Search results for: acoustic source detection

Authors: Tayyaba Bibi, Jenny Ronan, Robert Hernan, Kathleen O’Rourke, Brendan McHugh, Evin McGovern, Michelle Giltrap, Gordon Chambers, James Wilson

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Sediment contamination is a major source of ecosystem stress and has received significant attention from the scientific community. Both the Water Framework Directive (WFD) and Marine Strategy Framework Directive (MSFD) require a robust set of tools for biological and chemical monitoring. For the MSFD in particular, causal links between contaminant and effects need to be assessed. Appropriate assessment tools are required in order to make an accurate evaluation. In this study, a range of recommended sediment bioassays and chemical measurements are assessed in a number of potentially impacted and lowly impacted locations around Ireland. Previously, assessment indices have been developed on individual compartments, i.e. contaminant levels or biomarker/bioassay responses. A number of assessment indices are applied to chemical and ecotoxicological data from the Seachange project (Project code) and compared including the metal pollution index (MPI), pollution load index (PLI) and Chapman index for chemistry as well as integrated biomarker response (IBR). The benefits and drawbacks of the use of indices and aggregation techniques are discussed. In addition to this, modelling of raw data is investigated to analyse links between contaminant and effects.

Keywords: bioassays, contamination indices, ecotoxicity, marine environment, sediments

Procedia PDF Downloads 211

Authors: Zheng Yi

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Among the attempts made worldwide to foster urban and transport sustainability, transit-oriented development certainly is one of the most successful. Residents' travel behavior is a concern in the researches about the impacts of transit-oriented development. The study takes 620 English journal papers in the core collection database of Web of Science as the study objects; the paper tries to map out the scientific knowledge mapping in the field and draw the basic conditions by co-citation analysis, co-word analysis, a total of citation network analysis and visualization techniques. This study teases out the research hotspots and evolution of the relationship between urban rail transit and resident's travel behavior from 1999 to 2019. According to the results of the analysis of the time-zone view and burst-detection, the paper discusses the trend of the next stage of international study. The results show that in the past 20 years, the research focuses on these keywords: land use, behavior, model, built environment, impact, travel behavior, walking, physical activity, smart card, big data, simulation, perception. According to different research contents, the key literature is further divided into these topics: the attributes of the built environment, land use, transportation network, transportation policies. The results of this paper can help to understand the related researches and achievements systematically. These results can also provide a reference for identifying the main challenges that relevant researches need to address in the future.

Keywords: urban rail transit, travel behavior, knowledge map, evolution of researches

Procedia PDF Downloads 99

Authors: R. Kumaravelu, S. Poornima, Sunil Kumar Kashyap

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The optimized and digitalized restoration of the information from the old and used manual jacquard punched card in textile industry is referred to as Jacquard Punch Card (JPC) reader. In this paper, we present a novel design and development of photo electronics based system for reading old and used punched cards and storing its binary information for transforming them into an effective image file format. In our textile industry the jacquard punched cards holes diameters having the sizes of 3mm, 5mm and 5.5mm pitch. Before the adaptation of computing systems in the field of textile industry those punched cards were prepared manually without digital design source, but those punched cards are having rich woven designs. Now, the idea is to retrieve binary information from the jacquard punched cards and store them in digital (Non-Graphics) format before processing it. After processing the digital format (Non-Graphics) it is converted into an effective image file format through either by Row major or Column major parsing technique.To accomplish these activities, an embedded system based device and software integration is developed. As part of the test and trial activity the device was tested and installed for industrial service at Weavers Service Centre, Kanchipuram, Tamilnadu in India.

Keywords: file system, SPI. UART, ARM controller, jacquard, punched card, photo LED, photo diode

Procedia PDF Downloads 149

Authors: Saad M. Howladar

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Although, there are a little data on the use of littoral plants as heavy metals bioaccumulators over large areas of the wetlands environment. So, soil samples and biomass of the five plant species: Pluchea dioscroides, Pulicaria crispa, Lavandula pubescens, Tarchononthus comporatus and Argemone ochroleuca were collected from two different sites (basin and mouth) of four dams at Baha province, KSA. Nutrients and heavy metals were extracted from plant samples (leaves and stems) for analyzing elements (Na, K, Ca, P and N) and heavy metals (Pb, Cu and Ni). The soils of the mouth of the dam had the highest concentrations of all elements, while that of basin had the highest ones of most heavy metals except Pb. The soil elements in relation to the two sites arranged as: Ca > K > P > Na > N; and the heavy metals as: Cu > Ni > Pb. The present study indicated that Pluchea dioscroides had the highest values of most elements and heavy metals, while Lavandula pubescens had the lowest. In general, leaves attain the highest concentrations of all nutrients and heavy metals in most studied species as compared with stem. It was indicated that Pluchea dioscroides showed a high transfer factor for almost elements and heavy metals such as K, Na, Cu, Ni and Pb, while Pulicaria crispa showed the highest translocation factor of N, P, Ca-Na ratio and Cu. All studied species growing in the basin had almost the highest concentrations of elements and heavy metals as compared with that in the mouth of dam except K in Pluchea dioscroides, Tarchononthus comporatus and Argemone ochroleuca tissues. Otherwise tissues of Tarchononthus comporatus growing in the basin had the lowest concentrations of K and Ni, while that growing in the mouth had the highest of P and N.

