Search results for: human machine interface

Authors: Yi-Shuan ShaoShao, Yen-An Tsai, Chia-Huang Chang, Kai-Wei Liao, Ming-Song Tsai, Mei-Lien Chen

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Organophosphate pesticides (OPs) is an environmental hormone with proven endocrine-disrupting effects that may affect the growth and development in human. A large amount of organophosphate pesticides (OPs) is used throughout Taiwan, and human may be exposed through dietary intake or residential use. During pregnancy, OPs can be transferred to the blood stream reaching the fetus through the placenta. The aim of this study was to explore the association between maternal OPs exposure levels and fetal developments and birth outcomes. A birth cohort was follow-up. Maternal urine sample were collected at the first, second, and third gestational trimester. Fetal growth characteristics were measured by ultrasonic scan and birth outcomes were assessed by pediatrician. Urinary metabolite of organophosphate pesticides were assessed using gas chromatography-mass spectrometry. The analytes included dimethylphosphate (DMP), dimethylthiophosphate (DMTP), dimethyldithiophosphates (DMDTP), diethylphosphate (DEP), diethylthiophosphate (DETP), and diethyldithiophosphate (DEDTP). We found that all of urine samples in each trimester were detected at least one metabolite for dialkyl phosphate (DAP). The detection rate range of OP urinary metabolites were from the lowest 22% DEDTP to the highest 100% DMP and DMTP. And to compared geometric means (GM) of urinary metabolites with three trimesters, that third trimester had the highest concentration for DMPs, DEPs, and DAPs in pregnant women were 368.01, 169.85 and 543.75 nmol/g creatinine, respectively. We observed that DAPs concentration in first and second trimester were significantly negative association with head circumference. DMPs in first trimester was significantly negative association with thoracic circumference (p=0.05) by spearman correlation. Our results support associations with prenatal OPs exposure with fetal head circumference and thoracic circumference. It provided that maternal OPs exposure might affect birth outcomes. Thus, prenatal exposure to OPs and health risk worthy of attention and concern.

Keywords: DAPs, birth outcomes, organophosphate pesticides, prenatal

Procedia PDF Downloads 328

Authors: Shreya Pare, Parvin Akhter

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Remotely sensing image classification becomes a very challenging task owing to the high dimensionality of hyperspectral images. The pixel-wise classification methods fail to take the spatial structure information of an image. Therefore, to improve the performance of classification, spatial information can be integrated into the classification process. In this paper, the multilevel thresholding algorithm based on a modified fuzzy entropy function is used to perform the segmentation of hyperspectral images. The fuzzy parameters of the MFE function have been optimized by using a new meta-heuristic algorithm based on the Tree-Search algorithm. The segmented image is classified by a large distribution machine (LDM) classifier. Experimental results are shown on a hyperspectral image dataset. The experimental outputs indicate that the proposed technique (MFE-TSA-LDM) achieves much higher classification accuracy for hyperspectral images when compared to state-of-art classification techniques. The proposed algorithm provides accurate segmentation and classification maps, thus becoming more suitable for image classification with large spatial structures.

Keywords: classification, hyperspectral images, large distribution margin, modified fuzzy entropy function, multilevel thresholding, tree search algorithm, hyperspectral image classification using tree search algorithm

Procedia PDF Downloads 157

Authors: K. Rattawan, W. Intagun, W. Kanoksilapatham

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Objective of this research is to study effect of coffee grounds on physical and heating value properties of sugarcane bagasse pellets. The coffee grounds were tested as an additive for pelletizing process of bagasse pellets. Pelletizing was performed using a Flat–die pellet mill machine. Moisture content of raw materials was controlled at 10-13%. Die temperature range during the process was 75-80 ^oC. Physical characteristics (bulk density and durability) of the bagasse pellet and pellets with 1-5% coffee ground were determined following the standard assigned by the Pellet Fuel Institute (PFI). The results revealed increasing values of 648±3.4, 659 ± 3.1, 679 ± 3.3 and 685 ± 3.1 kg/m³ (for pellet bulk density); and 98.7 ± 0.11, 99.2 ± 0.26, 99.3 ± 0.19 and 99.4 ± 0.07% (for pellet durability), respectively. In addition, the heating values of the coffee ground supplemented pellets (15.9 ± 1.16, 17.0 ± 1.23 and 18.8 ± 1.34 MJ/kg) were improved comparing to the non-supplemented control (14.9 ± 1.14 MJ/kg), respectively. The results indicated that both the bulk density and durability values of the bagasse pellets were increased with the increasing proportion of the coffee ground additive.

Keywords: bagasse, coffee grounds, pelletizing, heating value, sugar cane bagasse

Procedia PDF Downloads 151

Authors: Despoina Andrioti Bygvraa, Ida-Maja Hassellöv, George Charalambous

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Exhaust gas cleaning systems, also known as scrubbers, are today widely used to allow for the use of High Sulphur Heavy Fuel Oil and still comply with the regulations limiting sulphur content in marine fuels. There are extensive concerns about environmental consequences, especially in the Baltic Sea, from the wide-scale use of scrubbers, as the wash water is acidic (ca pH 3) and contains high concentrations of toxic, carcinogenic, and mutagenic substances. The aim of this feasibility study is to investigate the potential adverse effects on seafarers’ health with the ultimate goal of raising awareness of chemical-related health and safety issues in the shipping environment. The project got funding from the Swedish Foundation. The team will extend previously compiled data on scrubber wash water concentrations of hazardous substances and pH to include the use of strong base in closed-loop scrubbers, and scoping assessment on handling and disposing practices. Based on the findings (a), a systematic review of risk assessment will follow to show the risk of exposures, the establishment of the hazardous levels for human health as well as the respective prevention practices. In addition, the researchers will perform (b) a systematic review to identify facilitators and barriers of the crew on compliance with the safe handling of chemicals. The study will run for 12 months, delivering (a) a risk assessment inventory with risk exposures and (b) a course description of safe handling practices. This feasibility study could provide valuable knowledge on how pollutants found in scrubbers should be considered from a human health perspective to facilitate evidence-based informed decisions in future technology- and policy development to make shipping a safer, healthier, and more attractive workplace.

