Search results for: grape seed extract

Authors: Wided Bakari, Patrce Bellot, Mahmoud Neji

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With the development of electronic media and the heterogeneity of Arabic data on the Web, the idea of building a clean corpus for certain applications of natural language processing, including machine translation, information retrieval, question answer, become more and more pressing. In this manuscript, we seek to create and develop our own corpus of pair’s questions-texts. This constitution then will provide a better base for our experimentation step. Thus, we try to model this constitution by a method for Arabic insofar as it recovers texts from the web that could prove to be answers to our factual questions. To do this, we had to develop a java script that can extract from a given query a list of html pages. Then clean these pages to the extent of having a database of texts and a corpus of pair’s question-texts. In addition, we give preliminary results of our proposal method. Some investigations for the construction of Arabic corpus are also presented in this document.

Keywords: Arabic, web, corpus, search engine, URL, question, corpus building, script, Google, html, txt

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Authors: Adferotimi Banso

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A laboratory investigation was conducted to determine the effect of Justica flava and Aframonium melegueta on the growth of Aspergillus niger, Rhizopus stolonifer and Fusarium species in sweet orange and mango juices. Aqueous extract (3%v/v) of Justica flava and Aframonium melegueta reduced the growth of the fungi, a combination of 2% (v/v) each of Justica flava and Aframonium melegueta extracts reduced the growth better. Partial purification of aqueous extracts of Justica flava and Aframonium melegueta showed that ethyl acetate fraction of the extracts exhibited the highest level of inhibition of growth of the test fungi compared with diethyl ether and n-hexane fractions. The results suggest that extracts of Justica flava and Aframonium melegueta may be important substitutes for conventional chemical preservatives in the processing of fruit juices.

Keywords: aqueous, fraction, mango, orange, purification, sweet

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Authors: Avatharam Ganivada, Krishna Shah

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The Mask R-CNN is recently introduced by the team of Facebook AI Research (FAIR), which is mainly concerned with instance segmentation in images. Here, the Mask R-CNN is based on ResNet and feature pyramid network (FPN), where a single dropout method is employed. This paper provides a modified Mask R-CNN by adding multiple dropout methods into the Mask R-CNN. The proposed model has also utilized the concepts of Resnet and FPN to extract stage-wise network feature maps, wherein a top-down network path having lateral connections is used to obtain semantically strong features. The proposed model produces three outputs for each object in the image: class label, bounding box coordinates, and object mask. The performance of the proposed network is evaluated in the segmentation of every instance in images using COCO and cityscape datasets. The proposed model achieves better performance than the state-of-the-networks for the datasets.

Keywords: instance segmentation, object detection, convolutional neural networks, deep learning, computer vision

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Authors: Eman Alzahrani, Hala M. Abo-Dief, Ashraf T. Mohamed

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The present work is aimed at examining carbon steel oil pipelines corrosion using three natural extracts (Eruca Sativa, Rosell and Mango peels) that are used as inhibitors of different concentrations ranging from 0.05-0.1wt. %. Two sulphur compounds are used as corrosion mediums. Weight loss method was used for measuring the corrosion rate of the carbon steel specimens immersed in technical white oil at 100ºC at various time intervals in absence and presence of the two sulphur compounds. The corroded specimens are examined using the chemical wear test, scratch test and hardness test. The scratch test is carried out using scratch loads from 0.5 Kg to 2.0 Kg. The scratch width is obtained at various scratch load and test conditions. The Brinell hardness test is carried out and investigated for both corroded and inhibited specimens. The results showed that three natural extracts can be used as environmentally friendly corrosion inhibitors.

Keywords: inhibition, natural extract, oil pipelines corrosion, sulphur compounds

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Authors: J. Suneetha, Vijayalaxmi

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Sequential Pattern Mining involves applying data mining methods to large data repositories to extract usage patterns. Sequential pattern mining methodologies used to analyze the data and identify patterns. The patterns have been used to implement efficient systems can recommend on previously observed patterns, in making predictions, improve usability of systems, detecting events, and in general help in making strategic product decisions. In this paper, identified performance of approximate sequential pattern mining defines as identifying patterns approximately shared with many sequences. Approximate sequential patterns can effectively summarize and represent the databases by identifying the underlying trends in the data. Conducting an extensive and systematic performance over synthetic and real data. The results demonstrate that ApproxMAP effective and scalable in mining large sequences databases with long patterns.