Keywords: Baha Region, bioindicators, plant, pollution, dams, heavy metals

Procedia PDF Downloads 443

Authors: Kanokkan Titipornpun, Somphorn Sriarpanon, Apinun Titipornpun, Jan Gimsa, Tripob Bhongsuwan, Noodchanath Kongchouy

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The Phanom and Ko Pha-ngan districts of Surat Thani province are known for their high atmospheric radon concentrations from different sources. While Phanom district is located in an active fault zone, the main radon source in Ko Pha-ngan district is the high amounts of equivalent uranium in the ground surface. Survey measurements of the indoor radon concentrations have been carried out in 105 dwellings and 93 workplaces, using CR-39 detectors that were exposed to indoor radon for forty days. Alpha tracks were made visible by chemical etching and counted manually under an optical microscope. The indoor radon concentrations in the two districts were found to vary between 9 and 63 Bq m-3 (Phanom) and 12 and 645 Bq m-3 (Ko Pha-ngan). The geometric mean radon concentration in Ko Pha-ngan district (51±2 Bq m-3) was significantly higher than in the Phanom district (26±1 Bq m-3) at a significance level of p<0.05 (t-test for independent samples). Nevertheless, only in two dwellings (1%), located in Ko Pha-ngan district, radon concentrations (177 and 645 Bq m-3) were found to exceed the limit recommended by the US EPA of 148 Bq m-3. The two houses are probably located near to radon sources which, in combination with low air convection, led to increased indoor levels of radon. Our study also shows that the geometric mean radon concentration was higher in workplaces than in dwellings (0.05 significance level) in both districts.

Keywords: indoor radon, CR-39 detector, active fault zone, equivalent uranium

Procedia PDF Downloads 286

Authors: Suvarna Kumar Gogula, Sandhya Devi Gogula, P. Chanakya

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Augmented reality is defined as the collection of the digital (or) computer generated information like images, audio, video, 3d models, etc. and overlay them over the real time environment. Augmented reality can be thought as a blend between completely synthetic and completely real. Augmented reality provides scope in a wide range of industries like manufacturing, retail, gaming, advertisement, tourism, etc. and brings out new dimensions in the modern digital world. As it overlays the content, it makes the users enhance the knowledge by providing the content blended with real world. In this application, we integrated augmented reality with data analytics and integrated with cloud so the virtual content will be generated on the basis of the data present in the database and we used marker based augmented reality where every marker will be stored in the database with corresponding unique ID. This application can be used in wide range of industries for different business processes, but in this paper, we mainly focus on the marketing industry which helps the customer in gaining the knowledge about the products in the market which mainly focus on their prices, customer feedback, quality, and other benefits. This application also focuses on providing better market strategy information for marketing managers who obtain the data about the stocks, sales, customer response about the product, etc. In this paper, we also included the reports from the feedback got from different people after the demonstration, and finally, we presented the future scope of Augmented Reality in different business processes by integrating with new technologies like cloud, big data, artificial intelligence, etc.

Keywords: augmented reality, data analytics, catch room, marketing and sales

Procedia PDF Downloads 219

Authors: Agoubi Belgacem, Adel Kharroubi

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Geothermal groundwater is the main water source to supply various sectors in El Hamma city, southeastern Tunisia. This region was long the destination of thousands of people from Tunisia and neighboring countries for care and bathing. The main objective of this study is to understand the groundwater mineralization origins and factors that control. The second goal is the appraisal of radon in geothermal groundwater in the study area. For this aim, geothermal groundwater was sampled and collected from different locations (thermal baths and deep wells). Physical parameters were measured and major ions were analyzed. Results reveal three water types. The water first type has Na-Mg-Ca-SO4-Cl facies and T>55°C. The second water type dominated by Na-Ca-Cl-SO4 facies with a temperature < 45 °C. However the third water type is dominated by Ca-SO4-Na-Cl-Mg. The three water types may be controlled by depth and geology. The first represent groundwater from deep aquifer (lower cretaceous), the second type was the shallow aquifer and the first is mixed water from deep and shallow water with a temperature ranging from 45 to 55°C. Measured Radon shows that shallow aquifer has a higher 222Rn concentration (677 to 2903 Bq.m-3) than deep water (203 to 1100 Bq.m-3). R-222 in El Hamma thermal aquifer was controlled by structures, porosity and permeability of aquifers. Geostatistical analyses of hydrogeological data and radon activities confirm the vertical flow and communication between deep and shallow aquifers through vertical faults system.

Keywords: Radon-222, geothermal, water, environment, Tunisia

Procedia PDF Downloads 349

Authors: Ryotaro Ishikawa

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Social Anxiety Disorder (SAD) is marked by the persistent fear of social or performance situations in which embarrassment may occur. In contrast, SA in Japan and in China is understood differently. Taijin Kyofusho (TKS) is a culture-bound subtype of SAD which has been the focus of recent research. TKS refers to a unique form of SAD found in Japanese and East Asian cultures characterized by a fear of offending others, in contrast to prototypical SAD in which the source of fear is typically concerned about one’s own embarrassment, humiliation, or rejection by others. Criteria for TKS partially overlap with but are distinct from SAD; a primary factor distinguishing TKS from SAD appears to be individualistic versus interdependent or collectivistic self-construals. The aim of this study was to develop a scale to assess the typical SAD and offensive type of SAD (TKS). This study aimed to test the internal consistency and validity of the scale (Dimensional Social Anxiety Scale: DSAS) using university students sample. For this, 148 university students were enrolled (male=90, female=58, age=19.77, Standard Deviation=1.04). As a result of confirmatory factor analysis, three-factor models of DSAS were verified (χ2(74) =128.36). These three factors were named ‘general’, ‘perfomance’, and ‘offensive’. DSAS were significantly correlated with the Liebowitz Social Anxiety Scale (r = .538, p < .001). Good internal consistencies were indicated on the three subscales (α = .76 to 89). In conclusion, this study indicated DSAS has adequate internal consistency and validity for assessing of multi-type of SADs.

