Search results for: apple leaf disease recognition

Authors: Shiwani Bhatnagar, K. K. Srivastava, Sangeeta Singh, Ameen Ullah Khan, Bundesh Kumar, Lokendra Singh Rathore

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From the instigation of the world medicinal plants are treated as part and parcel of human society to fight against diseases. Azadirachta indica (Neem) a herbal plant has been used as an Indian traditional medicine since ages and its products are acknowledged to solve agricultural, forestry and public health related problems, owing to its beneficial medicinal properties. Each part of the neem tree is known for its medicinal property. Bark & leaf extracts of neem have been used to control leprosy, respiratory disorders, constipation and also as blood purifier and a general health tonic. Neem is still regarded as ' rural community dispensary' in India or a tree for solving medical problems. Use of Neem as pesticides for the management of insect pest of agriculture crops and forestry has been seen as a shift in the use of synthetic pesticides to ecofriendly botanicals. Neem oil and seed extracts possess germicidal and anti-bacterial properties which when sprayed on the plant helps in protecting them from foliage pests. Azadirachtin, the main active ingredient found in neem tree, acts as an insect repellent and antifeedant. However the young plants are susceptible to many insect pest and foliar diseases. Recently, in the avenue plantation, planted by Arid Forest Research Institute, Jodhpur, around the premises of IIT Jodhpur, two years old neem plants were found to be severely infested with tip borer Laspeyresia koenigana (Family: Eucosmidae). The adult moth of L. koenigana lays eggs on the tender shoots and the young larvae tunnel into the shoot and feed inside. A small pinhole can be seen at the entrance point, from where the larva enters in to the stem. The severely attached apical shoots exhibit profuse gum exudation resulting in development of a callus structure. The internal feeding causes the stem to wilt and the leaves to dry up from the tips resulting in growth retardation. Alternaria Leaf spot and blight symptoms were also recorded on these neem plants. For the management of tip borer and Alternaria Leaf spot, foliar spray of monocrotophos @0.05% and Dithane M-45 @ 0.15% and powermin @ 2ml/lit were found efficient in managing the insect pest and foliar disease problem. No Further incidence of pest/diseases was noticed.

Keywords: azadirachta indica, alternaria leaf spot, laspeyresia koenigana, management

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Authors: Kairat Uteulin, Azhar Iskakova, Serik Mukhambetzhanov, Bayan Yesbolayeva, Gabit Bari, Aslan Zheksenbai, Kabyl Zhambakin, Chingis Dzhabykbayev, Vladimir Piven, Izbasar Rakhimbaiev

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To explore the potential for in vitro rapid regeneration of Russian dandelion (Taraxacum kok-saghyz Rodin), different concentrations of 6-Benzylaminopurine (BAP), 2,4-Dichlorophenoxyacetic acid (2.4-D) and BAP combined with Indole-3-acetic acid (IAA) were evaluated for their effects on the induction of somatic embryos from leaf, seed stem and root explants. Different explants were cultured on MS medium supplemented with various concentrations (0, 0.5, 1, 1.5, 2, 2.5 and 3 mg/l) of each kind of hormone. Callus induction percentage, fresh weight, color and texture of the callus were assessed after 14 and 28 days of culture. The optimum medium for the proliferation of embryogenic calli from leaf and root explants was MS supplemented with 2.5 mg/L BAP and 0.5 mg/L 2.4-D. Concentrations of 2.5 mg/L BAP and 1.5 mg/L IAA also had a remarkable effect on root and stem explants. The best concentration to produce callus from stem explants was 0.5 mg/L BAP and 1 mg/L IAA. Results of mean comparison showed that BAP and 2.4-D were more effective on different explants than BAP and IAA. Results of the double staining method proved that somatic embryogenesis occurred in the most concentrations of BAP and 2.4-D. Under microscopic observations, the different developmental stages of the embryos (globular, heart, torpedo and cotyledonary) were revealed together in callus cells, indicating that the most tested hormone combinations were effective for somatic embryogenesis formation in this species. Seed explants formed torpedo and cotyledonary stages faster than leaf and root explants in the most combinations. Most calli from seed explants were cream colored and friable, while calli were compact and light green from leaf and root explants. Some combinations gave direct regeneration and (3 mg/L BAP and 2 mg/L IAA) in seed explants and (0.5 mg/L BAP and 2.5 mg/L IAA) in leaf explants had the highest number of shoots with average of 21 and 27 shoots per callus. The developed protocol established the production of different callus types from seed, leaf, and root explants and plant regeneration through somatic embryogenesis.

Keywords: taraxacum kok-saghyz Rodin, callus, somatic embryogenesis

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Authors: M. Jebali, M. Jemni

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This work is the part of vision based hand gesture recognition system for Natural Human Computer Interface. Hand tracking and segmentation are the primary steps for any hand gesture recognition system. The aim of this paper is to develop robust and efficient hand segmentation algorithm such as an input to another system which attempt to bring the HCI performance nearby the human-human interaction, by modeling an intelligent sign language recognition system based on prediction in the context of dialogue between the system (avatar) and the interlocutor. For the purpose of hand segmentation, an overcoming occlusion approach has been proposed for superior results for detection of hand from an image.

