Search results for: fruit recognition

Authors: Malika Yaici, Soraya Aloui, Sara Semchaoui

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This paper deals with human activity recognition from sensor data. It is an active research area, and the main objective is to obtain a high recognition rate. In this work, a recognition system based on expert systems is proposed; the recognition is performed using the objects, object states, and gestures and taking into account the context (the location of the objects and of the person performing the activity, the duration of the elementary actions and the activity). The system recognizes complex activities after decomposing them into simple, easy-to-recognize activities. The proposed method can be applied to any type of activity. The simulation results show the robustness of our system and its speed of decision.

Keywords: human activity recognition, ubiquitous computing, context-awareness, expert system

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Authors: Ainagul Yermekova, Liudmila Goncharenko, Ali Baghirzade, Sergey Sybachin

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In this article, we address the problem of Kazakhstan's transition to the Latin alphabet. The transition process started in 2017 and is scheduled to be completed in 2025. In connection with these events, the problem of recognizing the characters of the new alphabet is raised. Well-known character recognition programs such as ABBYY FineReader, FormReader, MyScript Stylus did not recognize specific Kazakh letters that were used in Cyrillic. The author tries to give an assessment of the well-known method of character recognition that could be in demand as part of the country's transition to the Latin alphabet. Three methods of character recognition: template, structured, and feature-based, are considered through the algorithms of operation. At the end of the article, a general conclusion is made about the possibility of applying a certain method to a particular recognition process: for example, in the process of population census, recognition of typographic text in Latin, or recognition of photos of car numbers, store signs, etc.

Keywords: text detection, template method, recognition algorithm, structured method, feature method

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Authors: Gheida J. Shahrour, Martin J. Russell

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The 3D body movement signals captured during human-human conversation include clues not only to the content of people’s communication but also to their culture and personality. This paper is concerned with automatic extraction of this information from body movement signals. For the purpose of this research, we collected a novel corpus from 27 subjects, arranged them into groups according to their culture. We arranged each group into pairs and each pair communicated with each other about different topics. A state-of-art recognition system is applied to the problems of person, culture, and topic recognition. We borrowed modeling, classification, and normalization techniques from speech recognition. We used Gaussian Mixture Modeling (GMM) as the main technique for building our three systems, obtaining 77.78%, 55.47%, and 39.06% from the person, culture, and topic recognition systems respectively. In addition, we combined the above GMM systems with Support Vector Machines (SVM) to obtain 85.42%, 62.50%, and 40.63% accuracy for person, culture, and topic recognition respectively. Although direct comparison among these three recognition systems is difficult, it seems that our person recognition system performs best for both GMM and GMM-SVM, suggesting that inter-subject differences (i.e. subject’s personality traits) are a major source of variation. When removing these traits from culture and topic recognition systems using the Nuisance Attribute Projection (NAP) and the Intersession Variability Compensation (ISVC) techniques, we obtained 73.44% and 46.09% accuracy from culture and topic recognition systems respectively.

Keywords: person recognition, topic recognition, culture recognition, 3D body movement signals, variability compensation

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Authors: Yingisani Chabalala, Elhadi Adam, Khalid Adem Ali

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Mapping smallholder fruit plantations using optical data is challenging due to morphological landscape heterogeneity and crop types having overlapped spectral signatures. Furthermore, cloud covers limit the use of optical sensing, especially in subtropical climates where they are persistent. This research assessed the effectiveness of Sentinel-1 (S1) and Sentinel-2 (S2) data for mapping fruit trees and co-existing land-use types by using support vector machine (SVM) and random forest (RF) classifiers independently. These classifiers were also applied to fused data from the two sensors. Feature ranks were extracted using the RF mean decrease accuracy (MDA) and forward variable selection (FVS) to identify optimal spectral windows to classify fruit trees. Based on RF MDA and FVS, the SVM classifier resulted in relatively high classification accuracy with overall accuracy (OA) = 0.91.6% and kappa coefficient = 0.91% when applied to the fused satellite data. Application of SVM to S1, S2, S2 selected variables and S1S2 fusion independently produced OA = 27.64, Kappa coefficient = 0.13%; OA= 87%, Kappa coefficient = 86.89%; OA = 69.33, Kappa coefficient = 69. %; OA = 87.01%, Kappa coefficient = 87%, respectively. Results also indicated that the optimal spectral bands for fruit tree mapping are green (B3) and SWIR_2 (B10) for S2, whereas for S1, the vertical-horizontal (VH) polarization band. Including the textural metrics from the VV channel improved crop discrimination and co-existing land use cover types. The fusion approach proved robust and well-suited for accurate smallholder fruit plantation mapping.

