Search results for: natural plant recognition

Authors: Almagul Assainova , Dariya Abykenova, Liudmila Goncharenko, Sergey Sybachin, Saule Rakhimova, Abay Aman

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The recognition of a handwritten Kazakh text is a relevant objective today for the digitization of materials. The study presents a model of a hybrid neural network for handwriting recognition, which includes a convolutional neural network and a multi-layer perceptron. Each network includes 1024 input neurons and 42 output neurons. The model is implemented in the program, written in the Python programming language using the EMNIST database, NumPy, Keras, and Tensorflow modules. The neural network training of such specific letters of the Kazakh alphabet as ә, ғ, қ, ң, ө, ұ, ү, h, і was conducted. The neural network model and the program created on its basis can be used in electronic document management systems to digitize the Kazakh text.

Keywords: handwriting recognition system, image recognition, Kazakh font, machine learning, neural networks

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Authors: Aleksandra Zysk, Pawel Badura

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Recognizing and controlling vocal registers during singing is a difficult task for beginner vocalist. It requires among others identifying which part of natural resonators is being used when a sound propagates through the body. Thus, an application has been designed allowing for sound recording, automatic vocal register recognition (VRR), and a graphical user interface providing real-time visualization of the signal and recognition results. Six spectral features are determined for each time frame and passed to the support vector machine classifier yielding a binary decision on the head or chest register assignment of the segment. The classification training and testing data have been recorded by ten professional female singers (soprano, aged 19-29) performing sounds for both chest and head register. The classification accuracy exceeded 93% in each of various validation schemes. Apart from a hard two-class clustering, the support vector classifier returns also information on the distance between particular feature vector and the discrimination hyperplane in a feature space. Such an information reflects the level of certainty of the vocal register classification in a fuzzy way. Thus, the designed recognition and training application is able to assess and visualize the continuous trend in singing in a user-friendly graphical mode providing an easy way to control the vocal emission.

Keywords: classification, singing, spectral analysis, vocal emission, vocal register

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Authors: Rakkrit Duangsoithong, Jermphiphut Jaruenpunyasak, Alba Garcia

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The use of foot recognition can be applied in many medical fields such as the gait pattern analysis and the knee exercises of patients in rehabilitation. Generally, a camera-based foot recognition system is intended to capture a patient image in a controlled room and background to recognize the foot in the limited views. However, this system can be inconvenient to monitor the knee exercises at home. In order to overcome these problems, this paper proposes to use the deep learning method using Convolutional Neural Networks (CNNs) for foot recognition. The results are compared with the traditional classification method using LBP and HOG features with kNN and SVM classifiers. According to the results, deep learning method provides better accuracy but with higher complexity to recognize the foot images from online databases than the traditional classification method.

Keywords: foot recognition, deep learning, knee rehabilitation, convolutional neural network

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Authors: Jain Jyoti, Jain Shorab, Sinha Shishir

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In the field of material engineering, composites are in great concern for their nonbiodegradability and their cost. In order to reduce its cost and weight, plant derived fibers witnessed miraculous triumph. Plant fibers can be of different types like seed fibers, blast fibers, leaf fibers, etc. Composites can be reinforced with exclusively one type of natural fiber or also can be combined with two or more different types of natural or synthetic fibers to boost up their specific properties. Among all natural fibers, wheat straw, bagasse, kenaf, pineapple leaf, banana, coir, ramie, flax, etc. pineapple leaf fibers have very good mechanical properties. Being hydrophilic in nature, pineapple leaf fibers have very less affinity towards all types of polymer matrixes like HDPE, LDPE, PET, epoxy, etc. Surface treatments like alkaline treatment in different concentrations were conducted to improve its adhesion and compatibility towards hydrophobic polymer matrix i.e. epoxy resin. Pineapple leaf fiber epoxy composites have been prepared using hand layup method. Effect of fiber loading and surface treatments have been studied for different mechanical properties i.e. tensile strength, flexural strength and impact properties of pineapple leaf fiber composites. Analysis of fiber morphology has also been studied using FTIR, XRD. Scanning electron microscopy has also been used to study and compare the morphology of untreated and treated fibers. Also, the fracture surface has been reviewed comparing the reported literature of other eminent researchers of this field.

