Search results for: monitoring/methods and impact assessment
Commenced in January 2007
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Edition: International
Paper Count: 28925

Search results for: monitoring/methods and impact assessment

10475 A Comprehensive Study of Camouflaged Object Detection Using Deep Learning

Authors: Khalak Bin Khair, Saqib Jahir, Mohammed Ibrahim, Fahad Bin, Debajyoti Karmaker

Abstract:

Object detection is a computer technology that deals with searching through digital images and videos for occurrences of semantic elements of a particular class. It is associated with image processing and computer vision. On top of object detection, we detect camouflage objects within an image using Deep Learning techniques. Deep learning may be a subset of machine learning that's essentially a three-layer neural network Over 6500 images that possess camouflage properties are gathered from various internet sources and divided into 4 categories to compare the result. Those images are labeled and then trained and tested using vgg16 architecture on the jupyter notebook using the TensorFlow platform. The architecture is further customized using Transfer Learning. Methods for transferring information from one or more of these source tasks to increase learning in a related target task are created through transfer learning. The purpose of this transfer of learning methodologies is to aid in the evolution of machine learning to the point where it is as efficient as human learning.

Keywords: deep learning, transfer learning, TensorFlow, camouflage, object detection, architecture, accuracy, model, VGG16

Procedia PDF Downloads 125
10474 Applying Hybrid Graph Drawing and Clustering Methods on Stock Investment Analysis

Authors: Mouataz Zreika, Maria Estela Varua

Abstract:

Stock investment decisions are often made based on current events of the global economy and the analysis of historical data. Conversely, visual representation could assist investors’ gain deeper understanding and better insight on stock market trends more efficiently. The trend analysis is based on long-term data collection. The study adopts a hybrid method that combines the Clustering algorithm and Force-directed algorithm to overcome the scalability problem when visualizing large data. This method exemplifies the potential relationships between each stock, as well as determining the degree of strength and connectivity, which will provide investors another understanding of the stock relationship for reference. Information derived from visualization will also help them make an informed decision. The results of the experiments show that the proposed method is able to produced visualized data aesthetically by providing clearer views for connectivity and edge weights.

Keywords: clustering, force-directed, graph drawing, stock investment analysis

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10473 Evaluation of Antioxidant Activity and Total Phenolic Content of Lens Esculenta Moench, Seeds

Authors: Vivek Kumar Gupta, Kripi Vohra, Monika Gupta

Abstract:

Pulses have been a vital ingredient of the balanced human diet in India. Lentil (Lens culinaris Medikus or Lens esculenta Moench.) is a common legume known since biblical times. Lentil seeds, with or without hulls, are cooked as dhal and this has been the main dish for millennia in the South Asian region. Oxidative stress can damage lipids, proteins, enzymes, carbohydrates and DNA in cells and tissues, resulting in membrane damage, fragmentation or random cross linking of molecules like DNA, enzymes and structural proteins and even lead to cell death induced by DNA fragmentation and lipid peroxidation. These consequences of oxidative stress construct the molecular basis in the development of cancer, neurodegenerative disorders, cardiovascular diseases, diabetes and autoimmune. The aim of the present work is to assess the antioxidant potential of the peteroleum ether, acetone, methanol and water extract of the Lens esculenta seeds. In vitro antioxidant assessment of the extracts was carried out using 1,1-diphenyl-2-picryl hydrazyl (DPPH) radical scavenging activity, hydroxyl radical scavenging activity, reducing power assay. The quantitative estimation of total phenolic content, total flavonoid content in extracts and in plant material, total saponin content, total alkaloid content, crude fibre content, total volatile content, fat content and mucilage content in drug material was also carried out. Though all the extracts exhibited dose dependent reducing power activity the acetone extract was found to possess significant hydrogen donating ability in DPPH (45.83%-93.13%) and hydroxyl radical scavenging system (28.7%-46.41%) than the peteroleum ether, methanol and water extracts. Total phenolic content in the acetone and methanol extract was found to be 608 and 188 mg gallic acid equivalent of phenol/g of sample respectively. Total flavonoid content of acetone and methanol extract was found to be 128 and 30.6 mg quercetin equivalent/g of sample respectively. It is evident that acetone extract of Lentil seeds possess high levels of polyphenolics and flavonoids that could be utilized as antioxidants and neutraceuticals.

Keywords: antioxidant, flavanoids, Lens esculenta, polyphenols

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10472 The Role of Knowledge Sharing in Market Response: The Case of Saman Bank of Iran

Authors: Fatemeh Torabi, Jamal El-Den, Narumon Sriratanviriyakul

Abstract:

Perpetual changes in the workplace and daily business activities bring a need for imbedding organizational knowledge sharing within the organizations’ culture, routines and processes. Organizations should adapt to the changing in the environment in order to survive. Accordingly, the management should promote a knowledge sharing culture which might result in knowledge accumulation, hence better response to these changing environmental conditions. Researchers in the field of strategy and marketing stressed that employees’, as well as the overall performance of the organization, would improve as a result of implementing a knowledge-oriented culture. The research investigated the significant impact of knowledge sharing on market response and the competitiveness of organizations. A knowledge sharing framework was developed based on current literary frameworks with additional constructs such as employees’ learning commitments, experiences and prior knowledge. Linear regression was used to analyze the relationships among dependent and independent variables. The research’s results indicated strong positive correlation between the dependent and independent variables, especially in organizational market sharing. We anticipate that this correlation would improve organizational knowledge sharing related practices and the associated knowledge entities. The research posits the introduced framework could be a solid ground for further investigations on how some organizational factors would influence the organization’s response to the market as well as on competitiveness. Final results support all hypotheses. Finding of this research show that knowledge sharing intention had the significant and positive effect on market response and competitiveness of organizations.

