Search results for: automated fibre placement

Authors: P. Tej, P. Kněž, M. Blank

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The paper presents design and production of thin-walled U-profile footbridge made of UHPFRC. The main structure of the bridge is one prefabricated shell structure made of UHPFRC with dispersed steel fibers without any conventional reinforcement. The span of the bridge structure is 10 m and the clear width of 1.5 m. The thickness of the UHPFRC shell structure oscillated in an interval of 30-45 mm. Several calculations were made during the bridge design and compared with the experiments. For the purpose of verifying the calculations, a segment of 1.5 m was first produced, followed by the whole footbridge for testing. After the load tests were done, the design was optimized to cast the final footbridge.

Keywords: footbridge, non-linear analysis, shell structure, UHPFRC, Ultra-High Performance Fibre Reinforced Concrete

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Authors: Yun Chan Lee

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Background: End-of-life care is a large area of all nursing practice and student nurses are likely to meet dying patients in many placement areas. It is therefore important to understand the emotional responses and coping strategies of student nurses in order for nursing education systems to have some appreciation of how nursing students might be supported in the future. Methodology: This research used a qualitative phenomenological approach. Six student nurses understanding a degree-level adult nursing course were interviewed. Their responses to questions were analyzed using interpretative phenomenological analysis. Finding: The findings identified 3 main themes. First, the common experience of ‘unpreparedness’. A very small number of participants felt that this was unavoidable and that ‘no preparation is possible’, the majority felt that they were unprepared because of ‘insufficient input’ from the university and as a result of wider ‘social taboos’ around death and dying. The second theme showed that emotions were affected by ‘the personal connection to the patient’ and the important sub-themes of ‘the evoking of memories’, ‘involvement in care’ and ‘sense of responsibility’. The third theme, the coping strategies used by students, seemed to fall into two broad areas those ‘internal’ with the student and those ‘external’. In terms of the internal coping strategies, ‘detachment’, ‘faith’, ‘rationalization’ and ‘reflective skills’ are the important components of this part. Regarding the external coping strategies, ‘clinical staff’ and ‘the importance of family and friends’ are the importance of accessing external forms of support. Implication: It is clear that student nurses are affected emotionally by caring for dying patients and many of them have apprehension even before they begin on their placements but very often this is unspoken. Those anxieties before the placement become more pronounced during and continue after the placements. This has implications for when support is offered and possibly its duration. Another significant point of the study is that participants often highlighted their wish to speak to qualified nurses after their experiences of being involved in end-of-life care and especially when they had been present at the time of death. Many of the students spoke that qualified nurses were not available to them. This seemed to be due to a number of reasons. Because the qualified nurses were not available, students had to make use of family members and friends to talk to. Consequently, the implication of this study is not only to educate student nurses but also to educate the qualified mentors on the importance of providing emotional support to students.

Keywords: nursing students, coping strategies, end-of-life care, emotional responses

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Authors: Hamed Kalhori, Lin Ye

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In this study, an inverse method was developed to reconstruct the magnitude and duration of impact forces exerted to a rectangular carbon fibre-epoxy composite honeycomb sandwich panel. The dynamic signals captured by Piezoelectric (PZT) sensors installed on the panel remotely from the impact locations were utilized to reconstruct the impact force generated by an instrumented hammer through an extended deconvolution approach. Two discretized forms of convolution integral are considered; the traditional one with an explicit transfer function and the modified one without an explicit transfer function. Deconvolution, usually applied to reconstruct the time history (e.g. magnitude) of a stochastic force at a defined location, is extended to identify both the location and magnitude of the impact force among a number of potential impact locations. It is assumed that a number of impact forces are simultaneously exerted to all potential locations, but the magnitude of all forces except one is zero, implicating that the impact occurs only at one location. The extended deconvolution is then applied to determine the magnitude as well as location (among the potential ones), incorporating the linear superposition of responses resulted from impact at each potential location. The problem can be categorized into under-determined (the number of sensors is less than that of impact locations), even-determined (the number of sensors equals that of impact locations), or over-determined (the number of sensors is greater than that of impact locations) cases. For an under-determined case, it comprises three potential impact locations and one PZT sensor for the rectangular carbon fibre-epoxy composite honeycomb sandwich panel. Assessments are conducted to evaluate the factors affecting the precision of the reconstructed force. Truncated Singular Value Decomposition (TSVD) and the Tikhonov regularization are independently chosen to regularize the problem to find the most suitable method for this system. The selection of optimal value of the regularization parameter is investigated through L-curve and Generalized Cross Validation (GCV) methods. In addition, the effect of different width of signal windows on the reconstructed force is examined. It is observed that the impact force generated by the instrumented impact hammer is sensitive to the impact locations of the structure, having a shape from a simple half-sine to a complicated one. The accuracy of the reconstructed impact force is evaluated using the correlation co-efficient between the reconstructed force and the actual one. Based on this criterion, it is concluded that the forces reconstructed by using the extended deconvolution without an explicit transfer function together with Tikhonov regularization match well with the actual forces in terms of magnitude and duration.

Keywords: honeycomb composite panel, deconvolution, impact localization, force reconstruction

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Authors: Nur Nadhirah Rusyda Rosnan, Nursuhaili Najwa Masrol, Nurul Fatiha MD Nor, Mohammad Zafrullah Mohammad Salim, Sim Choon Cheak

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Accurate inventories of oil palm planted areas are crucial for plantation management as this would impact the overall economy and production of oil. One of the technological advancements in the oil palm industry is semi-automated palm counting, which is replacing conventional manual palm counting via digitizing aerial imagery. Most of the semi-automated palm counting method that has been developed was limited to mature palms due to their ideal canopy size represented by satellite image. Therefore, immature palms were often left out since the size of the canopy is barely visible from satellite images. In this paper, an approach using a morphological filter and high-resolution satellite image is proposed to detect immature palm trees. This approach makes it possible to count the number of immature oil palm trees. The method begins with an erosion filter with an appropriate window size of 3m onto the high-resolution satellite image. The eroded image was further segmented using watershed segmentation to delineate immature palm tree regions. Then, local minimum detection was used because it is hypothesized that immature oil palm trees are located at the local minimum within an oil palm field setting in a grayscale image. The detection points generated from the local minimum are displaced to the center of the immature oil palm region and thinned. Only one detection point is left that represents a tree. The performance of the proposed method was evaluated on three subsets with slopes ranging from 0 to 20° and different planting designs, i.e., straight and terrace. The proposed method was able to achieve up to more than 90% accuracy when compared with the ground truth, with an overall F-measure score of up to 0.91.