Keywords: smallholder agriculture, fruit trees, data fusion, precision agriculture

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Authors: Jamal Ayour, Mohamed Benichou

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Fruit quality is one of the main concerns of consumers, producers, and distributors. The evolution of apricot fruits undergoes a strong acceleration during maturation, and the rapidity of post-harvest evolution of the ripe fruit is particularly selective in the apricot. The objective of this study is to identify new cultivars with an interesting quality as well as a better yield allowing a more prolonged production over time. The evaluation of the fruit quality of new apricot cultivars from the Marrakech region was carried out by analyzing their physical and biochemical attributes during ripening. The results obtained clearly show a great diversity of the physicochemical attributes of the selected clones. Also, some genotypes of apricots showed contents of sugars, organic acids (vitamin C) and β carotene significantly higher than those of the most famous varieties of Morocco: Canino, Delpatriarca, and Maoui. Principal component analysis (PCA), taking into account the maturity stage and the diversity of cultivars, made it possible to define three groups with similar physicochemical attributes. The results of this study are of great use, particularly for the selection of genotypes with a better quality of fruit, both for consumption or industrial processing and with important contents of physicochemical attributes.

Keywords: apricot, acidity, carotenoids, color, sugar, quality, vitamin C

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Authors: Mandeep Kataria, Ritu Narula, Navneet Kaur

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Asparagine is vital amino acid which is required for the development of brain and it regulates the equilibrium of central nervous system. Asparagine is the chief amino acid that forms acrylamide in baked food by reacting with reducing sugars at high temperature ( Millard Reaction i.e. amino acids and sugars give new flavors at high temperature). It can also be a parameter of freshness in fruit juices because on storage of juices at 37°C caused an 87% loss in the total free amino acids and major decrease was recorded in asparagine contents. With this significance of monitoring asparagine, in the present work a biosensor for determining asparagine in fruit juices is developed. For the construction of biosensor L-asparaginase enzyme (0.5 IU) was co-immobilized with phenol red on TEOS chitosan sol-gel plastic disc and fixed on the fiber optic tip. Tip was immersed in a cell having 5ml of substrate and absorption was noted at response time of 5 min with 10-1 - 10-10 M concentrations of asparagine at 538 nm. L-asparaginase was extracted and from Solanum nigrum Asparagine biosensor was applied fruit juices on the monitoring asparagine contents. L-asparagine concentration found to be present in fruit juices like Guava Juice, Apple Juice, Mango Juice, Litchi juice, Strawberry juice, Pineapple juice Lemon juice, and Orange juice. Hence the developed biosensor has commercial aspects in quality insurance of fruit juices.

Keywords: fiber optic biosensor, chitosan, teos, l-asparaginase

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Authors: Goreti Botelho, Filomena Gomes, Fernanda M. Ferreira, Ilda Caldeira