Keywords: knowledge management, knowledge sharing, market response, organizational competitiveness

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10471 Computer-Aided Teaching of Transformers for Undergraduates

Authors: Rajesh Kumar, Roopali Dogra, Puneet Aggarwal

Abstract:

In the era of technological advancement, use of computer technology has become inevitable. Hence it has become the need of the hour to integrate software methods in engineering curriculum as a part to boost pedagogy techniques. Simulations software is a great help to graduates of disciplines such as electrical engineering. Since electrical engineering deals with high voltages and heavy instruments, extra care must be taken while operating with them. The viable solution would be to have appropriate control. The appropriate control could be well designed if engineers have knowledge of kind of waveforms associated with the system. Though these waveforms can be plotted manually, but it consumes a lot of time. Hence aid of simulation helps to understand steady state of system and resulting in better performance. In this paper computer, aided teaching of transformer is carried out using MATLAB/Simulink. The test carried out on a transformer includes open circuit test and short circuit respectively. The respective parameters of transformer are then calculated using the values obtained from open circuit and short circuit test respectively using Simulink.

Keywords: computer aided teaching, open circuit test, short circuit test, simulink, transformer

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10470 Functional Analysis of Thyroid Peroxidase (TPO) Gene Mutations Detected in Patients with Thyroid Dyshormonogenesis

Authors: Biswabandhu Bankura, Srikanta Guria, Madhusudan Das

Abstract:

Purpose: Thyroid peroxidase (TPO) is the key enzyme in the biosynthesis of thyroid hormones. We aimed to identify the spectrum of mutations in the TPO gene leading to hypothyroidism in the population of West Bengal to establish the genetic etiology of the disease. Methods: 200 hypothyroid patients (case) and their corresponding sex and age matched 200 normal individuals (control) were screened depending on their clinical manifestations. Genomic DNA was isolated from peripheral blood samples and TPO gene (Exon 7 to Exon 14) was amplified by PCR. The PCR products were subjected to sequencing to identify mutations. Results: Single nucleotide changes such as Glu 641 Lys, Asp 668 Asn, Thr 725 Pro, Asp 620 Asn, Ser 398 Thr, and Ala 373 Ser were found. Changes in the TPO were assayed in vitro to compare mutant and wild-type activities. Five mutants were enzymatically inactive in the guaiacol and iodide assays. This is a strong indication that the mutations are present at crucial positions of the TPO gene, resulting in inactivated TPO. Key Findings: The results of this study may help to develop a genetic screening protocol for goiter and hypothyroidism in the population of West Bengal.

Keywords: thyroid peroxidase, hypothyroidism, mutation, in vitro assay, transfection

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10469 Functional Analysis of Thyroid Peroxidase Gene Mutations Detected in Patients with Thyroid Dyshormonogenesis

Authors: Biswabandhu Bankura, Srikanta Guria, Madhusudan Das

Abstract:

Purpose: Thyroid peroxidase (TPO) is the key enzyme in the biosynthesis of thyroid hormones. We aimed to identify the spectrum of mutations in the TPO gene leading to hypothyroidism in the population of West Bengal to establish the genetic etiology of the disease. Methods: 200 hypothyroid patients (case) and their corresponding sex and age matched 200 normal individuals (control) were screened depending on their clinical manifestations. Genomic DNA was isolated from peripheral blood samples and TPO gene (Exon 7 to Exon 14) was amplified by PCR. The PCR products were subjected to sequencing to identify mutations. Results: Single nucleotide changes such as Glu 641 Lys, Asp 668 Asn, Thr 725 Pro, Asp 620 Asn, Ser 398 Thr, and Ala 373 Ser were found. Changes in the TPO were assayed in vitro to compare mutant and wild-type activities. Five mutants were enzymatically inactive in the guaiacol and iodide assays. This is a strong indication that the mutations are present at crucial positions of the TPO gene, resulting in inactivated TPO. Key Findings: The results of this study may help to develop a genetic screening protocol for goiter and hypothyroidism in the population of West Bengal.

Keywords: thyroid peroxidase, hypothyroidism, mutation, in vitro assay, transfection

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10468 Assessing the Feasibility of Italian Hydrogen Targets with the Open-Source Energy System Optimization Model TEMOA - Italy

Authors: Alessandro Balbo, Gianvito Colucci, Matteo Nicoli, Laura Savoldi

Abstract:

Hydrogen is expected to become a game changer in the energy transition, especially enabling sector coupling possibilities and the decarbonization of hard-to-abate end-uses. The Italian National Recovery and Resilience Plan identifies hydrogen as one of the key elements of the ecologic transition to meet international decarbonization objectives, also including it in several pilot projects for the early development in Italy. This matches the European energy strategy, which aims to make hydrogen a leading energy carrier of the future, setting ambitious goals to be accomplished by 2030. The huge efforts needed to achieve the announced targets require to carefully investigate of their feasibility in terms of economic expenditures and technical aspects. In order to quantitatively assess the hydrogen potential within the Italian context and the feasibility of the planned investments and projects, this work uses the TEMOA-Italy energy system model to study pathways to meet the strict objectives above cited. The possible hydrogen development has been studied both in the supply-side and demand-side of the energy system, also including storage options and distribution chains. The assessment comprehends alternative hydrogen production technologies involved in a competition market, reflecting the several possible investments declined by the Italian National Recovery and Resilience Plan to boost the development and spread of this infrastructure, including the sector coupling potential with natural gas through the currently existing infrastructure and CO2 capture for the production of synfuels. On the other hand, the hydrogen end-uses phase covers a wide range of consumption alternatives, from fuel-cell vehicles, for which both road and non-road transport categories are considered, to steel, and chemical industries uses and cogeneration for residential and commercial buildings. The model includes both high and low TRL technologies in order to provide a consistent outcome for the future decades as it does for the present day, and since it is developed through the use of an open-source code instance and database, transparency and accessibility are fully granted.

