Search results for: fruit recognition

Authors: Shaode Yu, Jiajian Meng, Bing Zhu, Hang Yu, Qiurui Sun

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Speech emotion recognition (SER) is for recognizing human subjective emotions through audio data in-depth analysis. From speech audios, how to comprehensively extract emotional information and how to effectively fuse extracted features remain challenging. This paper presents a dual-stream SER framework that embraces both full training and transfer learning of different networks for thorough feature encoding. Besides, a plug-and-play cross-attention fusion (CAF) module is implemented for the valid integration of the dual-stream encoder output. The effectiveness of the proposed CAF module is compared to the other three fusion modules (feature summation, feature concatenation, and feature-wise linear modulation) on two databases (RAVDESS and IEMO-CAP) using different dual-stream encoders (full training network, DPCNN or TextRCNN; transfer learning network, HuBERT or Wav2Vec2). Experimental results suggest that the CAF module can effectively reconcile conflicts between features from different encoders and outperform the other three feature fusion modules on the SER task. In the future, the plug-and-play CAF module can be extended for multi-branch feature fusion, and the dual-stream SER framework can be widened for multi-stream data representation to improve the recognition performance and generalization capacity.

Keywords: speech emotion recognition, cross-attention fusion, dual-stream, pre-trained

Procedia PDF Downloads 76

Authors: Maurizio E. Picarella, Ludovica Fumelli, Francesca Siligato, Andrea Mazzucato

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Studies on reproductive dynamics in crops subjected to heat stress are crucial to breed more tolerant cultivars. In tomato, cultivars, breeding lines, and wild species have been thoroughly evaluated for the response to heat stress in several studies. Here, we address the reaction to temperature stress in a panel of selected landraces representing genotypes cultivated before the advent of professional varieties that usually show high adaptation to local environments. We adopted an experimental design with two open field trials, where transplanting was spaced by one month. In the second field, plants were thus subjected to mild stress with natural temperature fluctuations. The genotypes showed wide variation for both vegetative (plant height) and reproductive (stigma exsertion, pollen viability, number of flowers per inflorescence, and fruit set) traits. On average, all traits were affected by heat conditions; except for the number of flowers per inflorescence, the “G*E” interaction was always significant. In agreement with studies based on different materials, estimated broad sense heritability was high for plant height, stigma exsertion, and pollen viability and low for the number of flowers per inflorescence and fruit set. Despite the interaction, traits recorded in control and in heat conditions were positively correlated. The first two principal components estimated by multivariate analysis explained more than 50% of the total variability. The study indicated that landraces present a wide variability for the response of reproductive traits to temperature stress and that such variability could be very informative to dissect the traits with higher heritability and identify new QTL useful for breeding more resilient varieties.

Keywords: fruit set, heat stress, solanum lycopersicum L., style exsertion, tomato

Procedia PDF Downloads 129

Authors: Anderson Rocha, Pedro Miguel de Figueiredo Dinis Oliveira Gaspar

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Machine vision has been widely used in recent years in agriculture, as a tool to promote the automation of processes and increase the levels of productivity. The aim of this work is the development of a path recognition algorithm based on image processing to guide a terrestrial robot in-between tree rows. The proposed algorithm was developed using the software MATLAB, and it uses several image processing operations, such as threshold detection, morphological erosion, histogram equalization and the Hough transform, to find edge lines along tree rows on an image and to create a path to be followed by a mobile robot. To develop the algorithm, a set of images of different types of orchards was used, which made possible the construction of a method capable of identifying paths between trees of different heights and aspects. The algorithm was evaluated using several images with different characteristics of quality and the results showed that the proposed method can successfully detect a path in different types of environments.

Keywords: agricultural mobile robot, image processing, path recognition, hough transform

Procedia PDF Downloads 146

Authors: P. Ghosh, S. B. Sharma

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The growing problem of food waste is causing unacceptable economic, environmental and social impacts across the globe. In Australia, food waste is estimated at about AU$8 billion per year; however, information on the extent of wastage at different stages of the food value chain from farm to fork is very limited. This study aims to identify causes for and extent of food waste at wholesaler stage of the food value chain in the state of Western Australia. It also explores approaches applied to reduce and utilize food waste by the wholesalers. The study was carried out at Perth city market in Caning Vale, the main wholesale distribution centre for fruits and vegetables in Western Australia. A survey questionnaire was prepared and shared with 51 wholesalers and their responses to 10 targeted questions on quantity of produce (fruits and vegetables) delivery received and further supplied, reasons for waste generation and innovations applied or being considered to reduce and utilize food waste. Data were computed using the Statistical Package for the Social Sciences (SPSS version 21). Among the wholesalers 52% were primary wholesalers (buy produce directly from growers) and 48% were secondary wholesalers (buy produce in bulk from major wholesalers and supply to the local retail market, caterers, and customers with specific requirements). Average fruit and vegetable waste was 180 Kilogram per week per primary wholesaler and 30 Kilogram per secondary wholesaler. Based on this survey, the fruit and vegetable waste at wholesaler stage was estimated at about 286 tonnes per year. The secondary wholesalers distributed pre-ordered commodities, which minimized the potential to cause waste. Non-parametric test (Mann Whitney test) was carried out to assess contributions of wholesalers to waste generation. Over 56% of secondary wholesalers generally had nothing to bin as waste. Pearson’s correlation coefficient analysis showed positive correlation (r = 0.425; P=0.01) between the quantity of produce received and waste generated. Low market demand was the predominant reason identified by the wholesalers for waste generation. About a third of the wholesalers suggested that high cosmetic standards for fruits and vegetables - appearance, shape, and size - should be relaxed to reduce waste. Donation of unutilized fruits and vegetables to charity was overwhelmingly (95%) considered as one of the best options for utilization of discarded produce. The extent of waste at other stages of fruit and vegetable supply chain is currently being studied.