Keywords: composite, mechanical, natural fiber, pineapple leaf fiber

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Authors: Belaynesh Chekol, Numan Çelebi

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The main purpose of this work is to recognize individual characters extracted from natural scene images using scale invariant feature transform (SIFT) features as an input to K-nearest neighbor (KNN); a classification learner algorithm. For this task, 1,068 and 78 images of English alphabet characters taken from Chars74k data set is used to train and test the classifier respectively. For each character image, We have generated describing features by using SIFT algorithm. This set of features is fed to the learner so that it can recognize and label new images of English characters. Two types of KNN (fine KNN and weighted KNN) were trained and the resulted classification accuracy is 56.9% and 56.5% respectively. The training time taken was the same for both fine and weighted KNN.

Keywords: character recognition, KNN, natural scene image, SIFT

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Authors: Jinsiang Shaw, Pik-Hoe Chen

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This paper aims to integrate human recognition, motion recognition, and object tracking technologies without requiring a pre-training database model for motion recognition or the unknown object itself. Furthermore, it can simultaneously track multiple users and multiple objects. Unlike other existing human motion recognition methods, our approach employs a rule-based condition method to determine if a user hand is approaching or departing an object. It uses a background subtraction method to separate the human and object from the background, and employs behavior features to effectively interpret human object-grabbing actions. With an object’s histogram characteristics, we are able to isolate and track it using back projection. Hence, a moving object trajectory can be recorded and the object itself can be located. This particular technique can be used in a camera surveillance system in a shopping area to perform real-time intelligent surveillance, thus preventing theft. Experimental results verify the validity of the developed surveillance algorithm with an accuracy of 83% for shoplifting detection.

Keywords: Automatic Tracking, Back Projection, Motion Recognition, Shoplifting

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Authors: Hasan Sungur, Evrim Baran, Benjamin Ahn, Aliye Karabulut Ilgu, Chris Rehmann, Cassandra Rutherford

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Engineering identity contributes to the professional and educational persistence of women engineers. A crucial factor contributing to the development of the engineering identity is recognition. Those without adequate recognition often do not succeed in positively building their identities. This research draws on Honneth’s recognition theory to identify factors impacting women civil engineers’ feelings of recognition as civil engineers. A survey was composed and distributed to 330 female alumni who graduated from the Department of Civil, Construction, and Environmental Engineering at Iowa State University in the last ten years. The survey items include demographics, perceptions of the identity of civil engineering, and factors that influence the recognition of civil engineering identities, such as views of society and family. Descriptive analysis of the survey responses revealed that the perceptions of civil engineering varied widely. Participants’ definitions of civil engineering included the terms: construction, design, and infrastructure. Almost half of the participants reported that the major reason to study civil engineering was their interest in the subject matter, and most reported that they were proud to be civil engineers. Many study participants reported that their parents see them as civil engineers. Treatment of institutions and the workplace were also considered as having a significant impact on the recognition of women civil engineers. Almost half of the participants reported that they felt isolated or ignored at work because of their gender. This research emphasizes the importance of recognition for the development of the civil engineering identity of women

Keywords: civil engineering, gender, identity, recognition

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Authors: S. K. Hemalata, M. N. Shiva Kameshwari

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The present work focusses on anti-inflammatory action of Urginea wightii in-vitro. Urginea wightii is a member of Hyacinthaceae and considered to be wonder plant because of its varied important medicinal properties. The plant is endemic to India, Africa, and Mediterranian regions. Presence of alkaloids, flavonoid-glycosides especially flavonone derivatives are responsible for the strong anti-inflammatory activity of Urginea wightii. In present research work, anti-inflammatory activity of methanol extract of the bulb powder was tested on Male Wistar Rats. In these test animals, inflammation was induced by injecting carrageenan as the irritant to induce paw edema in Wistar rats. Inflammation of Paw edema was treated with both plant extract and Pyrox gel a known synthetic anti-inflammatory drug through external application. The result indicated that anti-inflammatory activity of Urginea wightii extract was almost similar to the synthetic Pyrox gel. This disproves the modern world's scepticism towards the herbal medicines and encourages to rely on natural plant extracts.

Keywords: anti-inflammatory activity, flavonoid-glycosides, Pyrox gel, Urginia wightii

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Authors: Khenfer Koummich Fatma, Hendel Fatiha, Mesbahi Larbi

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This paper presents an approach based on Hidden Markov Models (HMM: Hidden Markov Model) using HTK tools. The goal is to create a human-machine interface with a voice recognition system that allows the operator to teleoperate a mentor robot to execute specific tasks as rotate, raise, close, etc. This system should take into account different levels of environmental noise. This approach has been applied to isolated words representing the robot commands pronounced in two languages: French and Arabic. The obtained recognition rate is the same in both speeches, Arabic and French in the neutral words. However, there is a slight difference in favor of the Arabic speech when Gaussian white noise is added with a Signal to Noise Ratio (SNR) equals 30 dB, in this case; the Arabic speech recognition rate is 69%, and the French speech recognition rate is 80%. This can be explained by the ability of phonetic context of each speech when the noise is added.

