich has been released by the government as a drought-tolerant varieties and obtained from Cereal Crops Research Institute (ICERI) Maros South Sulawesi. Leaf samples were taken is the second leaf after the flag leaf at the 65 days after planting. Isolation of total RNA from leaf samples was carried out according to the protocols of the R & A-BlueTM Total RNA Extraction Kit and was used as a template for cDNA synthesis. The making of cDNA from total RNA was carried out according to the protocol of One-Step Reverse Transcriptase PCR Premix Kit. Real Time-PCR was performed on cDNA from reverse transcription followed the procedures of Real MODTM Green Real-Time PCR Master Mix Kit. Data obtained from the real time-PCR results were analyzed using relative quantification method based on the critical point / Cycle Threshold (CP / CT). The results of gene expression analysis of DREB gene showed that the expression level of the gene was highest obtained at Deep Yellow local corn cultivar, and the lowest one was obtained at the Rubby Brown Cob cultivar. It can be concluded that the expression level of DREB gene of Deep Yellow local corn cultivar was highest than other local corn cultivars and Srikandi variety as a reference variety.

Keywords: expression, level, DREB gene, local corn cultivars, Kisar Island, Maluku

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Authors: Brittany Richardson, Ying Wang

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For physical therapy, exercise prescription, athlete training, and regular fitness training, it is crucial to perform health assessments or fitness assessments periodically. An accurate assessment is propitious for tracking recovery progress, preventing potential injury and making long-range training plans. Assessments include necessary measurements, height, weight, blood pressure, heart rate, body fat, etc. and advanced evaluation, muscle group strength, stability-mobility, and movement evaluation, etc. In the current standard assessment procedures, the accuracy of assessments, especially advanced evaluations, largely depends on the experience of physicians, coaches, and personal trainers. And it is challenging to track clients’ progress in the current assessment. Unlike the tradition assessment, in this paper, we present a deep learning based face recognition algorithm for accurate, comprehensive and trackable assessment. Based on the result from our assessment, physicians, coaches, and personal trainers are able to adjust the training targets and methods. The system categorizes the difficulty levels of the current activity for the client or user, furthermore make more comprehensive assessments based on tracking muscle group over time using a designed landmark detection method. The system also includes the function of grading and correcting the form of the clients during exercise. Experienced coaches and personal trainer can tell the clients' limit based on their facial expression and muscle group movements, even during the first several sessions. Similar to this, using a convolution neural network, the system is trained with people’s facial expression to differentiate challenge levels for clients. It uses landmark detection for subtle changes in muscle groups movements. It measures the proximal mobility of the hips and thoracic spine, the proximal stability of the scapulothoracic region and distal mobility of the glenohumeral joint, as well as distal mobility, and its effect on the kinetic chain. This system integrates data from other fitness assistant devices, including but not limited to Apple Watch, Fitbit, etc. for a improved training and testing performance. The system itself doesn’t require history data for an individual client, but the history data of a client can be used to create a more effective exercise plan. In order to validate the performance of the proposed work, an experimental design is presented. The results show that the proposed work contributes towards improving the quality of exercise plan, execution, progress tracking, and performance.

Keywords: exercise prescription, facial recognition, landmark detection, fitness assessments

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Authors: Fei Gao, Xinyang Dong, Yisu Ge, Shufang Lu, Libo Weng

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Vehicle color recognition plays an important role in traffic accident investigation. However, due to the influence of illumination, weather, and noise, vehicle color recognition still faces challenges. In this paper, a vehicle color classification network based on spatial cluster loss and channel attention mechanism (SCNet) is proposed for vehicle color recognition. A channel attention module is applied to extract the features of vehicle color representative regions and reduce the weight of nonrepresentative color regions in the channel. The proposed loss function, called spatial clustering loss (SC-loss), consists of two channel-specific components, such as a concentration component and a diversity component. The concentration component forces all feature channels belonging to the same class to be concentrated through the channel cluster. The diversity components impose additional constraints on the channels through the mean distance coefficient, making them mutually exclusive in spatial dimensions. In the comparison experiments, the proposed method can achieve state-of-the-art performance on the public datasets, VCD, and VeRi, which are 96.1% and 96.2%, respectively. In addition, the ablation experiment further proves that SC-loss can effectively improve the accuracy of vehicle color recognition.

