Search results for: medical image processing

Authors: Siyamak Sarafraz, Reza Esmaeil Pour, Saeed Jamshidi, Asghar Molaei Dehkordi

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Cutting transport is one of the major problems in directional and extended reach oil and gas wells. Lack of sufficient attention to this issue may bring some troubles such as casing running, stuck pipe, excessive torque and drag, hole pack off, bit wear, decreased the rate of penetration (ROP), increased equivalent circulation density (ECD) and logging. Since it is practically impossible to directly observe the behavior of deep wells, a test setup was designed to investigate cutting transport phenomena. This experimental work carried out to scrutiny behavior of the effective variables in cutting transport. The test setup contained a test section with 17 feet long that made of a 3.28 feet long transparent glass pipe with 3 inch diameter, a storage tank with 100 liters capacity, drill pipe rotation which made of stainless steel with 1.25 inches diameter, pump to circulate drilling fluid, valve to adjust flow rate, bit and a camera to record all events which then converted to RGB images via the Image Processing Toolbox. After preparation of test process, each test performed separately, and weights of the output particles were measured and compared with each other. Observation charts were plotted to assess the behavior of viscosity, flow rate and RPM in inclinations of 0°, 30°, 60° and 90°. RPM was explored with other variables such as flow rate and viscosity in different angles. Also, effect of different flow rate was investigated in directional conditions. To access the precise results, captured image were analyzed to find out bed thickening and particles behave in the annulus. The results of this experimental study demonstrate that drill string rotation helps particles to be suspension and reduce the particle deposition cutting movement increased significantly. By raising fluid velocity, laminar flow converted to turbulence flow in the annulus. Increases in flow rate in horizontal section by considering a lower range of viscosity is more effective and improved cuttings transport performance.

Keywords: cutting transport, directional drilling, flow rate, hole cleaning, pipe rotation

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Authors: Zeineb Yousse, Fakher Kharrat

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Mosaic is a part of a broad universal cultural heritage; sometimes it represents a rather essential source for the researches on the everyday life of some of the previous civilizations. Tunisia has one of the finest and largest collections of mosaics in the world, which is essentially exhibited in the Museums of Bardo and Sousse. Restored and reconstituted, they bear witnesses to hard work. Our paper deals with the discipline of conservation of Roman mosaics based on the proceedings of the workshop of the Museum of Sousse. Thus, we highlight two main objectives. In the first place, it is a question of revealing the techniques adopted by professionals to handle mosaics and to which school of conservation these techniques belong. In the second place, we are going to interpret the works initiated to preserve the archaeological heritage in order to protect it in present time and transmit it to future generations. To this end, we paid attention to four Roman mosaics currently exhibited in the Museum of Sousse. These Mosaics show different voids or gaps at the level of their surfaces and the method used to fill these gaps seems to be interesting to analyze. These mosaics are known under the names of: Orpheus Charming the Animals, Gladiator and Bears, Stud farm of Sorothus and finally Head of Medusa. The study on the conservation passes through two chained phases. We start with a small historical overview in order to gather information related to the original location, the date of its composition as well as the description of its image. Afterward, the intervention process is analyzed by handling three complementary elements which are: diagnosis of the existing state, the study of the medium processing and the study of the processing of the tesselatum surface which includes the pictorial composition of the mosaic. Furthermore, we have implemented an evaluation matrix with six operating principles allowing the assessment of the appropriateness of the intervention. These principles are the following: minimal intervention, reversibility, compatibility, visibility, durability, authenticity and enhancement. Various accumulated outcomes are pointing out the techniques used to fill the gaps as well as the level of compliance with the principles of conservation. Accordingly, the conservation of mosaics in Tunisia is a practice that combines various techniques without really arguing about the choice of a particular theory.

Keywords: conservation, matrix, museum of Sousse, operating particular theory, principles, Roman mosaics

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Authors: Abdelghani Chahmi

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This article examines the detection and localization of faults in electrical systems, particularly those using asynchronous machines. First, the process of failure will be characterized, relevant symptoms will be defined and based on those processes and symptoms, a model of those malfunctions will be obtained. Second, the development of the diagnosis of the machine will be shown. As studies of malfunctions in electrical systems could only rely on a small amount of experimental data, it has been essential to provide ourselves with simulation tools which allowed us to characterize the faulty behavior. Fault detection uses signal processing techniques in known operating phases.

Keywords: induction motor, modeling, bearing damage, airgap eccentricity, torque variation

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Authors: Rahul Mohite, Lahcen Ouarbya

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This paper focuses on the interplay between humans and computer systems and the ability of these systems to understand and respond to human emotions, including non-verbal communication. Current emotion recognition systems are based solely on either facial or verbal expressions. The limitation of these systems is that it requires large training data sets. The paper proposes a system for recognizing human emotions that combines both speech and emotion recognition. The system utilizes advanced techniques such as deep learning and image recognition to identify facial expressions and comprehend emotions. The results show that the proposed system, based on the combination of facial expression and speech, outperforms existing ones, which are based solely either on facial or verbal expressions. The proposed system detects human emotion with an accuracy of 86%, whereas the existing systems have an accuracy of 70% using verbal expression only and 76% using facial expression only. In this paper, the increasing significance and demand for facial recognition technology in emotion recognition are also discussed.