Keywords: health and safety, seafarers, scrubbers, chemicals, risk exposures

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Authors: Abu Salim Mustafa

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Brucellosis is a zoonotic disease endemic in Kuwait. Human brucellosis can be caused by several Brucella species with Brucella melitensis causing the most severe and Brucella abortus the least severe disease. Furthermore, relapses are common after successful chemotherapy of patients. The classical biochemical methods of culture and serology for identification of Brucellae provide information about the species and serotypes only. However, to differentiate between relapse and reinfection/epidemiological investigations, the identification of genotypes using molecular methods is essential. In this study, four molecular methods [16S rRNA gene sequencing, real-time PCR, enterobacterial repetitive intergenic consensus (ERIC)-PCR and multilocus variable-number tandem-repeat analysis (MLVA)-16] were evaluated for the identification and typing of 75 strains of Brucella isolated in Kuwait. The 16S rRNA gene sequencing suggested that all the strains were B. melitensis and real-time PCR confirmed their species identity as B. melitensis. The ERIC-PCR band profiles produced a dendrogram of 75 branches suggesting each strain to be of a unique type. The cluster classification, based on ~ 80% similarity, divided all the ERIC genotypes into two clusters, A and B. Cluster A consisted of 9 ERIC genotypes (A1-A9) corresponding to 9 individual strains. Cluster B comprised of 13 ERIC genotypes (B1-B13) with B5 forming the largest cluster of 51 strains. MLVA-16 identified all isolates as B. melitensis and divided them into 71 MLVA-types. The cluster analysis of MLVA-16-types suggested that most of the strains in Kuwait originated from the East Mediterranean Region, a few from the African group and one new genotype closely matched with the West Mediterranean region. In conclusion, this work demonstrates that B. melitensis, the most pathogenic species of Brucella, is prevalent in Kuwait. Furthermore, MLVA-16 is the best molecular method, which can identify the Brucella species and genotypes as well as determine their origin in the global context. Supported by Kuwait University Research Sector grants MI04/15 and SRUL02/13.

Keywords: Brucella, ERIC-PCR, MLVA-16, RT-PCR, 16S rRNA gene sequencing

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Authors: Akanksha Lohmore, Devanshu Arya, Preeti Kapur

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Rarely does the human mind look at the positive fallout of highly negative events. Positive psychology attempts to emphasize on the strengths and positives for human well-being. The present study examines the underpinning socio-cognitive factors of the protest movements regarding the gang rape case of December 16th, 2012 through the lens of positive psychology. A gamut of negative emotions came to the forum globally: of anger, shame, hatred, violence, death penalty for the perpetrators, amongst other equally strong. In relation to this incident, a number of questions can be raised. Can such a heinous crime have some positive inputs for contemporary society? What is it that has held people to protests for long even when they see faded lines of success in view? This paper explains the constant feeding of protests and continuation of movements by the robust model of Collective Hope by Snyder, a phenomenon unexplored by social psychologists. In this paper, mixed method approach was undertaken. Results confirmed the interaction of various socio-psychological factors that imitated the Snyders model of collective hope. Emergence of major themes was: Sense of Agency, Sense of Worthiness, Social Sharing and Common Grievances and Hope of Collective Efficacy. Statistical analysis (correlation and regression) showed significant relationship between media usage and occurrence of these themes among participants. Media-communication processes and educational theories for development of citizenship behavior can find implications from these results. Theory development as indicated by theorists working in the area of Social Psychology of Protests can be furthered by the direction of research.

Keywords: agency, collective, hope, positive psychology, protest, social media

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Authors: M. Al-Farttoosi, M. Y. Rafiq, J. Summerscales, C. Williams

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Many buildings and bridges are damaged due to impact loading, explosions, terrorist attacks and wars. Most of the damaged structures members such as beams, columns and slabs are not totally failed and it can be repaired. Nowadays, carbon fibre reinforced polymer CFRP has been wildly used in strengthening and retrofitting the structures members. CFRP can rector the load carrying capacity of the damaged structures members to make them serviceable. An experimental investigation was conducted to investigate the impact behaviour of the damaged beams repaired with CFRP. The tested beams had different degrees of damage and near surface mounted technique NSM was used to install the CFRP. A heavy drop weight impact test machine was used to conduct the experimental work. The study investigated the impact strength, stiffness, cracks and deflection of the CFRP repaired beams. The results show that CFRP significantly increased the impact resistance of the damaged beams. CFRP increased the damaged beams stiffness and reduced the deflection. The results showed that the NSM technique is more effective in repairing beams and preventing the debonding of the CFRP.

