Search results for: feature detection and description

Authors: Julia Desiree Velastegui Caceres, Luis Alejandro Velastegui Caceres, Oswaldo Padilla, Eduardo Kirby, Francisco Guerrero, Theofilos Toulkeridis

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It is fundamental to conserve sites of natural and cultural heritage with any available technique or existing methodology of preservation in order to sustain them for the following generations. We propose a further skill to protect the actual view of such sites, in which with high technology instrumentation we are able to digitally preserve natural and cultural heritages applied in Ecuador. In this project the use of laser technology is presented for three-dimensional models, with high accuracy in a relatively short period of time. In Ecuador so far, there are not any records on the use and processing of data obtained by this new technological trend. The importance of the project is the description of the methodology of the laser scanner system using the Faro Laser Scanner Focus 3D 120, the method for 3D modeling of geospatial data and the development of virtual environments in the areas of Cultural and Natural Heritage. In order to inform users this trend in technology in which three-dimensional models are generated, the use of such tools has been developed to be able to be displayed in all kinds of digitally formats. The results of the obtained 3D models allows to demonstrate that this technology is extremely useful in these areas, but also indicating that each data campaign needs an individual slightly different proceeding starting with the data capture and processing to obtain finally the chosen virtual environments.

Keywords: laser scanner system, 3D model, cultural heritage, natural heritage

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Authors: Giovanni Gonzalez Araujo, Michael Kyrilov, Angelo Kyrilov

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STEAMplug is a web-based innovative educational platform which makes teaching easier and learning more effective. It requires no setup, eliminating the barriers to entry, allowing students to focus on their learning throughreal-world development environments. The student-centric tools enable easy collaboration between peers and teachers. Analyzing user interactions with the system enables us to predict student performance and identify at-risk students, allowing early instructor intervention.

Keywords: plagiarism detection, identifying at-Risk Students, education technology, e-learning system, collaborative development, learning and teaching with technology

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Authors: Adeolu O. Dairo

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Getting the consumer marketing strategy right is a crucial and complex task for firms with a large customer base such as mobile operators in a competitive mobile market. While empirical studies have made efforts to identify key constructs, no geospatial model has been developed to comprehensively assess the viability and interdependency of ground realities regarding the customer, competition, channel and the network quality of mobile operators. With this research, a geo-analytic framework is proposed for strategy formulation and allocation for mobile operators. Firstly, a fuzzy analytic network using a self-organizing feature map clustering technique based on inputs from managers and literature, which depicts the interrelationships amongst ground realities is developed. The model is tested with a mobile operator in the Nigeria mobile market. As a result, a customer-centric geospatial and visualization solution is developed. This provides a consolidated and integrated insight that serves as a transparent, logical and practical guide for strategic, tactical and operational decision making.

Keywords: geospatial, geo-analytics, self-organizing map, customer-centric

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Authors: Meghamala Nugehally

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This paper hypothesises and draws inferences on the impact of minimalism in dance education on the development of artistic and aesthetic sensibilities in individuals in the age group of 5-18 yrs of age. This research and conclusions are within the context of Indian Classical Dance, which is based on Indian theories of aesthetics drawn from the Natyashastra, an ancient treatise on Indian dance and drama. The research employs training methods handed down through a strict one-on-one teacher-student tradition known as the Guru-Shishya Parampara. Aesthetic principles used are defined, and basic theories from the Natyashastra are explained to provide background for the research design. The paper also discusses dance curriculum design and training methodology design within the context of these aesthetic theories. The scope of the research is limited to two genres of Indian classical forms: Bharatanatyam and Odissi. A brief description of these dance forms is given as background and dance aesthetics specific to these forms are described. The research design includes individual case studies of subjects studied, independent predetermined attributes for observations and a qualitative scoring methodology devised for the purpose of the study. The study describes the training techniques used and contrasts minimal solo training techniques with the more elaborate group training techniques. Study groups were divided and the basis for the division are discussed. Study observations are recorded and presented as evidences. The results inform the conclusion and set the stage for further research in this area.