Keywords: multiple data, performance analysis, sequential pattern, sequence database scalability

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Authors: Hee-Jeong Ahn, Kee-Won Kim, Seung-Hoon Kim

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The knowledge of the relationship between characters can help readers to understand the overall story or plot of the literary fiction. In this paper, we present a method for extracting the specific relationship between characters from a Korean literary fiction. Generally, methods for extracting relationships between characters in text are statistical or computational methods based on the sentence distance between characters without considering Korean linguistic features. Furthermore, it is difficult to extract the relationship with direction from text, such as one-sided love, because they consider only the weight of relationship, without considering the direction of the relationship. Therefore, in order to identify specific relationships between characters, we propose a statistical method considering linguistic features, such as syntactic patterns and speech verbs in Korean. The result of our method is represented by a weighted directed graph of the relationship between the characters. Furthermore, we expect that proposed method could be applied to the relationship analysis between characters of other content like movie or TV drama.

Keywords: data mining, Korean linguistic feature, literary fiction, relationship extraction

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Authors: Mihir Mouchum Hazarika, Maddali Ramgopal, Souvik Bhattacharyya

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The thermodynamic analysis shows that the performance of the R744 based transcritical refrigeration cycle drops drastically for higher ambient temperatures. This is due to the peculiar s-shape of the isotherm in the supercritical region. However, subcooling of the refrigerant at the gas cooler exit enhances the performance of the R744 based system. The present study is carried out to analyze the R744 based transcritical system with dedicated mechanical subcooling cycle. Based on this proposed cycle, the thermodynamic analysis is performed, and optimum operating parameters are determined. The amount of subcooling and the pressure ratio in the subcooling cycle are the parameters which are needed to be optimized to extract the maximum COP from this proposed cycle. It is expected that this study will be helpful in implementing the dedicated subcooling cycle with R744 based transcritical system to improve the performance.

Keywords: optimization, R744, subcooling, transcritical

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Authors: Sam Khozama, Ali M. Mayya

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Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data needs a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM) and ensemble learning with hyper parameters optimization are used, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.

Keywords: machine learning, deep learning, cancer prediction, breast cancer, LSTM, fusion

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Authors: Arunporn Itharat, Srisopa Ruangnoo, Pakakrong Thongdeeying

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The rhizomes of Dioscorea membranacea (DM) has long been used in Thai Traditional medicine to treat cancer and inflammatory conditions such as rheumatism. The objective of this study was to investigate anti-inflammatory activity by determining the inhibitory effect on LPS-induced TNF-α from RAW264.7 cells of crude extracts and pure isolated compounds from DM. Three known dihydrophenantrene compounds were isolated by a bioassay guided isolation method from DM ethanolic extract [2,4 dimethoxy-5,6-dihydroxy-9,10-dihydrophenanthrene (1) and 5-hydroxy-2,4,6-trimethoxy-9,10-dihydrophenanthrene(2) and 5,6,2 -trihydroxy 3,4-methoxy, 9,10- dihydrophenanthrene (3)]. 1 showed the highest inhibitory effect on PGE2, followed by 3 and 1 (IC50 = 2.26, 4.97 and >20 μg/ml or 8.31,17.25 and > 20 µM respectively). These findings suggest that this plant showed anti-inflamatory effects by displaying an inhibitory effect on TNF-α release, hence, this result supports the usage of Thai traditional medicine to treat inflammation related diseases.

Keywords: Dioscorea membranacea, anti-inflammatory activity, TNF-Alpha , dihidrophenantrene compound

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Authors: P. S. Akami, H. Nahunnaro, A. Zubainatu

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Cercospora leaf spot (Cercospora sesami. Zimm) has been identified as one of the most prevalent diseases, posing serious constraints to sesame production in producing areas. Two sets of experiments were carried out. The first and second experiments were conducted in the Modibbo Adama University of Technology Yola at the Crop Production and Horticulture and Plant Science Departments, respectively. The field experiment was carried out using a Randomized Complete Block Design and was replicated three times on a plot size of 4m x 5m with four sesame varieties and three Mancob-M fungicide levels (0g, 2g and 4g) to give a total of Twelve treatments. The laboratory experiment involved the isolation of the pathogens from diseased leaves with symptoms of Cercospora leaf spot, which was identified as Cercospora sesami. Data collected were subjected to analysis of variance for a randomized complete block design using SAS (1999) statistical package. The treatment means that are significantly different were separated using the Least Significant Difference at P=0.05. The result revealed that 4g Mancob M recorded the lowest mean value for disease incidence and severity at 8WAS, which was 90.30% and 35.60%, respectively, while the control (0g) recorded the highest mean value for disease incidence and severity at 90.30% and 59.80% respectively. Ex-Sudan recorded the lowest value of 720 kg/ha, while NCRIBEN 03 recorded the highest yield of 834 kg/ha-¹. For the concentrations, 2g recorded a higher yield of 843 kg/ha-¹ followed by 0g, which recorded 765 kg/ha-¹. Conclusively, Cercospora leaf spot of sesame was found to be prevalent. E8 has a higher resistance to the disease, while NCRIBEN 03 tends to be more susceptible. It is therefore recommended that further trials should be carried out using different varieties in different locations.