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The strawberry tree (Arbutus unedo L.) is a small tree or shrub from botanical Ericaceae family that grows spontaneously nearby the Mediterranean basin and produce edible red fruits. A traditional processed fruit application, in Mediterranean countries, is the production of a spirit (known as aguardente de medronho, in Portugal) obtained from the fermented fruit. The main objective of our study was to contribute to the knowledge about the influence of the degree of maturation of fruits in the volatile composition and quality of arbutus spirit. The major volatiles in the three distillates fractions (head, heart and tail) obtained from fermentation of two different fruit maturation levels were quantified by GC-FID analysis and ANOVA one-way was performed. Additionally, the total antioxidant capacity and total phenolic compounds of both arbutus fruit spirits were determined, by ABTS and Folin-Ciocalteau method, respectively. The methanol concentration is superior (1022.39 g/hL a.a.) in the spirit made from fruits with highest total soluble solids, which is a value above the legal limit (1000 g/hL a.a.). Overall, our study emphasizes, for the first time, the influence of maturation degree of arbutus fruits in the spirit volatile composition and quality.

Keywords: arbutus fruit, maturation, quality, spirit

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Authors: Malika Yaici, Soraya Aloui, Sara Semchaoui

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Recognition of human activities from sensor data is an active research area, and the main objective is to obtain a high recognition rate. In this work, we propose a recognition system based on expert systems. The proposed system makes the recognition based on the objects, object states, and gestures, taking into account the context (the location of the objects and of the person performing the activity, the duration of the elementary actions, and the activity). This work focuses on complex activities which are decomposed into simple easy to recognize activities. The proposed method can be applied to any type of activity. The simulation results show the robustness of our system and its speed of decision.

Keywords: human activity recognition, ubiquitous computing, context-awareness, expert system

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Authors: Nunu Nakashidze, Shota Lominadze, Darejan Jashi

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Citrus culture used to be one of the leading fields of sub-tropical agriculture in Georgia and especially in Adjara region, but the citrus production has been significantly decreased in recent years due to deterioration of quality index of fruit and reduction of sale markets. The fact severely affected both the economy of Republic and population. Intensive technologies of citrus fruit production are widely implemented in the world practices, which include the following: variety of species, consumption of fertilizers and chemicals, proper use of fruit production and etc. However working on technologies which ensure getting of high quality and plentiful product is very much important if taking into consideration modern, global ecological problems. Using of bio-preparations for plant nourishment is considered as one of the activities. The present work discusses liquid organic fertilizer 'Biorag' produced in Georgia and influence of its growth stimulation (Gakhokidze N1, N2, N3) on agrochemical index of soils and mineral composition of fruit of Citrus Unshiu orchards cultivated in the sub-tropical zone of Black Sea in Adjara region. It was ascertained that liquid organic fertilizers used in the orchard of citrus 'Unshiu' and influence of growth stimulators on the quality index of fruit are not clearly shown in comparison with control one. A small priority is noticed in case of growth stimulators. In conditions of red soils, liquid organic fertilizers and growth stimulators added in the nutrition of the citrus more or less influence the dry material of fruit and the composition of ash and nutrition elements. Agro-chemical index of the soil, except exchange acidity, is somehow enlarged which is one of the positive results in this case.

Keywords: growth stimulator, liquid fertilizer, plant, fruit, soil

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Authors: J. Y. Ijato, A. Adewumi, H. O Yakubu, O. O. Olajide, B. O. Ojo, B. A. Adanikin