Keywords: HCI, sign language recognition, object tracking, hand segmentation

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Authors: S. Jagadeesh Kumar

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Face detection and recognition is an authoritative technology for image database management, video surveillance, and human computer interface (HCI). Face recognition is a rapidly nascent method, which has been extensively discarded in forensics such as felonious identification, tenable entree, and custodial security. This paper recommends an erudite technique using curvature analysis (CA) that has less false positives incidence, operative in different light environments and confiscates the artifacts that are introduced during image acquisition by ring correction in polar coordinate (RCP) method. This technique affronts mean and median filtering technique to remove the artifacts but it works in polar coordinate during image acquisition. Investigational fallouts for face detection and recognition confirms decent recitation even in diagonal orientation and stance variation.

Keywords: curvature analysis, ring correction in polar coordinate method, face detection, face recognition, human computer interaction

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Authors: Jie Zhao, Meng Su

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Image recognition, as one of the most critical technologies in computer vision, works to help machine-like robotics understand a scene, that is, if deployed appropriately, will trigger the revolution in remote sensing and industry automation. With the developments of AI technologies, there are many prevailing and sophisticated neural networks as technologies developed for image recognition. However, computer vision platforms as hardware, supporting neural networks for image recognition, as crucial as the neural network technologies, need to be more congruently addressed as the research subjects. In contrast, different computer vision platforms are deterministic to leverage the performance of different neural networks for recognition. In this paper, three different computer vision platforms – Jetson Nano(with 4GB), a standalone laptop(with RTX 3000s, using CUDA), and Google Colab (web-based, using GPU) are explored and four prominent neural network architectures (including AlexNet, VGG(16/19), GoogleNet, and ResNet(18/34/50)), are investigated. In the context of pairwise usage between different computer vision platforms and distinctive neural networks, with the merits of recognition accuracy and time efficiency, the performances are evaluated. In the case study using public imageNets, our findings provide a nuanced perspective on optimizing image recognition tasks across Edge-AI platforms, offering guidance on selecting appropriate neural network structures to maximize performance under hardware constraints.

Keywords: alexNet, VGG, googleNet, resNet, Jetson nano, CUDA, COCO-NET, cifar10, imageNet large scale visual recognition challenge (ILSVRC), google colab

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Authors: Ksenia Meshkova

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With increasing amount of multimedia data, it is very important to automate and speed up the process of obtaining meta. This process means not just recognition of some object or its movement, but recognition of the entire scene versus separate frames and having timeline segmentation as a final result. Labeling datasets is time consuming, besides, attributing characteristics to particular scenes is clearly difficult due to their nature. In this article, we will consider autoencoders application to unsupervised scene recognition and clusterization based on interpretable features. Further, we will focus on particular types of auto encoders that relevant to our study. We will take a look at the specificity of deep learning related to information theory and rate-distortion theory and describe the solutions empowering poor interpretability of deep learning in media content processing. As a conclusion, we will present the results of the work of custom framework, based on autoencoders, capable of scene recognition as was deeply studied above, with highlights generation resulted out of this recognition. We will not describe in detail the mathematical description of neural networks work but will clarify the necessary concepts and pay attention to important nuances.

Keywords: neural networks, computer vision, representation learning, autoencoders

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Authors: Sri Rahayu, Supriyatin, Yuli Rahma Dini

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One of the consequences of excess physical activity is the oxidative stress which resulted in damage to blood cells. Oxidative stress condition can be reduced by an exogenous antioxidant. The natural exogenous antioxidant can be extracted from Manggong bamboo (Gigantochloa manggong). This research was aim to evaluate the effect of physical exercise and Manggong bamboo (Gigantochloa manggong) leaf extract on blood profile of rats. This research was conducted in July 2013 to May 2014 using experimental method with completely randomized design (CRD) with two factors, physical exercise and Manggong bamboo leaf extract. The rats blood profile to be measured were the level of erythrocyte cells, leucocyte cells and hemoglobin. Data were analyzed with parametric statistical 2-way ANOVA test (α = 0.05). Manggong bamboo leaf extract was non toxic and contained flavonoid, triterpenoid, saponin and alkaloid. There was an effect of physical exercise and manggong bamboo leaf extract on blood profile of rats. Data obtained on physical activity, giving erythrocyte cells (2.5 million/µl) and hemoglobin (12,42g/dL) declined compared to the number of leucocyte cells increases (6,500cells/L). Extract treatment was increased the erythrocytes (5,13 million/µl) and hemoglobin level (14,72 g/dL.) while the leukocytes level were decreased (1.591,67 cells/L). The extract and physical activity treatment showed an increase in erythrocytes (2,96 million/µl) and hemoglobin (14,3 g/dL) but decrease the number of leukocytes (1.291,67 cells/L). The conclusion was that physical activity and Manggong bamboo leafs extract gaves effect on the blood profile of white rat.