Keywords: disease, evaluation, prevalence, treatment, resistance

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Authors: Rauf R. Hussein, Devon M. Ramey

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Integrating Ground Penetrating Radar (GPR) with Geographic Information Systems (GIS) can provide valuable insights for various applications, such as archaeology, transportation, and utility locating. Although there has been progress toward automating the integration of GPR data with GIS, fully automatic integration has not been achieved yet. Additionally, manually integrating GPR data with GIS can be a time-consuming and error-prone process. In this study, actual, real-world GPR applications are presented, and a software named GPR-GIS 10 is created to interactively extract subsurface targets from GPR radargrams and automatically integrate them into GIS. With this software, it is possible to quickly and reliably integrate the two techniques to create informative subsurface maps. The results indicated that automatic integration of GPR with GIS can be an efficient tool to map and view any subsurface targets in their appropriate location in a 3D space with the needed precision. The findings of this study could help GPR-GIS integrators save time and reduce errors in many GPR-GIS applications.

Keywords: GPR, GIS, GPR-GIS 10, drone technology, automation

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Authors: Zhibo Xiao, Tharini Nayanika de Silva, Kezhi Mao

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In this paper, we present an evolving knowledge extraction system named AKEOS (Automatic Knowledge Extraction from Online Sources). AKEOS consists of two modules, including a one-time learning module and an evolving learning module. The one-time learning module takes in user input query, and automatically harvests knowledge from online unstructured resources in an unsupervised way. The output of the one-time learning is a structured vector representing the harvested knowledge. The evolving learning module automatically schedules and performs repeated one-time learning to extract the newest information and track the development of an event. In addition, the evolving learning module summarizes the knowledge learned at different time points to produce a final knowledge vector about the event. With the evolving learning, we are able to visualize the key information of the event, discover the trends, and track the development of an event.

Keywords: evolving learning, knowledge extraction, knowledge graph, text mining

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Authors: Anupalli Roja Rani, Pavithra Dasari

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Background: Among several, breast cancer has emerged as the most common female cancer in developing countries. It is the most common cause of cancer-related deaths worldwide among women. It is a molecularly and clinically heterogeneous disease. Moreover, it is a hormone–dependent tumor in which estrogens can regulate the growth of breast cells by binding with estrogen receptors (ERs). Moreover, the use of natural products in cancer therapeutics is due to their properties of biocompatibility and less toxicity. Plants are the vast reservoirs for various bioactive compounds. Coleus barbatus (Lamiaceae) contains anticancer properties against several cancer cell lines. Method: In the present study, an attempt is being made to enrich the knowledge of the anticancer activity of pure compounds extracted from Coleus barbatus (Andrew). On human breast cancer cell lines MCF-7. Here in, we are assessing the antiproliferative activity of Coleus barbatus (Andrew) plant extracts against MCF 7 and also evaluating their toxicity in normal human mammary cell lines such as Human Mammary Epithelial Cells (HMEC). The active fraction of plant extract was further purified with the help of Flash chromatography, Medium Pressure Liquid Chromatography (MPLC) and preparative High-Performance Liquid Chromatography (HPLC). The structure of pure compounds will be elucidated by using modern spectroscopic methods like Nuclear magnetic resonance (NMR), Electrospray Ionisation Mass Spectrometry (ESI-MS) methods. Later, the growth inhibition morphological assessment of cancer cells and cell cycle analysis of purified compounds were assessed using FACS. The growth and progression of signaling molecules HER2, GRP78 was studied by secretion assay using ELISA and expression analysis by flow cytometry. Result: Cytotoxic effect against MCF-7 with IC50 values were derived from dose response curves, using six concentrations of twofold serially diluted samples, by SOFTMax Pro software (Molecular device) and respectively Ellipticine and 0.5% DMSO were used as a positive and negative control. Conclusion: The present study shows the significance of various bioactive compounds extracted from Coleus barbatus (Andrew) root material. It acts as an anti-proliferative and shows cytotoxic effects on human breast cancer cell lines MCF7. The plant extracts play an important role pharmacologically. The whole plant has been used in traditional medicine for decades and the studies done have authenticated the practice. Earlier, as described, the plant has been used in the ayurveda and homeopathy medicine. However, more clinical and pathological studies must be conducted to investigate the unexploited potential of the plant. These studies will be very useful for drug designing in the future.

Keywords: coleus barbatus, HPLC, MPLC, NMR, MCF7, flash chromatograph, ESI-MS, FACS, ELISA.