Keywords: food waste, fruits and vegetables, supply chain, waste generation

Procedia PDF Downloads 312

Authors: Efri Mardawati, Ronny Purwadi, Made Tri Ari Penia Kresnowati, Tjandra Setiadi

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EFB are mainly composed of cellulose (≈ 43%), hemicellulose (≈ 23%) and lignin (≈20%). The palm oil empty fruit bunches (EFB) is the lignosellulosic waste from crude palm oil industries mainly compose of (≈ 43%), hemicellulose (≈ 23%) and lignin (≈20%). Xylan, a polymer made of pentose sugar xylose and the most abundant component of hemicellulose in plant cell wall. Further xylose can be used as a raw material for production of a wide variety of chemicals such as xylitol, which is extensively used in food, pharmaceutical and thin coating applications. Currently, xylose is mostly produced from xylan via chemical hydrolysis processes. However, these processes are normally conducted at a high temperature and pressure, which is costly, and the required downstream processes are relatively complex. As an alternative method, enzymatic hydrolysis of xylan to xylose offers an environmentally friendly biotechnological process, which is performed at ambient temperature and pressure with high specificity and at low cost. This process is catalysed by xylanolytic enzymes that can be produced by some fungal species such as Aspergillus niger, Penicillium crysogenum, Tricoderma reseei, etc. Fungal that will be used to produce crude xylanase enzyme in this study is T. Viride ITB CC L.67. It is the purposes of this research to study the influence of pretreatment of EFB for the enzymatic hydrolysis process, optimation of temperature and pH of the hydrolysis process, the influence of substrate and enzyme concentration to the enzymatic hydrolysis process, the dynamics of hydrolysis process and followingly to study the kinetics of this process. Xylose as the product of enzymatic hydrolysis process analyzed by HPLC. The results show that the thermal pretreatment of EFB enhance the enzymatic hydrolysis process. The enzymatic hydrolysis can be well approached by the Michaelis Menten kinetic model, and kinetic parameters are obtained from experimental data.

Keywords: oil palm empty fruit bunches (EFB), xylose, enzymatic hydrolysis, kinetic modelling

Procedia PDF Downloads 389

Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting

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Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.

Keywords: deep learning, image processing, convolution neural network, YOLOv2, 7A6 series manipulator

Procedia PDF Downloads 250

Authors: Hami-Ziniman Revital, Ashwall Rachelly

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The conflict resolution realm has developed tremendously during the last half-decade. Three main approaches should be mentioned: an Alternative Dispute Resolution (ADR) suggesting processes such as Arbitration or Interests-based Negotiation was developed as an answer to obligations and rights-based conflicts. The Pragmatic mediation approach focuses on the gap between interests and needs of disputants. The Transformative mediation approach focusses on relations and suits identity-based conflicts. In the current study, we examine the conflictual relations between religious and non-religious Jews in Israel and the impact of three transformative mechanisms: Inter-group recognition, In-group empowerment and Value-based reframing on the relations between the participants. The research was conducted during four facilitated joint mediation classes. A unique finding was found. Using both transformative mechanisms and the Contact Hypothesis criteria, we identify transformation in participants’ relations and a considerable change from anger, alienation, and suspiciousness to an increased understanding, affection and interpersonal concern towards the out-group members. Intergroup Recognition, In-group empowerment, and Values-based reframing were the skills discovered as the main enablers of the change in the relations and the research participants’ fostered mutual recognition of the out-group values and identity-based issues. We conclude this transformation was possible due to a constant intergroup contact, based on the Contact Hypothesis criteria. In addition, as Interests-based mediation uses “Reframing” as a skill to acknowledge both mutual and opposite needs of the disputants, we suggest the use of “Value-based Reframing” in intergroup identity-based conflicts, as a skill contributes to the empowerment and the recognition of both mutual and different out-group values. We offer to implement those insights and skills to assist conflict resolution facilitators in various intergroup identity-based conflicts resolution efforts and to establish further research and knowledge.