Keywords: facial reputation, expression reputation, deep gaining knowledge of, photo reputation, facial technology, sign processing, photo type

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Authors: Okhee Woo, Hye Seon Shin

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Purpose: To investigate the diagnostic power of digital breast tomosynthesis (DBT) in evaluation of breast microcalcifications and usefulness as a pre-procedural study for stereotactic biopsy in comparison with full-field digital mammogram (FFDM) and FFDM plus magnification image (FFDM+MAG). Methods and Materials: An IRB approved retrospective observer performance study on DBT, FFDM, and FFDM+MAG was done. Image quality was rated in 5-point scoring system for lesion clarity (1, very indistinct; 2, indistinct; 3, fair; 4, clear; 5, very clear) and compared by Wilcoxon test. Diagnostic power was compared by diagnostic values and AUC with 95% confidence interval. Additionally, procedural report of biopsy was analysed for patient positioning and adequacy of instruments. Results: DBT showed higher lesion clarity (median 5, interquartile range 4-5) than FFDM (3, 2-4, p-value < 0.0001), and no statistically significant difference to FFDM+MAG (4, 4-5, p-value=0.3345). Diagnostic sensitivity and specificity of DBT were 86.4% and 92.5%; FFDM 70.4% and 66.7%; FFDM+MAG 93.8% and 89.6%. The AUCs of DBT (0.88) and FFDM+MAG (0.89) were larger than FFDM (0.59, p-values < 0.0001) but there was no statistically significant difference between DBT and FFDM+MAG (p-value=0.878). In 2 cases with DBT, petit needle could be appropriately prepared; and other 3 without DBT, patient repositioning was needed. Conclusion: DBT showed better image quality and diagnostic values than FFDM and equivalent to FFDM+MAG in the evaluation of breast microcalcifications. Evaluation with DBT as a pre-procedural study for breast stereotactic biopsy can lead to more accurate localization and successful biopsy and also waive the need for additional magnification images.

Keywords: DBT, breast cancer, stereotactic biopsy, mammography

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Authors: Rui Du

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This paper attempts to assess the impact of a major sporting event —the Super Bowl on the local economies. The identification strategy is to compare the winning and losing cities at the National Football League (NFL) conference finals under the assumption of similar pre-treatment trends. The stock market performances of companies headquartered in these cities are used to capture the sudden changes in local economic activities during a short time span. The exogenous variations in the football game outcome allow a straightforward difference-in-differences approach to identify the effect. This study finds that the post-event trends in winning and losing cities diverge despite the fact that both cities have economically and statistically similar pre-event trends. Empirical analysis provides suggestive evidence of a positive, significant local economic impact of conference final wins, possibly through city image enhancement. Further empirical evidence shows the presence of heterogeneous effects across industrial sectors, suggesting that city image enhancing the effect of the Super Bowl participation is empirically relevant for the changes in the composition of local industries. Also, this study also adopts a similar strategy to examine the local economic impact of Super Bowl successes, however, finds no statistically significant effect.

Keywords: Super Bowl Participation, local economies, city image enhancement, difference-in-differences, industrial sectors

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Authors: N. Ghatwary, A. Ahmed, H. Jalab

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In this paper, an approach for the liver tumor detection in computed tomography (CT) images is represented. The detection process is based on classifying the features of target liver cell to either tumor or non-tumor. Fractional differential (FD) is applied for enhancement of Liver CT images, with the aim of enhancing texture and edge features. Later on, a fusion method is applied to merge between the various enhanced images and produce a variety of feature improvement, which will increase the accuracy of classification. Each image is divided into NxN non-overlapping blocks, to extract the desired features. Support vector machines (SVM) classifier is trained later on a supplied dataset different from the tested one. Finally, the block cells are identified whether they are classified as tumor or not. Our approach is validated on a group of patients’ CT liver tumor datasets. The experiment results demonstrated the efficiency of detection in the proposed technique.

Keywords: fractional differential (FD), computed tomography (CT), fusion, aplha, texture features.