Keywords: decarbonization, energy system optimization models, hydrogen, open-source modeling, TEMOA

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10467 Impact of VARK Learning Model at Tertiary Level Education

Authors: Munazza A. Mirza, Khawar Khurshid

Abstract:

Individuals are generally associated with different learning styles, which have been explored extensively in recent past. The learning styles refer to the potential of an individual by which s/he can easily comprehend and retain information. Among various learning style models, VARK is the most accepted model which categorizes the learners with respect to their sensory characteristics. Based on the number of preferred learning modes, the learners can be categorized as uni-modal, bi-modal, tri-modal, or quad/multi-modal. Although there is a prevalent belief in the learning styles, however, the model is not being frequently and effectively utilized in the higher education. This research describes the identification model to validate teacher’s didactic practice and student’s performance linkage with the learning styles. The identification model is recommended to check the effective application and evaluation of the various learning styles. The proposed model is a guideline to effectively implement learning styles inventory in order to ensure that it will validate performance linkage with learning styles. If performance is linked with learning styles, this may help eradicate the distrust on learning style theory. For this purpose, a comprehensive study was conducted to compare and understand how VARK inventory model is being used to identify learning preferences and their correlation with learner’s performance. A comparative analysis of the findings of these studies is presented to understand the learning styles of tertiary students in various disciplines. It is concluded with confidence that the learning styles of students cannot be associated with any specific discipline. Furthermore, there is not enough empirical proof to link performance with learning styles.

Keywords: learning style, VARK, sensory preferences, identification model, didactic practices

Procedia PDF Downloads 261
10466 Feasibility of Using Bike Lanes in Conjunctions with Sidewalks for Ground Drone Applications in Last Mile Delivery for Dense Urban Areas

Authors: N. Bazyar Shourabi, K. Nyarko, C. Scott, M. Jeihnai

Abstract:

Ground drones have the potential to reduce the cost and time of making last-mile deliveries. They also have the potential to make a huge impact on human life. Despite this potential, little work has gone into developing a suitable feasibility model for ground drone delivery in dense urban areas. Today, most of the experimental ground delivery drones utilize sidewalks only, with just a few of them starting to use bike lanes, which a significant portion of some urban areas have. This study works on the feasibility of using bike lanes in conjunction with sidewalks for ground drone applications in last-mile delivery for dense urban areas. This work begins with surveying bike lanes and sidewalks within the city of Boston using Geographic Information System (GIS) software to determine the percentage of coverage currently available within the city. Then six scenarios are examined. Based on this research, a mathematical model is developed. The daily cost of delivering packages using each scenario is calculated by the mathematical model. Comparing the drone delivery scenarios with the traditional method of package delivery using trucks will provide essential information concerning the feasibility of implementing routing protocols that combine the use of sidewalks and bike lanes. The preliminary results of the model show that ground drones that can travel via sidewalks or bike lanes have the potential to significantly reduce delivery cost.

Keywords: ground drone, intelligent transportation system, last-mile delivery, sidewalk robot

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10465 Poly(Methyl Methacrylate) Degradation Products and Its in vitro Cytotoxicity Evaluation in NIH3T3 Cells

Authors: Lesly Y Carmona-Sarabia, Luisa Barraza-Vergara, Vilmalí López-Mejías, Wandaliz Torres-García, Maribella Domenech-Garcia, Madeline Torres-Lugo

Abstract:

Biosensors are used in many applications providing real-time monitoring to treat long-term conditions. Thus, understanding the physicochemical properties and biological side effects on the skin of polymers (e. g., poly(methyl methacrylate), PMMA) employed in the fabrication of wearable biosensors is crucial for the selection of manufacturing materials within this field. The PMMA (hydrophobic and thermoplastic polymer) is commonly employed as a coating material or substrate in the fabrication of wearable devices. The cytotoxicityof PMMA (including residual monomers or degradation products) on the skin, in terms of cells and tissue, is required to prevent possible adverse effects (cell death, skin reactions, sensitization) on human health. Within this work, accelerated aging of PMMA (Mw ~ 15000) through thermal and photochemical degradation was under-taken. The accelerated aging of PMMA was carried out by thermal (200°C, 1h) and photochemical degradation (UV-Vis, 8-15d) adapted employing ISO protocols (ISO-10993-12, ISO-4892-1:2016, ISO-877-1:2009, ISO-188: 2011). In addition, in vitro cytotoxicity evaluation of PMMA degradation products was performed using NIH3T3 fibroblast cells to assess the response of skin tissues (in terms of cell viability) exposed with polymers utilized to manufacture wearable biosensors, such as PMMA. The PMMA (Mw ~ 15000) before and after accelerated aging experiments was characterized by thermal gravimetric analysis (TGA), differential scanning calorimetric (DSC), powder X-ray diffractogram (PXRD), and scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS) to determine and verify the successful degradation of this polymer under the specific conditions previously mention. The degradation products were characterized through nuclear magnetic resonance (NMR) to identify possible byproducts generated after the accelerated aging. Results demonstrated a percentage (%) weight loss between 1.5-2.2% (TGA thermographs) for PMMA after accelerated aging. The EDS elemental analysis reveals a 1.32 wt.% loss of carbon for PMMA after thermal degradation. These results might be associated with the amount (%) of PMMA degrade after the accelerated aging experiments. Furthermore, from the thermal degradation products was detected the presence of the monomer and methyl formate (low concentrations) and a low molecular weight radical (·COOCH3) in higher concentrations by NMR. In the photodegradation products, methyl formate was detected in higher concentrations. These results agree with the proposed thermal or photochemical degradation mechanisms found in the literature.1,2 Finally, significant cytotoxicity on the NIH3T3 cells was obtained for the thermal and photochemical degradation products. A decrease in cell viability by > 90% (stock solutions) was observed. It is proposed that the presence of byproducts (e.g. methyl formate or radicals such as ·COOCH₃) from the PMMA degradation might be responsible for the cytotoxicity observed in the NIH3T3 fibroblast cells. Additionally, experiments using skin models will be employed to compare with the NIH3T3 fibroblast cells model.