Keywords: Arabic speech recognition, Hidden Markov Model (HMM), HTK, noise, TIMIT, voice command

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Authors: Boris M. Fedorov, Liudmila P. Goncharenko, Sergey A. Sybachin, Natalia A. Mamedova, Ekaterina V. Makarenkova, Saule Rakhimova

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In modern economic conditions, the question of the possibility of correct recognition of a signature on digital documents in order to verify the expression of will or confirm a certain operation is relevant. The additional complexity of processing lies in the dynamic variability of the signature for each individual, as well as in the way information is processed because the signature refers to biometric data. The article discusses the issues of using artificial intelligence models in order to improve the quality of signature confirmation in document recognition. The analysis of several possible options for using the model is carried out. The results of the study are given, in which it is possible to correctly determine the authenticity of the signature on small samples.

Keywords: signature recognition, biometric data, artificial intelligence, neural networks

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Authors: Jawad Alzeer

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Natural products are well recognized as sources of drugs in several human ailments. To investigate the impact of variable extraction techniques on the cytotoxic effects of medicinal plant extracts, 5 well-known medicinal plants from Palestine were extracted with 90% ethanol, 80% methanol, acetone, coconut water, apple vinegar, grape vinegar or 5% acetic acid. The resulting extracts were screened for cytotoxic activities against three different cancer cell lines (B16F10, MCF-7, and HeLa) using a standard resazurin-based cytotoxicity assay and Nile Blue A as the positive control. Highly variable toxicities and tissue sensitivity were observed, depending upon the solvent used for extraction. Acetone consistently gave lower extraction yields but higher cytotoxicity, whereas other solvent systems gave much higher extraction yields with lower cytotoxicity. Interestingly, coconut water was found to offer a potential alternative to classical organic solvents; it gave consistently highest extraction yields, and in the case of S. officinalis L., highly toxic extracts towards MCF-7 cells derived from human breast cancer. These results demonstrate how the cytotoxicity of plant extracts can be inversely proportional to the yield, and that solvent selection plays an important role in both factors.

Keywords: plant extract, natural products, anti cancer drug, cytotoxicity

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Authors: Abdel-Tawab H. Mossa

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Synthetic pesticides are widely used in large-scale worldwide for control pests in agriculture and public health sectors in both developed and developing countries. Although the positive role of pesticides, they have many adverse toxic effects on humans, animals, and the ecosystem. Therefore, in the last few years, scientists have been searching for new active compounds from natural resources as an alternative to synthetic pesticides. Currently, many commercial natural pesticides are available commercially worldwide. These products are recommended for uses in organic farmers and considered as safe pesticides. This paper focuses on the adverse effects of natural pesticides on mammals. Available commercial pesticides in the market contain essential oils (e.g. pepper, cinnamon, and garlic), plant extracts, microorganism (e.g. bacteria, fungi or their toxin), mineral oils and some active compounds from natural recourses e.g. spinosad, neem, pyrethrum, rotenone, abamectin and other active compounds from essential oils (EOs). Some EOs components, e.g., thujone, pulegone, and thymol have high acute toxicity (LD50) is 87.5, 150 and 980 mg/kg. B.wt on mice, respectively. Natural pesticides such as spinosad, pyrethrum, neem, abamectin, and others have toxicological effects to mammals and ecosystem. These compounds were found to cause hematotoxicity, hepato-renal toxicity, biochemical alteration, reproductive toxicity, genotoxicity, and mutagenicity. It caused adverse effects on the ecosystem. Therefore, natural pesticides in general not safe and have high acute toxicity and can induce adverse effects at long-term exposure.

