Search results for: metallurgical image processing

Authors: Hsiu-Chuan Hsueh, Kuei-Feng Shen Jr., Chia-Ling Chao, Hui-Chuan Pan

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This article described a 75 years old woman who has suffered from intestinal perforation and accepted surgery with temporary enterostomy, the operation makes her depressed, refused relatives and friend's care, facing low willingness to participate in various activities due to fear of changing body appearance caused by surgery and leave enterostomy. The author collected information through observation talks, physical evaluation, and medical records during the period of care from November 14 to November 30, 2016, we used the four aspects of physiology, psychology, society and spirituality as a whole sexual assessment to establish the nursing problems of patient, included of acute pain, disturbance of body image,coping ineffective individual. For patient care issues, to encouraged case to express their inner feelings and take part in self-care programs through providing good therapeutic interpersonal relationships with their families. However, it provided clear information about the disease and follow-up treatment plan, give compliments in a timely manner, enhanced self-confidence of individual cases and their motivation to participate in self-care of stoma, further face the disease in a positive manner. At the same time, cross-section team care model and individual care measures were developed to enhance the care skills after returning home and at the same time assist the individual in facing the psychological impact caused by stoma. Hope to provide this experience, as a reference for the future care of the disease.

Keywords: enterostomy, intestinal perforation, nursing experience, ostomy

Procedia PDF Downloads 139

Authors: Rodrigo T. Sepulveda-Hirose, Ana B. Carrera-Aguilar, Francisco Andree Ramirez-Casas, Alondra Orozco-Gomez, Miguel Angel Sanchez-Caro, Carlos Herrera-Ventosa

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High concentrations of particulate matter in the atmosphere pose a threat to human health, especially over areas with high concentrations of population; however, field air pollution monitoring is expensive and time-consuming. In order to achieve reduced costs and global coverage of the whole urban area, remote sensing can be used. This study evaluates PM2.5 concentrations, over the Mexico City´s metropolitan area, are estimated using atmospheric reflectance from LANDSAT 8, satellite imagery and historical PM2.5 measurements of the Automatic Environmental Monitoring Network of Mexico City (RAMA). Through the processing of the available satellite images, a preliminary model was generated to evaluate the optimal bands for the generation of the final model for Mexico City. Work on the final model continues with the results of the preliminary model. It was found that infrared bands have helped to model in other cities, but the effectiveness that these bands could provide for the geographic and climatic conditions of Mexico City is still being evaluated.

Keywords: air pollution modeling, Landsat 8, PM2.5, remote sensing

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Authors: Iftikhar Ahmad, Mohammad Islam

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Thermally exfoliated graphene nanomaterial was reinforced into Al2O3 ceramic and the nanocomposites were consolidated using rapid high-frequency induction heat sintering route. The resulting nanocomposites demonstrated higher mechanical properties due to efficient GNS incorporation and chemical interaction with the Al2O3 matrix grains. The enhancement in mechanical properties is attributed to (i) uniformly-dispersed GNS in the consolidated structure (ii) ability of GNS to decorate Al2O3 nanoparticles and (iii) strong GNS/Al2O3 chemical interaction during colloidal mixing and pullout/crack bridging toughening mechanisms during mechanical testing. The GNS/Al2O3 interaction during different processing stages was thoroughly examined by thermal and structural investigation of the interfacial area. The formation of an intermediate aluminum oxycarbide phase (Al2OC) via a confined carbothermal reduction reaction at the GNS/Al2O3 interface was observed using advanced electron microscopes. The GNS surface roughness improves GNS/Al2O3 mechanical locking and chemical compatibility. The sturdy interface phase facilitates efficient load transfer and delayed failure through impediment of crack propagation. The resulting nanocomposites, therefore, offer superior toughness.

Keywords: ceramics, nanocomposites, interfaces, nanostructures, electron microscopy, Al2O3

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Authors: Arnab Mondal, Sanjeev Kumar Sharma, Ranjit Kumar Upadhyay

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We study the spatiotemporal dynamics of a neuronal cable. The processes of one- dimensional (1D) and 2D diffusion are considered for a single variable, which is the membrane voltage, i.e., membrane voltage diffusively interacts for spatiotemporal pattern formalism. The recovery and other variables interact through the membrane voltage. A 3D Leech-Heart (LH) model is introduced to investigate the nonlinear responses of an excitable neuronal cable. The deterministic LH model shows different types of firing properties. We explore the parameter space of the uncoupled LH model and based on the bifurcation diagram, considering v_k2_ashift as a bifurcation parameter, we analyze the 1D diffusion dynamics in three regimes: bursting, regular spiking, and a quiescent state. Depending on parameters, it is shown that the diffusive system may generate regular and irregular bursting or spiking behavior. Further, it is explored a 2D diffusion acting on the membrane voltage, where different types of patterns can be observed. The results show that the LH neurons with different firing characteristics depending on the control parameters participate in a collective behavior of an information processing system that depends on the overall network.

