Search results for: socio technical research
1111 Extraction of Rice Bran Protein Using Enzymes and Polysaccharide Precipitation
Authors: Sudarat Jiamyangyuen, Tipawan Thongsook, Riantong Singanusong, Chanida Saengtubtim
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Rice is a staple food as well as exported commodity of Thailand. Rice bran, a 10.5% constituent of rice grain, is a by-product of rice milling process. Rice bran is normally used as a raw material for rice bran oil production or sold as feed with a low price. Therefore, this study aimed to increase value of defatted rice bran as obtained after extracting of rice bran oil. Conventionally, the protein in defatted rice bran was extracted using alkaline extraction and acid precipitation, which results in reduction of nutritious components in rice bran. Rice bran protein concentrate is suitable for those who are allergenic of protein from other sources eg. milk, wheat. In addition to its hypoallergenic property, rice bran protein also contains good quantity of lysine. Thus it may act as a suitable ingredient for infant food formulations while adding variety to the restricted diets of children with food allergies. The objectives of this study were to compare properties of rice bran protein concentrate (RBPC) extracted from defatted rice bran using enzymes together with precipitation step using polysaccharides (alginate and carrageenan) to those of a control sample extracted using a conventional method. The results showed that extraction of protein from rice bran using enzymes exhibited the higher protein recovery compared to that extraction with alkaline. The extraction conditions using alcalase 2% (v/w) at 50 C, pH 9.5 gave the highest protein (2.44%) and yield (32.09%) in extracted solution compared to other enzymes. Rice bran protein concentrate powder prepared by a precipitation step using alginate (protein in solution: alginate 1:0.006) exhibited the highest protein (27.55%) and yield (6.62%). Precipitation using alginate was better than that of acid. RBPC extracted with alkaline (ALK) or enzyme alcalase (ALC), then precipitated with alginate (AL) (samples RBP-ALK-AL and RBP-ALC-AL) yielded the precipitation rate of 75% and 91.30%, respectively. Therefore, protein precipitation using alginate was then selected. Amino acid profile of control sample, and sample precipitated with alginate, as compared to casein and soy protein isolated, showed that control sample showed the highest content among all sample. Functional property study of RBP showed that the highest nitrogen solubility occurred in pH 8-10. There was no statically significant between emulsion capacity and emulsion stability of control and sample precipitated by alginate. However, control sample showed a higher of foaming and lower foam stability compared to those of sample precipitated with alginate. The finding was successful in terms of minimizing chemicals used in extraction and precipitation steps in preparation of rice bran protein concentrate. This research involves in a production of value-added product in which the double amount of protein (28%) compared to original amount (14%) contained in rice bran could be beneficial in terms of adding to food products eg. healthy drink with high protein and fiber. In addition, the basic knowledge of functional property of rice bran protein concentrate was obtained, which can be used to appropriately select the application of this value-added product from rice bran.Keywords: alginate, carrageenan, rice bran, rice bran protein
Procedia PDF Downloads 2951110 A Framework for Teaching the Intracranial Pressure Measurement through an Experimental Model
Authors: Christina Klippel, Lucia Pezzi, Silvio Neto, Rafael Bertani, Priscila Mendes, Flavio Machado, Aline Szeliga, Maria Cosendey, Adilson Mariz, Raquel Santos, Lys Bendett, Pedro Velasco, Thalita Rolleigh, Bruna Bellote, Daria Coelho, Bruna Martins, Julia Almeida, Juliana Cerqueira
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This project presents a framework for teaching intracranial pressure monitoring (ICP) concepts using a low-cost experimental model in a neurointensive care education program. Data concerning ICP monitoring contribute to the patient's clinical assessment and may dictate the course of action of a health team (nursing, medical staff) and influence decisions to determine the appropriate intervention. This study aims to present a safe method for teaching ICP monitoring to medical students in a Simulation Center. Methodology: Medical school teachers, along with students from the 4th year, built an experimental model for teaching ICP measurement. The model consists of a mannequin's head with a plastic bag inside simulating the cerebral ventricle and an inserted ventricular catheter connected to the ICP monitoring system. The bag simulating the ventricle can also be changed for others containing bloody or infected simulated cerebrospinal fluid. On the mannequin's ear, there is a blue point indicating the right place to set the "zero point" for accurate pressure reading. The educational program includes four steps: 1st - Students receive a script on ICP measurement for reading before training; 2nd - Students watch a video about the subject created in the Simulation Center demonstrating each step of the ICP monitoring and the proper care, such as: correct positioning of the patient, anatomical structures to establish the zero point for ICP measurement and a secure range of ICP; 3rd - Students train the procedure in the model. Teachers help students during training; 4th - Student assessment based on a checklist form. Feedback and correction of wrong actions. Results: Students expressed interest in learning ICP monitoring. Tests concerning the hit rate are still being performed. ICP's final results and video will be shown at the event. Conclusion: The study of intracranial pressure measurement based on an experimental model consists of an effective and controlled method of learning and research, more appropriate for teaching neurointensive care practices. Assessment based on a checklist form helps teachers keep track of student learning progress. This project offers medical students a safe method to develop intensive neurological monitoring skills for clinical assessment of patients with neurological disorders.Keywords: neurology, intracranial pressure, medical education, simulation
Procedia PDF Downloads 1721109 Phylogenetic Analysis of Georgian Populations of Potato Cyst Nematodes Globodera Rostochiensis
Authors: Dali Gaganidze, Ekaterine Abashidze
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Potato is one of the main agricultural crops in Georgia. Georgia produces early and late potato varieties in almost all regions. In traditional potato growing regions (Svaneti, Samckhet javaheti and Tsalka), the yield is higher than 30-35 t/ha. Among the plant pests that limit potato production and quality, the potato cyst nematodes (PCN) are harmful around the world. Yield losses caused by PCN are estimated up to 30%. Rout surveys conducted in two geographically distinct regions of Georgia producing potatoes - Samtskhe - Javakheti and Svaneti revealed potato cyst nematode Globodera rostochiensi. The aim of the study was the Phylogenetic analyses of Globodera rostochiensi revealed in Georgia by the amplification and sequencing of 28S gen in the D3 region and intergenic ITS1-15.8S-ITS2 region. Identification of all the samples from the two Globodera populations (Samtskhe - Javakheti and Svaneti), i.e., G. rostochiensis (20 isolates) were confirmed by conventional multiplex PCR with ITS 5 universal and PITSp4, PITSr3 specific primers of the cyst nematodes’ (G. pallida, G. rostochiensis). The size of PCR fragment 434 bp confirms that PCN samples from two populations, Samtskhe- Javakheti and Svaneti, belong to G. rostochiensi . The ITS1–5.8S-ITS2 regions were amplified using prime pairs: rDNA1 ( 5’ -TTGATTACGTCCCTGCCCTTT-3’ and rDNA2( 5’ TTTCACTCGCCGTTACTAAGG-3’), D3 expansion regions were amplified using primer pairs: D3A (5’ GACCCCTCTTGAAACACGGA-3’) and D3B (5’-TCGGAAGGAACCAGCTACTA-3’. PCR products of each region were cleaned up and sequenced using an ABI 3500xL Genetic Analyzer. Obtained sequencing results were analyzed by computer program BLASTN (https://blast.ncbi.nlm.nih.gov/Blast.cg). Phylogenetic analyses to resolve the relationships between the isolates were conducted in MEGA7 using both distance- and character-based methods. Based on analysis of G.rostochiensis isolate`s D3 expansion regions are grouped in three major clades (A, B and C) on the phylogenetic tree. Clade A is divided into three subclades; clade C is divided into two subclades. Isolates from the Samtckhet-javakheti population are in subclade 1 of clade A and isolates in subclade 1 of clade C. Isolates) from Svaneti populations are in subclade 2 of clade A and in clad B. In Clade C, subclade two is presented by three isolates from Svaneti and by one isolate (GL17) from Samckhet-Javakheti. . Based on analysis of G.rostochiensis isolate`s ITS1–5.8S-ITS2 regions are grouped in two main clades, the first contained 20 Georgian isolates of Globodera rostochiensis from Svaneti . The second clade contained 15 isolates of Globodera rostochiensis from Samckhet javakheti. Our investigation showed of high genetic variation of D3 and ITS1–5.8S-ITS2 region of rDNA of the isolates of G. rostochiensis from different geographic origins (Svameti, Samckhet-Javakheti) of Georgia. Acknowledgement: The research has been supported by the Shota Rustaveli National Scientific Foundation of Georgia : Project # FR17_235Keywords: globodera rostochiensi, PCR, phylogenetic tree, sequencing
Procedia PDF Downloads 1951108 Machine Learning for Disease Prediction Using Symptoms and X-Ray Images
Authors: Ravija Gunawardana, Banuka Athuraliya
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Machine learning has emerged as a powerful tool for disease diagnosis and prediction. The use of machine learning algorithms has the potential to improve the accuracy of disease prediction, thereby enabling medical professionals to provide more effective and personalized treatments. This study focuses on developing a machine-learning model for disease prediction using symptoms and X-ray images. The importance of this study lies in its potential to assist medical professionals in accurately diagnosing diseases, thereby improving patient outcomes. Respiratory diseases are a significant cause of morbidity and mortality worldwide, and chest X-rays are commonly used in the diagnosis of these diseases. However, accurately interpreting X-ray images requires significant expertise and can be time-consuming, making it difficult to diagnose respiratory diseases in a timely manner. By incorporating machine learning algorithms, we can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The study utilized the Mask R-CNN algorithm, which is a state-of-the-art method for object detection and segmentation in images, to process chest X-ray images. The model was trained and tested on a large dataset of patient information, which included both symptom data and X-ray images. The performance of the model was evaluated using a range of metrics, including accuracy, precision, recall, and F1-score. The results showed that the model achieved an accuracy rate of over 90%, indicating that it was able to accurately detect and segment regions of interest in the X-ray images. In addition to X-ray images, the study also incorporated symptoms as input data for disease prediction. The study used three different classifiers, namely Random Forest, K-Nearest Neighbor and Support Vector Machine, to predict diseases based on symptoms. These classifiers were trained and tested using the same dataset of patient information as the X-ray model. The results showed promising accuracy rates for predicting diseases using symptoms, with the ensemble learning techniques significantly improving the accuracy of disease prediction. The study's findings indicate that the use of machine learning algorithms can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The model developed in this study has the potential to assist medical professionals in diagnosing respiratory diseases more accurately and efficiently. However, it is important to note that the accuracy of the model can be affected by several factors, including the quality of the X-ray images, the size of the dataset used for training, and the complexity of the disease being diagnosed. In conclusion, the study demonstrated the potential of machine learning algorithms for disease prediction using symptoms and X-ray images. The use of these algorithms can improve the accuracy of disease diagnosis, ultimately leading to better patient care. Further research is needed to validate the model's accuracy and effectiveness in a clinical setting and to expand its application to other diseases.Keywords: K-nearest neighbor, mask R-CNN, random forest, support vector machine
