Search results for: animal artificial insemination

Authors: Suzanne Ahmed

Abstract:

Nanomotors, also commonly referred to as nanorobotics or nanomachines, have garnered considerable research attention due to their numerous potential applications in biomedicine, including drug delivery and microsurgery. Nanomotors typically consist of inorganic or polymeric particles that are powered to undergo motion. These artificial, man-made nanoscale motors operate in the low Reynolds number regime and typically have no moving parts. Several methods have been developed to actuate the motion of nanomotors including magnetic fields, electrical fields, electromagnetic waves, and chemical fuel. Since their introduction in 2012, ultrasonically powered nanomotors have been explored in biocompatible fluids and even within living cells. Due to the common use of ultrasound within the biomedical community for both imaging and therapeutics, the introduction of ultrasonically propelled nanomotors holds significant potential for biomedical applications. In this work, metallic nanomotors are electrochemically plated within porous anodic alumina templates to have a diameter of 300 nm and a length that is 2-4 µm. Nanomotors are placed within an acoustic chamber capable of producing bulk acoustic waves in the ultrasonic range. The motion of nanomotors within biomimetic confines is explored. The control over nanomotor motion is exerted by virtue of the properties of the acoustic signal within these biomimetic confines to control speed, modes of motion and directionality of motion. To expand the range of control over nanorod motion within biomimetic confines, external forces from biocompatible magnetic fields, are exerted onto the acoustically propelled nanomotors.

Keywords: nanomotors, nanomachines, nanorobots, ultrasound

Procedia PDF Downloads 71

Authors: Theresia El Khoury, Georges Badr, Amir Hajjam El Hassani, Stéphane N’Guyen Van Ky

Abstract:

The widespread adoption of machine learning and artificial intelligence across different domains can be attributed to the digitization of data over several decades, resulting in vast amounts of data, types, and structures. Thus, data processing and preparation turn out to be a crucial stage. However, applying these techniques to S1000D standard-based data poses a challenge due to its complexity and the need to preserve logical information. This paper describes SALERNO, an S1000d AppLicability dEpended pRocessiNg mOdel. This python-based model analyzes and converts the XML S1000D-based files into an easier data format that can be used in machine learning techniques while preserving the different logic and relationships in files. The model parses the files in the given folder, filters them, and extracts the required information to be saved in appropriate data frames and Excel sheets. Its main idea is to group the extracted information by applicability. In addition, it extracts the full text by replacing internal and external references while maintaining the relationships between files, as well as the necessary requirements. The resulting files can then be saved in databases and used in different models. Documents in both English and French languages were tested, and special characters were decoded. Updates on the technical manuals were taken into consideration as well. The model was tested on different versions of the S1000D, and the results demonstrated its ability to effectively handle the applicability, requirements, references, and relationships across all files and on different levels.

Keywords: aeronautics, big data, data processing, machine learning, S1000D

Procedia PDF Downloads 143

Authors: O. B. Oriolowo, O. J. John

Abstract:

Empirical findings have shown insects to be nutritious and good source of food for man. However, human food preferences are not only determined by nutritional values of food consumed but, more importantly, by sociology and economic pressure. This study examined the interrelation between science and sociology in sustaining the acceptance of entomophagy among college students to combat food insecurity. A twenty items five Likert scale, College Students Entomophagy Questionnaire (CSEQ), was used to elucidate information from the respondents. The reliability coefficient was obtained to be 0.91 using Spearman-Brown Prophecy formula. Three research questions and three hypotheses were raised. Also, quantitative nutritional analysis of few insects and some established conventional protein sources were undertaking in order to compare their nutritional status. The data collected were analyzed using descriptive statistics of percentages and inferential statistics of correlation and Analysis of Variance (ANOVA). The results obtained showed that entomophagy has cultural heritage among different tribes in Nigeria and is an acceptable practice; it cuts across every social stratum and is practiced among both major religions. Moreover, insects compared favourably in term of nutrient contents when compared with the conventional animal protein sources analyzed. However, there is a gradual decline in the practice of entomophagy among students, which may be attributed to the influence of western civilization. This study, therefore, recommended an intensification of research and enlightenment of people on the usefulness of entomophagy so as to preserve its cultural heritage as well as boost human food security.

Keywords: entomophagy, food security, malnutrition, poverty alleviation, sociology

Procedia PDF Downloads 116

Authors: Marziyeh Khavari

Abstract:

In recent decades, climate change, global warming, and the growing population worldwide face some challenges, such as increasing food consumption and shortage of resources. Assessing how climate change could disturb crops, especially hazelnut production, seems crucial for sustainable agriculture production. For hazelnut cultivation in the mid-warm condition, such as in Iran, here we present an investigation of climate parameters and how much they are effective on fertility and nut production of hazelnut trees. Therefore, the climate change of the northern zones in Iran has investigated (1960-2017) and was reached an uptrend in temperature. Furthermore, the descriptive analysis performed on six cultivars during seven years shows how this small-scale survey could demonstrate the effects of climate change on hazelnut production and stability. Results showed that some climate parameters are more significant on nut production, such as solar radiation, soil temperature, relative humidity, and precipitation. Moreover, some cultivars have produced more stable production, for instance, Negret and Segorbe, while the Mervill de Boliver recorded the most variation during the study. Another aspect that needs to be met is training and predicting an actual model to simulate nut production through a neural network and linear regression simulation. The study developed and estimated the ANN model's generalization capability with different criteria such as RMSE, SSE, and accuracy factors for dependent and independent variables (environmental and yield traits). The models were trained and tested while the accuracy of the model is proper to predict hazelnut production under fluctuations in weather parameters.