Keywords: natural pesticides, toxicity, safety, genotoxicity, ecosystem, biochemical

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Authors: B. Chandar, M. K. Ramasamy, P. Madasamy

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The discovery and development of newer antibiotics are limited with the increase in resistance of such multi-drug resistant bacteria creating the need for alternative new therapeutic agents. The recently discovered New Delhi Metallo-betalactamase-1 (NDM-1), which confers antibiotic resistance to most of the currently available β-lactams, except colistin and tigecycline, is a global concern. Several antibacterial drugs approved are natural products or their semisynthetic derivatives, but plant extracts remain to be explored to find molecules that are effective against NDM-1 bacteria. Therefore, it is necessary to explore the possibility of finding new and effective antibacterial compounds against NDM-1 bacteria. In the present study, we have screened a diverse set South Indian plant species, and report most plant species as a potential source for antimicrobial compounds against NDM-1 bacteria. Ethanol extracts from the leaves of taxonomically diverse South Indian medicinal plants were screened for antibacterial activity against NDM-1 E. coli using streak plate method. Among the plant screened against NDM-1 E. coli, the ethanol extracts from many plant extracts showed minimum bactericidal concentration between 5 and 15 mg /ml and MIC between 2.54 and 5.12 mg/ml. These extracts also showed a potent synergistic effect when combined with antibiotics colistin and tetracycline. Combretum albidum that was effective was taken for further analysis. At 5mg/L concentration, these extracts inhibited the NDM-1 enzyme in vitro, and residual activity for Combretum albidum was 33.09%. Treatment of NDM-1 E. coli with the extracts disrupted the cell wall integrity and caused 89.7% cell death. The plant extract of Combretum albidum that was effective was subjected to fractionation and the fraction was further subjected to HPLC, LC-MS for identification of antibacterial compound.

Keywords: antibacterial activity, combretum albidum, Escherichia coli, NDM-1

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Authors: Angelos Kaminis, Dakotah Stirnweis

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Advances in robotic technology have driven the development of improved robotic companions in the last couple decades. However, commercially available robotic companions lack the ability to create an emotional connection with their user. By developing a companion robot that has a symbiotic relationship with a plant, an element of co-dependency is introduced into the human companion robot dynamic. This companion robot, while theoretically capable of providing most of the plant’s needs, still requires human interaction for watering, moving obstacles, and solar panel cleaning. To facilitate the interaction between human and robot, the robot is capable of limited auditory and visual communication to help express its and the plant’s needs. This paper seeks to fully describe the Autonomous Plant Care Robot system and its symbiotic relationship with its botanical ward and the plant and robot’s dependent relationship with their owner.

Keywords: symbiotic, robotics, autonomous, plant-care, companion

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Authors: Mads H. Clausen

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Plant cell walls are structurally complex and contain a larger number of diverse carbohydrate polymers. These plant fibers are a highly valuable bio-resource and the focus of food, energy and health research. We are interested in studying the interplay of plant cell wall carbohydrates with proteins such as enzymes, cell surface lectins and antibodies. However, detailed molecular level investigations of such interactions are hampered by the heterogeneity and diversity of the polymers of interest. To circumvent this, we target well-defined oligosaccharides with representative structures that can be used for characterizing protein-carbohydrate binding. The presentation will highlight chemical syntheses of plant cell wall oligosaccharides from our group and provide examples from studies of their interactions with proteins.

Keywords: oligosaccharides, carbohydrate chemistry, plant cell walls, carbohydrate-acting enzymes

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Authors: Yuan-Hsiang Chang, Zhong-Xian Peng, Li-Der Jeng

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Music has always been an integral part of human’s daily lives. But, for the most people, reading musical score and turning it into melody is not easy. This study aims to develop an Automatic music score recognition system using digital image processing, which can be used to read and analyze musical score images automatically. The technical approaches included: (1) staff region segmentation; (2) image preprocessing; (3) note recognition; and (4) accidental and rest recognition. Digital image processing techniques (e.g., horizontal /vertical projections, connected component labeling, morphological processing, template matching, etc.) were applied according to musical notes, accidents, and rests in staff notations. Preliminary results showed that our system could achieve detection and recognition rates of 96.3% and 91.7%, respectively. In conclusion, we presented an effective automated musical score recognition system that could be integrated in a system with a media player to play music/songs given input images of musical score. Ultimately, this system could also be incorporated in applications for mobile devices as a learning tool, such that a music player could learn to play music/songs.