Keywords: antioxidant, blood profile of rats, Manggong bamboo leaf extract, leukocytes

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Authors: Sultan Mahmud, Qamar Zaman, Travis Esau, Young Chang

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Strawberry powdery mildew (PM) is a serious disease that has a significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVMs) and k-nearest neighbors (kNNs). The methodology of the proposed study is based on image processing which is composed of five main steps including image acquisition, pre-processing, segmentation, features extraction and classification. Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM (Sphaerotheca macularis) disease under artificial cloud lighting condition. Colour thresholding was utilized to segment all images before textural analysis. Colour co-occurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to a physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The normalized feature data were utilized for training and validation, respectively, using developed classifiers. The classifiers have experimented with internal, external and cross-validations. The best classifier was selected based on their performance and accuracy. Experimental results suggested that SVMs classifier showed 98.33%, 85.33%, 87.33%, 93.33% and 95.0% of accuracy on internal, external-I, external-II, 4-fold cross and 5-fold cross-validation, respectively. Whereas, kNNs results represented 90.0%, 72.00%, 74.66%, 89.33% and 90.3% of classification accuracy, respectively. The outcome of this study demonstrated that SVMs classified PM disease with a highest overall accuracy of 91.86% and 1.1211 seconds of processing time. Therefore, overall results concluded that the proposed study can significantly support an accurate and automatic identification and recognition of strawberry PM disease with SVMs classifier.

Keywords: powdery mildew, image processing, textural analysis, color co-occurrence matrix, support vector machines, k-nearest neighbors

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Authors: Anil F. Felek, Mehmet M. Ozcan, Faruk Akyazi

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Volatile oils of medicinal and aromatic plants are important for managing nematological problems in agriculture. In present study, volatile oils extracted from five medicinal and aromatic plants including Origanum onites (flower+steam+leaf), Salvia officinalis (leaf), Lippia citriodora (leaf+seed), Mentha spicata (leaf) and Mentha longifolia (leaf) were tested for egg hatching inhibition activity against root-knot nematode Meloidogyne hapla under laboratory conditions. The essential oils were extracted using water distillation method with a Clevenger system. For the homogenisation process of the oils, 2% gum arabic solution was used and 4 µl oils was added into 1ml filtered gum arabic solution to prepare the last stock solution. 5 ml of stock solution and 1 ml of M. hapla egg suspension (about 100 eggs) were added into petri dishes. Gum arabic solution was used as control. Seven days after exposure to oils at room temperature (26±2 °C), the cumulative hatched and unhatched eggs were counted under 40X inverted light microscope and Abbott’s formula was used to calculate egg hatching inhibition rates. As a result, the highest inhibition rate was found as 54% for O. onites. In addition, the other inhibition rates varied as 31.4%, 21.6%, 23.8%, 25.67% for the other plants, S. officinalis, M. longifolia, M. spicata and L. citriodora, respectively. Carvacrol was found as the main component (68.8%) of O. onites followed by Thujone 27.77% for S. officinalis, I-Menthone 76.92% for M. longifolia, Carvone 27.05% for M. spicata and Citral 19.32% for L. citriodora.

Keywords: egg hatching, Meloidogyne hapla, medicinal and aromatic plants, root-knot nematodes, volatile oils

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Authors: Alia Ali, Azeem Taj, Muhammed Joher Amin, Farrukh Iqbal, Zafar Iqbal

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Background: Hypertension is commonly found in patients with Diabetic Kidney Disease (DKD). Microalbuminuria is the first clinical sign of involvement of kidneys in patients with type 2 diabetes. Uncontrolled hypertension induces a higher risk of cardiovascular events, including death, increasing proteinuria and progression to kidney disease. Objectives: To determine the correlation between microalbuminuria and hypertension and their association with other risk factors in type 2 diabetic patients. Methods: One hundred and thirteen type 2 diabetic patients were screened for microalbuminuria and raised blood pressure, attending the diabetic clinic of Shaikh Zayed Hospital, Lahore, Pakistan. The study was conducted from November 2012 to June 2013. Results: Patients were divided into two groups. Group 1, those with normoalbuminuria (n=63) and Group 2, those having microalbuminuria (n=50). Group 2 patients showed higher blood pressure values as compared to Group 1. The results were statistically significant and showed poor glycemic control as a contributing risk factor. Conclusion: The study concluded that there is high frequency of hypertension among type 2 diabetics but still much higher among those having microalbuminuria. So, early recognition of renal dysfunction through detection of microalbuminuria and to start treatment without any delay will confer future protection from end-stage renal disease as well as hypertension and its complications in type 2 diabetic patients.