Keywords: climate change, neural network, hazelnut, global warming

Procedia PDF Downloads 127

Authors: Arunava Chakrabarti

Abstract:

A one-dimensional chain of magnetic atoms, representative of a quantum gas in an artificial quasi-periodic potential and modeled by the well-known Aubry-Andre function and its variants are studied in respect of its capability of working as a spin filter for arbitrary spins. The basic formulation is explained in terms of a perfectly periodic chain first, where it is shown that a definite correlation between the spin S of the incoming particles and the magnetic moment h of the substrate atoms can open up a gap in the energy spectrum. This is crucial for a spin filtering action. The simple one-dimensional chain is shown to be equivalent to a 2S+1 strand ladder network. This equivalence is exploited to work out the condition for the opening of gaps. The formulation is then applied for a one-dimensional chain with quasi-periodic variation in the site potentials, the magnetic moments and their orientations following an Aubry-Andre modulation and its variants. In addition, we show that a certain correlation between the system parameters can generate absolutely continuous bands in such systems populated by Bloch like extended wave functions only, signaling the possibility of a metal-insulator transition. This is a case of correlated disorder (a deterministic one), and the results provide a non-trivial variation to the famous Anderson localization problem. We have worked within a tight binding formalism and have presented explicit results for the spin half, spin one, three halves and spin five half particles incident on the magnetic chain to explain our scheme and the central results.

Keywords: Aubry-Andre model, correlated disorder, localization, spin filter

Procedia PDF Downloads 353

Authors: Amos Ekow Coffie

Abstract:

This exploratory study investigates the impact of AI-driven health communications and media reportage on health outcomes in rural Ghana, focusing on rural communities within Accra. Despite the potential of AI-driven health communications in improving health outcomes, its adoption in rural Ghana is hindered by infrastructure challenges, digital literacy, and cultural factors. Media reportage plays a crucial role in shaping health perceptions and behaviors, but its impact is limited by inadequate health reporting, lack of specialized health journalists, and limited access to health information. This study aims to explore the integration of AI-driven health communications into media practices in rural Ghana, addressing the following research questions: How do AI-driven health communications impact health outcomes in rural Ghana? What role does media reportage play in shaping health perceptions and behaviors in Accra? How can AI-driven health communications and media reportage be optimized to improve health outcomes in rural Ghana? Using a mixed-methods approach, this study will combine surveys, interviews, and content analysis to investigate the impact of AI-driven Health Communication and media reportage on health outcomes in rural areas in Ghana. AI-driven health communications is the use of artificial intelligence (AI) technologies to design, deliver, and evaluate health messages, interventions, and campaigns. The study's findings will contribute to the development of effective health communication strategies, addressing the significant health disparities in rural areas in Ghana.

Keywords: AI Driven Health Communication, Media Reporting, Rural Areas, Communication Channels

Procedia PDF Downloads 17

Authors: Nader Khalafian, Mohsen Ghaderi

Abstract:

Field observations have revealed many examples of structures which were damaged due to ground surface deformation caused by the faulting phenomena. In this paper some efforts were made in order to estimate the length and location of the ground surface where large displacements were created due to the reverse faulting. This research has conducted in two steps; (1) in the first step, a 2D explicit finite element model were developed using ABAQUS software. A subroutine for Mohr-Coulomb failure criterion with strain softening model was developed by the authors in order to properly model the stress strain behavior of the soil in the fault rapture zone. The results of the numerical analysis were verified with the results of available centrifuge experiments. Reasonable coincidence was found between the numerical and experimental data. (2) In the second step, the effects of the fault dip angle (δ), depth of soil layer (H), dilation and friction angle of sand (ψ and φ) and the amount of fault offset (d) on the soil surface displacement and fault rupture path were investigated. An artificial neural network-based model (ANN), as a powerful prediction tool, was developed to generate a general model for predicting faulting characteristics. A properly sized database was created to train and test network. It was found that the length and location of the zone of displaced ground surface can be accurately estimated using the proposed model.

Keywords: reverse faulting, surface deformation, numerical, neural network

Procedia PDF Downloads 420

Authors: A. M. John-Otumu, M. M. Rahman, M. C. Onuoha, E. P. Ojonugwa

Abstract:

A Convolutional Neural Network (CNN) model for predicting Lassa fever was built using Python 3.8.0 programming language, alongside Keras 2.2.4 and TensorFlow 2.6.1 libraries as the development environment in order to reduce the current high risk of Lassa fever in West Africa, particularly in Nigeria. The study was prompted by some major flaws in existing conventional laboratory equipment for diagnosing Lassa fever (RT-PCR), as well as flaws in AI-based techniques that have been used for probing and prognosis of Lassa fever based on literature. There were 15,679 blood smear microscopic image datasets collected in total. The proposed model was trained on 70% of the dataset and tested on 30% of the microscopic images in avoid overfitting. A 3x3x3 convolution filter was also used in the proposed system to extract features from microscopic images. The proposed CNN-based model had a recall value of 96%, a precision value of 93%, an F1 score of 95%, and an accuracy of 94% in predicting and accurately classifying the images into clean or infected samples. Based on empirical evidence from the results of the literature consulted, the proposed model outperformed other existing AI-based techniques evaluated. If properly deployed, the model will assist physicians, medical laboratory scientists, and patients in making accurate diagnoses for Lassa fever cases, allowing the mortality rate due to the Lassa fever virus to be reduced through sound decision-making.