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Authors: K. Harrat, M. Hidjeb, M. T’kint

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The aim of the present research work is to characterize a cement palm date fiber composite in order to be used in isolation and in the manufacture of new structural materials. This technique may possibly participate seriously in the preservation of the environment and develop a growing need for plant products. On one hand, It has been shown that the presence of natural fiber in the composite materials manufacture, based on hydraulic binder, has improved the mechanical behaviour of the material. On the Other hand, It has been proven that the durability of composite materials reinforced with untreated fibers was largely affected by the presence of organic matter. In order to extract the organic material, the fibers were treated with boiling water and then coated with different types of products. A considerable improvement in the sensitivity to water of the fibers, as well as in the mechanical strength and in the ductility of the composite material was observed. The fiber being sensitive to water, the study put the emphasis on its dimensional stability.

Keywords: cement composite, durability, heat treatment, mechanical behaviour, vegetal fiber

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Authors: Reenu Yadav, S. K. Yadav

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Herbal therapy has been used for daily oral health care to prevent, treat or cure oral conditions from halitosis to periodontal diseases. The importance of mouth and teeth cleanliness has been recognized from the earliest days of civilization to the 21st century. In the present study, leaves and seeds of Cordia obliqua and barks and twigs of Beautea monosperma, which is used traditionally for oral diseases was evaluated for its antimicrobial activity. The antimicrobial activity tests indicated that the methanolic extract exhibited stronger activities against the commonly encountered oral bacterial and fungal pathogens. The mouthwash formulation prepared and it is compared with marketed formulation HiOra. The results indicated that the herbal mouthwash could inhibit the growth of oral pathogens and may prevent plaque and other periodontal diseases caused by dental pathogens.

Keywords: herbal mouthwash, bio medicine, life sciences, herbal extracts

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Authors: Vahid Bairami Rad

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Extracting knowledge from spatial data like GIS data is important to reduce the data and extract information. Therefore, the development of new techniques and tools that support the human in transforming data into useful knowledge has been the focus of the relatively new and interdisciplinary research area ‘knowledge discovery in databases’. Thus, we introduce a set of database primitives or basic operations for spatial data mining which are sufficient to express most of the spatial data mining algorithms from the literature. This approach has several advantages. Similar to the relational standard language SQL, the use of standard primitives will speed-up the development of new data mining algorithms and will also make them more portable. We introduced a database-oriented framework for spatial data mining which is based on the concepts of neighborhood graphs and paths. A small set of basic operations on these graphs and paths were defined as database primitives for spatial data mining. Furthermore, techniques to efficiently support the database primitives by a commercial DBMS were presented.

Keywords: spatial data base, knowledge discovery database, data mining, spatial relationship, predictive data mining

Procedia PDF Downloads 460

Authors: Fatimazahrae Elbakri, Azeddine Ibrahimi, Meryem Lemrani, Dris Belghyti

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Leishmaniasis represents a major public health problem because of the number of cases recorded each year and the wide distribution of the disease. It is a parasitic disease of flagellated protozoa transmitted by the bite of certain species of sandfly, causing a spectrum of clinical pathology in humans ranging from disfiguring skin lesions to fatal visceral leishmaniasis. Cutaneous leishmaniasis due to Leishmania major is a polymorphic disease; in fact, the infection can be asymptomatic, localized, or disseminated. The objective of this work is to determine the genomic diversity that contributes to clinical variability by trying to identify the variation in chromosome number and to extract SNPs and SNPs and InDels; it is based on four sequences (WGS) of Leishmania major available on NCBI in Fastq form, from three countries: Tunisia, Algeria, and Israel, the analysis is set up from a pipeline to facilitate the discovery of genetic diversity, in particular SNP and chromosomal somy.

Keywords: Leshmania major, cutaneous Leishmania, NGS, genomic, somy, variant calling

Procedia PDF Downloads 79

Authors: Bushra Jamil, Nudrat Baqri, Muhammad Hassan Saeed

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Entrepreneurship is creating or setting up a business not only for the purpose of generating profit but also for providing job opportunities. Entrepreneurs are problem solvers and product developers. They use their financial asset for hiring a professional team and combine the innovation, knowledge, and leadership leads to a successful startup or a business. To be a successful entrepreneur, one should be people-oriented and have perseverance. One must have the ability to take risk, believe in his/her potential, and have the courage to move forward in all circumstances. Most importantly, have the ability to take risk and can assess the risk. For STEM students, entrepreneurship is of specific importance and relevance as it helps them not just to be able to solve real life existing complications but to be able to recognize and identify emerging needs and glitches. It is becoming increasingly apparent that in today’s world, there is a need as well as a desire for STEM and entrepreneurship to work together. In Pakistan, entrepreneurship is slowly emerging, yet we are far behind. It is high time that we should introduce modern teaching methods and inculcate entrepreneurial initiative in students. A course on entrepreneurship can be included in the syllabus, and we must invite businessmen and policy makers to motivate young minds for entrepreneurship. This must be pitching competitions, opportunities to win seed funding, and facilities of incubation centers. In Pakistan, there are many good public sector research institutes, yet there is a void gap in the private sector. Only few research institute are meant for research and development. BJ Micro Lab is one of them. It is SECP registered company and is working in academia to promote and facilitate research in STEM. BJ Micro Lab is a women led initiative, and we are trying to promote research as a passion, not as an arduous burden. For this, we are continuously arranging training workshops and sessions. More than 100 students have been trained in ten different workshops arranged at BJ Micro Lab.