Keywords: hypertension, microalbuminuria, diabetic kidney disease, type 2 Diabetes mellitus

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Authors: Yao-Hong Tsai

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This paper presents a weighted approach to unconstrained iris recognition. Nowadays, commercial systems are usually characterized by strong acquisition constraints based on the subject’s cooperation. However, it is not always achievable for real scenarios in our daily life. Researchers have been focused on reducing these constraints and maintaining the performance of the system by new techniques at the same time. With large variation in the environment, there are two main improvements to develop the proposed iris recognition system. For solving extremely uneven lighting condition, statistic based illumination normalization is first used on eye region to increase the accuracy of iris feature. The detection of the iris image is based on Adaboost algorithm. Secondly, the weighted approach is designed by Gaussian functions according to the distance to the center of the iris. Furthermore, local binary pattern (LBP) histogram is then applied to texture classification with the weight. Experiment showed that the proposed system provided users a more flexible and feasible way to interact with the verification system through iris recognition.

Keywords: authentication, iris recognition, adaboost, local binary pattern

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Authors: Daniel O. Wasonga, Jouko Kleemola, Laura Alakukku, Pirjo Makela

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Cassava (Manihot esculenta Crantz) is a major food crop for millions of people in the tropics. Growth and yield of cassava in the arid-tropics are seriously constrained by intermittent water deficit and low soil K content. Therefore, experiments were conducted to investigate the effects of interaction between water deficit and K fertigation on growth and yield response of biofortified cassava at early growth phase. Yellow cassava cultivar was grown under controlled glasshouse conditions in 5-L pots containing 1.7 kg of pre-fertilized potting mix. Plants were watered daily for 30 days after planting. Treatments were three watering levels (30%, severe water deficit; 60%, mild water deficit; 100%, well-watered), on which K (0.01, 1, 4, 16 and 32 mM) was split. Plants were harvested at 90 days after planting. Leaf area was smallest in plants grown with 30% watering and 0.01 mM K, and largest in plants grown with 100% watering and 32 mM K. Leaf, root, and total dry mass decreased in water-stressed plants. However, dry mass was markedly higher when plants were grown with 16 mM K under all watering levels in comparison to other K concentrations. The highest leaf, root and total dry mass were in plants with 100% watering and 16 mM K. In conclusion, K improved the growth of plants under water deficit and thus, K application on soils with low moisture and low K may improve the productivity of cassava.

Keywords: dry mass, interaction, leaf area, Manihot esculenta

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Authors: Preshanthan Moodley, E. B. Gueguim-Kana

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The objective of this study was to develop a method to pretreat sugarcane leaf waste using microwave-assisted (MA) inorganic salt. The effects of process parameters of salt concentration, microwave power intensity and pretreatment time on reducing sugar yield from enzymatically hydrolysed sugarcane leaf waste were investigated. Pretreatment models based on MA-NaCl, MA-ZnCl2 and MA-FeCl3 were developed. Maximum reducing sugar yield of 0.406 g/g was obtained with 2 M FeCl3 at 700W for 3.5 min. Scanning electron microscopy (SEM) and Fourier Transform Infrared analysis (FTIR) showed major changes in lignocellulosic structure after MA-FeCl3 pretreatment with 71.5 % hemicellulose solubilization. This pretreatment was further assessed on sorghum leaves and Napier grass under optimal MA-FeCl3 conditions. A 2 fold and 3.1-fold increase in sugar yield respectively were observed compared to previous reports. This pretreatment was highly effective for enhancing enzymatic saccharification of lignocellulosic biomass.

Keywords: acid, pretreatment, salt, sugarcane leaves

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Authors: Zakirul Islam, Yugo Kumokawa, Quoc Thinh Tran, Motoki Kubo

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Clubroot is a disease of cruciferous plant caused by soil born pathogen Plasmodiophora brassicae and can significantly limit the production through rapid spreading. The present study was designed to investigate the effect of cultivation practices (chemical and organic soils) on clubroot disease development in Brassica rapa. Disease index and root bacterial composition were investigated for both chemical and organic soils. The bacterial biomass and diversity in organic soil were higher than those in chemical soil. Disease severity was distinct for two different cultivation methods. The number of endophytic bacteria decreased in the infected root for both soils. The increased number of endophytic bacterial number led to reduce the proliferation of pathogen spore inside the root and thus reduced the disease severity in organic plants.

Keywords: clubroot disease, bacterial biomass, root infection, disease index, chemical cultivation, organic cultivation

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Authors: Fathia Ehmouda Zaid, Reim Abudelnbi