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Post-harvest fruit rot pathogens are one of the major factors that are responsible for food security challenges in developing countries like Nigeria. These pathogens also cause fruit food poisoning. Biocidal effects of ethanolic extracts of Khaya grandifoliola, Hyptis suaveolens, Zingiber officinale, Calophyllum inophyllum, Datura stramonium on the mycelia growth of fungal rot pathogens of pineapple fruit was investigated, the ethanolic extracts of these test plants exhibited high significant inhibitory effects on the rot pathogens, the highest ethanolic extract inhibition of Zingiber officinale was on Aspergillus flavus (38.40%) at 1.0g/ml while the least inhibitory effect was on Aspergillus fumigatus (23.10%) at 1.0g/ml, the highest ethanol extract inhibition of Datura stramonium was on Aspergillus tubingensis (24.00%) at 1.0g/ml while the least inhibitory effect was 10.00% on Colletotrichum fruticola at 1.0g/ml, the highest ethanol extract inhibition of Calophyllum inophyllum was on Trichoderma harzianum (18.50%) at 1.0g/ml while the least inhibitory effect was on Aspergillus flavus (15.00%) at 1.0g/ml, the highest ethanol extract inhibition of Hyptis suaveolens was on Aspergillus fumigatus (35.00%) at 1.0g/ml while the least inhibitory effect was on Aspergillus niger (20.00%) at 1.0g/ml, the highest ethanol extract inhibition of Khaya grandifoliola was on Aspergillus flavus (35.00%) at 1.00g/ml while the least inhibitory effect was on Aspergillus fumigates (22.00%) at 1.0g/ml, the antifungal capacity of these test plant extracts on rot causing fungi on pineapple fruit reveals the possibility of their use by farmers and fruit traders as alternative to chemical fungicide that portends great threat to human and environmental health.

Keywords: fruit rot, pathogens, plant extracts, pineapple, food poisoning

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Authors: Siavash Azarbani

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Background and Objective: The side effects of NSAIDS drugs have caused the increasing interest of scientists in herbal medicines as alternative treatment. In this study, the effect of anti inflammatory of seed and fruit of date palm hydroalcolic extracts, due to having antioxidants, was studied. Materials and Methods: In this study, the extraxts of date palm seed and fruit were prepared by the maceration method in 70% alcohol. Eighty male rats Wistar, divided into 10 groups of eight in each, 4 groups received different doses (100, 200, 400, and 600 mg/kg) of seed extract, and 4 other groups different doses (100, 200, 400, and 600 mg/kg) of fruits extract of the palm, and the positive control aspirin (300mg/kg) and the negative control group saline (5ml/kg) via injection intraperitoneally. Half an hour later, all animals received 100 µl of 1% carrageenan into the rats hind paw subcutaneous. The changes in rats paw edema was measured by plethysmometer every hour for five hours. Results: The effect of all of the doses of date palm seed extract on edema were less than aspirine (P<0.05). But there was no significant difference between the group that received 400 and 600 mg/kg of date palm fruit extract when compared with the aspirin group. The Dose 400 mg/kg of fruit extract showed the most anti-inflammatory effect, and it was assignded as the best dose. Conclusion: It is likely that with further studies on different model of animals and also on the human model, the palm fruit extract could be used for pain treatment.

Keywords: palm, inflamentory, date, aspirin, karageenan

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Authors: Fang Bo Yu, Li Bo Guan

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Biogas slurry is a low-cost source of crop nutrients and can offer extra benefits to soil fertility and fruit quality. However, its current utilization mode and low content of active ingredients limit its application scale. In this report, one growing season field research was conducted to assess the effects of concentrated biogas slurry on soil property, tomato fruit quality, and composition of the microflora in both non-rhizosphere and rhizosphere soils. The results showed that application of concentrated slurry could cause significant changes to tomato cultivation, including increases in organic matter, available N, P, and K, total N, and P, electrical conductivity, and fruit contents of amino acids, protein, soluble sugar, β-carotene, tannins, and vitamin C, together with the R/S ratios and the culturable counts of bacteria, actinomycetes, and fungi in soils. It could be concluded as the application is a practicable means in tomato production and might better service the sustainable agriculture in the near future.

Keywords: concentrated slurry, fruit quality, soil fertility, sustainable agriculture

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Authors: Andrés I. Ávila, Patricia Aros, César San Martín, Elizabeth Kehr, Yovana Leal

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We consider a linear programming model to help farmers to decide if it is convinient to choose among three kinds of export fruits for their future investment. We consider area, investment, water, productivitiy minimal unit, and harvest restrictions and a monthly based model to compute the average income in five years. Also, conditions on the field as area, water availability and initia investment are required. Using the Chilean costs and dollar-peso exchange rate, we can simulate several scenarios to understand the possible risks associated to this market.