Keywords: immature palm count, oil palm, precision agriculture, remote sensing

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Authors: Sanelisiwe Ndlovu

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Cities have become testbeds for automation and experimenting with artificial intelligence (AI) in managing urban services and public spaces. Smart Cities and AI systems are changing most human experiences from health and education to personal relations. For instance, in healthcare, social robots are being implemented as tools to assist patients. Similarly, in education, social robots are being used as tutors or co-learners to promote cognitive and affective outcomes. With that general picture in mind, one can now ask a further question about Smart Cities and artificial agents and their moral standing in the African context of personhood. There has been a wealth of literature on the topic of personhood; however, there is an absence of literature on African personhood in highly automated environments. Personhood in African philosophy is defined by the role one can and should play in the community. However, in today’s technologically advanced world, a risk is that machines become more capable of accomplishing tasks that humans would otherwise do. Further, on many African communitarian accounts, personhood and moral standing are associated with active relationality with the community. However, in the Smart City, human closeness is gradually diminishing. For instance, humans already do engage and identify with robotic entities, sometimes even romantically. The primary aim of this study is to investigate how African conceptions of personhood and community interact in a highly automated environment such as Smart Cities. Accordingly, this study lies in presenting a rarely discussed African perspective that emphasizes the necessity and the importance of relationality in handling Smart Cities and AI ethically. Thus, the proposed approach can be seen as the sub-Saharan African contribution to personhood and the growing AI debates, which takes the reality of the interconnectedness of society seriously. And it will also open up new opportunities to tackle old problems and use existing resources to confront new problems in the Fourth Industrial Revolution.

Keywords: smart city, artificial intelligence, personhood, community

Procedia PDF Downloads 198

Authors: Lanchi Xie, Zhihui Li, Zhigang Li, Guiqiang Wang, Lei Xu, Yuwen Yan

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Image-based facial features can be classified into category recognition features and individual recognition features. Current automated face recognition systems extract a specific feature vector of different dimensions from a facial image according to their pre-trained neural network. However, to improve the efficiency of parameter calculation, an algorithm generally reduces the image details by pooling. The operation will overlook the details concerned much by forensic experts. In our experiment, we adopted a variety of face recognition algorithms based on deep learning, compared a large number of naturally collected face images with the known data of the same person's frontal ID photos. Downscaling and manual handling were performed on the testing images. The results supported that the facial recognition algorithms based on deep learning detected structural and morphological information and rarely focused on specific markers such as stains and moles. Overall performance, distribution of genuine scores and impostor scores, and likelihood ratios were tested to evaluate the accuracy of biometric systems and forensic experts. Experiments showed that the biometric systems were skilled in distinguishing category features, and forensic experts were better at discovering the individual features of human faces. In the proposed approach, a fusion was performed at the score level. At the specified false accept rate, the framework achieved a lower false reject rate. This paper contributes to improving the interpretability of the objective method of facial comparison and provides a novel method for human-machine collaboration in this field.

Keywords: likelihood ratio, automated facial recognition, facial comparison, biometrics

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Authors: Aarti Agarwal, Ajmal Khan

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Background and Objective: Breathing difficulty is most distressing symptom for the patient and their caregivers providing palliative care to individuals with advanced malignancy. It needs to be tackled effectively and sometimes preemptively to provide relief from respiratory obstruction. Interventional procedures like tracheal stenting are becoming increasingly popular as a part of palliation for respiratory symptoms. We present a case of esophageal tumor earlier stented by Gastroenterologist to maintain esophageal patency, but the tumor outgrew to produce tracheal infiltration and thereby causing airway obstruction. Method and Result: 62-year-old man presented with unresectable Carcinoma oesophagus with inability to swallow. A metallic stent was placed by the gastroenterologist, to maintain esophageal patency and enable patient to swallow. Two months later, the patient returned to hospital in emergency with respiratory distress. CT neck and thorax revealed tumor infiltration through posterior tracheal wall. Lower extent of the tumor was till 1 cm above the carina. Airway stenting with Tracheo bronchial stent with Y configuration was planned under general anaesthesia with airway blocks. Superior Laryngeal Nerve Block, Glossopharyngeal block and Trans tracheal infiltration of local anaesthetics were performed. The patient was sedated with Fentanyl, Midazolam and propofol infusion but was breathing spontaneously. Once the rigid bronchoscope was placed inside trachea, breathing was supported with oxygen and sevoflurane. Initially, the trachea was cleared of tumor by coring. After creating space, tracheal stent was positioned and deployed. After stent placement patient was awakened, suctioned and nebulized. His respiratory stridor relieved instantaneously and was shifted to recovery. Conclusion: Airway blocks help in decreasing the incidence and severity of coughing during airway instrumentation thereby help in proper stent placement. They also reduce the requirement of general anaesthetics and hasten the post stenting recovery. Airway stent provided immediate relief to patient from symptoms of respiratory difficulty. Decision for early tracheal stenting may be taken for a select group of patients with high propensity for local spread, thereby avoiding respiratory complications and providing better quality of life in patients with inoperable malignancy.

Keywords: tracheal stent, respiratory difficulty, esophageal tumor, anaesthetic management

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Authors: Dimitra Alexiou

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In an urban area the allocation placement of an emergency service mobile units, such as ambulances, police patrol must be designed so as to achieve a prompt response to demand locations. In this paper, a partition of a given urban network into distinct sub-networks is performed such that; the vertices in each component are close and simultaneously the difference of the sums of the corresponding population in the sub-networks is almost uniform. The objective here is to position appropriately in each sub-network a mobile emergency unit in order to reduce the response time to the demands. A mathematical model in the framework of graph theory is developed. In order to clarify the corresponding method a relevant numerical example is presented on a small network.

