Search results for: visual features

Authors: Raid R. O. Al-Nima, S. S. Dlay, W. L. Woo

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A relationship between face and signature biometrics is established in this paper. A new approach is developed to predict faces from signatures by using artificial intelligence. A multilayer perceptron (MLP) neural network is used to generate face details from features extracted from signatures, here face is the physical biometric and signatures is the behavioural biometric. The new method establishes a relationship between the two biometrics and regenerates a visible face image from the signature features. Furthermore, the performance efficiencies of our new technique are demonstrated in terms of minimum error rates compared to published work.

Keywords: behavioural biometric, face biometric, neural network, physical biometric, signature biometric

Procedia PDF Downloads 464

Authors: Nadia Selene Molina-Moreno, Maria Susana Avila-Garcia, Marco Bianchetti, Marcelina Pantoja-Flores

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Visual Programming Tools available are a great tool for introducing children to programming and to develop a skill set for algorithmic thinking. On the other hand, collaborative learning and pair programming within the context of programming activities, has demonstrated to have social and learning benefits. However, some of the online tools available for programming for children are not designed to allow simultaneous and equitable participation of the team members since they allow only for a single control point. In this paper, a report the work conducted with children playing a user role is presented. A preliminary study to cull ideas, insights, and design considerations for a formal programming course for children aged 8-10 using collaborative learning as a pedagogical approach was conducted. Three setups were provided: 1) lo-fi prototype, 2) PC, 3) a 46' multi-touch single display groupware limited by the application to a single touch entry. Children were interviewed at the end of the sessions in order to know their opinions about teamwork and the different setups defined. Results are mixed regarding the setup, but they agree to like teamwork.

Keywords: children, collaborative programming, visual programming, multi-touch tabletop, lo-fi prototype

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Authors: Dhurgham Al-Karawi, Nisreen Polus, Shakir Al-Zaidi, Sabah Jassim

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The management of COVID-19 patients based on chest imaging is emerging as an essential tool for evaluating the spread of the pandemic which has gripped the global community. It has already been used to monitor the situation of COVID-19 patients who have issues in respiratory status. There has been increase to use chest imaging for medical triage of patients who are showing moderate-severe clinical COVID-19 features, this is due to the fast dispersal of the pandemic to all continents and communities. This article demonstrates the development of machine learning techniques for the test of COVID-19 patients using Chest X-Ray (CXR) images in nearly real-time, to distinguish the COVID-19 infection with a significantly high level of accuracy. The testing performance has covered a combination of different datasets of CXR images of positive COVID-19 patients, patients with viral and bacterial infections, also, people with a clear chest. The proposed AI scheme successfully distinguishes CXR scans of COVID-19 infected patients from CXR scans of viral and bacterial based pneumonia as well as normal cases with an average accuracy of 94.43%, sensitivity 95%, and specificity 93.86%. Predicted decisions would be supported by visual evidence to help clinicians speed up the initial assessment process of new suspected cases, especially in a resource-constrained environment.

Keywords: COVID-19, chest x-ray scan, artificial intelligence, texture analysis, local binary pattern transform, Gabor filter

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Authors: Shao-Tzu Huang, Chen-Chien Hsu, Wei-Yen Wang

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Matching high dimensional features between images is computationally expensive for exhaustive search approaches in computer vision. Although the dimension of the feature can be degraded by simplifying the prior knowledge of homography, matching accuracy may degrade as a tradeoff. In this paper, we present a feature matching method based on k-means algorithm that reduces the matching cost and matches the features between images instead of using a simplified geometric assumption. Experimental results show that the proposed method outperforms the previous linear exhaustive search approaches in terms of the inlier ratio of matched pairs.