Keywords: dance aesthetics, dance education, Indian classical dance, minimalism

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Authors: Marcio Freire Cruz, Naoaki Ono, Shigehiko Kanaya, Carlos Arthur Mattos Teixeira Cavalcante

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The systems that record patient care information, known as Electronic Medical Record (EMR) and those that monitor vital signs of patients, such as heart rate, body temperature, and blood pressure have been extremely valuable for the effectiveness of the patient’s treatment. Several kinds of research have been using data from EMRs and vital signs of patients to predict illnesses. Among them, we highlight those that intend to predict, classify, or, at least identify patterns, of sepsis illness in patients under vital signs monitoring. Sepsis is an organic dysfunction caused by a dysregulated patient's response to an infection that affects millions of people worldwide. Early detection of sepsis is expected to provide a significant improvement in its treatment. Preceding works usually combined medical, statistical, mathematical and computational models to develop detection methods for early prediction, getting higher accuracies, and using the smallest number of variables. Among other techniques, we could find researches using survival analysis, specialist systems, machine learning and deep learning that reached great results. In our research, patients are modeled as points moving each hour in an n-dimensional space where n is the number of vital signs (variables). These points can reach a sepsis target point after some time. For now, the sepsis target point was calculated using the median of all patients’ variables on the sepsis onset. From these points, we calculate for each hour the position vector, the first derivative (velocity vector) and the second derivative (acceleration vector) of the variables to evaluate their behavior. And we construct a prediction model based on a Long Short-Term Memory (LSTM) Network, including these derivatives as explanatory variables. The accuracy of the prediction 6 hours before the time of sepsis, considering only the vital signs reached 83.24% and by including the vectors position, speed, and acceleration, we obtained 94.96%. The data are being collected from Medical Information Mart for Intensive Care (MIMIC) Database, a public database that contains vital signs, laboratory test results, observations, notes, and so on, from more than 60.000 patients.

Keywords: dynamic analysis, long short-term memory, prediction, sepsis

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Authors: Shima Soltanzadeh, Mohammad Hosain Fazel Zarandi, Mojtaba Barzegar Astanjin

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Diagnosis of male infertility by the laboratory tests is expensive and, sometimes it is intolerable for patients. Filling out the questionnaire and then using classification method can be the first step in decision-making process, so only in the cases with a high probability of infertility we can use the laboratory tests. In this paper, we evaluated the performance of four classification methods including naive Bayesian, neural network, logistic regression and fuzzy c-means clustering as a classification, in the diagnosis of male infertility due to environmental factors. Since the data are unbalanced, the ROC curves are most suitable method for the comparison. In this paper, we also have selected the more important features using a filtering method and examined the impact of this feature reduction on the performance of each methods; generally, most of the methods had better performance after applying the filter. We have showed that using fuzzy c-means clustering as a classification has a good performance according to the ROC curves and its performance is comparable to other classification methods like logistic regression.

Keywords: classification, fuzzy c-means, logistic regression, Naive Bayesian, neural network, ROC curve

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Authors: Sapan Tiwari, Namrata Ghosh

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In urban mass transit, crew scheduling always plays a significant role. It deals with the formulation of work timetables for its staff so that an organization can meet the demand for its products or services. The efficient schedules of a specified timetable have an enormous impact on staff demand. It implies that an urban mass transit company's financial outcomes are strongly associated with planning operations in the region. The research aims to demonstrate the state of the crew scheduling studies and its practical implementation in mass transit businesses in metropolitan areas. First, there is a short overview of past studies in the field. Subsequently, the restrictions and problems with crew scheduling and some models, which have been developed to solve the related issues with their mathematical formulation, are defined. The comments are completed by a description of the solution opportunities provided by computer-aided scheduling program systems for operational use and exposures from urban mass transit organizations. Furthermore, Bus scheduling is performed using the Hungarian technique of problem-solving tasks and mathematical modeling. Afterward, the crew scheduling problem, which consists of developing duties using predefined tasks with set start and end times and places, is resolved. Each duty has to comply with a set line of work. The objective is to minimize a mixture of fixed expenses (number of duties) and varying costs. After the optimization of cost, the outcome of the research is that the same frequency can be provided with fewer buses and less workforce.

Keywords: crew scheduling, duty, optimization of cost, urban mass transit

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Authors: Alexander Hudson, Shaogang Gong

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Structure determination is key to understanding protein function at a molecular level. Whilst significant advances have been made in predicting structure and function from amino acid sequence, researchers must still rely on expensive, time-consuming analytical methods to visualise detailed protein conformation. In this study, we demonstrate that it is possible to make accurate (≥80%) predictions of protein class and architecture from structures determined at low (>3A) resolution, using a deep convolutional neural network trained on high-resolution (≤3A) structures represented as 2D matrices. Thus, we provide proof of concept for high-speed, low-cost protein structure classification at low resolution, and a basis for extension to prediction of function. We investigate the impact of the input representation on classification performance, showing that side-chain information may not be necessary for fine-grained structure predictions. Finally, we confirm that high resolution, low-resolution and NMR-determined structures inhabit a common feature space, and thus provide a theoretical foundation for boosting with single-image super-resolution.