Keywords: bifurcation, pattern formation, spatio-temporal dynamics, stability analysis

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Authors: Jin-Hui Lee, Myung-Min Oh

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The application of temporary abiotic stresses before crop harvest is a potential strategy to enhance phytochemical content. The objective of this study was to determine the effect of various UV-A LED lights on the growth and content of bioactive compounds in kale (Brassica oleracea var. acephala). Fourteen-day-old kale seedlings were cultivated in a plant factory with artificial lighting (air temperature of 20℃, relative humidity of 60%, photosynthesis photon flux density (PPFD) of 125 µmol·m⁻²·s⁻¹) for 3 weeks. Kale plants were irradiated by four types of UV-A LEDs (peak wavelength; 365, 375, 385, and 395 nm) with 30 W/m² for 7 days. As a result, image chlorophyll fluorescence (Fv/Fm) value of kale leaves was lower as the UV-A LEDs peak wavelength was shorter. Fresh and dry weights of shoots and roots of kale plants were significantly higher in the plants under UV-A than the control at 7 days of treatment. In particular, the growth was significantly increased with a longer peak wavelength of the UV-A LEDs. The results of leaf area and specific leaf weight showed a similar pattern with those of growth characteristics. Chlorophyll content was highest in kale leaves subjected to UV-A LEDs with the peak wavelength of 395 nm at 3 days of treatment compared with the control. Total phenolic contents of UV-A LEDs with the peak wavelength of 395 nm at 5 and 6 days of treatment were 44% and 47% higher than those of the control, respectively. Antioxidant capacity showed almost the same pattern as the results of total phenol content. The activity of phenylalanine ammonia-lyase was approximately 11% and 8% higher in the UV-A LEDs with the peak wavelength of 395 nm compared to the control at 5 and 6 days of treatment, respectively. Our results imply that the UV-A LEDs with relative longer peak wavelength were effective to improve growth as well as the content of bioactive compounds of kale plants.

Keywords: bioactive compounds, growth, Kale, UV-A LEDs

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Authors: Robertoes K. K. Wibowo, Siswoyo Soekarno, Irma Puspitasari

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Indonesian people use trains for their transportation, especially they use economy class train transportation because it is cheaper and has a more precise schedule than any other ground transportation. Nevertheless, the economy class passenger seat raises some inconvenience issues for passengers. This is due to the design of the chair on the economic class of trains that did not adjusted to the shape of anthropometry of Indonesian people. Thus, research needs to be conducted on the design of the seats in the economic class of trains. The purpose of this research is to make the design of economy class passenger seats ergonomic. This research method uses questionnaires and anthropometry measurements. The data obtained is processed using House of Quality of Ergonomic Function Development. From the results of analysis and data processing were obtained important changes from the original design. Ergonomic chair design according to the analysis is a stainless steel frame, seat height 390 mm, with a seat width for each passenger of 400 mm and a depth of 400 mm. Design of the backrest has a height of 840 mm, width of 430 mm and length of 300 mm that can move at the angle of 105-115 degrees. The width of the footrest is 42 mm and 400 mm length. The thickness of the seat cushion is 100 mm.

Keywords: chair, ergonomics, function development, train passenger

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Authors: Shailly Kumar

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Gender is a social construction resulting in defining roles and responsibilities to carried out according to masculine and feminine traits. The main aim of the study was to explore gender awareness among college going students of Delhi. The objectives of studies were to find out (i) the understanding of term gender and roles and responsibilities associated with male and female as masculine and feminine traits in our society. (ii)Gender images representing the attributes and characteristics attached to particular gender. (iii) Gender discrimination prevailing among girls and boys in our society. (iv)Gender stereotypes resulting in gendering with respect to religion, culture, family and media. The sample of study consisted of 100 undergraduate college girl students. The findings of study stated that the students had this understanding that sex is a natural phenomenon and gender is socially constructed. Gender defines the roles and responsibilities among two sexes. On a gender image students concluded that males are represented as a powerful members of society showing physical strength and violence, force and society gave the power to men oppress and subjugate women in society that's why women are treated inferior and given secondary position in society. On gender discrimination, girl students stated that they faced discrimination at all level such as family, media ,education, workplace etc .There is strong prevailing gender stereotypes among girls and boys with respect to religious practices, choice of career ,preference of child etc. This study concluded that students were aware of gendered practices in various domains of life. The study helped to interpret the notions and perceptions of students towards gendering of social spaces and in their lives.

Keywords: gender, gender awareness, gender role, masculinity and feminity

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Authors: Vijaykumar M. Baragi, Ramtilak Gattu, Gabriela Trifan, John L. Woodard, K. Meyers, Tim S. Halstead, Eric Hipple, Ewart Mark Haacke, Randall R. Benson