Keywords: connected component labeling, image processing, morphological processing, optical musical recognition

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Authors: Shanxiong Chen, Xu Han, Xiaolong Wang, Hui Ma

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Yi is an ethnic group mainly living in mainland China, with its own spoken and written language systems, after development of thousands of years. Ancient Yi is one of the six ancient languages in the world, which keeps a record of the history of the Yi people and offers documents valuable for research into human civilization. Recognition of the characters in ancient Yi helps to transform the documents into an electronic form, making their storage and spreading convenient. Due to historical and regional limitations, research on recognition of ancient characters is still inadequate. Thus, deep learning technology was applied to the recognition of such characters. Five models were developed on the basis of the four-layer convolutional neural network (CNN). Alpha-Beta divergence was taken as a penalty term to re-encode output neurons of the five models. Two fully connected layers fulfilled the compression of the features. Finally, at the softmax layer, the orthographic features of ancient Yi characters were re-evaluated, their probability distributions were obtained, and characters with features of the highest probability were recognized. Tests conducted show that the method has achieved higher precision compared with the traditional CNN model for handwriting recognition of the ancient Yi.

Keywords: recognition, CNN, Yi character, divergence

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Authors: Nayra Martin-Key, Erich Graf, Wendy Adams, Graeme Fairchild

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Children and adolescents with Conduct Disorder (CD) have been shown to demonstrate impairments in emotion recognition, but it is currently unclear whether this deficit is related to specific emotions or whether it represents a global deficit in emotion recognition. An emotion recognition task with concurrent eye-tracking was employed to further explore this relationship in a sample of male and female adolescents with CD. Participants made emotion categorization judgements for presented dynamic and morphed static facial expressions. The results demonstrated that males with CD, and to a lesser extent, females with CD, displayed impaired facial expression recognition in general, whereas callous-unemotional (CU) traits were linked to specific problems in sadness recognition in females with CD. A region-of-interest analysis of the eye-tracking data indicated that males with CD exhibited reduced fixation times for the eye-region of the face compared to typically-developing (TD) females, but not TD males. Females with CD did not show reduced fixation to the eye-region of the face relative to TD females. In addition, CU traits did not influence CD subjects’ attention to the eye-region of the face. These findings suggest that the emotion recognition deficits found in CD males, the worst performing group in the behavioural tasks, are partly driven by reduced attention to the eyes.

Keywords: attention, callous-unemotional traits, conduct disorder, emotion recognition, eye-region, eye-tracking, sex differences

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Authors: Marcio Leal, Marta Villamil

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Computacional recognition of sign languages aims to allow a greater social and digital inclusion of deaf people through interpretation of their language by computer. This article presents a model of recognition of two of global parameters from sign languages; hand configurations and hand movements. Hand motion is captured through an infrared technology and its joints are built into a virtual three-dimensional space. A Multilayer Perceptron Neural Network (MLP) was used to classify hand configurations and Dynamic Time Warping (DWT) recognizes hand motion. Beyond of the method of sign recognition, we provide a dataset of hand configurations and motion capture built with help of fluent professionals in sign languages. Despite this technology can be used to translate any sign from any signs dictionary, Brazilian Sign Language (Libras) was used as case study. Finally, the model presented in this paper achieved a recognition rate of 80.4%.

Keywords: artificial neural network, computer vision, dynamic time warping, infrared, sign language recognition

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Authors: Chirawat Wattanapanich, Hong Wei

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This study presents new gait representations for improving gait recognition accuracy on cross gait appearances, such as normal walking, wearing a coat and carrying a bag. Based on the Gait Energy Image (GEI), two ideas are implemented to generate new gait representations. One is to append lower knee regions to the original GEI, and the other is to apply convolutional operations to the GEI and its variants. A set of new gait representations are created and used for training multi-class Support Vector Machines (SVMs). Tests are conducted on the CASIA dataset B. Various combinations of the gait representations with different convolutional kernel size and different numbers of kernels used in the convolutional processes are examined. Both the entire images as features and reduced dimensional features by Principal Component Analysis (PCA) are tested in gait recognition. Interestingly, both new techniques, appending the lower knee regions to the original GEI and convolutional GEI, can significantly contribute to the performance improvement in the gait recognition. The experimental results have shown that the average recognition rate can be improved from 75.65% to 87.50%.

Keywords: convolutional image, lower knee, gait

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Authors: Rajpal Kaur, Pooja Choudhary

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Biometrics, which refers to identifying an individual based on his or her physiological or behavioral characteristics, has the capabilities to the reliably distinguish between an authorized person and an imposter. The Signature recognition systems can categorized as offline (static) and online (dynamic). This paper presents Surf Feature based recognition of offline signatures system that is trained with low-resolution scanned signature images. The signature of a person is an important biometric attribute of a human being which can be used to authenticate human identity. However the signatures of human can be handled as an image and recognized using computer vision and HMM techniques. With modern computers, there is need to develop fast algorithms for signature recognition. There are multiple techniques are defined to signature recognition with a lot of scope of research. In this paper, (static signature) off-line signature recognition & verification using surf feature with HMM is proposed, where the signature is captured and presented to the user in an image format. Signatures are verified depended on parameters extracted from the signature using various image processing techniques. The Off-line Signature Verification and Recognition is implemented using Mat lab platform. This work has been analyzed or tested and found suitable for its purpose or result. The proposed method performs better than the other recently proposed methods.