Keywords: damaged, concrete, impact, repaired

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Authors: Samson Abayomi Olasoju, Olufemi Adekunle, Titilope Edun, Johnson Owoseni

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Science offers opportunities for revolutionizing human activities, enriched by input from scientific research and technology. Biotechnology is a major force for development in developing countries such as Nigeria. It is found to contribute to solving human problems like water and food insecurity that impede national development and threaten peace wherever it is applied. This review identified the problems of agricultural biotechnology in Nigeria. On the part of rural farmers, there is a lack of adequate knowledge or awareness of biotechnology despite the fact that they constitute the bulk of Nigerian farmers. On part of the government, the problems include: lack of adequate implementation of government policy on bio-safety and genetically modified products, inadequate funding of education as well as research and development of products related to biotechnology. Other problems include: inadequate infrastructures (including laboratory), poor funding and lack of national strategies needed for development and running of agricultural biotechnology. In spite of all the challenges associated with agricultural biotechnology, its prospects still remain great if Nigeria is to meet with the food needs of the country’s ever increasing population. The introduction of genetically engineered products will lead to the high productivity needed for commercialization and food security. Insect, virus and other related diseases resistant crops and livestock are another viable area of contribution of biotechnology to agricultural production. In conclusion, agricultural biotechnology will not only ensure food security, but, in addition, will ensure that the local farmers utilize appropriate technology needed for large production, leading to the prosperity of the farmers and national economic growth, provided government plays its role of adequate funding and good policy implementation.

Keywords: biosafety, biotechnology, food security, genetic engineering, genetic modification

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Authors: Brian M. Mehling, Louis Quartararo, Marine Manvelyan, Paul Wang, Dong-Cheng Wu

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Numerous investigations suggest that Mesenchymal Stem Cells (MSCs) in general represent a valuable tool for therapy of symptoms related to chronic inflammatory diseases. Blue Horizon Stem Cell Therapy Program is a leading provider of adult and children’s stem cell therapies. Uniquely we have safely and efficiently treated more than 600 patients with documenting each procedure. The purpose of our study is primarily to monitor the immune response in order to validate the safety of intravenous infusion of human umbilical cord blood derived MSCs (UC-MSCs), and secondly, to evaluate effects on biomarkers associated with chronic inflammation. Nine patients were treated for conditions associated with chronic inflammation and for the purpose of anti-aging. They have been given one intravenous infusion of UC-MSCs. Our study of blood test markers of 9 patients with chronic inflammation before and within three months after MSCs treatment demonstrates that there is no significant changes and MSCs treatment was safe for the patients. Analysis of different indicators of chronic inflammation and aging included in initial, 24-hours, two weeks and three months protocols showed that stem cell treatment was safe for the patients; there were no adverse reactions. Moreover data from follow up protocols demonstrates significant improvement in energy level, hair, nails growth and skin conditions. Intravenously administered UC-MSCs were safe and effective in the improvement of symptoms related to chronic inflammation. Further close monitoring and inclusion of more patients are necessary to fully characterize the advantages of UC-MSCs application in treatment of symptoms related to chronic inflammation.

Keywords: chronic inflammatory diseases, intravenous infusion, stem cell therapy, umbilical cord blood derived mesenchymal stem cells (UC-MSCs)

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Authors: Ramita Vongrat, Pornsri Sapsrithong, Manit Nithitanakul

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In this work, blends of polyamide 6 (PA6) and polybutylene terephthalate (PBT) were successfully prepared. The effect of epoxidized natural rubber (ENR-25) and n butyl acrylate glycidyl methacrylate ethylene (EBa-GMA) as a compatibilizer on properties of PA6/PBT blends was also investigated by varying amount of ENR-50 and EBa-GMA, i.e., 0, 0.1, 0.5, 5 and 10 phr. All blends were prepared and shaped by using twin-screw extruder at 230 °C and injection molding machine, respectively. All test specimens were characterized by phase morphology, impact strength, tensile, flexural properties, and hardness. The results exhibited that phase morphology of PA6/PBT blend without compatibilizer was incompatible. This could be attributed to poor interfacial adhesion between the two polymers. SEM micrographs showed that the addition of ENR-25 and EBa-GMA improved the compatibility of PA6/PBT blends. With the addition of ENR-50 as a compatibilizer, the uniformity and the maximum reduction of dispersed phase size were observed. Additionally, the results indicate that, as the amount of ENR-25 increased, and EBa-GMA increased, the mechanical properties, including stress at the peak, tensile modulus, and izod impact strength, were also improved.

Keywords: EBa-GMA, epoxidized natural rubber-25, polyamide 6, polybutylene terephthalate

Procedia PDF Downloads 157

Authors: Reza Mohammadi, Mahmod R. Sahebi, Mehrnoosh Omati, Milad Vahidi

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Classification of high resolution polarimetric Synthetic Aperture Radar (PolSAR) images plays an important role in land cover and land use management. Recently, classification algorithms based on Bag of Visual Words (BOVW) model have attracted significant interest among scholars and researchers in and out of the field of remote sensing. In this paper, BOVW model with pixel based low-level features has been implemented to classify a subset of San Francisco bay PolSAR image, acquired by RADARSAR 2 in C-band. We have used segment-based decision-making strategy and compared the result with the result of traditional Support Vector Machine (SVM) classifier. 90.95% overall accuracy of the classification with the proposed algorithm has shown that the proposed algorithm is comparable with the state-of-the-art methods. In addition to increase in the classification accuracy, the proposed method has decreased undesirable speckle effect of SAR images.