Keywords: transfer learning, protein distance maps, protein structure classification, neural networks

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Authors: Roscoe McLean, Jared Padayachee, Glen Bright

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There is currently a gap in the technology covering the rapid establishment of control after a reconfiguration in a Reconfigurable Manufacturing System. This gap involves the detection of the factory floor state and the communication link between the factory floor and the high-level software. In this paper, a thin, hardware-supported Middleware Management System (MMS) is proposed and its design and implementation are discussed. The research found that a cost-effective localization technique can be combined with intelligent software to speed up the ramp-up of a reconfigured system. The MMS makes the process more intelligent, more efficient and less time-consuming, thus supporting the industrial implementation of the RMS paradigm.

Keywords: intelligent systems, middleware, reconfigurable manufacturing, management system

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Authors: Hyunho Shin, Jaekwang Jung, Jeongho Park, Sungwon Hwang

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For the application of graphene quantum dots (GQDs) to optoelectronic nanodevices, it is of critical importance to understand the mechanisms which result in novel phenomena of their light absorption/emission. The optical transitions are known to be available up to ~6 eV in GQDs, especially useful for ultraviolet (UV) photodetectors (PDs). Here, we present size-dependent shape/edge-state variations of GQDs and visible photoluminescence (PL) showing anomalous size dependencies. With varying the average size (da) of GQDs from 5 to 35 nm, the peak energy of the absorption spectra monotonically decreases, while that of the visible PL spectra unusually shows nonmonotonic behaviors having a minimum at diameter ∼17 nm. The PL behaviors can be attributed to the novel feature of GQDs, that is, the circular-to-polygonal-shape and corresponding edge-state variations of GQDs at diameter ∼17 nm as the GQD size increases, as demonstrated by high resolution transmission electron microscopy. We believe that such a comprehensive scheme in designing device architecture and the structural formulation of GQDs provides a device for practical realization of environmentally benign, high performance flexible devices in the future.

Keywords: graphene, quantum dot, size, photoluminescence

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Authors: H. Hotait, X. Chiementin, L. Rasolofondraibe

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This paper presents a continuous work to detect the abnormal state in the rolling bearing by studying the vibration signature analysis and calculation of the remaining useful life. To achieve these aims, two methods; the first method is the classification to detect the degradation state by the AOM-OPTICS (Acousto-Optic Modulator) method. The second one is the prediction of the degradation state using least-squares support vector regression and then compared with the linear degradation model. An experimental investigation on ball-bearing was conducted to see the effectiveness of the used method by applying the acquired vibration signals. The proposed model for predicting the state of bearing gives us accurate results with the experimental and numerical data.

Keywords: bearings, automatization, optimization, prognosis, classification, defect detection

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Authors: Prathiksha Kamath, Pratibha Jamkhandi, Prateek Ghanti, Priyanshu Gupta, M. Lakshmi Neelima

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Combining Image Captioning and Visual Question Answering (VQA) tasks have emerged as a new and exciting research area. The image captioning task involves generating a textual description that summarizes the content of the image. VQA aims to answer a natural language question about the image. Both these tasks include computer vision and natural language processing (NLP) and require a deep understanding of the content of the image and semantic relationship within the image and the ability to generate a response in natural language. There has been remarkable growth in both these tasks with rapid advancement in deep learning. In this paper, we present a comprehensive review of recent progress in combining image captioning and visual question-answering (VQA) tasks. We first discuss both image captioning and VQA tasks individually and then the various ways in which both these tasks can be integrated. We also analyze the challenges associated with these tasks and ways to overcome them. We finally discuss the various datasets and evaluation metrics used in these tasks. This paper concludes with the need for generating captions based on the context and captions that are able to answer the most likely asked questions about the image so as to aid the VQA task. Overall, this review highlights the significant progress made in combining image captioning and VQA, as well as the ongoing challenges and opportunities for further research in this exciting and rapidly evolving field, which has the potential to improve the performance of real-world applications such as autonomous vehicles, robotics, and image search.