Keywords: mixed integer problem, fruit production, support decision model, fruit tree farms

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Authors: Sevil Igit, Merve Meric, Sarp Erturk

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In this paper, it is proposed to improve Daisy descriptor based face recognition using a novel One-Bit Transform (1BT) based pre-registration approach. The 1BT based pre-registration procedure is fast and has low computational complexity. It is shown that the face recognition accuracy is improved with the proposed approach. The proposed approach can facilitate highly accurate face recognition using DAISY descriptor with simple matching and thereby facilitate a low-complexity approach.

Keywords: face recognition, Daisy descriptor, One-Bit Transform, image registration

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Authors: Sengul Uysal, Gokhan Zengin, Abdurrahman Aktumsek, Sukru Karatas

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In this research, we determined the total sugar content, fatty acid compositions and α-amylase and α-glucosidase inhibitory activity of methanolic and water extracts of nine different fruit tree leaves. α-amylase and α-glycosidase inhibitory activity were determined by using Caraway-Somogyi–iodine/potassium iodide (IKI) and 4-nitrophenyl-α-D-glucopyranoside (PNPG) as substrate, respectively. Total sugar content of the nine different fruit tree leaves varies from 281.02 mg GE/g (glucose equivalents) to 643.96 mg GE/g. Methanolic extract from avocado leaves had the strongest in α-amylase and α-glucosidase inhibitory activity, 69.21% and 96.26 %, respectively. Fatty acid composition of nine fruit tree leaves was characterized by GC (gas chromatography) and twenty-four components were identified. Among the tested fruit tree leaves, the main component was linolenic acid (49.09%). The level of essential fatty acids are over 50% in mulberry, grape and loquat leaves. PUFAs (polyunsaturated fatty acids) were major group of fatty acids present in oils of mulberry, fig, pomegranate, grape, and loquat leaves. Therefore, these oils can be considered as a good source of polyunsaturated fatty acids. Furthermore, avocado can be regarded as a new source for diabetic therapies.

Keywords: fatty acid compositions, total sugar contents, α-amylase, α-glucosidase, fruit tree leaves, Turkey

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Authors: Getamesay Kassaye Dimru

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The cultivation of fruit tree in degraded areas has two-fold importance. Firstly, it improves food availability and income, and secondly, it promotes the conservation of soil and water improving, in turn, the productivity of the land. The main objectives of this study are to identify the determinant of farmer's fruit trees plantation decision and to major fruit production challenges and opportunities of the study area. The analysis was made using primary data collected from 60 sample household selected randomly from the study area in 2016. The primary data was supplemented by data collected from a key informant. In addition to the descriptive statistics and statistical tests (Chi-square test and t-test), a logit model was employed to identify the determinant of fruit tree plantation decision. Drought, pest incidence, land degradation, lack of input, lack of capital and irrigation schemes maintenance, lack of misuse of irrigation water and limited agricultural personnel are the major production constraints identified. The opportunities that need to further exploited are better access to irrigation, main road access, endowment of preferred guava variety, experience of farmers, and proximity of the study area to research center. The result of logit model shows that from different factors hypothesized to determine fruit tree plantation decision, age of the household head accesses to market and perception of farmers about fruits' disease and pest resistance are found to be significant. The result has revealed important implications for the promotion of fruit production for both land degradation control and rehabilitation and increasing the livelihood of farming households.

Keywords: degradation, fruit, irrigation, pest

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Authors: XuKe Cao

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This paper reviews the current state of research on low-resource languages in the field of speech recognition, focusing on the challenges faced by low-resource language speech recognition, including the scarcity of data resources, the lack of linguistic resources, and the diversity of dialects and accents. The article reviews recent progress in low-resource language speech recognition, including techniques such as data augmentation, end to-end models, transfer learning, and multi-task learning. Based on the challenges currently faced, the paper also provides an outlook on future research directions. Through these studies, it is expected that the performance of speech recognition for low resource languages can be improved, promoting the widespread application and adoption of related technologies.