Keywords: Bag of Visual Words (BOVW), classification, feature extraction, land cover management, Polarimetric Synthetic Aperture Radar (PolSAR)

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Authors: Pakize Ozlem Kurt Polat

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GMO (genetically modified organism) is the result of a laboratory process where genes from the DNA of one species are extracted and artificially forced into the genes of an unrelated plant or animal. This technology includes; nucleic acid hybridization, recombinant DNA, RNA, PCR, cell culture and gene cloning techniques. The studies are divided into three groups of properties transferred to the transgenic plant. Up to 59% herbicide resistance characteristic of the transfer, 28% resistance to insects and the virus seems to be related to quality characteristics of 13%. Transgenic crops are not included in the commercial production of each product; mostly commercial plant is soybean, maize, canola, and cotton. Day by day increasing GMO interest can be listed as follows; Use in the health area (Organ transplantation, gene therapy, vaccines and drug), Use in the industrial area (vitamins, monoclonal antibodies, vaccines, anti-cancer compounds, anti -oxidants, plastics, fibers, polyethers, human blood proteins, and are used to produce carotenoids, emulsifiers, sweeteners, enzymes , food preservatives structure is used as a flavor enhancer or color changer),Use in agriculture (Herbicide resistance, Resistance to insects, Viruses, bacteria, fungi resistance to disease, Extend shelf life, Improving quality, Drought , salinity, resistance to extreme conditions such as frost, Improve the nutritional value and quality), we explain all this methods step by step in this research. GMO has advantages and disadvantages, which we explain all of them clearly in full text, because of this topic, worldwide researchers have divided into two. Some researchers thought that the GMO has lots of disadvantages and not to be in use, some of the researchers has opposite thought. If we look the countries law about GMO, we should know Biosafety law for each country and union. For this Biosecurity reasons, the problems caused by the transgenic plants, including Turkey, to minimize 130 countries on 24 May 2000, ‘the United Nations Biosafety Protocol’ signed nudes. This protocol has been prepared in addition to Cartagena Biosafety Protocol entered into force on September 11, 2003. This protocol GMOs in general use by addressing the risks to human health, biodiversity and sustainable transboundary movement of all GMOs that may affect the prevention, transit covers were dealt and used. Under this protocol we have to know the, ‘US Regulations GMO’, ‘European Union Regulations GMO’, ‘Turkey Regulations GMO’. These three different protocols have different applications and rules. World population increasing day by day and agricultural fields getting smaller for this reason feeding human and animal we should improve agricultural product yield and quality. Scientists trying to solve this problem and one solution way is molecular biotechnology which is including the methods of GMO too. Before decide to support or against the GMO, should know the GMO protocols and it effects.

Keywords: biotechnology, GMO (genetically modified organism), molecular marker

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Authors: Meftah O. Bashir, Fatma A. Karkory

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Rapid prototyping is a new group of manufacturing processes, which allows fabrication of physical of any complexity using a layer by layer deposition technique directly from a computer system. The rapid prototyping process greatly reduces the time and cost necessary to bring a new product to market. The prototypes made by these systems are used in a range of industrial application including design evaluation, verification, testing, and as patterns for casting processes. These processes employ a variety of materials and mechanisms to build up the layers to build the part. The present work was to build a FDM prototyping machine that could control the X-Y motion and material deposition, to generate two-dimensional and three-dimensional complex shapes. This study focused on the deposition of wax material. This work was to find out the properties of the wax materials used in this work in order to enable better control of the FDM process. This study will look at the integration of a computer controlled electro-mechanical system with the traditional FDM additive prototyping process. The characteristics of the wax were also analysed in order to optimize the model production process. These included wax phase change temperature, wax viscosity and wax droplet shape during processing.

Keywords: rapid prototyping, wax, manufacturing processes, shape

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Authors: H. J. Kim, K. H. Kim, N. H. Park, K. T. Nam, Y. H. Jung, T. H. Kim, J. H. Shin

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Underground excavations in an urban area can cause various geotechnical problems such as ground loss and lowering of groundwater level. When the ground loss becomes uncontrollably large, sinkholes can be developed to the ground surface. A sinkhole is commonly known as the natural phenomenon associated with lime rock areas. However, sinkholes in urban areas due to pressurized sewers and/or tunneling are also frequently reported. In this study, mechanism of a sinkhole developed at the site ‘A’ where a tunneling work underwent is investigated. The sinkhole occurred in the sand strata with the high level of groundwater when excavating a tunnel of which diameter is 3.6 m. The sinkhole was progressed in two steps. The first step began with the local failure around the tunnel face followed by tons of groundwater inflow, and the second step was triggered by the TBM (Tunnel Boring Machine) chamber opening which led to the progressive general failure. The possibility of the sinkhole was evaluated by using Limit Equilibrium Method (LEM), and critical height was evaluated by the empirical stability chart. It is found that the lowering of the face pressure and inflow of groundwater into the tunnel face turned to be the main reason for the sinkhole.