Keywords: graph partition, emergency service, distances, location

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Authors: L. Angiuli, L. Trizio, R. Giua, A. Digilio, M. Tutino, P. Dambruoso, F. Mazzone, C. M. Placentino

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In the winter of 2014 a series of measurements were performed to evaluate the behavior of real-time PAHs and black carbon analyzers in a coke oven plant located in Taranto, a city of Southern Italy. Data were collected both insides than outside the plant, at air quality monitoring sites. Contemporary measures of PM2.5 and PM1 were performed. Particle-bound PAHs were measured by two methods: (1) aerosol photoionization using an Ecochem PAS 2000 analyzer, (2) PM2.5 and PM1 quartz filter collection and analysis by gas chromatography/mass spectrometry (GC/MS). Black carbon was determined both in real-time by Magee Aethalometer AE22 analyzer than by semi-continuous Sunset Lab EC/OC instrument. Detected PM2.5 and PM1 levels were higher inside than outside the plant while PAHs real-time values were higher outside than inside. As regards PAHs, inside the plant Ecochem PAS 2000 revealed concentrations not significantly different from those determined on the filter during low polluted days, but at increasing concentrations the automated instrument underestimated PAHs levels. At the external site, Ecochem PAS 2000 real-time concentrations were steadily higher than those on the filter. In the same way, real-time black carbon values were constantly lower than EC concentrations obtained by Sunset EC/OC in the inner site, while outside the plant real-time values were comparable to Sunset EC values. Results showed that in a coke plant real-time analyzers of PAHs and black carbon in the factory configuration provide qualitative information, with no accuracy and leading to the underestimation of the concentration. A site specific calibration is needed for these instruments before their installation in high polluted sites.

Keywords: black carbon, coke oven plant, PAH, PAS, aethalometer

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Authors: Parminder Kaur Heer, Alexei Lapkin

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Due to global challenges of increased competition and demand for more sustainable products/processes, there is a rising pressure on the industry to develop innovative processes. Through Process Intensification (PI) the existing and new processes may be able to attain higher efficiency. However, very few PI options are generally considered. This is because processes are typically analysed at a unit operation level, thus limiting the search space for potential process options. PI performed at more detailed levels of a process can increase the size of the search space. The different levels at which PI can be achieved is unit operations, functional and phenomena level. Physical/chemical phenomena form the lowest level of aggregation and thus, are expected to give the highest impact because all the intensification options can be described by their enhancement. The objective of the current work is thus, generation of numerous process alternatives based on phenomena, and development of their corresponding computer aided models. The methodology comprises: a) automated generation of process options, and b) automated generation of process models. The process under investigation is disintegrated into functions viz. reaction, separation etc., and these functions are further broken down into the phenomena required to perform them. E.g., separation may be performed via vapour-liquid or liquid-liquid equilibrium. A list of phenomena for the process is formed and new phenomena, which can overcome the difficulties/drawbacks of the current process or can enhance the effectiveness of the process, are added to the list. For instance, catalyst separation issue can be handled by using solid catalysts; the corresponding phenomena are identified and added. The phenomena are then combined to generate all possible combinations. However, not all combinations make sense and, hence, screening is carried out to discard the combinations that are meaningless. For example, phase change phenomena need the co-presence of the energy transfer phenomena. Feasible combinations of phenomena are then assigned to the functions they execute. A combination may accomplish a single or multiple functions, i.e. it might perform reaction or reaction with separation. The combinations are then allotted to the functions needed for the process. This creates a series of options for carrying out each function. Combination of these options for different functions in the process leads to the generation of superstructure of process options. These process options, which are formed by a list of phenomena for each function, are passed to the model generation algorithm in the form of binaries (1, 0). The algorithm gathers the active phenomena and couples them to generate the model. A series of models is generated for the functions, which are combined to get the process model. The most promising process options are then chosen subjected to a performance criterion, for example purity of product, or via a multi-objective Pareto optimisation. The methodology was applied to a two-step process and the best route was determined based on the higher product yield. The current methodology can identify, produce and evaluate process intensification options from which the optimal process can be determined. It can be applied to any chemical/biochemical process because of its generic nature.

Keywords: Phenomena, Process intensification, Process models , Process options

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Authors: Saleh Gorji, Sahil Gulati, Ana Pakzad

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Continuous electron diffraction tomography, also known as microcrystal electron diffraction (MicroED) or three-dimensional electron diffraction (3DED), is a powerful technique, which in combination with cryo-electron microscopy (cryo-ED), can provide atomic-scale 3D information about the crystal structure and composition of different classes of crystalline materials such as proteins, peptides, and small molecules. Unlike the well-established X-ray crystallography method, 3DED does not require large single crystals and can collect accurate electron diffraction data from crystals as small as 50 – 100 nm. This is a critical advantage as growing larger crystals, as required by X-ray crystallography methods, is often very difficult, time-consuming, and expensive. In most cases, specimens studied via 3DED method are electron beam sensitive, which means there is a limitation on the maximum amount of electron dose one can use to collect the required data for a high-resolution structure determination. Therefore, collecting data using a conventional scintillator-based fiber coupled camera brings additional challenges. This is because of the inherent noise introduced during the electron-to-photon conversion in the scintillator and transfer of light via the fibers to the sensor, which results in a poor signal-to-noise ratio and requires a relatively higher and commonly specimen-damaging electron dose rates, especially for protein crystals. As in other cryo-EM techniques, damage to the specimen can be mitigated if a direct detection camera is used which provides a high signal-to-noise ratio at low electron doses. In this work, we have used two classes of such detectors from Gatan, namely the K3® camera (a monolithic active pixel sensor) and Stela™ (that utilizes DECTRIS hybrid-pixel technology), to address this problem. The K3 is an electron counting detector optimized for low-dose applications (like structural biology cryo-EM), and Stela is also a counting electron detector but optimized for diffraction applications with high speed and high dynamic range. Lastly, data collection workflows, including crystal screening, microscope optics setup (for imaging and diffraction), stage height adjustment at each crystal position, and tomogram acquisition, can be one of the other challenges of the 3DED technique. Traditionally this has been all done manually or in a partly automated fashion using open-source software and scripting, requiring long hours on the microscope (extra cost) and extensive user interaction with the system. We have recently introduced Latitude® D in DigitalMicrograph® software, which is compatible with all pre- and post-energy-filter Gatan cameras and enables 3DED data acquisition in an automated and optimized fashion. Higher quality 3DED data enables structure determination with higher confidence, while automated workflows allow these to be completed considerably faster than before. Using multiple examples, this work will demonstrate how to direct detection electron counting cameras enhance 3DED results (3 to better than 1 Angstrom) for protein and small molecule structure determination. We will also show how Latitude D software facilitates collecting such data in an integrated and fully automated user interface.