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Authors: Sarah Ullrich, Juliane Rolle, Christian Beste, Nicole Wolff

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Inhibition and cognitive flexibility are essential parts of executive functions in our daily lives, as they enable the avoidance of unwanted responses or selectively switch between mental processes to generate appropriate behavior. There is growing interest in improving inhibition and response selection through brief mindfulness-based meditations. Arguably, open-monitoring meditation (OMM) improves inhibitory and flexibility performance by optimizing cognitive control and information processing. Yet, the underlying neurophysiological processes have been poorly studied. Using the Simon-Go/Nogo paradigm, the present work examined the effect of a single 15-minute smartphone app-based OMM on inhibitory performance and response selection in meditation novices. We used both behavioral and neurophysiological measures (event-related potentials, ERPs) to investigate which subprocesses of response selection and inhibition are altered after OMM. The study was conducted in a randomized crossover design with N = 32 healthy adults. We thereby investigated Go and Nogo trials in the paradigm. The results show that as little as 15 minutes of OMM can improve response selection and inhibition at behavioral and neurophysiological levels. More specifically, OMM reduces the rate of false alarms, especially during Nogo trials regardless of congruency. It appears that OMM optimizes conflict processing and response inhibition compared to no meditation, also reflected in the ERP N2 and P3 time windows. The results may be explained by the meta control model, which argues in terms of a specific processing mode with increased flexibility and inclusive decision-making under OMM. Importantly, however, the effects of OMM were only evident when there was the prior experience with the task. It is likely that OMM provides more cognitive resources, as the amplitudes of these EKPs decreased. OMM novices seem to induce finer adjustments during conflict processing after familiarization with the task.

Keywords: EEG, inhibition, meditation, Simon Nogo

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Authors: Alireza Akbari, Gelareh Babaee Khou

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Ground Penetrating Radar (GPR) is an important nondestructive remote sensing tool that has been used in both military and civilian fields. Recently, GPR imaging has attracted lots of attention in detection of subsurface shallow small targets such as landmines and unexploded ordnance and also imaging behind the wall for security applications. For the monostatic arrangement in the space-time GPR image, a single point target appears as a hyperbolic curve because of the different trip times of the EM wave when the radar moves along a synthetic aperture and collects reflectivity of the subsurface targets. With this hyperbolic curve, the resolution along the synthetic aperture direction shows undesired low resolution features owing to the tails of hyperbola. However, highly accurate information about the size, electromagnetic (EM) reflectivity, and depth of the buried objects is essential in most GPR applications. Therefore hyperbolic curve behavior in the space-time GPR image is often willing to be transformed to a focused pattern showing the object's true location and size together with its EM scattering. The common goal in a typical GPR image is to display the information of the spatial location and the reflectivity of an underground object. Therefore, the main challenge of GPR imaging technique is to devise an image reconstruction algorithm that provides high resolution and good suppression of strong artifacts and noise. In this paper, at first, the standard back-projection (BP) algorithm that was adapted to GPR imaging applications used for the image reconstruction. The standard BP algorithm was limited with against strong noise and a lot of artifacts, which have adverse effects on the following work like detection targets. Thus, an improved BP is based on cross-correlation between the receiving signals proposed for decreasing noises and suppression artifacts. To improve the quality of the results of proposed BP imaging algorithm, a weight factor was designed for each point in region imaging. Compared to a standard BP algorithm scheme, the improved algorithm produces images of higher quality and resolution. This proposed improved BP algorithm was applied on the simulation and the real GPR data and the results showed that the proposed improved BP imaging algorithm has a superior suppression artifacts and produces images with high quality and resolution. In order to quantitatively describe the imaging results on the effect of artifact suppression, focusing parameter was evaluated.

Keywords: algorithm, back-projection, GPR, remote sensing

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Authors: Magdalena Chrabąszcz, Teresa Wolniewicz, Cezary Maciejewski, Joanna Czuwara