Keywords: empowerment, identity-based conflict, intergroup recognition, intergroup relations, mediation skills, multi-cultural society, reframing, value-based recognition

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Authors: Samuel Mwangi, Josephine K. Mule

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Access control as a security technique regulates who or what can access resources. It is a fundamental concept in security that minimizes risks to the institutions that use access control. Regulating access to institutions of higher learning is key to ensure only authorized personnel and students are allowed into the institutions. The use of biometrics has been criticized due to the setup and maintenance costs, hygiene concerns, and trepidations regarding data privacy, among other apprehensions. Facial recognition is arguably a fast and accurate way of validating identity in order to guard protected areas. It guarantees that only authorized individuals gain access to secure locations while requiring far less personal information whilst providing an additional layer of security beyond keys, fobs, or identity cards. This exploratory study sought to investigate the use of facial recognition in controlling access in institutions of higher learning in Kenya. The sample population was drawn from both private and public higher learning institutions. The data is based on responses from staff and students. Questionnaires were used for data collection and follow up interviews conducted to understand responses from the questionnaires. 80% of the sampled population indicated that there were many security breaches by unauthorized people, with some resulting in terror attacks. These security breaches were attributed to stolen identity cases, where staff or student identity cards were stolen and used by criminals to access the institutions. These unauthorized accesses have resulted in losses to the institutions, including reputational damages. The findings indicate that security breaches are a major problem in institutions of higher learning in Kenya. Consequently, access control would be beneficial if employed to curb security breaches. We suggest the use of facial recognition technology, given its uniqueness in identifying users and its non-repudiation capabilities.

Keywords: facial recognition, access control, technology, learning

Procedia PDF Downloads 125

Authors: Shweta Pinjarkar, Shrutika Yawale, Mayuri Patil, Reshma Adagale

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Face recognition is the technique which can be applied to the wide variety of problems like image and film processing, human computer interaction, criminal identification etc. This has motivated researchers to develop computational models to identify the faces, which are easy and simple to implement. In this, demonstrates the face recognition system in android device using eigenface. The system can be used as the base for the development of the recognition of human identity. Test images and training images are taken directly with the camera in android device.The test results showed that the system produces high accuracy. The goal is to implement model for particular face and distinguish it with large number of stored faces. face recognition system detects the faces in picture taken by web camera or digital camera and these images then checked with training images dataset based on descriptive features. Further this algorithm can be extended to recognize the facial expressions of a person.recognition could be carried out under widely varying conditions like frontal view,scaled frontal view subjects with spectacles. The algorithm models the real time varying lightning conditions. The implemented system is able to perform real-time face detection, face recognition and can give feedback giving a window with the subject's info from database and sending an e-mail notification to interested institutions using android application. Face recognition is the technique which can be applied to the wide variety of problems like image and film processing, human computer interaction, criminal identification etc. This has motivated researchers to develop computational models to identify the faces, which are easy and simple to implement. In this , demonstrates the face recognition system in android device using eigenface. The system can be used as the base for the development of the recognition of human identity. Test images and training images are taken directly with the camera in android device.The test results showed that the system produces high accuracy. The goal is to implement model for particular face and distinguish it with large number of stored faces. face recognition system detects the faces in picture taken by web camera or digital camera and these images then checked with training images dataset based on descriptive features. Further this algorithm can be extended to recognize the facial expressions of a person.recognition could be carried out under widely varying conditions like frontal view,scaled frontal view subjects with spectacles. The algorithm models the real time varying lightning conditions. The implemented system is able to perform real-time face detection, face recognition and can give feedback giving a window with the subject's info from database and sending an e-mail notification to interested institutions using android application.

Keywords: face detection, face recognition, eigen faces, algorithm

Procedia PDF Downloads 361

Authors: Madihah Shukri

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Research examining whether eating behaviour is related to unhealthy or healthy eating pattern is required to explain the mechanisms underlying obesity, and to inform health intervention aim to prevent and treat obesity. The purpose of this study was to investigate the relationship between eating behaviours and nature of food consumption. Methods: This was a cross-sectional study of 588 adults (males = 231 and females = 357). The Dutch Eating Behaviour Questionnaire (DEBQ) was used to measure restrained, emotional and external eating. Nature of food consumption was assessed by self-reported consumption of fruit and vegetables, sweet food, junk food and snacking. Results: Results revealed that emotional eating was found to be the principal predictor of the consumption of less healthy food (sweet food, junk food and snacking), while external eating predicted sweet food intake. Intake of fruit and vegetable was associated with restrained eating. In light of the significant associations between eating behaviour and nature of food consumption, acknowledging individuals eating styles can have implications for tailoring effective nutritional programs in the context of obesity and chronic disease epidemic.

Keywords: eating behaviour, food consumption, adult, Malaysia

Procedia PDF Downloads 369

Authors: Violina R. Angelova, Sava G. Tabakov, Aleksander B. Peltekov, Krasimir I. Ivanov

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A field study was conducted to evaluate the chemical composition and quality of the Aronia fruits, as well as the possibilities of Aronia cultivation on soils contaminated with heavy metals. The experiment was performed on an agricultural field contaminated by the Non-Ferrous-Metal Works (NFMW) near Plovdiv, Bulgaria. The study included four varieties of Aronia; Aron variety, Hugin variety, Viking variety and Nero variety. The Aronia was cultivated according to the conventional technology on areas at a different distance from the source of pollution NFMW- Plovdiv (1 km, 3.5 km, and 15 km). The concentrations of macroelements, microelements, and heavy metals in Aronia fruits were determined. The dry matter content, ash, sugars, proteins, and fats were also determined. Aronia is a crop that is tolerant to heavy metals and can successfully be grown on soils contaminated with heavy metals. The increased content of heavy metals in the soil leads to less absorption of the nutrients (Ca, Mg and P) in the fruit of the Aronia. Soil pollution with heavy metals does not affect the quality of the Aronia fruit varieties.

