Search results for: star image

Authors: Rodrigo C. Belleza, Jr., Roselyn A. Maaño, Karl Patrick E. Camota, Darwin Kim Q. Bulawan

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Eyes are an essential and conspicuous organ of the human body. Human eyes are outward and inward portals of the body that allows to see the outside world and provides glimpses into ones inner thoughts and feelings. Inevitable blindness and visual impairments may result from eye-related disease, trauma, or congenital or degenerative conditions that cannot be corrected by conventional means. The study emphasizes innovative tools that will serve as an aid to the blind and visually impaired (VI) individuals. The researchers fabricated a prototype that utilizes the Microsoft Kinect for Windows and Arduino microcontroller board. The prototype facilitates advanced gesture recognition, voice recognition, obstacle detection and indoor environment navigation. Open Computer Vision (OpenCV) performs image analysis, and gesture tracking to transform Kinect data to the desired output. A computer vision technology device provides greater accessibility for those with vision impairments.

Keywords: algorithms, blind, computer vision, embedded systems, image analysis

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Authors: Mohammed M. Ibrahim, A. A. Yusuf, Manuel Du, Fiona Mumoki

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The traditional honey bee species of Sudan is Apis mellifera, but in 1985, the dwarf bee Apis florea was introduced to the country, so now there are two species present. However, there are conflicting assessments regarding the subspecies of Apis mellifera colonies in Sudan. Likewise, it is unclear if, in the 40 years since its introduction, Apis florea has already developed regional differences or ecotypes. To shed light on these questions, we performed a morphology study on Sudanese honeybees. Samples of 10 to 20 honeybee workers per colony of the two species were collected from 16 locations, spanning different climatic zones in Sudan during 2021. Measurements were taken from 16 morphometric characteristics using a stereo-microscope equipped with an Image Analysis System (Moticam Image Plus 5.0 Digital Microscope Camera) to study their variability. The results indicate that in both species, the general means of various characters showed significant differences (p < 0.05) within a species between different locations, indicating that there might indeed be regional differences. However, more taxonomic investigation and, ideally also, molecular studies are needed in order to confirm the proper identification of subspecies and their ecotypes.

Keywords: Apis, subspecies, morphology, Sudan

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Authors: Xiang Shijie, Zhou Dong, Tian Dan

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This paper focuses on the application of real-time semantic segmentation technology in complex road condition recognition, aiming to address the critical issue of how to improve segmentation accuracy while ensuring real-time performance. Semantic segmentation technology has broad application prospects in fields such as autonomous vehicle navigation and remote sensing image recognition. However, current real-time semantic segmentation networks face significant technical challenges and optimization gaps in balancing speed and accuracy. To tackle this problem, this paper conducts an in-depth study and proposes an innovative Guided Image Reconstruction Module. By resampling high-resolution images into a set of low-resolution images, this module effectively reduces computational complexity, allowing the network to more efficiently extract features within limited resources, thereby improving the performance of real-time segmentation tasks. In addition, a dual-branch network structure is designed in this paper to fully leverage the advantages of different feature layers. A novel Hybrid Attention Mechanism is also introduced, which can dynamically capture multi-scale contextual information and effectively enhance the focus on important features, thus improving the segmentation accuracy of the network in complex road condition. Compared with traditional methods, the proposed model achieves a better balance between accuracy and real-time performance and demonstrates competitive results in road condition segmentation tasks, showcasing its superiority. Experimental results show that this method not only significantly improves segmentation accuracy while maintaining real-time performance, but also remains stable across diverse and complex road conditions, making it highly applicable in practical scenarios. By incorporating the Guided Image Reconstruction Module, dual-branch structure, and Hybrid Attention Mechanism, this paper presents a novel approach to real-time semantic segmentation tasks, which is expected to further advance the development of this field.

Keywords: hybrid attention mechanism, image reconstruction, real-time, road status recognition

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Authors: H. Alheeh, M. Alameri, A. Al Tarabsheh

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There has been a growing interest in CMOS-based sensors technology in cameras as they afford low-power, small-size, and cost-effective imaging systems. This article describes the CMOS image sensor pixel categories and presents the design and the simulation of the 3-Transistor (3T) Active Pixel Sensor (APS) in MATLAB/Simulink tool. The analysis investigates the conversion of the light into an electrical signal for a single pixel sensing circuit, which consists of a photodiode and three NMOS transistors. The paper also proposes three modes for the pixel operation; reset, integration, and readout modes. The simulations of the electrical signals for each of the studied modes of operation show how the output electrical signals are correlated to the input light intensities. The charging/discharging speed for the photodiodes is also investigated. The output voltage for different light intensities, including in dark case, is calculated and showed its inverse proportionality with the light intensity.