Keywords: artificial intelligence, ANN, blood smear, CNN, deep learning, Lassa fever

Procedia PDF Downloads 114

Authors: Dionisio Andujar, Juan lópez-Correa, Hugo Moreno, Angela Ri

Abstract:

The increased number of weeds in tomato crops highly lower yields. Weed identification with the aim of machine learning is important to carry out site-specific control. The last advances in computer vision are a powerful tool to face the problem. The analysis of RGB (Red, Green, Blue) images through Artificial Neural Networks had been rapidly developed in the past few years, providing new methods for weed classification. The development of the algorithms for crop and weed species classification looks for a real-time classification system using Object Detection algorithms based on Convolutional Neural Networks. The site study was located in commercial corn fields. The classification system has been tested. The procedure can detect and classify weed seedlings in tomato fields. The input to the Neural Network was a set of 10,000 RGB images with a natural infestation of Cyperus rotundus l., Echinochloa crus galli L., Setaria italica L., Portulaca oeracea L., and Solanum nigrum L. The validation process was done with a random selection of RGB images containing the aforementioned species. The mean average precision (mAP) was established as the metric for object detection. The results showed agreements higher than 95 %. The system will provide the input for an online spraying system. Thus, this work plays an important role in Site Specific Weed Management by reducing herbicide use in a single step.

Keywords: deep learning, object detection, cnn, tomato, weeds

Procedia PDF Downloads 101

Authors: Hamid Mustafa, Huson J. Heather, Kim Eiusoo, McClure Matt, Khalid Javed, Talat Nasser Pasha, Afzal Ali1, Adeela Ajmal, Tad Sonstegard

Abstract:

Genetic differences associated with speciation, breed formation or local adaptation can help to preserve and effective utilization of animals in selection programs. Analyses of population structure and breed diversity have provided insight into the origin and evolution of cattle. In this study, we used a high-density panel of SNP markers to examine population structure and diversity among ten Pakistani indigenous cattle breeds. In total, 25 individuals from three cattle populations, including Achi (n=08), Bhagnari (n=04) and Cholistani (n=13) were genotyped for 777, 962 single nucleotide polymorphism (SNP) markers. Population structure was examined using the linkage model in the program STRUCTURE. After characterizing SNP polymorphism in the different populations, we performed a detailed analysis of genetic structure at both the individual and population levels. The whole-genome SNP panel identified several levels of population substructure in the set of examined cattle breeds. We further searched for spatial patterns of genetic diversity among these breeds under the recently developed spatial principal component analysis framework. Overall, such high throughput genotyping data confirmed a clear partitioning of the cattle genetic diversity into distinct breeds. The resulting complex historical origins associated with both natural and artificial selection have led to the differentiation of numerous different cattle breeds displaying a broad phenotypic variety over a short period of time.

Keywords: Pakistan, cattle, genetic diversity, population structure

Procedia PDF Downloads 613

Authors: Hatim Laalej, Salvador Sumohano-Verdeja, Thomas McLeay

Abstract:

Monitoring of tool wear in milling operations is essential for achieving the desired dimensional accuracy and surface finish of a machined workpiece. Although there are numerous statistical models and artificial intelligence techniques available for monitoring the wear of cutting tools, these techniques cannot pin point which cutting edge of the tool, or which insert in the case of indexable tooling, is worn or broken. Currently, the task of monitoring the wear on the tool cutting edges is carried out by the operator who performs a manual inspection, causing undesirable stoppages of machine tools and consequently resulting in costs incurred from lost productivity. The present study is concerned with the development of a flute tracking system to segment signals related to each physical flute of a cutter with three flutes used in an end milling operation. The purpose of the system is to monitor the cutting condition for individual flutes separately in order to determine their progressive wear rates and to predict imminent tool failure. The results of this study clearly show that signals associated with each flute can be effectively segmented using the proposed flute tracking system. Furthermore, the results illustrate that by segmenting the sensor signal by flutes it is possible to investigate the wear in each physical cutting edge of the cutting tool. These findings are significant in that they facilitate the online condition monitoring of a cutting tool for each specific flute without the need for operators/engineers to perform manual inspections of the tool.

Keywords: machining, milling operation, tool condition monitoring, tool wear prediction

Procedia PDF Downloads 299

Authors: Shatha Ghareeb, Rawaa Al-Jumeily, Thar Baker

Abstract:

In Abu Dhabi, there are many different education curriculums where sector of private schools and quality assurance is supervising many private schools in Abu Dhabi for many nationalities. As there are many different education curriculums in Abu Dhabi to meet expats’ needs, there are different requirements for registration and success. In addition, there are different age groups for starting education in each curriculum. In fact, each curriculum has a different number of years, assessment techniques, reassessment rules, and exam boards. Currently, students that transfer curriculums are not being placed in the right year group due to different start and end dates of each academic year and their date of birth for each year group is different for each curriculum and as a result, we find students that are either younger or older for that year group which therefore creates gaps in their learning and performance. In addition, there is not a way of storing student data throughout their academic journey so that schools can track the student learning process. In this paper, we propose to develop a computational framework applicable in multicultural countries such as UAE in which multi-education systems are implemented. The ultimate goal is to use cloud and fog computing technology integrated with Artificial Intelligence techniques of Machine Learning to aid in a smooth transition when assigning students to their year groups, and provide leveling and differentiation information of students who relocate from a particular education curriculum to another, whilst also having the ability to store and access student data from anywhere throughout their academic journey.