Keywords: aronia, chemical composition, fruits, quality

Procedia PDF Downloads 204

Authors: Ajmal Khan Kassi, Humayun Javed, Syed Abdul Qadeem

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The study was conducted to find out the best management practices against American bollworm on Okra variety Arka Anamika during 2016. The three different management practices viz. Release of Trichogramma chilonis, hoeing and weeding, clipping and lufenuron insect growth regulator (IGR) which were tested individually and with all possible combinations for the controlling of American bollworm at 3 diverse areas viz. University Research Farm Koont, NARC and Farmer Field Taxila. All the treatment combinations regarding damage of fruit showed significant results. The minimum fruit infestation i.e. 3.20% and 3.58% was recorded with combined treatment (i.e. T. chilonis + hoeing + weeding + lufenuron) in two different localities. This combined treatment also resulted in maximum yield at NARC and Taxila i.e. 57.67 and 62.66 q/ha respectively. This treatment gave the best results to manage H. armigera. On the basis of different integrated pest management techniques, Arka Anamika variety proved to be comparatively resistant against H. armigera in different localities. So this variety is recommended for the cultivation in Pothwar region to get maximum yield.

Keywords: management, american bollworm, arka anamika, okra

Procedia PDF Downloads 55

Authors: Kamla Malik

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For ethanol production from paddy straw firstly pretreatment was done by using sodium hydroxide solution (2.0%) at 15 psi for 1 hr. The maximum lignin removal was achieved with 0.5 mm mesh size of paddy straw. It contained 72.4 % cellulose, 15.9% hemicelluloses and 2.0 % lignin after pretreatment. Paddy straw hydrolysate (PSH) with fruits wastes (5%), such as sweet lime, apple, sapota, grapes, kinnow, banana, papaya, mango, and watermelon were subjected to simultaneous saccharification and co-fermentation (SSCF) for 72 hrs by co-culture of Saccharomyces cerevisiae HAU-1 and Candida sp. with 0.3 % urea as a cheap nitrogen source. Fermentation was carried out at 35°C and determined ethanol yield at 24 hours interval. The maximum production of ethanol was produced within 72 hrs of fermentation in PSH + sapota peels (3.9% v/v) followed by PSH + kinnow peels (3.6%) and PSH+ papaya peels extract (3.1 %). In case of PSH+ banana peels and mango peel extract the ethanol produced were 2.8 % and 2.2 % (v/v). The results of this study suggest that wastes from fruits that contain fermentable sugar should not be discarded into our environment, but should be supplemented in paddy straw which converted to useful products like bio-ethanol that can serve as an alternative energy source.

Keywords: ethanol, fermentation, fruit wastes, paddy straw

Procedia PDF Downloads 390

Authors: Rishi Richa, N. C. Shahi, J. P. Pandey, S. S. Kautkar

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Citrus fruits rank third in area and production after banana and mango in India. Sweet oranges are the second largest citrus fruits cultivated in the country. Andhra Pradesh, Maharashtra, Karnataka, Punjab, Haryana, Rajasthan, and Uttarakhand are the main sweet orange-growing states. Citrus fruits occupy a leading position in the fruit trade of Uttarakhand, is casing about 14.38% of the total area under fruits and contributing nearly 17.75 % to the total fruit production. Malta is grown in most of the hill districts of the Uttarakhand. Malta common is having high acceptability due to its attractive colour, distinctive flavour, and taste. The excellent quality fruits are generally available for only one or two months. However due to its less shelf-life, Malta can not be stored for longer time under ambient conditions and cannot be transported to distant places. Continuous loss of water adversely affects the quality of Malta during storage and transportation. Method of picking, packaging, and cold storage has detrimental effects on moisture loss. The climatic condition such as ambient temperature, relative humidity, wind condition (aeration) and microbial attack greatly influences the rate of moisture loss and quality. Therefore, different agro-climatic zone will have different moisture loss pattern. The rate of moisture loss can be taken as one of the quality parameters in combination of one or more parameter such as RH, and aeration. The moisture contents of the fruits and vegetables determine their freshness. Hence, it is important to maintain initial moisture status of fruits and vegetable for prolonged period after the harvest. Keeping all points in views, effort was made to store Malta at ambient condition. In this study, the response surface method and experimental design were applied for optimization of independent variables to enhance the shelf life of four months stored malta. Box-Benkhen design, with, 12 factorial points and 5 replicates at the centre point were used to build a model for predicting and optimizing storage process parameters. The independent parameters, viz., scavenger (3, 4 and 5g), polythene thickness (75, 100 and 125 gauge) and fungicide concentration (100, 150 and 200ppm) were selected and analyzed. 5g scavenger, 125 gauge and 200ppm solution of fungicide are the optimized value for storage which may enhance life up to 4months.