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Cardiovascular disease is a major cause of morbidity and mortality in patients with systemic lupus erythematosus (SLE). Patients and method: Cross-section study (68) patients diagnosed as systemic lupus erythematosus (SLE), who visited the outpatient clinic of rheumatology, these patients were interviewed with a structured questionnaire about their past and current clinically for presence of Cardiovascular disease in systemic lupus and use SLEDAI, specific tests [ECG –ECHO –CXRAY] the data are analyzed statistically by Pearson's correlation coefficient was calculated and statistical significance was defined as P< 0.05,during period (2013-2014). Objective: Estimation Cardiovascular disease manifestation of systemic lupus erythematosus, correlation with disease activity, morbidity, and mortality. Result: (68) Patients diagnosed as systemic lupus erythematosus' age range from (18-48 years), M=(13±29Y), Sex were female 66/68 (97.1%), male 2/68 (2.9%),duration of disease range[1-15year], M =[7±8y], we found Cardiovascular disease manifestation of systemic lupus erythematosus 32/68 (47.1%), correlation with disease activity use SLEDAI,(r= 476** p=0.000),Morbidity,(r= .554**; p=0.000) and mortality (r=.181; p=.139), Cardiovascular disease manifestations of systemic lupus erythematosus are pericarditis 8/68 (11.8%), pericardial effusion 6/68 (8.8%), myocarditis 4/68 (5.9 %), valvular lesions (endocarditis) 1/68 (1.5%), pulmonary hypertension (PAH) 12/68 (17.6%), coronary artery disease 1/68 (1.5%), none of patients have conduction abnormalities involvement. Correlation with disease activity use SLEDAI, pericarditis (r= .210, p=.086), pericardial effusion (r= 0.079, p=.520), myocarditis (r= 272*, p=.027), valvular lesions (endocarditis) (r= .112, p= .362), pulmonary hypertension (PAH) (r= .257*, p=.035) and coronary artery disease (r=.075, p=.544) correlation between cardiovascular disease manifestations of systemic lupus erythematosus and specific organ involvement we found Mucocutaneous (r=.091 p= .459), musculoskeletal (MSK) (r=.110 p=.373), Renal disease (r=.278*, p=.022), neurologic disease (r=.085, p=.489) and Hematologic disease (r=-.264*, p=.030). Conclusion: Cardiovascular manifestation is more frequent symptoms with systemic lupus erythematosus (SLE) is 47 % correlation with disease activity and morbidity but not with mortality. Recommendations: Focus research to evaluation and an adequate assessment of cardiovascular complications on the morbidity and mortality of the patients with SLE are still required.

Keywords: cardiovascular disease, systemic lupus erythematosus, disease activity, mortality

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Authors: Berrin Şentürk

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In this study, due to the recurrence of bovine tuberculosis, in the same areas, the risk factors for the disease were determined and evaluated at the local level. This study was carried out in 32 farms where the disease was detected in the district and center of Samsun province in 2014. Predetermined risk factors, such as farm, environmental and economic risks, were investigated with the survey method. It was predetermined that risks in the three groups are similar to the risk variables of the disease on the global scale. These risk factors that increase the susceptibility of the infection must be understood by the herd owners. The risk-based contagious disease management system approach should be applied for bovine tuberculosis by farmers, animal health professionals and public and private sector decision makers.

Keywords: bovine tuberculosis, disease management, control, outbreak, risk analysis

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Authors: Yao-Hong Tsai

Abstract:

This paper presents an efficient fusion algorithm for iris images to generate stable feature for recognition in unconstrained environment. Recently, iris recognition systems are focused on real scenarios in our daily life without the subject’s cooperation. Under large variation in the environment, the objective of this paper is to combine information from multiple images of the same iris. The result of image fusion is a new image which is more stable for further iris recognition than each original noise iris image. A wavelet-based approach for multi-resolution image fusion is applied in the fusion process. The detection of the iris image is based on Adaboost algorithm and then local binary pattern (LBP) histogram is then applied to texture classification with the weighting scheme. Experiment showed that the generated features from the proposed fusion algorithm can improve the performance for verification system through iris recognition.

Keywords: image fusion, iris recognition, local binary pattern, wavelet

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Authors: Steffy Maria Joseph, Abdu Rahiman V, Abdul Hameed K. M.

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Online handwritten character recognition is a challenging field in Artificial Intelligence. The classification success rate of current techniques decreases when the dataset involves similarity and complexity in stroke styles, number of strokes and stroke characteristics variations. Malayalam is a complex south indian language spoken by about 35 million people especially in Kerala and Lakshadweep islands. In this paper, we consider the significant feature extraction for the similar stroke styles of Malayalam. This extracted feature set are suitable for the recognition of other handwritten south indian languages like Tamil, Telugu and Kannada. A classification scheme based on support vector machines (SVM) is proposed to improve the accuracy in classification and recognition of online malayalam handwritten characters. SVM Classifiers are the best for real world applications. The contribution of various features towards the accuracy in recognition is analysed. Performance for different kernels of SVM are also studied. A graphical user interface has developed for reading and displaying the character. Different writing styles are taken for each of the 44 alphabets. Various features are extracted and used for classification after the preprocessing of input data samples. Highest recognition accuracy of 97% is obtained experimentally at the best feature combination with polynomial kernel in SVM.

Keywords: SVM, matlab, malayalam, South Indian scripts, onlinehandwritten character recognition

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Authors: Xiaoqi Jia, Qing Zhu, Hao Zhang, Su Yang

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A gender recognition system is able to tell the gender of the given person through a few of frontal facial images. An effective gender recognition approach enables to improve the performance of many other applications, including security monitoring, human-computer interaction, image or video retrieval and so on. In this paper, we present an effective method for gender classification task in frontal facial images based on deep belief networks (DBNs), which can pre-train model and improve accuracy a little bit. Our experiments have shown that the pre-training method with DBNs for gender classification task is feasible and achieves a little improvement of accuracy on FERET and CAS-PEAL-R1 facial datasets.