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BACKGROUND: Dermoscopy is a clinical tool known to improve the early detection of melanoma and other malignancies of the skin. Over the past few years melanoma has grown into a disease of socio-economic importance due to the increasing incidence and persistently high mortality rates. Early diagnosis remains the best method to reduce melanoma and non-melanoma skin cancer– related mortality and morbidity. Dermoscopy is a noninvasive technique that consists of viewing pigmented skin lesions through a hand-held lens. This simple procedure increases melanoma diagnostic accuracy by up to 35%. Dermoscopy is currently the standard for clinical differential diagnosis of cutaneous melanoma and for qualifying lesion for the excision biopsy. Like any clinical tool, training is required for effective use. The introduction of small and handy dermoscopes contributed significantly to the switch of dermatoscopy toward a first-level useful tool. Non-dermatologist physicians are well positioned for opportunistic melanoma detection; however, education in the skin cancer examination is limited during medical school and traditionally lecture-based. AIM: The aim of this randomized study was to determine whether the adjunct of dermoscopy to the standard fourth year medical curriculum improves the ability of medical students to distinguish between benign and malignant lesions and assess acceptability and satisfaction with the intervention. METHODS: We performed a prospective study in 2 cohorts of fourth-year medical students at Medical University of Warsaw. Groups having dermatology course, were randomly assigned to:  cohort A: with limited access to dermatoscopy from their teacher only – 1 dermatoscope for 15 people  Cohort B: with a full access to use dermatoscopy during their clinical classes:1 dermatoscope for 4 people available constantly plus 15-minute dermoscopy tutorial. Students in both study arms got an image-based test of 10 lesions to assess ability to differentiate benign from malignant lesions and postintervention survey collecting minimal background information, attitudes about the skin cancer examination and course satisfaction. RESULTS: The cohort B had higher scores than the cohort A in recognition of nonmelanocytic (P < 0.05) and melanocytic (P <0.05) lesions. Medical students who have a possibility to use dermatoscope by themselves have also a higher satisfaction rates after the dermatology course than the group with limited access to this diagnostic tool. Moreover according to our results they were more motivated to learn dermatoscopy and use it in their future everyday clinical practice. LIMITATIONS: There were limited participants. Further study of the application on clinical practice is still needed. CONCLUSION: Although the use of dermatoscope in dermatology as a specialty is widely accepted, sufficiently validated clinical tools for the examination of potentially malignant skin lesions are lacking in general practice. Introducing medical students to dermoscopy in their fourth year curricula of medical school may improve their ability to differentiate benign from malignant lesions. It can can also encourage students to use dermatoscopy in their future practice which can significantly improve early recognition of malignant lesions and thus decrease melanoma mortality.

Keywords: dermatoscopy, early detection of melanoma, medical education, skin cancer

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Authors: Sucihatiningsih Dian Wisika Prajanti, Himawan Arif Susanto

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Fruits are perishable products and have relatively low price, especially at harvest time. Generally, farmers only sell the products shortly after the harvest time without any processing. Farmers also only play role as price takers leading them to have less power to set the price. Sometimes, farmers are manipulated by middlemen, especially during abundant harvest. Therefore, it requires an effort to cultivate fruits and create innovation to make them more durable and have higher economic value. The purpose of this research is how to increase the added- value of fruits that have high economic value. The research involved 60 farmers of Salak fruit as the sample. Then, descriptive analysis was used to analyze the data in this study. The results showed the selling price of Salak fruit is very low. Hence, to increase the added-value of the fruits, fruit processing is carried out by freezing - frying which can cause the fruits last longer. In addition to increase these added-value, the products can be accommodated for further processed without worrying about their crops rotted or unsold.

Keywords: fruits processing, Salak fruit, freezing frying, farmer’s welfare, Sleman, Yogyakarta

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Authors: Amina Aquil, Abdeljalil El Got

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Background: Sleep quality is one of the most important indicators related to the quality of life of patients suffering from cancer. Many factors could affect this quality of sleep and then be considered as associated predictors. Methods: The aim of this study was to assess the prevalence of sleep disorders and the associated factors with impaired sleep quality in Moroccan women with gynecological cancer. A cross-sectional study was carried out within the oncology department of the Ibn Rochd University Hospital, Casablanca, on Moroccan women who had undergone radical surgery for gynecological cancer (n=100). Translated and validated Arabic versions of the following international scales were used: Pittsburgh sleep quality index (PSQI), Hospital Anxiety and Depression Scale (HADS), Rosenberg's self-esteem scale (RSES), and Body image scale (BIS). Results: 78% of participants were considered poor sleepers. Most of the patients exhibited very poor subjective quality, low sleep latency, a short period of sleep, and a low rate of usual sleep efficiency. The vast majority of these patients were in poor shape during the day and did not use sleep medication. Waking up in the middle of the night or early in the morning and getting up to use the bathroom were the main reasons for poor sleep quality. PSQI scores were positively correlated with anxiety, depression, body image dissatisfaction, and lower self-esteem (p < 0.001). Conclusion: Sleep quality and its predictors require a systematic evaluation and adequate management to prevent sleep disturbances and mental distress as well as to improve the quality of life of these patients.

Keywords: body image, gynecological cancer, self esteem, sleep quality

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Authors: Thomas Ousterhout

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In an effort to test the ability of a commercial grade EEG headset to effectively measure the N400 ERP, a replication study was conducted to see if similar results could be produced as that which used a medical grade EEG. Pictures of meaningful and meaningless hand postures were borrowed from the original author and subjects were required to perform a semantic discrimination task. The N400 was detected indicating semantic processing of the meaningfulness of the hand postures. The results corroborate those of the original author and support the use of some commercial grade EEG headsets for non-critical research applications.