Keywords: feature matching, k-means clustering, SIFT, RANSAC

Procedia PDF Downloads 342

Authors: A: Annis Fathima, V. Vaidehi, S. Ajitha

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Face recognition system finds many applications in surveillance and human computer interaction systems. As the applications using face recognition systems are of much importance and demand more accuracy, more robustness in the face recognition system is expected with less computation time. In this paper, a hybrid approach for face recognition combining Gabor Wavelet and Linear Discriminant Analysis (HGWLDA) is proposed. The normalized input grayscale image is approximated and reduced in dimension to lower the processing overhead for Gabor filters. This image is convolved with bank of Gabor filters with varying scales and orientations. LDA, a subspace analysis techniques are used to reduce the intra-class space and maximize the inter-class space. The techniques used are 2-dimensional Linear Discriminant Analysis (2D-LDA), 2-dimensional bidirectional LDA ((2D)2LDA), Weighted 2-dimensional bidirectional Linear Discriminant Analysis (Wt (2D)2 LDA). LDA reduces the feature dimension by extracting the features with greater variance. k-Nearest Neighbour (k-NN) classifier is used to classify and recognize the test image by comparing its feature with each of the training set features. The HGWLDA approach is robust against illumination conditions as the Gabor features are illumination invariant. This approach also aims at a better recognition rate using less number of features for varying expressions. The performance of the proposed HGWLDA approaches is evaluated using AT&T database, MIT-India face database and faces94 database. It is found that the proposed HGWLDA approach provides better results than the existing Gabor approach.

Keywords: face recognition, Gabor wavelet, LDA, k-NN classifier

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Authors: Seyed Nima Tayarani Bathaie

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In this paper, an image-receiving system was designed and implemented through optimization of object detection algorithms using Haar features. This optimized algorithm served as face and eye detection separately. Then, cascading them led to a clear image of the user. Utilization of this feature brought about higher security by preventing fraud. This attribute results from the fact that services will be given to the user on condition that a clear image of his face has already been captured which would exclude the inappropriate person. In order to expedite processing and eliminating unnecessary ones, the input image was compressed, a motion detection function was included in the program, and detection window size was confined.

Keywords: face detection algorithm, Haar features, security of ATM

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Authors: Bjorn-Ole Meyer, Dominik Marti, Peter E. Andersen

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A multimodal imaging system, combining spectrally resolved multiphoton microscopy (MPM) and optical coherence microscopy (OCM) is demonstrated. MPM and OCM are commonly integrated into multimodal imaging platforms to combine functional and morphological information. The MPM signals, such as two-photon fluorescence emission (TPFE) and signals created by second harmonic generation (SHG) are biomarkers which exhibit information on functional biological features such as the ratio of pyridine nucleotide (NAD(P)H) and flavin adenine dinucleotide (FAD) in the classification of cancerous tissue. While the spectrally resolved imaging allows for the study of biomarkers, using a spectrometer as a detector limits the imaging speed of the system significantly. To overcome those limitations, an OCM setup was added to the system, which allows for fast acquisition of structural information. Thus, after rapid imaging of larger specimens, navigation within the sample is possible. Subsequently, distinct features can be selected for further investigation using MPM. Additionally, by probing a different contrast, complementary information is obtained, and different biomarkers can be investigated. OCM images of tissue and cell samples are obtained, and distinctive features are evaluated using MPM to illustrate the benefits of the system.

Keywords: optical coherence microscopy, multiphoton microscopy, multimodal imaging, two-photon fluorescence emission

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Authors: Sharifa Alshahrani

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Comics is a multimodal text wherein meaning is created by taking in all modes of expression at once. It uses two different semiotic modes, the verbal and the visual modes, together to make meaning and these different semiotic modes can be socially and culturally shaped to give meaning. Therefore, comics translation cannot treat comics as a monomodal text by translating only the verbal mode inside or outside the speech balloons as the cultural differences are encoded in the visual mode as well. Due to the development of the internet and editing software, comics translation is not anymore confined to the publishing houses and official translation as scanlation, or the fan translation took the initiative in translating comics for being emotionally attracted to the culture and genre. Scanlation is carried out by volunteering fans who translate out of passion. However, quality is one of the debatable issues relating to scanlation and fan translation. This study will investigate how the dynamic multimodal relationship in comics is exploited and interpreted in the translation by exploring the translation strategies and procedures adopted by the publishing houses and scanlation in interpreting comics into Arabic using three analytical frameworks; cultural references model, multimodal relation model and translation strategies and procedures models.

Keywords: comics, multimodality, translation, scanlation

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Authors: Maryam Heidari, James H. Jones Jr.