Keywords: gender recognition, beep belief net-works, semi-supervised learning, greedy-layer wise RBMs

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Authors: G. E. Forcados, M. L. Shu, C. N. Chinyere

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Acalypha wilkesiana is a medicinal plant commonly used in most parts of West Africa as a decoction in treating several human diseases. Existing literature on its toxicity is predominantly on the organic extracts in contrast to the routine use of hot aqueous extracts as decoction. The aim of this study was to examine the phytochemical profile and sub-acute toxicity of A. wilkesiana leaf extracts in albino rats. Three groups of 8 experimental rats each were administered 300 mg/kg, 600 mg/kg and 1200 mg/kg body weight per day for 14 days while a fourth (control) group took tap-water. On day 15, the rats were sacrificed, and blood collected. Biochemical and hematological parameters were analysed and histopathological examination of liver and kidney were performed. There was significant increase (p<0.05) in the levels of some biochemical parameters (AST, ALT, creatinine, urea) in all the test groups compared to control. Histopathological examination of the liver revealed centrilobular degeneration and necrosis with sinusoidal dilatation as well as polymorphonuclear and mononuclear infiltration, likewise severe glomerular and tubular degeneration and necrosis with hemorrhage in the kidney at all dose levels. The results from this study suggest that aqueous leaf extract of A. wilkesiana is hepatotoxic and nephrotoxic at dose levels of 300 mg/kg and above. Therefore, precautionary measures are necessary for home use of the leaf extract of A. wilkesiana.

Keywords: acute toxicity, A. wilkesiana, aqeous extract, albino rats, biochemical and haematological parameters, histopathological examination

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Authors: Nazmul Haque, Syeda Tasnuva Maria

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Sheehan's Syndrome (SS), also known as postpartum hypopituitarism, is a rare but potentially serious condition resulting from ischemic necrosis of the pituitary gland, often occurring during or after childbirth. This syndrome is characterized by hypopituitarism, leading to deficiencies in various hormones produced by the pituitary gland. The primary cause is typically severe postpartum hemorrhage, leading to inadequate blood supply and subsequent necrosis of the pituitary tissue. This chronic hypopituitarism sometimes plays the role of premature atherosclerosis, which may lead to cardiovascular disease. This abstract provides a comprehensive overview of Sheehan's Syndrome with ischaemic heart disease, encompassing its pathophysiology, clinical manifestations, and current management strategies. The disorder presents a wide spectrum of symptoms, including chest pain, fatigue, amenorrhea, lactation failure, hypothyroidism, and adrenal insufficiency. Timely diagnosis is crucial, as delayed recognition can lead to complications and long-term health consequences. We herein report a patient complaining of chronic fatigue symptoms, aggressiveness, chest pain, and breathlessness with repeated LOC that were diagnosed with SS with IHD. The patient was treated with antiplatelet, antianginal, steroids, and hormone replacement with marked improvement in his overall condition.

Keywords: ischaemic heart disease, Sheehan's syndrome, post-partum haemorrhage, pituitary gland

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Authors: Mirnawati, G. Ciptaan, Ferawati

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This study aims to improve the quality of the cassava peel-leaf mixture (CPLM) through fermentation with Rhizopus oligosporusas poultry ration. This research is an experimental study using a completely randomized design (CRD) with four treatments and five replications. The treatments were cassava peel-leaf mixture (CPLM) fermented with Rhizopus oligosporus. The treatments were a combination of cassava peel and leaves with the ratio of; A (9:1), B (8:2), C (7:3), and D (6:4). The observed variables were protease enzyme activity, crude protein, crude fiber, nitrogen retention, digestibility of crude fiber, and metabolic energy. The results of the diversity analysis showed that there was a very significant (p < 0.01) effect on protease activity, crude protein, crude fiber, nitrogen retention, digestibility of crude fiber, and energy metabolism of fermented CPLM. Based on the results of the study, it can be concluded that CPLM (6:4) fermented with Rhizopus oligosporus gave the best results seen from protease activity 7,25 U/ml, 21.23% crude protein, 19.80% crude fiber, 59.65% nitrogen retention, 62.99% crude fiber digestibility and metabolic energy 2671 Kcal/kg.

Keywords: quality, Casava peel-leaf mixture, fermentation, Rhizopus oligosporus

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Authors: Rahul Mohite, Lahcen Ouarbya

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This paper focuses on the interplay between humans and computer systems and the ability of these systems to understand and respond to human emotions, including non-verbal communication. Current emotion recognition systems are based solely on either facial or verbal expressions. The limitation of these systems is that it requires large training data sets. The paper proposes a system for recognizing human emotions that combines both speech and emotion recognition. The system utilizes advanced techniques such as deep learning and image recognition to identify facial expressions and comprehend emotions. The results show that the proposed system, based on the combination of facial expression and speech, outperforms existing ones, which are based solely either on facial or verbal expressions. The proposed system detects human emotion with an accuracy of 86%, whereas the existing systems have an accuracy of 70% using verbal expression only and 76% using facial expression only. In this paper, the increasing significance and demand for facial recognition technology in emotion recognition are also discussed.