Keywords: limit equilibrium method, sinkhole, stability chart, tunneling

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Authors: Seyyed Mohammad Amin Mousavi Sagharchi, Elham Javanroudi

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Introduction: Tuberculosis (TB) is a known disease with hidden features caused by Mycobacterium tuberculosis (MTB). This disease, which is one of the 10 deadliest in the world, has caused millions of deaths in recent decades. Furthermore, TB is responsible for infecting about 30% population of world. Like any infection, TB can activate the immune system by locating and colonization in the human body, especially in the alveoli. TB is granulomatosis, so MTB can absorb the host’s immune cells and other cells to form granuloma. Method: Different databases (e.g., PubMed) were recruited to prepare this paper and fulfill our goals to search and find effective papers and investigations. Results: Immune response to MTB is related to T cell killers and contains CD1, CD4, and CD8 T lymphocytes. CD1 lymphocytes can recognize glycolipids, which highly exist in the Mycobacterial fatty cell wall. CD4 lymphocytes and macrophages form granuloma, and it is the main line of immune response to Mycobacteria. On the other hand, CD8 cells have cytolytic function for directly killing MTB by secretion of granulysin. Other functions and secretion to the deal are interleukin-12 (IL-12) by induction of expression interferon-γ (INF-γ) for macrophages activation and creating a granuloma, and tumor necrosis factor (TNF) by promoting macrophage phagolysosomal fusion. Conclusion: Immune cells in battle with MTB are macrophages, dendritic cells (DCs), neutrophils, and natural killer (NK) cells. These immune cells can recognize the Mycobacterium by various receptors, including Toll-like receptors (TLRs), Nod-like receptors (NLRs), and C-type lectin receptors (CLRs) located in the cell surface. In human alveoli exist about 50 dendritic macrophages, which have close communication with other immune cells in the circulating system and epithelial cells to deal with Mycobacteria. Against immune cells, MTB handles some factors (e.g., cordfactor, O-Ag, lipoarabinomannan, sulfatides, and adenylate cyclase) and practical functions (e.g., inhibition of macrophages).

Keywords: mycobacterium tuberculosis, immune responses, immunological mechanisms, respiratory tuberculosis

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Authors: Belayneh Matebie, Michael Melese

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The study focuses on addressing the challenges in classifying and ensuring the quality of Eragrostis Teff, a small and round grain that is the smallest cereal grain. Employing a traditional classification method is challenging because of its small size and the similarity of its environmental characteristics. To overcome this, this study employs a machine learning approach to develop a source and quality classification system for Teff cereal. Data is collected from various production areas in the Amhara regions, considering two types of cereal (high and low quality) across eight classes. A total of 5,920 images are collected, with 740 images for each class. Image enhancement techniques, including scaling, data augmentation, histogram equalization, and noise removal, are applied to preprocess the data. Convolutional Neural Network (CNN) is then used to extract relevant features and reduce dimensionality. The dataset is split into 80% for training and 20% for testing. Different classifiers, including FVGG16, FINCV3, QSCTC, EMQSCTC, SVM, and RF, are employed for classification, achieving accuracy rates ranging from 86.91% to 97.72%. The ensemble of FVGG16, FINCV3, and QSCTC using the Max-Voting approach outperforms individual algorithms.

Keywords: Teff, ensemble learning, max-voting, CNN, SVM, RF

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Authors: Noureddine Mohtaram, Jeremy Patrix, Jerome Verny

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As an enormous number of online services have been developed into web applications, security problems based on web applications are becoming more serious now. Most intrusion detection systems rely on each request to find the cyber-attack rather than on user behavior, and these systems can only protect web applications against known vulnerabilities rather than certain zero-day attacks. In order to detect new attacks, we analyze the HTTP protocols of web servers to divide them into two categories: normal attacks and malicious attacks. On the other hand, the quality of the results obtained by deep learning (DL) in various areas of big data has given an important motivation to apply it to cybersecurity. Deep learning for attack detection in cybersecurity has the potential to be a robust tool from small transformations to new attacks due to its capability to extract more high-level features. This research aims to take a new approach, deep learning to cybersecurity, to classify these two categories to eliminate attacks and protect web servers of the defense sector which encounters different web traffic compared to other sectors (such as e-commerce, web app, etc.). The result shows that by using a machine learning method, a higher accuracy rate, and a lower false alarm detection rate can be achieved.

Keywords: anomaly detection, HTTP protocol, logs, cyber attack, deep learning

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Authors: Teklu Urgessa, Wookjae Maeng, Joong Seek Lee

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Application of five implementations of three data mining classification techniques was experimented for extracting important insights from tourism data. The aim was to find out the best performing algorithm among the compared ones for tourism knowledge discovery. Knowledge discovery process from data was used as a process model. 10-fold cross validation method is used for testing purpose. Various data preprocessing activities were performed to get the final dataset for model building. Classification models of the selected algorithms were built with different scenarios on the preprocessed dataset. The outperformed algorithm tourism dataset was Random Forest (76%) before applying information gain based attribute selection and J48 (C4.5) (75%) after selection of top relevant attributes to the class (target) attribute. In terms of time for model building, attribute selection improves the efficiency of all algorithms. Artificial Neural Network (multilayer perceptron) showed the highest improvement (90%). The rules extracted from the decision tree model are presented, which showed intricate, non-trivial knowledge/insight that would otherwise not be discovered by simple statistical analysis with mediocre accuracy of the machine using classification algorithms.