Keywords: APS, CMOS image sensor, light intensities photodiode, simulation

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Authors: Mai Anh Pham Ho

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Ao Dai is the traditional dress of Vietnamese women that consists of a long tunic with slits on either side and wide trousers. This is the Vietnamese national costume which most common worn by women in daily life. The Vietnamese men may wear Ao Dai on special occasions like New Year Eve or Wedding Ceremony. Ao Dai is one of the few Vietnamese words that appear in English language dictionaries. Nowadays, there are variations in modern Ao Dai that consist of a short tunic on knee and slim trousers with the other materials like kaki or jeans. This paper aims to apply Pop art pattern on modern Ao Dai through the image of Vietnamese women by modifying the creation process of fashion design. It reflects on how modern culture is involved in Ao Dai and how it affects on fashion design. The research method of this paper is done through surveying the various examples of technological applications to fashion design, then the pop art pattern with the image of Vietnamese women is applied on modern Ao Dai. The results of this paper have shown through the collection of modern Ao Dai with three artworks applied the pop art pattern. In conclusion, the role of fashion technology supports and evolves the traditional value in order to establish the Vietnamese national personality as well as distinguish to other cultural values in the world.

Keywords: pop art pattern, Vietnamese national costume, modern ao dai, fashion design

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Authors: Tanish Mittal, Preyansh Agrawal, Esha Pahwa, Aarya Makwana

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Multi-Scale and U-shaped Networks are widely used in various image restoration problems, including deblurring. Keeping in mind the wide range of applications, we present a comparison of these architectures and their effects on image deblurring. We also introduce a new block called as NFResblock. It consists of a Fast Fourier Transformation layer and a series of modified Non-Linear Activation Free Blocks. Based on these architectures and additions, we introduce NFResnet and NFResnet+, which are modified multi-scale and U-Net architectures, respectively. We also use three differ-ent loss functions to train these architectures: Charbonnier Loss, Edge Loss, and Frequency Reconstruction Loss. Extensive experiments on the Deep Video Deblurring dataset, along with ablation studies for each component, have been presented in this paper. The proposed architectures achieve a considerable increase in Peak Signal to Noise (PSNR) ratio and Structural Similarity Index (SSIM) value.

Keywords: multi-scale, Unet, deblurring, FFT, resblock, NAF-block, nfresnet, charbonnier, edge, frequency reconstruction

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Authors: Patricia P. M. C. Lourenco, Javier Bringué Sala, Anaisa D. A. de Sena

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Almost everyone in Dramaland knows the names of big Korean stars that grace their computer screens on a roll through social media and video streaming platforms that enable awareness of Korean dramas and lifestyle at a click. A surface culture instilled with notions of belonging has redefined the meaning of friendship and challenged deep inner values. Not everyone, however, knows Chinese Dramas or their stars, which is a consequence of Dramaland's focus on Korean dramas and promoting the Korean experience. Despite a parity in terms of production quality, star power, scripts and compelling visual settings, Chinese Dramas have been playing catch up to their famous counterparts. While they might have a strong competitive soft power for international drama fans, the soft power of Korean dramas is imbued with substantial societal values that they want to share with others. Those values are portrayed in an artistic way that connects with audiences who experience loneliness in the non-virtual world contrary to the way Chinese Dramas are perceived.

Keywords: Chinese dramas, fandom, Korean dramas, participatory culture, value perception, soft power, surface culture

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Authors: Claudio Burguez, María Castelló, Mikaela Pisani, Marcos Umpiérrez

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BIOFEEDBACK exhibition offers a unique experience for each visitor, combining art, neuroscience, and technology in an interactive way. Using a headband that captures the bioelectric activity of the brain, the visitors are able to generate sound and images in a sequence loop, making them an integral part of the artwork. Through this interactive exhibit, visitors gain a deeper appreciation of the beauty and complexity of the brain. As a special takeaway, visitors will receive an NFT as a present, allowing them to continue their engagement with the exhibition beyond the physical space. We used the EEG Biofeedback technique following a closed-loop neuroscience approach, transforming EEG data captured by a Muse S headband in real-time into audiovisual stimulation. PureData is used for sound generation and Generative Adversarial Networks (GANs) for image generation. Thirty participants have experienced the exhibition. For some individuals, it was easier to focus than others. Participants who said they could focus during the exhibit stated that at one point, they felt that they could control the sound, while images were more abstract, and they did not feel that they were able to control them.

Keywords: art, audiovisual, biofeedback, EEG, NFT, neuroscience, technology

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Authors: Sotiris Papantonopoulos, Marianna Bortziou

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This study aimed at developing a new package of saffron using emotional design and specifically the Kansei Engineering method. Kansei Engineering is a proactive product development methodology, which aims to improve the product development process and to translate consumers' feelings and image of a product into design elements. A survey was conducted with two major purposes: (1) to determine the target group of saffron use and to collect information about the adequacy of the product’s promotion and the importance of its packaging, (2) to collect the most important properties of a package according to consumers and to evaluate the existing saffron packages according to these properties (benchmarking). The interaction with the general public conducted by the distribution of online questionnaires and personal interviews as well as the statistical analysis of the results were performed using the SPSS software. The results of the survey were used in all stages of Kansei Engineering. Based on the results, a new saffron package was designed by using various designing and image processing software. This improved package is expected to achieve a better promotion and increased sales of the product.