Keywords: continuous electron diffraction tomography, direct detection, diffraction, Latitude D, Digitalmicrograph, proteins, small molecules

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Authors: Swati Kapoor, Rajeev Upreti, Monica Mahajan, Abhaya Indrayan, Dinesh Srivastava

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Enteric Fever is caused by gram negative bacilli Salmonella typhi and paratyphi. It is associated with high morbidity and mortality worldwide. Timely initiation of treatment is a crucial step for prevention of any complications. Cultures of body fluids are diagnostic, but not always conclusive or practically feasible in most centers. Moreover, the results of cultures delay the treatment initiation. Serological tests lack diagnostic value. The blood counts can offer a promising option in diagnosis. A retrospective study to find out the relevance of leucopenia and eosinopenia was conducted on 203 culture proven enteric fever patients and 159 culture proven non-enteric fever patients in a tertiary care hospital in New Delhi. The patient details were retrieved from the electronic medical records section of the hospital. Absolute eosinopenia was considered as absolute eosinophil count (AEC) of less than 40/mm³ (normal level: 40-400/mm³) using LH-750 Beckman Coulter Automated machine. Leucopoenia was defined as total leucocyte count (TLC) of less than 4 X 10⁹/l. Blood cultures were done using BacT/ALERT FA plus automated blood culture system before first antibiotic dose was given. Case and control groups were compared using Pearson Chi square test. It was observed that absolute eosinophil count (AEC) of 0-19/mm³ was a significant finding (p < 0.001) in enteric fever patients, whereas leucopenia was not a significant finding (p=0.096). Using Receiving Operating Characteristic (ROC) curves, it was observed that patients with both AEC < 14/mm³ and TCL < 8 x 10⁹/l had 95.6% chance of being diagnosed as enteric fever and only 4.4% chance of being diagnosed as non-enteric fever. This result was highly significant with p < 0.001. This is a very useful association of AEC and TLC found in enteric fever patients of this study which can be used for the early initiation of treatment in clinically suspected enteric fever patients.

Keywords: absolute eosinopenia, absolute eosinophil count, enteric fever, leucopenia, total leucocyte count

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Authors: Feiyu Yang, Chunfang Ni, Rong Wang, Yun Zou, Wenbin Liu, Chenggong Zhang, Fenjin Sun, Chun Wang

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Cocaine is the most frequently used illegal drug globally, with the global annual prevalence of cocaine used ranging from 0.3% to 0.4 % of the adult population aged 15–64 years. Growing consumption trend of abused cocaine and drug crimes are a great concern, therefore urine sample testing has become an important noninvasive sampling whereas cocaine and its metabolites (COCs) are usually present in high concentrations and relatively long detection windows. However, direct analysis of urine samples is not feasible because urine complex medium often causes low sensitivity and selectivity of the determination. On the other hand, presence of low doses of analytes in urine makes an extraction and pretreatment step important before determination. Especially, in gathered taking drug cases, the pretreatment step becomes more tedious and time-consuming. So developing a sensitive, rapid and high-throughput method for detection of COCs in human body is indispensable for law enforcement officers, treatment specialists and health officials. In this work, a new automated magnetic dispersive solid-phase extraction (MDSPE) sampling method followed by high performance liquid chromatography-mass spectrometry (HPLC-MS) was developed for quantitative enrichment of COCs from human urine, using prepared magnetic nanoparticles as absorbants. The nanoparticles were prepared by silanizing magnetic Fe3O4 nanoparticles and modifying them with divinyl benzene and vinyl pyrrolidone, which possesses the ability for specific adsorption of COCs. And this kind of magnetic particle facilitated the pretreatment steps by electromagnetically controlled extraction to achieve full automation. The proposed device significantly improved the sampling preparation efficiency with 32 samples in one batch within 40mins. Optimization of the preparation procedure for the magnetic nanoparticles was explored and the performances of magnetic nanoparticles were characterized by scanning electron microscopy, vibrating sample magnetometer and infrared spectra measurements. Several analytical experimental parameters were studied, including amount of particles, adsorption time, elution solvent, extraction and desorption kinetics, and the verification of the proposed method was accomplished. The limits of detection for the cocaine and cocaine metabolites were 0.09-1.1 ng·mL-1 with recoveries ranging from 75.1 to 105.7%. Compared to traditional sampling method, this method is time-saving and environmentally friendly. It was confirmed that the proposed automated method was a kind of highly effective way for the trace cocaine and cocaine metabolites analyses in human urine.

Keywords: automatic magnetic dispersive solid-phase extraction, cocaine detection, magnetic nanoparticles, urine sample testing

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Authors: N. C. Okoronkwo, I. E. Mbaeyi-Nwaoha, C. P. Agbata

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Childhood malnutrition is one of the most persistent public health problems throughout developing countries, including Nigeria. Demographic and Health survey data from twenty-one developing countries indicated that poor complementary feeding of children aged 6- 23 months contributes to negative growth trends. To reduce malnutrition among children in the society, formulation of complimentary food rich in essential nutrient for optimum growth and development of infants is essential. This study focused on the evaluation of complementary food produced by solid-state fermentation of Acha and Soybean using Rhizopus oligosporus (2710) and Orange-fleshed sweet potatoes (OFSP) using Lactobacillus planterum (B-41621). The raw materials were soaked separately, each in four volumes of 0.9M acetic acid for 16 hours, rinsed with clean water, steam cooked and cooled. Solid-state fermentation (SSF) was carried out by inoculating Acha and Soybean with spore suspension (1x 10⁶spores/ml) of Rhizopus oligosporus (2710) and OFSP with spore suspension (1x 106spores/ml) of Lactobacillus planterum (B-41621). Fermentation which lasted for 72hours was carried out with 24hours sampling. The samples were blended in the following ratios: Acha and soybean 100: 100 (AS), Acha/soybean and OFSP 50: 50(ASO), made into gruel and compared with a commercial infant formula (Cerelac) which served as the control (CTRL). The samples were analyzed for proximate composition using AOAC methods and sensory attributes using a hedonic scale. Results showed that moisture, crude protein, fibre and ash content increased significantly (p<0.05) as fermentation progressed, while carbohydrate and fat content decreased. The protein, moisture, fibre and ash content ranged from 17.10-19.02%, 54.97-56.27%, 7.08-7.60% and2.09-2.38%, respectively, while carbohydrate and fat content ranged from 12.95-10.21% and 5.81-4.52%, respectively. In sensory scores, there were no significant (p>0.05) difference between the average mean scores of colours, texture and consistency of the samples. The sensory score for the overall acceptability ranged from 6.20-7.80. Sample CTRL had the highest score, while sample ASO had the least score. There was no significant (p>0.05) difference between samples CTRL and AS. Solid-state fermentation improved the nutritional content and flavour of the developed complementary food, which is needed for infant growth and development.

