Search results for: traditional techniques

Authors: Alamrew Eyayu, Abebe Getahun, James Last Keyombe

Abstract:

Demand for fish continued to grow worldwide while production from capture fisheries has decreased. In the Eastern African Region (EAR), the open-access nature of capture fisheries has resulted in illegal fishing. Within communities engaged in fishing, small-scale fisheries support food security strategies and sustain livelihoods. Despite the role of fisheries in EAR, inland fisheries are vulnerable to loss, and management solutions authorized for inland fisheries are inadequate. This review investigates production potential, challenges, opportunities, and management of inland fisheries in the EAR. It is therefore expected that in aquaculture promising areas, the EAR will turn to depend more on aquaculture to meet the extended needs and supply gaps created as a result of capture fisheries shortfalls. However, aquaculture is still in its infant stage in the region, and there exists no adequate aquaculture policy framework and funds in some EAR (e.g., Ethiopia, Somalia). Stakeholders at all levels should entertain the importance of fishery-based activities for food security in EAR. As a result, easily implemented and community-oriented fisheries legislative documents need to be prepared for advancing sustainable fisheries management. Legislative documents might consider techniques of continual catch statistics (consider small water bodies as much as possible) of inland fisheries and enforcing existing laws to manage illegal fishing activities to accustom sustainable development of inland capture fisheries.

Keywords: aquaculture, capture fisheries, East Africa, fisheries management

Procedia PDF Downloads 29

Authors: V. Suganya, V. Balasuriya

Abstract:

The functioning of Micro and Small Scale (MSS) businesses in the northern part of Sri Lanka was vulnerable due to three decades of internal conflict and the subsequent post-war economic openings has resulted new market prospects for MSS businesses. MSS businesses survive and operate with limited resources and struggle to access finance, raw material, markets, and technology. This study attempts to identify the manner in which entrepreneurial orientation puts into practice by the business operators to overcome these business challenges. Business operators in the traditional food processing sector are taken for this study as this sub-sector of the food industry is developing at a rapid pace. A review of the literature was done to recognize the concepts of entrepreneurial orientation, defining MMS businesses and the manner in which business performance is measured. Direct interview method supported by a structured questionnaire is used to collect data from 80 respondents; based on a fixed interval random sampling technique. This study reveals that more than half of the business operators have opted to commence their business ventures as a result of identifying a market opportunity. 41 per cent of the business operators are highly entrepreneurial oriented in a scale of 1 to 5. Entrepreneurial orientation shows significant relationship and strongly correlated with business performance. Pro-activeness, innovativeness and competitive aggressiveness shows a significant relationship with business performance while risk taking is negative and autonomy is not significantly related to business performance. It is evident that entrepreneurial oriented business practices contribute to better business performance even though 70 per cent prefer the ideas/views of the support agencies than the stakeholders when making business decisions. It is recommended that appropriate training should be introduced to develop entrepreneurial skills focusing to improve business networks so that new business opportunities and innovative business practices are identified.

Keywords: Micro and Small Scale (MMS) businesses, entrepreneurial orientation (EO), food processing, business operators

Procedia PDF Downloads 497

Authors: Xiao-Yan Li, Takashi Hashimoto, Guanhong Li, Shuo Yang

Abstract:

In Japanese, onomatopoeia is an important element in the lively expression of feelings and experiences. It is very difficult for students of Japanese to acquire onomatopoeia, especially, its nuances. In this paper, based on traditional L2 learning theories, we propose a new method to improve the efficiency of teaching the nuances – both explicit and tacit - to non-native speakers of Japanese. The method for teaching the tacit nuances of onomatopoeia consists of three elements. First is to teach the formal rules representing the explicit nuances of onomatopoeic words. Second is to have the students create new onomatopoeic words by utilizing those formal rules. The last element is to provide feedback by evaluating the onomatopoeias created. Our previous study used five-grade relative estimation. However students were confused about the five-grade system, because they could not understand the evaluation criteria only based on a figure. In this new system, then, we built an evaluation database through native speakers’ narrative interpretation. We asked Japanese native speakers to describe their awareness of the nuances of onomatopoeia in writing. Then they voted on site and defined priorities for showing to learners on the system. To verify the effectiveness of the proposed method and the learning system, we conducted a preliminary experiment involving two groups of subjects. While Group A got feedback about the appropriateness of their onomatopoeic constructions from the native speakers’ narrative interpretation, Group B got feedback just in the form of the five-grade relative estimation. A questionnaire survey administered to all of the learners clarified our learning system availability and also identified areas that should be improved. Repetitive learning of word-formation rules, creating new onomatopoeias and gaining new awareness from narrative interpretation is the total process used to teach the explicit and tacit nuances of onomatopoeia.

Keywords: onomatopoeia, tacit nuance, narrative interpretation, e-learning system, second language teaching

Procedia PDF Downloads 399

Authors: Ryuji Hashimoto, Yuri Murayama, Kiyoshi Izumi

Abstract:

This study aims to analyze the mechanism underlying the power law of stock returns through artificial market simulations. Although traditional financial theory postulates a Gaussian distribution for stock price fluctuations, empirical evidence indicates that the tail distribution of these fluctuations follows a power law. Research motivated by this gap has proposed various hypotheses regarding the components that generate power laws in financial price fluctuations. One hypothesis attributes the power law to investor behavior, whereas the other points to the demand distribution of institutional investors. However, existing research has not simultaneously modeled these components to study their individual contributions to the power law and their interactions. The complexity of real financial markets complicates the isolation of the contribution of a single component using existing data. To determine the extent to which each component contributes to the formation of this stylized fact and the effect when multiple components are present simultaneously, this study utilizes artificial markets and optimal transport (OT) to conduct controlled experiments. Artificial markets have been used for both financial counterfactual analysis and synthetic data generation, facing trade-off between explainability and realism. The proposed pipeline of hypotheses evaluation cycles of agent models based on quantitative evaluation using OT tackles this trade-off by examining the impact of each component in the agent model on the realism of the simulation, providing insights into why the simulations are able to reproduce real-world phenomena. The experiments revealed that the informational effect of prices plays a dominant role in generating realistic power law distributions, and a synergistic effect exists among multiple components.