Keywords: social anxiety, cognitive theory, assessment, anxiety disorder

Procedia PDF Downloads 103

Authors: Marianne Paimre

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Estonia is heralded as the most successful digital country in the world with the highly acclaimed eHealth system. Yet 40% of the 65–74-year-olds do not use the Internet at all, and digital divide between young and elderly people's use of ICT is larger than in many advanced countries. Poor access to ICT resource and insufficient digital skills can lead to detachment from digital health resources, delayed diagnoses, and increased rates of hospitalization. To reveal digital divide within the elderly population itself, the presentation focuses on the health information behavior of Estonian seniors who either continue or have stopped working after retirement to use digital health applications. The author's main interest is on access, trust, and skills to use the Internet for medical purposes. Fifteen in-depth interviews with 65+ working persons, as well as 15 interviews with full-time retirees, were conducted. Also, six think-aloud protocols were conducted. The results indicate that older adults, who due to the nature of their work, have regular access to computers, often search for health-related information online. They exposed high source criticism and were successful in solving the given tasks. Conversely, most of the fully retired older adults claimed not using computers or other digital devices and cited lack of skills as the main reason for their inactivity. Thus, when developing health applications, it should be borne in mind that the ability and willingness of older adults to use e-solutions are very different.

Keywords: digital divide, digital healthcare, health information behavior, older adults

Procedia PDF Downloads 141

Authors: Jing Zhao, Dayong Liu, Shihao Wang, Xinghua Zhu, Delong Li

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Uhumanned Underwater Vehicles generally operate in the deep sea, which has its own unique working conditions. Lithium-ion power batteries should have the necessary stability and endurance for use as an underwater vehicle’s power source. Therefore, it is essential to accurately forecast how long lithium-ion batteries will last in order to maintain the system’s reliability and safety. In order to model and forecast lithium battery Remaining Useful Life (RUL), this research suggests a model based on Complete Ensemble Empirical Mode Decomposition with Adaptive noise-Temporal Convolutional Net (CEEMDAN-TCN). In this study, two datasets, NASA and CALCE, which have a specific gap in capacity data fluctuation, are used to verify the model and examine the experimental results in order to demonstrate the generalizability of the concept. The experiments demonstrate the network structure’s strong universality and ability to achieve good fitting outcomes on the test set for various battery dataset types. The evaluation metrics reveal that the CEEMDAN-TCN prediction performance of TCN is 25% to 35% better than that of a single neural network, proving that feature expansion and modal decomposition can both enhance the model’s generalizability and be extremely useful in industrial settings.

Keywords: lithium-ion battery, remaining useful life, complete EEMD with adaptive noise, temporal convolutional net

Procedia PDF Downloads 127

Authors: Nemanja Kajtez, Yue Zhan, Basel Halak

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The significant rise in the cost of manufacturing of nanoscale integrated circuits (IC) has led the majority of IC design companies to outsource the fabrication of their products to other companies, often located in different countries. This multinational nature of the hardware supply chain has led to a host of security threats, including IP piracy, IC overproduction, and Trojan insertion. To combat that, researchers have proposed logic locking techniques to protect the intellectual properties of the design and increase the difficulty of malicious modification of its functionality. However, the adoption of logic locking approaches is rather slow due to the lack of the integration with IC production process and the lack of efficacy of existing algorithms. This work automates the logic locking process by developing software using Python that performs the locking on a gate-level netlist and can be integrated with the existing digital synthesis tools. Analysis of the latest logic locking algorithms has demonstrated that the SFLL-HD algorithm is one of the most secure and versatile in trading-off levels of protection against different types of attacks and was thus selected for implementation. The presented tool can also be expanded to incorporate the latest locking mechanisms to keep up with the fast-paced development in this field. The paper also presents a case study to demonstrate the functionality of the tool and how it could be used to explore the design space and compare different locking solutions. The source code of this tool is available freely from (https://www.researchgate.net/publication/353195333_Source_Code_for_The_Lockit_Tool).

Keywords: design automation, hardware security, IP piracy, logic locking

Procedia PDF Downloads 164

Authors: Klaudia Gołębiowska

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This article analyzes the actions of Poland's ruling party facing two refugee crises. These crises emerged almost one after the other within a few months. The first concerned irregular migrants from various countries, including the Middle East, seeking to cross the Polish border from the territory of Belarus. The second was caused by Russia's full-scale invasion of Ukraine. I aim to show the evolution of the discourse and law towards immigrants and refugees by the party Prawo i Sprawiedliwość (PiS, ang. Law and Justice), which has been in power in Poland since 2015. The authorities, in power since 2015, have radically changed its anti-immigrant discourse towards the exodus of civilians from Ukraine. Research questions are the following: What were the roots of the refugee crises in Poland in 2021 and 2022? What legal or illegal measures were taken in Poland to deal with the refugee crises? The methods of qualitative source analysis and process tracing. From the first days of the war in Ukraine, not only was aid organised for Ukrainians, but they were also given access to public services and education. All refugees were granted temporary international protection. At the same time, the basic physiological needs of those on the Polish-Belarusian border were ignored. Moreover, illegal pushbacks were used against those coming mainly from the Middle East, pushing them into the territory of Belarus, where they were often subjected to torture and inhumane treatment. The Polish government justified such treatment on the grounds that these people were part of a 'hybrid war' waged by Russia and Belarus using migrants. Only Ukrainians were treated as 'real' refugees in the analyzed crises at the Polish borders.