Keywords: EEG, ERP, N400, semantics, congruency, gestures, emotiv

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Authors: Elena Antonova Unlu, Cigdem Sagin Simsek

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The research presents two studies examining the impact of formal interpreting training (FIT) on Working Memory Capacity (WMC) of student-interpreters. In Study 1, the storage and processing capacities of the working memory (WM) of last-year student-interpreters were compared with those of last-year Foreign Language Education (FLE) students. In Study 2, the impact of FIT on the WMC of student-interpreters was examined via comparing their results on WM tasks at the beginning and the end of their FIT. In both studies, Digit Span Task (DST) and Reading Span Task (RST) were utilized for testing storage and processing capacities of WM. The results of Study 1 revealed that the last-year student-interpreters outperformed the control groups on the RST but not on the DST. The findings of Study 2 were consistent with Study 1 showing that after FIT, the student-interpreters performed better on the RST but not on the DST. Our findings can be considered as evidence supporting the view that FIT has a beneficial effect not only on the interpreting skills of student-interpreters but also on the central executive and processing capacity of their WM.

Keywords: working memory capacity, formal interpreting training, student-interpreters, cross-sectional and longitudinal data

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Authors: Sankaran Rajendran

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Remote sensing plays a vital role in mapping of resources and monitoring of environments of the earth. In the present research study, mapping and monitoring of clay siltations occurred in the Alkhod Dam of Muscat, Sultanate of Oman are carried out using low-cost multispectral Landsat and ASTER data. The dam is constructed across the Wadi Samail catchment for ground water recharge. The occurrence and spatial distribution of siltations in the dam are studied with five years of interval from the year 1987 of construction to 2014. The deposits are mainly due to the clay, sand, and silt occurrences derived from the weathering rocks of ophiolite sequences occurred in the Wadi Samail catchment. The occurrences of clays are confirmed by minerals identification using ASTER VNIR-SWIR spectral bands and Spectral Angle Mapper supervised image processing method. The presence of clays and their spatial distribution are verified in the field. The study recommends the technique and the low-cost satellite data to similar region of the world.

Keywords: Alkhod Dam, ASTER siltation, Landsat, remote sensing, Oman

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Authors: Rios A. S., Hild F., Deus E. P., Aimedieu P., Benallal A.

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The damage micromechanisms of chopped strand mats manufactured by compression of Brazilian coconut fiber and coconut fibers in different external conditions (chemical treatment) were used in this study. Mechanical analysis testing uniaxial traction were used with Digital Image Correlation (DIC). The images captured during the tensile test in the coconut fibers and coconut fiber mats showed an uncertainty of measurement in order centipixels. The initial modulus (modulus of elasticity) and tensile strength decreased with increasing diameter for the four conditions of coconut fibers. The DIC showed heterogeneous deformation fields for coconut fibers and mats and the displacement fields showed the rupture process of coconut fiber. The determination of poisson’s ratio of the mat was performed through of transverse and longitudinal deformations found in the elastic region.

Keywords: coconut fiber, mechanical behavior, digital image correlation, micromechanism

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Authors: Christopher Schwarz, Katrin Riegler, Erwin Zinser

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The management of outsourcing relationships between IT service providers and their customers proofs to be a critical issue that has to be stipulated by means of Service Level Agreements (SLAs). Since service requirements differ from customer to customer, SLA content and language structures vary largely, standardized SLA templates may not be used and an automated processing of SLA content is not possible. Hence, SLA management is usually a time-consuming and inefficient manual process. For overcoming these challenges, this paper presents an innovative and ITIL V3-conform approach for automated SLA design and management using controlled natural language in enterprise collaboration portals. The proposed novel concept is based on a self-developed controlled natural language that follows a subject-predicate-object approach to specify well-defined SLA content structures that act as templates for customized contracts and support automated SLA processing. The derived results eventually enable IT service providers to automate several SLA request, approval and negotiation processes by means of workflows and business rules within an enterprise collaboration portal. The illustrated prototypical realization gives evidence of the practical relevance in service-oriented scenarios as well as the high flexibility and adaptability of the presented model. Thus, the prototype enables the automated creation of well defined, customized SLA documents, providing a knowledge representation that is both human understandable and machine processable.

Keywords: automated processing, controlled natural language, knowledge representation, information technology outsourcing, service level management

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Authors: O. Iyare, A. H. Afolayan, O. T. Oluwadare, B. K. Alese

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Access to advanced medical services has been one of the medical challenges faced by our present society especially in distant geographical locations which may be inaccessible. Then the need for telemedicine arises through which live videos of a doctor can be streamed to a patient located anywhere in the world at any time. Patients’ medical records contain very sensitive information which should not be made accessible to unauthorized people in order to protect privacy, integrity and confidentiality. This research work focuses on a more robust security measure which is biometric (fingerprint) as a form of access control to data of patients by the medical specialist/practitioner.