Keywords: classification algorithms, data mining, knowledge discovery, tourism

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Authors: Hiromi Kawasaki, Satoko Yamasaki, Mika Iwasa, Tomoko Iki, Akiko Takaki

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In basic nursing, the conditions necessary for maintaining human health -temperature, humidity, illumination, distance from others, noise, moisture, meals, and excretion- were explained. Nursing students often think of these conditions in the context of a hospital room. In order to make students think of these conditions in terms of an environment necessary for maintaining health and preventing illness for residents, in the third year of community health nursing, students learned how to assess and improve the environment -particularly via the case of shelters in the event of a disaster. The importance of environmental management has increased in 2020 as a preventive measure against COVID-19 infection. We verified the effect of the lessons, which was decided to be conducted through distance learning. Sixty third-year nursing college students consented to participate in this study. Environmental standard knowledge for conducting environmental assessment was examined before and after class, and the percentage of correct answers was compared. The χ² test was used for the test, with a 5% significance level employed. Measures were evaluated via a report submitted by the students after class. Student descriptions were analyzed both qualitatively and descriptively with respect to expected health problems and suggestions for improvement. Students have already learned about the environment in terms of basic nursing in their second year. The correct answers for external environmental values concerning interpersonal distance, illumination, noise, and room temperature (p < 0.001) increased significantly after taking the class. Humidity was registered 83.3% before class and 93.3% after class (p = 0.077). Regarding the body, the percentage of students who answered correctly was 70% or more, both before and after the class. The students’ reports included overcrowding, high humidity/high temperature, and the number of toilets as health hazards. Health disorders to be prevented were heat stroke, infectious diseases, and economy class syndrome; improvement methods were recommended for hyperventilation, stretching, hydration, and waiting at home. After the public health nursing class, the students were able to not only propose environmental management of a hospital room but also had an understanding of the environment in terms of the lives of individuals, environmental assessment, and solutions to health problems. The response rate for basic items learned in the second year was already high before and after class, and interpersonal distance and ventilation were described by students. Students were able to use what they learned in basic nursing about the standards of the human mind and body. In the external environment, the memory of specific numerical values was ambiguous. The environment of the hospital room is controlled, and interest in numerical values may decrease. Nursing staff needs to maintain and improve human health as well as hospital rooms. With COVID-19, it was thought that students would continue to not only consider this point in reference to hospital rooms but also in regard to places where people gather. Even in distance learning, students were able to learn the important issues and lessons.

Keywords: environmental assessment, evacuation center, nursing education, nursing students

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Authors: Peter Ekene Egwu

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Waste management is of critical importance in Africa for reasons related to public health, human dignity, climate resilience and environmental preservation. However, delivering waste management services requires adequate funding, which has generally been lacking in a context where the generation of waste is outpacing the development of waste management infrastructure in most cities. The sector represents a growing percentage of cities’ greenhouse gas (GHG) emissions, and some of the African cities profiled in this study are now designing waste management strategies with emission reduction in mind.

Keywords: management waste material, Africa, uses of new technology to manage waste, waste management

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Authors: Lisa Tragbar

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Since the Rio declaration, the agreement resulting from the Earth Summit in 1992, the UN member states acknowledge that peace and environmental protection are deeply linked to each other. It has also been made clear by Contemporary Peace research since the early 2000 that the lack of natural resources increases conflicts, as well as potential war conflicts (general environmental conflict thesis). I argue that peace ethics need to reconsider the role of the environment in peace ethics, from conflict prevention to peacebuilding. Sumak kawsay is a concept that offers a non-anthropocentric perspective on the subject. Several Contemporary Peace Ethicists don’t take environmental peace sufficiently into account. 1. The Peace theorist Johan Galtung famously argues that positive peace depends mostly on social, economic and political factors, as institutional structures establish peace. Galtung has a relational approach to peace, yet only between human interactors. 2. Michael Fox claims in his anti-war argument to consider nonhuman entities in conflicts. Because of their species interrelation, humans cannot decide on the fate of other species. 3. Although Mark Woods considers himself a peace ecologist, following Reichberg and Syse, and argues from a duty-based perspective towards nature, he mostly focuses on the protection of the environment during war conflicts. I want to focus on a non-anthropocentric view to argue that the environment is an entity of human concern in order to construct peace. Based on the premises that the lack of natural resources create tensions that play a significant part in international conflicts and these conflicts are potential war conflicts, I argue that a non-anthropocentric account to peace ethics is an indispensable perspective towards the recovery of these resources and therefore the reduction of war conflicts. Sumak kawsay is an approach contributing to a peaceful environment, which can play a crucial role in international peacekeeping operations. To emphasize sumak kawsay in peace ethics, it is necessary to explain what this principle includes and how it renews Contemporary Peace ethics. The indigenous philosophy of life of the Andean Quechua philosophy in Ecuador and varities from other countries from the Global South include a holistic real-world vision that contains concepts like the de-hierarchization of humans and nature as well as the reciprocity principle towards nature. Sumak kawsay represents the idea of the intrinsic value of nature and an egalitarian way of life and interconnectedness between human and nonhuman entities, which has been widely neglected in Traditional War and Peace Ethics. If sumak kawsay is transferred to peacekeeping practices, peacekeepers have restorative duties not only towards humans, but also towards nature. Resource conservation and environmental protection are the first step towards a positive peace. By recognising that healthy natural resources contribute to peacebuilding, by restoring balance through compensatory justice practices like recovery, by fostering dialogue between peacekeeping forces and by entitling ecosystems with rights natural resources and environmental conflicts are more unlikely to happen. This holistic approach pays nature sufficient attention and can contribute to a positive peace.

