Search results for: plant detection

Authors: Mohammadreza Judaki, Hosein Mohammadnezhad Shourkaei

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Usually, noise generated by industrial units, is a pollution and disturbs people and causes problems for human health and sometimes these units will be closed because they cannot eliminate this pollution. Small-scale power plants usually are built close to residential areas, and noise generated by these power plants is an important factor in choosing their location and their design. Materials used to reduce noise are studied by measuring their absorption and reflection index numerically and experimentally. We can use MIKI model (Yasushi Miki, 1990) to simulate absorption index by using software like Ansys or Soundflow and compare calculation results with experimental simulation data. We consider high frequency sounds of power plant engines octave band diagram because dB value of high frequency noise is more noticeable for human ears. To prove this, in this study we first will study calculating octave band of engines exhausts and then we will study acoustic behavior of materials that we will use in high frequencies and this will give us our optimum noise reduction plan.

Keywords: acoustic materials, eliminating engine noise, octave level diagram, power plant noise

Procedia PDF Downloads 138

Authors: B. J. Sonani, J. K. Ratnadhariya, Srinivas Palanki

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Cryogenic engineering is the fast growing branch of the modern technology. There are various applications of the cryogenic engineering such as liquefaction in gas industries, metal industries, medical science, space technology, and transportation. The low-temperature technology developed superconducting materials which lead to reduce the friction and wear in various components of the systems. The liquid oxygen, hydrogen and helium play vital role in space application. The liquefaction process is produced very low temperature liquid for various application in research and modern application. The air liquefaction system for oxygen plants in gas industries is based on the Claude cycle. The effect of process parameters on the overall system is difficult to be analysed by manual calculations, and this provides the motivation to use process simulators for understanding the steady state and dynamic behaviour of such systems. The parametric study of this system via MATLAB simulations provide useful guidelines for preliminary design of air liquefaction system based on the Claude cycle. Every organization is always trying for reduce the cost and using the optimum performance of the plant for the staying in the competitive market.

Keywords: cryogenic, liquefaction, low -temperature, oxygen, claude cycle, optimization, MATLAB

Procedia PDF Downloads 318

Authors: Zahia Aliche, Fatiha Boudjema, Benyoucef Khelidj, Selma Mettai, Zohra Bouriahi, Saliha Mohammed Belkebir, Ridha Mazouz

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The purpose of this work is the study of the viscoelastic behaviour formulating gels based plant extractions. The extracts of Zingibar officinale and Cinnamomum cassia were included in the gel at different concentrations of these plants in order to be applied in anti-inflammatory drugs. The yield of ethanolic extraction of Zingibar o. is 3.98% and for Cinnamomum c., essential oil by hydrodistillation is 1.67 %. The ethanolic extract of Zingibar.o, the essential oil of Cinnamomum c. and the mixture showed an anti-DPPH radicals’ activity, presented by EC50 values of 11.32, 13.48 and 14.39 mg/ml respectively. A gel based on different concentrations of these extracts was prepared. Microbiological tests conducted against Staphylococcus aureus and Escherichia colishowed moderate inhibition of Cinnamomum c. gel and less the gel based on Cinnamomum c./ Zingibar o. (20/80). The yeast Candida albicansis resistant to gels. The viscoelastic formulation property was carried out in dynamic and creep and modeled with the Kelvin-Voigt model. The influence of some parameters on the stability of the gel (time, temperature and applied stress) has been studied.

Keywords: Cinnamomum cassia, Zingibar officinale, antioxidant activity, antimicrobien activity, gel, viscoelastic behaviour

Procedia PDF Downloads 81

Authors: Rosna Mat Taha, Sakinah Abdullah, Sadegh Mohajer, Asmah Awal

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Lycium barbarum L. (Goji) belongs to Solanaceae family and native to some areas of China. Ethnobotanical studies have shown that this plant has been consumed by the Chinese since ancient times. It has been used as medicine in providing excellent effects on cardiovascular system and cholesterol level, besides contains high antioxidant and antidiabetic properties. In the present study, some tissue culture work has been carried out to induce callus, in vitro regeneration from various explants of Goji and also some acclimatization protocols were followed to transfer the regenerated plants to soil. The main aims being to establish high efficient regeneration system for mass production and commercialization for future uses, since the growth of this species is very limited in Malaysia. The optimum hormonal regime and the most suitable and responsive explants were identified. It was found that leaves and stems gave good responses. Murashige and Skoog’s (MS) medium supplemented with 2.0 mg/L NAA and 0.5 mg/L BAP was the best for callus induction and MS media fortified with 1.0 mg/L NAA and 1.0 mg/L BAP was optimum for in vitro regeneration. The survival rates of plantlets after acclimatization was 63±1.5 % on black soil and 50±1.3 % on mixed soil (combination of black and red soil at a ratio of 2 to 1), respectively.

Keywords: callus, acclimatization, in vitro culture, regeneration

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Authors: Akila Murali, Prithika Manivel

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Disasters are defined as a serious disruption of the functioning of a community or a society, which involves widespread human, material, economic or environmental impacts. The number of people suffering food crisis as a result of natural disasters has tripled in the last thirty years. The economic losses due to natural disasters have shown an increase with a factor of eight over the past four decades, caused by the increased vulnerability of the global society, and also due to an increase in the number of weather-related disasters. Efficient disaster detection and alerting systems could reduce the loss of life and properties. In the event of a disaster, another important issue is a good search and rescue system with high levels of precision, timeliness and safety for both the victims and the rescuers. Wireless Sensor Networks technology has the capability of quick capturing, processing, and transmission of critical data in real-time with high resolution. This paper studies the capacity of sensors and a Wireless Sensor Network to collect, collate and analyze valuable and worthwhile data, in an ordered manner to help with disaster management.