Keywords: biosensors, polymer, skin irritation, degradation products, cell viability

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10464 Multi-Classification Deep Learning Model for Diagnosing Different Chest Diseases

Authors: Bandhan Dey, Muhsina Bintoon Yiasha, Gulam Sulaman Choudhury

Abstract:

Chest disease is one of the most problematic ailments in our regular life. There are many known chest diseases out there. Diagnosing them correctly plays a vital role in the process of treatment. There are many methods available explicitly developed for different chest diseases. But the most common approach for diagnosing these diseases is through X-ray. In this paper, we proposed a multi-classification deep learning model for diagnosing COVID-19, lung cancer, pneumonia, tuberculosis, and atelectasis from chest X-rays. In the present work, we used the transfer learning method for better accuracy and fast training phase. The performance of three architectures is considered: InceptionV3, VGG-16, and VGG-19. We evaluated these deep learning architectures using public digital chest x-ray datasets with six classes (i.e., COVID-19, lung cancer, pneumonia, tuberculosis, atelectasis, and normal). The experiments are conducted on six-classification, and we found that VGG16 outperforms other proposed models with an accuracy of 95%.

Keywords: deep learning, image classification, X-ray images, Tensorflow, Keras, chest diseases, convolutional neural networks, multi-classification

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10463 A Deletion in Duchenne Muscular Dystrophy Gene Found Through Whole Exome Sequencing in Iran

Authors: Negin Parsamanesh, Saman Ameri-Mahabadi, Ali Nikfar, Mojdeh Mansouri, Hossein Chiti, Gita Fatemi Abhari

Abstract:

Duchenne muscular dystrophy (DMD) is a severe progressive X-linked neuromuscular illness that affects movement through mutations in dystrophin gene. The mutation leads to insufficient, lack of or dysfunction of dystrophin. The cause of DMD was determined in an Iranian family. Exome sequencing was carried out along with a complete physical examination of the family. In silico methods were applied to find the alteration in the protein structure. The homozygous variant in DMD gene (NM-004006.2) was defined as c.2732-2733delTT (p.Phe911CysfsX8) in exon 21. In addition, phylogenetic conservation study of the human dystrophin protein sequence revealed that phenylalanine 911 is one of the evolutionarily conserved amino acids. In conclusion, our study indicated a new deletion in the DMD gene in the affected family. This deletion with an X-linked inheritance pattern is new in Iran. These findings could facilitate genetic counseling for this family and other patients in the future.

Keywords: duchenne muscular dystrophy, whole exome sequencing, iran, metabolic syndrome

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10462 The Impact of Life Satisfaction on Substance Abuse: Delinquency as a Mediator

Authors: Mahadzirah Mohamad, Morliyati Mohammad, Nor Azman Mat Ali, Zainudin Awang

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Globally, youth substance abuse has been identified as the problem that causes substantial damage not only to individuals, but also to families and communities. In addition, substance abuse youths have become unproductive resources that would play lesser roles in the nation’s development. The increasing trend of substance abuse among youths has raised a lot of concern among various quarters in Malaysia. It has also been reported that Malay youths are the majority group involved in substance abuse. However, it was noted that life satisfaction had been found to be an important mitigating factor that addressed substance abuse. The objectives of the study were twofold: firstly, to ascertain the effect of life satisfaction on substance abuse among Malay youth. Secondly, to identify the role of delinquency on the relationship between life satisfaction and substance abuse. This study adopted a cross-sectional research design. Self-administered questionnaires were distributed to 500 Malay youths at the youth programmes using a two-step sampling technique: area sampling and systematic sampling. The research hypotheses were tested using Structural Equation Modelling. The findings of the study revealed that there is no significance relationship between life satisfaction and substance abuse. There is a significant inverse relationship between life satisfaction and delinquency. Moreover, delinquency has a positive significant influence on substance abuse. The use of Bootstrapping analysis proved that delinquency plays a full mediating role in the relationship between life satisfaction and substance abuse. This study suggested that life satisfaction has no effect on youth substance abuse. In order to reduce substance abuse, efforts should be undertaken to reduce delinquency behaviour by increasing youth life satisfaction.

Keywords: delinquency, life satisfaction, substance abuse, youth

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10461 Evaluation of a Mindfulness and Self-Care-Based Intervention for Teachers to Enhance Mental Health

Authors: T. Noichl, M. Cramer, G. E. Dlugosch, I. Hosenfeld

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Teachers are exposed to a variety of stresses in their work context. These can have a negative impact on physical and psychological well-being. The online training ‘Better Living! Self-care for teachers’ is based on the training ‘Better Living! Self-care for mental health professionals’, which has been proven to be effective over a period of 3 years. The training for teachers is being evaluated for its effectiveness between October 2021 and March 2023 in a study funded by the German Federal Ministry of Education and Research. The aim of the training is to promote self-care and mindfulness among participants and thereby to foster well-being. The concept of self-care was already mentioned in antiquity and was also named as an imperative by philosophers such as Socrates and Epictetus. In the absence of a universal understanding of self-care today, the following definition was developed within the research group: Self-care is 1) facing oneself in a loving and appreciative way, 2) taking one's own needs seriously, and 3) actively contributing to one's own well-being. The study is designed as a randomized wait-control group repeated-measures design with 4 (treatment group) resp. 6 (wait-control group) measurement points. Central dependent variables are self-care, mindfulness, stress, and well-being. To assess the long-term effectiveness of training participation, these constructs are surveyed at the beginning and the end of the training as well as five weeks and one year later. Based on the results of the evaluation with mental health professionals, it is expected that participation will lead to an increase in subjective well-being, self-care, and mindfulness. The first results of the evaluation study are presented and discussed with regard to the effectiveness of the training among teachers.