Keywords: admissions, algorithms, cloud computing, differentiation, fog computing, levelling, machine learning

Procedia PDF Downloads 139

Authors: A. Chari, A. El Bouari, B. Orayech, A. Faik, J. M. Igartua

Abstract:

The phosphate is a natural resource of great importance in Morocco. In order to exploit this wealth, synthesis and studies of new a material based phosphate, were carried out. The apatite structure present o lot of characteristics, One of the main characteristics is to allow large and various substitutions for both cations and anions. Beside their biological importance in hard tissue (bone and teeth), apatites have been extensively studied for their potential use as fluorescent lamp phosphors or laser host materials.The apatite have interesting possible application fields such as in medicine as materials of bone filling, coating of dental implants, agro chemicals as artificial fertilizers. The LiPb2Ca2(PO4)3 was synthesized by the solid-state method, its crystal structure was investigated by Rietveld analysis using XRPD data. This material crystallizes with a structure of lacunar apatite anion deficit. The LiPb2Ca2(PO4)3 is hexagonal apatite at room temperature, adopting the space group P63/m (ITA No. 176), Rietveld refinements showed that the site 4f is shared by three cations Ca, Pb and Li. While the 6h is occupied by the Pb and Li cations. The structure can be described as built up from the PO4 tetrahedra and the sixfold coordination cavities, which delimit hexagonal tunnels along the c-axis direction. These tunnels are linked by the cations occupying the 4 f sites. Raman and Infrared spectroscopy analyses were carried out. The observed frequencies were assigned and discussed on the basis of unit-cell group analysis and by comparison to other apatite-type materials.

Keywords: apatite, Lacunar, crystal structure, Rietveldmethod, LiPb2Ca2(PO4)3, Phase transition

Procedia PDF Downloads 400

Authors: Adesoji Tunbosun Jaiyeola, Josiah Adeyemo

Abstract:

Sediment yield can be considered to be the total sediment load that leaves a drainage basin. The knowledge of the quantity of sediments present in a river at a particular time can lead to better flood capacity in reservoirs and consequently help to control over-bane flooding. Furthermore, as sediment accumulates in the reservoir, it gradually loses its ability to store water for the purposes for which it was built. The development of hydrological models to forecast the quantity of sediment present in a reservoir helps planners and managers of water resources systems, to understand the system better in terms of its problems and alternative ways to address them. The application of artificial intelligence models and technique to such real-life situations have proven to be an effective approach of solving complex problems. This paper makes an extensive review of literature relevant to the theories and applications of evolutionary algorithms, and most especially genetic programming. The successful applications of genetic programming as a soft computing technique were reviewed in sediment modelling and other branches of knowledge. Some fundamental issues such as benchmark, generalization ability, bloat and over-fitting and other open issues relating to the working principles of GP, which needs to be addressed by the GP community were also highlighted. This review aim to give GP theoreticians, researchers and the general community of GP enough research direction, valuable guide and also keep all stakeholders abreast of the issues which need attention during the next decade for the advancement of GP.

Keywords: benchmark, bloat, generalization, genetic programming, over-fitting, sediment yield

Procedia PDF Downloads 442

Authors: M. R. Akshaya, Veena Rao

Abstract:

Pet population in India is increasing phenomenally owing to the changes in urban lifestyle with increasing number of single professionals, single parents, delayed parenthood etc. The animal companionship as a means of reducing stress levels, deriving emotional support, and unconditional love provided by dogs are a few reasons attributed for increasing pet ownership. The consequence is the booming of the pet care products and dog care centers catering to the different requirements of rearing the pets. Dog care centers quite popular in tier 1 metros of India cater to the requirement of the dog owners providing space for the dogs in absence of the owner. However, it is often reported that the absence of the owner leads to destructive and exploratory behavior issues; the main being the anxiety disorders. In the above context, it becomes imperative for a designer to design dog boarding centers that help in reducing the separation anxiety in dogs keeping in mind the different interior design parameters. An exploratory research with focus group discussion is employed involving a group of dog owners, behaviorists, proprietors of day care as well as boarding centers, and veterinarians to understand their perception on the significance of different interior parameters of color, texture, ventilation, aroma therapy and acoustics as a means of reducing the stress levels in dogs sent to the boarding centers. The data collected is organized as thematic networks thus enabling the listing of the interior design parameters that needs to be considered in designing dog boarding centers. 

Keywords: behavioral response, design parameters, dog boarding centers, interior environment

Procedia PDF Downloads 200

Authors: Karthika Durairaj, Buvaneswari G., Gowdham M., Gilles M., Velmurugan G.