Keywords: power law, artificial market, multi-agent simulation, optimal transport, financial synthetic data

Procedia PDF Downloads 0

Authors: Osama Sassi, Manal Eltorki, Iftikhar Ahmad

Abstract:

Poor integrity is one of the major causes of leaks and accidents in gas transmission pipelines. To ensure safe operation, it is must to have efficient and effective pipeline integrity management (PIM) system. The corrosion management is one of the important aspects of successful pipeline integrity management program together design, material selection, operations, risk evaluation and communication aspects to maintain pipelines in a fit-for-service condition. The objective of a corrosion management plan is to design corrosion mitigation, monitoring, and inspection strategy, and for maintenance in a timely manner. This paper presents the experience of corrosion management of a gas transmission pipeline from Wafa field to Mellitah gas plant in Libya. The pipeline is 525.5 km long and having 32 inches diameter. It is a buried pipeline. External corrosion on pipeline is controlled with a combination of coatings and cathodic protection while internal corrosion is controlled with a combination of chemical inhibitors, periodic cleaning and process control. The monitoring and inspection techniques provide a way to measure the effectiveness of corrosion control systems and provide an early warning when changing conditions may be causing a corrosion problem. This paper describes corrosion management system used in Mellitah Oil & Gas BV for its gas transmission pipeline based on standard practices of corrosion mitigation and inspection.

Keywords: corrosion mitigation on gas transmission pipelines, pipeline integrity management, corrosion management of gas pipelines, prevention and inspection of corrosion

Procedia PDF Downloads 84

Authors: Atefeh Heydari, Mohammadali Tavakoli, Naomie Salim

Abstract:

In recent years, we have witnessed that online reviews are the most important source of customers’ opinion. They are progressively more used by individuals and organisations to make purchase and business decisions. Unfortunately, for the reason of profit or fame, frauds produce deceptive reviews to hoodwink potential customers. Their activities mislead not only potential customers to make appropriate purchasing decisions and organisations to reshape their business, but also opinion mining techniques by preventing them from reaching accurate results. Spam reviews could be divided into two main groups, i.e. multiple and singleton spam reviews. Detecting a singleton spam review that is the only review written by a user ID is extremely challenging due to lack of clue for detection purposes. Singleton spam reviews are very harmful and various features and proofs used in multiple spam reviews detection are not applicable in this case. Current research aims to propose a novel supervised technique to detect singleton spam reviews. To achieve this, various features are proposed in this study and are to be combined with the most appropriate features extracted from literature and employed in a classifier. In order to compare the performance of different classifiers, SVM and naive Bayes classification algorithms were used for model building. The results revealed that SVM was more accurate than naive Bayes and our proposed technique is capable to detect singleton spam reviews effectively.

Keywords: classification algorithms, Naïve Bayes, opinion review spam detection, singleton review spam detection, support vector machine

Procedia PDF Downloads 310

Authors: Maryam Kiani

Abstract:

This study focuses on the development of composite nanomaterials based on SiO2 and carbon black for oxygen reduction reaction (ORR) electrocatalysts in batteries and fuel cells. The aim was to explore the potential of these composite materials as efficient catalysts for ORR, which is a critical process in energy conversion devices. The SiO2/carbon black composite nanomaterials were synthesized using a facile and scalable method. The morphology, structure, and electrochemical properties of the materials were characterized using various techniques, including scanning electron microscopy (SEM), X-ray diffraction (XRD), and electrochemical measurements. The results demonstrated that the incorporation of SiO2 into the carbon black matrix enhanced the ORR performance of the composite material. The composite nanomaterials exhibited improved electrocatalytic activity, enhanced stability, and increased durability compared to pure carbon black. The presence of SiO2 facilitated the formation of active sites, improved electron transfer, and increased the surface area available for ORR. This study contributes to the advancement of battery and fuel cell technology by offering a promising approach for the development of high-performance ORR electrocatalysts. The SiO2/carbon black composite nanomaterials show great potential for improving the efficiency and durability of energy conversion devices, leading to more sustainable and efficient energy solutions.

Keywords: oxygen reduction reaction, batteries, fuel cells, electrrocatalyst

Procedia PDF Downloads 123

Authors: Genesis Julyus T. Agcaoili, Esperanza C. Cabrera

Abstract:

Thirty (30) isolates of lactic acid bacteria (LAB) from traditionally-prepared fermented products specifically fermented soy-bean paste, fermented mustard and fermented rice-fish mixture were studied for their in vitro antimicrobial and cytotoxic activities. Seventeen (17) isolates were identified as Lactobacillus plantarum, while 13 isolates were identified as Enterococcus spp using 16s rDNA sequences. Disc diffusion method was used to determine the antibacterial activity of LAB against Staphylococcus aureus (ATCC 25923) and Escherichia coli (ATCC 25922), while the modified agar overlay method was used to determine the antifungal activity of LAB isolates on the yeast Candida albicans, and the dermatophytes Microsporum gypseum, Trichophyton rubrum and Epidermophyton floccosum. The filter-sterilized LAB supernatants were evaluated for their cytotoxicity to mammalian colon cancer cell lines (HT-29 and HCT116) and normal human dermal fibrolasts (HDFn) using resazurin assay (PrestoBlueTM). Colchicine was the positive control. No antimicrobial activity was observed against the bacterial test organisms and the yeast Candida albicans. On the other hand, all of the tested LAB strains were fungicidal for all the test dermatophytes. Cytotoxicity index profiles of the supernatants of the 15 randomly picked LABs and negative control (brain heart infussion broth) suggest nontoxicity to the cells when compared to colchicine, whereas all LAB supernatants were found to be cytotoxic to HT-29 and HCT116 colon cancer cell lines. Results provide strong support for the role of the lactic acid bacteria studied in antimicrobial treatment and anticancer therapy.