Keywords: Complementary food, malnutrition, proximate composition, solid-state fermentation

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Authors: Antonio A. M. Laudani, Igor O. Golosnoy, Ole T. Thomsen

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Rotor blades of large, modern wind turbines are highly susceptible to downward lightning strikes, as well as to triggering upward lightning; consequently, it is necessary to equip them with an effective lightning protection system (LPS) in order to avoid any damage. The performance of existing LPSs is affected by carbon fibre reinforced polymer (CFRP) structures, which lead to lightning-induced damage in the blades, e.g. via electrical sparks. A solution to prevent internal arcing would be to electrically bond the LPS and the composite structures such that to obtain the same electric potential. Nevertheless, elevated temperatures are achieved at the joint interfaces because of high contact resistance, which melts and vaporises some of the epoxy resin matrix around the bonding. The produced high-pressure gasses open up the bonding and can ignite thermal sparks. The objective of this paper is to predict the current density distribution and the temperature field in the adhesive joint cross-section, in order to check whether the resin pyrolysis temperature is achieved and any damage is expected. The finite element method has been employed to solve both the current and heat transfer problems, which are considered weakly coupled. The mathematical model for electric current includes Maxwell-Ampere equation for induced electric field solved together with current conservation, while the thermal field is found from heat diffusion equation. In this way, the current sub-model calculates Joule heat release for a chosen bonding configuration, whereas the thermal analysis allows to determining threshold values of voltage and current density not to be exceeded in order to maintain the temperature across the joint below the pyrolysis temperature, therefore preventing the occurrence of outgassing. In addition, it provides an indication of the minimal number of bonding points. It is worth to mention that the numerical procedures presented in this study can be tailored and applied to any type of joints other than adhesive ones for wind turbine blades. For instance, they can be applied for lightning protection of aerospace bolted joints. Furthermore, they can even be customized to predict the electromagnetic response under lightning strikes of other wind turbine systems, such as nacelle and hub components.

Keywords: carbon fibre reinforced polymer, equipotential bonding, finite element method, FEM, lightning protection system, LPS, wind turbine blades

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Authors: Sharda Kumari, Saiman Shetty

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Autonomous trucking is just one of the numerous significant shifts impacting fleet management services. The Society of Automotive Engineers (SAE) has defined six levels of vehicle automation that have been adopted internationally, including by the United States Department of Transportation. On public highways in the United States, organizations are testing driverless vehicles with at least Level 4 automation which indicates that a human is present in the vehicle and can disable automation, which is usually done while the trucks are not engaged in highway driving. However, completely driverless vehicles are presently being tested in the state of California. While autonomous trucking can increase safety, decrease trucking costs, provide solutions to trucker shortages, and improve efficiencies, logistics, too, requires advancements to keep up with trucking innovations. Given that artificial intelligence, machine learning, and automated procedures enable people to do their duties in other sectors with fewer resources, CRM (Customer Relationship Management) can be applied to the autonomous trucking business to provide the same level of efficiency. In a society witnessing significant digital disruptions, fleet management is likewise being transformed by technology. Utilizing strategic alliances to enhance core services is an effective technique for capitalizing on innovations and delivering enhanced services. Utilizing analytics on CRM systems improves cost control of fuel strategy, fleet maintenance, driver behavior, route planning, road safety compliance, and capacity utilization. Integration of autonomous trucks with automated fleet management, yard/terminal management, and customer service is possible, thus having significant power to redraw the lines between the public and private spheres in autonomous trucking logistics.

Keywords: autonomous vehicles, customer relationship management, customer experience, autonomous trucking, digital transformation

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Authors: Gertraud Koch, Teresa Stumpf, Alejandra Tijerina García

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Discourse analysis research approaches belong to the central research strategies applied throughout the humanities; they focus on the countless forms and ways digital texts and images shape present-day notions of the world. Despite the constantly growing number of relevant digital, multimodal discourse resources, digital humanities (DH) methods are thus far not systematically developed and accessible for discourse analysis approaches. Specifically, the significance of multimodality and meaning plurality modelling are yet to be sufficiently addressed. In order to address this research gap, the D-WISE project aims to develop a prototypical working environment as digital support for the sociology of knowledge approach to discourse analysis and new IT-analysis approaches for the use of context-oriented embedding representations. Playing an essential role throughout our research endeavor is the constant optimization of hermeneutical methodology in the use of (semi)automated processes and their corresponding epistemological reflection. Among the discourse analyses, the sociology of knowledge approach to discourse analysis is characterised by the reconstructive and accompanying research into the formation of knowledge systems in social negotiation processes. The approach analyses how dominant understandings of a phenomenon develop, i.e., the way they are expressed and consolidated by various actors in specific arenas of discourse until a specific understanding of the phenomenon and its socially accepted structure are established. This article presents insights and initial findings from D-WISE, a joint research project running since 2021 between the Institute of Anthropological Studies in Culture and History and the Language Technology Group of the Department of Informatics at the University of Hamburg. As an interdisciplinary team, we develop central innovations with regard to the availability of relevant DH applications by building up a uniform working environment, which supports the procedure of the sociology of knowledge approach to discourse analysis within open corpora and heterogeneous, multimodal data sources for researchers in the humanities. We are hereby expanding the existing range of DH methods by developing contextualized embeddings for improved modelling of the plurality of meaning and the integrated processing of multimodal data. The alignment of this methodological and technical innovation is based on the epistemological working methods according to grounded theory as a hermeneutic methodology. In order to systematically relate, compare, and reflect the approaches of structural-IT and hermeneutic-interpretative analysis, the discourse analysis is carried out both manually and digitally. Using the example of current discourses on digitization in the healthcare sector and the associated issues regarding data protection, we have manually built an initial data corpus of which the relevant actors and discourse positions are analysed in conventional qualitative discourse analysis. At the same time, we are building an extensive digital corpus on the same topic based on the use and further development of entity-centered research tools such as topic crawlers and automated newsreaders. In addition to the text material, this consists of multimodal sources such as images, video sequences, and apps. In a blended reading process, the data material is filtered, annotated, and finally coded with the help of NLP tools such as dependency parsing, named entity recognition, co-reference resolution, entity linking, sentiment analysis, and other project-specific tools that are being adapted and developed. The coding process is carried out (semi-)automated by programs that propose coding paradigms based on the calculated entities and their relationships. Simultaneously, these can be specifically trained by manual coding in a closed reading process and specified according to the content issues. Overall, this approach enables purely qualitative, fully automated, and semi-automated analyses to be compared and reflected upon.