Abstract:

Background: Hyperglycaemia is the primary cause of metabolic illness. Recently, researchers focused on the possibility that chemical exposure could promote metabolic disease. Hyperglycaemia causes a variety of metabolic diseases dependent on its etiologic conditions. According to animal and population-based research, individual chemical exposure causes health problems through alteration of endocrine function with the influence of microbial influence. We were intrigued by the function of gut microbiota variation in high fat and chemically induced hyperglycaemia. Methodology: C57/Bl6 mice were subjected to two different treatments to generate the etiologic-based diabetes model: I – a high-fat diet with a 45 kcal diet, and II - endocrine disrupting chemicals (EDCs) cocktail. The mice were monitored periodically for changes in body weight and fasting glucose. After 120 days of the experiment, blood anthropometry, faecal metagenomics and metabolomics were performed and analyzed through statistical analysis using one-way ANOVA and student’s t-test. Results: After 120 days of exposure, we found hyperglycaemic changes in both experimental models. The treatment groups also differed in terms of plasma lipid levels, creatinine, and hepatic markers. To determine the influence on glucose metabolism, microbial profiling and metabolite levels were significantly different between groups. The gene expression studies associated with glucose metabolism vary between hosts and their treatments. Conclusion: This research will result in the identification of biomarkers and molecular targets for better diabetes control and treatment.

Keywords: hyperglycaemia, endocrine-disrupting chemicals, gut microbiota, host metabolism

Procedia PDF Downloads 36

Authors: Sean W. T. Bayly, Daniel Glover, Don Horrell, Simon Horrocks, Barnes Callum, Stuart Gibson, Mac Misuira

Abstract:

We assess suitability of recent, ∼7B parameter, instruction-tuned Language Models Mistral-v0.3, Llama-3, and Phi-3, for Generative Named Entity Recognition (GNER). Our proposed Multi-Level Information Retrieval method achieves notable improvements over finetuned entity-level and sentence-level methods. We consider recent developments at the cross roads of prompt engineering and Retrieval Augmented Generation (RAG), such as EmotionPrompt. We conclude that language models directed toward this task are highly capable when distinguishing between positive classes (precision). However, smaller models seem to struggle to find all entities (recall). Poorly defined classes such as ”Miscellaneous” exhibit substantial declines in performance, likely due to the ambiguity it introduces to the prompt. This is partially resolved through a self verification method using engineered prompts containing knowledge of the stricter class definitions, particularly in areas where their boundaries are in danger of overlapping, such as the conflation between the location ”Britain” and the nationality ”British”. Finally, we explore correlations between model performance on the GNER task with performance on relevant academic benchmarks.

Keywords: generative named entity recognition, information retrieval, lightweight artificial intelligence, prompt engineering, personal information identification, retrieval augmented generation, self verification

Procedia PDF Downloads 29

Authors: Seung Ju Yeon, Seul Ki Min, Jun Sang Park, Yeo Seon Kwon, Hoo Cheol Lee, Hyun Jung Shim, Il-Doo Kim, Ja Kyeong Lee, Hwa Sung Shin

Abstract:

In brain injury, depleting oxidative stress is the most effective way to reduce the brain infarct size. C-phycocyanin (C-Pc) is a well-known antioxidant protein that has neuroprotective effects obtained from green microalgae. Astrocyte is glial cell that supports the nerve cell such as neuron, which account for a large portion of the brain. In brain injury, such as ischemia and reperfusion, astrocyte has an important rule that overcomes the oxidative stress and protect from brain reactive oxygen species (ROS) injury. However little is known about how C-Pc regulates the anti-oxidants effects of astrocyte. In this study, when the C-Pc was treated in oxidized astrocyte, we confirmed that inflammatory factors Interleukin-6 and Interleukin-3 were increased and antioxidants enzyme, Superoxide dismutase (SOD) and catalase was upregulated, and neurotrophic factors, brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF) was alleviated. Also, it was confirmed to reduce infarct size of the brain in ischemia and reperfusion because C-Pc has anti-oxidant effects in middle cerebral artery occlusion (MCAO) animal model. These results show that C-Pc can help astrocytes lead neuroprotective activities in the oxidative stressed environment of the brain. In summary, the C-PC protects astrocytes from oxidative stress and has anti-oxidative, anti-inflammatory, neurotrophic effects under ischemic situations.

Keywords: c-phycocyanin, astrocyte, reactive oxygen species, ischemia and reperfusion, neuroprotective effect

Procedia PDF Downloads 314

Authors: Jianghao Hu, Hongyu Wang

Abstract:

The effective and efficient human pose estimation algorithm is an important task for real-time human pose estimation on mobile devices. This paper proposes a light-weight human key points detection algorithm, Light-Weight Network for Real-Time Pose Estimation (LWPE). LWPE uses light-weight backbone network and depthwise separable convolutions to reduce parameters and lower latency. LWPE uses the feature pyramid network (FPN) to fuse the high-resolution, semantically weak features with the low-resolution, semantically strong features. In the meantime, with multi-scale prediction, the predicted result by the low-resolution feature map is stacked to the adjacent higher-resolution feature map to intermediately monitor the network and continuously refine the results. At the last step, the key point coordinates predicted in the highest-resolution are used as the final output of the network. For the key-points that are difficult to predict, LWPE adopts the online hard key points mining strategy to focus on the key points that hard predicting. The proposed algorithm achieves excellent performance in the single-person dataset selected in the AI (artificial intelligence) challenge dataset. The algorithm maintains high-precision performance even though the model only contains 3.9M parameters, and it can run at 225 frames per second (FPS) on the generic graphics processing unit (GPU).