Keywords: image captioning, visual question answering, deep learning, natural language processing

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Authors: Justo Rodriguez, Daming Chen, Amador M. Guzman

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The detection, treatment, and control of rapidly propagating, deadly viruses such as COVID-19, require the development of inexpensive, fast, and accurate devices to address the urgent needs of the population. Microfluidics-based sensors are amongst the different methods and techniques for detection that are easy to use. A micro analyzer is defined as a microfluidics-based sensor, composed of a network of microchannels with varying functions. Given their size, portability, and accuracy, they are proving to be more effective and convenient than other solutions. A micro analyzer based on the concept of “Lab on a Chip” presents advantages concerning other non-micro devices due to its smaller size, and it is having a better ratio between useful area and volume. The integration of multiple processes in a single microdevice reduces both the number of necessary samples and the analysis time, leading the next generation of analyzers for the health-sciences. In some applications, the flow of solution within the microchannels is originated by a pressure gradient, which can produce adverse effects on biological samples. A more efficient and less dangerous way of controlling the flow in a microchannel-based analyzer is applying an electric field to induce the fluid motion and either enhance or suppress the mixing process. Electrokinetic flows are characterized by no less than two non-dimensional parameters: the electric Rayleigh number and its geometrical aspect ratio. In this research, stable and unstable flows have been studied numerically (and when possible, will be experimental) in a T-shaped microchannel. Additionally, unstable electrokinetic flows for Rayleigh numbers higher than critical have been characterized. The flow mixing enhancement was quantified in relation to the stretching and folding that fluid particles undergo when they are subjected to supercritical electrokinetic flows. Computational simulations were carried out using a finite element-based program while working with the flow mixing concepts developed by Gollub and collaborators. Hundreds of seeded massless particles were tracked along the microchannel from the entrance to exit for both stable and unstable flows. After post-processing, their trajectories, the folding and stretching values for the different flows were found. Numerical results show that for supercritical electrokinetic flows, the enhancement effects of the folding and stretching processes become more apparent. Consequently, there is an improvement in the mixing process, ultimately leading to a more homogenous mixture.

Keywords: microchannel, stretching and folding, electro kinetic flow mixing, micro-analyzer

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Authors: Latifah Putti Tiananda, Sasti Khoirunnisa, Taniadiana Yapwito, Jessica Noviena

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Innovations are often met with two responses, acceptance or rejection. In the past few years, Indonesia is experiencing a revolution of transportation service, which utilizes online platform for its operation. Such improvement is welcomed by consumers and challenged by conventional or ‘non-online’ transportation providers simultaneously. Conflicts arise as the existence of this online transportation mode results in declining income of non-online transportation workers. Physical confrontations and demonstrations demand policing from central authority. However, the obscurity of legal measures from the government persists the social instability. Bandung, a city in West Java with the highest rate of online transportation usage, has recently issued a recommendation withholding the operation of online transportation services to maintain peace and order. Thus, this paper seeks to elaborate the social unrest between the two contesting transportation actors in Bandung and explore community-based approaches to solve this problem. Using qualitative research method, this paper will also feature in-depth interviews with directly involved sources from Bandung.

Keywords: Bandung, market competition, online transportation services, social unrest

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Authors: Yunyong Guo, Man Wang, Bryan Guo, Nathan Guo

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This paper introduces an advanced security and privacy model tailored for Telehealth systems, emphasizing end-to-end protection across IoT, Fog, and Cloud components. The proposed model integrates encryption, key management, intrusion detection, and privacy-preserving measures to safeguard patient data. A comprehensive simulation study evaluates the model's effectiveness in scenarios such as unauthorized access, physical breaches, and insider threats. Results indicate notable success in detecting and mitigating threats yet underscore areas for refinement. The study contributes insights into the intricate balance between security and usability in Telehealth environments, setting the stage for continued advancements.

Keywords: cloud, enhancing security, fog, IoT, telehealth

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Authors: Chao-Ming Su, Pei-Sheng Wu, Yu-Chi Kuo, Yin-Chou Huang, Tan-Yueh Chen, Jefunnie Matahum, Tzong-Rong Ger

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Application of magnetic particles (MPs) has been applied in biomedical field for many years. There are lots of advantages through this mediator including high biocompatibility and multi-diversified bio-applications. However, current techniques for evaluating the quantity of the magnetic-labeled sample assays are rare. In this paper, a Wheatstone bridge giant magnetoresistance (GMR) sensor integrated with a homemade detecting system was fabricated and used to quantify the concentration of MPs. The homemade detecting system has shown high detecting sensitivity of 10 μg/μl of MPs with optimized parameter vertical magnetic field 100 G, horizontal magnetic field 2 G and flow rate 0.4 ml/min.