Procedia PDF Downloads 1541107 Carbon Dioxide Capture and Utilization by Using Seawater-Based Industrial Wastewater and Alkanolamine Absorbents
Authors: Dongwoo Kang, Yunsung Yoo, Injun Kim, Jongin Lee, Jinwon Park
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Since industrial revolution, energy usage by human-beings has been drastically increased resulting in the enormous emissions of carbon dioxide into the atmosphere. High concentration of carbon dioxide is well recognized as the main reason for the climate change by breaking the heat equilibrium of the earth. In order to decrease the amount of carbon dioxide emission, lots of technologies have been developed. One of the methods is to capture carbon dioxide after combustion process using liquid type absorbents. However, for some nations, captured carbon dioxide cannot be treated and stored properly due to their geological structures. Also, captured carbon dioxide can be leaked out when crust activities are active. Hence, the method to convert carbon dioxide as stable and useful products were developed. It is usually called CCU, that is, Carbon Capture and Utilization. There are several ways to convert carbon dioxide into useful substances. For example, carbon dioxide can be converted and used as fuels such as diesel, plastics, and polymers. However, these types of technologies require lots of energy to make stable carbon dioxide into a reactive one. Hence, converting it into metal carbonates salts have been studied widely. When carbon dioxide is captured by alkanolamine-based liquid absorbents, it exists as ionic forms such as carbonate, carbamate, and bicarbonate. When adequate metal ions are added, metal carbonate salt can be produced by ionic reaction with fast reaction kinetics. However, finding metal sources can be one of the problems for this method to be commercialized. If natural resources such as calcium oxide were used to supply calcium ions, it is not thought to have the economic feasibility to use natural resources to treat carbon dioxide. In this research, high concentrated industrial wastewater produced from refined salt production facility have been used as metal supplying source, especially for calcium cations. To ensure purity of final products, calcium ions were selectively separated in the form of gypsum dihydrate. After that, carbon dioxide is captured using alkanolamine-based absorbents making carbon dioxide into reactive ionic form. And then, high purity calcium carbonate salt was produced. The existence of calcium carbonate was confirmed by X-Ray Diffraction (XRD) and Scanning Electron Microscopy (SEM) images. Also, carbon dioxide loading curves for absorption, conversion, and desorption were provided. Also, in order to investigate the possibility of the absorbent reuse, reabsorption experiments were performed either. Produced calcium carbonate as final products is seemed to have potential to be used in various industrial fields including cement and paper making industries and pharmaceutical engineering fields.Keywords: alkanolamine, calcium carbonate, climate change, seawater, industrial wastewater
Procedia PDF Downloads 1851106 Aquatic Sediment and Honey of Apis mellifera as Bioindicators of Pesticide Residues
Authors: Luana Guerra, Silvio C. Sampaio, Vladimir Pavan Margarido, Ralpho R. Reis
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Brazil is the world's largest consumer of pesticides. The excessive use of these compounds has negative impacts on animal and human life, the environment, and food security. Bees, crucial for pollination, are exposed to pesticides during the collection of nectar and pollen, posing risks to their health and the food chain, including honey contamination. Aquatic sediments are also affected, impacting water quality and the microbiota. Therefore, the analysis of aquatic sediments and bee honey is essential to identify environmental contamination and monitor ecosystems. The aim of this study was to use samples of honey from honeybees (Apis mellifera) and aquatic sediment as bioindicators of environmental contamination by pesticides and their relationship with agricultural use in the surrounding areas. The sample collections of sediment and honey were carried out in two stages. The first stage was conducted in the Bituruna municipality region in the second half of the year 2022, and the second stage took place in the regions of Laranjeiras do Sul, Quedas do Iguaçu, and Nova Laranjeiras in the first half of the year 2023. In total, 10 collection points were selected, with 5 points in the first stage and 5 points in the second stage, where one sediment sample and one honey sample were collected for each point, totaling 20 samples. The honey and sediment samples were analyzed at the Laboratory of the Paraná Institute of Technology, with ten samples of honey and ten samples of sediment. The selected extraction method was QuEChERS, and the analysis of the components present in the sample was performed using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). The pesticides Azoxystrobin, Epoxiconazole, Boscalid, Carbendazim, Haloxifope, Fomesafen, Fipronil, Chlorantraniliprole, Imidacloprid, and Bifenthrin were detected in the sediment samples from the study area in Laranjeiras do Sul, Paraná, with Carbendazim being the compound with the highest concentration (0.47 mg/kg). The honey samples obtained from the apiaries showed satisfactory results, as they did not show any detection or quantification of the analyzed pesticides, except for Point 9, which had the fungicide tebuconazole but with a concentration1105 Translating Creativity to an Educational Context: A Method to Augment the Professional Training of Newly Qualified Secondary School Teachers
Authors: Julianne Mullen-Williams
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This paper will provide an overview of a three year mixed methods research project that explores if methods from the supervision of dramatherapy can augment the occupational psychology of newly qualified secondary school teachers. It will consider how creativity and the use of metaphor, as applied in the supervision of dramatherapists, can be translated to an educational context in order to explore the explicit / implicit dynamics between the teacher trainee/ newly qualified teacher and the organisation in order to support the super objective in training for teaching; how to ‘be a teacher.’ There is growing evidence that attrition rates among teachers are rising after only five years of service owing to too many national initiatives, an unmanageable curriculum and deteriorating student discipline. The fieldwork conducted entailed facilitating a reflective space for Newly Qualified Teachers from all subject areas, using methods from the supervision of dramatherapy, to explore the social and emotional aspects of teaching and learning with the ultimate aim of improving the occupational psychology of teachers. Clinical supervision is a formal process of professional support and learning which permits individual practitioners in frontline service jobs; counsellors, psychologists, dramatherapists, social workers and nurses to expand their knowledge and proficiency, take responsibility for their own practice, and improve client protection and safety of care in complex clinical situations. It is deemed integral to continued professional practice to safeguard vulnerable people and to reduce practitioner burnout. Dramatherapy supervision incorporates all of the above but utilises creative methods as a tool to gain insight and a deeper understanding of the situation. Creativity and the use of metaphor enable the supervisee to gain an aerial view of the situation they are exploring. The word metaphor in Greek means to ‘carry across’ indicating a transfer of meaning form one frame of reference to another. The supervision support was incorporated into each group’s induction training programme. The first year group attended fortnightly one hour sessions, the second group received two one hour sessions every term. The existing literature on the supervision and mentoring of secondary school teacher trainees calls for changes in pre-service teacher education and in the induction period. There is a particular emphasis on the need to include reflective and experiential learning, within training programmes and within the induction period, in order to help teachers manage the interpersonal dynamics and emotional impact within a high pressurised environmentKeywords: dramatherapy supervision, newly qualified secondary school teachers, professional development, teacher education
Procedia PDF Downloads 3881104 Dry Reforming of Methane Using Metal Supported and Core Shell Based Catalyst
Authors: Vinu Viswanath, Lawrence Dsouza, Ugo Ravon
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Syngas typically and intermediary gas product has a wide range of application of producing various chemical products, such as mixed alcohols, hydrogen, ammonia, Fischer-Tropsch products methanol, ethanol, aldehydes, alcohols, etc. There are several technologies available for the syngas production. An alternative to the conventional processes an attractive route of utilizing carbon dioxide and methane in equimolar ratio to generate syngas of ratio close to one has been developed which is also termed as Dry Reforming of Methane technology. It also gives the privilege to utilize the greenhouse gases like CO2 and CH4. The dry reforming process is highly endothermic, and indeed, ΔG becomes negative if the temperature is higher than 900K and practically, the reaction occurs at 1000-1100K. At this temperature, the sintering of the metal particle is happening that deactivate the catalyst. However, by using this strategy, the methane is just partially oxidized, and some cokes deposition occurs that causing the catalyst deactivation. The current research work was focused to mitigate the main challenges of dry reforming process such coke deposition, and metal sintering at high temperature.To achieve these objectives, we employed three different strategies of catalyst development. 1) Use of bulk catalysts such as olivine and pyrochlore type materials. 2) Use of metal doped support materials, like spinel and clay type material. 3) Use of core-shell model catalyst. In this approach, a thin layer (shell) of redox metal oxide is deposited over the MgAl2O4 /Al2O3 based support material (core). For the core-shell approach, an active metal is been deposited on the surface of the shell. The shell structure formed is a doped metal oxide that can undergo reduction and oxidation reactions (redox), and the core is an alkaline earth aluminate having a high affinity towards carbon dioxide. In the case of metal-doped support catalyst, the enhanced redox properties of doped CeO2 oxide and CO2 affinity property of alkaline earth aluminates collectively helps to overcome coke formation. For all of the mentioned three strategies, a systematic screening of the metals is carried out to optimize the efficiency of the catalyst. To evaluate the performance of them, the activity and stability test were carried out under reaction conditions of temperature ranging from 650 to 850 ̊C and an operating pressure ranging from 1 to 20 bar. The result generated infers that the core-shell model catalyst showed high activity and better stable DR catalysts under atmospheric as well as high-pressure conditions. In this presentation, we will show the results related to the strategy.Keywords: carbon dioxide, dry reforming, supports, core shell catalyst