Keywords: alerting systems, disaster detection, Ad Hoc network, WSN technology

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Authors: Julia Ive, Lucia Specia

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Understanding and detecting toxicity is an important problem to support safer human interactions online. Our work focuses on the important problem of contextual toxicity detection, where automated classifiers are tasked with determining whether a short textual segment (usually a sentence) is toxic within its conversational context. We use “toxicity” as an umbrella term to denote a number of variants commonly named in the literature, including hate, abuse, offence, among others. Detecting toxicity in context is a non-trivial problem and has been addressed by very few previous studies. These previous studies have analysed the influence of conversational context in human perception of toxicity in controlled experiments and concluded that humans rarely change their judgements in the presence of context. They have also evaluated contextual detection models based on state-of-the-art Deep Learning and Natural Language Processing (NLP) techniques. Counterintuitively, they reached the general conclusion that computational models tend to suffer performance degradation in the presence of context. We challenge these empirical observations by devising better contextual predictive models that also rely on NLP data augmentation techniques to create larger and better data. In our study, we start by further analysing the human perception of toxicity in conversational data (i.e., tweets), in the absence versus presence of context, in this case, previous tweets in the same conversational thread. We observed that the conclusions of previous work on human perception are mainly due to data issues: The contextual data available does not provide sufficient evidence that context is indeed important (even for humans). The data problem is common in current toxicity datasets: cases labelled as toxic are either obviously toxic (i.e., overt toxicity with swear, racist, etc. words), and thus context does is not needed for a decision, or are ambiguous, vague or unclear even in the presence of context; in addition, the data contains labeling inconsistencies. To address this problem, we propose to automatically generate contextual samples where toxicity is not obvious (i.e., covert cases) without context or where different contexts can lead to different toxicity judgements for the same tweet. We generate toxic and non-toxic utterances conditioned on the context or on target tweets using a range of techniques for controlled text generation(e.g., Generative Adversarial Networks and steering techniques). On the contextual detection models, we posit that their poor performance is due to limitations on both of the data they are trained on (same problems stated above) and the architectures they use, which are not able to leverage context in effective ways. To improve on that, we propose text classification architectures that take the hierarchy of conversational utterances into account. In experiments benchmarking ours against previous models on existing and automatically generated data, we show that both data and architectural choices are very important. Our model achieves substantial performance improvements as compared to the baselines that are non-contextual or contextual but agnostic of the conversation structure.

Keywords: contextual toxicity detection, data augmentation, hierarchical text classification models, natural language processing

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Authors: Amira Racha Ben Yakoub, Ali Ferchichi

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In order to investigate the impact of sowing time on growth parameters, the length of the development cycle and yield of tossa jute (Corchorus olitorius L.), a field experiment was conducted from March to May 2011 at the Laboratoire d’Aridoculture et Cultures Oasiennes, ‘Institut des Régions Arides de Médénine’, Tunisia. Results of the experiment revealed that the early sowing (the middle of March, the beginning of April) induced a cycle of more than 100 days to reach the stage maturity and generates a marked drop in production. This period of plantation affects plant development and leads to a sharp drop in performance marked primarily by a reduction in growth, number and size of leaves, number of flowers and pods and weight of different parts of plant. Sowing from the end of April seems appropriate for shortening the development cycle and better profitability than the first two dates. Seeding of C. olitorius during May enhance the development of plants more dense, which explains the superiority of production marked by the increase of seed yield and leaf fresh and dry weight of this leafy vegetables.

Keywords: tossa jute (Corchorus olitorius L), sowing date, growth, yield

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Authors: Abrahão S. Fontes, Carlos A. V. Cardoso, Levi P. B. Oliveira

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The induction motors are used worldwide in various industries. Several maintenance techniques are applied to increase the operating time and the lifespan of these motors. Among these, the predictive maintenance techniques such as Motor Current Signature Analysis (MCSA), Motor Square Current Signature Analysis (MSCSA), Park's Vector Approach (PVA) and Park's Vector Square Modulus (PVSM) are used to detect and diagnose faults in electric motors, characterized by patterns in the stator current frequency spectrum. In this article, these techniques are applied and compared on a real motor, which has the fault of eccentricity in the air-gap. It was used as a theoretical model of an electric induction motor without fault in order to assist comparison between the stator current frequency spectrum patterns with and without faults. Metrics were purposed and applied to evaluate the sensitivity of each technique fault detection. The results presented here show that the above techniques are suitable for the fault of eccentricity in the air gap, whose comparison between these showed the suitability of each one.

Keywords: eccentricity in the air-gap, fault diagnosis, induction motors, predictive maintenance

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Authors: Leydi Noemi Peraza Gómez, Jose Álvarez Nemegyei, Damaris Francis Estrella Castillo

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In order to have an epidemiological tool to detect biomechanical stress (ERGO-Mex), which impose physical labor or recreational activities, a questionnaire is constructed in Spanish, validated and culturally adapted to the Mayan indigenous population of Yucatan. Through the seven steps proposed by Guillemin and Beaton the procedure was: initial translation, synthesis of the translations, feed back of the translation. After that review by a committee of experts, pre-test of the preliminary version, and presentation of the results to the committee of experts and members of the community. Finally the evaluation of its internal validity (Cronbach's α coefficient) and external (intraclass correlation coefficient). The results for the validation in Spanish indicated that 45% of the participants have biomechanical stress. The ERGO-Mex correlation was 0.69 (p <0.0001). Subjects with high biomechanical stress had a higher score than subjects with low biomechanical stress (17.4 ± 8.9 vs.9.8 ± 2.8, p = 0.003). The Cronbach's α coefficient was 0.92; and for validation in Cronbach's α maya it was 0.82 and CCI = 0.70 (95% CI: 0.58-0.79; p˂0.0001); ERGO-Mex is suitable for performing early detection of musculoskeletal diseases and helping to prevent disability.