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NFL players, by virtue of their exposure to repetitive head injury, are at least twice as likely to develop Alzheimer's disease (AD) and dementia as the general population. Early recognition and intervention prior to onset of clinical symptoms could potentially avert/delay the long-term consequences of these diseases. Since AD is thought to have a long preclinical incubation period, the aim of the current research was to determine whether former NFL players, referred to a depression center, showed evidence of incipient dementia in their structural imaging prior to diagnosis of dementia. Thus, to identify neuroimaging markers of AD, against which former NFL players would be compared, we conducted a comprehensive volumetric analysis using a cohort of early stage AD patients (ADNI) to produce a set of brain regions demonstrating sensitivity to early AD pathology (i.e., the “AD fingerprint”). A cohort of 46 former NFL players’ brain MRIs were then interrogated using the AD fingerprint. Brain scans were done using a T1-weighted MPRAGE sequence. The Free Surfer image analysis suite (version 6.0) was used to obtain the volumetric and cortical thickness data. A total of 55 brain regions demonstrated significant atrophy or ex vacuo dilatation bilaterally in AD patients vs. healthy controls. Of the 46 former NFL players, 19 (41%) demonstrated a greater than expected number of atrophied/dilated AD regions when compared with age-matched controls, presumably reflecting AD pathology.

Keywords: alzheimers, neuroimaging biomarkers, traumatic brain injury, free surfer, ADNI

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Authors: Md. Shakhawat Hossain, Jimma Hossain, Md. Naushad Ali

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Acute pancreatitis is a dangerous medical emergency in the practice of gastroenterology. Management of acute pancreatitis needs multidisciplinary approach with support starts from emergency to ICU. So, there is a chance of mismanagement in every steps, especially in low resource settings. Other factors such as patient’s financial condition, education, social custom, transport facility, referral system from periphery may also challenge the current guidelines for management. The present study is intended to determine the clinico-pathological profile, severity assessment and challenges of management of acute pancreatitis in a government laid tertiary care hospital to image the real scenario of management in a low resource place. A total 100 patients of acute pancreatitis were studied in this prospective study, held in the Department of Gastroenterology, Rangpur medical college hospital, Bangladesh from July 2017 to July 2018 within one year. Regarding severity, 85 % of the patients were mild, whereas 13 were moderately severe, and 2 had severe acute pancreatitis according to the revised Atlanta criteria. The most common etiologies of acute pancreatitis in our study were gall stone (15%) and biliary sludge (15%), whereas 54% were idiopathic. The most common challenges we faced were delay in hospital admission (59%) and delay in hospital diagnosis (20%). Others are non-adherence of patient party, and lack of investigation facility, physician’s poor knowledge about current guidelines. We were able to give early aggressive fluid to only 18% of patients as per current guideline. Conclusion: Management of acute pancreatitis as per guideline is challenging when optimum facility is lacking. So, modified guidelines for assessment and management of acute pancreatitis should be prepared for low resource setting.

Keywords: acute pancreatitis, challenges of management, severity, prognosis

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Authors: Anand Choudhary

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Following the global economic crisis in 2008, businesses and more especially the big multinational conglomerates were increasingly viewed by the people world over as one of the major causes of the economic problems faced by millions globally, in terms of job loss and lifetime savings being wiped out as banks and pension funds went bankrupt and people stared at an insecure financial future. This caused a lot of resentment in the public against big businesses and fueled several protest movements by the people such as “Occupy Wall Street” in different parts of the world. This forced the big businesses to respond to the challenge by adopting more people-centric policies and initiatives for local communities in societies where they operate as part of their corporate social responsibility (CSR), in order to regain their social acceptance among the people whilst earning their ‘social license to operate’. The current paper studies many of such large MNCs across the United States of America, India and South Africa, which changed the way they did business earlier, following the global economic crisis in 2008, by incorporating capacity building initiatives for local communities as part of their CSR strategy and explores whether it has contributed to improving their financial performance. It is a conceptual research paper using secondary source data. The findings reveal that there is a positive correlation between the companies’ corporate social performance and corporate financial performance. In addition, the findings also bring to light that the MNCs examined as part of the current paper have improved their image in the eyes of their stakeholders following the change in their CSR strategy and initiatives.

Keywords: corporate social responsibility (CSR), Corporate Social Performance (CSP), Corporate Financial Performance (CFP), local communities

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Authors: Amine Benmoussa, Mohamed Bouanini, Mebrouk Rebhi

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Stirring is one of the unifying processes which form part of the mechanical unit operations in process technology such chemical, biotechnological, pharmaceutical, petrochemical, cosmetic, and food processing. Therefore determining the level of mixing and overall behavior and performance of the mixing tanks are crucial from the product quality and process economics point of views. The most fundamental needs for the analysis of these processes from both a theoretical and industrial perspective are the knowledge of the hydrodynamic behavior and the flow structure in such tanks. Depending on the purpose of the operation carried out in mixer, the best choice for geometry of the tank and agitator type can vary widely. Initially, a local and global study namely the velocity and power number on a typical agitation system agitated by a mobile-type two-blade straight (d/D=0.5) allowed us to test the reliability of the CFD, the result were compared with those of experimental literature, a very good concordance was observed. The stream function, the velocity profile, the velocity fields and power number are analyzed. It was shown that the hydrodynamics is modified by the curvature of the mobile which plays a key role.

Keywords: agitated vessels, curved blade agitator, laminar flow, finite volume method

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Authors: Valentina Narvaez Gaitan, Laura Valentina Rodriguez Leguizamon, Ruben Dario Hernandez B.