Procedia PDF Downloads 1781103 Shear Strength Envelope Characteristics of LimeTreated Clays
Authors: Mohammad Moridzadeh, Gholamreza Mesri
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The effectiveness of lime treatment of soils has been commonly evaluated in terms of improved workability and increased undrained unconfined compressive strength in connection to road and airfield construction. The most common method of strength measurement has been the unconfined compression test. However, if the objective of lime treatment is to improve long-term stability of first-time or reactivated landslides in stiff clays and shales, permanent changes in the size and shape of clay particles must be realized to increase drained frictional resistance. Lime-soil interactions that may produce less platy and larger soil particles begin and continue with time under the highly alkaline pH environment. In this research, pH measurements are used to monitor chemical environment and progress of reactions. Atterberg limits are measured to identify changes in particle size and shape indirectly. Also, fully softened and residual strength measurements are used to examine an improvement in frictional resistance due to lime-soil interactions. The main variables are soil plasticity and mineralogy, lime content, water content, and curing period. Lime effect on frictional resistance is examined using samples of clays with different mineralogy and characteristics which may react with lime to various extents. Drained direct shear tests on reconstituted lime-treated clay specimens with various properties have been performed to measure fully softened shear strength. To measure residual shear strength, drained multiple reversal direct shear tests on precut specimens were conducted. This way, soil particles are oriented along the direction of shearing to the maximum possible extent and provide minimum frictional resistance. This is applicable to reactivated and part of first-time landslides. The Brenna clay, which is the highly plastic lacustrine clay of Lake Agassiz causing slope instability along the banks of the Red River, is one of the soil samples used in this study. The Brenna Formation characterized as a uniform, soft to firm, dark grey, glaciolacustrine clay with little or no visible stratification, is full of slickensided surfaces. The major source of sediment for the Brenna Formation was the highly plastic montmorillonitic Pierre Shale bedrock. The other soil used in this study is one of the main sources of slope instability in Harris County Flood Control District (HCFCD), i.e. the Beaumont clay. The shear strengths of untreated and treated clays were obtained under various normal pressures to evaluate the shear envelope nonlinearity.Keywords: Brenna clay, friction resistance, lime treatment, residual
Procedia PDF Downloads 1591102 Structural and Morphological Characterization of the Biomass of Aquatics Macrophyte (Egeria densa) Submitted to Thermal Pretreatment
Authors: Joyce Cruz Ferraz Dutra, Marcele Fonseca Passos, Rubens Maciel Filho, Douglas Fernandes Barbin, Gustavo Mockaitis
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The search for alternatives to control hunger in the world, generated a major environmental problem. Intensive systems of fish production can cause an imbalance in the aquatic environment, triggering the phenomenon of eutrophication. Currently, there are many forms of growth control aquatic plants, such as mechanical withdrawal, however some difficulties arise for their final destination. The Egeria densa is a species of submerged aquatic macrophyte-rich in cellulose and low concentrations of lignin. By applying the concept of second generation energy, which uses lignocellulose for energy production, the reuse of these aquatic macrophytes (Egeria densa) in the biofuels production can turn an interesting alternative. In order to make lignocellulose sugars available for effective fermentation, it is important to use pre-treatments in order to separate the components and modify the structure of the cellulose and thus facilitate the attack of the microorganisms responsible for the fermentation. Therefore, the objective of this research work was to evaluate the structural and morphological transformations occurring in the biomass of aquatic macrophytes (E.densa) submitted to a thermal pretreatment. The samples were collected in an intensive fish growing farm, in the low São Francisco dam, in the northeastern region of Brazil. After collection, the samples were dried in a 65 0C ventilation oven and milled in a 5mm micron knife mill. A duplicate assay was carried, comparing the in natural biomass with the pretreated biomass with heat (MT). The sample (MT) was submitted to an autoclave with a temperature of 1210C and a pressure of 1.1 atm, for 30 minutes. After this procedure, the biomass was characterized in terms of degree of crystallinity and morphology, using X-ray diffraction (XRD) techniques and scanning electron microscopy (SEM), respectively. The results showed that there was a decrease of 11% in the crystallinity index (% CI) of the pretreated biomass, leading to the structural modification in the cellulose and greater presence of amorphous structures. Increases in porosity and surface roughness of the samples were also observed. These results suggest that biomass may become more accessible to the hydrolytic enzymes of fermenting microorganisms. Therefore, the morphological transformations caused by the thermal pretreatment may be favorable for a subsequent fermentation and, consequently, a higher yield of biofuels. Thus, the use of thermally pretreated aquatic macrophytes (E.densa) can be an environmentally, financially and socially sustainable alternative. In addition, it represents a measure of control for the aquatic environment, which can generate income (biogas production) and maintenance of fish farming activities in local communities.Keywords: aquatics macrophyte, biofuels, crystallinity, morphology, pretreatment thermal
Procedia PDF Downloads 3301101 Improving Teaching in English-Medium Instruction Classes at Japanese Universities through Needs-Based Professional Development Workshops
Authors: Todd Enslen
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In order to attract more international students to study for undergraduate degrees in Japan, many universities have been developing English-Medium Instruction degree programs. This means that many faculty members must now teach their courses in English, which raises a number of concerns. A common misconception of English-Medium Instruction (EMI) is that teaching in English is simply a matter of translating materials. Since much of the teaching in Japan still relies on a more traditional, teachercentered, approach, continuing with this style in an EMI environment that targets international students can cause a clash between what is happening and what students expect in the classroom, not to mention what the Scholarship of Teaching and Learning (SoTL) has shown is effective teaching. A variety of considerations need to be taken into account in EMI classrooms such as varying English abilities of the students, modifying input material, and assuring comprehension through interactional checks. This paper analyzes the effectiveness of the English-Medium Instruction (EMI) undergraduate degree programs in engineering, agriculture, and science at a large research university in Japan by presenting the results from student surveys regarding the areas where perceived improvements need to be made. The students were the most dissatisfied with communication with their teachers in English, communication with Japanese students in English, adherence to only English being used in the classes, and the quality of the education they received. In addition, the results of a needs analysis survey of Japanese teachers having to teach in English showed that they believed they were most in need of English vocabulary and expressions to use in the classroom and teaching methods for teaching in English. The result from the student survey and the faculty survey show similar concerns between the two groups. By helping the teachers to understand student-centered teaching and the benefits for learning that it provides, teachers may begin to incorporate more student-centered approaches that in turn help to alleviate the dissatisfaction students are currently experiencing. Through analyzing the current environment in Japanese higher education against established best practices in teaching and EMI, three areas that need to be addressed in professional development workshops were identified. These were “culture” as it relates to the English language, “classroom management techniques” and ways to incorporate them into classes, and “language” issues. Materials used to help faculty better understand best practices as they relate to these specific areas will be provided to help practitioners begin the process of helping EMI faculty build awareness of better teaching practices. Finally, the results from faculty development workshops participants’ surveys will show the impact that these workshops can have. Almost all of the participants indicated that they learned something new and would like to incorporate the ideas from the workshop into their teaching. In addition, the vast majority of the participants felt the workshop provided them with new information, and they would like more workshops like these.Keywords: English-medium instruction, materials development, professional development, teaching effectiveness
Procedia PDF Downloads 891100 Analyzing Social Media Discourses of Domestic Violence in Promoting Awareness and Support Seeking: An Exploratory Study
Authors: Sudha Subramani, Hua Wang
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Domestic Violence (DV) against women is now recognized to be a serious and widespread problem worldwide. There is a growing concern that violence against women has a global public health impact, as well as a violation of human rights. From the existing statistical surveys, it is revealed that there exists a strong relationship between DV and health issues of women like bruising, lacerations, depression, anxiety, flashbacks, sleep disturbances, hyper-arousal, emotional distress, sexually transmitted diseases and so on. This social problem is still considered as behind the closed doors issue and stigmatized topic. Women conceal their sufferings from family and friends, as they experience a lack of trust in others, feelings of shame and embarrassment among the society. Hence, women survivors of DV experience some barriers in seeking the support of specialized services such as health care access, crisis support, and legal guidance. Fortunately, with the popularity of social media like Facebook and Twitter, people share their opinions and emotional feelings to seek the social and emotional support, for sympathetic encouragement, to show compassion and empathy among the public. Considering the DV, social media plays a predominant role in creating the awareness and promoting the support services to the public, as we live in the golden era of social media. The various professional people like the public health researchers, clinicians, psychologists, social workers, national family health organizations, lawyers, and victims or their family and friends share the unprecedentedly valuable information (personal opinions and experiences) in a single platform to improve the social welfare of the community. Though each tweet or post contains a less informational value, the consolidation of millions of messages can generate actionable knowledge and provide valuable insights about the public opinion in general. Hence, this paper reports on an exploratory analysis of the effectiveness of social media for unobtrusive assessment of attitudes and awareness towards DV. In this paper, mixed methods such as qualitative analysis and text mining approaches are used to understand the social media disclosures of DV through the lenses of opinion sharing, anonymity, and support seeking. The results of this study could be helpful to avoid the cost of wide scale surveys, while still maintaining appropriate research conditions is to leverage the abundance of data publicly available on the web. Also, this analysis with data enrichment and consolidation would be useful in assisting advocacy and national family health organizations to provide information about resources and support, raise awareness and counter common stigmatizing attitudes about DV.Keywords: domestic violence, social media, social stigma and support, women health