Keywords: design, emotional design, Kansei Engineering, packaging, saffron

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Authors: R. Periyasamy, Deepak Joshi, Sneh Anand

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Foot posture assessment is important to evaluate foot type, causing gait and postural defects in all age groups. Although different methods are used for classification of foot arch type in clinical/research examination, there is no clear approach for selecting the most appropriate measurement system. Therefore, the aim of this study was to develop a system for evaluation of foot type as clinical decision-making aids for diagnosis of flat and normal arch based on the Arch Index (AI) and foot pressure distribution parameter - Power Ratio (PR) data. The accuracy of the system was evaluated for 27 subjects with age ranging from 24 to 65 years. Foot area measurements (hind foot, mid foot, and forefoot) were acquired simultaneously from foot pressure intensity image using portable PedoPowerGraph system and analysis of the image in frequency domain to obtain foot pressure distribution parameter - PR data. From our results, we obtain 100% classification accuracy of normal and flat foot by using the linear discriminant analysis method. We observe there is no misclassification of foot types because of incorporating foot pressure distribution data instead of only arch index (AI). We found that the mid-foot pressure distribution ratio data and arch index (AI) value are well correlated to foot arch type based on visual analysis. Therefore, this paper suggests that the proposed system is accurate and easy to determine foot arch type from arch index (AI), as well as incorporating mid-foot pressure distribution ratio data instead of physical area of contact. Hence, such computational tool based system can help the clinicians for assessment of foot structure and cross-check their diagnosis of flat foot from mid-foot pressure distribution.

Keywords: arch index, computational tool, static foot pressure intensity image, foot pressure distribution, linear discriminant analysis

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Authors: Huilan Yao, Huaixin Zhang

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Simulations of the transition flow of model propellers are important for predicting hydrodynamic performance and studying scale effects. In this paper, the transition flow of a model propeller under different loadings are simulated using a transition model provided by STAR-CCM+, and the influence of turbulence intensity (TI) on the transition, especially friction and pressure components of propeller performance, was studied. Before that, the transition model was applied to simulate the transition flow of a flat plate and an airfoil. Predicted transitions agree well with experimental results. Then, the transition model was applied for propeller simulations in open water, and the influence of TI was studied. Under the heavy and moderate loadings, thrust and torque of the propeller predicted by the transition model (different TI) and two turbulence models are very close and agree well with measurements. However, under the light loading, only the transition model with low TI predicts the most accurate results. Above all, the friction components of propeller performance predicted by the transition model with different TI have obvious difference.

Keywords: transition flow, model propellers, hydrodynamic performance, numerical simulation

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Authors: A. Vani, M. N. Mamatha

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Visual signal processing in human beings occurs in the occipital lobe of the brain. The signals that are generated in the brain are universal for all the human beings and they are called Visual Evoked Potential (VEP). Generally, the visually impaired people lose sight because of severe damage to only the eyes natural photo sensors, but the occipital lobe will still be functioning. In this paper, a technique of artificially generating VEP is proposed to enhance the visual ability of the subject. The system uses the electrical photoreceptors to capture image, process the image, to detect and recognize the subject or object. This voltage is further processed and can transmit wirelessly to a BIOMEMS implanted into occipital lobe of the patient’s brain. The proposed BIOMEMS consists of array of electrodes that generate the neuron potential which is similar to VEP of normal people. Thus, the neurons get the visual data from the BioMEMS which helps in generating partial vision or sight for the visually challenged patient. 

Keywords: BioMEMS, neuro-prosthetic, openvibe, visual evoked potential

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Authors: Su Chul Han, Seungwoo Park

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As the increasing incidence of cancer, the technology and modality of radiotherapy have advanced and the importance of preclinical model is increasing in the cancer research. Furthermore, the small animal dosimetry is an essential part of the evaluation of the relationship between the absorbed dose in preclinical small animal and biological effect in preclinical study. In this study, we carried out realistic modeling of the preclinical small animal phantom possible to verify irradiated dose using commercial software. The small animal phantom was modeling from 4D Digital Mouse whole body phantom. To manipulate Moby phantom in commercial software (Mimics, Materialise, Leuven, Belgium), we converted Moby phantom to DICOM image file of CT by Matlab and two- dimensional of CT images were converted to the three-dimensional image and it is possible to segment and crop CT image in Sagittal, Coronal and axial view). The CT images of small animals were modeling following process. Based on the profile line value, the thresholding was carried out to make a mask that was connection of all the regions of the equal threshold range. Using thresholding method, we segmented into three part (bone, body (tissue). lung), to separate neighboring pixels between lung and body (tissue), we used region growing function of Mimics software. We acquired 3D object by 3D calculation in the segmented images. The generated 3D object was smoothing by remeshing operation and smoothing operation factor was 0.4, iteration value was 5. The edge mode was selected to perform triangle reduction. The parameters were that tolerance (0.1mm), edge angle (15 degrees) and the number of iteration (5). The image processing 3D object file was converted to an STL file to output with 3D printer. We modified 3D small animal file using 3- Matic research (Materialise, Leuven, Belgium) to make space for radiation dosimetry chips. We acquired 3D object of realistic small animal phantom. The width of small animal phantom was 2.631 cm, thickness was 2.361 cm, and length was 10.817. Mimics software supported efficiency about 3D object generation and usability of conversion to STL file for user. The development of small preclinical animal phantom would increase reliability of verification of absorbed dose in small animal for preclinical study.