Keywords: entanglement of structural IT and hermeneutic-interpretative analysis, multimodality, plurality of meaning, sociology of knowledge approach to discourse analysis

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Authors: Barun Chakrabarti, Evangelos Kalamaras, Vladimir Yufit, Xinhua Liu, Billy Wu, Nigel Brandon, C. T. John Low

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In this work, we perform electrophoretic deposition of activated carbon on a number of substrates to prepare symmetrical coin cells for supercapacitor applications. From several recipes that involve the evaluation of a few solvents such as isopropyl alcohol, N-Methyl-2-pyrrolidone (NMP), or acetone to binders such as polyvinylidene fluoride (PVDF) and charging agents such as magnesium chloride, we display a working means for achieving supercapacitors that can achieve 100 F/g in a consistent manner. We then adapt this EPD method to deposit reduced graphene oxide on SGL 10AA carbon paper to achieve cathodic materials for testing in a hydrogen/vanadium flow battery. In addition, a self-supported hierarchical carbon nano-fibre is prepared by means of electrospray deposition of an iron phthalocyanine solution onto a temporary substrate followed by carbonisation to remove heteroatoms. This process also induces a degree of nitrogen doping on the carbon nano-fibres (CNFs), which allows its catalytic performance to improve significantly as detailed in other publications. The CNFs are then used as catalysts by attaching them to graphite felt electrodes facing the membrane inside an all-vanadium flow battery (Scribner cell using serpentine flow distribution channels) and efficiencies as high as 60% is noted at high current densities of 150 mA/cm². About 20 charge and discharge cycling show that the CNF catalysts consistently perform better than pristine graphite felt electrodes. Following this, we also test the CNF as an electro-catalyst in the hydrogen/vanadium flow battery (cathodic side as mentioned briefly in the first paragraph) facing the membrane, based upon past studies from our group. Once again, we note consistently good efficiencies of 85% and above for CNF modified graphite felt electrodes in comparison to 60% for pristine felts at low current density of 50 mA/cm² (this reports 20 charge and discharge cycles of the battery). From this preliminary investigation, we conclude that the CNFs may be used as catalysts for other systems such as vanadium/manganese, manganese/manganese and manganese/hydrogen flow batteries in the future. We are generating data for such systems at present, and further publications are expected.

Keywords: electrospinning, carbon nano-fibres, all-vanadium redox flow battery, hydrogen-vanadium fuel cell, electrocatalysis

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Authors: A. U. Adamu, E. D Paul, C. E. Gimba, I. G. Ndukwe

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The phytochemical and proximate composition of Aspillia kotschyi belonging to Compositae family which is commonly used as medicinal plant in Nigeria was determined on both the Methanolic and Petroleum sprit extract of the plant. The Methanolic extract of the plant revealed the presence of carbohydrates, cardiac glyscosides, flavonoids, triterpene, and alkaloids. The Petroleum sprit extract showed the presence of only carbohydrates and alkaloid. Proximate composition analysis shows moisture content of 5.7%, total ash of 4.03%, crude protein 10.94%, fibre 9.06%, fat value 0.83%, and nitrogen free extract of 70.19%. The results of this study suggest some merit in the popular use of Aspillia kotschi in herbal medicine.

Keywords: Aspillia kotschyi, herbal medicine, phytochemical, proximate composition

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Authors: Basant Singh Sikarwar, Mukesh Roy, Ayush Goyal, Priya Ranjan

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This work combines two bodies of knowledge which includes biomedical basis of blood stain formation and fluid communities’ wisdom that such formation of blood stain depends heavily on physical properties. Moreover biomedical research tells that different patterns in stains of blood are robust indicator of blood donor’s health or lack thereof. Based on these valuable insights an innovative screening tool is proposed which can act as an aide in the diagnosis of diseases such Anemia, Hyperlipidaemia, Tuberculosis, Blood cancer, Leukemia, Malaria etc., with enhanced confidence in the proposed analysis. To realize this powerful technique, simple, robust and low-cost micro-fluidic devices, a micro-capillary viscometer and a pendant drop tensiometer are designed and proposed to be fabricated to measure the viscosity, surface tension and wettability of various blood samples. Once prognosis and diagnosis data has been generated, automated linear and nonlinear classifiers have been applied into the automated reasoning and presentation of results. A support vector machine (SVM) classifies data on a linear fashion. Discriminant analysis and nonlinear embedding’s are coupled with nonlinear manifold detection in data and detected decisions are made accordingly. In this way, physical properties can be used, using linear and non-linear classification techniques, for screening of various diseases in humans and cattle. Experiments are carried out to validate the physical properties measurement devices. This framework can be further developed towards a real life portable disease screening cum diagnostics tool. Small-scale production of screening cum diagnostic devices is proposed to carry out independent test.