Keywords: longitudinal intervention study, mindfulness, self-care, teachers’ mental health, well-being

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10460 Phytochemical Screening and Assessment of Hepatoprotective Activity of Geigeria alata Leaves Ethanolic Extract on Wistar Rats

Authors: Girgis Younan, Ikram Eltayeb

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Geigeria alata belongs to the family Asteraceae, is an effective plant traditionally used in Sudan as a therapy for hepatic disease and as an antiepileptic, antispasmodic and to treat cough and intestinal complaints.The liver is responsible for many critical functions within the body and any liver disease or injury will result in the loss of those functions leading to significant damage in the body. Liver diseases cause increase in liver enzymes (AST, ALP ALT) and total bilirubin and a decrease in total blood protein level. The objective of this study is to investigate the hepato-protective activity of Geigeria alata leaves ethanolic extract. The plant leaves were extracted using 96% ethanol using Soxhlet apparatus. The hepatoprotective effect was determined using 25 wistar rats, the rats was divided to 5 groups, each group contain 5 rats: [Normal control group] receiving purified water, liver damage was induced in wistar rats by administering a 1:1 (v/v) mixture of CCl4 (1.25 ml/kg) and olive oil once at day four of the experiment [negative control group]. Two doses of extract [400mg/kg and 200mg/kg] was applied daily for 7 days, and standard drug Silymarin (200 mg/kg) were administered daily for 7 days to CCl4-treated rats. The degree of hepato-protective activity was evaluated by determining the hepatic marker enzymes AST, ALP, ALT, total Bilirubin and total proteins (TP). Results have shown that, the extract of G.alata leaves reduced the level of liver enzymes ALT, AST, ALP, total bilirubin and increased the level of total proteins. Since the levels of liver enzymes; bilirubin and total protein are considered as markers of liver function, the extract has proven to reduce the detrimental effects of liver toxicity induced using CCl4. The hepato-protective effect of extract on liver was found to be dose dependent, where the 400mg/kg dose of the extract exhibited higher activity than 200mg/kg dose. In addition, the effect of the higher dose (400mg/kg) of the extract was found to be higher than Silymarin standard drug. The result concludes that, G.alata leaves extract was found to exhibit profound hepato-protective activity, which justifies the traditional use of the plant for the treatment of hepatic diseases.

Keywords: alata, extract, geigeria, hepatoprotective

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10459 Soil Penetration Resistance and Water Content Spatial Distribution Following Different Tillage and Crop Rotation in a Chinese Mollisol

Authors: Xuewen Chen, Aizhen Liang, Xiaoping Zhang

Abstract:

To better understand the spatial variability of soil penetration resistance (SPR) and soil water content (SWC) induced by different tillage and crop rotation in a Mollisol of Northeast China, the soil was sampled from the tillage experiment which was established in Dehui County, Jilin Province, Northeast China, in 2001. Effect of no-tillage (NT), moldboard plow (MP) and ridge tillage (RT) under corn-soybean rotation (C-S) and continuous corn (C-C) system on SPR and SWC were compared with horizontal and vertical variations. The results showed that SPR and SWC spatially varied across the ridge. SPR in the rows was higher than inter-rows, especially in topsoil (2.5-15 cm) of NT and RT plots. SPR of MP changed in the trend with the curve-shaped ridge. In contrast to MP, NT, and RT resulted in average increment of 166.3% and 152.3% at a depth of 2.5-17.5 cm in the row positions, respectively. The mean SPR in topsoil in the rows means soil compaction is not the main factor limiting plant growth and crop yield. SPR in the row of RT soil was lower than NT at a depth of 2.5-12.5 cm. The SWC in NT and RT soil was highest in the inter-rows and least in the rows or shoulders, respectively. However, the lateral variation trend of MP was opposite to NT. From the profile view of SWC, MP was greater than NT and RT in 0-20 cm of the rows. SWC in RT soil was higher than NT in the row of 0-20 cm. Crop rotation did not have a marked impact on SPR and SWC. In addition to the tillage practices, the factor which affects SPR greatly was depth but not position. These two factors have significant effects on SWC. These results indicated that the adoption of RT was a more suitable conservation tillage practices than NT in the black soil of Northeast China.

Keywords: row, soil penetration resistance, spatial variability, tillage practice

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10458 Wind Velocity Climate Zonation Based on Observation Data in Indonesia Using Cluster and Principal Component Analysis

Authors: I Dewa Gede Arya Putra

Abstract:

Principal Component Analysis (PCA) is a mathematical procedure that uses orthogonal transformation techniques to change a set of data with components that may be related become components that are not related to each other. This can have an impact on clustering wind speed characteristics in Indonesia. This study uses data daily wind speed observations of the Site Meteorological Station network for 30 years. Multicollinearity tests were also performed on all of these data before doing clustering with PCA. The results show that the four main components have a total diversity of above 80% which will be used for clusters. Division of clusters using Ward's method obtained 3 types of clusters. Cluster 1 covers the central part of Sumatra Island, northern Kalimantan, northern Sulawesi, and northern Maluku with the climatological pattern of wind speed that does not have an annual cycle and a weak speed throughout the year with a low-speed ranging from 0 to 1,5 m/s². Cluster 2 covers the northern part of Sumatra Island, South Sulawesi, Bali, northern Papua with the climatological pattern conditions of wind speed that have annual cycle variations with low speeds ranging from 1 to 3 m/s². Cluster 3 covers the eastern part of Java Island, the Southeast Nusa Islands, and the southern Maluku Islands with the climatological pattern of wind speed conditions that have annual cycle variations with high speeds ranging from 1 to 4.5 m/s².