Keywords: mimics, preclinical small animal, segmentation, 3D printer

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Authors: Andrea Fiorista

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The learning of prepositions is a quite problematic aspect in foreign language instruction, and Italian is certainly not an exception. In their prototypical function, prepositions express schematic relations of two entities in a highly abstract, typically image-schematic way. In other terms, prepositions assume concepts such as directionality, collocation of objects in space and time and, in Cognitive Linguistics’ terms, the position of a trajector with respect to a landmark. Learners of different native languages may conceptualize them differently, implying that they are supposed to operate a recategorization (or create new categories) fitting with the target language. However, most current Italian Foreign/Second Language handbooks and didactic grammars do not facilitate learners in carrying out the task, as they tend to provide partial and idiosyncratic descriptions, with the consequent learner’s effort to memorize them, most of the time without success. In their prototypical meaning, prepositions are used to specify precise topographical positions in the physical environment which become less and less accurate as they radiate out from what might be termed a concrete prototype. According to that, the present study aims to elaborate a cognitive and conceptually well-grounded analysis of some extensive uses of the Italian preposition a, in order to propose effective pedagogical solutions in the Teaching/Learning process. Image schemas, cognitive metaphors and embodiment represent efficient cognitive tools in a task like this. Actually, while learning the merely spatial use of the preposition a (e.g. Sono a Roma = I am in Rome; vado a Roma = I am going to Rome,…) is quite straightforward, it is more complex when a appears in constructions such as verbs of motion +a + infinitive (e.g. Vado a studiare = I am going to study), inchoative periphrasis (e.g. Tra poco mi metto a leggere = In a moment I will read), causative construction (e.g. Lui mi ha mandato a lavorare = He sent me to work). The study reports data from a teaching intervention of Focus on Form, in which a basic cognitive schema is used to facilitate both teachers and students to respectively explain/understand the extensive uses of a. The educational material employed translates Cognitive Linguistics’ theoretical assumptions, such as image schemas and cognitive metaphors, into simple images or proto-scenes easily comprehensible for learners. Illustrative material, indeed, is supposed to make metalinguistic contents more accessible. Moreover, the concept of embodiment is pedagogically applied through activities including motion and learners’ bodily involvement. It is expected that replacing rote learning with a methodology that gives grammatical elements a proper meaning, makes learning process more effective both in the short and long term.

Keywords: cognitive approaches to language teaching, image schemas, embodiment, Italian as FL/SL

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Authors: Anthony D. Rhodes, Manan Goel

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We provide a high fidelity deep learning algorithm (HyperSeg) for interactive video segmentation tasks using a dense convolutional network with context-aware skip connections and compressed, 'hypercolumn' image features combined with a convolutional tessellation procedure. In order to maintain high output fidelity, our model crucially processes and renders all image features in high resolution, without utilizing downsampling or pooling procedures. We maintain this consistent, high grade fidelity efficiently in our model chiefly through two means: (1) we use a statistically-principled, tensor decomposition procedure to modulate the number of hypercolumn features and (2) we render these features in their native resolution using a convolutional tessellation technique. For improved pixel-level segmentation results, we introduce a boundary loss function; for improved temporal coherence in video data, we include temporal image information in our model. Through experiments, we demonstrate the improved accuracy of our model against baseline models for interactive segmentation tasks using high resolution video data. We also introduce a benchmark video segmentation dataset, the VFX Segmentation Dataset, which contains over 27,046 high resolution video frames, including green screen and various composited scenes with corresponding, hand-crafted, pixel-level segmentations. Our work presents a improves state of the art segmentation fidelity with high resolution data and can be used across a broad range of application domains, including VFX pipelines and medical imaging disciplines.

Keywords: computer vision, object segmentation, interactive segmentation, model compression

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Authors: Kavyadevi N., Kaviya G., Gowsalya P., Janani M., Mohanraj S.

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Hevea brasiliensis, also known as the rubber tree, is one of the foremost assets of crops in the world. One of the most significant advantages of the Rubber Plant in terms of air oxygenation is its capacity to reduce the likelihood of an individual developing respiratory allergies like asthma. To construct such a system that can properly identify crop diseases and pests and then create a database of insecticides for each pest and disease, we must first give treatment for the illness that has been detected. We shall primarily examine three major leaf diseases since they are economically deficient in this article, which is Bird's eye spot, algal spot and powdery mildew. And the recommended work focuses on disease identification on rubber tree leaves. It will be accomplished by employing one of the superior algorithms. Input, Preprocessing, Image Segmentation, Extraction Feature, and Classification will be followed by the processing technique. We will use time-consuming procedures that they use to detect the sickness. As a consequence, the main ailments, underlying causes, and signs and symptoms of diseases that harm the rubber tree are covered in this study.