Keywords: blood, physical properties, diagnostic, nonlinear, classifier, device, surface tension, viscosity, wettability

Procedia PDF Downloads 372

Authors: Ahmed Belgasem, Walid Ben Hussin, Emad Krekshi, Jamal Hashad

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Waxy crude oil, characterized by its high paraffin wax content, poses significant challenges in the oil & gas industry due to its increased viscosity and semi-solid state at reduced temperatures. The wax formation process, which includes precipitation, crystallization, and deposition, becomes problematic when crude oil temperatures fall below the wax appearance temperature (WAT) or cloud point. Addressing these issues, this paper introduces a technical solution designed to mitigate the wax appearance and enhance the oil production process in Abu-Attifil Field via a 30-inch crude oil pipeline. A comprehensive flow assurance study validates the feasibility and performance of this solution across various production rates, temperatures, and operational scenarios. The study's findings indicate that maintaining the crude oil's temperature above a minimum threshold of 63°C is achievable through the strategic placement of two heating stations along the pipeline route. This approach effectively prevents wax deposition, gelling, and subsequent mobility complications, thereby bolstering the overall efficiency, reliability, safety, and economic viability of the production process. Moreover, this solution significantly curtails the environmental repercussions traditionally associated with wax deposition, which can accumulate up to 7,500kg. The research methodology involves a comprehensive flow assurance study to validate the feasibility and performance of the proposed solution. The study considers various production rates, temperatures, and operational scenarios. It includes crude oil analysis to determine the wax appearance temperature (WAT), as well as the evaluation and comparison of operating options for the heating stations. The study's findings indicate that the proposed solution effectively prevents wax deposition, gelling, and subsequent mobility complications. By maintaining the crude oil's temperature above the specified threshold, the solution improves the overall efficiency, reliability, safety, and economic viability of the oil production process. Additionally, the solution contributes to reducing environmental repercussions associated with wax deposition. The research conclusion presents a technical solution that optimizes oil production in the Abu-Attifil Field by addressing wax formation problems through the strategic placement of two heating stations. The solution effectively prevents wax deposition, improves overall operational efficiency, and contributes to environmental sustainability. Further research is suggested for field data validation and cost-benefit analysis exploration.

Keywords: oil production, wax depositions, solar cells, heating stations

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Authors: Mehmet Oren, Susan Pedersen, Sevket C. Cetin

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Despite the frequently criticized disadvantages of the traditional used paper and pencil assessment, it is the most frequently used method in our schools. Although assessments do an acceptable measurement, they are not capable of measuring all the aspects and the richness of learning and knowledge. Also, many assessments used in schools decontextualize the assessment from the learning, and they focus on learners’ standing on a particular topic but do not concentrate on how student learning changes over time. For these reasons, many scholars advocate that using simulations and games (S&G) as a tool for assessment has significant potentials to overcome the problems in traditionally used methods. S&G can benefit from the change in technology and provide a contextualized medium for assessment and teaching. Furthermore, S&G can serve as an instructional tool rather than a method to test students’ learning at a particular time point. To investigate the potentials of using educational games as an assessment and teaching tool, this study presents the implementation and the validation of an automated embedded assessment (AEA), which can constantly monitor student learning in the game and assess their performance without intervening their learning. The experiment was conducted on an undergraduate level engineering course (Digital Circuit Design) with 99 participant students over a period of five weeks in Spring 2016 school semester. The purpose of this research study is to examine if the proposed method of AEA is valid to assess student learning in a 3D Educational game and present the implementation steps. To address this question, this study inspects three aspects of the AEA for the validation. First, the evidence-centered design model was used to lay out the design and measurement steps of the assessment. Then, a confirmatory factor analysis was conducted to test if the assessment can measure the targeted latent constructs. Finally, the scores of the assessment were compared with an external measure (a validated test measuring student learning on digital circuit design) to evaluate the convergent validity of the assessment. The results of the confirmatory factor analysis showed that the fit of the model with three latent factors with one higher order factor was acceptable (RMSEA < 0.00, CFI =1, TLI=1.013, WRMR=0.390). All of the observed variables significantly loaded to the latent factors in the latent factor model. In the second analysis, a multiple regression analysis was used to test if the external measure significantly predicts students’ performance in the game. The results of the regression indicated the two predictors explained 36.3% of the variance (R2=.36, F(2,96)=27.42.56, p<.00). It was found that students’ posttest scores significantly predicted game performance (β = .60, p < .000). The statistical results of the analyses show that the AEA can distinctly measure three major components of the digital circuit design course. It was aimed that this study can help researchers understand how to design an AEA, and showcase an implementation by providing an example methodology to validate this type of assessment.

Keywords: educational video games, automated embedded assessment, assessment validation, game-based assessment, assessment design

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Authors: Shraddha Chaudhary, Raksha Agarwal, Niladri Chatterjee

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This work demonstrates a web crawler-based generalized end-to-end open domain Question Answering (QA) system. An efficient QA system requires a significant amount of domain knowledge to answer any question with the aim to find an exact and correct answer in the form of a number, a noun, a short phrase, or a brief piece of text for the user's questions. Analysis of the question, searching the relevant document, and choosing an answer are three important steps in a QA system. This work uses a web scraper (Beautiful Soup) to extract K-documents from the web. The value of K can be calibrated on the basis of a trade-off between time and accuracy. This is followed by a passage ranking process using the MS-Marco dataset trained on 500K queries to extract the most relevant text passage, to shorten the lengthy documents. Further, a QA system is used to extract the answers from the shortened documents based on the query and return the top 3 answers. For evaluation of such systems, accuracy is judged by the exact match between predicted answers and gold answers. But automatic evaluation methods fail due to the linguistic ambiguities inherent in the questions. Moreover, reference answers are often not exhaustive or are out of date. Hence correct answers predicted by the system are often judged incorrect according to the automated metrics. One such scenario arises from the original Google Natural Question (GNQ) dataset which was collected and made available in the year 2016. Use of any such dataset proves to be inefficient with respect to any questions that have time-varying answers. For illustration, if the query is where will be the next Olympics? Gold Answer for the above query as given in the GNQ dataset is “Tokyo”. Since the dataset was collected in the year 2016, and the next Olympics after 2016 were in 2020 that was in Tokyo which is absolutely correct. But if the same question is asked in 2022 then the answer is “Paris, 2024”. Consequently, any evaluation based on the GNQ dataset will be incorrect. Such erroneous predictions are usually given to human evaluators for further validation which is quite expensive and time-consuming. To address this erroneous evaluation, the present work proposes an automated approach for evaluating time-dependent question-answer pairs. In particular, it proposes a metric using the current timestamp along with top-n predicted answers from a given QA system. To test the proposed approach GNQ dataset has been used and the system achieved an accuracy of 78% for a test dataset comprising 100 QA pairs. This test data was automatically extracted using an analysis-based approach from 10K QA pairs of the GNQ dataset. The results obtained are encouraging. The proposed technique appears to have the possibility of developing into a useful scheme for gathering precise, reliable, and specific information in a real-time and efficient manner. Our subsequent experiments will be guided towards establishing the efficacy of the above system for a larger set of time-dependent QA pairs.