Keywords: PCA, cluster, Ward's method, wind speed

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10457 An Analysis of Miguel Syjuco’s Ilustrado: The Reconstructed Oriental Image

Authors: Christine Ivy A. Nogot

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Under the colony of Spain for more than three centuries, the Philippines has a deep-rooted structure of Western ideologies and colonialism. The late 19th century, the period of Enlightenment, created a significant impact on our history when a group of middle-class Filipino men were sent to Europe to study. They were called Ilustrados, a Spanish word for erudite. They were the enlightened; the well-educated, intellectual scholars. Their writings provide intellectual grounds for the awakening of national consciousness that eventually prompted national movements and revolutions. They helped to establish a postcolonial society. In the modern era, Miguel Syjuco, a Filipino expatriate, wrote a novel and titled it Ilustrado. It is a representation of the liberal mind of the diasporic author in contemporary discourse. It provides a critical examination of the ilustrado in transition through the character of Miguel, who is also an expatriate writer. Using Syjuco’s award-winning novel as the primary text and anchored on Said’s concept of Orientalism, this paper examines how the depiction of features of the Eastern world is presented in the literary discourse. This paper looks into Said’s concept of orientalism as a hegemonic discursive structure and shows how Western superiority influences the Eastern culture in literary discourse. It explores Gramsci’s theory of cultural hegemony to explore Said’s argument that Western powers conquer the orient through culture and ideology. This paper presents how dominant ideologies and the social context redefine the ilustrado in the contemporary era.

Keywords: cultural hegemony, ilustrado, orientalism, postcolonial

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10456 A Method to Identify Areas for Hydraulic Fracturing by Using Production Logging Tools

Authors: Armin Shirbazo, Hamed Lamei Ramandi, Mohammad Vahab, Jalal Fahimpour

Abstract:

Hydraulic fracturing, especially multi-stage hydraulic fracturing, is a practical solution for wells with uneconomic production. The wide range of applications is appraised appropriately to have a stable well-production. Production logging tool, which is known as PLT in the oil and gas industry, is counted as one of the most reliable methods to evaluate the efficiency of fractures jobs. This tool has a number of benefits and can be used to prevent subsequent production failure. It also distinguishes different problems that occurred during well-production. In this study, the effectiveness of hydraulic fracturing jobs is examined by using the PLT in various cases and situations. The performance of hydraulically fractured wells is investigated. Then, the PLT is employed to gives more information about the properties of different layers. The PLT is also used to selecting an optimum fracturing design. The results show that one fracture and three-stage fractures behave differently. In general, the one-stage fracture should be created in high-quality areas of the reservoir to have better performance, and conversely, in three-stage fractures, low-quality areas are a better candidate for fracturing

Keywords: multi-stage fracturing, horizontal well, PLT, fracture length, number of stages

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10455 Business-Intelligence Mining of Large Decentralized Multimedia Datasets with a Distributed Multi-Agent System

Authors: Karima Qayumi, Alex Norta

Abstract:

The rapid generation of high volume and a broad variety of data from the application of new technologies pose challenges for the generation of business-intelligence. Most organizations and business owners need to extract data from multiple sources and apply analytical methods for the purposes of developing their business. Therefore, the recently decentralized data management environment is relying on a distributed computing paradigm. While data are stored in highly distributed systems, the implementation of distributed data-mining techniques is a challenge. The aim of this technique is to gather knowledge from every domain and all the datasets stemming from distributed resources. As agent technologies offer significant contributions for managing the complexity of distributed systems, we consider this for next-generation data-mining processes. To demonstrate agent-based business intelligence operations, we use agent-oriented modeling techniques to develop a new artifact for mining massive datasets.

Keywords: agent-oriented modeling (AOM), business intelligence model (BIM), distributed data mining (DDM), multi-agent system (MAS)

Procedia PDF Downloads 417
10454 Simulation-Based Parametric Study for the Hybrid Superplastic Forming of AZ31

Authors: Fatima Ghassan Al-Abtah, Naser Al-Huniti, Elsadig Mahdi

Abstract:

As the lightest constructional metal on earth, magnesium alloys offer excellent potential for weight reduction in the transportation industry, and it was observed that some magnesium alloys exhibit superior ductility and superplastic behavior at high temperatures. The main limitation of the superplastic forming (SPF) includes the low production rate since it needs a long forming time for each part. Through this study, an SPF process that starts with a mechanical pre-forming stage is developed to promote formability and reduce forming time. A two-dimensional finite element model is used to simulate the process. The forming process consists of two steps. At the pre-forming step (deep drawing), the sheet is drawn into the die to a preselected level, using a mechanical punch, and at the second step (SPF) a pressurized gas is applied at a controlled rate. It is shown that a significant reduction in forming time and improved final thickness uniformity can be achieved when the hybrid forming technique is used, where the process achieved a fully formed part at 400°C. Investigation for the impact of different forming process parameters achieved by comparing forming time and the distribution of final thickness that were obtained from the simulation analysis. Maximum thinning decreased from over 67% to less than 55% and forming time significantly decreased by more than 6 minutes, and the required gas pressure profile was predicted for optimum forming process parameters based on the 0.001/sec target constant strain rate within the sheet.