Keywords: magnetic particles, magnetoresistive sensors, microfluidics, biosensor

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Authors: Mohamed Bekheit Gad Khaleil

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The Maadi was a civilization .It is considered one of the oldest civilizations in the world and an area of prehistoric times, especially the civilization (Nakada 1&2 ) It contains the oldest stone house in the history. Many excavations have been done in this area. This report was prepared under my supervision and in cooperation with the German institute .The stone building was redocumented, photographed and drawn once again . The stone building has been built carefully. The measurements for this building are (8m x 4m).and the depth of this building is 2m underground and an entrance located at the eastern part of the northern wall and it has three huge pits in the middle of the building seem to have contained wooden posts, most probably to support the roof. The use of the building is unclear. Circular impressions in front of the north wall and in the south-eastern part of the floor indicate that much of it was a storehouse for numerous vessels such as unique feature may have not only served for private domestic purposes. Before starting work in any site, instruction must be followed :- 1-Gather as much information about this place as possible . (Historical background - previous excavations - maps - pictures) 2-Writing, recording, describing and documenting 3- Draw a map of the site showing the place’s division system (trenches) 4- Safe ( Workers & The Place )

Keywords: photographing, excavations, documentation, registration

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Authors: Samira Karimi-Mansoub, Rahem Abri

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Currently, users expect high quality and personalized information from search results. To satisfy user’s needs, personalized approaches to web search have been proposed. These approaches can provide the most appropriate answer for user’s needs by using user context and incorporating information about query provided by combining search technologies. To carry out personalized web search, there is a need to make different techniques on whole of user search process. There are the number of possible deployment of personalized approaches such as personalized web search, personalized recommendation, personalized summarization and filtering systems and etc. but the common feature of all approaches in various domains is that user modeling is utilized to provide personalized information from the Web. So the most important work in personalized approaches is user model mining. User modeling applications and technologies can be used in various domains depending on how the user collected information may be extracted. In addition to, the used techniques to create user model is also different in each of these applications. Since in the previous studies, there was not a complete survey in this field, our purpose is to present a survey on applications and techniques of user modeling from the viewpoint of improvement in search results by considering the existing literature and researches.

Keywords: filtering systems, personalized web search, user modeling, user search behavior

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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: Mariana Mangas, Yaroslava Martins, Ana Charraz, Ana Matos Pires

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Introduction: Health literacy empowers people of knowledge, motivation and skills to access, understand, evaluate and mobilize information relating to health. Although the benefits of public knowledge of physical disease are widely accepted, knowledge about mental disorder has been compatibly neglected. Nowadays there is considerably evidence that literacy is of great importance for the promotion of health and prevention of mental illness. Objective: Disclosure the concept and importance of mental health literacy and introduce the literacy program of Psychiatry Service of Hospital José Joaquim Fernandes. Methodology: A search was conducted on PubMed, using keywords “literacy” and “mental health”. A description of mental health literacy interventions implemented on Psychiatry Service of Hospital José Joaquim Fernandes was performed, namely, psychoeducation programs for depression and bipolar disorder. Results and discussion: Health literacy enables patient to be able to actively participate in his treatment. The improving of mental health literacy can promote early identification of mental disorders, improve treatment results, increase the use of health services and allow the community to take action to achieve better mental health. Psychoeducation is very useful in improving the course of disease and in reducing the number of episodes and hospitalizations. Bipolar patients who received psychoeducation and pharmacotherapy have no relapses during the program and last year. Conclusion: Mental health literacy is not simply a matter of having knowledge, rather, it is knowledge linked to action which can benefit mental health.

Keywords: mental health, literacy, psychoeducation, knowledge, empowerment

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Authors: Javad Khaligh, Aghileh Heydari, Ali Akbar Heydari

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Mathematical epidemiological models for the spread of disease through a population are used to predict the prevalence of a disease or to study the impacts of treatment or prevention measures. Initial conditions for these models are measured from statistical data collected from a population since these initial conditions can never be exact, the presence of chaos in mathematical models has serious implications for the accuracy of the models as well as how epidemiologists interpret their findings. This paper confirms the chaotic behavior of a model for dengue fever and SI by investigating sensitive dependence, bifurcation, and 0-1 test under a variety of initial conditions.