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Millions of online posts about different topics and products are shared on popular social media platforms. One use of this content is to provide crowd-sourced information about a specific topic, event or product. However, this use raises an important question: what percentage of information available through these services is trustworthy? In particular, might some of this information be generated by a machine, i.e., a bot, instead of a human? Bots can be, and often are, purposely designed to generate enough volume to skew an apparent trend or position on a topic, yet the consumer of such content cannot easily distinguish a bot post from a human post. In this paper, we introduce a model for social media bot detection which uses Bidirectional Encoder Representations from Transformers (Google Bert) for sentiment classification of tweets to identify topic-independent features. Our use of a Natural Language Processing approach to derive topic-independent features for our new bot detection model distinguishes this work from previous bot detection models. We achieve 94\% accuracy classifying the contents of data as generated by a bot or a human, where the most accurate prior work achieved accuracy of 92\%.

Keywords: bot detection, natural language processing, neural network, social media

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Authors: Wei-Jong Yang, Yu-Siang Su, Pau-Choo Chung, Jar-Ferr Yang

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Moving object detection (MOD) is an important issue in advanced driver assistance systems (ADAS). There are two important moving objects, pedestrians and scooters in ADAS. In real-world systems, there exist two important challenges for MOD, including the computational complexity and the detection accuracy. The histogram of oriented gradient (HOG) features can easily detect the edge of object without invariance to changes in illumination and shadowing. However, to reduce the execution time for real-time systems, the image size should be down sampled which would lead the outlier influence to increase. For this reason, we propose the histogram of uniformly-oriented gradient (HUG) features to get better accurate description of the contour of human body. In the testing phase, the support vector machine (SVM) with linear kernel function is involved. Experimental results show the correctness and effectiveness of the proposed method. With SVM classifiers, the real testing results show the proposed HUG features achieve better than classification performance than the HOG ones.

Keywords: moving object detection, histogram of oriented gradient, histogram of uniformly-oriented gradient, linear support vector machine

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Authors: Faris Tarlochan, Siva Mahesh Tangutooru

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Lateral Geniculate Nucleus (LGN) is the relay center in the visual pathway as it receives most of the input information from retinal ganglion cells (RGC) and sends to visual cortex. Low threshold calcium currents (IT) at the membrane are the unique indicator to characterize this firing functionality of the LGN neurons gained by the RGC input. According to the LGN functional requirements such as functional mapping of RGC to LGN, the morphologies of the LGN neurons were developed. During the neurological disorders like glaucoma, the mapping between RGC and LGN is disconnected and hence stimulating LGN electrically using deep brain electrodes can restore the functionalities of LGN. A computational model was developed for simulating the LGN neurons with three predominant morphologies, each representing different functional mapping of RGC to LGN. The firings of action potentials at LGN neuron due to IT were characterized by varying the stimulation parameters, morphological parameters and orientation. A wide range of stimulation parameters (stimulus amplitude, duration and frequency) represents the various strengths of the electrical stimulation with different morphological parameters (soma size, dendrites size and structure). The orientation (0-1800) of LGN neuron with respect to the stimulating electrode represents the angle at which the extracellular deep brain stimulation towards LGN neuron is performed. A reduced dendrite structure was used in the model using Bush–Sejnowski algorithm to decrease the computational time while conserving its input resistance and total surface area. The major finding is that an input potential of 0.4 V is required to produce the action potential in the LGN neuron which is placed at 100 µm distance from the electrode. From this study, it can be concluded that the neuroprostheses under design would need to consider the capability of inducing at least 0.4V to produce action potentials in LGN.

Keywords: Lateral Geniculate Nucleus, visual cortex, finite element, glaucoma, neuroprostheses

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Authors: M. Alsharqawi, T. Zayed, S. Abu Dabous

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To ensure safety and serviceability of bridge infrastructure, accurate condition assessment and rating methods are needed to provide basis for bridge Maintenance, Repair and Replacement (MRR) decisions. In North America, the common practices to assess condition of bridges are through visual inspection. These practices are limited to detect surface defects and external flaws. Further, the thresholds that define the severity of bridge deterioration are selected arbitrarily. The current research discusses the main deteriorations and defects identified during visual inspection and Non-Destructive Evaluation (NDE). NDE techniques are becoming popular in augmenting the visual examination during inspection to detect subsurface defects. Quality inspection data and accurate condition assessment and rating are the basis for determining appropriate MRR decisions. Thus, in this paper, a novel method for bridge condition assessment using the Quality Function Deployment (QFD) theory is utilized. The QFD model is designed to provide an integrated condition by evaluating both the surface and subsurface defects for concrete bridges. Moreover, an integrated condition rating index with four thresholds is developed based on the QFD condition assessment model and using K-means clustering technique. Twenty case studies are analyzed by applying the QFD model and implementing the developed rating index. The results from the analyzed case studies show that the proposed threshold model produces robust MRR recommendations consistent with decisions and recommendations made by bridge managers on these projects. The proposed method is expected to advance the state of the art of bridges condition assessment and rating.