Keywords: Malta fruit, scavenger, packaging, shelf life

Procedia PDF Downloads 280

Authors: Amna Jalal, Muhammad Dildar Gogi, Muhammad Jalal Arif, Anum Tariq, Waleed Afzal Naveed, Talha Farooq, Mubashir Iqbal, Muhammad Junaid Nisar

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Melon fruit flies (Diptera: Tephritidae: Dacinae) are economically important pests of the cucurbits and are geographically distributed throughout the tropics and subtropics of the world. It causes heavy quantitative and qualitative losses in bitter gourd. The present experiment was carried out to evaluate the performance of different biodegradable waxes based SPLAT-MAT-CL (Specialized Pheromone and Lure Application Technology-Male Anhelation Technique- Cue Lure) formulations in bitter gourd field. Fourteen SPLAT-MAT emulsions/formulations were prepared by admixing different SPLAT matrices with toxicant (spinosad) and sex pheromone cuelure (attractant) in different proportionate percentage by weight. The results revealed that attraction and trapping of fruit flies of B. cucurbitae varied significantly for different SPLAT-MAT-CL formulations (p < 0.05). The maximum B. cucurbitae males were trapped in SPLAT-MAT-CL-7 (60 flies/trap/day) followed by SPLAT-MAT-CL-9 (40 flies/trap/day). The performance of all other formulations of SPLAT-MAT-CL was found in the order of SPLAT-MAT-CL-8 (30 flies/trap/day) > SPLAT-MAT-CL-3 (28 flies/trap/day) > SPLAT-MAT-CL-5 (25 flies/trap/day) > SPLAT-MAT-CL-4 (22 flies/trap/day) > SPLAT-MAT-CL-12 (20 flies/trap/day) SPLAT-MAT-CL-2 (19 flies/trap/day) > SPLAT-MAT-CL-14 (17 flies/trap/day) > SPLAT-MAT-CL-13 (15 flies/trap/day) > SPLAT-MAT-CL-11 (10 flies/trap/day) > SPLAT-MAT-CL-1 (8 flies/trap/day) > SPLAT-MAT-CL-10 (02 flies/trap/day). Overall, all the SPLAT-MAT-CL formulations, except SPLAT-MAT-CL-10, demonstrated higher density of captures of B. cucurbitae males as compared to standard (06 flies/trap/day). The results also demonstrate that SPLAT-MAT-CL-7, SPLAT-MAT-CL-9, SPLAT-MAT-CL-8, SPLAT-MAT-CL-3, SPLAT-MAT-CL-5, SPLAT-MAT-CL-4, SPLAT-MAT-CL-12, SPLAT-MAT-CL-2, SPLAT-MAT-CL-14, SPLAT-MAT-CL-13, SPLAT-MAT-CL-11 and SPLAT-MAT-CL-1 explained approximately 5, 4.6, 4.1, 3.6, 3.3, 3.1,2.8,2.5 and 1.6 times higher captures of B. cucurbitae males over standards. However, SPLAT-MAT-CL-10 demonstrated 3 times fewer captures of B. cucurbitae males over standards. In conclusion, SPLAT-MAT-CL-7, SPLAT-MAT-CL-9 can be exploited for the monitoring and trapping of B. cucurbitae in its IPM of program.

Keywords: attractancy, field conditions, melon fruit fly, SPLAT-MAT-CL

Procedia PDF Downloads 268

Authors: El Sayed A. Sharara, A. Tsuji, K. Terada

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Call centers have been expanding and they have influence on activation in various markets increasingly. A call center’s work is known as one of the most demanding and stressful jobs. In this paper, we propose the fatigue detection system in order to detect burnout of call center agents in the case of a neck pain and upper back pain. Our proposed system is based on the computer vision technique combined skin color detection with the Viola-Jones object detector. To recognize the gesture of hand poses caused by stress sign, the YCbCr color space is used to detect the skin color region including face and hand poses around the area related to neck ache and upper back pain. A cascade of clarifiers by Viola-Jones is used for face recognition to extract from the skin color region. The detection of hand poses is given by the evaluation of neck pain and upper back pain by using skin color detection and face recognition method. The system performance is evaluated using two groups of dataset created in the laboratory to simulate call center environment. Our call center agent burnout detection system has been implemented by using a web camera and has been processed by MATLAB. From the experimental results, our system achieved 96.3% for upper back pain detection and 94.2% for neck pain detection.

Keywords: call center agents, fatigue, skin color detection, face recognition

Procedia PDF Downloads 294

Authors: James Rigor Camacho, Wansu Lim

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Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

Procedia PDF Downloads 105

Authors: Albandary Alamer, Noura Alaskar, Sana Bukhamseen, Jawaher Alkhamis, Enas Alghamdi, Almaha Almulhim, Hina Gull, Rachid Zagrouba, Madeeha Saqib

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A good and healthy seed will always produce a nice fruit, whereas an infected seed will produce an infected fruit. The same concept applies to the children, and the healthier the environment in which the kids grow, the more likely they become valuable members of society. Kiddo project introduces us to a mobile application that focuses on enhancing the sense of responsibility from a young age and makes raising kids fun and easy. The application aims to enhance the communication between parents and their children and to enrich the good habits of the kid. Kiddo Application enables kids to share their accomplishments with their peers in an interactive environment full of enjoyment, followed by parental monitoring to handle what their kids are posting and friends following. Kiddo provides the kids' and parents’ society with a safe platform free of cyberbullying and inappropriate content with parents' fun engagement.