Keywords: epidemiological models, SEIR disease model, bifurcation, chaotic behavior, 0-1 test

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Authors: Souheila Zemmouchi

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Introduction: Diabetes is currently the leading cause of end-stage chronic kidney disease and dialysis, so it adds additional complexity to the management of chronic hemodialysis patients. These patients are extremely fragile because of their multiple cardiovascular and metabolic comorbidities. Clear and complete description of the experience: the management of a diabetic on hemodialysis is particularly difficult due to frequent hypoglycaemia and significant inter and perdialyticglycemic variability that is difficult to predict. The aim of our study is to describe the clinical-biological profile and to assess the cardiovascular risk of diabetics undergoing chronic hemodialysis, and compare them with non-diabetic hemodialysis patients. Methods: This cross-sectional, descriptive, and analytical study was carried out between January 01 and December 31, 2018, involving 309 hemodialysis patients spread over 4 centersThe data were collected prospectively then compiled and analyzed by the SPSS Version 10 software The FRAMINGHAM RISK SCORE has been used to assess cardiovascular risk in all hemodialysis patients Results: The survey involved 309 hemodialysis patients, including 83 diabetics, for a prevalence of 27% The average age 53 ± 10.2 years. The sex ratio is 1.5. 50% of diabetic hemodialysis patients retained residual diuresis against 32% in non-diabetics. In the group of diabetics, we noted more hypertension (70% versus 38% non-diabetics P 0.004), more intradialytichypoglycemia (15% versus 3% non-diabetics P 0.007), initially, vascular exhaustion was found in 4 diabetics versus 2 non-diabetics. 70% of diabetics with anuria had postdialytichyperglycemia. The study found a statistically significant difference between the different levels of cardiovascular risk according to the diabetic status. Conclusion: There are many challenges in the management of diabetics on hemodialysis, both to optimize glycemic control according to an individualized target and to coordinate comprehensive and effective care.

Keywords: hemodialysis, diabetes, chronic renal failure, glycemic control

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Authors: Yunha Ryu, Kyoungsik Kim

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Raman spectroscopy is one of the most powerful techniques for chemical detection, but the low sensitivity originated from the extremely small cross-section of the Raman scattering limits the practical use of Raman spectroscopy. To overcome this problem, Surface Enhanced Raman Scattering (SERS) has been intensively studied for several decades. Because the SERS effect is mainly induced from strong electromagnetic near-field enhancement as a result of localized surface plasmon resonance of metallic nanostructures, it is important to design the plasmonic structures with high density of electromagnetic hot spots for SERS substrate. One of the useful fabrication methods is using porous nanomaterial as a template for metallic structure. Internal pores on a scale of tens of nanometers can be strong EM hotspots by confining the incident light. Also, porous structures can capture more target molecules than non-porous structures in a same detection spot thanks to the large surface area. Herein we report the facile fabrication method of porous SERS substrate by integrating solvent-assisted nanoimprint lithography and selective etching of block copolymer. We obtained nanostructures with high porosity via simple selective etching of the one microdomain of the diblock copolymer. Furthermore, we imprinted of the nanocone patterns into the spin-coated flat block copolymer film to make three-dimensional SERS substrate for the high density of SERS hot spots as well as large surface area. We used solvent-assisted nanoimprint lithography (SAIL) to reduce the fabrication time and cost for patterning BCP film by taking advantage of a solvent which dissolves both polystyrenre and poly(methyl methacrylate) domain of the block copolymer, and thus block copolymer film was molded under the low temperature and atmospheric pressure in a short time. After Ag deposition, we measured Raman intensity of dye molecules adsorbed on the fabricated structure. Compared to the Raman signals of Ag coated solid nanocone, porous nanocone showed 10 times higher Raman intensity at 1510 cm(-1) band. In conclusion, we fabricated porous metallic nanocone arrays with high density electromagnetic hotspots by templating nanoimprinted diblock copolymer with selective etching and demonstrated its capability as an effective SERS substrate.