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This work describes a physiological signal emulation system that uses electromyography (EMG) signals obtained from muscle sensors in the first instance. These signals are used to extract their characteristics to model and emulate specific arm movements. The main objective of this effort is to develop a new biomedical software system capable of generating physiological signals through the use of embedded systems by establishing the characteristics of the acquired signals. The acquisition system used was Biosignals, which contains two EMG electrodes used to acquire signals from the forearm muscles placed on the extensor and flexor muscles. Processing algorithms were implemented to classify the signals generated by the arm muscles when performing specific movements such as wrist flexion extension, palmar grip, and wrist pronation-supination. Matlab software was used to condition and preprocess the signals for subsequent classification. Subsequently, the mathematical modeling of each signal is performed to be generated by the embedded system, with a validation of the accuracy of the obtained signal using the percentage of cross-correlation, obtaining a precision of 96%. The equations are then discretized to be emulated in the embedded system, obtaining a system capable of generating physiological signals according to the characteristics of medical analysis.

Keywords: classification, electromyography, embedded system, emulation, physiological signals

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Authors: Marcela Ondova, Adriana Estokova

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Rapid industrialization results in increased use of natural resources bring along serious ecological and environmental imbalance due to the dumping of industrial wastes. Principles of sustainable construction have to be accepted with regard to the consumption of natural resources and the production of harmful emissions. Cement is a great importance raw material in the building industry and today is its large amount used in the construction of concrete pavements. Concerning raw materials cost and producing CO2 emission the replacing of cement in concrete mixtures with more sustainable materials is necessary. To reduce this environmental impact people all over the world are looking for a solution. Over a period of last ten years, the image of fly ash has completely been changed from a polluting waste to resource material and it can solve the major problems of cement use. Fly ash concretes are proposed as a potential approach for achieving substantial reductions in cement. It is known that it improves the workability of concrete, extends the life cycle of concrete roads, and reduces energy use and greenhouse gas as well as amount of coal combustion products that must be disposed in landfills. Life cycle assessment also proved that a concrete pavement with fly ash cement replacement is considerably more environmentally friendly compared to standard concrete roads. In addition, fly ash is cheap raw material, and the costs saving are guaranteed. The strength properties, resistance to a frost or de-icing salts, which are important characteristics in the construction of concrete pavements, have reached the required standards as well. In terms of human health it can´t be stated that a concrete cover with fly ash could be dangerous compared with a cover without fly ash. Final Multi-criteria analysis also pointed that a concrete with fly ash is a clearly proper solution.

Keywords: life cycle assessment, fly ash, waste, concrete pavements

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Authors: Muammer Kaya

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The main purpose of this article is to provide a comprehensive review of various physical and chemical processes for electronic waste (e-waste) recycling, their advantages and shortfalls towards achieving a cleaner process of waste utilization, with especial attention towards extraction of metallic values. Current status and future perspectives of waste printed circuit boards (PCBs) recycling are described. E-waste characterization, dismantling/ disassembly methods, liberation and classification processes, composition determination techniques are covered. Manual selective dismantling and metal-nonmetal liberation at – 150 µm at two step crushing are found to be the best. After size reduction, mainly physical separation/concentration processes employing gravity, electrostatic, magnetic separators, froth floatation etc., which are commonly used in mineral processing, have been critically reviewed here for separation of metals and non-metals, along with useful utilizations of the non-metallic materials. The recovery of metals from e-waste material after physical separation through pyrometallurgical, hydrometallurgical or biohydrometallurgical routes is also discussed along with purification and refining and some suitable flowsheets are also given. It seems that hydrometallurgical route will be a key player in the base and precious metals recoveries from e-waste. E-waste recycling will be a very important sector in the near future from economic and environmental perspectives.

Keywords: e-waste, WEEE, recycling, metal recovery, hydrometallurgy, pirometallurgy, biometallurgy

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Authors: T. Rocha, P. Carvalho, S. Paredes, J. Henriques, A. Bianchi, V. Traver, A. Martinez

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The main goal of LINK project is to join competences in intelligent processing in order to create a research ecosystem to address two central scientific and technical challenges for personal health care (PHC) deployment: i) how to merge clinical evidence knowledge in computational decision support systems for PHC management and ii) how to provide achieve personalized services, i.e., solutions adapted to the specific user needs and characteristics. The final goal of one of the work packages (WP2), designated Sustainable Linking and Synergies for Excellence, is the definition, implementation and coordination of the necessary activities to create and to strengthen durable links between the LiNK partners. This work focuses on the strategy that has been followed to achieve the definition of the Research Tracks (RT), which will support a set of actions to be pursued along the LiNK project. These include common research activities, knowledge transfer among the researchers of the consortium, and PhD student and post-doc co-advisement. Moreover, the RTs will establish the basis for the definition of concepts and their evolution to project proposals.