Keywords: magnesium, plasticity, superplastic forming, finite element analysis

Procedia PDF Downloads 143
10453 Development of Fault Diagnosis Technology for Power System Based on Smart Meter

Authors: Chih-Chieh Yang, Chung-Neng Huang

Abstract:

In power system, how to improve the fault diagnosis technology of transmission line has always been the primary goal of power grid operators. In recent years, due to the rise of green energy, the addition of all kinds of distributed power also has an impact on the stability of the power system. Because the smart meters are with the function of data recording and bidirectional transmission, the adaptive Fuzzy Neural inference system, ANFIS, as well as the artificial intelligence that has the characteristics of learning and estimation in artificial intelligence. For transmission network, in order to avoid misjudgment of the fault type and location due to the input of these unstable power sources, combined with the above advantages of smart meter and ANFIS, a method for identifying fault types and location of faults is proposed in this study. In ANFIS training, the bus voltage and current information collected by smart meters can be trained through the ANFIS tool in MATLAB to generate fault codes to identify different types of faults and the location of faults. In addition, due to the uncertainty of distributed generation, a wind power system is added to the transmission network to verify the diagnosis correctness of the study. Simulation results show that the method proposed in this study can correctly identify the fault type and location of fault with more efficiency, and can deal with the interference caused by the addition of unstable power sources.

Keywords: ANFIS, fault diagnosis, power system, smart meter

Procedia PDF Downloads 127
10452 What the Future Holds for Social Media Data Analysis

Authors: P. Wlodarczak, J. Soar, M. Ally

Abstract:

The dramatic rise in the use of Social Media (SM) platforms such as Facebook and Twitter provide access to an unprecedented amount of user data. Users may post reviews on products and services they bought, write about their interests, share ideas or give their opinions and views on political issues. There is a growing interest in the analysis of SM data from organisations for detecting new trends, obtaining user opinions on their products and services or finding out about their online reputations. A recent research trend in SM analysis is making predictions based on sentiment analysis of SM. Often indicators of historic SM data are represented as time series and correlated with a variety of real world phenomena like the outcome of elections, the development of financial indicators, box office revenue and disease outbreaks. This paper examines the current state of research in the area of SM mining and predictive analysis and gives an overview of the analysis methods using opinion mining and machine learning techniques.

Keywords: social media, text mining, knowledge discovery, predictive analysis, machine learning

Procedia PDF Downloads 414
10451 Agriculture Water Quality Evaluation in Minig Basin

Authors: Ben Salah Nahla

Abstract:

The problem of water in Tunisia affects the quality and quantity. Tunisia is in a situation of water shortage. It was estimated that 4.6 Mm3/an. Moreover, the quality of water in Tunisia is also mediocre. In fact, 50% of the water has a high salinity (> 1.5g/l). There are several parameters which affect water quality such as sodium, fluoride. An excess of this parameter may induce some human health. Furthermore, the mining basin area has a problem of industrial waste. This problem may affect the water quality of the groundwater. Therefore, the purpose of this work is to assess the water quality in Basin Mining and the impact of fluorine. For this research, some water samples were done in the field and specific water analysis was implemented in the laboratory. Sampling is carried out on eight drilling in the area of the mining region. In the following, we will look at water view composition, physical and chemical quality. A physical-chemical analysis of water from a survey of the Mining area of Tunisia was performed and showed an excess for the following items: fluorine, sodium, sulfate. So many chemicals may be present in water. However, only a small number of them immediately concern in terms of health in all circumstances. Fluorine (F) is one particular chemical that is considered both necessary for the human body, but an excess of the rate of this chemical causes serious diseases. Sodium fluoride and sodium silicofluoride are more soluble and may spread in animals and plants where their toxicity largest organizations. The more complex particles such as cryolite and fluorite, almost insoluble, are more stable and less toxic. Thereafter, we will study the problem of excess fluorine in the water. The latter intended for human consumption must always comply with the limits for microbiological quality parameters and physical-chemical parameters defined by European standards (1.5 mg/l) and Tunisian (2 mg/l).

Keywords: water, minier basin, fluorine, silicofluoride

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10450 Improving Second Language Speaking Skills via Video Exchange

Authors: Nami Takase

Abstract:

Computer-mediated-communication allows people to connect and interact with each other as if they were sharing the same space. The current study examined the effects of using video letters (VLs) on the development of second language speaking skills of Common European Framework of Reference for Languages (CEFR) A1 and CEFR B2 level learners of English as a foreign language. Two groups were formed to measure the impact of VLs. The experimental and control groups were given the same topic, and both groups worked with a native English-speaking university student from the United States of America. Students in the experimental group exchanged VLs, and students in the control group used video conferencing. Pre- and post-tests were conducted to examine the effects of each practice mode. The transcribed speech-text data showed that the VL group had improved speech accuracy scores, while the video conferencing group had increased sentence complexity scores. The use of VLs may be more effective for beginner-level learners because they are able to notice their own errors and replay videos to better understand the native speaker’s speech at their own pace. Both the VL and video conferencing groups provided positive feedback regarding their interactions with native speakers. The results showed how different types of computer-mediated communication impacts different areas of language learning and speaking practice and how each of these types of online communication tool is suited to different teaching objectives.