Keywords: feature extraction, convolutional neural networks, intelligent transportation, vehicle color recognition

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Authors: Moin Uddin, M. Masroor A. Khan, Faisal Rasheed, Tariq Ahmad Dar, Akbar Ali, Lalit Varshney

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Oligomers, obtained by exposing the natural polysaccharides (alginate, carrageenan, chitosan, etc.) to cobalt-60 generated gamma radiation may prove as potent plant growth promoters when applied as foliar sprays to the plants. They function as endogenous growth elicitors, triggering the synthesis of different enzymes and modulating various plant responses by exploiting the gene expression. Exogenous application of Jasmonic acid or of its methyl ester, methyl jasmonate (MeJ) has been reported to increase the secondary metabolites production in medicinal and aromatic plants. Keeping this in mind, three pot experiments were conducted to test whether the foliar application of irradiated-chitosan (IC) and MeJ, applied alone or in combination, could augment the active constituents as well as growth, physiological and yield attributes of Catharanthus roseus, which carries anticancer alkaloids, viz. vincristine and vinblastine, in its leaves in addition to various other useful alkaloids. Totally, 5 spray treatments, comprising various aqueous solutions of IC [20, 40, 80 and 160 mg L-1 (Experiment 1)], MeJ (10, 20, 30 and 40 mg L-1 (Experiment 2)] and those of IC+MeJ [40+20, 40+30, 80+20, 80+30, 160+20 and 160+30 mg L-1 (Experiment 3)], were applied at seven days interval. Total leaf-alkaloids content as well as growth, physiological and yield parameters, evaluated at 120 days after sowing, were significantly enhanced by IC application. IC application could not increase the leaf-content of vincristine and vinblastine; nonetheless, it significantly augmented the yield of these alkaloids owing to enhancing the dry mass of leaves per plant. MeJ application, particularly at 30 mg L-1, increased both content (17%) and yield (48%) of total leaf-alkaloids as well as the content and yield of vincristine ( 29 and 63%, respectively) and vinblastine (14 and 44%, respectively) alkaloids, though it significantly decreased most other parameters studied, particularly at higher concentrations (30 and 40 mg L-1 of MeJ). As compared to the control (water-spray treatment), collective application of IC (80 mg L-1) and MeJ (20 mg L-1) resulted in the highest values of most of the parameters studied. However, 80 mg L-1 of IC applied with 30 mg L-1 of MeJ gave the best results for the content and yield of total as well as anticancer leaf-alkaloids (vincristine and vinblastine). Comparing the control, it increased the content and yield of total leaf-alkaloids (37 and 118%, respectively) and those of vincristine (65 and 163%, respectively) and vinblastine (31 and 107%, respectively). Conclusively, the applied technique significantly enhanced the production of total as well as anticancer alkaloids of Catharanthus roseus.

Keywords: anticancer alkaloids (vincristine and vinblastine), catharanthus roseus, irradiated chitosan, methyl jasmonate

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Authors: Emineh Tsegahun Gedif

Abstract:

Zinc oxide nanoparticles (ZnO NPs) have garnered significant attention due to their diverse applications encompassing catalytic, optical, photonic, and antibacterial properties. In this study, we successfully synthesized zinc oxide nanoparticles using a rapid, environmentally benign, and cost-effective method. Neem (Azadirachta indica) leaf extract served as the reducing agent for Zn (NO₃)₂.6H2O solution under optimized conditions (pH = 9). Qualitative screening techniques and FT-IR Spectroscopy confirmed the presence of active biomolecules such as flavonoids, phenolic groups, alkaloids, terpenoids, and tannins within the Neem leaf extract, both before and after reduction. The formation of ZnO NPs was visually evident through a distinct color change from colorless to light yellow. The biosynthesized nanoparticles underwent comprehensive characterization through UV-visible, FT-IR, and XRD spectroscopies. The reduction process proved to be straightforward and user-friendly, with UV-visible spectroscopy demonstrating a surface plasmon resonance (SPR) at 321 nm, unequivocally confirming the ZnO NP formation. X-ray diffraction analysis elucidated the crystal structure, revealing an average particle size of approximately 20 nm using Scherrer's equation based on the line width of the plane. Furthermore, the synthesized zinc oxide nanoparticles were evaluated for their antimicrobial properties against both Gram-positive and Gram-negative bacteria. The results showcased significant inhibitory activity, with the highest zone of inhibition observed against Escherichia coli (15 mm) and comparatively lower activity against Staphylococcus aureus. This research underscores the potential of Neem leaf extract-mediated synthesis of ZnO NPs as an eco-friendly and effective approach for various applications, including antibacterial agents.

Keywords: zinc oxide nanoparticles (ZnO NPs), bioreducing agent, green synthesis, antibacterial activity

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Authors: Linda Blümel, Bettina Bert, Jan Brosda, Heidrun Fink, Melanie Hamann

Abstract:

Age-related cognitive decline can eventually lead to dementia, the most common mental illness in elderly people and an immense challenge for patients, their families and caregivers. Cholinesterase inhibitors constitute the most commonly used antidementia prescription medication. The standardized Ginkgo biloba leaf extract EGb 761® is approved for treating age-associated cognitive impairment and has been shown to improve the quality of life in patients suffering from mild dementia. A clinical trial with 96 Alzheimer´s disease patients indicated that the combined treatment with donepezil and EGb 761® had fewer side effects than donepezil alone. In an animal model of cognitive aging, we compared the effect of combined treatment with EGb 761® or donepezil monotherapy and vehicle. We compared the effect of chronic treatment (15 days of pretreatment) with donepezil (1.5 mg/kg p. o.), EGb 761® (100 mg/kg p. o.), or the combination of the two drugs, or vehicle in 18 – 20 month old male OFA rats. Learning and memory performance were assessed by Morris water maze testing, motor behavior in an open field paradigm. In addition to chronic treatment, the substances were administered orally 30 minutes before testing. Compared to the first day and to the control group, only the combination group showed a significant reduction in latency to reach the hidden platform on the second day of testing. Moreover, from the second day of testing onwards, the donepezil, the EGb 761® and the combination group required less time to reach the hidden platform compared to the first day. The control group did not reach the same latency reduction until day three. There were no effects on motor behavior. These results suggest a superiority of the combined treatment of donepezil with EGb 761® compared to monotherapy.

Keywords: age-related cognitive decline, dementia, ginkgo biloba leaf extract EGb 761®, learning and memory, old rats

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Authors: Marek Maruszczak

Abstract:

Gamified applications have been used successfully in education for years. The rapid development of technologies such as augmented reality and image recognition increases their availability and reduces their prices. Thus, there is an increasing possibility and need for a wide use of such applications in education. The main purpose of this article is to present the effects of work on a mobile application with augmented reality, the aim of which is to motivate tourists to pay more attention to the attractions and increase the likelihood of moving from one attraction to the next while visiting the Palácio Nacional de Sintra in Portugal. Work on the application was carried out together with the employees of Parques de Sintra from 2019 to 2021. Their effect was the preparation of a mobile application using augmented reality and image recognition. The application was tested on the palace premises by both Parques de Sintra employees and tourists visiting Palácio Nacional de Sintra. The collected conclusions allowed for the formulation of good practices and guidelines that can be used when designing gamified apps for the purpose of cultural education.