Keywords: LiNK Twin European Project, personal health care, cardiovascular diseases, research tracks

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Authors: Hamidreza Hoshyarmanesh, Hosein Madieh, Sanju Lama, Yaser Maddahi, Garnette R. Sutherland, Kourosh Zareinia

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This paper illustrates the concept of an algorithm to register specified markers on the neuroArm surgical manipulators, an image-guided MR-compatible tele-operated robot for microsurgery and stereotaxy. Two range-finding algorithms, namely time-of-flight and phase-shift, are evaluated for registration and supervisory control. The time-of-flight approach is implemented in a semi-field experiment to determine the precise position of a tiny retro-reflective moving object. The moving object simulates a surgical tool tip. The tool is a target that would be connected to the neuroArm end-effector during surgery inside the magnet bore of the MR imaging system. In order to apply flight approach, a 905-nm pulsed laser diode and an avalanche photodiode are utilized as the transmitter and receiver, respectively. For the experiment, a high frequency time to digital converter was designed using a field-programmable gate arrays. In the phase-shift approach, a continuous green laser beam with a wavelength of 530 nm was used as the transmitter. Results showed that a positioning error of 0.1 mm occurred when the scanner-target point distance was set in the range of 2.5 to 3 meters. The effectiveness of this non-contact approach exhibited that the method could be employed as an alternative for conventional mechanical registration arm. Furthermore, the approach is not limited by physical contact and extension of joint angles.

Keywords: 3D laser scanner, intraoperative MR imaging, neuroArm, real time registration, robot-assisted surgery, supervisory control

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Authors: Abdulmannan Fadel

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Arabinoxylan is a non-starch polysaccharide (NSP), which is one of the most important polysaccharides contained within cereal grains. Wheat endosperm pentosan and rice bran contain a significant amount of arabinoxylan (7% in rice bran and 10-12% in wheat endosperm pentosan). Several methods have been used for arabinoxylan extraction with varying degrees of success e.g. enzymatic and alkaline treatment. Yet, the use of extrusion alone as a pre-treatment to increase the yield and reduce the molecular weight in wheat endosperm pentosan and rice bran has not been investigated. The samples (wheat pentosan and rice bran) were extruded using a Twin-screw extruder at a range of screw speeds (80 and 160 rpm) and barrel temperatures range (80 to 140°C) with a throughput of 30 Kg hr-1 and moisture content of 25%. Arabinoxylans were extracted with water and the extraction yield and molecular weight was determined using size exclusion high-pressure liquid chromatography system. It was found that increasing screw speed from 80 rpm to 160 rpm, did not effect the extraction yield (p < 0.05) of arabinoxylan from either the wheat endosperm pentosan or the rice bran. However, the molecular weight of the extracted arabinoxylans from pentosan was found to decrease with increasing screw speed in wheat endosperm pentosan. These low molecular weight arabinoxylans have been suggested as immunomodulators.

Keywords: arabinoxylans, extrusion, wheat endosperm pentosan, rice bran

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Authors: Hsin-Yang Wang, K. M. A. Salam, Ying-Jia Lin, Daniel Tan, Tzu-Hsuan Chou, Hung-Yu Kao

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Detecting user intent from natural language expression has a wide variety of use cases in different natural language processing applications. Recently few-shot training has a spike of usage on commercial domains. Due to the lack of significant sample features, the downstream task performance has been limited or leads to an unstable result across different domains. As a state-of-the-art method, the pre-trained BERT model gathering the sentence-level information from a large text corpus shows improvement on several NLP benchmarks. In this research, we are proposing a method to change multi-class classification tasks into binary classification tasks, then use the confidence score to rank the results. As a language model, BERT performs well on sequence data. In our experiment, we change the objective from predicting labels into finding the relations between words in sequence data. Our proposed method achieved 71.0% accuracy in the internal intent detection dataset and 63.9% accuracy in the HuffPost dataset. Acknowledgment: This work was supported by NCKU-B109-K003, which is the collaboration between National Cheng Kung University, Taiwan, and SoftBank Corp., Tokyo.

Keywords: OSML, BERT, text classification, one shot

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Authors: Roshani Gusain, Deep Sinha, Karan Nayal, Anmol Kumar Mishra, Manav Singh

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In this research paper, we introduce "Mind Care Assistant - Companion App", which is a Flutter and Firebase-based mental health monitor. The app wants to improve and monitor the mental health of its users, it uses noninvasive ways to check for a change in their emotional state. By responding to questions, the app will provide individualized suggestions ᅳ tasks and mindfulness exercises ᅳ for users who are depressed or anxious. The app features a chat-bot that incorporates cognitive behavioural therapy (CBT) principles and combines natural language processing with machine learning to develop personalised responses. The feature of the app that makes it easy for us to choose between iOS and Android is cross-platform, which allows users from both mobile systems to experience almost no changes in their interfaces. With Firebase integration synchronized and real-time data storage, security is easily possible. The paper covers the architecture of the app, how it was developed and some important features. The primary research result presents the promise of a "Mind Care Assistant" in mental health care using new wait-for-health technology, proposing a full stack application to be able to manage depression/anxiety and overall Mental well-being very effectively.