Keywords: antimicrobial, fermented products, fungicidal activity, lactic acid bacteria, probiotics

Procedia PDF Downloads 239

Authors: Cleopatra Oluseye Ibukun

Abstract:

Following the endogenous growth theory, entrepreneurship has been considered pivotal to economic growth and development, particularly in developing countries like Nigeria. Meanwhile, efforts to reduce unemployment has yielded minimal result with over 36% of youth unemployment and a dwindling economic growth despite the country’s natural and human resource endowment. This study, therefore, investigates the effects of entrepreneurship and institutional quality on economic growth and unemployment in Nigeria over the period 1996 to 2018. The data is obtained from the National Bureau of Statistics (NBS), World Bank’s World Development Indicators (WDI), and the World Bank’s World Governance Indicators (WGI). The study period is guided by the availability of data, and the study employs both descriptive and econometric techniques of analysis (specifically, the Auto-regressive Distributed Lag Approach). This approach is preferable given that the variables are stationary at the first difference, while the bounds test suggests the existence of co-integration among the variables. By implication, an increase in entrepreneurship significantly improves economic growth, and it reduces unemployment in both the short-run and the long-run. Besides, institutional quality proxied by the control of corruption, political stability, and government effectiveness significantly mediates the interaction between entrepreneurship and macroeconomic performance. This study concludes that improved institutional quality enhances the effect of entrepreneurship on economic growth and unemployment in Nigeria, and it recommends an improvement in Nigeria’s institutional quality because it can jeopardise or augment the effect of entrepreneurship on macroeconomic performance.

Keywords: entrepreneurship, institutional quality, unemployment, gross domestic product, Nigeria

Procedia PDF Downloads 139

Authors: Viacheslav Shkuratskyy, Aminu Bello Usman, Michael O’Dea, Saifur Rahman Sabuj

Abstract:

This paper examines relationships between solar activity and earthquakes; it applied machine learning techniques: K-nearest neighbour, support vector regression, random forest regression, and long short-term memory network. Data from the SILSO World Data Center, the NOAA National Center, the GOES satellite, NASA OMNIWeb, and the United States Geological Survey were used for the experiment. The 23rd and 24th solar cycles, daily sunspot number, solar wind velocity, proton density, and proton temperature were all included in the dataset. The study also examined sunspots, solar wind, and solar flares, which all reflect solar activity and earthquake frequency distribution by magnitude and depth. The findings showed that the long short-term memory network model predicts earthquakes more correctly than the other models applied in the study, and solar activity is more likely to affect earthquakes of lower magnitude and shallow depth than earthquakes of magnitude 5.5 or larger with intermediate depth and deep depth.

Keywords: k-nearest neighbour, support vector regression, random forest regression, long short-term memory network, earthquakes, solar activity, sunspot number, solar wind, solar flares

Procedia PDF Downloads 75

Authors: Mubeshera Tufail

Abstract:

The purpose of the study was to explore the experiences and challenges faced by teachers and students with Flipped Classroom Instruction (FCI) for an undergraduate course at university level. The Flipped Classroom lesson plan consisted of two components: one was out-of-class component consisting of learning material for reading for students and other was within-class component involving a class quiz, class activity and the feedback/further reading task. Besides, experiences, the research study also covered the adaptations made to improve their experiences with Flipped Classroom during the study. The phenomenological research strategy was used for this research study. The data consisted of weekly reflective journals documented by class teacher and students. The reflective journals were recorded by teacher and students while working in Flipped Classroom for an undergraduate course at university level. The main challenges highlighted by teacher were related to effort and time required for planning, time management and students' guidance for shift of their role from passive to independent learner. The main challenges found in reflective journals of students were personal computers issue, electricity and internet speed issue. It is recommended to adapt to some locally useful lesson planning and classroom management techniques to enhance the effectiveness of Flipped Classroom Instruction in an undergraduate university level course.

Keywords: flipped classroom instruction, undergraduate students, independent learner, technology-integrated classroom

Procedia PDF Downloads 164

Authors: Djoudi Abdelhak, Djibaoui Rachid, Reguieg Yassaad Houcine

Abstract:

Our study focuses on the identification of some species of Pseudomonas (P4, P5, P7 and P8) isolated from saline soils in northwestern Algeria and the effect of their metabolites on the growth of Alternaria alternata the causative agent of the blight of the bean disease (Vicia faba). We are also interested in stimulating the growth of this plant species in saline conditions (60 mM/l NaCl) and the absence of salts. The analysis focuses on rates of inhibition of mycelial growth of Alternaria alternata strain and the rate of growth of plants inoculated with strains of Pseudomonas expressed by biometrics. According to the results of the in-vitro test, P5 and P8 species and their metabolites showed a significant effect on mycelia growth and production of spores of Alternaria alternata. The in-vivo test shows that the species P8 and P5 were significantly and positively influencing the growth in biometric parameters of the bean in saline and salt-free condition. Inoculation with strain P5 has promoted the growth of the bean in stem height, stem fresh weight and dry weight of stems of 108.59%, 115.28%, 104.33%, respectively, in the presence of salt Inoculation with strain P5 has fostered the growth of the bean stem fresh weight of 112.47% in the presence of salt The effect of Pseudomonas species on the development of Vicia faba and the growth of Alternaria alternata is considering new techniques and methods of biological production and crop protection.

Keywords: pseudomonas, vicia faba, alternaria alternata, promoting of plant growth

Procedia PDF Downloads 393

Authors: Moustafa M. S. Sanad

Abstract:

The worsening of energy supply crisis and the exacerbation of climate change by environmental pollution problems have become the greatest threat to human life. One of the ways to confront these problems is to rely on renewable energy and its storage systems. Nowadays, huge attention has been directed to the development of lithium-ion batteries (LIBs) as efficient tools for storing the clean energy produced by green sources like solar and wind energies. Accordingly, the demand for powerful electrode materials with excellent electrochemical characteristics has been progressively increased to meet fast and continuous growth in the market of energy storage systems. Therefore, the electronic and electrical properties of conversion anode materials for rechargeable lithium-ion batteries (LIBs) can be enhanced by introducing lattice defects and oxygen vacancies in the crystal structure. In this regard, the intended presentation will demonstrate new insights and effective ways for enhancing the electrical conductivity and improving the electrochemical performance of different anode materials such as MgFe₂O₄, CdFe₂O₄, Fe₃O₄, LiNbO₃ and Nb₂O₅. The changes in the physicochemical and morphological properties have been deeply investigated via structural and spectroscopic analyses (e.g., XRD, FESEM, HRTEM, and XPS). Moreover, the enhancement in the electrochemical properties of these anode materials will be discussed through Galvanostatic Cycling (GC), Cyclic Voltammetry (CV) and Electrochemical Impedance Spectroscopy (EIS) techniques.