Keywords: biometrics, telemedicine, privacy, patient information

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Authors: Nougrara Zineb

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The unique structure of the blood vessels in the retina has been used for biometric identification. The retina blood vessel pattern is a unique pattern in each individual and it is almost impossible to forge that pattern in a false individual. The retina biometrics’ advantages include high distinctiveness, universality, and stability overtime of the blood vessel pattern. Once the creases have been extracted from the images, a registration stage is necessary, since the position of the retinal vessel structure could change between acquisitions due to the movements of the eye. Image registration consists of following steps: Feature detection, feature matching, transform model estimation and image resembling and transformation. In this paper, we present an algorithm of registration; it is based on the characterization of retinal feature points. For experiments, retinal images from the DRIVE database have been tested. The proposed methodology achieves good results for registration in general.

Keywords: fovea, optic disc, registration, retinal images

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Authors: W. H. El Garaihy, A. Nassef, S. Samy

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Equal channel angular pressing (ECAP) of commercial Al-Mg-Si alloy was conducted using two strain rates. The ECAP processing was conducted at room temperature and at 250 °C. Route A was adopted up to a total number of four passes in the present work. Structural evolution of the aluminum alloy discs was investigated before and after ECAP processing using optical microscopy (OM). Following ECAP, simple compression tests and Vicker’s hardness were performed. OM micrographs showed that, the average grain size of the as-received Al-Mg-Si disc tends to be larger than the size of the ECAP processed discs. Moreover, significant difference in the grain morphologies of the as-received and processed discs was observed. Intensity of deformation was observed via the alignment of the Al-Mg-Si consolidated particles (grains) in the direction of shear, which increased with increasing the number of passes via ECAP. Increasing the number of passes up to 4 resulted in increasing the grains aspect ratio up to ~5. It was found that the pressing temperature has a significant influence on the microstructure, Hv-values, and compressive strength of the processed discs. Hardness measurements demonstrated that 1-pass resulted in increase of Hv-value by 42% compared to that of the as-received alloy. 4-passes of ECAP processing resulted in additional increase in the Hv-value. A similar trend was observed for the yield and compressive strength. Experimental data of the Hv-values demonstrated that there is a lack of any significant dependence on the processing strain rate.

Keywords: Al-Mg-Si alloy, equal channel angular pressing, grain refinement, severe plastic deformation

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Authors: Chirawat Wattanapanich, Hong Wei

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This study presents new gait representations for improving gait recognition accuracy on cross gait appearances, such as normal walking, wearing a coat and carrying a bag. Based on the Gait Energy Image (GEI), two ideas are implemented to generate new gait representations. One is to append lower knee regions to the original GEI, and the other is to apply convolutional operations to the GEI and its variants. A set of new gait representations are created and used for training multi-class Support Vector Machines (SVMs). Tests are conducted on the CASIA dataset B. Various combinations of the gait representations with different convolutional kernel size and different numbers of kernels used in the convolutional processes are examined. Both the entire images as features and reduced dimensional features by Principal Component Analysis (PCA) are tested in gait recognition. Interestingly, both new techniques, appending the lower knee regions to the original GEI and convolutional GEI, can significantly contribute to the performance improvement in the gait recognition. The experimental results have shown that the average recognition rate can be improved from 75.65% to 87.50%.

Keywords: convolutional image, lower knee, gait

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Authors: Eiman Kattan, Hong Wei

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In using Convolutional Neural Network (CNN) for classification, there is a set of hyperparameters available for the configuration purpose. This study aims to evaluate the impact of a range of parameters in CNN architecture i.e. AlexNet on land cover classification based on four remotely sensed datasets. The evaluation tests the influence of a set of hyperparameters on the classification performance. The parameters concerned are epoch values, batch size, and convolutional filter size against input image size. Thus, a set of experiments were conducted to specify the effectiveness of the selected parameters using two implementing approaches, named pertained and fine-tuned. We first explore the number of epochs under several selected batch size values (32, 64, 128 and 200). The impact of kernel size of convolutional filters (1, 3, 5, 7, 10, 15, 20, 25 and 30) was evaluated against the image size under testing (64, 96, 128, 180 and 224), which gave us insight of the relationship between the size of convolutional filters and image size. To generalise the validation, four remote sensing datasets, AID, RSD, UCMerced and RSCCN, which have different land covers and are publicly available, were used in the experiments. These datasets have a wide diversity of input data, such as number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in both training and testing. The results have shown that increasing the number of epochs leads to a higher accuracy rate, as expected. However, the convergence state is highly related to datasets. For the batch size evaluation, it has shown that a larger batch size slightly decreases the classification accuracy compared to a small batch size. For example, selecting the value 32 as the batch size on the RSCCN dataset achieves the accuracy rate of 90.34 % at the 11th epoch while decreasing the epoch value to one makes the accuracy rate drop to 74%. On the other extreme, setting an increased value of batch size to 200 decreases the accuracy rate at the 11th epoch is 86.5%, and 63% when using one epoch only. On the other hand, selecting the kernel size is loosely related to data set. From a practical point of view, the filter size 20 produces 70.4286%. The last performed image size experiment shows a dependency in the accuracy improvement. However, an expensive performance gain had been noticed. The represented conclusion opens the opportunities toward a better classification performance in various applications such as planetary remote sensing.