Keywords: image processing, python, convolution neural network (CNN), machine learning

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Authors: Chuanqiao Zheng, Wei Zeng, Haozhen Lin

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As of March 2020, the number of Chinese netizens has reached 904 million. The proportion of Internet users accessing the Internet through mobile phones is as high as 99.3%. Under the background of 'Internet +', tourists have a stronger sense of independence in the choice of tourism destinations and tourism products. Tourists are more inclined to learn about the relevant information on tourism destinations and other tourists' evaluations of tourist products through the Internet. The search engine, as an integrated platform that contains a wealth of information, is highly valuable to the analysis of the characteristics of the Internet attention given to various tourism destinations, through big data mining and analysis. This article uses the Baidu Index as the data source, which is one of the products of Baidu Search. The Baidu Index is based on big data, which collects and shares the search results of a large number of Internet users on the Baidu search engine. The big data used in this article includes search index, demand map, population profile, etc. The main research methods used are: (1) based on the search index, analyzing the Internet attention given to the tourism in five cities in Northeast Sichuan at different times, so as to obtain the overall trend and individual characteristics of tourism development in the region; (2) based on the demand map and the population profile, analyzing the demographic characteristics and market positioning of the tourist groups in these cities to understand the characteristics and needs of the target groups; (3) correlating the Internet attention data with the permanent population of each province in China in the corresponding to construct the Boston matrix of the Internet attention rate of the Northeast Sichuan tourism, obtain the tourism target markets, and then propose development strategies for different markets. The study has found that: a) the Internet attention given to the tourism in the region can be categorized into tourist off-season and peak season; the Internet attention given to tourism in different cities is quite different. b) tourists look for information including tour guide information, ticket information, traffic information, weather information, and information on the competing tourism cities; with regard to the population profile, the main group of potential tourists searching for the keywords of tourism in the five prefecture-level cities in Northeast Sichuan are youth. The male to female ratio is about 6 to 4, with males being predominant. c) through the construction of the Boston matrix, it is concluded that the star market for tourism in the Northeast Sichuan Economic Zone includes Sichuan and Shaanxi; the cash cows market includes Hainan and Ningxia; the question market includes Jiangsu and Shanghai; the dog market includes Hubei and Jiangxi. The study concludes with the following planning strategies and recommendations: i) creating a diversified business format that integrates cultural and tourism; ii) creating a brand image of niche tourism; iii) focusing on the development of tourism products; iv) innovating composite three-dimensional marketing channels.

Keywords: Baidu Index, big data, internet attention, tourism

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Authors: Tomasz Wejrzanowski, Łukasz Kaczmarek, Michał Maksimczuk

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High-resolution X-ray computed microtomography (µCT) is a non-destructive technique commonly used to determine the internal structure of reservoir rock sample. This study concerns µCT analysis of Silurian and Ordovician shales and mudstones from a borehole in the Baltic Basin, north of Poland. The spatial resolution of the µCT images obtained was 27 µm, which enabled the authors to create accurate 3-D visualizations and to calculate the ratio of pores and fractures volume to the total sample volume. A total of 1024 µCT slices were used to create a 3-D volume of sample structure geometry. These µCT slices were processed to obtain a clearly visible image and the volume ratio. A copper X-ray source filter was used to reduce image artifacts. Due to accurate technical settings of µCT it was possible to obtain high-resolution 3-D µCT images of low X-ray transparency samples. The presented results confirm the utility of µCT implementations in geoscience and show that µCT has still promising applications for reservoir exploration and characterization.

Keywords: fractures, material density, pores, structure

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Authors: Masao Nakagawa, Toshiki Hirogaki, Eiichi Aoyama, Mohamed Ali Ben Abbes

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A planetary gear set is widely used in hybrid vehicles as the power distribution system or in electric vehicles as the high reduction system, but due to its complexity with planet gears, its dynamic characteristic is not fully understood. There are many reports on two-axes driving or displacement of the planet gears under these conditions, but only few reports deal with three-axes driving. A three-axes driving condition is tested using three-axes torque measurement and focuses on the dynamic characteristic around the planet gears in this report. From experimental result, it was confirmed that the transition forces around the planet gears were balanced and the torques were also balanced around the instantaneous rotation center. The meshing frequency under these conditions was revealed to be the harmonics of two meshing frequencies; meshing frequency of the ring gear and that of the planet gears. The input power of the ring gear is distributed to the carrier and the sun gear in the dynamic sequential change of three fixed conditions; planet, star and solar modes.

Keywords: dynamic characteristic, gear, planetary gear set, torque measuring

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Authors: Heshalini Rajagopal, Li Sze Chow, Raveendran Paramesran

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Magnetic Resonance Imaging (MRI) is one of the most important medical imaging modality. Subjective assessment of the image quality is regarded as the gold standard to evaluate MR images. In this study, a database of 210 MR images which contains ten reference images and 200 distorted images is presented. The reference images were distorted with four types of distortions: Rician Noise, Gaussian White Noise, Gaussian Blur and DCT compression. The 210 images were assessed by ten subjects. The subjective scores were presented in Difference Mean Opinion Score (DMOS). The DMOS values were compared with four FR-IQA metrics. We have used Pearson Linear Coefficient (PLCC) and Spearman Rank Order Correlation Coefficient (SROCC) to validate the DMOS values. The high correlation values of PLCC and SROCC shows that the DMOS values are close to the objective FR-IQA metrics.