Procedia PDF Downloads 2901099 Assessment of Water Pollution in the River Nile (Egypt) by Applying Blood Biomarkers in Two Excellent Model Species Oreochromis niloticus niloticus and Clarias gariepinus
Authors: Alaa G. M. Osman, Abd-El –Baset M. Abd El Reheem, Khaled Y. Abouelfadl, Usama M. Mahmoud, Mohsen A. Moustafa
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This study aimed to explore new sites of biomarker research and to establish the use of blood parameters in wild fish populations. Four hundred and twenty fish samples were collected from six sites along the whole course of the river Nile, Egypt. The mean values of erythrocytes, thrombocytes, hemoglobin concentration, hematocrit value, and mean corpuscular volume were significantly lower in the blood of Nile tilapia and African catfish collected from downstream (contaminated) compared to upstream sites. In contrast, mean corpuscular hemoglobin and mean corpuscular hemoglobin concentration in the peripheral blood of both fish species significantly increased from upstream to downstream river Nile. The leukocytes count was significantly decreased in contaminated sites compared to upstream area. Hematological variables in the peripheral blood of Oreochromis niloticus niloticus and Clarias gariepinus exhibited significant (p<0.05) correlation with nearly all the detected chemical and physical parameters along the Nile course. In the present study, lower cellular and nuclear areas and cellular and nuclear shape factor were recorded in the erythrocytes of fish collected from downstream compared to those caught from upstream sites. This was confirmed by higher immature ratios of red cells in the blood of fish sampled from downstream river Nile. Karyorrhetic and enucleated erythrocytes were significantly correlated with physiochemical parameters in water samples collected from the same sites is being higher in the blood of fish collected from downstream sites. To see if there was any correlation between fish altered physiological fitness and environmental stress, we measured serum biochemical variables namely; total protein, cholesterol, triglycerides, calcium, chlorides, alkaline phosphatase activity (ALP), aspartate aminotransferase (AST), alanine aminotransferase (ALT), uric acid activity, creatinine, and serum glucose. The level of all the selected biochemical variables in the blood of O. niloticus niloticus and C. gariepinus were recorded to be significantly higher (p<0.05) in downstream sites. According to the present results, nearly all the detected haematological and blood biochemical variables are suitable indicators of contaminant exposure in O. niloticus niloticus and C. gariepinus. Also the detected erythrocytes malformations in blood collected from Nile tilapia and African catfish were proven to be suitable for bio-monitoring aquatic pollution. The results revealed species-specific differences in sensitivities, suggesting that Nile tilapia may serve as a more sensitive test species compared to African catfish.Keywords: biomarkers, water pollution, blood parameters, river nile, african catfish, nile tilapia
Procedia PDF Downloads 2911098 Baricitinib Lipid-based Nanosystems as a Topical Alternative for Atopic Dermatitis Treatment
Authors: N. Garrós, P. Bustos, N. Beirampour, R. Mohammadi, M. Mallandrich, A.C. Calpena, H. Colom
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Atopic dermatitis (AD) is a persistent skin condition characterized by chronic inflammation caused by an autoimmune response. It is a prevalent clinical issue that requires continual treatment to enhance the patient's quality of life. Systemic therapy often involves the use of glucocorticoids or immunosuppressants to manage symptoms. Our objective was to create and assess topical liposomal formulations containing Baricitinib (BNB), a reversible inhibitor of Janus-associated kinase (JAK), which is involved in various immune responses. These formulations were intended to address flare-ups and improve treatment outcomes for AD. We created three distinct liposomal formulations by combining different amounts of 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC), cholesterol (CHOL), and ceramide (CER): (i) pure POPC, (ii) POPC mixed with CHOL (at a ratio of 8:2, mol/mol), and (iii) POPC mixed with CHOL and CER (at a ratio of 3.6:2.4:4.0 mol/mol/mol). We conducted various tests to determine the formulations' skin tolerance, irritancy capacity, and their ability to cause erythema and edema on altered skin. We also assessed the transepidermal water loss (TEWL) and skin hydration of rabbits to evaluate the efficacy of the formulations. Histological analysis, the HET-CAM test, and the modified Draize test were all used in the evaluation process. The histological analysis revealed that liposome POPC and POPC:CHOL avoided any damage to the tissues structures. The HET-CAM test showed no irritation effect caused by any of the three liposomes, and the modified Draize test showed a good Draize score for erythema and edema. Liposome POPC effectively counteracted the impact of xylol on the skin, and no erythema or edema was observed during the study. TEWL values were constant for all the liposomes with similar values to the negative control (within the range 8 - 15 g/h·m2, which means a healthy value for rabbits), whereas the positive control showed a significant increase. The skin hydration values were constant and followed the trend of the negative control, while the positive control showed a steady increase during the tolerance study. In conclusion, the developed formulations containing BNB exhibited no harmful or irritating effects, they did not demonstrate any irritant potential in the HET-CAM test and liposomes POPC and POPC:CHOL did not cause any structural alteration according to the histological analysis. These positive findings suggest that additional research is necessary to evaluate the efficacy of these liposomal formulations in animal models of the disease, including mutant animals. Furthermore, before proceeding to clinical trials, biochemical investigations should be conducted to better understand the mechanisms of action involved in these formulations.Keywords: baricitinib, HET-CAM test, histological study, JAK inhibitor, liposomes, modified draize test
Procedia PDF Downloads 921097 Support for Refugee Entrepreneurs Through International Aid
Authors: Julien Benomar
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The World Bank report published in April 2023 called “Migrants, Refugees and Society” allows us to first distinguish migrants in search of economic opportunities and refugees that flee a situation of danger and choose their destination based on their immediate need for safety. Amongst those two categories, the report distinguished people having professional skills adapted to the labor market of the host country and those who have not. Out of that distinction of four categories, we choose to focus our research on refugees that do not have professional skills adapted to the labor market of the host country. Given that refugees generally have no recourse to public assistance schemes and cannot count on the support of their entourage or support network, we propose to examine the extent to which external assistance, such as international humanitarian action, is likely to accompany refugees' transition to financial empowerment through entrepreneurship. To this end, we propose to carry out a case study structured in three stages: (i) an exchange with a Non-Governmental Organisation (NGO) active in supporting refugee populations from Congo and Burundi to Rwanda, enabling us to (i.i) define together a financial empowerment income, and (i. ii) learn about the content of the support measures taken for the beneficiaries of the humanitarian project; (ii) monitor the population of 118 beneficiaries, including 73 refugees and 45 Rwandans (reference population); (iii) conduct a participatory analysis to identify the level of performance of the project and areas for improvement. The case study thus involved the staff of an international NGO active in helping refugees from Rwanda since 2015 and the staff of a Luxembourg NGO that has been funding this economic aid project through entrepreneurship since 2021. The case study thus involved the staff of an international NGO active in helping refugees from Rwanda since 2015 and the staff of a Luxembourg NGO, which has been funding this economic aid through an entrepreneurship project since 2021, and took place over a 48-day period between April and May 2023. The main results are of two types: (i) the need to associate indicators for monitoring the impact of the project on the indirect beneficiaries of the project (refugee community) and (ii) the identification of success factors making it possible to bring concrete and relevant responses to the constraints encountered. The first result thus made it possible to identify the following indicators: Indicator of community potential ((jobs, training or mentoring) promoted by the activity of the entrepreneur), Indicator of social contribution (tax paid by the entrepreneur), Indicator of resilience (savings and loan capacity generated, and finally impact on social cohesion. The second result made it possible to identify that among the 7 success factors tested, the sector of activity chosen and the level of experience in the sector of the future activity are those that stand out the most clearly.Keywords: entrepreuneurship, refugees, financial empowerment, international aid
Procedia PDF Downloads 781096 Analysis Rescuers' Viewpoint about Victims Tracking in Earthquake by Using Radio Frequency Identification (RFID)
Authors: Sima Ajami, Batool Akbari