Keywords: environment, natural resources, peace, Sumak Kawsay

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Authors: Funmilayo Sarah Eguakun, Peter Oluremi Adesoye

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One of the major problems being faced by human society is that the global temperature is believed to be rising due to human activity that releases carbon IV oxide (CO2) to the atmosphere. Carbon IV oxide is the most important greenhouse gas influencing global warming and possible climate change. With climate change becoming alarming, reducing CO2 in our atmosphere has become a primary goal of international efforts. Forest landsare major sink and could absorb large quantities of carbon if the trees are judiciously managed. The study aims at estimating the carbon sequestration capacity of Pinus caribaea (pine)and Tectona grandis (Teak) under the prevailing environmental conditions and exploring tree growth variables that influencesthe carbon sequestration capacity in Omo Forest Reserve, Ogun State, Nigeria. Improving forest management by manipulating growth characteristics that influences carbon sequestration could be an adaptive strategy of forestry to climate change. Random sampling was used to select Temporary Sample Plots (TSPs) in the study area from where complete enumeration of growth variables was carried out within the plots. The data collected were subjected to descriptive and correlational analyses. The results showed that average carbon stored by Pine and Teak are 994.4±188.3 Kg and 1350.7±180.6 Kg respectively. The difference in carbon stored in the species is significant enough to consider choice of species relevant in climate change adaptation strategy. Tree growth variables influence the capacity of the tree to sequester carbon. Height, diameter, volume, wood density and age are positively correlated to carbon sequestration. These tree growth variables could be manipulated by the forest manager as an adaptive strategy for climate change while plantations of high wood density speciescould be relevant for management strategy to increase carbon storage.

Keywords: adaptation, carbon sequestration, climate change, growth variables, wood density

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Authors: Marwa A. A. Ragab, Hadir M. Maher, Eman I. El-Kimary

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Co-administration of methotrexate (MTX) and aspirin (ASP) can cause a pharmacokinetic interaction and a subsequent increase in blood MTX concentrations which may increase the risk of MTX toxicity. Therefore, it is important to develop a sensitive, selective, accurate and precise method for their simultaneous determination in urine. A new hybrid chemometric method has been applied to the emission response data of the two drugs. Spectrofluorimetric method for determination of MTX through measurement of its acid-degradation product, 4-amino-4-deoxy-10-methylpteroic acid (4-AMP), was developed. Moreover, the acid-catalyzed degradation reaction enables the spectrofluorimetric determination of ASP through the formation of its active metabolite salicylic acid (SA). The proposed chemometric method deals with convolution of emission data using 8-points sin xi polynomials (discrete Fourier functions) after the derivative treatment of these emission data. The first and second derivative curves (D1 & D2) were obtained first then convolution of these curves was done to obtain first and second derivative under Fourier functions curves (D1/FF) and (D2/FF). This new application was used for the resolution of the overlapped emission bands of the degradation products of both drugs to allow their simultaneous indirect determination in human urine. Not only this chemometric approach was applied to the emission data but also the obtained data were subjected to non-parametric linear regression analysis (Theil’s method). The proposed method was fully validated according to the ICH guidelines and it yielded linearity ranges as follows: 0.05-0.75 and 0.5-2.5 µg mL-1 for MTX and ASP respectively. It was found that the non-parametric method was superior over the parametric one in the simultaneous determination of MTX and ASP after the chemometric treatment of the emission spectra of their degradation products. The work combines the advantages of derivative and convolution using discrete Fourier function together with the reliability and efficacy of the non-parametric analysis of data. The achieved sensitivity along with the low values of LOD (0.01 and 0.06 µg mL-1) and LOQ (0.04 and 0.2 µg mL-1) for MTX and ASP respectively, by the second derivative under Fourier functions (D2/FF) were promising and guarantee its application for monitoring the two drugs in patients’ urine samples.

Keywords: chemometrics, emission curves, derivative, convolution, Fourier transform, human urine, non-parametric regression, Theil’s method

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Authors: Mafarja Majdi, Salwani Abdullah, Najmeh S. Jaddi

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One of the global combinatorial optimization problems in machine learning is feature selection. It concerned with removing the irrelevant, noisy, and redundant data, along with keeping the original meaning of the original data. Attribute reduction in rough set theory is an important feature selection method. Since attribute reduction is an NP-hard problem, it is necessary to investigate fast and effective approximate algorithms. In this paper, we proposed two feature selection mechanisms based on memetic algorithms (MAs) which combine the genetic algorithm with a fuzzy record to record travel algorithm and a fuzzy controlled great deluge algorithm to identify a good balance between local search and genetic search. In order to verify the proposed approaches, numerical experiments are carried out on thirteen datasets. The results show that the MAs approaches are efficient in solving attribute reduction problems when compared with other meta-heuristic approaches.

Keywords: rough set theory, attribute reduction, fuzzy logic, memetic algorithms, record to record algorithm, great deluge algorithm

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Authors: Kayla Murray, Andrew Green, Gopi Paliyath, Keith Warriner

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Introduction: It is now acknowledged that control of human pathogens associated with fresh produce requires an integrated approach of several interventions as opposed to relying on post-harvest washes to remove field acquired contamination. To this end, current research is directed towards identifying such interventions that can be applied at different points in leafy green processing. Purpose: In the following the efficacy of different gas phase treatments to decontaminate whole lettuce heads during pre-processing storage were evaluated. Methods: Whole Cos lettuce heads were spot inoculated with L. monocytogenes, E. coli O157:H7 or Salmonella spp. The inoculated lettuce heads were then placed in a treatment chamber and exposed to ozone, chlorine dioxide or hydroxyl radicals at different time periods under a range of relative humidity. Survivors of the treatments were enumerated along with sensory analysis performed on the treated lettuce. Results: Ozone gas reduced L. monocytogenes by 2-log10 after ten-minutes of exposure with Salmonella and E. coli O157:H7 being decreased by 0.66 and 0.56-log cfu respectively. Chlorine dioxide gas treatment reduced L. monocytogenes and Salmonella on lettuce heads by 4 log cfu but only supported a 0.8 log cfu reduction in E. coli O157:H7 numbers. In comparison, hydroxyl radicals supported a 2.9 – 4.8 log cfu reduction of model human pathogens inoculated onto lettuce heads but required extended exposure times and relative humidity < 0.8. Significance: From the gas phase sanitizers tested, chlorine dioxide and hydroxyl radicals are the most effective. The latter process holds most promise based on the ease of delivery, worker safety and preservation of lettuce sensory characteristics. Although expose times for hydroxyl radicles was relatively long (24h) this should not be considered a limitation given the intervention is applied in store rooms or in transport containers during transit.