Keywords: kids social media, educational app, child-raising, parental control, cyberbullying, parent-child relationship, good habits

Procedia PDF Downloads 158

Authors: Amin Pashaye Amiri

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Freedom of information, according to which the public has a right to have access to government-held information, is largely considered as a tool for improving transparency and accountability in governments, and as a requirement of self-governance and good governance. So far, more than ninety countries have recognized citizens’ right to have access to public information. This recognition often took place through the adoption of an act referred to as “freedom of information act”, “access to public records act”, and so on. A freedom of information act typically imposes a positive obligation on a government to initially and regularly release certain public information, and also obliges it to provide individuals with information they request. Such an act usually allows governmental bodies to withhold information only when it falls within a limited number of exemptions enumerated in the act such as exemptions for protecting privacy of individuals and protecting national security. Some steps have been taken at the national and international level towards the recognition of freedom of information as a human right. Freedom of information was recognized in a few countries as a part of freedom of expression, and therefore, as a human right. Freedom of information was also recognized by some international bodies as a human right. The Inter-American Court of Human Rights ruled in 2006 that Article 13 of the American Convention on Human Rights, which concerns the human right to freedom of expression, protects the right of all people to request access to government information. The European Court of Human Rights has recently taken a considerable step towards recognizing freedom of information as a human right. However, in spite of the measures that have been taken, public access to government information is not yet widely accepted as an international human right. The paper will consider the degree to which freedom of information has been recognized as a human right, and study the possibility of widespread recognition of such a human right in the future. It will also examine the possible benefits of such recognition for the development of the human right to free expression.

Keywords: freedom of information, freedom of expression, human rights, government information

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Authors: Sang-Keun Moon, Hong-Rok Lim, Jin-O Kim

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This paper presents a Power Quality (PQ) modeling and filtering processes for the distribution system disturbances using recognition learning methods. Typical PQ waveforms with mathematical applications and gathered field data are applied to the proposed models. The objective of this paper is analyzing PQ data with respect to monitoring, discriminating, and evaluating the waveform of power disturbances to ensure the system preventative system failure protections and complex system problem estimations. Examined signal filtering techniques are used for the field waveform noises and feature extractions. Using extraction and learning classification techniques, the efficiency was verified for the recognition of the PQ disturbances with focusing on interactive modeling methods in this paper. The waveform of selected 8 disturbances is modeled with randomized parameters of IEEE 1159 PQ ranges. The range, parameters, and weights are updated regarding field waveform obtained. Along with voltages, currents have same process to obtain the waveform features as the voltage apart from some of ratings and filters. Changing loads are causing the distortion in the voltage waveform due to the drawing of the different patterns of current variation. In the conclusion, PQ disturbances in the voltage and current waveforms indicate different types of patterns of variations and disturbance, and a modified technique based on the symmetrical components in time domain was proposed in this paper for the PQ disturbances detection and then classification. Our method is based on the fact that obtained waveforms from suggested trigger conditions contain potential information for abnormality detections. The extracted features are sequentially applied to estimation and recognition learning modules for further studies.

Keywords: power quality recognition, PQ modeling, waveform feature extraction, disturbance trigger condition, PQ signal filtering

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Authors: Sanja Seljan, Ivan Dunđer

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The paper presents combined automatic speech recognition (ASR) for English and machine translation (MT) for English and Croatian in the domain of business correspondence. The first part presents results of training the ASR commercial system on two English data sets, enriched by error analysis. The second part presents results of machine translation performed by online tool Google Translate for English and Croatian and Croatian-English language pairs. Human evaluation in terms of usability is conducted and internal consistency calculated by Cronbach's alpha coefficient, enriched by error analysis. Automatic evaluation is performed by WER (Word Error Rate) and PER (Position-independent word Error Rate) metrics, followed by investigation of Pearson’s correlation with human evaluation.

Keywords: automatic machine translation, integrated language technologies, quality evaluation, speech recognition

Procedia PDF Downloads 484

Authors: Ons Slimene, Aroua Taamallah, Maha Khemaja

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In recent years, human activity recognition (HAR) has been a key area of research due to its diverse applications. It has garnered increasing attention in the field of computer vision. HAR plays an important role in people’s daily lives as it has the ability to learn advanced knowledge about human activities from data. In HAR, activities are usually represented by exploiting different types of sensors, such as embedded sensors or visual sensors. However, these sensors have limitations, such as local obstacles, image-related obstacles, sensor unreliability, and consumer concerns. Recently, several deep learning-based approaches have been proposed for HAR and these approaches are classified into two categories based on the type of data used: vision-based approaches and sensor-based approaches. This research paper highlights the importance of multimodal data fusion from skeleton data obtained from videos and data generated by embedded sensors using deep neural networks for achieving HAR. We propose a deep multimodal fusion network based on a twostream architecture. These two streams use the Convolutional Neural Network combined with the Bidirectional LSTM (CNN BILSTM) to process skeleton data and data generated by embedded sensors and the fusion at the feature level is considered. The proposed model was evaluated on a public OPPORTUNITY++ dataset and produced a accuracy of 96.77%.