Keywords: offline signature verification, offline signature recognition, signatures, SURF features, HMM

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Authors: Abduraheem K., Suboohi Nasrin

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Herbaria are specimens of preserved plants, which are very delicate and cellulosic in nature. While these collections are very useful for the enrichment of knowledge and are considered as natural heritage of our entire world, it is very important to preserve and conserve them. The significance is not only to prevent the herbaria from the deterioration of biological agencies but also to preserve its colours and retain natural colour. Colour is not only characteristic of a plant, but it can also help to identify closely related species or to distinguish a plant from a collection of herbaria. Keeping this in mind, a selective solution has been prepared for the conservation and preservation of herbarium in the present study. In this, the quantity of all the selected chemicals, i.e., formaldehyde and copper sulphate was kept constant, and the solution was prepared by dissolving it in distilled water by increasing the amount of picric acid (1, 2, 3, 4, and 5 ml). Fresh specimens of roses and bougainvillea were washed with distilled water and kept in the above solution for 10 to 15 minutes at room temperature. After 10 minutes, the specimen was removed from the solution, dried with the help of paper, and then pressed under the plant press. Blotting sheets were used to absorb the moisture content and were changed every 2 to 3 days to protect against fungal growth. The results revealed that all solutions had insecticidal properties and protected the herbarium specimen against pests. While in the case of colour retention, solution-1 and 2 were not satisfactory colour preservation, and solutions-3 and 5 maintained the colour of rose and bougainvillea leaves for 15 to 20 days and for a month, respectively. After that, the colour begins to fade, and the process is faster in rose leaves than in bougainvillea. And it was also observed that the colour of young leaves started to fade before that of older leaves. When the leaves of rose and bougainvillea are treated with Solution-4, then the colour of rose leaves is maintained for six months.

Keywords: solutions, colour retention, preservation and conservation, leaves of roses and bougainvillea

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Authors: Anna Drabczyk, Sonia Kudlacik-Kramarczyk, Dagmara Malina, Bozena Tyliszczak, Agnieszka Sobczak-Kupiec

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Nowadays, nano-size materials are very popular group of materials among scientists. What is more, these materials find an application in a wide range of various areas. Therefore constantly increasing demand for nanomaterials including metallic nanoparticles such as silver of gold ones is observed. Therefore, new routes of their preparation are sought. Considering potential application of nanoparticles, it is important to select an adequate methodology of their preparation because it determines their size and shape. Among the most commonly applied methods of preparation of nanoparticles chemical and electrochemical techniques are leading. However, currently growing attention is directed into the biological or biochemical aspects of syntheses of metallic nanoparticles. This is associated with a trend of developing of new routes of preparation of given compounds according to the principles of green chemistry. These principles involve e.g. the reduction of the use of toxic compounds in the synthesis as well as the reduction of the energy demand or minimization of the generated waste. As a result, a growing popularity of the use of such components as natural plant extracts, infusions or essential oils is observed. Such natural substances may be used both as a reducing agent of metal ions and as a stabilizing agent of formed nanoparticles therefore they can replace synthetic compounds previously used for the reduction of metal ions or for the stabilization of obtained nanoparticles suspension. Methods that proceed in the presence of previously mentioned natural compounds are environmentally friendly and proceed without the application of any toxic reagents. Methodology: Presented research involves preparation of silver nanoparticles using selected plant extracts, e.g. artichoke extract. Extracts of natural origin were used as reducing and stabilizing agents at the same time. Furthermore, syntheses were carried out in the presence of additional polymeric stabilizing agent. Next, such features of obtained suspensions of nanoparticles as total antioxidant activity as well as content of phenolic compounds have been characterized. First of the mentioned studies involved the reaction with DPPH (2,2-Diphenyl-1-picrylhydrazyl) radical. The content of phenolic compounds was determined using Folin-Ciocalteu technique. Furthermore, an essential issue was also the determining of the stability of formed suspensions of nanoparticles. Conclusions: In the research it was demonstrated that metallic nanoparticles may be obtained using plant extracts or infusions as stabilizing or reducing agent. The methodology applied, i.e. a type of plant extract used during the synthesis, had an impact on the content of phenolic compounds as well as on the size and polydispersity of obtained nanoparticles. What is more, it is possible to prepare nano-size particles that will be characterized by properties desirable from the viewpoint of their potential application and such an effect may be achieved with the use of non-toxic reagents of natural origin. Furthermore, proposed methodology stays in line with the principles of green chemistry.