Keywords: CNNs, hyperparamters, remote sensing, land cover, land use

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Authors: Yangzhi Li

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Network transfer of information and performance customization is now a viable method of digital industrial production in the era of Industry 4.0. Robot platforms and network platforms have grown more important in digital design and construction. The pressing need for novel building techniques is driven by the growing labor scarcity problem and increased awareness of construction safety. Robotic approaches in construction research are regarded as an extension of operational and production tools. Several technological theories related to robot autonomous recognition, which include high-performance computing, physical system modeling, extensive sensor coordination, and dataset deep learning, have not been explored using intelligent construction. Relevant transdisciplinary theory and practice research still has specific gaps. Optimizing high-performance computing and autonomous recognition visual guidance technologies improves the robot's grasp of the scene and capacity for autonomous operation. Intelligent vision guidance technology for industrial robots has a serious issue with camera calibration, and the use of intelligent visual guiding and identification technologies for industrial robots in industrial production has strict accuracy requirements. It can be considered that visual recognition systems have challenges with precision issues. In such a situation, it will directly impact the effectiveness and standard of industrial production, necessitating a strengthening of the visual guiding study on positioning precision in recognition technology. To best facilitate the handling of complicated components, an approach for the visual recognition of parts utilizing machine learning algorithms is proposed. This study will identify the position of target components by detecting the information at the boundary and corner of a dense point cloud and determining the aspect ratio in accordance with the guidelines for the modularization of building components. To collect and use components, operational processing systems assign them to the same coordinate system based on their locations and postures. The RGB image's inclination detection and the depth image's verification will be used to determine the component's present posture. Finally, a virtual environment model for the robot's obstacle-avoidance route will be constructed using the point cloud information.

Keywords: robotic construction, robotic assembly, visual guidance, machine learning

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Authors: Kaaryn M. Cater

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Students with sensory processing sensitivity (SPS), Meares-Irlen Syndrome (MIS) and dyslexia can become overwhelmed and struggle to thrive in traditional tertiary learning environments. An estimated 50% of tertiary students who disclose learning related issues are dyslexic. This study explores the relationship between SPS, MIS and dyslexia. Baseline measures will be analysed to establish any correlation between these three minority methods of information processing. SPS is an innate sensitivity trait found in 15-20% of the population and has been identified in over 100 species of animals. Humans with SPS are referred to as Highly Sensitive People (HSP) and the measure of HSP is a 27 point self-test known as the Highly Sensitive Person Scale (HSPS). A 2016 study conducted by the author established base-line data for HSP students in a tertiary institution in New Zealand. The results of the study showed that all participating HSP students believed the knowledge of SPS to be life-changing and useful in managing life and study, in addition, they believed that all tutors and in-coming students should be given information on SPS. MIS is a visual processing and perception disorder that is found in approximately 10% of the population and has a variety of symptoms including visual fatigue, headaches and nausea. One way to ease some of these symptoms is through the use of colored lenses or overlays. Dyslexia is a complex phonological based information processing variation present in approximately 10% of the population. An estimated 50% of dyslexics are thought to have MIS. The study exploring possible correlations between these minority forms of information processing is due to begin in February 2017. An invitation will be extended to all first year students enrolled in degree programmes across all faculties and schools within the institution. An estimated 900 students will be eligible to participate in the study. Participants will be asked to complete a battery of on-line questionnaires including the Highly Sensitive Person Scale, the International Dyslexia Association adult self-assessment and the adapted Irlen indicator. All three scales have been used extensively in literature and have been validated among many populations. All participants whose score on any (or some) of the three questionnaires suggest a minority method of information processing will receive an invitation to meet with a learning advisor, and given access to counselling services if they choose. Meeting with a learning advisor is not mandatory, and some participants may choose not to receive help. Data will be collected using the Question Pro platform and base-line data will be analysed using correlation and regression analysis to identify relationships and predictors between SPS, MIS and dyslexia. This study forms part of a larger three year longitudinal study and participants will be required to complete questionnaires at annual intervals in subsequent years of the study until completion of (or withdrawal from) their degree. At these data collection points, participants will be questioned on any additional support received relating to their minority method(s) of information processing. Data from this study will be available by April 2017.