Keywords: mental health, mobile application, flutter, firebase, Depression, Anxiety

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Authors: Nour Tawil, Sandra Weber, Kirsten K. Roessler, Martin Mau, Simone Kuhn

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The link between “quality” residential environments and human health and well-being has long been proposed. While the physical properties of a sound environment have been fairly defined, little focus has been given to the psychological impact of architectural elements. Recently, studies have investigated the response to architectural parameters, using measures of physiology, brain activity, and emotion. Results showed different aspects of interest: detailed and open versus blank and closed facades, patterns in perceiving different elements, and a visual bias for capturing faces in buildings. However, in the absence of a consensus on methodologies, the available studies remain unsystematic and face many limitations regarding the underpinning psychological mechanisms. To bridge some of these gaps, an online study was launched to investigate design features that influence the aesthetic judgement and emotional evaluation of house facades, using a well-controlled stimulus set of Canadian houses. A methodical modelling of design features will be performed to extract both high and low level image properties, in addition to segmentation of layout-related features. 300 participants from Canada, Denmark, and Germany will rate the images on twelve psychological dimensions representing appealing aspects of a house. Subjective ratings are expected to correlate with specific architectural elements while controlling for typicality and familiarity, and other individual differences. With the lack of relevant studies, this research aims to identify architectural elements of beneficial qualities that can inform design strategies for optimized residential spaces.

Keywords: architectural elements, emotions, psychological response, residential facades.

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Authors: Wu You, Burra Venkata Durga Kumar

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This study examines the promising potential of integrating Blockchain and Artificial Intelligence (AI) technologies to scalability in Distributed Systems within the field of supply chain finance. The finance industry is continually confronted with scalability challenges in its Distributed Systems, particularly within the supply chain finance sector, impacting efficiency and security. Blockchain, with its inherent attributes of high scalability and secure distributed ledger system, coupled with AI's strengths in optimizing data processing and decision-making, holds the key to innovating the industry's approach to these issues. This study elucidates the synergistic interplay between Blockchain and AI, detailing how their fusion can drive a significant transformation in the supply chain finance sector's Distributed Systems. It offers specific use-cases within this field to illustrate the practical implications and potential benefits of this technological convergence. The study also discusses future possibilities and current challenges in implementing this groundbreaking approach within the context of supply chain finance. It concludes that the intersection of Blockchain and AI could ignite a new epoch of enhanced efficiency, security, and transparency in the Distributed Systems of supply chain finance within the financial industry.

Keywords: blockchain, artificial intelligence (AI), scaled distributed systems, supply chain finance, efficiency and security

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Authors: Pavel Shcherban, Vlad Golovanov

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Nowadays, the depletion of hydrocarbon deposits on the land of the Kaliningrad region leads to active geological exploration and development of oil and natural gas reserves in the southeastern part of the Baltic Sea. LLC 'Lukoil-Kaliningradmorneft' implements a comprehensive program for the development of the region's shelf in 2014-2023. Due to heterogeneity of reservoir rocks in various open fields, as well as with ambiguous conclusions on the contours of deposits, additional geological prospecting and refinement of the recoverable oil reserves are carried out. The key element is use of an effective technique of computer stock modeling at the first stage of processing of the received data. The following step uses information for the cluster analysis, which makes it possible to optimize the field development approaches. The article analyzes the effectiveness of various methods for reserves' calculation and computer modelling methods of the offshore hydrocarbon fields. Cluster analysis allows to measure influence of the obtained data on the development of a technical and economic model for mining deposits. The relationship between the accuracy of the calculation of recoverable reserves and the need of modernization of existing mining infrastructure, as well as the optimization of the scheme of opening and development of oil deposits, is observed.

Keywords: cluster analysis, computer modelling of deposits, correction of the feasibility study, offshore hydrocarbon fields

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Authors: Kavita Goel, Donald Winchester

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In a world of information overload and work complexities, academics often struggle to create an online instructional environment enabling efficient and effective student learning. Research has established that students’ learning styles are different, some learn faster when taught using audio and visual methods. Attributes like prior knowledge and mental effort affect their learning. ‘Cognitive load theory’, opines learners have limited processing capacity. Cognitive load depends on the learner’s prior knowledge, the complexity of content and tasks, and instructional environment. Hence, the proper allocation of cognitive resources is critical for students’ learning. Consequently, a lecturer needs to understand the limits and strengths of the human learning processes, various learning styles of students, and accommodate these requirements while designing online assessments. As acknowledged in the cognitive load theory literature, visual and auditory explanations of worked examples potentially lead to a reduction of cognitive load (effort) and increased facilitation of learning when compared to conventional sequential text problem solving. This will help learner to utilize both subcomponents of their working memory. Instructional design changes were introduced at the case site for the delivery of the postgraduate business subjects. To make effective use of auditory and visual modalities, video recorded lectures, and key concept webinars were delivered to students. Videos were prepared to free up student limited working memory from irrelevant mental effort as all elements in a visual screening can be viewed simultaneously, processed quickly, and facilitates greater psychological processing efficiency. Most case study students in the postgraduate programs are adults, working full-time at higher management levels, and studying part-time. Their learning style and needs are different from other tertiary students. The purpose of the audio and visual interventions was to lower the students cognitive load and provide an online environment supportive to their efficient learning. These changes were expected to impact the student’s learning experience, their academic performance and retention favourably. This paper posits that these changes to instruction design facilitates students to integrate new knowledge into their long-term memory. A mixed methods case study methodology was used in this investigation. Primary data were collected from interviews and survey(s) of students and academics. Secondary data were collected from the organisation’s databases and reports. Some evidence was found that the academic performance of students does improve when new instructional design changes are introduced although not statistically significant. However, the overall grade distribution of student’s academic performance has changed and skewed higher which shows deeper understanding of the content. It was identified from feedback received from students that recorded webinars served as better learning aids than material with text alone, especially with more complex content. The recorded webinars on the subject content and assessments provides flexibility to students to access this material any time from repositories, many times, and this enhances students learning style. Visual and audio information enters student’s working memory more effectively. Also as each assessment included the application of the concepts, conceptual knowledge interacted with the pre-existing schema in the long-term memory and lowered student’s cognitive load.