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Background: Radio frequency identification (RFID) system has been successfully applied to the areas of manufacturing, supply chain, agriculture, transportation, healthcare, and services. The RFID is already used to track and trace the victims in a disaster situation. Data can be collected in real time and be immediately available to emergency personnel and saves time by the RFID. Objectives: The aim of this study was, first, to identify stakeholders and customers for rescuing earthquake victims, second, to list key internal and external factors to use RFID to track earthquake victims, finally, to assess SWOT for rescuers' viewpoint. Materials and Methods: This study was an applied and analytical study. The study population included scholars, experts, planners, policy makers and rescuers in the "red crescent society of Isfahan province", "disaster management Isfahan province", "maintenance and operation department of Isfahan", "fire and safety services organization of Isfahan municipality", and "medical emergencies and disaster management center of Isfahan". After that, researchers held a workshop to teach participants about RFID and its usages in tracking earthquake victims. In the meanwhile of the workshop, participants identified, listed, and weighed key internal factors (strengths and weaknesses; SW) and external factors (opportunities and threats; OT) to use RFID in tracking earthquake victims. Therefore, participants put weigh strengths, weaknesses, opportunities, and threats (SWOT) and their weighted scales were calculated. Then, participants' opinions about this issue were assessed. Finally, according to the SWOT matrix, strategies to solve the weaknesses, problems, challenges, and threats through opportunities and strengths were proposed by participants. Results: The SWOT analysis showed that the total weighted score for internal and external factors were 3.91 (Internal Factor Evaluation) and 3.31 (External Factor Evaluation) respectively. Therefore, it was in a quadrant SO strategies cell in the SWOT analysis matrix and aggressive strategies were resulted. Organizations, scholars, experts, planners, policy makers and rescue workers should plan to use RFID technology in order to save more victims and manage their life. Conclusions: Researchers suppose to apply SO strategies and use a firm’s internal strength to take advantage of external opportunities. It is suggested, policy maker should plan to use the most developed technologies to save earthquake victims and deliver the easiest service to them. To do this, education, informing, and encouraging rescuers to use these technologies is essential. Originality/ Value: This study was a research paper that showed how RFID can be useful to track victims in earthquake.Keywords: frequency identification system, strength, weakness, earthquake, victim
Procedia PDF Downloads 3221095 Examining the Design of a Scaled Audio Tactile Model for Enhancing Interpretation of Visually Impaired Visitors in Heritage Sites
Authors: A. Kavita Murugkar, B. Anurag Kashyap
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With the Rights for Persons with Disabilities Act (RPWD Act) 2016, the Indian government has made it mandatory for all establishments, including Heritage Sites, to be accessible for People with Disabilities. However, recent access audit surveys done under the Accessible India Campaign by Ministry of Culture indicate that there are very few accessibility measures provided in the Heritage sites for people with disabilities. Though there are some measures for the mobility impaired, surveys brought out that there are almost no provisions for people with vision impairment (PwVI) in heritage sites thus depriving them of a reasonable physical & intellectual access that facilitates an enjoyable experience and enriching interpretation of the Heritage Site. There is a growing need to develop multisensory interpretative tools that can help the PwVI in perceiving heritage sites in the absence of vision. The purpose of this research was to examine the usability of an audio-tactile model as a haptic and sound-based strategy for augmenting the perception and experience of PwVI in a heritage site. The first phase of the project was a multi-stage phenomenological experimental study with visually impaired users to investigate the design parameters for developing an audio-tactile model for PwVI. The findings from this phase included user preferences related to the physical design of the model such as the size, scale, materials, details, etc., and the information that it will carry such as braille, audio output, tactile text, etc. This was followed by the second phase in which a working prototype of an audio-tactile model is designed and developed for a heritage site based on the findings from the first phase of the study. A nationally listed heritage site from the author’s city was selected for making the model. The model was lastly tested by visually impaired users for final refinements and validation. The prototype developed empowers People with Vision Impairment to navigate independently in heritage sites. Such a model if installed in every heritage site, can serve as a technological guide for the Person with Vision Impairment, giving information of the architecture, details, planning & scale of the buildings, the entrances, location of important features, lifts, staircases, and available, accessible facilities. The model was constructed using 3D modeling and digital printing technology. Though designed for the Indian context, this assistive technology for the blind can be explored for wider applications across the globe. Such an accessible solution can change the otherwise “incomplete’’ perception of the disabled visitor, in this case, a visually impaired visitor and augment the quality of their experience in heritage sites.Keywords: accessibility, architectural perception, audio tactile model , inclusive heritage, multi-sensory perception, visual impairment, visitor experience
Procedia PDF Downloads 1061094 USBware: A Trusted and Multidisciplinary Framework for Enhanced Detection of USB-Based Attacks
Authors: Nir Nissim, Ran Yahalom, Tomer Lancewiki, Yuval Elovici, Boaz Lerner
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Background: Attackers increasingly take advantage of innocent users who tend to use USB devices casually, assuming these devices benign when in fact they may carry an embedded malicious behavior or hidden malware. USB devices have many properties and capabilities that have become the subject of malicious operations. Many of the recent attacks targeting individuals, and especially organizations, utilize popular and widely used USB devices, such as mice, keyboards, flash drives, printers, and smartphones. However, current detection tools, techniques, and solutions generally fail to detect both the known and unknown attacks launched via USB devices. Significance: We propose USBWARE, a project that focuses on the vulnerabilities of USB devices and centers on the development of a comprehensive detection framework that relies upon a crucial attack repository. USBWARE will allow researchers and companies to better understand the vulnerabilities and attacks associated with USB devices as well as providing a comprehensive platform for developing detection solutions. Methodology: The framework of USBWARE is aimed at accurate detection of both known and unknown USB-based attacks by a process that efficiently enhances the framework's detection capabilities over time. The framework will integrate two main security approaches in order to enhance the detection of USB-based attacks associated with a variety of USB devices. The first approach is aimed at the detection of known attacks and their variants, whereas the second approach focuses on the detection of unknown attacks. USBWARE will consist of six independent but complimentary detection modules, each detecting attacks based on a different approach or discipline. These modules include novel ideas and algorithms inspired from or already developed within our team's domains of expertise, including cyber security, electrical and signal processing, machine learning, and computational biology. The establishment and maintenance of the USBWARE’s dynamic and up-to-date attack repository will strengthen the capabilities of the USBWARE detection framework. The attack repository’s infrastructure will enable researchers to record, document, create, and simulate existing and new USB-based attacks. This data will be used to maintain the detection framework’s updatability by incorporating knowledge regarding new attacks. Based on our experience in the cyber security domain, we aim to design the USBWARE framework so that it will have several characteristics that are crucial for this type of cyber-security detection solution. Specifically, the USBWARE framework should be: Novel, Multidisciplinary, Trusted, Lightweight, Extendable, Modular and Updatable and Adaptable. Major Findings: Based on our initial survey, we have already found more than 23 types of USB-based attacks, divided into six major categories. Our preliminary evaluation and proof of concepts showed that our detection modules can be used for efficient detection of several basic known USB attacks. Further research, development, and enhancements are required so that USBWARE will be capable to cover all of the major known USB attacks and to detect unknown attacks. Conclusion: USBWARE is a crucial detection framework that must be further enhanced and developed.Keywords: USB, device, cyber security, attack, detection
Procedia PDF Downloads 3981093 Using the ISO 9705 Room Corner Test for Smoke Toxicity Quantification of Polyurethane
Authors: Gabrielle Peck, Ryan Hayes
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Polyurethane (PU) foam is typically sold as acoustic foam that is often used as sound insulation in settings such as night clubs and bars. As a construction product, PU is tested by being glued to the walls and ceiling of the ISO 9705 room corner test room. However, when heat is applied to PU foam, it melts and burns as a pool fire due to it being a thermoplastic. The current test layout is unable to accurately measure mass loss and doesn’t allow for the material to burn as a pool fire without seeping out of the test room floor. The lack of mass loss measurement means gas yields pertaining to smoke toxicity analysis can’t be calculated, which makes data comparisons from any other material or test method difficult. Additionally, the heat release measurements are not representative of the actual measurements taken as a lot of the material seeps through the floor (when a tray to catch the melted material is not used). This research aimed to modify the ISO 9705 test to provide the ability to measure mass loss to allow for better calculation of gas yields and understanding of decomposition. It also aimed to accurately measure smoke toxicity in both the doorway and duct and enable dilution factors to be calculated. Finally, the study aimed to examine if doubling the fuel loading would force under-ventilated flaming. The test layout was modified to be a combination of the SBI (single burning item) test set up inside oof the ISO 9705 test room. Polyurethane was tested in two different ways with the aim of altering the ventilation condition of the tests. Test one was conducted using 1 x SBI test rig aiming for well-ventilated flaming. Test two was conducted using 2 x SBI rigs (facing each other inside the test room) (doubling the fuel loading) aiming for under-ventilated flaming. The two different configurations used were successful in achieving both well-ventilated flaming and under-ventilated flaming, shown by the measured equivalence ratios (measured using a phi meter designed and created for these experiments). The findings show that doubling the fuel loading will successfully force under-ventilated flaming conditions to be achieved. This method can therefore be used when trying to replicate post-flashover conditions in future ISO 9705 room corner tests. The radiative heat generated by the two SBI rigs facing each other facilitated a much higher overall heat release resulting in a more severe fire. The method successfully allowed for accurate measurement of smoke toxicity produced from the PU foam in terms of simple gases such as oxygen depletion, CO and CO2. Overall, the proposed test modifications improve the ability to measure the smoke toxicity of materials in different fire conditions on a large-scale.Keywords: flammability, ISO9705, large-scale testing, polyurethane, smoke toxicity
Procedia PDF Downloads 761092 Empowering Learners: From Augmented Reality to Shared Leadership