Keywords: web-based information retrieval, open domain question answering system, time-varying QA, QA evaluation

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Authors: Abdelkader Hadjoudja, Hajar Bouazza

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The PLD/CPLD devices are widely used for logic synthesis since several decades. Based on sum of product terms (PTs) architecture, the PLD/CPLD offer a high degree of flexibility to support various application requirements. They are suitable for large combinational logic, finite state machines as well as intensive I/O designs. CPLDs offer very predictable timing characteristics and are therefore ideal for critical control applications. This paper describes how the logic synthesis techniques, such as 1) XOR detection, 2) logic doubling, 3) complement of a Boolean function are combined, applied and used to optimize the CPLDs devices architecture that is based on PAL-like macrocells. Our goal is to use these techniques for minimizing the number of macrocells required to implement a circuit and minimize the delay of mapped circuit.

Keywords: CPLD, doubling, optimization, XOR

Procedia PDF Downloads 274

Authors: Renata Masarova, Bohuslava Juhasova, Martin Juhas, Zuzana Sutova

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In dynamic system theory a mathematical model is often used to describe their properties. In order to find a transfer matrix of a dynamic system we need to calculate an inverse matrix. The paper contains the fusion of the classical theory and the procedures used in the theory of automated control for calculating the inverse matrix. The final part of the paper models the given problem by the Matlab.

Keywords: dynamic system, transfer matrix, inverse matrix, modeling

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Authors: Vahid Rashtchi, Ashkan Pirooz

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This paper applies the Imperialist Competitive Algorithm (ICA) to find the optimal place and size of Static Compensator (STATCOM) in power systems. The output of the algorithm is a two dimensional array which indicates the best bus number and STATCOM's optimal size that minimizes all bus voltage deviations from their nominal value. Simulations are performed on IEEE 5, 14, and 30 bus test systems. Also some comparisons have been done between ICA and the famous Particle Swarm Optimization (PSO) algorithm. Results show that how this method can be considered as one of the most precise evolutionary methods for the use of optimum compensator placement in electrical grids.

Keywords: evolutionary computation, imperialist competitive algorithm, power systems compensation, static compensators, voltage profile

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Authors: Sana Ansari, Sirus Mohammadi

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In distribution systems, shunt capacitors are used to reduce power losses, to improve voltage profile, and to increase the maximum flow through cables and transformers. This paper presents a new method to determine the optimal locations and economical sizing of fixed and/or switched shunt capacitors with a view to power losses reduction and voltage stability enhancement. General Algebraic Modeling System (GAMS) has been used to solve the maximization modules using the MINOS optimization software with Linear Programming (LP). The proposed method is tested on 33 node distribution system and the results show that the algorithm suitable for practical implementation on real systems with any size.

Keywords: power losses, voltage stability, radial distribution systems, capacitor

Procedia PDF Downloads 641

Authors: Anthony I. Otuonye, Juliet N. Odii, Perpetual N. Ibe

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The obvious challenges faced by most commercial bank customers while using the services of ATMs (Automated Teller Machines) across developing countries have triggered the need for an improved system with better security features. Current ATM systems are password-based, and research has proved the vulnerabilities of these systems to heinous attacks and manipulations. We have discovered by research that the security of current ATM-assisted banking services in most developing countries of the world is easily broken and maneuvered by fraudsters, majorly because it is quite difficult for these systems to identify an impostor with privileged access as against the authentic bank account owner. Again, PIN (Personal Identification Number) code passwords are easily guessed, just to mention a few of such obvious limitations of traditional ATM operations. In this research work also, we have developed a system of fingerprint biometrics with PIN code Authentication that seeks to improve the security features of traditional ATM installations as well as other Banking Services. The aim is to ensure better security at all ATM installations and raise the confidence of bank customers. It is hoped that our system will overcome most of the challenges of the current password-based ATM operation if properly applied. The researchers made use of the OOADM (Object-Oriented Analysis and Design Methodology), a software development methodology that assures proper system design using modern design diagrams. Implementation and coding were carried out using Visual Studio 2010 together with other software tools. Results obtained show a working system that provides two levels of security at the client’s side using a fingerprint biometric scheme combined with the existing 4-digit PIN code to guarantee the confidence of bank customers across developing countries.

Keywords: fingerprint biometrics, banking operations, verification, ATMs, PIN code

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Authors: Catherine Omole

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Examination malpractice includes acts that temper with collecting accurate results during the conduct of an examination, thereby giving undue advantage to a student over his colleagues. Even though examination malpractice has been a lingering problem, examinations may not be easy to do away with completely as it is an important feedback tool in the learning process with several other functions e.g for the purpose of selection, placement, certification and promotion. Examination malpractice has created a lot of problems such as a relying on a weak work force based on false assessment results. The question is why is this problem still persisting, despite measures that have been taken to curb this ugly trend over the years? This opinion paper has identified modifications that could help relieve the student of the examination stress and thus increase the student’s effort towards effective learning and discourage examination malpractice in the long run.

Keywords: assessment, examination malpractice, learning, science classroom

Procedia PDF Downloads 254

Authors: Rishabh Beri, Sahil Shah

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We have applied a range of filters and processing in order to extract out the various features of the football game, like the field lines of a football field. Another important aspect was the detection of the players in the field and tagging them according to their teams distinguished by their jersey colours. This extracted information combined about the players and field helped us to create a virtual field that consists of the playing field and the players mapped to their locations in it.

Keywords: Detect, Football, Players, Virtual

Procedia PDF Downloads 321