Keywords: low-resource languages, speech recognition, data augmentation techniques, NLP

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Authors: S. Jagadeesh Kumar

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This expose presents a luculent of recent machine learning practices as employed in the modern and as pertinent to prospective automatic speech recognition schemes. The aspiration is to promote additional traverse ablution among the machine learning and automatic speech recognition factions that have transpired in the precedent. The manuscript is structured according to the chief machine learning archetypes that are furthermore trendy by now or have latency for building momentous hand-outs to automatic speech recognition expertise. The standards offered and convoluted in this article embraces adaptive and multi-task learning, active learning, Bayesian learning, discriminative learning, generative learning, supervised and unsupervised learning. These learning archetypes are aggravated and conferred in the perspective of automatic speech recognition tools and functions. This manuscript bequeaths and surveys topical advances of deep learning and learning with sparse depictions; further limelight is on their incessant significance in the evolution of automatic speech recognition.

Keywords: automatic speech recognition, deep learning methods, machine learning archetypes, Bayesian learning, supervised and unsupervised learning

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Authors: O. A. Adeyeye, E. R. Sadiku, Periyar Selvam Sellamuthu, Anand Babu Perumal, Reshma B. Nambiar

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Mango is a tropical fruit which is often labelled as ‘super-fruit’ because of its unquantifiable benefits to human beings. However, despite its great importance, mango is a seasonal fruit and only very few off-seasonal cultivars are available in the market for consumption. Therefore, to overcome the seasonal variation and to increase the shelf-life of mango fruits, different drying methods are considered. In this study, freeze drying and tray drying methods were used to preserve two different cultivars of mango from South Africa. Moisture content, total soluble solid, ascorbic acid, total phenol content (TPC), antioxidant activity (DPPH) and organoleptic tests were carried out on the samples before and after drying. The effects of different edible preservatives and selected packaging materials used were analyzed on each sample. The result showed that freeze drying method is the best method of preserving the selected cultivar.

Keywords: postharvest, Mangos, cultivar, total soluble solid, total phenol content, antioxidant

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Authors: O. A. Adeyeye, E. R. Sadiku, Selvam Sellamuthu Periyar, Babu Perumal Anand, B. Nambiar Reshma

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Mango is a tropical fruit which is often labelled as ‘super-fruit’ because of its unquantifiable benefits to human beings. However, despite its great importance, mango is a seasonal fruit, and only very few off-seasonal species are available in the market for consumption. Therefore, in order to overcome the seasonal variation and to increase the shelf-life of mango fruits, different drying methods are considered In this study, freeze drying and tray drying methods were used to preserve two different cultivars of mango from South Africa. Moisture content, total soluble solid, ascorbic acid, total phenol content (TPC), antioxidant activity (DPPH) and organoleptic tests were carried out on the samples before and after drying. The effects of different edible preservatives and selected packaging materials used were analyzed on each sample. The result showed that freeze drying method is the best method of preserving the selected cultivar.

Keywords: postharvest, mangos, cultivar, total soluble solid, total phenol content, antioxidant

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Authors: Khaled M. Alhawiti

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This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: speech recognition, acoustic phonetic, artificial intelligence, hidden markov models (HMM), statistical models of speech recognition, human machine performance

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Authors: Shabir Ahmad Sofi, Shubham Aggarwal, Sanyam Singhal, Roohie Naaz

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Biometric recognition refers to an automatic recognition of individuals based on a feature vector(s) derived from their physiological and/or behavioral characteristic. Biometric recognition systems should provide a reliable personal recognition schemes to either confirm or determine the identity of an individual. These features are used to provide an authentication for computer based security systems. Applications of such a system include computer systems security, secure electronic banking, mobile phones, credit cards, secure access to buildings, health and social services. By using biometrics a person could be identified based on 'who she/he is' rather than 'what she/he has' (card, token, key) or 'what she/he knows' (password, PIN). In this paper, a brief overview of biometric methods, both unimodal and multimodal and their advantages and disadvantages, will be presented.