Keywords: block copolymer, porous nanostructure, solvent-assisted nanoimprint, surface-enhanced Raman spectroscopy

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Authors: Nadia Syed

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The digital age has inevitably changed the way in which hate crime is committed. The cyber world has become a highly effective means for individuals and groups to be targeted, harmed, and marginalized , largely through online medium. Facebook has become one of the fastest growing social media platforms. At the end of 2013, Facebook had 1,23bn monthly active users and 757 million daily users who log onto Facebook. Within this online space, there are also an increasing number of online virtual communities, and hate groups who are using this freedom to share a violent, Islamophobic and racist description which attempts to create a aggressive virtual environment. This paper is a research on the rise of Islamophobia and the role of media in spreading it. This paper focusing on how the media especially Facebook is portraying Islam as the religion which promotes violence and ultimately playing a significant role in the global rise of Islamophobia against Muslims. It is important to analyse these ‘new’ communities by monitoring the activities they conduct, because the material they post, potentially can have a harmful impact on community cohesion within society. Additionally, as a result of recent figures that shows an increase in online anti-Muslim abuse, there is a pertinent need to address the issue about Islamophobia on social media. On the whole, this study found Muslims being demonized and vilified online which had manifested through negative attitudes, discrimination, stereotypes, physical threats and online harassment which all had the potential to incite violence or prejudicial action because it disparages and intimidates a protected individual or group.

Keywords: Islamophobia, online, social media, facebook, internet, extremism

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Authors: Khaled Saad Eldin Mohamed Ragab

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This paper investigates analytically the torsion behavior of steel fibered high strength self compacting concrete beams reinforced by GFRP bars. Nonlinear finite element analysis on 12­ beams specimens was achieved by using ANSYS software. The nonlinear finite element analysis program ANSYS is utilized owing to its capabilities to predict either the response of reinforced concrete beams in the post elastic range or the ultimate strength of a reinforced concrete beams produced from steel fiber reinforced self compacting concrete (SFRSCC) and reinforced by GFRP bars. A general description of the finite element method, theoretical modeling of concrete and reinforcement are presented. In order to verify the analytical model used in this research using test results of the experimental data, the finite element analysis were performed. Then, a parametric study of the effect ratio of volume fraction of steel fibers in ordinary strength concrete, the effect ratio of volume fraction of steel fibers in high strength concrete, and the type of reinforcement of stirrups were investigated. A comparison between the experimental results and those predicted by the existing models are presented. Results and conclusions thyat may be useful for designers have been raised and represented.

Keywords: nonlinear analysis, torsionally loaded, self compacting concrete, steel fiber reinforced self compacting concrete (SFRSCC), GFRP bars and sheets

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Authors: Haonan Hu, Shuge Lei, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Jijun Tang

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This paper focuses on the classification task of breast ultrasound images and conducts research on the reliability measurement of classification results. A dual-channel evaluation framework was developed based on the proposed inference reliability and predictive reliability scores. For the inference reliability evaluation, human-aligned and doctor-agreed inference rationals based on the improved feature attribution algorithm SP-RISA are gracefully applied. Uncertainty quantification is used to evaluate the predictive reliability via the test time enhancement. The effectiveness of this reliability evaluation framework has been verified on the breast ultrasound clinical dataset YBUS, and its robustness is verified on the public dataset BUSI. The expected calibration errors on both datasets are significantly lower than traditional evaluation methods, which proves the effectiveness of the proposed reliability measurement.

Keywords: medical imaging, ultrasound imaging, XAI, uncertainty measurement, trustworthy AI

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Authors: Faozia A. S. Abuhtana, Yahia S. Abujnah, Said O. Gnann

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Ultra High Temperature (UHT) processed milk is widely distributed and preferred in numerous countries all over the world due its relatively high quality and long shelf life. Because of the notable high consumption rate of UHT in Libya in addition to negligible studies related to such product on the local level, this study was designed to assess the shelf life of locally produced as well as imported reconstituted sterilized whole milk samples marketed in Tripoli, Libya . Four locally produced vs. three imported brands were used in this study. All samples were stored at room temperature (25± 2C ) for 8 month long period, and subjected to physical, chemical, microbiological and sensory tests. These tests included : measurement of pH, specific gravity, percent acidity, and determination of fat, protein and melamine content. Microbiological tests included total aerobic count, total psychotropic bacteria, total spore forming bacteria and total coliform counts. Results indicated no detection of microbial growth of any type during the study period, in addition to no detection of melamine in all samples. On the other hand, a gradual decline in pH accompanied with gradual increase in % acidity of both locally produced and imported samples was observed. Such changes in both pH and % acidity reached their lowest and highest values respectively during the 24th week of storage. For instance pH values were (6.40, 6.55, 6.55, 6.15) and (6.30, 6.50, 6.20) for local and imported brands respectively. On the other hand, % acidity reached (0.185, 0181, 0170, 0183) and (0180, 0.180, 0.171) at the 24th week for local and imported brands respectively. Similar pattern of decline was also observed in specific gravity, fat and protein content in some local and imported samples especially at later stages of the study. In both cases, some of the recorded pH values, % acidity, sp. gravity and fat content were in violation of the accepted limits set by Libyan standard no. 356 for sterilized milk. Such changes in pH, % acidity and other UHT sterilized milk constituents during storage were coincided with a gradual decrease in the degree of acceptance of the stored milk samples of both types as shown by sensory scores recorded by the panelists. In either case degree of acceptance was significantly low at late stages of storage and most milk samples became relatively unacceptable after the 18th and 20th week for both untrained and trained panelists respectively.