Keywords: cognitive load theory, learning style, instructional environment, working memory

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Authors: Jude K. Safo

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Knowledge Graphs KG) and their relation to Graph Embeddings (GE) represent a unique data structure in the landscape of machine learning (relative to image, text and acoustic data). Unlike the latter, GEs are the only data structure sufficient for representing hierarchically dense, semantic information needed for use-cases like supply chain data and protein folding where the search space exceeds the limits traditional search methods (e.g. page-rank, Dijkstra, etc.). While GEs are effective for compressing low rank tensor data, at scale, they begin to introduce a new problem of ’data retreival’ which we observe in Large Language Models. Notable attempts by transE, TransR and other prominent industry standards have shown a peak performance just north of 57% on WN18 and FB15K benchmarks, insufficient practical industry applications. They’re also limited, in scope, to next node/link predictions. Traditional linear methods like Tucker, CP, PARAFAC and CANDECOMP quickly hit memory limits on tensors exceeding 6.4 million nodes. This paper outlines a topological framework for linear mapping between concepts in KG space and GE space that preserve cardinality. Most importantly we introduce a traceable framework for composing dense linguistic strcutures. We demonstrate performance on WN18 benchmark this model hits. This model does not rely on Large Langauge Models (LLM) though the applications are certainy relevant here as well.

Keywords: representation theory, large language models, graph embeddings, applied algebraic topology, applied knot theory, combinatorics

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Authors: Shreyansh Jain Jeetmal, Shobith P. Chadaga, Shreyas H. Srinivas

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Internet of Things (IoT) is seen as the next major step in the ongoing revolution in the Information Age. It is predicted that in the near future billions of embedded devices will be communicating with each other to perform a plethora of tasks with or without human intervention. One of the major ongoing hotbed of research activity in IoT is Human Computer Interaction (HCI). HCI is used to facilitate communication between an intelligent system and a user. An intelligent system typically comprises of a system consisting of various sensors, actuators and embedded controllers which communicate with each other to monitor data collected from the environment. Communication by the user to the system is typically done using voice. One of the major ongoing applications of HCI is in home automation as a personal assistant. The prime objective of our project is to implement a use case of HCI for home automation. Our system is designed to detect and recognize the users and personalize the appliances in the house according to their individual preferences. Our HCI system is also capable of speaking with the user when certain commands are spoken such as searching on the web for information and controlling appliances. Our system can also monitor the environment in the house such as air quality and gas leakages for added safety.

Keywords: human computer interaction, internet of things, computer vision, sensor networks, speech to text, text to speech, android

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Authors: Stefan Andersson, Balram Panjwani, Bernd Wittgens, Jan Erik Olsen

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Polycyclic Aromatic hydrocarbons are organic compounds consisting of only hydrogen and carbon aromatic rings. PAH are neutral, non-polar molecules that are produced due to incomplete combustion of organic matter. These compounds are carcinogenic and interact with biological nucleophiles to inhibit the normal metabolic functions of the cells. Norways, the most important sources of PAH pollution is considered to be aluminum plants, the metallurgical industry, offshore oil activity, transport, and wood burning. Stricter governmental regulations regarding emissions to the outer and internal environment combined with increased awareness of the potential health effects have motivated Norwegian metal industries to increase their efforts to reduce emissions considerably. One of the objective of the ongoing industry and Norwegian research council supported "SCORE" project is to reduce potential PAH emissions from an off gas stream of a ferroalloy furnace through controlled combustion. In a dedicated combustion chamber. The sizing and configuration of the combustion chamber depends on the combined properties of the bulk gas stream and the properties of the PAH itself. In order to achieve efficient and complete combustion the residence time and minimum temperature need to be optimized. For this design approach reliable kinetic data of the individual PAH-species and/or groups thereof are necessary. However, kinetic data on the combustion of PAH are difficult to obtain and there is only a limited number of studies. The paper presents an evaluation of the kinetic data for some of the PAH obtained from literature. In the present study, the oxidation is modelled for pure PAH and also for PAH mixed with process gas. Using a perfectly stirred reactor modelling approach the oxidation is modelled including advanced reaction kinetics to study influence of residence time and temperature on the conversion of PAH to CO2 and water. A Chemical Reactor Network (CRN) approach is developed to understand the oxidation of PAH inside the combustion chamber. Chemical reactor network modeling has been found to be a valuable tool in the evaluation of oxidation behavior of PAH under various conditions.