Authors: Vilma Zydziunaite, Monika Kelpsiene
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In early childhood and preschool education, play has an important role in learning and cognitive processes. In the context of a changing world, personal autonomy and the use of technology are becoming increasingly important for the development of a wide range of learner competencies. By integrating technology into learning environments, the educational reality is changed, promoting unusual learning experiences for children through play-based activities. Alongside this, teachers are challenged to develop encouragement and motivation strategies that empower children to act independently. The aim of the study was to reveal the changes in the roles and experiences of teachers in the application of AR technology for the enrichment of the learning process. A quantitative research approach was used to conduct the study. The data was collected through an electronic questionnaire. Participants: 319 teachers of 5-6-year-old children using AR technology tools in their educational process. Methods of data analysis: Cronbach alpha, descriptive statistical analysis, normal distribution analysis, correlation analysis, regression analysis (SPSS software). Results. The results of the study show a significant relationship between children's learning and the educational process modeled by the teacher. The strongest predictor of child learning was found to be related to the role of the educator. Other predictors, such as pedagogical strategies, the concept of AR technology, and areas of children's education, have no significant relationship with child learning. The role of the educator was found to be a strong determinant of the child's learning process. Conclusions. The greatest potential for integrating AR technology into the teaching-learning process is revealed in collaborative learning. Teachers identified that when integrating AR technology into the educational process, they encourage children to learn from each other, develop problem-solving skills, and create inclusive learning contexts. A significant relationship has emerged - how the changing role of the teacher relates to the child's learning style and the aspiration for personal leadership and responsibility for their learning. Teachers identified the following key roles: observer of the learning process, proactive moderator, and creator of the educational context. All these roles enable the learner to become an autonomous and active participant in the learning process. This provides a better understanding and explanation of why it becomes crucial to empower the learner to experiment, explore, discover, actively create, and foster collaborative learning in the design and implementation of the educational content, also for teachers to integrate AR technologies and the application of the principles of shared leadership. No statistically significant relationship was found between the understanding of the definition of AR technology and the teacher’s choice of role in the learning process. However, teachers reported that their understanding of the definition of AR technology influences their choice of role, which has an impact on children's learning.Keywords: teacher, learner, augmented reality, collaboration, shared leadership, preschool education
Procedia PDF Downloads 401091 Enhanced Furfural Extraction from Aqueous Media Using Neoteric Hydrophobic Solvents
Authors: Ahmad S. Darwish, Tarek Lemaoui, Hanifa Taher, Inas M. AlNashef, Fawzi Banat
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This research reports a systematic top-down approach for designing neoteric hydrophobic solvents –particularly, deep eutectic solvents (DES) and ionic liquids (IL)– as furfural extractants from aqueous media for the application of sustainable biomass conversion. The first stage of the framework entailed screening 32 neoteric solvents to determine their efficacy against toluene as the application’s conventional benchmark for comparison. The selection criteria for the best solvents encompassed not only their efficiency in extracting furfural but also low viscosity and minimal toxicity levels. Additionally, for the DESs, their natural origins, availability, and biodegradability were also taken into account. From the screening pool, two neoteric solvents were selected: thymol:decanoic acid 1:1 (Thy:DecA) and trihexyltetradecyl phosphonium bis(trifluoromethylsulfonyl) imide [P₁₄,₆,₆,₆][NTf₂]. These solvents outperformed the toluene benchmark, achieving efficiencies of 94.1% and 97.1% respectively, compared to toluene’s 81.2%, while also possessing the desired properties. These solvents were then characterized thoroughly in terms of their physical properties, thermal properties, critical properties, and cross-contamination solubilities. The selected neoteric solvents were then extensively tested under various operating conditions, and an exceptional stable performance was exhibited, maintaining high efficiency across a broad range of temperatures (15–100 °C), pH levels (1–13), and furfural concentrations (0.1–2.0 wt%) with a remarkable equilibrium time of only 2 minutes, and most notably, demonstrated high efficiencies even at low solvent-to-feed ratios. The durability of the neoteric solvents was also validated to be stable over multiple extraction-regeneration cycles, with limited leachability to the aqueous phase (≈0.1%). Moreover, the extraction performance of the solvents was then modeled through machine learning, specifically multiple non-linear regression (MNLR) and artificial neural networks (ANN). The models demonstrated high accuracy, indicated by their low absolute average relative deviations with values of 2.74% and 2.28% for Thy:DecA and [P₁₄,₆,₆,₆][NTf₂], respectively, using MNLR, and 0.10% for Thy:DecA and 0.41% for [P₁₄,₆,₆,₆][NTf₂] using ANN, highlighting the significantly enhanced predictive accuracy of the ANN. The neoteric solvents presented herein offer noteworthy advantages over traditional organic solvents, including their high efficiency in both extraction and regeneration processes, their stability and minimal leachability, making them particularly suitable for applications involving aqueous media. Moreover, these solvents are more environmentally friendly, incorporating renewable and sustainable components like thymol and decanoic acid. This exceptional efficacy of the newly developed neoteric solvents signifies a significant advancement, providing a green and sustainable alternative for furfural production from biowaste.Keywords: sustainable biomass conversion, furfural extraction, ionic liquids, deep eutectic solvents
Procedia PDF Downloads 701090 Preparation of Papers - Developing a Leukemia Diagnostic System Based on Hybrid Deep Learning Architectures in Actual Clinical Environments
Authors: Skyler Kim
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An early diagnosis of leukemia has always been a challenge to doctors and hematologists. On a worldwide basis, it was reported that there were approximately 350,000 new cases in 2012, and diagnosing leukemia was time-consuming and inefficient because of an endemic shortage of flow cytometry equipment in current clinical practice. As the number of medical diagnosis tools increased and a large volume of high-quality data was produced, there was an urgent need for more advanced data analysis methods. One of these methods was the AI approach. This approach has become a major trend in recent years, and several research groups have been working on developing these diagnostic models. However, designing and implementing a leukemia diagnostic system in real clinical environments based on a deep learning approach with larger sets remains complex. Leukemia is a major hematological malignancy that results in mortality and morbidity throughout different ages. We decided to select acute lymphocytic leukemia to develop our diagnostic system since acute lymphocytic leukemia is the most common type of leukemia, accounting for 74% of all children diagnosed with leukemia. The results from this development work can be applied to all other types of leukemia. To develop our model, the Kaggle dataset was used, which consists of 15135 total images, 8491 of these are images of abnormal cells, and 5398 images are normal. In this paper, we design and implement a leukemia diagnostic system in a real clinical environment based on deep learning approaches with larger sets. The proposed diagnostic system has the function of detecting and classifying leukemia. Different from other AI approaches, we explore hybrid architectures to improve the current performance. First, we developed two independent convolutional neural network models: VGG19 and ResNet50. Then, using both VGG19 and ResNet50, we developed a hybrid deep learning architecture employing transfer learning techniques to extract features from each input image. In our approach, fusing the features from specific abstraction layers can be deemed as auxiliary features and lead to further improvement of the classification accuracy. In this approach, features extracted from the lower levels are combined into higher dimension feature maps to help improve the discriminative capability of intermediate features and also overcome the problem of network gradient vanishing or exploding. By comparing VGG19 and ResNet50 and the proposed hybrid model, we concluded that the hybrid model had a significant advantage in accuracy. The detailed results of each model’s performance and their pros and cons will be presented in the conference.Keywords: acute lymphoblastic leukemia, hybrid model, leukemia diagnostic system, machine learning
Procedia PDF Downloads 1871089 The Impact of Physical Exercise on Gestational Diabetes and Maternal Weight Management: A Meta-Analysis
Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei
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Physiological changes during pregnancy, such as alterations in the circulatory, respiratory, and musculoskeletal systems, can negatively impact daily physical activity. This reduced activity is often associated with an increased risk of adverse maternal health outcomes, particularly gestational diabetes mellitus (GDM) and excessive weight gain. This meta-analysis aims to evaluate the effectiveness of structured physical exercise interventions during pregnancy in reducing the risk of GDM and managing maternal weight gain. A comprehensive search was conducted across six major databases: PubMed, Cochrane Library, EMBASE, Web of Science, ScienceDirect, and ClinicalTrials.gov, covering the period from database inception until 2023. Randomized controlled trials (RCTs) that explored the effects of physical exercise programs on pregnant women with low physical activity levels were included. The search was performed using EndNote and results were managed using RevMan (Review Manager) for meta-analysis. RCTs involving healthy pregnant women with low levels of physical activity or sedentary lifestyles were selected. These RCTs must have incorporated structured exercise programs during pregnancy and reported on outcomes related to GDM and maternal weight gain. From an initial pool of 5,112 articles, 65 RCTs (involving 11,400 pregnant women) met the inclusion criteria. Data extraction was performed, followed by a quality assessment of the selected studies using the Cochrane Risk of Bias tool. The meta-analysis was conducted using RevMan software, where pooled relative risks (RR) and weighted mean differences (WMD) were calculated using a random-effects model to address heterogeneity across studies. Sensitivity analyses, subgroup analyses (based on factors such as exercise intensity, duration, and pregnancy stage), and publication bias assessments were also conducted. Structured physical exercise during pregnancy led to a significant reduction in the risk of developing GDM (RR = 0.68; P < 0.001), particularly when the exercise program was performed throughout the pregnancy (RR = 0.62; P = 0.035). In addition, maternal weight gain was significantly reduced (WMD = −1.18 kg; 95% CI −1.54 to −0.85; P < 0.001). There were no significant adverse effects reported for either the mother or the neonate, confirming that exercise interventions are safe for both. This meta-analysis highlights the positive impact of regular moderate physical activity during pregnancy in reducing the risk of GDM and managing maternal weight gain. These findings suggest that physical exercise should be encouraged as a routine part of prenatal care. However, more research is required to refine exercise recommendations and determine the most effective interventions based on individual risk factors and pregnancy stages.Keywords: gestational diabetes, maternal weight management, meta-analysis, randomized controlled trials