Keywords: concrete bridge decks, condition assessment and rating, quality function deployment, k-means clustering technique

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Authors: Alan S. Hoback

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Most people see human faces in car front and back ends because of the process of pareidolia. 96 people were surveyed to see how many of them saw a face in the vehicle styling. Participants were aged 18 to 72 years. 94% of the participants saw faces in the front-end design of production models. All participants that recognized faces indicated that most styles showed some degree of an angry expression. It was found that women were more likely to see faces in inanimate objects. However, with respect to whether women were more likely to perceive anger in the vehicle design, the results need further clarification. Survey responses were correlated to the design features of vehicles to determine what cues the respondents were likely looking at when responding. Whether the features looked anthropomorphic was key to anger perception. Features such as the headlights which could represent eyes and the air intake that could represent a mouth had high correlations to trends in scores. Results are compared among models, makers, by groupings of body styles classifications for the top 12 brands sold in the US, and by year for the top 20 models sold in the US in 2016. All of the top models sold increased in perception of an angry expression over the last 20 years or since the model was introduced, but the relative change varied by body style grouping.

Keywords: aggressive driving, face recognition, road rage, vehicle styling

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Authors: Ammar Khader Almasri

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The software processes play a vital role for delivering a high quality software system that meets the user’s needs. There are many software development models which are used by most system developers, which can be categorized into two categories (traditional and new methodologies). Mobile applications like other desktop applications need appropriate and well-working software development process. Nevertheless, mobile applications have different features which limit their performance and efficiency like application size, mobile hardware features. Moreover, this research aims to help developers in using a standardized model for developing mobile applications.

Keywords: software development process, agile methods , moblile application development, traditional methods

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Authors: Chapman Eze Nnadozie

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Relational databases constitute a very vital tool for the effective management and administration of both personal and organizational data. Data access ranges from a single user database management software to a more complex distributed server system. This paper intends to appraise the use a programming language extension like structured query language (SQL) to establish links to a relational database (Microsoft Access 2013) using Visual C++ 9 programming language environment. The methodology used involves the creation of tables to form a database using Microsoft Access 2013, which is Object Linking and Embedding (OLE) database compliant. The SQL command is used to query the tables in the database for easy extraction of expected records inside the visual C++ environment. The findings of this paper reveal that records can easily be accessed and manipulated to filter exactly what the user wants, such as retrieval of records with specified criteria, updating of records, and deletion of part or the whole records in a table.

Keywords: data access, database, database management system, OLE, programming language, records, relational database, software, SQL, table

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Authors: Shai Gabay

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The tunnel effect describes the phenomenon where a moving object seems to persist even when temporarily hidden from view. Numerous studies indicate that humans, infants, and nonhuman primates possess object persistence, relying on spatiotemporal cues to track objects that are dynamically occluded. While this ability is associated with neural activity in the cerebral neocortex of humans and mammals, the role of subcortical mechanisms remains ambiguous. In our current investigation, we explore the functional contribution of monocular aspects of the visual system, predominantly subcortical, to the representation of occluded objects. This is achieved by manipulating whether the reappearance of an object occurs in the same or different eye from its disappearance. Additionally, we employ Archerfish, renowned for their precision in dislodging insect prey with water jets, as a phylogenetic model to probe the evolutionary origins of the tunnel effect. Our findings reveal the active involvement of subcortical structures in the mental representation of occluded objects, a process evident even in species that do not possess cortical tissue.

Keywords: archerfish, tunnel effect, mental representations, monocular channels, subcortical structures

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Authors: Jinseon Song, Yongwan Park

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In this paper, propose method that can user’s position that based on database is built from single camera. Previous positioning calculate distance by arrival-time of signal like GPS (Global Positioning System), RF(Radio Frequency). However, these previous method have weakness because these have large error range according to signal interference. Method for solution estimate position by camera sensor. But, signal camera is difficult to obtain relative position data and stereo camera is difficult to provide real-time position data because of a lot of image data, too. First of all, in this research we build image database at space that able to provide positioning service with single camera. Next, we judge similarity through image matching of database image and transmission image from user. Finally, we decide position of user through position of most similar database image. For verification of propose method, we experiment at real-environment like indoor and outdoor. Propose method is wide positioning range and this method can verify not only position of user but also direction.