Keywords: refugee, irregular migrants, hybrid war, migrants

Procedia PDF Downloads 50

Authors: Maxime Merheb, Rachel Matar

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Retrieving ancient DNA sequences which in return permit the entire genome sequencing from fossils have extraordinarily improved in recent years, thanks to sequencing technology and other methodological advances. In any case, the quest to search for ancient DNA is still obstructed by the damage inflicted on DNA which accumulates after the death of a living organism. We can characterize this damage into three main categories: (i) Physical abnormalities such as strand breaks which lead to the presence of short DNA fragments. (ii) Modified bases (mainly cytosine deamination) which cause errors in the sequence due to an incorporation of a false nucleotide during DNA amplification. (iii) DNA modifications referred to as blocking lesions, will halt the PCR extension which in return will also affect the amplification and sequencing process. We can clearly see that the issues arising from breakage and coding errors were significantly decreased in recent years. Fast sequencing of short DNA fragments was empowered by platforms for high-throughput sequencing, most of the coding errors were uncovered to be the consequences of cytosine deamination which can be easily removed from the DNA using enzymatic treatment. The methodology to repair DNA sequences is still in development, it can be basically explained by the process of reintroducing cytosine rather than uracil. This technique is thus restricted to amplified DNA molecules. To eliminate any type of damage (particularly those that block PCR) is a process still pending the complete repair methodologies; DNA detection right after extraction is highly needed. Before using any resources into extensive, unreasonable and uncertain repair techniques, it is vital to distinguish between two possible hypotheses; (i) DNA is none existent to be amplified to begin with therefore completely un-repairable, (ii) the DNA is refractory to PCR and it is worth to be repaired and amplified. Hence, it is extremely important to develop a non-enzymatic technique to detect the most degraded DNA.

Keywords: ancient DNA, DNA barcodong, enzymatic repair, PCR

Procedia PDF Downloads 391

Authors: Olumuyiwa Ojo, Masengo Ilunga

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Artificial neural network (ANN) has broken the bounds of the convention programming, which is actually a function of garbage in garbage out by its ability to mimic the human brain. Its ability to adopt, adapt, adjust, evaluate, learn and recognize the relationship, behavior, and pattern of a series of data set administered to it, is tailored after the human reasoning and learning mechanism. Thus, the study aimed at modeling wastewater treatment process in order to accurately diagnose water control problems for effective treatment. For this study, a stage ANN model development and evaluation methodology were employed. The source data analysis stage involved a statistical analysis of the data used in modeling in the model development stage, candidate ANN architecture development and then evaluated using a historical data set. The model was developed using historical data obtained from Daspoort Wastewater Treatment plant South Africa. The resultant designed dimensions and model for wastewater treatment plant provided good results. Parameters considered were temperature, pH value, colour, turbidity, amount of solids and acidity. Others are total hardness, Ca hardness, Mg hardness, and chloride. This enables the ANN to handle and represent more complex problems that conventional programming is incapable of performing.

Keywords: ANN, artificial neural network, wastewater treatment, model, development

Procedia PDF Downloads 135

Authors: Bliss Singhal

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Machine learning (ML) is a branch of Artificial Intelligence (AI) where computers analyze data and find patterns in the data. The study focuses on the detection of metastatic cancer using ML. Metastatic cancer is the stage where cancer has spread to other parts of the body and is the cause of approximately 90% of cancer-related deaths. Normally, pathologists spend hours each day to manually classifying whether tumors are benign or malignant. This tedious task contributes to mislabeling metastasis being over 60% of the time and emphasizes the importance of being aware of human error and other inefficiencies. ML is a good candidate to improve the correct identification of metastatic cancer, saving thousands of lives and can also improve the speed and efficiency of the process, thereby taking fewer resources and time. So far, the deep learning methodology of AI has been used in research to detect cancer. This study is a novel approach to determining the potential of using preprocessing algorithms combined with classification algorithms in detecting metastatic cancer. The study used two preprocessing algorithms: principal component analysis (PCA) and the genetic algorithm, to reduce the dimensionality of the dataset and then used three classification algorithms: logistic regression, decision tree classifier, and k-nearest neighbors to detect metastatic cancer in the pathology scans. The highest accuracy of 71.14% was produced by the ML pipeline comprising of PCA, the genetic algorithm, and the k-nearest neighbor algorithm, suggesting that preprocessing and classification algorithms have great potential for detecting metastatic cancer.

Keywords: breast cancer, principal component analysis, genetic algorithm, k-nearest neighbors, decision tree classifier, logistic regression

Procedia PDF Downloads 66

Authors: Farnaz Yusuf, Naseem A. Gaur

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The increase in environmental concerns, rapid depletion of fossil fuel reserves and intense interest in achieving energy security has led to a global research effort towards developing renewable sources of fuels. Second generation biofuels have attracted more attention recently as the use of lignocellulosic biomass can reduce fossil fuel dependence and is environment-friendly. Xylose is the main pentose and second most abundant sugar after glucose in lignocelluloses. Saccharomyces cerevisiae does not readily uptake and use pentose sugars. For an economically feasible biofuel production, both hexose and pentose sugars must be fermented to ethanol. Therefore, it is important to develop S. cerevisiae host platforms with more efficient xylose utilization. This work aims to construct a xylose fermenting yeast strains with engineered oxido-reductative pathway for xylose metabolism. Engineered strain was further improved by adaptive evolutionary engineering approach. The engineered strain is able to grow on xylose as sole carbon source with the maximum ethanol yield of 0.39g/g xylose and productivity of 0.139g/l/h at 96 hours. The further improvement in strain development involves over expression of pentose phosphate pathway and protein engineering of xylose reductase/xylitol dehydrogenase to change their cofactor specificity in order to reduce xylitol accumulation.