Keywords: structure modification, cationic substitution, non-stoichiometric synthesis, plasma treatment, lithium-ion batteries

Procedia PDF Downloads 64

Authors: S. S. Sree Sanker, K. N. Madhusoodanan

Abstract:

Optical biosensors are dominant alternative for traditional analytical methods, because of their small size, simple design and high sensitivity. Photonic sensing method is one of the recent advancing technology for biosensors. It measures the change in refractive index which is induced by the difference in molecular interactions due to the change in concentration of the analyte. Glucose is an aldosic monosaccharide, which is a metabolic source in many of the organisms. The terahertz waves occupies the space between infrared and microwaves in the electromagnetic spectrum. Terahertz waves are expected to be applied to various types of sensors for detecting harmful substances in blood, cancer cells in skin and micro bacteria in vegetables. We have designed glucose sensors using silicon based 1D and 2D photonic crystal pillar arrays in terahertz frequency range. 1D photonic crystal has rectangular pillars with height 100 µm, length 1600 µm and width 50 µm. The array period of the crystal is 500 µm. 2D photonic crystal has 5×5 cylindrical pillar array with an array period of 75 µm. Height and diameter of the pillar array are 160 µm and 100 µm respectively. Two samples considered in the work are blood and glucose solution, which are labelled as sample 1 and sample 2 respectively. The proposed sensor detects the concentration of glucose in the samples from 0 to 100 mg/dL. For this, the crystal was irradiated with 0.3 to 3 THz waves. By analyzing the obtained S parameter, the refractive index of the crystal corresponding to the particular concentration of glucose was measured using the parameter retrieval method. Refractive indices of the two crystals decreased gradually with the increase in concentration of glucose in the sample. For 1D photonic crystals, a gradual decrease in refractive index was observed at 1 THz. 2D photonic crystal showed this behavior at 2 THz. The proposed sensor was simulated using CST Microwave studio. This will enable us to develop a model which can be used to characterize a glucose sensor. The present study is expected to contribute to blood glucose monitoring.

Keywords: CST microwave studio, glucose sensor, photonic crystal, terahertz waves

Procedia PDF Downloads 282

Authors: G. H. B. Dilhari, A. A. D. T. Saparamadu

Abstract:

Sri Lanka is one of the prominent countries for the coir production. The coir is one of the by-products of the coconut and the coir industry is considered to be one of the traditional industries in Sri Lanka. Because of the inherent nature of the coir industry, labourers play a significant role in the coir production process. The study has analyzed the determinants of the income of the household level coir yarn labourers. The study was conducted in the Kumarakanda Grama Niladhari division. Simple random sampling was used to generate a sample of 100 household level coir yarn labourers and structured questionnaire, personal interviews, and discussion were performed to gather the required data. The obtained data were statistically analyzed by using Statistical Package for Social Science (SPSS) software. Mann-Whitney U and Kruskal-Wallis test were performed for mean comparison. The findings revealed that the household level coir yarn industry is dominated by the female workers and it was identified that fewer numbers of workers have engaged in this industry as the main occupation. In addition to that, elderly participation in the industry is higher than the younger participation and most of them have engaged in the industry as a source of extra income. Level of education, the methods of engagement, satisfaction, engagement in the industry by the next generation, support from the government, method of government support, working hours per day, employed as a main job, number of completed units per day, suffering from job related diseases and type of the diseases were related with income level of household level coir yarn laboures. The recommendations as to flourish in future includes, technological transformation for coir yarn production, strengthening the raw material base and regulating the raw material supply, introduction of new technologies, markets and training programmes, the establishment of the labourers’ association, the initiation of micro credit schemes and better consideration about the job oriented diseases.

Keywords: coir yarn, determinants, income, Sri Lanka

Procedia PDF Downloads 314

Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Daniyal Haider, Xiaodong Yang

Abstract:

Chest X-rays are instrumental in the detection and monitoring of a wide array of diseases, including viral infections such as COVID-19, tuberculosis, pneumonia, lung cancer, and various cardiac and pulmonary conditions. To enhance the accuracy of diagnosis, artificial intelligence (AI) algorithms, particularly deep learning models like Convolutional Neural Networks (CNNs), are employed. However, these deep learning models demand a substantial and varied dataset to attain optimal precision. Generative Adversarial Networks (GANs) can be employed to create new data, thereby supplementing the existing dataset and enhancing the accuracy of deep learning models. Nevertheless, GANs have their limitations, such as issues related to stability, convergence, and the ability to distinguish between authentic and fabricated data. In order to overcome these challenges and advance the detection and classification of CXR normal and abnormal images, this study introduces a distinctive technique known as DCWGAN (Diverse Conditional Wasserstein GAN) for generating synthetic chest X-ray (CXR) images. The study evaluates the effectiveness of this Idiosyncratic DCWGAN technique using the ResNet50 model and compares its results with those obtained using the traditional GAN approach. The findings reveal that the ResNet50 model trained on the DCWGAN-generated dataset outperformed the model trained on the classic GAN-generated dataset. Specifically, the ResNet50 model utilizing DCWGAN synthetic images achieved impressive performance metrics with an accuracy of 0.961, precision of 0.955, recall of 0.970, and F1-Measure of 0.963. These results indicate the promising potential for the early detection of diseases in CXR images using this Inimitable approach.