Keywords: positioning, distance, camera, features, SURF(Speed-Up Robust Features), database, estimation

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Authors: Rebecca Angeles

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This case study features the Kuehne + Nagel PharmaChain solution for ‘cold chain’ pharmaceutical and biologic product shipments with IOT-enabled features for shipment temperature and location tracking. Using the case study method and content analysis, this research project investigates the application of the structurational model of technology theory introduced by Orlikowski in order to interpret the firm’s entry and participation in the IOT-impelled marketplace.

Keywords: Internet of Things (IOT), radio frequency identification (RFID), structurational model of technology (Orlikowski), supply chain management

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Authors: Abiodun Afolabi, Rufus Adesoji Adedoyin

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This study investigated and compared the effects of gym-based exercise programme (GEBP) and audio-visual guided home-based exercise programme (AVGHBEP) on selected Anthropometric variables (Weight (W), Body Mass Index (BMI), Waist Circumference (WC), Hip Circumference (HC), Thigh Circumference (TC), Waist-Hip-Ratio (WHR), Waist-Height-Ratio (WHtR), Waist-Thigh-Ratio (WTR), Biceps Skinfold Thickness (BSFT), Triceps Skinfold Thickness (TSFT), Suprailliac Skinfold Thickness (SISFT), Subscapular Skinfold Thickness (SSSFT) and Percent Body Fat (PBF)); and Cardiovasular variables (Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP) and Heart Rate (HR)) of overweight and obese students of Federal College of Education (Special), Oyo, Oyo State, Nigeria, with a view to providing information and evidence for GBEP and AVGHBEP in reducing overweight and obesity for promoting cardiovascular fitness. Eighty overweight and obese students (BMI ≥ 25 Kg/m²) were involved in this pretest-posttest quasi experimental study. Participants were randomly assigned into GBEP (n = 40) and AVGBBEP (n = 40) groups. Anthropometric and cardiovascular variables were measured using a weighing scale, height meter, tape measure, skinfold caliper and electronic sphygmomanometer following standard protocols. GBEP and AVGHBEP were implemented following a circuit training (aerobic and resistance training) pattern with a duration of 40-60 minutes, thrice weekly for twelve weeks. GBEP consisted of gymnasium supervised exercise programme while AVGHBEP is a Visual Display guided exercise programme conducted at the home setting. Data were analyzed by Descriptive and Inferential Statistics. The mean ages of the participants were 22.55 ± 2.55 and 23.65 ± 2.89 years for the GBEP group and AVGHBEP group, respectively. Findings showed that in the GBEP group, there were significant reductions in anthropometric variables and adiposity measures of Weight, BMI, BSFT, TSFT, SISFT, SSSFT, WC, HC, TC, WHtR, and PBF at week 12 of the study. Similarly, in the AVGHBEP group, there were significant reductions in Weight, BMI, BSFT, TSFT, SISFT, SSSFT, WC, HC, TC, WHtR and PBF at the 12th week of intervention. Comparison of the effects of GEBP and AVGHBEP on anthropometric variables and measures of adiposity showed that there was no significant difference between the two groups in weight, BMI, BSFT, TSFT, SISFT, SSSFT, WC, HC, TC, WHR, WHtR, WTR and PBF between the two groups at week 12 of the study. Furthermore, findings on the effects of exercise on programmes on cardiovascular variables revealed that significant reductions occurred in SBP in GBEP group and AVGHBEP group respectively. Comparison of the effects of GBEP and AVGHBEP on cardiovascular variables showed that there was no significant difference in SBP, DBP and HR between the two groups at week 12 of the study. It was concluded that the Audio-Visual Guided Home-based Exercise Programme was as effective as the Gym-Based Exercise Programme in causing a significant reduction in anthropometric variables and body fat among college students who are overweight and obese over a period of twelve weeks. Both Gymnasium-Based Exercise Programme and Audio-Visual Guided Home-Based Exercise Programme led to significant reduction in Systolic Blood Pressure over a period of weeks. Audio-Visual Guided Home-Based Exercise Programme can, therefore, be used as an alternative therapy in the non-pharmacological management of people who are overweight and obese.