Keywords: biofuel, lignocellulosic biomass, saccharomyces cerevisiae, xylose

Procedia PDF Downloads 196

Authors: Gabriela V. Angeles Perez, Jose Castillejos Lopez, Araceli L. Reyes Cabello, Emilio Bravo Grajales, Adriana Perez Espinosa, Jose L. Quiroz Fabian

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Road traffic accidents are among the principal causes of traffic congestion, causing human losses, damages to health and the environment, economic losses and material damages. Studies about traditional road traffic accidents in urban zones represents very high inversion of time and money, additionally, the result are not current. However, nowadays in many countries, the crowdsourced GPS based traffic and navigation apps have emerged as an important source of information to low cost to studies of road traffic accidents and urban congestion caused by them. In this article we identified the zones, roads and specific time in the CDMX in which the largest number of road traffic accidents are concentrated during 2016. We built a database compiling information obtained from the social network known as Waze. The methodology employed was Discovery of knowledge in the database (KDD) for the discovery of patterns in the accidents reports. Furthermore, using data mining techniques with the help of Weka. The selected algorithms was the Maximization of Expectations (EM) to obtain the number ideal of clusters for the data and k-means as a grouping method. Finally, the results were visualized with the Geographic Information System QGIS.

Keywords: data mining, k-means, road traffic accidents, Waze, Weka

Procedia PDF Downloads 394

Authors: Alisher Ibragimov, Sofya Senotrusova, Aleksandra Beliaeva, Egor Ushakov, Yuri Markin

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Mammography plays a critical role in screening for breast cancer in women, and artificial intelligence has enabled the automatic detection of diseases in medical images. Many of the current techniques used for mammogram analysis focus on a single view (mediolateral or craniocaudal view), while in clinical practice, radiologists consider multiple views of mammograms from both breasts to make a correct decision. Consequently, computer-aided diagnosis (CAD) systems could benefit from incorporating information gathered from multiple views. In this study, the introduce a method based on a Siamese neural network (SNN) model that simultaneously analyzes mammographic images from tri-view: bilateral and ipsilateral. In this way, when a decision is made on a single image of one breast, attention is also paid to two other images – a view of the same breast in a different projection and an image of the other breast as well. Consequently, the algorithm closely mimics the radiologist's practice of paying attention to the entire examination of a patient rather than to a single image. Additionally, to the best of our knowledge, this research represents the first experiments conducted using the recently released Vietnamese dataset of digital mammography (VinDr-Mammo). On an independent test set of images from this dataset, the best model achieved an AUC of 0.87 per image. Therefore, this suggests that there is a valuable automated second opinion in the interpretation of mammograms and breast cancer diagnosis, which in the future may help to alleviate the burden on radiologists and serve as an additional layer of verification.

Keywords: breast cancer, computer-aided diagnosis, deep learning, multi-view mammogram, siamese neural network

Procedia PDF Downloads 119

Authors: Feleke Terefe Fanta

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Background: The existence of heavy metals and coliform bacteria contaminants in aquatic system of Akaki river basin, a sub city of Addis Ababa, Ethiopia has become a public concern as human population increases and land development continues. Hence, it is the right time to design treatment technologies that can handle multiple pollutants. Results: In this study, we prepared a synthetic zeolites and copper doped zeolite composite adsorbents as cost effective and simple approach to simultaneously remove heavy metals and total coliforms from wastewater of Akaki river. The synthesized copper–zeolite X composite was obtained by ion exchange method of copper ions into zeolites frameworks. Iodine test, XRD, FTIR and autosorb IQ automated gas sorption analyzer were used to characterize the adsorbents. The mean concentrations of Cd, Cr, and Pb in untreated sample were 0.795, 0.654 and 0.7025 mg/L respectively. These concentrations decreased to Cd (0.005 mg/L), Cr (0.052 mg/L) and Pb (bellow detection limit, BDL) for sample treated with bare zeolite X while a further decrease in concentration of Cd (0.005 mg/L), Cr (BDL) and Pb (BDL) was observed for the sample treated with copper–zeolite composite. Zeolite X and copper-modified zeolite X showed complete elimination of total coliforms after 90 and 50 min contact time respectively. Conclusion: The results obtained in this study showed high antimicrobial disinfection and heavy metal removal efficiencies of the synthesized adsorbents. Furthermore, these sorbents are efficient in significantly reducing physical parameters such as electrical conductivity, turbidity, BOD and COD.