Keywords: UHT milk, shelf life, quality, gravity, bacteria

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Authors: Pedro Rubio

Abstract:

Antonio Romero y Andía, was one of the most active and interesting figures in 19th century Spanish music. He was not only an exceptional clarinetist, he was also a publisher, a brilliant oboist, a music critic, and he revitalized Madrid’s musical scene by promoting orchestras and a national opera. In 1849, Romero was appointed Professor of Clarinet at the Conservatory of Madrid. Shortly after, Romero introduced to Spain the Boehm-System clarinet recently appeared in France. However, when initial interest in that system waned, he conceived his own system in 1853. The clarinet was manufactured in Paris by Lefêvre, who registered its first patent in 1862. In 1867 a second version was patented, and a year earlier, in 1866, the Romero clarinet was adopted as an official instrument for teaching the clarinet at the Conservatory of Madrid. The Romero-System clarinet mechanism has incorporated numerous additional devices and several extra keys, its skillful combination in a single instrument represents not only one of the pinnacles in the manufacture of musical instruments of the 19th century, but also an authentic synthesis of knowledge and practice in an era in which woodwind instruments were shaped as we know them today. Through the description and analysis of the data related to the aforementioned historical period, this lecture will try to show a crucial time in the history of all woodwind instruments, a period of technological effervescence in which the Romero-System clarinet emerged. The different stages of conception of the clarinet will be described, as well as its manufacturing and marketing process. Romero played with his clarinet system over twenty-five years. The research has identified the repertoire associated with this instrument whose conclusions will be presented in its case in the Congress.

Keywords: Antonio Romero, clarinet, keywork, 19th century

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Authors: Francisco Lobo

Abstract:

Kant’s household theory of human dignity as a common feature of all rational beings is the starting point of any intellectual endeavor to unravel the implications of this normative notion. Yet, it is incomplete, as it neglects considering the importance of the singularity or uniqueness of the individual. In a first, deconstructive stage, this paper describes the Kantian account of human dignity as one among many conceptions of human dignity. It reads carefully into the original wording used by Kant in German and its English translations, as well as the works of modern commentators, to identify its shortcomings. In a second, constructive stage, it then draws on the theories of Aristotle, Alexis de Tocqueville, John Stuart Mill, and Hannah Arendt to try and enhance the Kantian conception, in the sense that these authors give major importance to the singularity of the individual. The Kantian theory can be perfected by including elements from the works of these authors, while at the same time being mindful of the dangers entailed in focusing too much on singularity. The conclusion of this paper is that the Kantian conception of human dignity can be enhanced if it acknowledges that not only morality has dignity, but also the irreplaceable human individual to the extent that she is a narrative, original creature with the potential to act morally.

Keywords: commonality, dignity, Kant, singularity

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Authors: Zhaoxin Luo, Michael Zhu

Abstract:

In natural languages, there are always complex semantic hierarchies. Obtaining the feature representation based on these complex semantic hierarchies becomes the key to the success of the model. Several RNN models have recently been proposed to use latent indicators to obtain the hierarchical structure of documents. However, the model that only uses a single-layer latent indicator cannot achieve the true hierarchical structure of the language, especially a complex language like Chinese. In this paper, we propose a deep layered model that stacks arbitrarily many RNN layers equipped with latent indicators. After using EM and training it hierarchically, our model solves the computational problem of stacking RNN layers and makes it possible to stack arbitrarily many RNN layers. Our deep hierarchical model not only achieves comparable results to large pre-trained models on the Chinese short text classification problem but also achieves state of art results on the Chinese long text classification problem.

Keywords: nature language processing, recurrent neural network, hierarchical structure, document classification, Chinese

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