Keywords: biomechanical stress, disability, musculoskeletal disorders, prevention

Procedia PDF Downloads 172

Authors: Kripesh Adhikari, Hamid Bouchachia, Hammadi Nait-Charif

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Falls are one of the major causes of injury and death among elderly people aged 65 and above. A support system to identify such kind of abnormal activities have become extremely important with the increase in ageing population. Pose estimation is a challenging task and to add more to this, it is even more challenging when pose estimations are performed on challenging poses that may occur during fall. Location of the body provides a clue where the person is at the time of fall. This paper presents a vision-based tracking strategy where available joints are grouped into three different feature points depending upon the section they are located in the body. The three feature points derived from different joints combinations represents the upper region or head region, mid-region or torso and lower region or leg region. Tracking is always challenging when a motion is involved. Hence the idea is to locate the regions in the body in every frame and consider it as the tracking strategy. Grouping these joints can be beneficial to achieve a stable region for tracking. The location of the body parts provides a crucial information to distinguish normal activities from falls.

Keywords: fall detection, machine learning, deep learning, pose estimation, tracking

Procedia PDF Downloads 182

Authors: Atuhurra Jesse, N'guessan Yves-Roland Douha, Pabitra Lenka

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The detection of diseases within plants has attracted a lot of attention from computer vision enthusiasts. Despite the progress made to detect diseases in many plants, there remains a research gap to train image classifiers to detect the cacao swollen shoot virus disease or CSSVD for short, pertinent to cacao plants. This gap has mainly been due to the unavailability of high quality labeled training data. Moreover, institutions have been hesitant to share their data related to CSSVD. To fill these gaps, image classifiers to detect CSSVD-infected cacao plants are presented in this study. The classifiers are based on VGG16, ResNet50 and Vision Transformer (ViT). The image classifiers are evaluated on a recently released and publicly accessible KaraAgroAI Cocoa dataset. The best performing image classifier, based on ResNet50, achieves 95.39\% precision, 93.75\% recall, 94.34\% F1-score and 94\% accuracy on only 20 epochs. There is a +9.75\% improvement in recall when compared to previous works. These results indicate that the image classifiers learn to identify cacao plants infected with CSSVD.

Keywords: CSSVD, image classification, ResNet50, vision transformer, KaraAgroAI cocoa dataset

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Authors: Contimi Kenfack Mouafo, Sebastian Klick

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In the rural and remote areas of Cameroon, access to electricity is very limited since most of the population is not connected to the main utility grid. Throughout the country, efforts are underway to not only expand the utility grid to these regions but also to provide reliable off-grid access to electricity. The Cameroonian company Solahydrowatt is currently working on the design and planning of one of the first hybrid solar-hydropower plants of Cameroon in Fotetsa, in the western region of the country, to provide the population with reliable access to electricity. This paper models and proposes a design for the low-voltage network with a hybrid solar-hydropower plant in Fotetsa. The modelling takes into consideration the voltage compliance of the distribution network, the maximum load of operating equipment, and most importantly, the ability for the network to operate as an off-grid system. The resulting modelled distribution network does not only comply with the Cameroonian voltage deviation standard, but it is also capable of being operated as a stand-alone network independent of the main utility grid.

Keywords: Cameroon, rural electrification, hybrid solar-hydro, off-grid electricity supply, network simulation

Procedia PDF Downloads 117

Authors: Efe Ogidiaka-Obende, Gabriel C. C. Ndinwa, John Atadiose, Ewoma O. Oduma

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Water hyacinth (Eichhornia crassipes), which is a native of South America, is believed to have found its way into Nigeria waters through Pot-Novo creek, Benin Republic, in September 1984. This study attempts to review the impacts, challenges, and prospects of water hyacinths in Nigeria's coastal waters. Water hyacinth possesses a very high proliferation rate, and its infestation in Nigeria's coastal waters poses severe problems to the fishing, recreational, transportation, and health sector, amongst other activities. The weed has been reported to disrupt aquatic ecosystems, clog waterways, and create associated problems with water supply, irrigation, and drainage. To curb this menace, a huge amount of money is used yearly for its management, which is not sustainable. There is, however, a positive twist to this plant as it has the potential to be used as fertilizers, feed for fish, craft materials, biogas, and many more. Due to its high population and related economic importance and implications in Nigeria's coastal waters, it is highly recommended that more research works be carried out on the of making optimal use of this plant.