Procedia PDF Downloads 111088 Beginning Physics Experiments Class Using Multi Media in National University of Laos
Authors: T. Nagata, S. Xaphakdy, P. Souvannavong, P. Chanthamaly, K. Sithavong, C. H. Lee, S. Phommathat, V. Srithilat, P. Sengdala, B. Phetarnousone, B. Siharath, X. Chemcheng, T. Yamaguchi, A. Suenaga, S. Kashima
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National University of Laos (NUOL) requested Japan International Cooperation Agency (JICA) volunteers to begin a physics experiments class using multi media. However, there are issues. NUOL had no physics experiment class, no space for physics experiments, experiment materials were not used for many years and were scattered in various places, and there is no projector and laptop computer in the unit. This raised the question: How do authors begin the physics experiments class using multimedia? To solve this problem, the JICA took some steps, took stock of what was available and reviewed the syllabus. The JICA then revised the experiment materials to assess what was available and then developed textbooks for experiments using them; however, the question remained, what about the multimedia component of the course? Next, the JICA reviewed Physics teacher Pavy Souvannavong’s YouTube channel, where he and his students upload video reports of their physics classes at NUOL using their smartphones. While they use multi-media, almost all the videos recorded were of class presentations. To improve the multimedia style, authors edited the videos in the style of another YouTube channel, “Science for Lao,” which is a science education group made up of Japan Overseas Cooperation Volunteers (JOCV) in Laos. They created the channel to enhance science education in Laos, and hold regular monthly meetings in the capital, Vientiane, and at teacher training colleges in the country. They edit the video clips in three parts, which are the materials and procedures part including pictures, practice footage of the experiment part, and then the result and conclusion part. Then students perform experiments and prepare for presentation by following the videos. The revised experiment presentation reports use PowerPoint presentations, material pictures and experiment video clips. As for providing textbooks and submitting reports, the students use the e-Learning system of “Moodle” of the Information Technology Center in Dongdok campus of NUOL. The Korean International Cooperation Agency (KOICA) donated those facilities. The authors have passed the process of the revised materials, developed textbooks, the PowerPoint slides presented by students, downloaded textbooks and uploaded reports, to begin the physics experiments class using multimedia. This is the practice research report for beginning a physics experiments class using multimedia in the physics unit at the Department of Natural Science, Faculty of Education, at the NUOL.Keywords: NUOL, JICA, KOICA, physics experiment materials, smartphone, Moodle, IT center, Science for Lao
Procedia PDF Downloads 3531087 Biocompatibility of Calcium Phosphate Coatings With Different Crystallinity Deposited by Sputtering
Authors: Ekaterina S. Marchenko, Gulsharat A. Baigonakova, Kirill M. Dubovikov, Igor A. Khlusov
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NiTi alloys combine biomechanical and biochemical properties. This makes them a perfect candidate for medical applications. However, there is a serious problem with these alloys, such as the release of Ni from the matrix. Ni ions are known to be toxic to living tissues and leach from the matrix into the surrounding implant tissues due to corrosion after prolonged use. To prevent the release of Ni ions, corrosive strong coatings are usually used. Titanium nitride-based coatings are perfect corrosion inhibitors and also have good bioactive properties. However, there is an opportunity to improve the biochemical compatibility of the surface by depositing another layer. This layer can consist of elements such as calcium and phosphorus. The Ca and P ions form different calcium phosphate phases, which are present in the mineral part of human bones. We therefore believe that these elements must promote osteogenesis and osteointegration. In view of the above, the aim of this study is to investigate the effect of crystallinity on the biocompatibility of a two-layer coating deposited on NiTi substrate by sputtering. The first step of the research, apart from the NiTi polishing, is the layer-by-layer deposition of Ti-Ni-Ti by magnetron sputtering and the subsequent synthesis of this composite in an N atmosphere at 900 °C. The total thickness of the corrosion resistant layer is 150 nm. Plasma assisted RF sputtering was then used to deposit a bioactive film on the titanium nitride layer. A Ca-P powder target was used to obtain such a film. We deposited three types of Ca-P layers with different crystallinity and compared them in terms of cytotoxicity. One group of samples had no Ca-P coating and was used as a control. We obtained different crystallinity by varying the sputtering parameters such as bias voltage, plasma source current and pressure. XRD analysis showed that all coatings are calcium phosphate, but the sample obtained at maximum bias and plasma source current and minimum pressure has the most intense peaks from the coating phase. SEM and EDS showed that all three coatings have a homogeneous and dense structure without cracks and consist of calcium, phosphorus and oxygen. Cytotoxic tests carried out on three types of samples with Ca-P coatings and a control group showed that the control sample and the sample with Ca-P coating obtained at maximum bias voltage and plasma source current and minimum pressure had the lowest number of dead cells on the surface, around 11 ± 4%. Two other types of samples with Ca-P coating have 40 ± 9% and 21 ± 7% dead cells on the surface. It can therefore be concluded that these two sputtering modes have a negative effect on the corrosion resistance of the whole samples. The third sputtering mode does not affect the corrosion resistance and has the same level of cytotoxicity as the control. It can be concluded that the most suitable sputtering mode is the third with maximum bias voltage and plasma source current and minimum pressure.Keywords: calcium phosphate coating, cytotoxicity, NiTi alloy, two-layer coating
Procedia PDF Downloads 661086 Cognition in Context: Investigating the Impact of Persuasive Outcomes across Face-to-Face, Social Media and Virtual Reality Environments
Authors: Claire Tranter, Coral Dando
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Gathering information from others is a fundamental goal for those concerned with investigating crime, and protecting national and international security. Persuading an individual to move from an opposing to converging viewpoint, and an understanding on the cognitive style behind this change can serve to increase understanding of traditional face-to-face interactions, as well as synthetic environments (SEs) often used for communication across varying geographical locations. SEs are growing in usage, and with this increase comes an increase in crime being undertaken online. Communication technologies can allow people to mask their real identities, supporting anonymous communication which can raise significant challenges for investigators when monitoring and managing these conversations inside SEs. To date, the psychological literature concerning how to maximise information-gain in SEs for real-world interviewing purposes is sparse, and as such this aspect of social cognition is not well understood. Here, we introduce an overview of a novel programme of PhD research which seeks to enhance understanding of cross-cultural and cross-gender communication in SEs for maximising information gain. Utilising a dyadic jury paradigm, participants interacted with a confederate who attempted to persuade them to the opposing verdict across three distinct environments: face-to-face, instant messaging, and a novel virtual reality environment utilising avatars. Participants discussed a criminal scenario, acting as a two-person (male; female) jury. Persuasion was manipulated by the confederate claiming an opposing viewpoint (guilty v. not guilty) to the naïve participants from the outset. Pre and post discussion data, and observational digital recordings (voice and video) of participant’ discussion performance was collected. Information regarding cognitive style was also collected to ascertain participants need for cognitive closure and biases towards jumping to conclusions. Findings revealed that individuals communicating via an avatar in a virtual reality environment reacted in a similar way, and thus equally persuasive, when compared to individuals communicating face-to-face. Anonymous instant messaging however created a resistance to persuasion in participants, with males showing a significant decline in persuasive outcomes compared to face to face. The findings reveal new insights particularly regarding the interplay of persuasion on gender and modality, with anonymous instant messaging enhancing resistance to persuasion attempts. This study illuminates how varying SE can support new theoretical and applied understandings of how judgments are formed and modified in response to advocacy.Keywords: applied cognition, persuasion, social media, virtual reality
Procedia PDF Downloads 1441085 Ensemble Machine Learning Approach for Estimating Missing Data from CO₂ Time Series
Authors: Atbin Mahabbati, Jason Beringer, Matthias Leopold