Keywords: depthwise separable convolutions, feature pyramid network, human pose estimation, light-weight backbone

Procedia PDF Downloads 149

Authors: Sintayehu W. Dejene, Ignas M. A. Heitkönig, Herbert H. T. Prins, Zewdu K. Tessema, Willem F. de Boer

Abstract:

Current theories on diversity-disease relationships describe host species diversity and species identity as important factors influencing disease risk, either diluting or amplifying disease prevalence in a community. Whereas the simple term ‘diversity’ embodies a set of animal community characteristics, it is not clear how different measures of species diversity are correlated with disease risk. We, therefore, tested the effects of species richness, Pielou’s evenness and Shannon’s diversity on bTB risk in cattle in the Afar Region and Awash National Park between November 2013 and April 2015. We also analysed the identity effect of a particular species and the effect of host habitat use overlap on bTB risk. We used the comparative intradermal tuberculin test to assess the number of bTB infected cattle. Our results suggested a dilution effect through species evenness. We found that the identity effect of greater kudu - a maintenance host – confounded the dilution effect of species diversity on bTB risk. bTB infection was positively correlated with habitat use overlap between greater kudu and cattle. Different diversity indices have to be considered together for assessing diversity-disease relationships, for understanding the underlying causal mechanisms. We posit that unpacking diversity metrics is also relevant for formulating control strategies to manage cattle in ecosystems characterized by seasonally limited resources and intense wildlife-livestock interactions.

Keywords: evenness, diversity, greater kudu, identity effect, maintenance hosts, multi-host disease ecology, habitat use overlap

Procedia PDF Downloads 328

Authors: Lindiwe Ngcobo

Abstract:

The aim of the study is to describe and understand the benefits and costs of having biogas digesters at both household and society level. On a household level, the purpose is to understand how rural households benefit from the biogas digesters, for example, by converting animal and human waste through biogas digesters, and at what costs the benefits are realized. At a societal level, the purpose is to understand the costs and benefits of biogas digesters relative to the situation of rural communities who do not have flush toilets and have no appropriate waste disposal services while they incur electricity costs. Multiple regression analysis was used to determine the effect of biogas digesters on electricity availability and waste management. The results showed that beneficiaries spent less on electricity using household waste, and also waste disposal costs were eliminated from household expenses. A move to biogas energy production can be beneficial to rural households. It is economically and environmentally friendly. Small-scale farmers need to be introduced to agricultural innovations that can assist them in producing nutritious crops at a low cost. This can be a good opportunity to start an agribusiness that focuses on organic crops. Extensions and training institutions have to play a part in supporting households to develop entrepreneurial skills. Cost-benefit analysis showed that the benefits of biogas exceed the costs of the biogas projects. This implies that this technology should be promoted in rural households. Government financial incentives must be put in place to motivate a generation of organic Agri-prenuers.

Keywords: Agri-prenuers, biogas digester, biogas energy, disposal costs

Procedia PDF Downloads 131

Authors: Christos Theoharatos, Dimitris Tsourounis, Spiros Oikonomou, Andreas Makedonas

Abstract:

This paper focuses on the problem of visually inspecting and recognizing the road conditions in front of moving vehicles, targeting automotive scenarios. The goal of road inspection is to identify whether the road is slippery or not, as well as to detect possible anomalies on the road surface like potholes or body bumps/humps. Our work is based on an artificial intelligence methodology for real-time monitoring of road conditions in autonomous driving scenarios, using state-of-the-art deep convolutional neural network (CNN) techniques. Initially, the road and ego lane are segmented within the field of view of the camera that is integrated into the front part of the vehicle. A novel classification CNN is utilized to identify among plain and slippery road textures (e.g., wet, snow, etc.). Simultaneously, a robust detection CNN identifies severe surface anomalies within the ego lane, such as potholes and speed bumps/humps, within a distance of 5 to 25 meters. The overall methodology is illustrated under the scope of an integrated application (or system), which can be integrated into complete Advanced Driver-Assistance Systems (ADAS) systems that provide a full range of functionalities. The outcome of the proposed techniques present state-of-the-art detection and classification results and real-time performance running on AI accelerator devices like Intel’s Myriad 2/X Vision Processing Unit (VPU).

Keywords: deep learning, convolutional neural networks, road condition classification, embedded systems

Procedia PDF Downloads 129

Authors: Sumra Siddique Abbasi, Cheng Shikun

Abstract:

Biogas technology has rapidly developed in agriculture sector to upgrade and improve the life of farmers by providing them alternative and cost-effective energy source. Main purpose of this study is to understand the advantages of biogas plants by livestock owners either they are household-based livestock owners or may own farms for livestock. Similarly, a pertinent and major purpose of this research is to examine the factors affecting the decision to adopt biogas technologies at the household level. Based on the result, both public and private sector organization can make decisions related to the installation of biogas projects. Biogas is major energy source which can be used as an alternative and renewable energy source. This energy production technology can contribute in uplifting the lifestyle of farmers and can contribute into sustainable development of rural communities in Pakistan. People with livestock in any community in Pakistan can get benefit from biogas plants and it will contribute in sustainable development program which generates socio economic benefits, heath upgradation, cost effective energy source and positive impact on climate change or environmental issues. This study was conductive using survey method and descriptive analysis. One hundred fifty (150) farmers were the respondents who participated in survey. These farmers were from Layyah district of Punjab and were selected using snowball sampling technique. To generate the results, SPSS tool was used for data analysis.