Keywords: gym-based exercises, audio-visual guided home-based exercises, anthropometric parameters, cardiovascular parameters, overweight students, obese students

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Authors: Muyatdinova Aigul, Aitkaliyeva Madina

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The article deals with the evaluation of the quality of medical services on the basis of quality indicators. For this purpose allocated initially the features of the medical services market. The Features of the market directly affect on the evaluation process that takes a multi-level and multi-stakeholder nature. Unlike ordinary goods market assessment of medical services does not only market. Such an assessment is complemented by continuous internal and external evaluation, including experts and accrediting bodies. In the article highlighted the composition of indicators for a comprehensive evaluation

Keywords: health care market, quality of health services, indicators of care quality

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Authors: Sheetal R. Jadhwani, Daisy Sang, Chang-Shyh Peng

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Web applications are an integral part of modem life. They are mostly based upon the HyperText Markup Language (HTML). While HTML meets the basic needs, there are some shortcomings. For example, applications can cease to work once user goes offline, real-time updates may be lagging, and user interface can freeze on computationally intensive tasks. The latest language specification HTML5 attempts to rectify the situation with new tools and protocols. This paper studies the new Web Storage, Geolocation, Web Worker, Canvas, and Web Socket APIs, and presents applications to test their features and efficiencies.

Keywords: HTML5, web worker, canvas, web socket

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Authors: Xinyi Le

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In this paper, 3D printing orientations were determined through our perceptual model. Some FDM (Fused Deposition Modeling) 3D printers, which are widely used in universities and industries, often require support structures during the additive manufacturing. After removing the residual material, some surface artifacts remain at the contact points. These artifacts will damage the function and visual effect of the model. To prevent the impact of these artifacts, we present a fuzzy extreme learning machine approach to find printing directions that avoid placing supports in perceptually significant regions. The proposed approach is able to solve the evaluation problem by combing both the subjective knowledge and objective information. Our method combines the advantages of fuzzy theory, auto-encoders, and extreme learning machine. Fuzzy set theory is applied for dealing with subjective preference information, and auto-encoder step is used to extract good features without supervised labels before extreme learning machine. An extreme learning machine method is then developed successfully for training and learning perceptual models. The performance of this perceptual model will be demonstrated on both natural and man-made objects. It is a good human-computer interaction practice which draws from supporting knowledge on both the machine side and the human side.

Keywords: 3d printing, perceptual model, fuzzy evaluation, data-driven approach

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Authors: Peter M. Maurer Maurer

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DGL is a context free grammar-based tool for generating random data. Many types of simulator input data require some computation to be placed in the proper format. For example, it might be necessary to generate ordered triples in which the third element is the sum of the first two elements, or it might be necessary to generate random numbers in some sorted order. Although DGL is universal in computational power, generating these types of data is extremely difficult. To overcome this problem, we have enhanced DGL to include features that permit direct computation within the structure of a context free grammar. The features have been implemented as special types of productions, preserving the context free flavor of DGL specifications.

Keywords: DGL, Enhanced Context Free Grammars, Programming Constructs, Random Data Generation

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Authors: Meysam Jamali, Ebrahim Moghimi, Zean Alabden Jafarpour

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Karst term is the determiner of a variety of areas or landforms and unique perspectives that have been formed in result of the ingredients dissolution of rocks constituter by natural waters. Shiraz area with an area of 5322km2 is located in the simple folded belt in the southern part of Zagros Mountain of Fars, and is surrounded with Limestone Mountains (Asmari formation). Shiraz area is located in Calcareous areas. The Infrastructure of this city is lime and absorbing wells that the city has, can influence on the Limestone dissolution and those accelerate its rate and increases the cavitation below the surface. Dasht-e Arjan is a graben, which has been created as the result of activity of two normal faults in its east and west sides. It is a complete sample of Karst plains (Polje) which has been created with the help of tectonic forces (fault) and dissolution process of water in Asmari limestone formation. It is located 60km. off south west of Shiraz (on Kazeroon-Shiraz road). In 1971, UNESCO has recognized this plain as a reserve of biosphere. It is considered as one of the world’s most beautiful geological phenomena, so that most of the world’s geologists are interested in visiting this place. The purpose of this paper is to identify and introduce landscapes of Karst features shiraz city and Dasht-e Arjan including Karst dissolution features (Lapiez, Karst springs, dolines, caves, underground caves, ponors, and Karst valleys), anticlines and synclines, and Arjan Lake, which are studied in this paper.