Keywords: green chemistry principles, metallic nanoparticles, plant extracts, stabilization of nanoparticles

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Authors: Mohamed Lotfy, Ghada Soliman

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Recognizing Arabic dot-matrix digits is a challenging problem due to the unique characteristics of dot-matrix fonts, such as irregular dot spacing and varying dot sizes. This paper presents an approach for recognizing Arabic digits printed in dot matrix format. The proposed model is based on Convolutional Neural Networks (CNN) that take the dot matrix as input and generate embeddings that are rounded to generate binary representations of the digits. The binary embeddings are then used to perform Optical Character Recognition (OCR) on the digit images. To overcome the challenge of the limited availability of dotted Arabic expiration date images, we developed a True Type Font (TTF) for generating synthetic images of Arabic dot-matrix characters. The model was trained on a synthetic dataset of 3287 images and 658 synthetic images for testing, representing realistic expiration dates from 2019 to 2027 in the format of yyyy/mm/dd. Our model achieved an accuracy of 98.94% on the expiry date recognition with Arabic dot matrix format using fewer parameters and less computational resources than traditional CNN-based models. By investigating and presenting our findings comprehensively, we aim to contribute substantially to the field of OCR and pave the way for advancements in Arabic dot-matrix character recognition. Our proposed approach is not limited to Arabic dot matrix digit recognition but can also be extended to text recognition tasks, such as text classification and sentiment analysis.

Keywords: computer vision, pattern recognition, optical character recognition, deep learning

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Authors: Dong Seop Lee, Byung Sik Kim

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In the 4th Industrial Revolution, various intelligent technologies have been developed in many fields. These artificial intelligence technologies are applied in various services, including disaster management. Disaster information management does not just support disaster work, but it is also the foundation of smart disaster management. Furthermore, it gets historical disaster information using artificial intelligence technology. Disaster information is one of important elements of entire disaster cycle. Disaster information management refers to the act of managing and processing electronic data about disaster cycle from its’ occurrence to progress, response, and plan. However, information about status control, response, recovery from natural and social disaster events, etc. is mainly managed in the structured and unstructured form of reports. Those exist as handouts or hard-copies of reports. Such unstructured form of data is often lost or destroyed due to inefficient management. It is necessary to manage unstructured data for disaster information. In this paper, the Optical Character Recognition approach is used to convert handout, hard-copies, images or reports, which is printed or generated by scanners, etc. into electronic documents. Following that, the converted disaster data is organized into the disaster code system as disaster information. Those data are stored in the disaster database system. Gathering and creating disaster information based on Optical Character Recognition for unstructured data is important element as realm of the smart disaster management. In this paper, Korean characters were improved to over 90% character recognition rate by using upgraded OCR. In the case of character recognition, the recognition rate depends on the fonts, size, and special symbols of character. We improved it through the machine learning algorithm. These converted structured data is managed in a standardized disaster information form connected with the disaster code system. The disaster code system is covered that the structured information is stored and retrieve on entire disaster cycle such as historical disaster progress, damages, response, and recovery. The expected effect of this research will be able to apply it to smart disaster management and decision making by combining artificial intelligence technologies and historical big data.

Keywords: disaster information management, unstructured data, optical character recognition, machine learning

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Authors: Archna Mall, Neelam Agrawal, Hari O. Saxena, Bhavana Sharma

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Butea monosperma occurs widely throughout central Indian states. Eco-friendly natural dyes were isolated in aqueous medium from leaves, bark and flowers of this plant. These dyes were used for dyeing on cotton fabric using various chemical (potassium aluminium sulphate, potassium dichromate, ferrous sulphate, stannous chloride & tannic acid) and natural mordants (rinds of Terminallia bellerica & Terminalia chebula fruits and shells of Prunus dulcis & Juglans regia nuts). Dyeing was carried out using the pre-mordanting technique. Large range of beautiful shades in terms of hue and darkness were recorded because of varying mordant concentrations and combinations. More importantly dyed fabrics registered varying the degree of colour fastness properties to washing (1-3, colour change and 4-5, colour staining), light (2-4), rubbing (4-5, dry and 3-5, wet) and perspiration (1-4, colour change and 4-5, colour staining). Thus, along with flowers which are traditionally known for natural dyes, the leaves and bark may also find their place in textile industries.