Keywords: WASTE WATER, COPPER DOPED ZEOITE X, ADSORPITION, HEAVY METAL, DISINFECTION, AKAKI RIVER

Procedia PDF Downloads 44

Authors: Birendra Kumar Bhattachan

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Organic soil media plays an important role for seed germination, growing, and producing organic jack fruits as the source of food such as vitamin A, C, and others for human health. An experiment was conducted to find out the appropriate organic soil medias to induce germination and seedling vigor of jack fruit seeds at the farm of Agriculture and Forestry University (AFU) Chitwan Nepal during June 2022 to October 2022. The organic soil medias used as treatments were as 1. soil collected under the Molingia tree; 2. soil, FYM and RH (2:1;1); 3. soil, FYM (1:1); 4. sand, FYM and RH (2:1:1), 5, sand, soil, FYM and RH (1:1:1:1) and 6. sand, soil and RH (1:2:1) under Completely Randomized Design (CRD) with four replications. Significantly highest germination of 88% was induced by soil media, followed by media of soil and FYM (!:1) i.e. 63% and the media of soil, FYM and RH (2:1;1) and the least media was sand, soil, FYM and RH (1:1:1:) to induce germination of 28%. Significantly highest seedling length of 73 cm was produced by soil media followed by the media soil, sand, and RH (1:2:1), i.e. 72 cm and the media soil, sand, FYM, and RH (1:1:1:1) and the least media was soil, FYM and RH (2:1:1) to produce 62 cm seedling length, Similarly, significantly highest seedling vigor of 6257 was produced by soil media followed by the media soil and FYM (1:1) i.e. 4253 and the least was the media sand, soil, FYM and RH (1:1:1:1) to produce seedling vigor of1916. Based on this experiment, it was concluded that soil media collected under the Moringia tree could induce the highest germinating capacity of jack fruit seeds and then seedling vigor.

Keywords: jack fruit seed, soil media, farm yard manure, sand media, rice husk

Procedia PDF Downloads 178

Authors: Rupinder Kaur, Parmjit S. Panesar, Ram S. Singh

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Whey is the lactose rich by-product of the dairy industry, having good amount of nutrient reservoir. Most abundant nutrients are lactose, soluble proteins, lipids and mineral salts. Disposing of whey by most of milk plants which do not have proper pre-treatment system is the major issue. As a result of which, there can be significant loss of potential food and energy source. Thus, whey has been explored as the substrate for the synthesis of different value added products such as enzymes. β-galactosidase is one of the important enzymes and has become the major focus of research due to its ability to catalyze both hydrolytic as well as transgalactosylation reaction simultaneously. The enzyme is widely used in dairy industry as it catalyzes the transformation of lactose to glucose and galactose, making it suitable for the lactose intolerant people. The enzyme is intracellular in both bacteria and yeast, whereas for molds, it has an extracellular location. The present work was carried to utilize the whey for the production of β-galactosidase enzyme using both yeast and fungal cultures. The yeast isolate Kluyveromyces marxianus WIG2 and various fungal strains have been used in the present study. Different disruption techniques have also been investigated for the extraction of the enzyme produced intracellularly from yeast cells. Among the different methods tested for the disruption of yeast cells, SDS-chloroform showed the maximum β-galactosidase activity. In case of the tested fungal cultures, Aureobasidium pullulans NCIM 1050, was observed to be the maximum extracellular enzyme producer.

Keywords: β-galactosidase, fungus, yeast, whey

Procedia PDF Downloads 311

Authors: Aleksandrs Kovalcuks

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Egg yolk oil is a natural source of bioactive compounds such as unsaturated fatty acids, oil soluble vitamins, pigments and others. Bioactive compound content in egg yolk oil depends from its content in eggs, from which oil was extracted. Many studies show that bioactive compound content in egg is correlated to the content of these compounds in hen feed, but there is also an opinion that hen housing systems also have influence on egg chemical content. The aim of this study was to determine which factor, laying hen housing system or hen diet, has a primary influence on bioactive compound content in egg yolk oil. The egg yolk oil was extracted from eggs obtained from 4 different hen housing systems: cage, barn and two groups of free range. All hens were fed with commercially produced compound feed except one group of free range hens which get free diet – pastured hens. Extracted egg yolk oils were analyzed for fatty acids, oil soluble vitamins and β-carotene content. α-tocopherol, ergocalcipherol and polyunsaturated fatty acid content in egg yolk oil was higher from eggs obtained from all housing systems where hens were fed with commercial compound feed. β-carotene and retinol content in egg yolk oils from free range free diet eggs was significantly (p>0.05) higher that from other eggs because hens have access to green forage. Hen physical activity in free range housing systems decreases content of some bioactive compound in egg yolk oil.

Keywords: egg yolk oil, vitamins, caged eggs, free range

Procedia PDF Downloads 450

Authors: Rong Wang, Sandra Hasanefendic, Elizabeth von Hauff, Bart Bossink

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Technological learning and learning curve models have been continuously used to estimate the photovoltaics (PV) cost development over time for the climate mitigation targets. They can integrate a number of technological learning sources which influence the learning process. Yet the accuracy and realistic predictions for cost estimations of PV development are still difficult to achieve. This paper develops four hypothetical-alternative learning curve models by proposing different combinations of technological learning sources, including both local and global technology experience and the knowledge stock. This paper specifically focuses on the non-linear relationship between the costs and technological learning source and their dynamic interaction and uses the system dynamics approach to predict a more accurate PV cost estimation for future development. As the case study, the data from China is gathered and drawn to illustrate that the learning curve model that incorporates both the global and local experience is more accurate and realistic than the other three models for PV cost estimation. Further, absorbing and integrating the global experience into the local industry has a positive impact on PV cost reduction. Although the learning curve model incorporating knowledge stock is not realistic for current PV cost deployment in China, it still plays an effective positive role in future PV cost reduction.