Keywords: entrepreneurship, STEM, challenges, oppurtunties

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Authors: Amir Mabhout, Toktam Ghafarian, Amirhossein Farzin, Zahra Makki, Sajjad Alizadeh, Amirhossein Ghavi

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The high number of Netflix subscribers makes it attractive for data scientists to extract valuable knowledge from the viewers' behavioural analyses. This paper presents a set of statistical insights into viewers' viewing history. After that, a deep learning model is used to predict the future watching behaviour of the users based on previous watching history within the Netflixlatte data pool. Netflixlatte in an aggregated and anonymized data pool of 320 Netflix viewers with a length 250 000 data points recorded between 2008-2022. We observe insightful correlations between the distribution of viewing time and the COVID-19 pandemic outbreak. The presented deep learning model predicts future movie and TV series viewing habits with an average loss of 0.175.

Keywords: data analysis, deep learning, LSTM neural network, netflix

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Authors: Maryam Nazari

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COVID-19 is a respiratory disease triggered by the novel coronavirus, SARS-CoV-2, that has reached pandemic status today. Acute inflammation and immune cells infiltration into lung injuries result in multi-organ failure. The presence of other non-communicable diseases (NCDs) with systemic inflammation derived from COVID-19 may exacerbate the patient's situation and increase the risk for adverse effects and mortality. This pandemic is a novel situation and the scientific community at this time is looking for vaccines or drugs to treat the pathology. One of the biggest challenges is focused on reducing inflammation without compromising the correct immune response of the patient. In this regard, addressing the nutritional factors should not be overlooked not only as a matter of avoiding the presence of NCDs with severe infections but also as an adjunctive way to modulate the inflammatory status of the patients. Despite the pivotal role of nutrition in modifying immune response, due to the novelty of the COVID-19 disease, information about the effects of specific dietary agents is limited in this area. From the macronutrients point of view, protein deficiency (quantity or quality) has negative effects on the number of functional immunoglobulins and gut-associated lymphoid tissue (GALT). High biological value proteins or some amino acids like arginine and glutamine are well known for their ability to augment the immune system. Among lipids, fish oil has the ability to inactivate enveloped viruses, suppress pro-inflammatory prostaglandin production and block platelet-activating factors and their receptors. In addition, protectin D1, which is an Omega-3 PUFAs derivation, is a novel antiviral drug. So it seems that these fatty acids can reduce the severity and/or improve recovery of patients with COVID-19. Carbohydrates with lower glycemic index and fibers are associated with lower levels of inflammatory cytokines (CRP, TNF-α, and IL-6). Short-Chain Fatty acids not only exert a direct anti-inflammatory effect but also provide appropriate gut microbial, which is important in gastrointestinal issues related to COVID-19. From the micronutrients point of view, Vitamins A, C, D, E, iron, magnesium, zinc, selenium and copper play a vital role in the maintenance of immune function. Inadequate status in these nutrients may result in decreased resistance against COVID-19 infection. There are specific bioactive compounds in the diet that interact with the ACE2 receptor, which is the gateway for SARS and SARS-CoV-2, and thus controls the viral infection. Regarding this, the potential benefits of probiotics, resveratrol (a polyphenol found in grape), oleoylethanolamide (derived from oleic acid), and natural peroxisome proliferator-activated receptor γ agonists in foodstuffs (like curcumin, pomegranate, hot pepper) are suggested. Yet, it should be pointed out that most of these results have been reported in animal models and further human studies are needed to be verified.