Keywords: facial reputation, expression reputation, deep gaining knowledge of, photo reputation, facial technology, sign processing, photo type

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Authors: Larry Powell, Seth Polsley, Drew Casey, Tracy Hammond

Abstract:

Human activity recognition (HAR) systems have shown positive performance when recognizing repetitive activities like walking, running, and sleeping. Water-based activities are a reasonably new area for activity recognition. However, water-based activity recognition has largely focused on supporting the elite and competitive swimming population, which already has amazing coordination and proper form. Beginner swimmers are not perfect, and activity recognition needs to support the individual motions to help beginners. Activity recognition algorithms are traditionally built around short segments of timed sensor data. Using a time window input can cause performance issues in the machine learning model. The window’s size can be too small or large, requiring careful tuning and precise data segmentation. In this work, we present a method that uses a time window as the initial segmentation, then separates the data based on the change in the sensor value. Our system uses a multi-phase segmentation method that pulls all peaks and valleys for each axis of an accelerometer placed on the swimmer’s lower back. This results in high recognition performance using leave-one-subject-out validation on our study with 20 beginner swimmers, with our model optimized from our final dataset resulting in an F-Score of 0.95.

Keywords: time window, peak/valley segmentation, feature extraction, beginner swimming, activity recognition

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Authors: Priya Bajaj, Baby Tabassum

Abstract:

Arsenic is a poisonous metalloid, naturally occurring in soil, air, rocks and ground water. This dreadful metalloid commonly exists as inorganic compound, arsenic trioxide. WHO permitted maximum limit for arsenic in water is 0.01 mg/L, but some affected areas show ground water level of arsenic up to 3 mg/L even. Ground water arsenic pollution has created a number of health problems, viz. keratosis, melanosis, lesions and even skin cancers. The key objective of our nested study was to characterize arsenic induced hepatotoxicity and to find out some herbal protection against it. For the purpose, we selected albino rat (Rattus norvegicus) as model for arsenic induced liver injury and wild turmeric (Curcuma aromatica) leaf extract as remedy for it. The study was performed at acute (1 day) and subacute (7, 14 & 21 days) levels. The LD50 estimated for arsenic trioxide was 14.98 mg/kg body weight. In our investigation, we observed a significant restoration of altered hepatic lipid, cholesterol, protein and glycogen contents as well as liver weight, body-weight and hepato-somatic index by Curcuma aromatica leaf extract before arsenic intoxication. The results reveal excellent protective efficacy of Curcuma aromatica leaf extract that further can be exploited in remediation programme in heavy metal affected areas.

Keywords: arsenic, Curcuma aromatica, glycogen, lipids

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Authors: Qin Long, Li Xiaoge

Abstract:

The Knowledge Graphs have now become a new form of knowledge representation. However, there is no consensus in regard to a plausible and definition of entities and relationships in the domain-specific knowledge graph. Further, in conjunction with several limitations and deficiencies, various domain-specific entities and relationships recognition approaches are far from perfect. Specifically, named entity recognition in Chinese domain is a critical task for the natural language process applications. However, a bottleneck problem with Chinese named entity recognition in new domains is the lack of annotated data. To address this challenge, a domain distant supervised named entity recognition framework is proposed. The framework is divided into two stages: first, the distant supervised corpus is generated based on the entity linking model of graph attention neural network; secondly, the generated corpus is trained as the input of the distant supervised named entity recognition model to train to obtain named entities. The link model is verified in the ccks2019 entity link corpus, and the F1 value is 2% higher than that of the benchmark method. The re-pre-trained BERT language model is added to the benchmark method, and the results show that it is more suitable for distant supervised named entity recognition tasks. Finally, it is applied in the computer field, and the results show that this framework can obtain domain named entities.

Keywords: distant named entity recognition, entity linking, knowledge graph, graph attention neural network

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Authors: Kaiyi Zhang, Wenlong Li, Haicheng Li, Yifei Luo, Zheng Li, Xiaoshi Wang, Xiaodong Chen

Abstract:

Plant wearable sensors facilitate the real-time monitoring of plant physiological status. In situ monitoring of the plant chlorophyll content over days could provide valuable information on the photosynthetic capacity, nitrogen content, and general plant health. However, it cannot be achieved by current chlorophyll measuring methods. Here, a miniaturized and plant-wearable chlorophyll meter was developed for rapid, non-destructive, in situ, and long-term chlorophyll monitoring. This reflectance-based chlorophyll sensor with 1.5 mm thickness and 0.2 g weight (1000 times lighter than the commercial chlorophyll meter), includes a light emitting diode (LED) and two symmetric photodetectors (PDs) on a flexible substrate and is patched onto the leaf upper epidermis with a conformal light guiding layer. A chlorophyll content index (CCI) calculated based on this sensor shows a better linear relationship with the leaf chlorophyll content (r² > 0.9) than the traditional chlorophyll meter. This meter can wirelessly communicate with a smartphone to monitor the leaf chlorophyll change under various stresses and indicate the unhealthy status of plants for long-term application of plants under various stresses earlier than chlorophyll meter and naked-eye observation. This wearable chlorophyll sensing patch is promising in smart and precision agriculture.