Keywords: waste to wealth, environmental pollution, water hyacinth, biogas, sustainable development goals

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Authors: K. Sunitra, T. Srisuda

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Centella asiatica, asiatic pennywort is a medicinal herb plant used widely which held in herbal health care group. The problem of asiatic pennywort production is the outbreak of Sclerotium rolfsii causing a damp-off disease which caused plant stem turn yellowish, finally they begin to die and result in extremely damaging to growers. Therefore, the studies were caried out to control damping off with Trichoderma sp., Bacillus subtilis and fermented banana as compared to the control to suppress with bi-culture under the laboratory condition. It was found that Trichoderma harzianum showed the highest percentage of inbihition, 69.44%. The pot experiments in greenhouse condition showed that chemical had minimum of damping-off (31.54%) and highest yield (1.20 tons/rai) and following by Trichoderma harzianum and Bacillus subtilis treatment. Due to the chemical usage leaving toxic residues on plants and affect the human bodies. Trichoderma harzianum and Bacillus subtilis should be considered as alternatives which have percent of damp-off disease and yields as follows: 45.50 and 43.75%, and 1.12 and 1.09 tons/rai, respectively. These two products are known that they have no health risk for growers and consumers in the future.

Keywords: Centella asiatica, Sclerotium rolfsii, Trichoderma harzianum, Bacillus subtilis

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Authors: L. Meksem Amara, M. Ferfar, N. Meksem, M. R. Djebar

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The wheat is the cereal the most consumed in the world. In Algeria, the production of this cereal covers only 20 in 25 % of the needs for the country, the rest being imported. To improve the efficiency and the productivity of the durum wheat, the farmers turn to the use of pesticides: weed-killers, fungicides and insecticides. However this use often entrains losses of products more at least important contaminating the environment and all the food chain. Weed-killers are substances developed to control or destroy plants considered unwanted. That they are natural or produced by the human being (molecule of synthesis), the absorption and the metabolization of weed-killers by plants cause the death of these plants. In this work, we set as goal the evaluation of the effect of a weed-killer sulfonylurea, the CossackOD with various concentrations (0, 2, 4 and 9 µg) on variety of Triticum durum: Cirta. We evaluated the plant growth by measuring the leaves and root length, compared with the witness as well as the content of proline and analyze the level of one of the antioxydative enzymes: catalase, after 14 days of treatment. Sulfonylurea is foliar and root weed-killers inhibiting the acetolactate synthase: a vegetable enzyme essential to the development of the plant. This inhibition causes the ruling of the growth then the death. The obtained results show a diminution of the average length of leaves and roots this can be explained by the fact that the ALS inhibitors are more active in the young and increasing regions of the plant, what inhibits the cellular division and talks a limitation of the foliar and root’s growth. We also recorded a highly significant increase in the proline levels and a stimulation of the catalase activity. As a response to increasing the herbicide concentrations a particular increases in antioxidative mechanisms in wheat cultivar Cirta suggest that the high sensitivity of Cirta to this sulfonylurea herbicide is related to the enhanced production and oxidative damage of reactive oxygen species.

Keywords: sulfonylurea, triticum durum, oxydative stress, toxicity

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Authors: Seonaid Hume, Gordon Dobie, Graeme West

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Detecting and localizing radioactive sources is a necessity for safe and secure decommissioning of nuclear facilities. An important aspect for the management of the sort-and-segregation process is establishing the spatial distributions and quantities of the waste radionuclides, their type, corresponding activity, and ultimately classification for disposal. The data received from surveys directly informs decommissioning plans, on-site incident management strategies, the approach needed for a new cell, as well as protecting the workforce and the public. Manual classification of nuclear waste from a nuclear cell is time-consuming, expensive, and requires significant expertise to make the classification judgment call. Also, in-cell decommissioning is still in its relative infancy, and few techniques are well-developed. As with any repetitive and routine tasks, there is the opportunity to improve the task of classifying nuclear waste using autonomous systems. Hence, this paper proposes a new framework for the automatic classification of nuclear waste. This framework consists of five main stages; 3D spatial mapping and object detection, object classification, radiological mapping, source localisation based on gathered evidence and finally, waste classification. The first stage of the framework, 3D visual mapping, involves object detection from point cloud data. A review of related applications in other industries is provided, and recommendations for approaches for waste classification are made. Object detection focusses initially on cylindrical objects since pipework is significant in nuclear cells and indeed any industrial site. The approach can be extended to other commonly occurring primitives such as spheres and cubes. This is in preparation of stage two, characterizing the point cloud data and estimating the dimensions, material, degradation, and mass of the objects detected in order to feature match them to an inventory of possible items found in that nuclear cell. Many items in nuclear cells are one-offs, have limited or poor drawings available, or have been modified since installation, and have complex interiors, which often and inadvertently pose difficulties when accessing certain zones and identifying waste remotely. Hence, this may require expert input to feature match objects. The third stage, radiological mapping, is similar in order to facilitate the characterization of the nuclear cell in terms of radiation fields, including the type of radiation, activity, and location within the nuclear cell. The fourth stage of the framework takes the visual map for stage 1, the object characterization from stage 2, and radiation map from stage 3 and fuses them together, providing a more detailed scene of the nuclear cell by identifying the location of radioactive materials in three dimensions. The last stage involves combining the evidence from the fused data sets to reveal the classification of the waste in Bq/kg, thus enabling better decision making and monitoring for in-cell decommissioning. The presentation of the framework is supported by representative case study data drawn from an application in decommissioning from a UK nuclear facility. This framework utilises recent advancements of the detection and mapping capabilities of complex radiation fields in three dimensions to make the process of classifying nuclear waste faster, more reliable, cost-effective and safer.