Keywords: dyslexia, highly sensitive person (HSP), Meares-Irlen Syndrome (MIS), minority forms of information processing, sensory processing sensitivity (SPS)

Procedia PDF Downloads 218

Authors: Muhammad Bilal Shaikh

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Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

Procedia PDF Downloads 56

Authors: Christine H. Cubelo

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This study consists of 2-parts: a systematic review of current publications on the therapeutic use of autonomous sensory meridian response (ASMR) and a within-subjects auditory training trial using ASMR videos. The main intent is to explore ASMR as potentially therapeutically beneficial for those with atypical sensory processing. Many hearing-related disorders and mood or anxiety symptoms overlap with symptoms of sensory processing issues. For this reason, inclusion and exclusion criteria of the systematic review were generated in an effort to produce optimal search outcomes and avoid overly confined criteria that would limit yielded results. Criteria for inclusion in the review for Part 1 are (1) adult participants diagnosed with hearing loss or atypical sensory processing, (2) inclusion of measures related to ASMR as a treatment method, and (3) published between 2000 and 2022. A total of 1,088 publications were found in the preliminary search, and a total of 13 articles met the inclusion criteria. A total of 14 participants completed the trial and post-trial questionnaire. Of all responses, 64.29% agreed that the duration of auditory training sessions was reasonable. In addition, 71.43% agreed that the training improved their perception of music. Lastly, 64.29% agreed that the training improved their perception of a primary talker when there are other talkers or background noises present.

Keywords: autonomous sensory meridian response, auditory training, atypical sensory processing, hearing loss, hearing aids

Procedia PDF Downloads 46

Authors: Yaeji Lim, Hee-Seok Oh

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The coherence analysis measures the linear time-invariant relationship between two data sets and has been studied various fields such as signal processing, engineering, and medical science. However classical coherence analysis tends to be sensitive to outliers and focuses only on mean relationship. In this paper, we generalized cross periodogram to quantile cross periodogram and provide richer inter-relationship between two data sets. This is a general version of Laplace cross periodogram. We prove its asymptotic distribution under the long range process and compare them with ordinary coherence through numerical examples. We also present real data example to confirm the usefulness of quantile coherence analysis.

Keywords: coherence, cross periodogram, spectrum, quantile

Procedia PDF Downloads 376

Authors: Mohd Iz'aan Paiz Bin Zamri, Anis Salwa Mohd Khairuddin, Norrima Mokhtar, Rubiyah Yusof

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Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.

Keywords: classification, feature extraction, fuzzy, inspection system, image analysis, macroscopic images

Procedia PDF Downloads 407

Authors: Atilla Tekin

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Amorium was one of the biggest cities of Byzantine Empire, located under and around the modern village of Hisarköy, Emirdağ, Afyonkarahisar Province, Turkey. It was situated on the routes of trades and Byzantine military road from Constantinople to Cilicia. In addition, it was on the routes of trades and a center of bishopric. After Arab invasion, Amorium gradually lost importance. The research consists of 1372 pieces of glass bracelet finds from mostly at 1998- 2009 excavations. Most of them were found as glass bracelets fragments. The fragments are of various size, forms, colors, and decorations. During the research, they were measured and grouped according to their crossings, at first. After being photographed, they were sketched by Adobe Illustrator and decoupaged by Photoshop. All forms, colors, and decorations were specified and compared to each other. Thus, they have been tried to be dated and uncovered the place of manufacture. The importance of the research is presenting the perception of image and admiration and comparing with other cultures.

Keywords: Amorium, glass bracelets, image, Byzantine empire, jewelry

Procedia PDF Downloads 179

Authors: Itsuo Yokoyama, Rikako Kikuti, Miti Sekikawa, Tosinori Asai, Sarai Tsuyoshi

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Introduction: Vascular access for hemodialysis therapy is often difficult, even for experienced medical personnel. Ultrasound guided needle placement have been performed occasionally but is not always helpful in certain cases with complicated vascular anatomy. Obtaining precise anatomical knowledge of the vascular structure is important to prevent access-related complications. With augmented reality (AR) device such as AR glasses, the virtual vascular structure is shown superimposed on the actual patient vessels, thus enabling the operator to maneuver catheter placement easily with free both hands. We herein report our method of AR guided vascular access method in dialysis treatment Methods: Three dimensional (3D) object of the arm with arteriovenous fistula is computer graphically created with 3D software from the data obtained by computer tomography, ultrasound echogram, and image scanner. The 3D vascular object thus created is viewed on the screen of the AR digital display device (such as AR glass or iPad). The picture of the vascular anatomical structure becomes visible, which is superimposed over the real patient’s arm, thereby the needle insertion be performed under the guidance of AR visualization with ease. By this method, technical difficulty in catheter placement for dialysis can be lessened and performed safely. Considerations: Virtual reality technology has been applied in various fields and medical use is not an exception. Yet AR devices have not been widely used among medical professions. Visualization of the virtual vascular object can be achieved by creation of accurate three dimensional object with the help of computer graphical technique. Although our experience is limited, this method is applicable with relative easiness and our accumulating evidence has suggested that our method of vascular access with the use of AR can be promising.

Keywords: abdominal-aorta, calcification, extraskeletal, dialysis, computer graphics, 3DCG, CT, calcium, phosphorus

Procedia PDF Downloads 122