Keywords: human activity recognition, action recognition, sensors, vision, human-centric sensing, deep learning, context-awareness

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Authors: Hong Li, Tingxian Li, Xudong Wang, Fengliang Zhao

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Unreliable flowering of chilling-required longan (Dimocarpus longan) due to increased air-temperatures have been the common concerns in the tropical areas. Our objectives were to assess the efficiency of chemicals in longan tree flowering and bearing using Growing Degree Days (GDD). The 2-year study was contacted in the tropical Haihan Island during 2012-2013. At pruning (August) the GDD values were started to count. The KClO3 treatments were applied to the root zones under the canopies at GDD 1300ºC while KH2PO4 rates were applied to the leaves at fruit setting at GDD 3000ºC and GDD 4000ºC. The results showed that total cumulative GDD was 6050ºC for longan. The GDD-guided KClO3 applications induced significant tree budding and flowering. The GDD-guided KH2PO4 applications stimulated higher leaf photosynthesis, carbonxylation efficiency, marketable fruit yield and quality (K+ and sugar) (P<0.05). It was concluded that the GDD-based model could efficiently support longan reliable flowering and bearing.

Keywords: canopy nutrition, flowering induction, growing degree days, longan, oxidant KClO3, tree physiology

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Authors: Yan Li, Qingxiang Meng, Bo Zhou, Zhenming Zhou

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The objective of this study was to compare the effects of ensiled mulberry leaves (EML), and sun-dried mulberry fruit pomace (SMFP) on fecal bacterial communities in Simmental crossbred finishing steers fed the following 3 diets: a standard TMR diet, standard diet containing EML and standard diet containing SMFP, and the diets had similar protein and energy levels. Bacterial communities in the fecal content were analyzed using Illumina Miseq sequencing of the V4 region of the 16S rRNA gene amplification. Quantitative real-time PCR was used to detect the selected bacterial species in the feces. Most of the sequences were assigned to phyla Firmicutes (56.67%) and Bacteroidetes(35.90%), followed by Proteobacteria(1.86%), Verrucomicrobia(1.80%) and Tenericutes(1.37%). And the predominant genera included the 5-7N15 (5.91%), CF231 (2.49%), Oscillospira (2.33%), Paludibacter (1.23%) and Akkermansia(1.11%). As for the treatments, no significant differences were observed in Firmicutes (p = 0.28), Bacteroidetes (p = 0.63), Proteobacteria (p = 0.46), Verrucomicrobia (p = 0.17) and Tenericutes (p = 0.75). On the genus level, classified genera with high abundance (more than 0.1%) mainly came from two phyla: Bacteroidetes and Firmicutes. Also no differences were observed in most genera level, 5-7N15 (p = 0.21), CF231 (p = 0.62), Oscillospira (p = 0.9), Paludibacter (p = 0.33) and Akkermansia (p = 0.37), except that rc4-4 were lower in the CON and SMFP groups compared to the EML animals (p = 0.02). Additionally, there were no differences in richness estimate and diversity indices (p > 0.16), and treatments had no significant effect on most selected bacterial species in the fecal (p > 0.06), except that Ruminococcus albus were higher in the EML group (p < 0.01) and Streptococcus bovis were lower in the CON group (p < 0.01). In conclusion, diets supplemented with EML and SMFP have little influence on fecal bacterial community composition in finishing steers.

Keywords: fecal bacteria community composition, sequencing, ensiled mulberry leaves (EML), sun-dried mulberry fruit pomace (SMFP)

Procedia PDF Downloads 323

Authors: Tuiana A. Aiusheeva, Sergey S. Tamozhnikov, Alexander E. Saprygin, Arina A. Antonenko, Valentina V. Stepanova, Natalia N. Tolstykh, Alexander N. Savostyanov

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Situation of choice is an important condition for the formation of essential character qualities of a child, such as being initiative, responsible, hard-working. We have studied the behavioral and EEG reactions in Russian schoolchildren during recognition of syntactic errors in emotionally colored sentences that describe the choice situation. Twenty healthy children (mean age 9,0±0,3 years, 12 boys, 8 girls) were examined. Forty sentences were selected for the experiment; the half of them contained a syntactic error. The experiment additionally had the hidden condition: 50% of the sentences described the children's own choice and were emotionally colored (positive or negative). The other 50% of the sentences described the forced-choice situation, also with positive or negative coloring. EEG were recorded during execution of error-recognition task. Reaction time and quality of syntactic error detection were chosen as behavioral measures. Event-related spectral perturbation (ERSP) was applied to characterize the oscillatory brain activity of children. There were two time-frequency intervals in EEG reactions: (1) 500-800 ms in the 3-7 Hz frequency range (theta synchronization) and (2) 500-1000 ms in the 8-12 Hz range (alpha desynchronization). We found out that behavioral and brain reactions in child brain during recognition of positive and negative sentences describing forced-choice situation did not have significant differences. Theta synchronization and alpha desynchronization were stronger during recognition of sentences with children's own choice, especially with negative coloring. Also, the quality and execution time of the task were higher for this types of sentences. The results of our study will be useful for improvement of teaching methods and diagnostics of children affective disorders.