Keywords: nuclear decommissioning, radiation detection, object detection, waste classification

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Authors: Dawit Chankaye

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Background: Azadirachta indica is the most versatile medicinal plant known as “the village pharmacy”. The plant is known for its broad spectrum of biological activity in India and various countries throughout history by many different human cultures. The present study was undertaken to determine the antimalarial and antidiabetic properties of the leaf extracts of A. indica grown in Ethiopia when treated in vivo. This work has also been concerned with determining essential oil composition and the antimicrobial activity of the plant in vitro. Methods: Leaf extracts were prepared using three different selected solvents. Standard and clinical isolates were treated with extracts of the leaves of A. indica using the agar well diffusion method. The antimalarial and antidiabetic tests were conducted in vivo in mice. Phytochemical screening was done using various chemical tests, and the volatile oil constituents were determined using gas chromatography-mass spectrometry (GC/MS). Results: In vivo antimalarial activity studies showed 85.23%, 69.01%, and 81.54% suppression of parasitemia for 70% ethanol, acetone, and water extracts, respectively. The extracts collected from the leaves also showed reduced blood sugar levels in alloxan-induced diabetic mice. In addition, the solvent extracts were shown to have an inhibitory effect on the growth of microorganisms under the study. The minimum inhibitory concentration (MIC) ranged from 850 to 1050 µg/ml. Notably, the phytochemical investigation of the ethanol extracts showed the presence of secondary metabolites. Seventeen compounds (mainly sesquiterpenes) that represent 75.45% of the essential oil were characterized by GC/MS analysis. Conclusion: Extracts examined in this study indicated that the leaf of A. indica grown in Ethiopia retained the biological activities demonstrating the extent equivalent to when it was grown in its natural habitat. In addition, phytochemical investigation and GC/MS analysis of volatile oil constituents showed comparable results to those presented in India and elsewhere.

Keywords: Azadirachta indica, vivo, antimalarial activity, antidiabetic activity, alloxan, mice, phytochemical

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Authors: Hongyu Chen, Li Jiang

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Ubiquitous anomalies endanger the security of our system con- stantly. They may bring irreversible damages to the system and cause leakage of privacy. Thus, it is of vital importance to promptly detect these anomalies. Traditional supervised methods such as Decision Trees and Support Vector Machine (SVM) are used to classify normality and abnormality. However, in some case, the abnormal status are largely rarer than normal status, which leads to decision bias of these methods. Generative adversarial network (GAN) has been proposed to handle the case. With its strong generative ability, it only needs to learn the distribution of normal status, and identify the abnormal status through the gap between it and the learned distribution. Nevertheless, existing GAN-based models are not suitable to process data with discrete values, leading to immense degradation of detection performance. To cope with the discrete features, in this paper, we propose an efficient GAN-based model with specifically-designed loss function. Experiment results show that our model outperforms state-of-the-art models on discrete dataset and remarkably reduce the overhead.

Keywords: GAN, discrete feature, Wasserstein distance, multiple intermediate layers

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Authors: Yong Ho Jeon, Youn Mi Lee, Yong Yoon Lee

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Effects of cold plasma treatment on various plant seed germination were studied. The seeds of hot pepper, cucumber, tomato and arabidopsis were exposed to plasma and the plasma was generated in various devices. The germination speed was evaluated compared to an unexposed control. A positive effect on germination speed was observed in all tested seeds but the effects strongly depended on the type of the used plasma device (Argon-DBD, surface-DBD or MARX generator), time of exposure (6s~10min or 1~10shots) and kind of seeds. The SEM images showed that arrays of gold particles along the cell wall were observed on the surface of cucumber seeds showed a germination-accelerating effect by plasma treatment, which was the same as untreated. However, when treated with the high dose plasma, gold particles were not arrayed at the seed surface, it seems that due to the surface etching. This may suggest that the germination is not promoted by etching or damage of surface caused by the plasma treatment. Seedling growth improvement was also observed by indirect plasma treatment. These lead to an important conclusion that the effect of charged particles on plasma play the essential role in plant germination and indirect plasma treatment offers new perspectives for large scale application.

Keywords: cold plasma, cucumber, germination, SEM

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Authors: Rita Chattopadhyay, Vivek Anand Thoutam

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Speech is the most acceptable means of communication where we can quickly exchange our feelings and thoughts. Quite often, people can communicate orally but cannot interact or work with computers or devices. It’s easy and quick to give speech commands than typing commands to computers. In the same way, it’s easy listening to audio played from a device than extract output from computers or devices. Especially with Robotics being an emerging market with applications in warehouses, the hospitality industry, consumer electronics, assistive technology, etc., speech-based human-machine interaction is emerging as a lucrative feature for robot manufacturers. Considering this factor, the objective of this paper is to design the “Audio-Visual Co-Data Processing Pipeline.” This pipeline is an integrated version of Automatic speech recognition, a Natural language model for text understanding, object detection, and text-to-speech modules. There are many Deep Learning models for each type of the modules mentioned above, but OpenVINO Model Zoo models are used because the OpenVINO toolkit covers both computer vision and non-computer vision workloads across Intel hardware and maximizes performance, and accelerates application development. A speech command is given as input that has information about target objects to be detected and start and end times to extract the required interval from the video. Speech is converted to text using the Automatic speech recognition QuartzNet model. The summary is extracted from text using a natural language model Generative Pre-Trained Transformer-3 (GPT-3). Based on the summary, essential frames from the video are extracted, and the You Only Look Once (YOLO) object detection model detects You Only Look Once (YOLO) objects on these extracted frames. Frame numbers that have target objects (specified objects in the speech command) are saved as text. Finally, this text (frame numbers) is converted to speech using text to speech model and will be played from the device. This project is developed for 80 You Only Look Once (YOLO) labels, and the user can extract frames based on only one or two target labels. This pipeline can be extended for more than two target labels easily by making appropriate changes in the object detection module. This project is developed for four different speech command formats by including sample examples in the prompt used by Generative Pre-Trained Transformer-3 (GPT-3) model. Based on user preference, one can come up with a new speech command format by including some examples of the respective format in the prompt used by the Generative Pre-Trained Transformer-3 (GPT-3) model. This pipeline can be used in many projects like human-machine interface, human-robot interaction, and surveillance through speech commands. All object detection projects can be upgraded using this pipeline so that one can give speech commands and output is played from the device.