Keywords: biometric, DNA, fingerprint, ear, face, retina scan, gait, iris, voice recognition, unimodal biometric, multimodal biometric

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Authors: Adenike Boyo Olasunkanmi Kesinro, Henry Boyo, Surukite Oluwole

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Utilizing solar energy in producing electricity can minimize environmental pollution generated by fossil fuel in producing electricity. Our research was base on the extraction of dye from Roystonea regia fruit by using methanol as solvent. The dye extracts were used as sensitizers in Dye-sensitized solar cell (DSSCs). Study was done on the electrical properties from the extracts of Roystonea regia fruit as Dye-sensitized solar cell (DSSCs). The absorptions of the extracts and extracts with dye were determined at different wavelengths (350-1000nm). Absorption peak was observed at 1.339 at wavelength 400nm. The obtained values for methanol extract Roystonea regia extract are, Imp = 0.015mA, Vmp = 12.0mV, fill factor = 0.763, Isc= 0.018 mA and Voc = 13.1 mV and efficiency of 0.32%. .The phytochemical screening was taken and it was observed that Roystonea regia extract contained less of anthocyanin compared to flavonoids. The nanostructured dye sensitized solar cell (DSSC) will provide economically credible alternative to present day silicon p–n junction photovoltaic.

Keywords: methanol, ethanol, titanium dioxide, roystonea regia fruit, dye-sensitized solar cell

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Authors: Phawin Sangsuvan, Chutimet Srinilta

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This Paper presents the applications of Particle Swarm Optimization (PSO) Method for Thai optical character recognition (OCR). OCR consists of the pre-processing, character recognition and post-processing. Before enter into recognition process. The Character must be “Prepped” by pre-processing process. The PSO is an optimization method that belongs to the swarm intelligence family based on the imitation of social behavior patterns of animals. Route of each particle is determined by an individual data among neighborhood particles. The interaction of the particles with neighbors is the advantage of Particle Swarm to determine the best solution. So PSO is interested by a lot of researchers in many difficult problems including character recognition. As the previous this research used a Projection Histogram to extract printed digits features and defined the simple Fitness Function for PSO. The results reveal that PSO gives 67.73% for testing dataset. So in the future there can be explored enhancement the better performance of PSO with improve the Fitness Function.

Keywords: character recognition, histogram projection, particle swarm optimization, pattern recognition techniques

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Authors: Benjawan Rangsikamol, Chutimet Srinilta

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This research paper deals with extraction of Thai character features using the proposed histogram projection so as to improve the recognition performance. The process starts with transformation of image files into binary files before thinning. After character thinning, the skeletons are entered into the proposed extraction using histogram projection (horizontal and vertical) to extract unique features which are inputs of the subsequent recognition step. The recognition rate with the proposed extraction technique is as high as 97 percent since the technique works very well with the idiosyncrasies of Thai characters.

Keywords: character recognition, histogram projection, multilayer perceptron, Thai character features extraction

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Authors: A. B. M. S. Hossain, A. Abdelgadir, N. A. Ibrahim

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Fresh ripen olive cannot be consumed immediately after harvest due to the excessive bitterness having polyphenol as antioxidant. Industrial processing needs to be edible the fruit. The laboratory processing technique has been used to make it edible by using acid (vinegar, 5% acetic acid) and alkaline solvent (NaOH). Based on the treatment and consequence, innovative data have been found in this regard. The experiment was conducted to investigate biochemical content, nutritional and DNA characterization of olive fruit treated with alkaline (Sodium chloride anhydrous) and acidic solvent (5% acetic acid, vinegar). The treatments were used as control (no water), water control, 10% sodium chloride anhydrous (NaOH), vinegar (5% acetic acid), vinegar + NaOH and vinegar + NaOH + hot water treatment. Our results showed that inverted sugar and glucose content were higher in the vinegar and NaOH treated olive than in other treatments. Fructose content was the highest in vinegar + NaOH treated fruit. Nutrient contents NO3 K, Ca and Na were found higher in the treated fruit than the control fruit. Moreover, maximum K content was observed in the case of all treatments compared to the other nutrient content. The highest acidic (lower pH) condition (sour) was found in treated fruit. DNA yield was found higher in water control than acid and alkaline treated olives. DNA band was wider in the olive treated water control compared to the NaOH, vinegar, vinegar + NaOH and vinegar + NaOH + Hot water treatment. Finally, results suggest that vinegar + NaOH treated olive fruit was the best for fresh olive homemade processing after harvesting for edible purpose.