Keywords: choice situation, electroencephalogram (EEG), emotionally colored sentences, schoolchildren

Procedia PDF Downloads 269

Authors: Yalong Jiang, Zheru Chi

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In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, convolutional neural network, capsule network, capacity optimization, character recognition, data augmentation, semantic segmentation

Procedia PDF Downloads 153

Authors: A. M. Attalla, A. F. lbrahim, Laila Y. Mostaffa

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This study was conducted during three seasons 2010, 2011 and 2012 on Zahhloul date palm cultivar grown in calcareous soil, Alexandria governorate, Egypt. The palms received recommended dose of mineral N only or plus different rates of organic N with or without bio fertilizer to study the effect of such treatments on date palm yield and fruit nitrate and nitrite content due to its negative influence on human, animal and environment. The obtained results clarified that all used treatments of organic and bio fertilizers were effective in improving date palm yield and decreased fruit content of NO2 and NO3 in comparison with 100 % mineral N. It was also noticed that combined treatments of 50 % mineral N + 50 % organic manure with bio fertilizer is the superior treatments for increasing the values of yield and decreasing its content of NO2 and NO3. Hence, it could be concluded that, minimizing the use of chemical nitrogen fertilizer to half of recommended dose through addition of 50 % mineral N + 50 % organic manure with bio fertilizer and also, the utilization of organic and bio fertilizers is considered as a promising alternative for chemical fertilizers to avoid pollution and reduce the costs of mineral fertilizers.

Keywords: organic and bio fertilizers, mineral fertilizer, nitrate, nitrite, zaghloul date palm cv

Procedia PDF Downloads 449

Authors: Xiaoxiao Li, Shuangcheng Jia, Qian Li

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Keypoint detection has always been a challenge in the field of image recognition. This paper proposes a novelty keypoint detection method which is called Multi-Scale Feature Fusion Convolutional Network with Attention (MFFCNA). We verified that the multi-scale features with the attention mechanism module have better feature expression capability. The feature fusion between different scales makes the information that the network model can express more abundant, and the network is easier to converge. On our self-made street sign corner dataset, we validate the MFFCNA model with an accuracy of 97.8% and a recall of 81%, which are 5 and 8 percentage points higher than the HRNet network, respectively. On the COCO dataset, the AP is 71.9%, and the AR is 75.3%, which are 3 points and 2 points higher than HRNet, respectively. Extensive experiments show that our method has a remarkable improvement in the keypoint recognition tasks, and the recognition effect is better than the existing methods. Moreover, our method can be applied not only to keypoint detection but also to image classification and semantic segmentation with good generality.

Keywords: keypoint detection, feature fusion, attention, semantic segmentation

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Authors: Amandeep Kaur, Sangeeta Sharma

Abstract:

Keeping in view the serious entanglement of heavy metals ( Pb+2 and Ni+2) ions in an aqueous environment, a rapid search for efficient adsorbents for the adsorption of heavy metals has become highly desirable. In this quest, green synthesized Fe np’s have gathered attention because of their excellent adsorption capability of heavy metals from aqueous solution. This research report aims at the fabrication of Fe np’s using the fruit Cucumis melo and leaves of Ficus virens via a biogenic synthesis route. Further, synthesized CM-Fe-np’s and FV-Fe-np’s have been tested as potential bio-adsorbents for the removal of Pb+2 and Ni+2 by carrying out adsorption batch experiments. The influence of myriad parameters like initial concentration of Pb/Ni (5,10,15,20,25 mg/L), contact time (10 to 200 min.), adsorbent dosage (0.5, 0.10, 0.15 mg/L), shaking speed (120 to 350 rpm) and pH value (6,7,8,9) has been investigated. The maximum removal with CM-Fe-np’s and FV-Fe-np’s has been achieved at pH 7, metal conc. 5 mg/L, dosage 0.9 g/L, shaking speed 200 rpm and reaction contact time 200 min during the adsorption experiment. The results obtained are found to be in accordance with Freundlich and Langmuir's adsorption models; consequently, they could be highly applicable to the wastewater treatment plant.

Keywords: adsorption, biogenic synthesis, nanoparticles, nickel, lead

Procedia PDF Downloads 87

Authors: Khadijat T. Bamigbade, Olufade F. W. Onifade

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The field of automatic facial expression analysis has been an active research area in the last two decades. Its vast applicability in various domains has drawn so much attention into developing techniques and dataset that mirror real life scenarios. Many techniques such as Local Binary Patterns and its variants (CLBP, LBP-TOP) and lately, deep learning techniques, have been used for facial expression recognition. However, the problem of occlusion has not been sufficiently handled, making their results not applicable in real life situations. This paper develops a simple, yet highly efficient method tagged Local Binary Pattern-Histogram of Gradient (LBP-HOG) with occlusion detection in face image, using a multi-class SVM for Action Unit and in turn expression recognition. Our method was evaluated on three publicly available datasets which are JAFFE, CK, SFEW. Experimental results showed that our approach performed considerably well when compared with state-of-the-art algorithms and gave insight to occlusion detection as a key step to handling expression in wild.

Keywords: automatic facial expression analysis, local binary pattern, LBP-HOG, occlusion detection

Procedia PDF Downloads 169