Keywords: computer-assisted-language-learning, computer-mediated-communication, english as a foreign language, speaking

Procedia PDF Downloads 88
10449 Impact of Air Pollution and Climate on the Incidence of Emergency Interventions in Slavonski Brod

Authors: Renata Josipovic, Ante Cvitkovic

Abstract:

Particulate matter belongs to pollutants that can lead to respiratory problems or premature death due to exposure (long-term, short-term) to these substances, all depending on the severity of the effects. The importance of the study is to determine whether the existing climatic conditions in the period from January 1st to August 31st, 2018 increased the number of emergency interventions in Slavonski Brod with regard to pollutants hydrogen sulfide and particles less than 10 µm (PM10) and less than 2.5 µm (PM2.5). Analytical data of the concentration of pollutants are collected from the Croatian Meteorological and Hydrological Service, which monitors the operation of two meteorological stations in Slavonski Brod, as well as climatic conditions. Statistics data of emergency interventions were collected from the Emergency Medicine Department of Slavonski Brod. All data were compared (air pollution, emergency interventions) according to climatic conditions (air humidity and air temperature) and statistically processed. Statistical significance, although weak positive correlation PM2.5 (correlation coefficient 0.147; p = 0.036), determined PM10 (correlation coefficient 0.122; p = 0.048), hydrogen sulfide (correlation coefficient 0.141; p = 0.035) with max. temperature (correlation coefficient 0.202; p = 0.002) with number of interventions. The association between mean air humidity was significant but negative (correlation coefficient - 0.172; p = 0.007). The values of the influence of air pressure are not determined. As the problem of air pollution is very complex, coordinated action at many levels is needed to reduce air pollution in Slavonski Brod and consequences that can affect human health.

Keywords: emergency interventions, human health, hydrogen sulfide, particulate matter

Procedia PDF Downloads 151
10448 Measuring the Embodied Energy of Construction Materials and Their Associated Cost Through Building Information Modelling

Authors: Ahmad Odeh, Ahmad Jrade

Abstract:

Energy assessment is an evidently significant factor when evaluating the sustainability of structures especially at the early design stage. Today design practices revolve around the selection of material that reduces the operational energy and yet meets their displinary need. Operational energy represents a substantial part of the building lifecycle energy usage but the fact remains that embodied energy is an important aspect unaccounted for in the carbon footprint. At the moment, little or no consideration is given to embodied energy mainly due to the complexity of calculation and the various factors involved. The equipment used, the fuel needed, and electricity required for each material vary with location and thus the embodied energy will differ for each project. Moreover, the method and the technique used in manufacturing, transporting and putting in place will have a significant influence on the materials’ embodied energy. This anomaly has made it difficult to calculate or even bench mark the usage of such energies. This paper presents a model aimed at helping designers select the construction materials based on their embodied energy. Moreover, this paper presents a systematic approach that uses an efficient method of calculation and ultimately provides new insight into construction material selection. The model is developed in a BIM environment targeting the quantification of embodied energy for construction materials through the three main stages of their life: manufacturing, transportation and placement. The model contains three major databases each of which contains a set of the most commonly used construction materials. The first dataset holds information about the energy required to manufacture any type of materials, the second includes information about the energy required for transporting the materials while the third stores information about the energy required by tools and cranes needed to place an item in its intended location. The model provides designers with sets of all available construction materials and their associated embodied energies to use for the selection during the design process. Through geospatial data and dimensional material analysis, the model will also be able to automatically calculate the distance between the factories and the construction site. To remain within the sustainability criteria set by LEED, a final database is created and used to calculate the overall construction cost based on R.M.S. means cost data and then automatically recalculate the costs for any modifications. Design criteria including both operational and embodied energies will cause designers to revaluate the current material selection for cost, energy, and most importantly sustainability.

Keywords: building information modelling, energy, life cycle analysis, sustainablity

Procedia PDF Downloads 259
10447 Family Firms and Investment–Cash Flow Sensitivity: Empirical Evidence from Canada

Authors: Imen Latrous

Abstract:

Family firm is the most common form of business organization in the world. Many family businesses rely heavily on their own capital to finance their expansion. This dependence on internal funds for their investment may be deliberate to maintain the family dominant position or involuntary as family firms have limited access to external funds. Our understanding of family firm’s choice to fund their own growth using existing capital is somewhat limited. The aim of this paper is to study whether the presence of a controlling family in the company either mitigates or exacerbates external financing constraints. The impact of family ownership on investment–cash flow sensitivity is ultimately an empirical question. We use a sample of 406 Canadian firms listed in Toronto Stock exchange (TSX) over the period 2005–2014 in order to explore this relationship. We distinguish between three elements in the definition of family firms, specifically ownership, control and management, to explore the issue whether family firms are more efficient organisational form. Our research contributes to the extant literature on family ownership in several ways. First, as our understanding of family firm’s investment cash flow sensitivity is somewhat limited in recession times, we explore the effect of family firms on the relation between investment and cash flow during the recent 2007-2009 financial crisis. We also analyse this relationship difference between family firms and non family firms before and during financial crisis. Finally, our paper addresses the endogeneity problem of family ownership and investment-cash flow sensitivity.

Keywords: family firms, investment–cash flow sensitivity, financial crisis, corporate governance

Procedia PDF Downloads 315
10446 Development of Tensile Stress-Strain Relationship for High-Strength Steel Fiber Reinforced Concrete

Authors: H. A. Alguhi, W. A. Elsaigh

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This paper provides a tensile stress-strain (σ-ε) relationship for High-Strength Steel Fiber Reinforced Concrete (HSFRC). Load-deflection (P-δ) behavior of HSFRC beams tested under four-point flexural load were used with inverse analysis to calculate the tensile σ-ε relationship for various tested concrete grades (70 and 90MPa) containing 60 kg/m3 (0.76 %) of hook-end steel fibers. A first estimate of the tensile (σ-ε) relationship is obtained using RILEM TC 162-TDF and other methods available in literature, frequently used for determining tensile σ-ε relationship of Normal-Strength Concrete (NSC) Non-Linear Finite Element Analysis (NLFEA) package ABAQUS® is used to model the beam’s P-δ behavior. The results have shown that an element-size dependent tensile σ-ε relationship for HSFRC can be successfully generated and adopted for further analyzes involving HSFRC structures.

Keywords: tensile stress-strain, flexural response, high strength concrete, steel fibers, non-linear finite element analysis

Procedia PDF Downloads 350