Keywords: Covid-19, inflammation, nutrition, dietary agents

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Authors: Indira K., Valsamma Joseph, I. S. Bright

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Introduction :Biofuels could replace fossil fuels and reduce our carbon footprint on the planet by technological advancements needed for sustainable and economic fuel production. Micro algae have proven to be a promising source to meet the current energy demand because of high lipid content and production of high biomass rapidly. Marine diatoms, which are key contributors in the biofuel sector and also play a significant role in primary productivity and ecology with high biodiversity and genetic and chemical diversity, are less well understood than other microalgae for producing hydrocarbons. Method :The marine diatom samples selected for hydrocarbon analysis were a total of eleven, out of which 9 samples were from the culture collection of NCAAH, and the remaining two of them were isolated by serial dilution method to get a pure culture from a mixed culture of microalgae obtained from the various cruise stations (350&357) FORV Sagar Sampada along the west coast of India. These diatoms were mass cultured in F/2 media, and the biomass harvested. The crude extract was obtained from the biomass by homogenising with n-hexane, and the hydrocarbons was further obtained by passing the crude extract through 500mg Bonna Agela SPE column and the quantitative analysis was done by GCHRMS analysis using HP-5 column and Helium gas was used as a carrier gas(1ml/min). The injector port temperature was 2400C, the detector temperature was 2500C, and the oven was initially kept at 600C for 1 minute and increased to 2200C at the rate of 60C per minute, and the analysis of a mixture of long chain hydrocarbons was done .Results:In the qualitative analysis done, the most potent hydrocarbon was found to be Psammodictyon Panduriforme (NCAAH-9) with a hydrocarbon mass of 37.27mg/g of the biomass and 2.1% of the total biomass 0f 1.395g and the other potent producer is Biddulphia(NCAAH 6) with hydrocarbon mass of 25.4mg/g of biomass and percentage of hydrocarbon is 1.03%. In the quantitative analysis by GCHRMS, the long chain hydrocarbons found in most of the marine diatoms were undecane, hexadecane, octadecane 3ethyl 5,2 ethyl butyl, Eicosane7hexyl, hexacosane, heptacosane, heneicosane, octadecane 3 methyl, triacontane. The exact mass of the long chain hydrocarbons in all the marine diatom samples was found to be Nonadecane 12C191H40, Tritriacontane,13-decyl-13-heptyl 12C501H102, Octadecane,3ethyl-5-(2-ethylbutyl 12C261H54, tetratetracontane 12C441H89, Eicosane, 7-hexyl 12C261H54. Conclusion:All the marine diatoms screened produced long chain hydrocarbons which can be used as diesel fuel with good cetane value example, hexadecane, undecane. All the long chain hydrocarbons can further undergo catalytic cracking to produce short chain alkanes which can give good octane values and can be used as gasoline. Optimisation of hydrocarbon production with the most potent marine diatom yielded long chain hydrocarbons of good fuel quality.

Keywords: biofuel, hydrocarbons, marine diatoms, screening

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Authors: B. X. Tchomeni, A. A. Alugongo, T. B. Tengen

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In this paper, de Laval rotor system has been characterized by a hinge model and its transient response numerically treated for a dynamic solution. The effect of the ensuing non-linear disturbances namely rub and breathing crack is numerically simulated. Subsequently, three analysis methods: Orbit Analysis, Fast Fourier Transform (FFT) and Wavelet Transform (WT) are employed to extract features of the vibration signal of the faulty system. An analysis of the system response orbits clearly indicates the perturbations due to the rotor-to-stator contact. The sensitivities of WT to the variation in system speed have been investigated by Continuous Wavelet Transform (CWT). The analysis reveals that features of crack, rubs and unbalance in vibration response can be useful for condition monitoring. WT reveals its ability to detect non-linear signal, and obtained results provide a useful tool method for detecting machinery faults.

Keywords: Continuous wavelet, crack, discrete wavelet, high acceleration, low acceleration, nonlinear, rotor-stator, rub

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Authors: In-Geun Lim, Sung-Woong Ra

Abstract:

As high resolution satellite images can be used, lots of studies are carried out for exploiting these images in various fields. This paper proposes the method based on mathematical morphology for extracting the ‘horse's hoof shaped object’. This proposed method can make an automatic object detection system to track the meaningful object in a large satellite image rapidly. Mathematical morphology process can apply in binary image, so this method is very simple. Therefore this method can easily extract the ‘horse's hoof shaped object’ from any images which have indistinct edges of the tracking object and have different image qualities depending on filming location, filming time, and filming environment. Using the proposed method by which ‘horse's hoof shaped object’ can be rapidly extracted, the performance of the automatic object detection system can be improved dramatically.

Keywords: facility detection, satellite image, object, mathematical morphology

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Authors: Stepan Grebeniuk, Ersi Hodo, Henri Ruotsalainen, Paul Tavolato

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Substation security plays an important role in the power delivery system. During the past years, there has been an increase in number of attacks on automation networks of the substations. In spite of that, there hasn’t been enough focus dedicated to the protection of such networks. Aiming to design a specialized anomaly detection system based on machine learning, in this paper we will discuss the IEC 60870-5-104 protocol that is used for communication between substation and control station and focus on the simulation of the substation traffic. Firstly, we will simulate the communication between substation slave and server. Secondly, we will compare the system's normal behavior and its behavior under the attack, in order to extract the right features which will be needed for building an anomaly detection system. Lastly, based on the features we will suggest the anomaly detection system for the asynchronous protocol IEC 60870-5-104.