Keywords: photovoltaic, system dynamics, technological learning, learning curve

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Authors: Faith Fang Xi Ooi, Kam-Fong Lee

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Headlines are generally the summary of the content of news articles. With the added influence of hectic lifestyles, readers may rely solely on the headlines for information. In the media, what is reported concerning health issues are government responses and community involvement. There is a need for a call to action to curb health issues and not just reporting on what the government is doing about these health-related issues. In other words, linguistic elements of persuasive communicative function should be realized when reporting on health issues. Hence, this paper aims at identifying and analyzing the transitivity, Mood and Modality systems in two hundred news headlines from two Malaysian online news portals, namely The Star Online and New Straits Times. This study employs the purposive sampling method to obtain the news headlines on healthy eating using the search keyword ‘healthy eating’ and is based on Halliday’s Systemic Functional Linguistics (SFL) framework. The results show that the Material process dominates the process types along with its participants of Scope and Goal. The mood type that constitutes most of the headlines in the two newspapers is the declarative mood. Moreover, for Modality, the median Probability constitutes the highest in the headlines on healthy eating. This study contributes to the implications of being a source of reference for news writers and producers in constructing news headlines and for health campaign strategists to realize the persuasive appeals to influence behaviors and attitudes of the public towards healthy eating.

Keywords: healthy eating, modality, mood, news headlines, SFL

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Authors: Jixiang Lei, Alexander Fuchs, Franz Pernkopf, Katrin Ellermann

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Within the Space@Sea project, funded by the Horizon 2020 program, an island consisting of multiple platforms was designed. The platforms are connected by ropes and fenders. The connection is critical with respect to the safety of the whole system. Therefore, fault detection systems are investigated, which could detect early warning signs for a possible failure in the connection elements. Previously, a model-based method called Extended Kalman Filter was developed to detect the reduction of rope stiffness. This method detected several types of faults reliably, but some types of faults were much more difficult to detect. Furthermore, the model-based method is sensitive to environmental noise. When the wave height is low, a long time is needed to detect a fault and the accuracy is not always satisfactory. In this sense, it is necessary to develop a more accurate and robust technique that can detect all rope faults under a wide range of operational conditions. Inspired by this work on the Space at Sea design, we introduce a fault diagnosis method based on deep neural networks. Our method cannot only detect rope degradation by using the acceleration data from each platform but also estimate the contributions of the specific acceleration sensors using methods from explainable AI. In order to adapt to different operational conditions, the domain adaptation technique DANN is applied. The proposed model can accurately estimate rope degradation under a wide range of environmental conditions and help users understand the relationship between the output and the contributions of each acceleration sensor.

Keywords: fault diagnosis, deep learning, domain adaptation, explainable AI

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Authors: Anh Duong

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The three-phase reading lesson has been put forth around the world as the new and innovative framework which is corresponding to the learner-centered trend in English language teaching and learning. Among three stages, pre-reading attracts many teachers’ and researchers’ attention for its vital role in preparing students with knowledge and interest in reading class. The researcher’s desire to exemplify effectiveness of activities prior to text reading has provoked the current study. Three main aspects were investigated in this paper, i.e. teachers’ and student’s perception of pre-reading stage, teachers’ exploitation of pre-reading techniques and teachers’ recommendation of effective pre-reading activities. Aiming at pre-reading techniques for first-year students at English Department, this study involved 200 fresh-men and 10 teachers from Division 1 to participate in the questionnaire survey. Interviews with the teachers and classroom observation were employed as a tool to take an insight into the responses gained from the early instrument. After a detailed procedure of analyzing data, the researcher discovered that thanks to the participants’ acclamation of pre-reading stage, this phase was frequently conducted by the surveyed teachers. Despite the fact that pre-reading activities apparently put a hand in motivating students to read and creating a joyful learning atmosphere, they did not fulfill another function as supporting students’ reading comprehension. Therefore, a range of techniques and notices when preparing and conducting pre-reading phase was detected from the interviewed teachers. The findings assisted the researcher to propose some related pedagogical implications concerning teachers’ source of pre-reading techniques, variations of suggested activities and first-year reading syllabus.

Keywords: pre-reading stage, pre-reading techniques, teaching reading, language teaching

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Authors: Qiaosi Li, Frankie Kwan Kit Wong, Tung Fung

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Lightweight unmanned aerial vehicle (UAV) loading with novel sensors offers a low cost approach for data acquisition in complex environment. This study established a framework for applying UAV system in complex environment quick mapping and assessed the performance of UAV-based hyperspectral image and digital surface model (DSM) derived from photogrammetric point clouds for 13 species classification in wetland area Mai Po Inner Deep Bay Ramsar Site, Hong Kong. The study area was part of shallow bay with flat terrain and the major species including reedbed and four mangroves: Kandelia obovata, Aegiceras corniculatum, Acrostichum auerum and Acanthus ilicifolius. Other species involved in various graminaceous plants, tarbor, shrub and invasive species Mikania micrantha. In particular, invasive species climbed up to the mangrove canopy caused damage and morphology change which might increase species distinguishing difficulty. Hyperspectral images were acquired by Headwall Nano sensor with spectral range from 400nm to 1000nm and 0.06m spatial resolution image. A sequence of multi-view RGB images was captured with 0.02m spatial resolution and 75% overlap. Hyperspectral image was corrected for radiative and geometric distortion while high resolution RGB images were matched to generate maximum dense point clouds. Furtherly, a 5 cm grid digital surface model (DSM) was derived from dense point clouds. Multiple feature reduction methods were compared to identify the efficient method and to explore the significant spectral bands in distinguishing different species. Examined methods including stepwise discriminant analysis (DA), support vector machine (SVM) and minimum noise fraction (MNF) transformation. Subsequently, spectral subsets composed of the first 20 most importance bands extracted by SVM, DA and MNF, and multi-source subsets adding extra DSM to 20 spectrum bands were served as input in maximum likelihood classifier (MLC) and SVM classifier to compare the classification result. Classification results showed that feature reduction methods from best to worst are MNF transformation, DA and SVM. MNF transformation accuracy was even higher than all bands input result. Selected bands frequently laid along the green peak, red edge and near infrared. Additionally, DA found that chlorophyll absorption red band and yellow band were also important for species classification. In terms of 3D data, DSM enhanced the discriminant capacity among low plants, arbor and mangrove. Meanwhile, DSM largely reduced misclassification due to the shadow effect and morphological variation of inter-species. In respect to classifier, nonparametric SVM outperformed than MLC for high dimension and multi-source data in this study. SVM classifier tended to produce higher overall accuracy and reduce scattered patches although it costs more time than MLC. The best result was obtained by combining MNF components and DSM in SVM classifier. This study offered a precision species distribution survey solution for inaccessible wetland area with low cost of time and labour. In addition, findings relevant to the positive effect of DSM as well as spectral feature identification indicated that the utility of UAV-borne hyperspectral and photogrammetry deriving 3D data is promising in further research on wetland species such as bio-parameters modelling and biological invasion monitoring.