Keywords: Dasht-eArjan, fault, Karst features, polje, Shiraz city, Zagros

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Authors: Bo Liu, Chi-Man Pun

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A novel technique for digital forgery detection by signal noise inconsistency is proposed in this paper. The forged area spliced from the other picture contains some features which may be inconsistent with the rest part of the image. Noise pattern and the level is a possible factor to reveal such inconsistency. To detect such noise discrepancies, the test picture is initially segmented into small pieces. The noise pattern and level of each segment are then estimated by using various filters. The noise features constructed in this step are utilized in energy-based graph cut to expose forged area in the final step. Experimental results show that our method provides a good illustration of regions with noise inconsistency in various scenarios.

Keywords: forgery detection, splicing forgery, noise estimation, noise

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Authors: Yuntao Liu, Lei Wang, Haoran Xia

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Machine learning has shown extensive applications in the development of classification models for autism spectrum disorder (ASD) using neural image data. This paper proposes a fusion multi-modal classification network based on a graph neural network. First, the brain is segmented into 116 regions of interest using a medical segmentation template (AAL, Anatomical Automatic Labeling). The image features of sMRI and the signal features of fMRI are extracted, which build the node and edge embedding representations of the brain map. Then, we construct a dynamically updated brain map neural network and propose a method based on a dynamic brain map adjacency matrix update mechanism and learnable graph to further improve the accuracy of autism diagnosis and recognition results. Based on the Autism Brain Imaging Data Exchange I dataset(ABIDE I), we reached a prediction accuracy of 74% between ASD and TD subjects. Besides, to study the biomarkers that can help doctors analyze diseases and interpretability, we used the features by extracting the top five maximum and minimum ROI weights. This work provides a meaningful way for brain disorder identification.

Keywords: autism spectrum disorder, brain map, supervised machine learning, graph network, multimodal data, model interpretability

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Authors: Slava Kalyuga, Sujanya Sombatteera

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In multimedia learning, written text is often transformed into spoken (narrated) text. This transient information may overwhelm limited processing capacity of working memory and inhibit learning instead of improving it. The paper reviews recent empirical studies in modality and verbal redundancy effects within a cognitive load framework and outlines conditions under which negative effects of transiency may occur. According to the modality effect, textual information accompanying pictures should be presented in an auditory rather than visual form in order to engage two available channels of working memory – auditory and visual - instead of only one of them. However, some studies failed to replicate the modality effect and found differences opposite to those expected. Also, according to the multimedia redundancy effect, the same information should not be presented simultaneously in different modalities to avoid unnecessary cognitive load imposed by the integration of redundant sources of information. However, a few studies failed to replicate the multimedia redundancy effect too. Transiency of information is used to explain these controversial results.

Keywords: cognitive load, transient information, modality effect, verbal redundancy effect

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Authors: Xiaoling Dai

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Many Chinese artists have used digital photography to create works with features of Chinese landscape paintings since the 20th century. The ‘New Mountains and Water’ works created by digital techniques reflect the fusion of photographic techniques and traditional Chinese aesthetic thoughts. Borrowing from Chinese landscape paintings in the Song Dynasty, the Chinese photographer Yao Lu uses digital photography to reflect contemporary environmental construction in his series New Landscapes. By portraying a variety of natural environments brought by urbanization in the contemporary period, Lu deconstructs traditional Chinese paintings and reconstructs contemporary photographic practices. The primary object of this study is to investigate how Chinese photographer Yao Lu redefines and re-interprets the relationship between tradition and contemporaneity. In this study, Yao Lu’s series work New Landscapes is used for photo elicitation, which seeks to broaden understanding of the development of Chinese landscape photography. Furthermore, discourse analysis will be used to evaluate how Chinese social developments influence the creation of photographic practices. Through visual and discourse analysis, this study aims to excavate the relationship between tradition and contemporaneity in Lu’s works. According to New Landscapes, the study argues that in Lu’s interpretations of landscapes, tradition and contemporaneity are seen to establish a new relationship. Traditional approaches to creation do not become obsolete over time. On the contrary, traditional notions and styles of creation can shed new light on contemporary issues or techniques.