Keywords: Anomaly detection, IEC-60870-5-104, Machine learning, Man-in-the-Middle attacks, Substation security

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Authors: Christopher Mkirema Maghanga, Maurice Mghendi Mwamburi

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Parametric modeling provides a means to deeper understand the properties of materials. Drude, Brendel, Lorentz and OJL incorporated in SCOUT® software are some of the models used to study dielectric films. In our work, we utilized Brendel and Drude models to extract the optical constants from spectroscopic data of fabricated undoped and niobium doped titanium oxide thin films. The individual contributions by the two models were studied to establish how they influence the dielectric function. The effect of dopants on their influences was also analyzed. For the undoped films, results indicate minimal contribution from the Drude term due to the dielectric nature of the films. However as doping levels increase, the rise in the concentration of free electrons favors the use of Drude model. Brendel model was confirmed to work well with dielectric films - the undoped titanium Oxide films in our case.

Keywords: modeling, Brendel model, optical constants, titanium oxide, Drude Model

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Authors: Marc Toutain, Pascale Leconte, Antoine Gauthier

Abstract:

Introduction: Eating Disorders (ED), such as anorexia, bulimia, and binge eating, are psychiatric illnesses that mostly affect young people. The main symptoms concern eating (restriction, excessive food intake) and weight control behaviors (laxatives, vomiting). Psychological comorbidities (depression, executive function disorders, etc.) and problematic behaviors toward physical activity (PA) are commonly associated with ED. Acquaintances on ED risk factors are still lacking, and more community sample studies are needed to improve prevention and early detection. To our knowledge, studies are needed to specifically investigate the link between ED risk level, PA, and psychological risk factors in a community sample of adolescents. The aim of this study is to assess the relation between ED risk level, exercise (type, frequency, and motivations for engaging in exercise), and psychological factors based on the Jacobi risk factors model. We suppose that a high risk of ED will be associated with the practice of high caloric cost PA, motivations oriented to weight and shape control, and psychological disturbances. Method: An online survey destined for students has been sent to several middle schools and colleges in northwest France. This survey combined several questionnaires, the Eating Attitude Test-26 assessing ED risk; the Exercise Motivation Inventory–2 assessing motivations toward PA; the Hospital Anxiety and Depression Scale assessing anxiety and depression, the Contour Drawing Rating Scale; and the Body Esteem Scale assessing body dissatisfaction, Rosenberg Self-esteem Scale assessing self-esteem, the Exercise Dependence Scale-Revised assessing PA dependence, the Multidimensional Assessment of Interoceptive Awareness assessing interoceptive awareness and the Frost Multidimensional Perfectionism Scale assessing perfectionism. Machine learning analysis will be performed in order to constitute groups with a tree-based model clustering method, extract risk profile(s) with a bootstrap method comparison, and predict ED risk with a prediction method based on a decision tree-based model. Expected results: 1044 complete records have already been collected, and the survey will be closed at the end of May 2022. Records will be analyzed with a clustering method and a bootstrap method in order to reveal risk profile(s). Furthermore, a predictive tree decision method will be done to extract an accurate predictive model of ED risk. This analysis will confirm typical main risk factors and will give more data on presumed strong risk factors such as exercise motivations and interoceptive deficit. Furthermore, it will enlighten particular risk profiles with a strong level of proof and greatly contribute to improving the early detection of ED and contribute to a better understanding of ED risk factors.

Keywords: eating disorders, risk factors, physical activity, machine learning

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Authors: Roukia Hammoudi, Chabrouk Farid, Dehak Karima, Mahfoud Hadj Mahammed, Mohamed Didi Ouldelhadj

Abstract:

The objective of this study was to optimise the extraction conditions for phenolic compounds from Deverra scoparia Coss and Dur. Apiaceae plant by ultrasound assisted extraction (UAE). The effects of solvent type (acetone, ethanol and methanol), solvent concentration (%), extraction time (mins) and extraction temperature (°C) on total phenolic content (TPC) were determined. The optimum extraction conditions were found to be acetone concentration of 80%, extraction time of 25 min and extraction temperature of 25°C. Under the optimized conditions, the value for TPC was 9.68 ± 1.05 mg GAE/g of extract. The study of the antioxidant power of these oils was performed by the method of DPPH. The results showed that antioxidant activity of the Deverra scoparia essential oil was more effective as compared to ascorbic acid and trolox.