Keywords: digital surface model (DSM), feature reduction, hyperspectral, photogrammetric point cloud, species mapping, unmanned aerial vehicle (UAV)

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Authors: Clement Leroy, Guillaume Boitel

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This paper presents a comparative benchmarking review of a steady and transient three-dimensional (3D) flow computations in centrifugal pump using commercial (AnsysCFX) and open source (OpenFOAM) computational fluid dynamics (CFD) software. In centrifugal rotor-dynamic pump, the fluid enters in the impeller along to the rotating axis to be accelerated in order to increase the pressure, flowing radially outward into another stage, vaned diffuser or volute casing, from where it finally exits into a downstream pipe. Simulations are carried out at the best efficiency point (BEP) and part load, for single-phase flow with several turbulence models. The results are compared with overall performance report from experimental data. The use of CFD technology in industry is still limited by the high computational costs, and even more by the high cost of commercial CFD software and high-performance computing (HPC) licenses. The main objectives of the present study are to define OpenFOAM methodology for high-quality 3D steady and transient turbomachinery CFD simulation to conduct a thorough time-accurate performance analysis. On the other hand a detailed comparisons between computational methods, features on latest Ansys release 18 and OpenFOAM is investigated to assess the accuracy and industrial applications of those solvers. Finally an automated connected workflow (IoT) for turbine blade applications is presented.

Keywords: benchmarking, CFX, internet of things, openFOAM, time-accurate, turbomachinery

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Authors: S. Cobos-Guzman

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This paper presents the results of a mechatronic design based on a 4-wheel omnidirectional mobile robot that can be used in indoor logistic applications. The low-level control has been selected using two open-source hardware (Raspberry Pi 3 Model B+ and Arduino Mega 2560) that control four industrial motors, four ultrasound sensors, four optical encoders, a vision system of two cameras, and a Hokuyo URG-04LX-UG01 laser scanner. Moreover, the system is powered with a lithium battery that can supply 24 V DC and a maximum current-hour of 20Ah.The Robot Operating System (ROS) has been implemented in the Raspberry Pi and the performance is evaluated with the selection of the sensors and hardware selected. The mechatronic system is evaluated and proposed safe modes of power distribution for controlling all the electronic devices based on different tests. Therefore, based on different performance results, some recommendations are indicated for using the Raspberry Pi and Arduino in terms of power, communication, and distribution of control for different devices. According to these recommendations, the selection of sensors is distributed in both real-time controllers (Arduino and Raspberry Pi). On the other hand, the drivers of the cameras have been implemented in Linux and a python program has been implemented to access the cameras. These cameras will be used for implementing a deep learning algorithm to recognize people and objects. In this way, the level of intelligence can be increased in combination with the maps that can be obtained from the laser scanner.

Keywords: autonomous, indoor robot, mechatronic, omnidirectional robot

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Authors: J. Bravo, F. Cabrera Suárez, B. Vega, L. Román, M. Martel, F. Acosta

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Ciguatera fish poisoning (CFP) is the most common non-bacterial intoxication in the world caused by ingestion of fish with bio-accumulated ciguatoxins (CTXs). It is typical in tropical and subtropical areas, mainly affecting the Caribbean Sea, Polynesia and other areas in the Pacific and Indian Oceans. Interest in Europe by the CFP is increasing in recent years as more and more cases in European hospitals are appearing, usually by people who have consumed ciguatoxin imported fish or have travelled to areas of risk for this poisoning. Since 2004 a series of poisonings raised the question of a possible occurrence of ciguatoxin in Europe, especially in the area of Macaronesia in the East Atlantic temperate zone. Furthermore, some studies have identified the presence of Gambierdiscus spp. in waters surrounding the Canary Islands and Madeira, a toxic dinoflagellate related to this poisoning. The toxin accumulates and concentrates through the food chain and affects to the end of the chain, the human consumer. Fish were collected from the Canary Islands waters and the toxin has been extracted and purified by using acetone and liquid/liquid partition in order to eliminate the excess of fatty acids that may interfere with the detection of the toxin. The fish extracts were inoculated in Neuroblastoma (neuro-2a) cells. After 24-h cell viability was used as an endpoint for cytotoxic effects measurement. Since 2011 our laboratory is collecting data for species such Seriola spp., Epinephelus spp., Makaira spp., Pomatomus spp., Xiphias spp., and Acantocybium spp., from all islands and including the sports fishing and professional activities, we obtained a 8% of fish that have ciguatoxin in their muscle. With these results, we conclude that the island where fishing and fish size affects the probability of catching a fish with the ciguatoxin.

Keywords: Canary Islands, ciguatera fish poisoning, ciguatoxin, Europe

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