Keywords: PAH, PSR, energy recovery, ferro alloy furnace

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Authors: Meng Su

Abstract:

High-dimensional data analysis often presents challenges in capturing the complex, nonlinear relationships and manifold structures inherent to the data. This article presents a novel approach that leverages the strengths of two powerful techniques, Diffusion Maps and Diffusion Probabilistic Models (DPMs), to address these challenges. By integrating the dimensionality reduction capability of Diffusion Maps with the data modeling ability of DPMs, the proposed method aims to provide a comprehensive solution for analyzing and generating high-dimensional data. The Diffusion Map technique preserves the nonlinear relationships and manifold structure of the data by mapping it to a lower-dimensional space using the eigenvectors of the graph Laplacian matrix. Meanwhile, DPMs capture the dependencies within the data, enabling effective modeling and generation of new data points in the low-dimensional space. The generated data points can then be mapped back to the original high-dimensional space, ensuring consistency with the underlying manifold structure. Through a detailed example implementation, the article demonstrates the potential of the proposed hybrid approach to achieve more accurate and effective modeling and generation of complex, high-dimensional data. Furthermore, it discusses possible applications in various domains, such as image synthesis, time-series forecasting, and anomaly detection, and outlines future research directions for enhancing the scalability, performance, and integration with other machine learning techniques. By combining the strengths of Diffusion Maps and DPMs, this work paves the way for more advanced and robust data analysis methods.

Keywords: diffusion maps, diffusion probabilistic models (DPMs), manifold learning, high-dimensional data analysis

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Authors: Shu Yin, Zhiyang Ding, Jianzhong Huang, Xiaojun Ruan, Xiaomin Zhu, Xiao Qin

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Since large-scale and data-intensive applications have been widely deployed, there is a growing demand for high-performance storage systems to support data-intensive applications. Compared with traditional storage systems, next-generation systems will embrace dedicated processor to reduce computational load of host machines and will have hybrid combinations of different storage devices. The advent of flash- memory-based solid state disk has become a critical role in revolutionizing the storage world. However, instead of simply replacing the traditional magnetic hard disk with the solid state disk, it is believed that finding a complementary approach to corporate both of them is more challenging and attractive. This paper explores an idea of active storage, an emerging new storage configuration, in terms of the architecture and design, the parallel processing capability, the cooperation of other machines in cluster computing environment, and a disk configuration, the hybrid combination of different types of disk drives. Experimental results indicate that the proposed HcDD achieves better I/O performance and longer storage system lifespan.

Keywords: arallel storage system, hybrid storage system, data inten- sive, solid state disks, reliability

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Authors: Alexandra Aslanidou

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The General Data Protection Regulation (GDPR), concerning the protection of natural persons within the European Union with regard to the processing of personal data and on the free movement of such data, became applicable in the European Union (EU) on 25 May 2018 and transformed the way personal data were being treated under the Data Protection Directive (DPD) regime, generating sweeping organizational changes to both public sector and business. A social practice that is considerably influenced in the way of its day-to-day operations is Human Resource (HR) management, for which the importance of GDPR cannot be underestimated. That is because HR processes personal data coming in all shapes and sizes from many different systems and sources. The significance of the proper functioning of an HR department, specifically in human-centered, service-oriented environments such as the education field, is decisive due to the fact that HR operations in schools, conducted effectively, determine the quality of the provided services and consequently have a considerable impact on the success of the educational system. The purpose of this paper is to analyze the decisive role that GDPR plays in HR departments that operate in schools and in order to practically evaluate the aftermath of the Regulation during the first months of its applicability; a comparative use cases analysis in five highly dynamic schools, across three EU Member States, was attempted.

Keywords: general data protection regulation, human resource management, educational system

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Authors: Chayanika Hazarika Bordoloi

Abstract:

This paper is an attempt to work on a highly inflectional language called Assamese. This is also one of the national languages of India and very little has been achieved in terms of computational research. Building a language processing tool for a natural language is not very smooth as the standard and language representation change at various levels. This paper presents inflectional suffixes of Assamese verbs and how the statistical tools, along with linguistic features, can improve the tagging accuracy. Conditional random fields (CRF tool) was used to automatically tag and train the text data; however, accuracy was improved after linguistic featured were fed into the training data. Assamese is a highly inflectional language; hence, it is challenging to standardizing its morphology. Inflectional suffixes are used as a feature of the text data. In order to analyze the inflections of Assamese word forms, a list of suffixes is prepared. This list comprises suffixes, comprising of all possible suffixes that various categories can take is prepared. Assamese words can be classified into inflected classes (noun, pronoun, adjective and verb) and un-inflected classes (adverb and particle). The corpus used for this morphological analysis has huge tokens. The corpus is a mixed corpus and it has given satisfactory accuracy. The accuracy rate of the tagger has gradually improved with the modified training data.

Keywords: CRF, morphology, tagging, tagset

Procedia PDF Downloads 194