Keywords: CNN, classification, deep learning, GAN, Resnet50

Procedia PDF Downloads 90

Authors: Djebbar Atmani, Dina Kilani, Tristan Richard

Abstract:

Medicinal plants are an important source for the discovery of potential new substances for use in medicine and food. Pistacia lentiscus, Fraxinus angustifolia and Clematis flammula, plants growing in the Mediterranean basin, are widely used in traditional medicine. Therefore, the present study was designed to investigate their antioxidant, anti-inflammatory, antidiabetic, anti-mutagenic/genotoxic and neuroprotective potential and identification of active compounds using appropriate methodology. Plant extracts and fractions exhibited high scavenging capacity against known radicals, enhanced superoxide dismutase and catalase activitiesand restored blood glucose levels, in vivo, to normal values, in agreement with the in vitro enzymatic inhibition data, through inhibition of amylase and glucosidase activities. Administration of Pistacia lentiscus extracts significantly decreased carrageenan-induced mice paw oedema and reduced effectively IL-1β levels in cell culture, whereas Fraxinus angustifolia extracts showed good healing capacity against wounds when applied topically on rabbits. Pistacia lentiscus and Fraxinus angustifolia extracts showed good neuro-protection and restored cognitive functions in mice, while Clematis flammula extracts showed potent anti-ulcerogenic activity associated to a promising anti-mutagenic/genotoxic activity. HPLC-MS and NMR analyses allowed the identification and structural elucidation of several known and new anthocyanins, flavonols and flavanols. Therefore, Pistacia lentiscus, Fraxinus angustifolia and Clematis flammulacould be used in palliative treatments against inflammatory conditions and diabetes complications, as well as against deterioration of cognitive functions.

Keywords: pistacia lentiscus, clematis flammula, fraxinus angustifolia, phenolic compounds, biological activity

Procedia PDF Downloads 76

Authors: Kyung Bae Park, Sung Ho Ha

Abstract:

Online user-generated contents (UGC) significantly change the way customers behave (e.g., shop, travel), and a pressing need to handle the overwhelmingly plethora amount of various UGC is one of the paramount issues for management. However, a current approach (e.g., sentiment analysis) is often ineffective for leveraging textual information to detect the problems or issues that a certain management suffers from. In this paper, we employ text mining of Latent Dirichlet Allocation (LDA) on a popular online review site dedicated to complaint from users. We find that the employed LDA efficiently detects customer complaints, and a further inspection with the visualization technique is effective to categorize the problems or issues. As such, management can identify the issues at stake and prioritize them accordingly in a timely manner given the limited amount of resources. The findings provide managerial insights into how analytics on social media can help maintain and improve their reputation management. Our interdisciplinary approach also highlights several insights by applying machine learning techniques in marketing research domain. On a broader technical note, this paper illustrates the details of how to implement LDA in R program from a beginning (data collection in R) to an end (LDA analysis in R) since the instruction is still largely undocumented. In this regard, it will help lower the boundary for interdisciplinary researcher to conduct related research.

Keywords: latent dirichlet allocation, R program, text mining, topic model, user generated contents, visualization

Procedia PDF Downloads 189

Authors: Dmytro Zubov, Francesco Volponi

Abstract:

In this paper, D-Wave quantum computing Ising model is used for the forecasting of positive extremes of daily mean air temperature. Forecast models are designed with two to five qubits, which represent 2-, 3-, 4-, and 5-day historical data respectively. Ising model’s real-valued weights and dimensionless coefficients are calculated using daily mean air temperatures from 119 places around the world, as well as sea level (Aburatsu, Japan). In comparison with current methods, this approach is better suited to predict heat wave values because it does not require the estimation of a probability distribution from scarce observations. Proposed forecast quantum computing algorithm is simulated based on traditional computer architecture and combinatorial optimization of Ising model parameters for the Ronald Reagan Washington National Airport dataset with 1-day lead-time on learning sample (1975-2010 yr). Analysis of the forecast accuracy (ratio of successful predictions to total number of predictions) on the validation sample (2011-2014 yr) shows that Ising model with three qubits has 100 % accuracy, which is quite significant as compared to other methods. However, number of identified heat waves is small (only one out of nineteen in this case). Other models with 2, 4, and 5 qubits have 20 %, 3.8 %, and 3.8 % accuracy respectively. Presented three-qubit forecast model is applied for prediction of heat waves at other five locations: Aurel Vlaicu, Romania – accuracy is 28.6 %; Bratislava, Slovakia – accuracy is 21.7 %; Brussels, Belgium – accuracy is 33.3 %; Sofia, Bulgaria – accuracy is 50 %; Akhisar, Turkey – accuracy is 21.4 %. These predictions are not ideal, but not zeros. They can be used independently or together with other predictions generated by different method(s). The loss of human life, as well as environmental, economic, and material damage, from extreme air temperatures could be reduced if some of heat waves are predicted. Even a small success rate implies a large socio-economic benefit.

Keywords: heat wave, D-wave, forecast, Ising model, quantum computing

Procedia PDF Downloads 502

Authors: Anuradha Chug, Sunali Gandhi

Abstract:

Regression Testing is a very expensive and time-consuming process carried out to ensure the validity of modified software. Due to the availability of insufficient resources to re-execute all the test cases in time constrained environment, efforts are going on to generate test data automatically without human efforts. Many search based techniques have been proposed to generate efficient, effective as well as optimized test data, so that the overall cost of the software testing can be minimized. The generated test data should be able to uncover all potential lapses that exist in the software or product. Inspired from the natural behavior of bat for searching her food sources, current study employed a meta-heuristic, search-based bat algorithm for optimizing the test data on the basis certain parameters without compromising their effectiveness. Mathematical functions are also applied that can effectively filter out the redundant test data. As many as 50 Java programs are used to check the effectiveness of proposed test data generation and it has been found that 86% saving in testing efforts can be achieved using bat algorithm while covering 100% of the software code for testing. Bat algorithm was found to be more efficient in terms of simplicity and flexibility when the results were compared with another nature inspired algorithms such as Firefly Algorithm (FA), Hill Climbing Algorithm (HC) and Ant Colony Optimization (ACO). The output of this study would be useful to testers as they can achieve 100% path coverage for testing with minimum number of test cases.