Keywords: Deverra scoparia, phenolic compounds, ultrasound assisted extraction, total phenolic content, antioxidant activity

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Authors: Roukia Hammoudi, Dehak Karima, Chabrouk Farid, Mahfoud Hadj Mahammed, Mohamed Didi Ouldelhadj

Abstract:

The objective of this study was to optimise the extraction conditions for phenolic compounds from Deverra scoparia Coss and Dur. Apiaceae plant by ultrasound assisted extraction (UAE). The effects of solvent type (Acetone, Ethanol and methanol), solvent concentration (%), extraction time (mins) and extraction temperature (°C) on total phenolic content (TPC) were determined. the optimum extraction conditions were found to be acetone concentration of 80%, extraction time of 25 min and extraction temperature of 25°C. Under the optimized conditions, the value for TPC was 9.68 ± 1.05 mg GAE/g of extract. The study of the antioxidant power of these oils was performed by the method of DPPH. The results showed that antioxidant activity of the Deverra scoparia essential oil was more effective as compared to ascorbic acid and trolox.

Keywords: Deverra scoparia, phenolic compounds, ultrasound assisted extraction, total phenolic content, antioxidant activity

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Authors: Z. Bouattou, R. Laurini, H. Belbachir

Abstract:

This paper describes a new approach for the automatic generation of the visual summaries dealing with cartographic visualization methods and sensors real time data modeling. Hence, the concept of chorems seems an interesting candidate to visualize real time geographic database summaries. Chorems have been defined by Roger Brunet (1980) as schematized visual representations of territories. However, the time information is not yet handled in existing chorematic map approaches, issue has been discussed in this paper. Our approach is based on spatial analysis by interpolating the values recorded at the same time, by sensors available, so we have a number of distributed observations on study areas and used spatial interpolation methods to find the concentration fields, from these fields and by using some spatial data mining procedures on the fly, it is possible to extract important patterns as geographic rules. Then, those patterns are visualized as chorems.

Keywords: geovisualization, spatial analytics, real-time, geographic data streams, sensors, chorems

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Authors: Jone Ibarruri, Mikel Manso, Marta Cebrián

Abstract:

A high amount of food is lost or discarded in the World every year. In addition, in the last decades, an increasing demand of new alternative and sustainable sources of proteins and other valuable compounds is being observed in the food and feeding sectors and, therefore, the use of food by-products as nutrients for these purposes sounds very interesting from the environmental and economical point of view. However, the direct use of discarded fruit and vegetables that present, in general, a low protein content is not interesting as feeding ingredient except if they are used as a source of fiber for ruminants. Especially in the case of aquaculture, several alternatives to the use of fish meal and other vegetable protein sources have been extensively explored due to the scarcity of fish stocks and the unsustainability of fishing for these purposes. Fish mortality is also of great concern in this sector as this problem highly reduces their economic feasibility. So, the development of new functional and natural ingredients that could reduce the need for vaccination is also of great interest. In this work, several fermentation tests were developed at lab scale using a selected mixture of fruit and vegetable discards from a wholesale market located in the Basque Country to increase their protein content and also to produce some bioactive extracts that could be used as additives in aquaculture. Fruit and vegetable mixtures (60/40 ww) were centrifugated for humidity reduction and crushed to 2-5 mm particle size. Samples were inoculated with a selected Rhizopus oryzae strain and fermented for 7 days in controlled conditions (humidity between 65 and 75% and 28ºC) in Petri plates (120 mm) by triplicate. Obtained results indicated that the final fermented product presented a twofold protein content (from 13 to 28% d.w). Fermented product was further processed to determine their possible functionality as a feed additive. Extraction tests were carried out to obtain an ethanolic extract (60:40 ethanol: water, v.v) and remaining biomass that also could present applications in food or feed sectors. The extract presented a polyphenol content of about 27 mg GAE/gr d.w with antioxidant activity of 8.4 mg TEAC/g d.w. Remining biomass is mainly composed of fiber (51%), protein (24%) and fat (10%). Extracts also presented antibacterial activity according to the results obtained in Agar Diffusion and to the Minimum Inhibitory Concentration (MIC) tests determined against several food and fish pathogen strains. In vitro, digestibility was also assessed to obtain preliminary information about the expected effect of extraction procedure on fermented product digestibility. First results indicated that remaining biomass after extraction doesn´t seem to improve digestibility in comparison to the initial fermented product. These preliminary results show that fermented fruit and vegetables can be a useful source of functional ingredients for aquaculture applications and a substitute of other protein sources in the feeding sector. Further validation will be also carried out through “in vivo” tests with trout and bass.

Keywords: fungal solid state fermentation, protein increase, functional extracts, feed ingredients

Procedia PDF Downloads 64