Keywords: OpenVINO, automatic speech recognition, natural language processing, object detection, text to speech

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Authors: Xiaodi Su, Xin Ting Zheng, Laura Sutarlie, Nur Asinah binte Mohamed Salleh, Yong Yu

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Wound healing is a dynamic process with multiple phases. Rapid profiling and quantitative characterization of inflammation and infection remain challenging. We have developed paper-like battery-free multiplexed sensors for holistic wound assessment via quantitative detection of multiple inflammation and infection markers. In one of the designs, the sensor patch consists of a wax-printed paper panel with five colorimetric sensor channels arranged in a pattern resembling a five-petaled flower (denoted as a ‘Petal’ sensor). The five sensors are for temperature, pH, trimethylamine, uric acid, and moisture. The sensor patch is sandwiched between a top transparent silicone layer and a bottom adhesive wound contact layer. In the second design, a palm-like-shaped paper strip is fabricated by a paper-cutter printer (denoted as ‘Palm’ sensor). This sensor strip carries five sensor regions connected by a stem sampling entrance that enables rapid colorimetric detection of multiple bacteria metabolites (aldehyde, lactate, moisture, trimethylamine, tryptophan) from wound exudate. For both the “\’ Petal’ and ‘Palm’ sensors, color images can be captured by a mobile phone. According to the color changes, one can quantify the concentration of the biomarkers and then determine wound healing status and identify/quantify bacterial species in infected wounds. The ‘Petal’ and ‘Palm’ sensors are validated with in-situ animal and ex-situ skin wound models, respectively. These sensors have the potential for integration with wound dressing to allow early warning of adverse events without frequent removal of the plasters. Such in-situ and early detection of non-healing condition can trigger immediate clinical intervention to facilitate wound care management.

Keywords: wound infection, colorimetric sensor, paper fluidic sensor, wound care

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Authors: Herman Susilo, Rahmat Budiman

Abstract:

Bali province is one of the most famous tourist destinations in Indonesia. As a central tourist destination, Bali is very concerned about the use of clean energy. Since Bali is an area that does not have natural resources, so all of its energy sources are imported from java island and other islands. As an example, currently, Pertagas is developing the use of LNG for the needs of the retail industry. Right now, LNG is transported from the LNG plant facility in Bontang (Kalimantan Province) using ISO Tanks which are transported by cargo ships and then transported by trucks to the island of Bali. After that, LNG from ISO Tank is breakbulk into LNG Cylinders for distribution to retail customers. The existing distribution scheme is very long and costly since the source of LNG is come from another island (Kalimantan) and is relatively far away. To solve this problem, we plan to build the mini-LNG plant on Java Island since there are lots of gas sources available. There are some small gas reserves (flared or stranded gas) that are not yet monetized and are less valuable (cheaper) because the volume is very small. After liquifying the gas from the gas field, the LNG is transported by the truck using ISO Tank. After that, LNG from ISO Tank is breakbulk into LNG Cylinders for distribution to retail customers. From this new LNG distribution scheme, there are 4-5 USD/MMBTU saving compared to the existing distribution scheme. It is hoped that with these cost savings, the number of retail LNG sales can increase rapidly.

Keywords: LNG, LNG retail, mini LNG, small scale LNG

Procedia PDF Downloads 93

Authors: Hammadi Larbi

Abstract:

The treatment of wastewater in sewage plants usually results in the formation of a large amount of sludge. These appear at the outlet of the treatment plant as a viscous fluid loaded with a high concentration of dry matter. This sludge production presents environmental, ecological, and economic risks. That is why it is necessary to find many solutions for minimizing these risks. In the present article, the effect of hydrogen peroxide, thermal treatment, and quicklime on the characteristics of the activated sludge produced in urban wastewater plant were evaluated in order to avoid any risk in the plants. The study shows increasing of the dose of H2O2 from 0 to 0.4 g causes an increase in the solubilization rate of COD from 12% to 45% and a reduction in the organic matter content of sludge (VM/SM) from 74% to 36% . The results also show that the optimum efficiency of the heat treatment corresponds to a temperature of 80 ° C for a treatment time of 40 min is 47% and 51.82% for a temperature equal to 100 ° C and 76.30 % for a temperature of 120 ° C, and 79.38% for a temperature of 140 ° C. The treatment of sludge by quicklime gives the optimum efficiency of 70.62 %. It was shown the increasing of the temperature from 80°C to 140°C, the pH of sludge was increased from 7.12 to 9.59. The obtained results showed that with increasing the dose of quicklime from 0 g/l to 1g/l in activated sludge led to an increase of their pH from 7.12 to 12.06. The study shows the increasing the dose of quicklime from 0 g/l to 1g/l causes also an increase in the solubilization of COD from 0% to 70.62 %