Keywords: regression testing, test case selection, test case prioritization, genetic algorithm, bat algorithm

Procedia PDF Downloads 383

Authors: Jagannath P. Tegar

Abstract:

The new National Education Policy (NEP) 2020 of Govt. of India has envisaged a major overhaul of the education system of India, in particular, the revamping of the Curriculum of Higher Education. In this process, the faculty members of the Indian universities and institutions have a challenging role in developing the curriculum, which is a shift from the traditional (content-based) curriculum to a student-centric- outcome-based Curriculum (SC-OBC) to be implemented in all of the Universities and institutions. The efforts and initiatives on the design and implementation of SC-OBC are remarkable in the engineering and technical education landscape of the country, but it is still in its early stages and many more steps are needed for the successful adaptation in every level of Higher Education. The premier institute of Govt. of India (NITTTR, Bhopal) has trained and developed the capacity and capability among the teachers of Polytechnics on the design and development of Student Centric - Outcome Based Curriculum and also providing academic consultancy for reforming curriculum in line of NEP- 2020 envisions for the states such as Chhattisgarh, Bihar and Maharashtra to make them responsibly ready for such a new shift in Higher Education. This research-based paper is on three main aspects: 1) the level of acceptance and preparedness of teachers /faculty towards NEP-2020 and student-centred outcome-based learning. 2) the extent of implementing NEP-2020 and student-centered outcome-based learning at Indian institutions/ universities and 3) the challenges of implementing NEP-2020 and student-centered outcome-based learning outcome-based education in the Indian context. The paper content will inspire curriculum designers and developers to prepare SC-OBC that meets the specific needs of industry and society at large, which is intended in the NEP-2020 of Govt. of India

Keywords: outcome based curriculum, student centric learning, national education policy -2020, implementation of nep-2020. outcome based learning, higher education curriculum

Procedia PDF Downloads 83

Authors: Maxime A. J. Kuitche, Ruxandra M. Botez, Arthur Guillemin

Abstract:

As the Unmanned Aerial Systems have found diverse utilities in both military and civil aviation, the necessity to obtain an accurate aerodynamic model has shown an enormous growth of interest. Recent modeling techniques are procedures using optimization algorithms and statistics that require many flight tests and are therefore extremely demanding in terms of costs. This paper presents a procedure to estimate the aerodynamic behavior of an unmanned aerial system from a numerical approach using computational fluid dynamic analysis. The study was performed using an unstructured mesh obtained from a grid convergence analysis at a Mach number of 0.14, and at an angle of attack of 0°. The flow around the aircraft was described using a standard k-ω turbulence model. Thus, the Reynold Averaged Navier-Stokes (RANS) equations were solved using ANSYS FLUENT software. The method was applied on the UAS-S45 designed and manufactured by Hydra Technologies in Mexico. The lift, the drag, and the pitching moment coefficients were obtained at different angles of attack for several flight conditions defined in terms of altitudes and Mach numbers. The results obtained from the Computational Fluid Dynamics analysis were compared with the results obtained by using the DATCOM semi-empirical procedure. This comparison has indicated that our approach is highly accurate and that the aerodynamic model obtained could be useful to estimate the flight dynamics of the UAS-S45.

Keywords: aerodynamic modelling, CFD Analysis, ANSYS FLUENT, UAS-S45

Procedia PDF Downloads 377

Authors: Mohammad Sharifi Bohlouli

Abstract:

Turkish language with many dialects is native or official language of great number of people all around the world. The Qashqaie dialect of Turkish language is spoken by the Qashqaie tribe mostly scattered in the southern part of Iran. This paper aims at analyzing the tense system of this dialect to detect the type and number of tense and aspects available to its speakers. To collect a reliable data, a group of 50 old native speakers were randomly chosen as the informants and different techniques such as; Shuy et al interviews, selective listening ,and eavesdropping were used. The results of data analysis showed that the tense system in the Qashqaie dialect of Turkish language includes 3 absolute tenses , 6 aspectual , and 2 subjunctive ones. The interesting part of the study is that Qashqaie dialect enables its speakers to make a kind of aspectual opposition through verb structure which seems to be almost impossible through verb forms in any other nonturkish languages. For example in the following examples sentences 1 &2 and 3&4 have the same translation In English although they are different in both meaning and structure. 1. Ali ensha yazirdi. 2. Ali ensha yazirmush. (Ali was writing a composition.) 3. Ali yadmishdi. 4. Ali yadmishimish. ( Ali had slept.) The changes in the verb structure in Qashqaie dialect enables its speakers to say that whether the doer of the action remembers the process of doing the action or not. So, it presents a new aspectual opposition as Observed /nonobserved. The research findings reveal many other regularities and linguistic features that can be useful for linguists interested in Turkish in general and for those interested in tense and aspect and also they can be helpful for different pedagogical purposes including teaching and translating.

Keywords: qashqaie dialect, tense, aspect, linguistics, Turkish Language

Procedia PDF Downloads 363

Authors: Faruk Ozdemir, Roy Kalawsky, Peter Hubbard

Abstract:

Accurate estimation of RUL provides a basis for effective predictive maintenance, reducing unexpected downtime for industrial equipment. However, while models such as the Random Forest have effective predictive capabilities, they are the so-called ‘black box’ models, where interpretability is at a threshold to make critical diagnostic decisions involved in industries related to aviation. The purpose of this work is to present a prognostic framework that embeds Explainable Artificial Intelligence (XAI) techniques in order to provide essential transparency in Machine Learning methods' decision-making mechanisms based on sensor data, with the objective of procuring actionable insights for the aviation industry. Sensor readings have been gathered from critical equipment such as turbofan jet engine and landing gear, and the prediction of the RUL is done by a Random Forest model. It involves steps such as data gathering, feature engineering, model training, and evaluation. These critical components’ datasets are independently trained and evaluated by the models. While suitable predictions are served, their performance metrics are reasonably good; such complex models, however obscure reasoning for the predictions made by them and may even undermine the confidence of the decision-maker or the maintenance teams. This is followed by global explanations using SHAP and local explanations using LIME in the second phase to bridge the gap in reliability within industrial contexts. These tools analyze model decisions, highlighting feature importance and explaining how each input variable affects the output. This dual approach offers a general comprehension of the overall model behavior and detailed insight into specific predictions. The proposed framework, in its third component, incorporates the techniques of causal analysis in the form of Granger causality tests in order to move beyond correlation toward causation. This will not only allow the model to predict failures but also present reasons, from the key sensor features linked to possible failure mechanisms to relevant personnel. The causality between sensor behaviors and equipment failures creates much value for maintenance teams due to better root cause identification and effective preventive measures. This step contributes to the system being more explainable. Surrogate Several simple models, including Decision Trees and Linear Models, can be used in yet another stage to approximately represent the complex Random Forest model. These simpler models act as backups, replicating important jobs of the original model's behavior. If the feature explanations obtained from the surrogate model are cross-validated with the primary model, the insights derived would be more reliable and provide an intuitive sense of how the input variables affect the predictions. We then create an iterative explainable feedback loop, where the knowledge learned from the explainability methods feeds back into the training of the models. This feeds into a cycle of continuous improvement both in model accuracy and interpretability over time. By systematically integrating new findings, the model is expected to adapt to changed conditions and further develop its prognosis capability. These components are then presented to the decision-makers through the development of a fully transparent condition monitoring and alert system. The system provides a holistic tool for maintenance operations by leveraging RUL predictions, feature importance scores, persistent sensor threshold values, and autonomous alert mechanisms. Since the system will provide explanations for the predictions given, along with active alerts, the maintenance personnel can make informed decisions on their end regarding correct interventions to extend the life of the critical machinery.

Keywords: predictive maintenance, explainable artificial intelligence, prognostic, RUL, machine learning, turbofan engines, C-MAPSS dataset

Procedia PDF Downloads 10

Authors: Badr M. Thamer

Abstract:

The use of hydrogels as adsorbents for pollutants removal from wastewater is limited due to their high swelling properties and the difficulty in recovering them after the adsorption process. To overcome these problems, a new hydrogel nanocomposite based on chitosan-g-polyacrylic acid/oxidized electrospun carbon nanofibers (CT-g-PAA/O-ECNFs) was prepared by in-situ grafting polymerization process. The prepared hydrogel nanocomposite was used as a novel effective and highly reusable adsorbent for the removal of methylene blue (MB) from polluted water with low cost. The morphology and the structure of CT-g-PAA/O-ECNFs were investigated by numerous techniques. The effect of incorporating O-ECNFs on the swelling capability of the prepared hydrogel was explored in distillated water and MB solution at normal pH. The effect of parameters including the ratio of O-ECNFs, contact time, pH, initial concentration, and temperature on the adsorption process were explored. The adsorption isotherm and kinetic were studied by numerous non-linear models. The obtained results confirmed that the incorporation of O-ECNFs into the hydrogel network improved its ability towards MB dye removal with decreasing their swelling capacity. The adsorption process depends on the pH value of the dye solution. Additionally, the adsorption and kinetic results were fitted using the Freundlich isotherm model and pseudo second order model (PSO), respectively. Moreover, the new adsorbents can be recycled for at least five cycles keeping its adsorption capacity and can be easily recovered without loss in its initial weight.

Keywords: carbon nanofibers, hydrogels, nanocomposites, water treatment

Procedia PDF Downloads 150

Authors: Saleh O. Allehabi, V. A. Dzubaa, V. V. Flambaum, Jiguang Li, A. V. Afanasjev, S. E. Agbemava

Abstract:

Recently developed versions of the configuration method for open shells, configuration interaction with perturbation theory (CIPT), and configuration interaction with many-body perturbation theory (CI+MBPT) techniques are used to study the electronic structure of Er, Fm, and No atoms. Excitation energies of odd states connected to the even ground state by electric dipole transitions, the corresponding transition rates, isotope shift, hyperfine structure, ionization potentials, and static scalar polarizabilities are calculated. The way of extracting parameters of nuclear charge distribution beyond nuclear root mean square (RMS) radius, e.g., a parameter of quadrupole deformation β, is demonstrated. In nuclei with spin > 1/2, parameter β is extracted from the quadrupole hyperfine structure. With zero nuclear spin or spin 1/2, it is impossible since quadrupole zero, so a different method was developed. The measurements of at least two atomic transitions are needed to disentangle the contributions of the changes in deformation and nuclear RMS radius into field isotopic shift. This is important for testing nuclear theory and for searching for the hypothetical island of stability. Fm and No are heavy elements approaching the superheavy region, for which the experimental data are very poor, only seven lines for the Fm element and one line for the No element. Since Er and Fm have similar electronic structures, calculations for Er serve as a guide to the accuracy of the calculations. Twenty-eight new levels of Fm atom are reported.

Keywords: atomic spectra, electronic transitions, isotope effect, electron correlation calculations for atoms

Procedia PDF Downloads 157

Authors: F. V. Matta, C. M. Donnelly, M. B. Jaafar, N. I. Ward

Abstract:

‘Yerba Mate’ (Ilex paraguariensis) is a native plant from South America with the main producers being Argentina and Brazil. ‘Mate’ is widely consumed in Argentina, Brazil, Uruguay and Paraguay. The most popular format is as an infusion made from dried leaves of a traditional cup, roasted material in tea bags or iced tea infusions. There are many alleged health benefits resulted from mate consumption, even though there is a lack of conclusive research published in the international literature. The main objective of this study was to develop and evaluate the sample preparation and instrumental analysis stages involved in the determination of trace elements in yerba mate using inductively coupled plasma mass spectrometry (ICP-MS). Specific details on the methods of sample digestion, validation of the ICP-MS analysis especially for polyatomic ion correction and matrix effects associated with the complex medium of mate will be presented. More importantly, mate produced in Brazil and Argentina, is subject to different soil conditions, methods of cultivation and production, especially for loose leaves and tea bags. The highest concentrations for loose mate leaf were for (mg/kg, dry weight): aluminium (253.6 – 506.9 for Brazil (Bra), 230.0 – 541.8 for Argentina (Arg), respectively), manganese (378.3 – 762.6 Bra; 440.8 – 879.9 Arg), iron (32.5 – 85.7 Bra; 28.2 – 132.9 Arg), zinc (28.2 – 91.1 Bra; 39.1 – 92.3 Arg), nickel (2.2 – 4.3 Bra; 2.9 – 10.8 Arg) and copper (4.8 – 9.1 Bra; 4.3 – 9.2 Arg), with lower levels of chromium, cobalt, selenium, molybdenum, cadmium, lead and arsenic. Elemental levels of mate leaf consumed in tea bags were found to be higher, mainly due to only using leaf material (as opposed to leaf and twig for loose packed product). Further implications of the way of consuming yerba mate will be presented, including different infusion methods in Brazil and Argentina. This research provides for the first time an extensive evaluation of mate products from both countries and the possible implications of specific trace elements, especially Mn, Fe, Se, Cu and Zn and the various health claims of consuming yerba mate.