Keywords: biogas plant, animal dunk, renewable energy, pakistan

Procedia PDF Downloads 66

Authors: Joel Y. Y. Loh, Geoffrey A. Ozin, Charles A. Mims, Nazir P. Kherani

Abstract:

A major goal in the emerging field of solar fuels is to realize an ‘artificial leaf’ – a material that converts light energy in the form of solar photons into chemical energy – using CO2 as a feedstock to generate useful chemical species. Enabling this technology will allow the greenhouse gas, CO2, emitted from energy and manufacturing production exhaust streams to be converted into valuable solar fuels or chemical products. Indium Oxide (In2O3) with surface hydroxyl (OH) groups have been shown to reduce CO2 in the presence of H2 to CO with a reaction rate of 15 μmol gcat−1 h−1. The likely mechanism is via a Frustrated Lewis Pair sites heterolytically splitting H2 to be absorbed and form protonic and hydric sites that can dissociate CO2. In this study, we investigate the dependence of oxygen composition of In2O3 on the CO2 reduction rate. In2O3-x films on quartz fiber paper were DC sputtered with an Indium target and varying O2/Ar plasma mixture. OH surface groups were then introduced by immersing the In2O3-x samples in KOH. We show that hydroxylated In2O3-x reduces more CO2 than non-hydroxylated groups and that a hydroxylated and higher O2/Ar ratio sputtered In2O3-x has a higher reaction rate of 45 μmol gcat-1 h-1. We show by electrical resistivity-temperature curves that H2 is adsorbed onto the surface of In2O3 whereas CO2 itself does not affect the indium oxide surface. We also present activation and ionization energy levels of the hydroxylated In2O3-x under vacuum, CO2 and H2 atmosphere conditions.

Keywords: solar fuels, photocatalysis, indium oxide nanoparticles, carbon dioxide

Procedia PDF Downloads 233

Authors: Won-Min Jo, Suk-Hee Park, Tae-Hee Kim

Abstract:

Although the number of vascular surgeries using vascular grafts is increasing, they are limited by vascular graft-related complications and size discrepancy. Current efforts to develop the ideal synthetic vascular graft for clinical application using tissue engineering or 3D printing are far from satisfactory. Therefore, we aimed to re-design the vascular graft with modified materials and 3D printing techniques and also demonstrated the improved applications of our vascular graft clinically. We designed the 3D printed polyvinyl alcohol (PVA) templates according to the vessel size and shape, and these were dip-coated with salt-suspended thermoplastic polyurethane (TPU). Next, the core template was removed to obtain a customized porous TPU graft. The mechanical testing and cytotoxicity studies of the synthetic 3D templated vascular grafts (3DT) were more appropriate compared with commercially available polytetrafluoroethylene (PTFE) grafts (ePTFE; standard graft, SG) for clinical use. Finally, we performed implantation of the 3DTs and SGs into the rat abdominal aorta as a patch technique. Four groups of the animal model (SG_7 days, SG_30 days, 3DT_7 days, and 3DT_30 days) were enrolled in this study. The abdominal aorta was surgically opened and sutured with SG or 3DT with 8/0 Prolene. The degree of endothelial cell activation, neovascularization, thrombus formation, calcification, inflammatory infiltrates, and fibrosis were analyzed histopathologically. There was significantly decreased thrombogenesis in the group treated with the 3DT for 30 days compared with the group treated with the SG for 7 and 30 days, and the 3DT for 7 days. In addition, the group treated with the 3DT for 30 days may also have shown increased postoperative endothelialization in the early stages. In conclusion, this study suggests the possibility of using the 3DT as an SG substitute in vascular surgery.

Keywords: 3D templated graft, hrombogenesis, calcification, inflammation

Procedia PDF Downloads 6

Authors: Laura Valdés-Santiago, José Luis Castro-Guillén, Jorge Noé García-Chávez, Rosalba Alonso-Rodríguez, Rafael Vargas-Bernal

Abstract:

The quality and availability of the water contained in dams (artificial bodies of water) are at risk due to the presence of uncontrolled growths of cyanobacteria capable of producing cyanotoxins that affect the ecosystem and harm the health of humans and animals. The physicochemical properties were measured, and the degree of eutrophy of four dams from Guanajuato was determined. They presented a pH of 6.1 to 8.4, conductivity of 121 to 415 μS/cm², chlorophyll of 0.43-42.43 μg/L, NO₃- 0-1.2 mg/L and PO₄3- 0.11 to 0.84 mg/L; considering these parameters, the prey most prone to the development of cyanobacterial blooms were El Palote dam, La Purísima dam, and Allende dam, but not El Conejo dam. The potentially toxic cyanobacteria identified were Planktothrix agardhii, Oscillatoria sp., Raphidiopsis sp., and Microcystis sp., Microcystin-LR, Nodularin, and Cylindrospermopsin were quantified, presenting values between 0.08-0.42 and 0.02-2.05 ppb, respectively, the water bodies with the highest concentration were El Palote dam and La Purísima dam. Microcystin-LR and/or Nodularin levels are within the guideline values for human consumption in drinking water established by the World Health Organization for Microcystin-LR and for Cylindrospermopsin by the Oregon Health Authority (OHA) in all dams. This work is relevant due to the use of these bodies of water for agriculture and human consumption in the state, and the presence of toxin-producing cyanobacteria can represent an environmental, ecotoxicological, and health problem, so it is recommended to establish a program of frequent monitoring of cyanobacteria and cyanotoxins in the state's dams.