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To address the global challenges of climate and environmental changes, there is a need for quantifying and reducing uncertainties in environmental data, including observations of carbon, water, and energy. Global eddy covariance flux tower networks (FLUXNET), and their regional counterparts (i.e., OzFlux, AmeriFlux, China Flux, etc.) were established in the late 1990s and early 2000s to address the demand. Despite the capability of eddy covariance in validating process modelling analyses, field surveys and remote sensing assessments, there are some serious concerns regarding the challenges associated with the technique, e.g. data gaps and uncertainties. To address these concerns, this research has developed an ensemble model to fill the data gaps of CO₂ flux to avoid the limitations of using a single algorithm, and therefore, provide less error and decline the uncertainties associated with the gap-filling process. In this study, the data of five towers in the OzFlux Network (Alice Springs Mulga, Calperum, Gingin, Howard Springs and Tumbarumba) during 2013 were used to develop an ensemble machine learning model, using five feedforward neural networks (FFNN) with different structures combined with an eXtreme Gradient Boosting (XGB) algorithm. The former methods, FFNN, provided the primary estimations in the first layer, while the later, XGB, used the outputs of the first layer as its input to provide the final estimations of CO₂ flux. The introduced model showed slight superiority over each single FFNN and the XGB, while each of these two methods was used individually, overall RMSE: 2.64, 2.91, and 3.54 g C m⁻² yr⁻¹ respectively (3.54 provided by the best FFNN). The most significant improvement happened to the estimation of the extreme diurnal values (during midday and sunrise), as well as nocturnal estimations, which is generally considered as one of the most challenging parts of CO₂ flux gap-filling. The towers, as well as seasonality, showed different levels of sensitivity to improvements provided by the ensemble model. For instance, Tumbarumba showed more sensitivity compared to Calperum, where the differences between the Ensemble model on the one hand and the FFNNs and XGB, on the other hand, were the least of all 5 sites. Besides, the performance difference between the ensemble model and its components individually were more significant during the warm season (Jan, Feb, Mar, Oct, Nov, and Dec) compared to the cold season (Apr, May, Jun, Jul, Aug, and Sep) due to the higher amount of photosynthesis of plants, which led to a larger range of CO₂ exchange. In conclusion, the introduced ensemble model slightly improved the accuracy of CO₂ flux gap-filling and robustness of the model. Therefore, using ensemble machine learning models is potentially capable of improving data estimation and regression outcome when it seems to be no more room for improvement while using a single algorithm.Keywords: carbon flux, Eddy covariance, extreme gradient boosting, gap-filling comparison, hybrid model, OzFlux network
Procedia PDF Downloads 1391084 Processing, Nutritional Assessment and Sensory Evaluation of Bakery Products Prepared from Orange Fleshed Sweet Potatoes (OFSP) and Wheat Composite Flours
Authors: Hategekimana Jean Paul, Irakoze Josiane, Ishimweyizerwe Valentin, Iradukunda Dieudonne, Uwanyirigira Jeannette
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Orange fleshed sweet potatoes (OFSP) are highly grown and are available plenty in rural and urban local markets and its contribution in reduction of food insecurity in Rwanda is considerable. But the postharvest loss of this commodity is a critical challenge due to its high perishability. Several research activities have been conducted on how fresh food commodities can be transformed into extended shelf life food products for prevention of post-harvest losses. However, such activity was not yet well studied in Rwanda. The aim of the present study was the processing of backed products from (OFSP)combined with wheat composite flour and assess the nutritional content and consumer acceptability of new developed products. The perishability of OFSP and their related lack during off season can be eradicated by producing cake, doughnut and bread with OFSP puree or flour. The processing for doughnut and bread were made by making OFSP puree and other ingredients then a dough was made followed by frying and baking while for cake OFSP was dried through solar dryer to have a flour together with wheat flour and other ingredients to make dough cake and baking. For each product, one control and three experimental samples, (three products in three different ratios (30,40 and50%) of OFSP and the remaining percentage of wheat flour) were prepared. All samples including the control were analyzed for the consumer acceptability (sensory attributes). Most preferred samples (One sample for each product with its control sample and for each OFSP variety) were analyzed for nutritional composition along with control sample. The Cake from Terimbere variety and Bread from Gihingumukungu supplemented with 50% OFSP flour or Puree respectively were most acceptable except Doughnut from Vita variety which was highly accepted at 50% of OFSP supplementation. The moisture, ash, protein, fat, fiber, Total carbohydrate, Vitamin C, reducing sugar and minerals (Sodium, Potassium and Phosphorus.) content was different among products. Cake was rich in fibers (14.71%), protein (6.590%), and vitamin c(19.988mg/100g) compared to other samples while bread found to be rich in reducing sugar with 12.71mg/100g compared to cake and doughnut. Also doughnut was found to be rich in fat content with 6.89% compared to other samples. For sensory analysis, doughnut was highly accepted in ratio of 60:40 compared to other products while cake was least accepted at ratio of 50:50. The Proximate composition and minerals content of all the OFSP products were significantly higher as compared to the control samples.Keywords: post-harvest loss, OFSP products, wheat flour, sensory evaluation, proximate composition
Procedia PDF Downloads 621083 The Impact of Team Heterogeneity and Team Reflexivity on Entrepreneurial Decision -Making - Empirical Study in China
Authors: Chang Liu, Rui Xing, Liyan Tang, Guohong Wang
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Entrepreneurial actions are based on entrepreneurial decisions. The quality of decisions influences entrepreneurial activities and subsequent new venture performance. Uncertainty of surroundings put heightened demands on the team as a whole, and each team member. Diverse team composition provides rich information, which a team can draw when making complex decisions. However, team heterogeneity may cause emotional conflicts, which is adverse to team outcomes. Thus, the effects of team heterogeneity on team outcomes are complex. Although team heterogeneity is an essential factor influencing entrepreneurial decision-making, there is a lack of empirical analysis on under what conditions team heterogeneity plays a positive role in promoting decision-making quality. Entrepreneurial teams always struggle with complex tasks. How a team shapes its teamwork is key in resolving constant issues. As a collective regulatory process, team reflexivity is characterized by continuous joint evaluation and discussion of team goals, strategies, and processes, and adapt them to current or anticipated circumstances. It enables diversified information to be shared and overtly discussed. Instead of hostile interpretation of opposite opinions team members take them as useful insights from different perspectives. Team reflexivity leads to better integration of expertise to avoid the interference of negative emotions and conflict. Therefore, we propose that team reflexivity is a conditional factor that influences the impact of team heterogeneity on high-quality entrepreneurial decisions. In this study, we identify team heterogeneity as a crucial determinant of entrepreneurial decision quality. Integrating the literature on decision-making and team heterogeneity, we investigate the relationship between team heterogeneity and entrepreneurial decision-making quality, treating team reflexivity as a moderator. We tested our hypotheses using the hierarchical regression method and the data gathered from 63 teams and 205 individual members from 45 new firms in China's first-tier cities such as Beijing, Shanghai, and Shenzhen. This research found that both teams' education heterogeneity and teams' functional background heterogeneity were significantly positively related to entrepreneurial decision-making quality, and the positive relation was stronger in teams with a high level of team reflexivity. While teams' specialization of education heterogeneity was negatively related to decision-making quality, and the negative relationship was weaker in teams with a high level of team reflexivity. We offer two contributions to decision-making and entrepreneurial team literatures. Firstly, our study enriches the understanding of the role of entrepreneurial team heterogeneity in entrepreneurial decision-making quality. Different from previous entrepreneurial decision-making literatures, which focus more on decision-making modes of entrepreneurs and the top management team, this study is a significant attempt to highlight that entrepreneurial team heterogeneity makes a unique contribution to generating high-quality entrepreneurial decisions. Secondly, this study introduced team reflexivity as the moderating variable, to explore the boundary conditions under which the entrepreneurial team heterogeneity play their roles.Keywords: decision-making quality, entrepreneurial teams, education heterogeneity, functional background heterogeneity, specialization of education heterogeneity
Procedia PDF Downloads 1191082 Hardware Implementation on Field Programmable Gate Array of Two-Stage Algorithm for Rough Set Reduct Generation
Authors: Tomasz Grzes, Maciej Kopczynski, Jaroslaw Stepaniuk
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The rough sets theory developed by Prof. Z. Pawlak is one of the tools that can be used in the intelligent systems for data analysis and processing. Banking, medicine, image recognition and security are among the possible fields of utilization. In all these fields, the amount of the collected data is increasing quickly, but with the increase of the data, the computation speed becomes the critical factor. Data reduction is one of the solutions to this problem. Removing the redundancy in the rough sets can be achieved with the reduct. A lot of algorithms of generating the reduct were developed, but most of them are only software implementations, therefore have many limitations. Microprocessor uses the fixed word length, consumes a lot of time for either fetching as well as processing of the instruction and data; consequently, the software based implementations are relatively slow. Hardware systems don’t have these limitations and can process the data faster than a software. Reduct is the subset of the decision attributes that provides the discernibility of the objects. For the given decision table there can be more than one reduct. Core is the set of all indispensable condition attributes. None of its elements can be removed without affecting the classification power of all condition attributes. Moreover, every reduct consists of all the attributes from the core. In this paper, the hardware implementation of the two-stage greedy algorithm to find the one reduct is presented. The decision table is used as an input. Output of the algorithm is the superreduct which is the reduct with some additional removable attributes. First stage of the algorithm is calculating the core using the discernibility matrix. Second stage is generating the superreduct by enriching the core with the most common attributes, i.e., attributes that are more frequent in the decision table. Described above algorithm has two disadvantages: i) generating the superreduct instead of reduct, ii) additional first stage may be unnecessary if the core is empty. But for the systems focused on the fast computation of the reduct the first disadvantage is not the key problem. The core calculation can be achieved with a combinational logic block, and thus add respectively little time to the whole process. Algorithm presented in this paper was implemented in Field Programmable Gate Array (FPGA) as a digital device consisting of blocks that process the data in a single step. Calculating the core is done by the comparators connected to the block called 'singleton detector', which detects if the input word contains only single 'one'. Calculating the number of occurrences of the attribute is performed in the combinational block made up of the cascade of the adders. The superreduct generation process is iterative and thus needs the sequential circuit for controlling the calculations. For the research purpose, the algorithm was also implemented in C language and run on a PC. The times of execution of the reduct calculation in a hardware and software were considered. Results show increase in the speed of data processing.Keywords: data reduction, digital systems design, field programmable gate array (FPGA), reduct, rough set
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