Keywords: beverage analysis, ICP-MS, trace elements, yerba mate

Procedia PDF Downloads 233

Authors: Wei Wang, Yaohua Zhao, Yanhua Diao

Abstract:

The exponential growth of the lighting industry has rendered traditional thermal technologies inadequate for addressing the thermal management challenges inherent to high-power light-emitting diode (LED) technology. To enhance the thermal management of LEDs, this study proposes a heat sink configuration that integrates a miniature heat pipe array based on phase change technology with rectangular channels. The thermal performance of the heat sink was evaluated through experimental testing, and the results demonstrated that when the input power was 100W, 150W, and 200W, the temperatures of the LED substrate were 47.64℃, 56.78℃, and 69.06℃, respectively. Additionally, the maximum temperature difference of the MHPA in the vertical direction was observed to be 0.32℃, 0.30℃, and 0.30℃, respectively. The results demonstrate that the heat sink not only effectively dissipates the heat generated by the LEDs, but also exhibits excellent temperature uniformity. In consideration of the experimental measurement outcomes, a corresponding numerical model was developed as part of this study. Following the model validation, the effect of the structural parameters of the heat sink on its heat dissipation efficacy was examined through the use of response surface methodology (RSM) analysis. The rectangular channel width, channel height, channel length, number of channel cross-sections, and channel cross-section spacing were selected as the input parameters, while the LED substrate temperature and the total mass of the heat sink were regarded as the response variables. Subsequently, the response was subjected to an analysis of variance (ANOVA), which yielded a regression model that predicted the response based on the input variables. This offers some direction for the design of the radiator.

Keywords: light-emitting diodes, heat transfer, heat pipe, natural convection, response surface methodology

Procedia PDF Downloads 38

Authors: Yuri Teterin, Lomali Generdukaev, Dmitry Blagovestnov, Peter Yartcev

Abstract:

Introduction: Under the definition "large biliary stones," we referred to stones over 1.5 cm, in which standard transpapillary litho extraction techniques were unsuccessful. Electrohydraulic and laser contact lithotripsy under SpyGlass control have been actively applied for the last decade in order to improve endoscopic treatment results. Aims and Methods: Between January 2019 and July 2022, the N.V. Sklifosovsky Research Institute of Emergency Care treated 706 patients diagnosed with choledocholithiasis who underwent biliary stones removed from the common bile duct. Of them, in 57 (8, 1%) patients, the use of a Dormia basket or Biliary stone extraction balloon was technically unsuccessful due to the size of the stones (more than 15 mm in diameter), which required their destruction. Mechanical lithotripsy was used in 35 patients, and electrohydraulic and laser lithotripsy under SpyGlass direct visualization system - in 26 patients. Results: The efficiency of mechanical lithotripsy was 72%. Complications in this group were observed in 2 patients. In both cases, on day one after lithotripsy, acute pancreatitis developed, which resolved on day three with conservative therapy (Clavin-Dindo type 2). The efficiency of contact lithotripsy was in 100% of patients. Complications were not observed in this group. Bilirubin level in this group normalized on the 3rd-4th day. Conclusion: Our study showed the efficacy and safety of electrohydraulic and laser lithotripsy under SpyGlass control in a well-defined group of patients with large bile duct stones.

Keywords: contact lithotripsy, choledocholithiasis, SpyGlass, cholangioscopy, laser, electrohydraulic system, ERCP

Procedia PDF Downloads 84

Authors: Surena V.

Abstract:

Background and Aim: Periodontal diseases are among the most common infectious diseases all around the world, even in developed countries. Considering the increased rate of microbial resistance to antibiotics and the chemical side effects of antibiotics and antiseptics used for the treatment of periodontal disease, there is a need for an alternative antimicrobial agent with fewer complications. Medicinal herbs have recently become popular as antimicrobial and preventive agents. This study aimed to assess the antibacterial effects of hydroalcoholic extracts of Lawsonia inermis, Malva sylvestris and Boswellia serrata on Aggregatibacter actinomycetemcomitans (A. actinomycetemcomitans). Materials and Methods: Hydroalcoholic extracts of the three medicinal plants were obtained by the maceration technique and A. actinomycetemcomitans was cultured. The antimicrobial efficacy of the three medicinal plants was compared with that of 0.2% chlorhexidine (CHX) according to the CLSI protocol using agar disc diffusion and broth microdilution techniques. All tests were repeated three times. Results: Hydroalcoholic extracts of all three plants had antimicrobial activity against A. actinomycetemcomitans. The minimum inhibitory concentration (MIC) of Lawsonia inermis, Malva sylvestris, and Boswellia serrata was 78.1, 156.2, and 1666 µg/mL with no significant difference between them. The MIC of CHX was 3.33 µg/mL, which was significantly higher than that of Boswellia serrata extract. Conclusion: Given that, further in vivo studies confirm other properties of these extracts and their safety in terms of cytotoxicity and mutagenicity, hydroalcoholic extracts of Lawsonia inermis and Malva sylvestris may be used in mouthwashes or local delivery systems to affect periodontal biofilm.

Keywords: actinobacilus actinomycetem commitans, lawsonia inermis, malva sylvestris, boswellia serrata

Procedia PDF Downloads 61