Keywords: activated sludge, hydrogen peroxide, thermal treatment, quicklime

Procedia PDF Downloads 96

Authors: S. Delgado, C. Cerrada, R. S. Gómez

Abstract:

This research introduces an approach to voxelizing the surfaces of triangular meshes with efficiency and accuracy. Our method leverages parallel equidistant scan-lines and introduces a Gap Detection technique to address the limitations of existing approaches. We present a comprehensive study showcasing the method's effectiveness, scalability, and versatility in different scenarios. Voxelization is a fundamental process in computer graphics and simulations, playing a pivotal role in applications ranging from scientific visualization to virtual reality. Our algorithm focuses on enhancing the voxelization process, especially for complex models and high resolutions. One of the major challenges in voxelization in the Graphics Processing Unit (GPU) is the high cost of discovering the same voxels multiple times. These repeated voxels incur in costly memory operations with no useful information. Our scan-line-based method ensures that each voxel is detected exactly once when processing the triangle, enhancing performance without compromising the quality of the voxelization. The heart of our approach lies in the use of parallel, equidistant scan-lines to traverse the interiors of triangles. This minimizes redundant memory operations and avoids revisiting the same voxels, resulting in a significant performance boost. Moreover, our method's computational efficiency is complemented by its simplicity and portability. Written as a single compute shader in Graphics Library Shader Language (GLSL), it is highly adaptable to various rendering pipelines and hardware configurations. To validate our method, we conducted extensive experiments on a diverse set of models from the Stanford repository. Our results demonstrate not only the algorithm's efficiency, but also its ability to produce 26 tunnel free accurate voxelizations. The Gap Detection technique successfully identifies and addresses gaps, ensuring consistent and visually pleasing voxelized surfaces. Furthermore, we introduce the Slope Consistency Value metric, quantifying the alignment of each triangle with its primary axis. This metric provides insights into the impact of triangle orientation on scan-line based voxelization methods. It also aids in understanding how the Gap Detection technique effectively improves results by targeting specific areas where simple scan-line-based methods might fail. Our research contributes to the field of voxelization by offering a robust and efficient approach that overcomes the limitations of existing methods. The Gap Detection technique fills a critical gap in the voxelization process. By addressing these gaps, our algorithm enhances the visual quality and accuracy of voxelized models, making it valuable for a wide range of applications. In conclusion, "Closing the Gap: Efficient Voxelization with Equidistant Scan-lines and Gap Detection" presents an effective solution to the challenges of voxelization. Our research combines computational efficiency, accuracy, and innovative techniques to elevate the quality of voxelized surfaces. With its adaptable nature and valuable innovations, this technique could have a positive influence on computer graphics and visualization.

Keywords: voxelization, GPU acceleration, computer graphics, compute shaders

Procedia PDF Downloads 64

Authors: Samiul Islam Hazarika, Domngam Boje, Ananta Kumar Atta

Abstract:

It is well familiar that solvents play a significant role in modern chemistry. Solvents can change the reactivity and physicochemical properties of molecules in a solution. Keeping this in mind, we have designed and synthesized a mono-triazolyl-linked pyrenyl-appended xylofuranose derivative for the detection of metal ions with changing solvent systems. The incorporation of a sugar backbone in the sensor increases the water solubility and biocompatibility. The experimental study revealed that the xylofuranose-based fluorescence probe did not exhibit any specific selectivity towards metal ions in acetonitrile (CH₃CN) solvent. Whereas, we revealed that triazole-linked pyrenyl-appended xylofuranose-based fluorescent sensor would exhibit high selectivity and sensitivity towards Au³⁺ ions in CH₃CN-H₂O (1/1, v/v) system. This observation might be explained by the viscosity and polarity differences of CH₃CN and CH₃CN-H₂O solvent systems. The formation of the sensor-Au³⁺ complex was also established by high-resolution mass spectrometry (HRMS) data of the complex.

Keywords: triazole, furanose, fluorometric, solvent dependent

Procedia PDF Downloads 112

Authors: T. Kizza, M. Muyinda

Abstract:

Irrigation schedules are normally given in terms of frequency (irrigation days). Specific timings within a given day are not usually included. This study examined the effect of irrigation timing for a two-day irrigation schedule of a surface drip-irrigated tomato field on yield. It was carried out for three dry seasons; July-Sept 2016, Jan-April 2017 and Jan-March 2018, at MuZARDI research station. Four irrigation treatments; T1 morning (8.00hrs), T2 noon (12:00hrs), T3 evening (17:00hr) and T4, a combination of morning and evening, were evaluated. The irrigation duration was one hour for T1-T3 and split into 30 minutes for T4. First season results indicated noon watering as having the best yield over other treatments at 51.59t/ha followed closely by morning watering at 50.6t/ha. Plants watered at noon had the highest number of fruits at 19/plant with an average weight of 94g/fruit. Plants watered in the morning had fruits with the highest average weight at 111.2g/fruit but they were the lowest number at 16 fruits/plant. The three-season data indicated the highest yield at 45.9t/ha for morning watering, followed by noon watering at 44.3t/ha and the least yield was for evening watering at 40.9t/ha. Watering tomatoes in the morning will give optimum yields for a two-day irrigation schedule.