Keywords: Chinese aesthetics, Yao Lu, new landscapes, tradition, contemporaneity

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Authors: Guilherme Oliveira

Abstract:

The assimilation of images and their potential symbolism into lived experiences is inherent. It is through this exercise of recognition via imagistic records that the questioning of the origins of a constant narrative stimulated by the media arises. The construction of the "Man" archetype and the reflections of active masculine imagery in the 21st century, when conveyed through media channels, could potentially have detrimental effects. Addressing this systematic behavioral chronology of virile cisgender, permeated imagistically through these means, involves exploring potential resolutions. Thus, an investigation process is initiated into the potential representation of the 'hero' in this media emulation through idols contextualized in the political sphere, with the purpose of elucidating the processes of simulation and emulation of narratives based on mythical, historical, and sacred accounts. In this process of sharing, the narratives contained in the imagistic structuring offered by information dissemination channels seek validation through a process of public acceptance. To achieve this consensus, a visual set adorned with mythological and sacred symbolisms adapted to the intended environment is promoted, thus utilizing sociocultural characteristics in favor of political marketing. Visual recognition, therefore, becomes a direct reflection of a cultural heritage acquired through lived human experience, stimulated by continuous representations throughout history. Echoes of imagery and narratives undergo a constant process of resignification of their concepts, sharpened by their premises, and adapted to the environment in which they seek to establish themselves. Political figures analyzed in this article employ the practice of taking possession of symbolisms, mythological stories, and heroisms and adapt their visual construction through a continuous praxis of emulation. Thus, they utilize iconic mythological narratives to gain credibility through belief. Utilizing iconic mythological narratives for credibility through belief, the idol becomes the very act of release of trauma, offering believers liberation from preconceived concepts and allowing for the attribution of new meanings. To dissolve this issue and highlight the subjectivities within the intention of the image, a linguistic, semiotic, and anthropological methodology is created. Linguistics uses expressions like 'Blaming the Image' to create a mechanism of expressive action in questioning why to blame a construction or visual composition and thus seek answers in the first act. Semiotics and anthropology develop an imagistic atlas of graphic analysis, seeking to make connections, comparisons, and relations between modern and sacred/mystical narratives, emphasizing the different subjective layers of embedded symbolism. Thus, it constitutes a performative act of disarming the image. It creates a disenchantment of the superficial gaze under the constant reproduction of visual content stimulated by virtual networks, enabling a discussion about the acceptance of caricatures characterized by past fables.

Keywords: image, heroic narrative, media heroism, virile politics, political, myth, sacred performance, visual mythmaking, characterization dynamics

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Authors: Aisyiyah Fauziah Rahmah

Abstract:

Generally, an urban city has a rapid growth, it has frequent a variety of problems, especially of convenience in public space usage. The density of population in urban areas and the high activity is also indicated as a cause of urban resident lifestyle for the worse in social relationships and allow for the stress. Streets and green space (parks) are the only public space in a residential area which is used as a place to build social activity, to meet and interact with the other housing dweller. The high level of activity and social interaction that occurs will affect the spatial arrangement. It can be effected the space structures in housing more complex. Ease in access to public space is the reason many dweller prefer doing social activities there. Hillier in Carmona et al (2003) explains that the pattern and intensity of movement of individuals is influenced by the configuration of space, even the space structure can be regarded as the single most influential determinant of movements in the space. Whyte in Zhang and Lawson (2009) also suggest some factors such as seats, trees, water and legibility of space encourage people to stay in public outdoor space. Furthermore this activities can attract more activities. Villa Bukit Tidar is a housing in Lowokwaru District which highest number of people in Malang City, so social activity is also high there. It has natural and recreational concept and provided with view of Malang City from heights. This potential is able to attract the people who live there to stay in public outdoor space and doing activities there. From this study we can find whether the ease of access to public space and visual satisfaction of Villa Bukit Tidar housing affect the usage of public space. This study was carried out by observing the streets pattern and plot pattern to know the configuration space of Villa Bukit Tidar housing through values of connectivity and integrity by resulting from space sintax analysis. Distributing questionnaires also carried out to determine the level of satisfaction and importance perception of visual condition in the public space in Villa Bukit Tidar housing through Important Performance Analysis (IPA). Results of this research indicated that the public spaces in Villa Bukit Tidar housing who has high connectivity and integrity is considered to be visually satisfied and it has a higher public space usage than has low connectivity and integrity are considered to be visually dissatisfied.

Keywords: configuration space, visual perception, social activities, public space usage

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