Keywords: medical resonance (MR) images, difference mean opinion score (DMOS), full reference image quality assessment (FR-IQA)

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Authors: Anastasios Zopiatis, Antonis L. Theocharous

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In the midst of a fierce war for talent, the hospitality industry is seeking new and innovative ways to enrich its image as an employer of choice and not a necessity. Historically, the industry’s professions are portrayed as ‘unattractive’ due to their repetitious nature, long and unsocial working schedules, below average remunerations, and the mental and physical demands of the job. Aligning with the industry, hospitality and tourism scholars embarked on a journey to investigate pertinent topics with the aim of enhancing our conceptual understanding of the elements that influence employees at the hospitality world of work. Topics such as job involvement, commitment, job and career satisfaction, and turnover intentions became the focal points in a multitude of relevant empirical and conceptual investigations. Nevertheless, gaps or inconsistencies in existing theories, as a result of both the volatile complexity of the relationships governing human behavior in the hospitality workplace, and the academic community’s unopposed acceptance of theoretical frameworks mainly propounded in the United States and United Kingdom years ago, necessitate our continuous vigilance. Thus, in an effort to enhance and enrich the discourse, we set out to investigate the relationship between intrinsic and extrinsic job satisfaction traits and the individual’s career satisfaction, and subsequent intention to remain in the hospitality industry. Reflecting on existing literature, a quantitative survey was developed and administered, face-to-face, to 650 individuals working as full-time employees in 4- and 5- star hotel establishments in Cyprus, whereas a multivariate statistical analysis method, namely Structural Equation Modeling (SEM), was utilized to determine whether relationships existed between constructs as a means to either accept or reject the hypothesized theory. Findings, of interest to both industry stakeholders and academic scholars, suggest that the individual’s future intention to remain within the industry is primarily associated with extrinsic job traits. Our findings revealed that positive associations exist between extrinsic job traits, and both career satisfaction and future intention. In contrast, when investigating the relationship of intrinsic traits, a positive association was revealed only with career satisfaction. Apparently, the local industry’s environmental factors of seasonality, excessive turnover, overdependence on seasonal, and part-time migrant workers, prohibit industry stakeholders in effectively investing the time and resources in the development and professional growth of their employees. Consequently intrinsic job satisfaction factors such as advancement, growth, and achievement, take backstage to the more materialistic extrinsic factors. Findings from the subsequent mediation analysis support the notion that intrinsic traits can positively influence future intentions indirectly only through career satisfaction, whereas extrinsic traits can positively impact both career satisfaction and future intention both directly and indirectly.

Keywords: career satisfaction, Cyprus, hotel employees, structural equation modeling, SEM

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Authors: Tegan H. Emerson, Colin C. Olson, George Stantchev, Jason A. Edelberg, Michael Wilson

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Detecting small targets at range is difficult because there is not enough spatial information present in an image sub-region containing the target to use correlation-based methods to differentiate it from dynamic confusers present in the scene. Moreover, this lack of spatial information also disqualifies the use of most state-of-the-art deep learning image-based classifiers. Here, we use characteristics of target tracks extracted from video sequences as data from which to derive distinguishing topological features that help robustly differentiate targets of interest from confusers. In particular, we calculate persistent homology from time-delayed embeddings of dynamic statistics calculated from motion tracks extracted from a wide field-of-view video stream. In short, we use topological methods to extract features related to target motion dynamics that are useful for classification and disambiguation and show that small targets can be detected at range with high probability.

Keywords: motion tracks, persistence images, time-delay embedding, topological data analysis

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Authors: Pimploi Tirastittam, Phutthiwat Waiyawuththanapoom

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Nowadays the promotion of the public transportation system in the Bangkok Metropolitan Area is increased such as the “Free Bus for Thai Citizen” Campaign and the prospect of the several MRT routes to increase the convenient and comfortable to the Bangkok Metropolitan area citizens. But citizens do not make full use of them it because the citizens are lack of the data and information and also the confident to the public transportation system of Thailand especially in the time and safety aspects. This research is the Public Transport Planning System by Dijkstra Algorithm: Case Study Bangkok Metropolitan Area by focusing on buses, BTS and MRT schedules/routes to give the most information to passengers. They can choose the way and the routes easily by using Dijkstra STAR Algorithm of Graph Theory which also shows the fare of the trip. This Application was evaluated by 30 normal users to find the mean and standard deviation of the developed system. Results of the evaluation showed that system is at a good level of satisfaction (4.20 and 0.40). From these results we can conclude that the system can be used properly and effectively according to the objective.