Keywords: plant wearable sensors, reflectance-based measurements, chlorophyll content monitoring, smart agriculture

Procedia PDF Downloads 57

Authors: Gül Çevik

Abstract:

This paper summarizes the work conducted to assess the root cause of the failure of a medium commercial vehicle leaf spring failed in service. Macro- and micro-fractographic analyses by scanning electron microscope as well as material verification tests were conducted in order to understand the failure mechanisms and root cause of the failure. Findings from the fractographic analyses indicated that failure mechanism is fatigue. Crack initiation was identified to have occurred from a point on the top surface near to the front face and to the left side. Two other crack initiation points were also observed, however, these cracks did not propagate. The propagation mode of the fatigue crack revealed that the cyclic loads resulting in crack initiation and propagation were unidirectional bending. Fractographic analyses have also showed that the root cause of the fatigue crack initiation and propagation was loading the part above design stress. Material properties of the part were also verified by chemical composition analysis, microstructural analysis by optical microscopy and hardness tests.

Keywords: leaf spring, failure analysis, fatigue, fractography

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Authors: Hafiza Javaria Ashraf, Asim Abbasi, Muhammad Hussnain Babar, Muhammad Sufyan

Abstract:

Brevicoryne brassicae (Aphid) is not only the major biotic constraint of rapeseed crop but also transmits 20 different viral pathogens that cause diseases in crucifers. Aphids cause major losses to rapeseed by stunting growth and yield, with real damage being contamination of harvested heads. The misuse of pesticides has led to tremendous economic losses and hazards to human health and environmental pollution. Thus, newer approaches for pest control are continuously being sought. The naturally occurring, biologically active plant-based products seem to have a prominent role in the development of future commercial pesticides not only for increased productivity but their eco-friendly nature. The present experiment was carried out in Research Area of Ayub Agriculture Research Institute, Faisalabad to check the efficacy of different botanicals against rapeseed aphid. The tested botanicals were, neem seed extract, neem leaf extract, dathora seed extract, kaner leaf extract and aak leaf extract. Insecticide, advantage 20 EC served as the positive control in the experiment. Data was recorded before and after 1, 3 and 7 days of treatment application. The results of the experiment revealed that neem seed extract exhibited maximum mortality (48.42%) followed by dathora (45.54%) and kaner leaf extract (40.29%) after 7 days of treatment application. However minimum mortality i.e. 26.64% was observed in case of aak leaf extract. Advantage encountered maximum mortality i.e. 86.14%. All treatments caused maximum mortality after 7 days of treatment application. In case of pollinators maximum population reduction was observed in case of insecticide (74.29%) while minimum reduction was observed in neem leaf extract (11.57%). Hence it was concluded that unlike insecticides, plant based products can be a better option for regulating pests and conserving beneficial insect fauna.

Keywords: Aphid, mortality, plant based, pollinators

Procedia PDF Downloads 195

Authors: Cajethan U. Ugwuoke, Hyginus O. Omeje, Emmanuel C. Osinem

Abstract:

The study was carried out to determine the effects of Moringa oleifera leaf powder additive on the feed intake and average weight of pullets. A completely Randomized Design (CRD) was adopted for the study. On the procedure of the experiment, 240 chicks were randomly selected from 252 Isa Brown day-old chicks. The chicks were equally randomly allotted to 12 pens with 20 chicks each. The pens were randomly assigned to four different treatment groups with three replicates each. T1 was fed with control feed while T2, T3, and T4 were fed with 2.5%, 5% and 7.5% Moringa oleifera leaf powder fortified feed respectively. The chicks were fed with uniform feed up to week four. From week five, experimental feeds were given to the pullet up to 20 weeks of age. The birds were placed on the same treatment conditions except different experimental feeds given to different groups. Data on the feed intake were collected daily while the average weight of the pullets was collected weekly using weighing scale. Data collected were analyzed using mean, bar charts and Analysis of Variance. The layers fed with control feed consumed the highest amount of feed in most of the weeks under study. The average weights of all the treatment groups were equal from week 1 to week 4. Little variation in average weight started in week 5 with T2 topping the groups. However, there was no statistically significant difference (p>0.05) in the feed intake and average weight of layers fed with different inclusion rates of Moringa oleifera leaf powder in feeds.

Keywords: average weight, feed intake, Moringa oleifera, pullets

Procedia PDF Downloads 163