Keywords: drip irrigation, irrigation schedule, irrigation timing, tomato yield

Procedia PDF Downloads 132

Authors: Hachemi Nouria

Abstract:

The olive tree is a Mediterranean tree, which belongs to the family Oleaceae. The Olea genus contains various species and subspecies, and the only species bearing edible fruit is Olea europaea. The desired issue in this study is to provide the current status of plant cover and especially the training in Olea europaea currently existing in the major centers of the region of Tlemcen. While based on the flora and biometric aspect of this plant germplasm. In order to make an assessment of the phytomass, we made measurements of the four parameters of the aerial part of the taxon: height, diameter, and canopy density to ten feet of the olive tree per station. The floristic analysis shows a certain floristic difference between the different stations. The vegetal formations reflect the biotic and abiotic conditions including climate affecting the ecosystem. Biometric study on the feet of Olea in the six study sites, has led us to conclude that the four measured parameters provides insight on the development or degradation of Olea feet depending on the layout of the stations and the factors environmental. We find that the terrains are havens for these assets. Also the local microclimate (Oued Thalweg) promotes the healthy development of this species.

Keywords: olivier, ecology, biometrics, Tlemcen, Algeria

Procedia PDF Downloads 291

Authors: S. A. M. Sabrina, Gouget Lammel, Anne Chantal, Chazalviel, Jean Noël, Ozanam François, Etcheberry Arnaud, Tighlit Fatma Zohra, B. Samia, Gabouze Noureddine

Abstract:

The elaboration and characterization of hybrid nano materials give rise to considerable interest due to the new properties that arising. They are considered as an important category of new materials having innovative characteristics by combining the specific intrinsic properties of inorganic compounds (semiconductors) with the grafted organic species. This open the way to improved properties and spectacular applications in various and important fields, especially in the environment. In this work, nano materials based-semiconductors were elaborated by chemical route. The obtained surfaces were grafted with organic functional groups. The functionalization process was optimized in order to confer to the hybrid nano material a good stability as well as the right properties required for the subsequent applications. Different characterization techniques were used to investigate the resulting nano structures, such as SEM, UV-Visible, FTIR, Contact angle and electro chemical measurements. Finally, applications were envisaged in environmental area. The elaborated nano structures were tested for the detection and the elimination of pollutants.

Keywords: hybrid materials, porous silicon, peptide, metal detection

Procedia PDF Downloads 493

Authors: Henry Pariaman, Iwa Garniwa, Isti Surjandari, Bambang Sugiarto

Abstract:

Availability of a complex system of thermal power plant is strongly influenced by the reliability of spare parts and maintenance management policies. A reliability-centered maintenance (RCM) technique is an established method of analysis and is the main reference for maintenance planning. This method considers the consequences of failure in its implementation, but does not deal with further risk of down time that associated with failures, loss of production or high maintenance costs. Risk-based maintenance (RBM) technique provides support strategies to minimize the risks posed by the failure to obtain maintenance task considering cost effectiveness. Meanwhile, condition-based maintenance (CBM) focuses on monitoring the application of the conditions that allow the planning and scheduling of maintenance or other action should be taken to avoid the risk of failure prior to the time-based maintenance. Implementation of RCM, RBM, CBM alone or combined RCM and RBM or RCM and CBM is a maintenance technique used in thermal power plants. Implementation of these three techniques in an integrated maintenance will increase the availability of thermal power plants compared to the use of maintenance techniques individually or in combination of two techniques. This study uses the reliability, risks and conditions-based maintenance in an integrated manner to increase the availability of thermal power plants. The method generates MPI (Priority Maintenance Index) is RPN (Risk Priority Number) are multiplied by RI (Risk Index) and FDT (Failure Defense Task) which can generate the task of monitoring and assessment of conditions other than maintenance tasks. Both MPI and FDT obtained from development of functional tree, failure mode effects analysis, fault-tree analysis, and risk analysis (risk assessment and risk evaluation) were then used to develop and implement a plan and schedule maintenance, monitoring and assessment of the condition and ultimately perform availability analysis. The results of this study indicate that the reliability, risks and conditions-based maintenance methods, in an integrated manner can increase the availability of thermal power plants.

Keywords: integrated maintenance techniques, availability, thermal power plant, MPI, FDT

Procedia PDF Downloads 787

Authors: Amaladhithyan Krishnamoorthy, Ruvaitha Banu

Abstract:

Vision is considered as the most important sense in humans, without which leading a normal can be often difficult. There are many existing smart canes for visually impaired with obstacle detection using ultrasonic transducer to help them navigate. Though the basic smart cane increases the safety of the users, it does not help in filling the void of visual loss. This paper introduces the concept of Digi-Buddy which is an evolved smart cane for visually impaired. The cane consists for several modules, apart from the basic obstacle detection features; the Digi-Buddy assists the user by capturing video/images and streams them to the server using a wide-angled camera, which then detects the objects using Deep Convolutional Neural Network. In addition to determining what the particular image/object is, the distance of the object is assessed by the ultrasonic transducer. The sound generation application, modelled with the help of Natural Language Processing is used to convert the processed images/object into audio. The object detected is signified by its name which is transmitted to the user with the help of Bluetooth hear phones. The object detection is extended to facial recognition which maps the faces of the person the user meets in the database of face images and alerts the user about the person. One of other crucial function consists of an automatic-intimation-alarm which is triggered when the user is in an emergency. If the user recovers within a set time, a button is provisioned in the cane to stop the alarm. Else an automatic intimation is sent to friends and family about the whereabouts of the user using GPS. In addition to safety and security by the existing smart canes, the proposed concept devices to be implemented as a prototype helping visually-impaired visualize their surroundings through audio more in an amicable way.

Keywords: artificial intelligence, facial recognition, natural language processing, internet of things

Procedia PDF Downloads 346