Keywords: Planktrothrix agardhii, Raphidiopsis sp., Microcystis sp., Cyanobacterial blooms, Cyanotoxins

Procedia PDF Downloads 73

Authors: Kelvin Lo

Abstract:

Nowadays, numerical modelling in geotechnical engineering is very common but sophisticated. Many advanced input settings and considerable computational efforts are required to optimize the design to reduce the construction cost. To optimize a design, it usually requires huge numerical models. If the optimization is conducted manually, there is a potentially dangerous consequence from human errors, and the time spent on the input and data extraction from output is significant. This paper presents an automation process introduced to numerical modelling (Plaxis 2D) of a trench excavation supported by a secant-pile retaining structure for a top-down tunnel project. Python code is adopted to control the process, and numerical modelling is conducted automatically in every 20m chainage along the 200m tunnel, with maximum retained height occurring in the middle chainage. Python code continuously changes the geological stratum and excavation depth under groundwater flow conditions in each 20m section. It automatically conducts trial and error to determine the required pile length and the use of props to achieve the required factor of safety and target displacement. Once the bending moment of the pile exceeds its capacity, it will increase in size. When the pile embedment reaches the default maximum length, it will turn on the prop system. Results showed that it saves time, increases efficiency, lowers design costs, and replaces human labor to minimize error.

Keywords: automation, numerical modelling, Python, retaining structures

Procedia PDF Downloads 47

Authors: Santosh Thapa, Sankar Gurung

Abstract:

Chaupadi is a tradition widely practiced in the far and mid-western region of Nepal. It is a practice where girls and women are not allowed to inter the house and touch the food, water and milk during their menstruation period of 4-7 days. They have to spend all the nights during the period in a specific hut (Chhaupadi Goth) which is a bit far from their residence where they faces various kinds of risk and violence like bullying, snakes and insect bite, wild animal attack etc. Sometimes the girls even do not go to school during their menstruation periods. After childbirth, the woman must stay in a cow shed for 11 days in such Chhaupadi practiced areas. This study limits the Achham district of the far western region which is the most vulnerable Chhaupadi practicing district. Several governmental and non-governmental organizations have been involving and spending huge amount of money for capacity building and awareness raising campaign for last 2 decades but still 9 out of 75 Village Development Committees (VDCs) have been partially practicing Chaupadi in the district. This study shows that the school attendance rate of the girls during the period have visibly increased which helps to increase the number of the girl graduation as well. Similarly, the practice of Chhaupadi is one of the reasons for increasing the number of cases of uterus prolapsus and poor reproductive health of women and girls. Triggering tools are the one of the best ways to accelerate the awareness campaign in the VDCs. This study recommends that the local bodies should coordinate and lead the overall awareness campaign program to sustain the Chaupadi free VDCs.

Keywords: awareness campaign, chaupadi practice, gender discrimination, violence

Procedia PDF Downloads 307

Authors: Kyou Hee Shim, Hwa Sung Shin

Abstract:

When a thrombolysis agent is administered to treat ischemic stroke, excessive reactive oxygen species are generated due to a sudden provision of oxygen and occurs secondary damage cell necrosis. Thus, it is necessary to administrate adjuvant as well as thrombolysis agent to protect and reduce damaged tissue. As cerebral blood vessels have specific structure called blood-brain barrier (BBB), it is not easy to transfer substances from blood to tissue. Therefore, development of a drug carrier is required to increase drug delivery efficiency to brain tissue. In this study, cyanobacterial pigment from the blue-green algae known for having neuroprotective effect as well as antioxidant effect was nasally administrated for bypassing BBB. In order to deliver cyanobacterial pigment efficiently, the nano-sized liposome was used as a carrier. Liposomes were coated with a positive charge of chitosan since negative residues are present at the nasal mucosa the first gateway of nasal administration. Characteristics of liposome including morphology, size and zeta potential were analyzed by transmission electron microscope (TEM) and zeta analyzer. As a result of cytotoxic test, the liposomes were not harmful. Also, being administered a drug to the ischemic stroke animal model, we could confirm that the pharmacological effect of the pigment delivered by chitosan coated liposome was enhanced compared to that of non-coated liposome. Consequently, chitosan coated liposome could be considered as an optimized drug delivery system for the treatment of acute ischemic stroke.

Keywords: ischemic stroke, cyanobacterial pigment, liposome, chitosan, nasal administration

Procedia PDF Downloads 222

Authors: Maria Pavlova

Abstract:

In our days, it is possible to put the camera on different vehicles like quadcopter, train, airplane and etc. The camera also can be the input sensor in many different systems. That means the object recognition like non separate part of monitoring control can be key part of the most intelligent systems. The aim of this paper is to focus of the object recognition process during vehicles movement. During the vehicle’s movement the camera takes pictures from the environment without storage in Data Base. In case the camera detects a special object (for example human or animal), the system saves the picture and sends it to the work station in real time. This functionality will be very useful in emergency or security situations where is necessary to find a specific object. In another application, the camera can be mounted on crossroad where do not have many people and if one or more persons come on the road, the traffic lights became the green and they can cross the road. In this papers is presented the system has solved the aforementioned problems. It is presented architecture of the object recognition system includes the camera, Raspberry platform, GPS system, neural network, software and Data Base. The camera in the system takes the pictures. The object recognition is done in real time using the OpenCV library and Raspberry microcontroller. An additional feature of this library is the ability to display the GPS coordinates of the captured objects position. The results from this processes will be sent to remote station. So, in this case, we can know the location of the specific object. By neural network, we can learn the module to solve the problems using incoming data and to be part in bigger intelligent system. The present paper focuses on the design and integration of the image recognition like a part of smart systems.

Keywords: camera, object recognition, OpenCV, Raspberry

Procedia PDF Downloads 215