Keywords: Butea monosperma, cotton, mordants, natural dyes

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Authors: L. Almulla

Abstract:

Native plants are better adapted to the local environment providing a more natural effect on landscape projects; their use will both conserve natural resources and produce sustainable greenery. Continuation of evaluation of additional native plants is essential to increase diversity of plant resources for greenery projects. Therefore, in this project an effort was made to study the mass multiplication of further native plants for greenery applications. Standardization of vegetative propagation methods is essential for conservation and sustainable utilization of native plants in restoration projects. Moreover, these simple propagation methods can be readily adapted by the local nursery sector in Kuwait. In the present study, various treatments were used to mass multiply selected plants using vegetative parts to secure maximum rooting and initial growth. Soft or semi-hardwood cuttings of selected native plants were collected from mother plants and subjected to different treatments. Pennisetum divisum can be vegetatively propagated by cuttings/off-shoots. However, Tamarix aucheriana showed maximum number of rooted cuttings and stronger vigor seedlings with the lowest growth hormone concentration. Standardizing the propagation techniques for the native plant species will add to the rehabilitation and landscape revegetation projects in Kuwait.

Keywords: Kuwait desert, landscape, rooting percentage, vegetative propagation

Procedia PDF Downloads 100

Authors: Farshideh Einsele, Hassan Foroosh

Abstract:

In this paper, we present a robust algorithm to recognize extracted text from grocery product images captured by mobile phone cameras. Recognition of such text is challenging since text in grocery product images varies in its size, orientation, style, illumination, and can suffer from perspective distortion. Pre-processing is performed to make the characters scale and rotation invariant. Since text degradations can not be appropriately defined using wellknown geometric transformations such as translation, rotation, affine transformation and shearing, we use the whole character black pixels as our feature vector. Classification is performed with minimum distance classifier using the maximum likelihood criterion, which delivers very promising Character Recognition Rate (CRR) of 89%. We achieve considerably higher Word Recognition Rate (WRR) of 99% when using lower level linguistic knowledge about product words during the recognition process.

Keywords: camera-based OCR, feature extraction, document, image processing, grocery products

Procedia PDF Downloads 393

Authors: Jalal Karam

Abstract:

The methods of Fourier, Laplace, and Wavelet Transforms provide transfer functions and relationships between the input and the output signals in linear time invariant systems. This paper shows the equivalence among these three methods and in each case presenting an application of the appropriate (Fourier, Laplace or Wavelet) to the convolution theorem. In addition, it is shown that the same holds for a direct integration method. The Biorthogonal wavelets Bior3.5 and Bior3.9 are examined and the zeros distribution of their polynomials associated filters are located. This paper also presents the significance of utilizing wavelets as effective tools in processing speech signals for common multimedia applications in general, and for recognition and compression in particular. Theoretically and practically, wavelets have proved to be effective and competitive. The practical use of the Continuous Wavelet Transform (CWT) in processing and analysis of speech is then presented along with explanations of how the human ear can be thought of as a natural wavelet transformer of speech. This generates a variety of approaches for applying the (CWT) to many paradigms analysing speech, sound and music. For perception, the flexibility of implementation of this transform allows the construction of numerous scales and we include two of them. Results for speech recognition and speech compression are then included.

Keywords: continuous wavelet transform, biorthogonal wavelets, speech perception, recognition and compression

Procedia PDF Downloads 395

Authors: Amalia Zuhra

Abstract:

Indonesia is very rich with its natural resources. Natural resource management becomes a challenge for Indonesia. Improper management will make the natural resources run out and future generations will not be able to enjoy the natural wealth. A good rule of law and proper implementation determines the success of the management of a country's natural resources. This paper examines the need to redefine problems and challenges in the management of natural resources in Indonesia in the context of law. The purpose of this article is to overview the latest issues and challenges in natural resource management and to redefine legal provisions related to environmental management and human rights protection so that the management of natural resources in the present and future will be more sustainable. This paper finds that sustainable management of natural resources is absolutely essential. The aspect of environmental protection and human rights must be elaborated more deeply so that the management of natural resources can be done maximally without harming not only people but also the environment.

Keywords: international environmental law, human rights law, natural resource management, sustainable development

Procedia PDF Downloads 251