Keywords: Dijkstra algorithm, graph theory, public transport, Bangkok metropolitan area

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Authors: Katri K. Cornelissen, Lise Gulli Brokjob, Kristofor McCarty, Jiri Gumancik, Martin J. Tovee, Piers L. Cornelissen

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Recent research has shown that body size estimation of healthy women is driven by independent attitudinal and perceptual components. The attitudinal component represents psychological concerns about body, coupled to low self-esteem and a tendency towards depressive symptomatology, leading to over-estimation of body size, independent of the Body Mass Index (BMI) someone actually has. The perceptual component is a normal bias known as contraction bias, which, for bodies is dependent on actual BMI. Women with a BMI less than the population norm tend to overestimate their size, while women with a BMI greater than the population norm tend to underestimate their size. Women whose BMI is close to the population mean are most accurate. This is indexed by a regression of estimated BMI on actual BMI with a slope less than one. It is well established that body dissatisfaction, i.e. an attitudinal distortion, leads to body size overestimation in eating disordered individuals. However, debate persists as to whether women with eating disorders may also suffer a perceptual body distortion. Therefore, the current study was set to ask whether women with eating disorders exhibit the normal contraction bias when they estimate their own body size. If they do not, this would suggest differences in the way that women with eating disorders process the perceptual aspects of body shape and size in comparison to healthy controls. 100 healthy controls and 33 women with a history of eating disorders were recruited. Critically, it was ensured that both groups of participants represented comparable and adequate ranges of actual BMI (e.g. ~18 to ~40). Of those with eating disorders, 19 had a history of anorexia nervosa, 6 bulimia nervosa, and 8 OSFED. 87.5% of the women with a history of eating disorders self-reported that they were either recovered or recovering, and 89.7% of them self-reported that they had had one or more instances of relapse. The mean time lapsed since first diagnosis was 5 years and on average participants had experienced two relapses. Participants were asked to fill number of psychometric measures (EDE-Q, BSQ, RSE, BDI) to establish the attitudinal component of their body image as well as their tendency to internalize socio-cultural body ideals. Additionally, participants completed a method of adjustment psychophysical task, using photorealistic avatars calibrated for BMI, in order to provide an estimate of their own body size and shape. The data from the healthy controls replicate previous findings, revealing independent contributions to body size estimation from both attitudinal and perceptual (i.e. contraction bias) body image components, as described above. For the eating disorder group, once the adequacy of their actual BMI ranges was established, a regression of estimated BMI on actual BMI had a slope greater than 1, significantly different to that from controls. This suggests that (some) eating disordered individuals process the perceptual aspects of body image differently from healthy controls. It therefore is necessary to develop interventions which are specific to the perceptual processing of body shape and size for the management of (some) individuals with eating disorders.

Keywords: body image distortion, perception, recovery, relapse, BMI, eating disorders

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Authors: Asim Alsharif, Christophe Pinna, Hassan Ghadbeigi

Abstract:

The development of next-generation advanced high strength steels (AHSS) used in the automotive industry requires a better understanding of local deformation and damage development at the scale of their microstructures. This work is focused on dual-phase DP1000 steels and involves micro-mechanical tensile testing inside a scanning electron microscope (SEM) combined with digital image correlation (DIC) to quantify the heterogeneity of deformation in both ferrite and martensite and its evolution up to fracture. Natural features of the microstructure are used for the correlation carried out using Davis LaVision software. Strain localization is observed in both phases with tensile strain values up to 130% and 110% recorded in ferrite and martensite respectively just before final fracture. Damage initiation sites have been observed during deformation in martensite but could not be correlated to local strain values. A finite element (FE) model of the microstructure has then been developed using Abaqus to map stress distributions over representative areas of the microstructure by forcing the model to deform as in the experiment using DIC-measured displacement maps as boundary conditions. A MATLAB code has been developed to automatically mesh the microstructure from SEM images and to map displacement vectors from DIC onto the FE mesh. Results show a correlation of damage initiation at the interface between ferrite and martensite with local principal stress values of about 1700MPa in the martensite phase. Damage in ferrite is now being investigated, and results are expected to bring new insight into damage development in DP steels.

Keywords: advanced high strength steels, digital image correlation, finite element modelling, micro-mechanical testing

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Authors: Dumont Maxime, Correia Carlos, Sauvage Jean-François, Schwartz Noah, Gray Morgan

Abstract:

Context: The concept of the segmented telescope is unavoidable to build extremely large telescopes (ELT) in the quest for spatial resolution, but it also allows one to fit a large telescope within a reduced volume of space (JWST) or into an even smaller volume (Standard Cubesat). Cubesats have tight constraints on the computational burden available and the small payload volume allowed. At the same time, they undergo thermal gradients leading to large and evolving optical aberrations. The pupil segmentation comes nevertheless with an obvious difficulty: to co-phase the different segments. The CubeSat constraints prevent the use of a dedicated wavefront sensor (WFS), making the focal-plane images acquired by the science detector the most practical alternative. Yet, one of the challenges for the wavefront sensing is the non-linearity between the image intensity and the phase aberrations. Plus, for Earth observation, the object is unknown and unrepeatable. Recently, several studies have suggested Neural Networks (NN) for wavefront sensing; especially convolutional NN, which are well known for being non-linear and image-friendly problem solvers. Aims: We study in this paper the prospect of using NN to measure the phasing aberrations of a segmented pupil from the focal-plane image directly without a dedicated wavefront sensing. Methods: In our application, we take the case of a deployable telescope fitting in a CubeSat for Earth observations which triples the aperture size (compared to the 10cm CubeSat standard) and therefore triples the angular resolution capacity. In order to reach the diffraction-limited regime in the visible wavelength, typically, a wavefront error below lambda/50 is required. The telescope focal-plane detector, used for imaging, will be used as a wavefront-sensor. In this work, we study a point source, i.e. the Point Spread Function [PSF] of the optical system as an input of a VGG-net neural network, an architecture designed for image regression/classification. Results: This approach shows some promising results (about 2nm RMS, which is sub lambda/50 of residual WFE with 40-100nm RMS of input WFE) using a relatively fast computational time less than 30 ms which translates a small computation burder. These results allow one further study for higher aberrations and noise.

Keywords: wavefront sensing, deep learning, deployable telescope, space telescope

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Authors: R. Sri Karthi Krishna, A. Saravana Kumar, Kesava Brahmaji, V. S. Vinoj

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The lunar surface may contain rough and non-uniform terrain with dips and peaks. Soft-landing is a method of landing the lander on the lunar surface without any damage to the vehicle. This project focuses on finding a safe landing site for the vehicle by developing a method for the lateral velocity determination of the lunar lander. This is done by processing the real time images obtained by means of an on-board vision sensor. The hazard avoidance phase of the soft-landing starts when the vehicle is about 200 m above the lunar surface. Here, the lander has a very low velocity of about 10 cm/s:vertical and 5 m/s:horizontal. On the detection of a hazard the lander is navigated by controlling the vertical and lateral velocity. In order to find an appropriate landing site and to accordingly navigate, the lander image processing is performed continuously. The images are taken continuously until the landing site is determined, and the lander safely lands on the lunar surface. By integrating this vision-based navigation with the INS a better accuracy for the soft-landing of the lunar lander can be obtained.

Keywords: vision aided INS, image processing, lateral velocity estimation, materials engineering

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

Abstract:

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

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

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Authors: Maria Albuquerque, Miguel Matias, Ângelo Sá, Juliana Sousa, Maria Manuel Mouzinho

Abstract:

Obesity is a frequent disease in Portugal. The surgical treatment is very effective and has an indication when there is a failure of the medical treatment. Although massive weight loss is associated with considerable health gains, these patients are characterized by a variable degree of dermolipodistrophy. In some cases, there is even the development of physical symptoms such as intertriginous, and some degree of psychological distress is present. In almost all cases, a desire for a better body contour, which inhibits some aspects of social life, is a fact. A prospective study was made to access the impact of body contouring surgery in the quality of life of patients who underwent a massive weight lost correction surgical procedure at Centro Hospitalar de Lisboa Central between January 2020 and December 2021. The patients were submitted to the Body Q subjective questionnaire adapted for the Portuguese language and accessed for the following categories: Anguish with Appearance, Contempt with Body Image, Satisfaction with the Abdomen, and Overall Satisfaction with the Body. The questionnaire was repeated at the 6 months mark. A total of 80 patients were sampled. The sex distribution was 79 female and 1 male. The median BMI index before surgery was inferior to 28%. The pre operatory questionnaire showed high scores for Anguish with Appearance and low scores for the body image self-evaluation. Overall, there was an improvement of at least 50% in all the evaluated scores. Additionally, a correlation was found between abdominoplasty and the contempt with body image and satisfaction with the abdomen (p-value <0.05). Massive weight loss is associated with important body deformities that have a significant impact on the patient’s personal and social life. Body contouring surgery is then vital for these patients as it implicates major aesthetic and functional benefits.

Keywords: abdominoplasty, cruroplasty, obesity, massive weight loss

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Authors: Yagya Sharma, Basanta K. Rana, Arup K. Das

Abstract:

Rotary entrainment is a phenomenon in which the interfaces of two immiscible fluids are subjected to external flux in the form of rotation. Present work reports the experimental study on rotary motion of a horizontal cylinder between the interface of air and water to observe the penetration of gas inside the liquid. Experiments have been performed to establish entrainment of air mass in water alongside the cylindrical surface. The movement of tracer and seeded particles have been tracked to calculate the speed and path of the entrained air inside water. Simplified particle image velocimetry technique has been used to trace the movement of particles/tracers at the moment they are injected inside the entrainment zone and suspended beads have been used to replicate the particle movement with respect to time in order to determine the flow dynamics of the fluid along the cylinder. Present paper establishes a thorough experimental analysis of the rotary entrainment phenomenon between air and water keeping in interest the extent to which we can intermix the two and also to study its entrainment trajectories.

Keywords: entrainment, gas-liquid flow, particle image velocimetry, stratified layer mixing

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