Keywords: olive, vinegar, sugars, DNA band, bioprocess biotechnology

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Authors: Nestor A. Garcia Fragoso, Tetyana Baydyk, Ernst Kussul

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This article contains information from our investigation in the field of voice recognition. For this purpose, we created a voice database that contains different phrases in two languages, English and Spanish, for men and women. As a classifier, the LIRA (Limited Receptive Area) grayscale neural classifier was selected. The LIRA grayscale neural classifier was developed for image recognition tasks and demonstrated good results. Therefore, we decided to develop a recognition system using this classifier for voice recognition. From a specific set of speakers, we can recognize the speaker’s voice. For this purpose, the system uses spectrograms of the voice signals as input to the system, extracts the characteristics and identifies the speaker. The results are described and analyzed in this article. The classifier can be used for speaker identification in security system or smart buildings for different types of intelligent devices.

Keywords: extreme learning, LIRA neural classifier, speaker identification, voice recognition

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Authors: U. Ravi Babu, Mohd Mastan

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The present paper proposes a novel approach for handwritten digit recognition system. The present paper extract digit image features based on distance measure and derives an algorithm to classify the digit images. The distance measure can be performing on the thinned image. Thinning is the one of the preprocessing technique in image processing. The present paper mainly concentrated on an extraction of features from digit image for effective recognition of the numeral. To find the effectiveness of the proposed method tested on MNIST database, CENPARMI, CEDAR, and newly collected data. The proposed method is implemented on more than one lakh digit images and it gets good comparative recognition results. The percentage of the recognition is achieved about 97.32%.

Keywords: handwritten digit recognition, distance measure, MNIST database, image features

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Authors: Faizan Tariq, Moayid Ali Zaidi

Abstract:

Facial emotion recognition algorithms are expanding rapidly now a day. People are using different algorithms with different combinations to generate best results. There are six basic emotions which are being studied in this area. Author tried to recognize the facial expressions using object detector algorithms instead of traditional algorithms. Two object detection algorithms were chosen which are Faster R-CNN and YOLO. For pre-processing we used image rotation and batch normalization. The dataset I have chosen for the experiments is Static Facial Expression in Wild (SFEW). Our approach worked well but there is still a lot of room to improve it, which will be a future direction.

Keywords: face recognition, emotion recognition, deep learning, CNN

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Authors: Qiu Chen, Koji Kotani, Feifei Lee, Tadahiro Ohmi

Abstract:

In this paper, we propose an improved face recognition algorithm using histogram-based features in spatial and frequency domains. For adding spatial information of the face to improve recognition performance, a region-division (RD) method is utilized. The facial area is firstly divided into several regions, then feature vectors of each facial part are generated by Binary Vector Quantization (BVQ) histogram using DCT coefficients in low frequency domains, as well as Local Binary Pattern (LBP) histogram in spatial domain. Recognition results with different regions are first obtained separately and then fused by weighted averaging. Publicly available ORL database is used for the evaluation of our proposed algorithm, which is consisted of 40 subjects with 10 images per subject containing variations in lighting, posing, and expressions. It is demonstrated that face recognition using RD method can achieve much higher recognition rate.

Keywords: binary vector quantization (BVQ), DCT coefficients, face recognition, local binary patterns (LBP)

Procedia PDF Downloads 349