Keywords: augmented reality, cultural education, gamification, image recognition, mobile games

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Authors: Zunjarrao Kadam, Vikas Minchekar

Abstract:

The facial recognition is an important task in criminal investigation procedure. The security guards-constantly watching the persons-can help to identify the suspected accused. The forensic psychologists are tackled such cases in the criminal justice system. The security personnel may loss their ability to correctly identify the persons due to constant stress while performing the duty. The present study aimed at to identify the effect of experimentally induced stress on facial recognition ability of security personnel’s. For this study 50, security guards from Sangli, Miraj & Jaysingpur city of the Maharashtra States of India were recruited in the experimental study. The randomized two group design was employed to carry out the research. In the initial condition twenty identity card size photographs were shown to both groups. Afterward, artificial stress was induced in the experimental group through the difficultpuzzle-solvingtask in a limited period. In the second condition, both groups were presented earlier photographs with another additional thirty new photographs. The subjects were asked to recognize the photographs which are shown earliest. The analyzed data revealed that control group has ahighest mean score of facial recognition than experimental group. The results were discussed in the present research.

Keywords: experimentally induced stress, facial recognition, cognition, security personnel

Procedia PDF Downloads 237

Authors: Ewuola E. O., Sokunbi O. A., Oyedemi O. M., Sanni K. M

Abstract:

Moringa oleifera leaf has been traditionally used in the local medicine as an ingredient in some herbal formulations for blood purifier, cholesterol reducing agent, immune and reproductive enhancers. Twenty-four pubertal rabbit are divided equally into four groups were administered with varied concentrations of crude extract of the leaves of Moringa oleifera gavage at doses of 2.5ml/kg body weight (BW) in every 48 hours for 63 days. These rabbits were allotted into four treatments and each treatment was replicated six times to investigate the effect of administered crude Moringa oleifera leaf extract (CMOLE) on haematology and reproductive performance of pubertal rabbit does. Four experimental treatments were used. The animals on the control (T1) were administered water only. Rabbits on treatments 2, 3, and 4 were administered 100ml CMOLE/L, 200ml CMOLE/L, and 300ml CMOLE/L, respectively. The does were placed on extract two weeks before mating, five weeks after mating and continued for another two weeks after kindling. Six proven untreated bucks were used for the mating of the twenty-four treated does and these bucks were randomly allotted to the does such that each buck mated at least one treated does in each treatment. The same management practices and experimental diets were given ad libitum to all animals. Blood was sampled from the gestating does at the third trimester for haematological analysis. The haematology results showed that treated rabbits with 100ml CMOLE/L with mean corpuscular volume value of 93.38fl significantly (p < 0.05) higher than those on the control which is water only (82.24fl) but not significantly different from T3 (200ml CMOLE/L) and T4 (300ml CMOLE/L) which had mean values of 91.69fl and 91.49fl, respectively. While the erythrocyte counts, leukocyte counts, haematocrit, haemoglobin concentration, mean corpuscular haemoglobin, mean corpuscular haemoglobin concentration, lymphocyte, neutrophil, monocyte, and eosinophil count were not significantly different across the treatments. For platelets, treated animals on T2 (100ml CMOLE/L) had the highest numerical value of 148.80 x 109/L which was identical with those on T3 (200ml CMOLE/L) with mean value of 141.50x109/L but significantly (p < 0.05) higher than those on T4 (300ml CMOLE/L) with mean value of 135.00 x 109/L and those on the control which had the least mean value of 126.60 x 109/L. The percentage conception rate of the treated animals was higher than those in the control group. The animals administered 300ml CMOLE/L had the apparently highest litter size of 5.75, while gestation length and litter weight tended to decline with increase in CMOLE concentrations The investigation demonstrated the potential effect of crude Moringa oleifera leaf extract on pubertal rabbit does. The administration of up to 300ml crude Moringa oleifera leaf extract per liter did not adversely affect but improved the haematological response and reproductive potential in gestating rabbit does.

Keywords: conception, haematology, moringa leaf extract, rabbit does

Procedia PDF Downloads 482