Keywords: gas phase sanitizers, iceberg lettuce heads, leafy green processing

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Authors: Harish Aryal, Roger Hague, Daniel Sotelo, Felipe Astete Salinas

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This paper presents a comparative study of different coolants, materials, and temperatures that can affect the effectiveness of heat exchangers that are used in small modular reactors. The corrugated plate heat exchangers were chosen out of different plate options for testing purposes because of their ease of access and better performance than other existing heat exchangers in recent years. SolidWorks enables us to see various results between water coolants and helium coolants acting upon different types of conducting metals, which were selected from different fluids that ultimately satisfied accessibility requirements and were compatible with the software. Though not every element, material, fluid, or method was used in the testing phase, their purpose is to help further research that is to come since the innovation of nuclear power is the future. The tests that were performed are to help better understand the constant necessities that are seen in heat exchangers and through every adjustment see what the breaking points or improvements in the machine are. Depending on consumers and researchers, the results may give further feedback as to show why different types of materials and fluids would be preferred and why it is necessary to keep failures to improve future research.

Keywords: heat exchangers, Solidworks, coolants, small modular reactors, nuclear power, nanofluids, Nusselt number, friction factor, Reynolds number

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Authors: Vaidehi Iyer, Konstantin Borozdin

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Time series prediction problems have many important practical applications, but are notoriously difficult for statistical modeling. Recently, machine learning methods have been attracted significant interest as a practical tool applied to a variety of problems, even though developments in this field tend to be semi-empirical. This paper explores application of Long Short Term Memory based Recurrent Neural Networks to the one-step prediction of time series for both trend and stochastic components. Two types of data are analyzed - daily stock prices, that are often considered to be a typical example of a random walk, - and weather patterns dominated by seasonal variations. Results from both analyses are compared, and reinforced learning framework is used to select more efficient between Recurrent Neural Networks and more traditional auto regression methods. It is shown that both methods are able to follow long-term trends and seasonal variations closely, but have difficulties with reproducing day-to-day variability. Future research directions and potential real world applications are briefly discussed.

Keywords: long short term memory, prediction methods, recurrent neural networks, reinforcement learning

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Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: big data, k-NN, machine learning, traffic speed prediction

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Authors: Ilme Faridatul, Bo Wu

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Bangladesh is often called as a motherland of rivers. It contains about 700 rivers among all these the Padma River is one of the largest rivers of Bangladesh. The change of river bank and erosion has become a common environmental natural hazard in Bangladesh. The river banks are under intense pressure from natural processes such as erosion and accretion as well as anthropogenic processes such as urban growth and pollution. The Padma River is flowing along ten districts of Bangladesh among all these Faridpur district is most vulnerable to river bank erosion. The severity of the river erosion is so high that each year a thousand of populations become homeless and lose their agricultural lands. Though the Faridpur district is most vulnerable to river bank erosion no specific research has been conducted to identify the changing pattern of river bank along this district. The outcome of the research may serve as guidance to prepare river bank monitoring program and management. This research has utilized integrated techniques of remote sensing and geographic information system to monitor the changes from 1995 to 2015 at Faridpur district. To discriminate the land water interface Modified Normalized Difference Water Index (MNDWI) algorithm is applied and on screen digitization approach is used over MNDWI images of 1995, 2002 and 2015 for river bank line extraction. The extent of changes in the river bank along Faridpur district is estimated through overlaying the digitized maps of all three years. The river bank lines are highlighted to infer the erosion and accretion and the changes are calculated. The result shows that the middle of the river is gaining land through sedimentation and the both side river bank is shifting causing severe erosion that consequently resulting the loss of farmland and homestead. Over the study period from 1995 to 2015 it witnessed huge erosion and accretion that played an active role in the changes of the river bank.

Keywords: river bank, erosion and accretion, change monitoring, remote sensing

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Authors: Jens Friedrich, Matthias A. Gebele, Armin Lechler, Alexander Verl

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Chatter vibrations and process instabilities are the most important factors limiting the productivity of the milling process. Chatter can leads to damage of the tool, the part or the machine tool. Therefore, the estimation and prediction of the process stability is very important. The process stability depends on the spindle speed, the depth of cut and the width of cut. In milling, the process conditions are defined in the NC-program. While the spindle speed is directly coded in the NC-program, the depth and width of cut are unknown. This paper presents a new simulation based approach for the prediction of the depth and width of cut of a milling process. The prediction is based on a material removal simulation with an analytically represented tool shape and a multi-dexel approach for the work piece. The new calculation method allows the direct estimation of the depth and width of cut, which are the influencing parameters of the process stability, instead of the removed volume as existing approaches do. The knowledge can be used to predict the stability of new, unknown parts. Moreover with an additional vibration sensor, the stability lobe diagram of a milling process can be estimated and improved based on the estimated depth and width of cut.

Keywords: dexel, process stability, material removal, milling

Procedia PDF Downloads 508