Search results for: image narrative

Authors: Yehuda Roth

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In quantum theory, a system’s time evolution is predictable unless an observer performs measurement, as the measurement process can randomize the system. This randomness appears when the measuring device does not accurately describe the measured item, i.e., when the states characterizing the measuring device appear as a superposition of those being measured. When such a mismatch occurs, the measured data randomly collapse into a single eigenstate of the measuring device. This scenario resembles the interpretation process in which the observer does not experience an objective reality but interprets it based on preliminary descriptions initially ingrained into his/her mind. This distinction is the motivation for the present study in which the collapse scenario is regarded as part of the interpretation process of the observer. By adopting the formalism of the quantum theory, we present a complete mathematical approach that describes the interpretation process. We demonstrate this process by applying the proposed interpretation formalism to the ambiguous image "My wife and mother-in-law" to identify whether a woman in the picture is young or old.

Keywords: quantum-like interpretation, ambiguous image, determination, quantum-like collapse, classified representation

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Authors: Terungwa Simon Yange, Agana Moses A.

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This paper studied steganography and designed a simplistic approach to a steganographic tool for hiding information in image files with the view of addressing the security challenges with data by hiding data from unauthorized users to improve its security. The Structured Systems Analysis and Design Method (SSADM) was used in this work. The system was developed using Java Development Kit (JDK) 1.7.0_10 and MySQL Server as its backend. The system was tested with some hypothetical health records which proved the possibility of protecting data from unauthorized users by making it secret so that its existence cannot be easily recognized by fraudulent users. It further strengthens the confidentiality of patient records kept by medical practitioners in the health setting. In conclusion, this work was able to produce a user friendly steganography software that is very fast to install and easy to operate to ensure privacy and secrecy of sensitive data. It also produced an exact copy of the original image and the one carrying the secret message when compared with each.

Keywords: steganography, cryptography, encryption, decryption, secrecy

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Authors: Nguyen Van Toan, Suguru Sangu, Tetsuro Saito, Naoki Inomata, Takahito Ono

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This paper presents the design and fabrication of an optical window for an optical modulator toward image sensing applications. An optical window consists of micrometer-order SiO2 capillaries (porous solid) that can modulate transmission light intensity by moving the liquid in and out of porous solid. A high optical transmittance of the optical window can be achieved due to refractive index matching when the liquid is penetrated into the porous solid. Otherwise, its light transmittance is lower because of light reflection and scattering by air holes and capillary walls. Silicon capillaries fabricated by deep reactive ion etching (DRIE) process are completely oxidized to form the SiO2 capillaries. Therefore, high aspect ratio SiO2 capillaries can be achieved based on silicon capillaries formed by DRIE technique. Large compressive stress of the oxide causes bending of the capillary structure, which is reduced by optimizing the design of device structure. The large stress of the optical window can be released via thin supporting beams. A 7.2 mm x 9.6 mm optical window area toward a fully integrated with the image sensor format is successfully fabricated and its optical transmittance is evaluated with and without inserting liquids (ethanol and matching oil). The achieved modulation range is approximately 20% to 35% with and without liquid penetration in visible region (wavelength range from 450 nm to 650 nm).

Keywords: thermal oxidation process, SiO2 capillaries, optical window, light transmittance, image sensor, liquid penetration

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Authors: Nadia Diyana Mohd Muhaiyuddin, Dayang Rohaya Awang Rambli

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The aim of our work is to identify whether user’s calmness can be a factor to elicit user’s spatial presence experience. Hence, a systematic mental model technique called repertory grid was selected to collect data because users can freely give their opinions in this approach. Three image-based virtual reality (IBVR) environments were created to satisfy the requirement of the repertory grid. Different virtual environments were necessary to allow users to compare and give feedback. Result was analyzed by using descriptive analysis through the SPSS software. The result revealed that ‘users feel calm’ is accepted as one of the factors that can elicit spatial presence. Users also highlighted five IBVR characteristics that could elicit spatial presence, namely, calm sound, calm content, calm color, calm story line, and the calm feeling of the user.

Keywords: spatial presence, presence, virtual reality, image-based virtual reality, human-computer interaction

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Authors: U.V. Suryawanshi, S.S. Chowhan, U.V Kulkarni

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Accuracy of segmentation methods is of great importance in brain image analysis. Tissue classification in Magnetic Resonance brain images (MRI) is an important issue in the analysis of several brain dementias. This paper portraits performance of segmentation techniques that are used on Brain MRI. A large variety of algorithms for segmentation of Brain MRI has been developed. The objective of this paper is to perform a segmentation process on MR images of the human brain, using Fuzzy c-means (FCM), Kernel based Fuzzy c-means clustering (KFCM), Spatial Fuzzy c-means (SFCM) and Improved Fuzzy c-means (IFCM). The review covers imaging modalities, MRI and methods for noise reduction and segmentation approaches. All methods are applied on MRI brain images which are degraded by salt-pepper noise demonstrate that the IFCM algorithm performs more robust to noise than the standard FCM algorithm. We conclude with a discussion on the trend of future research in brain segmentation and changing norms in IFCM for better results.

Keywords: image segmentation, preprocessing, MRI, FCM, KFCM, SFCM, IFCM

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Authors: Ado Ismail Sabo

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Statement of the Problem: The global trend in tertiary education institutions today is changing and moving towards engagement, promotion and marketing. The reason is to upscale reputation and impact positioning. More prominently, existing rivalry today seeks to draw-in the best and brightest students. A university or college is no longer just an institution of higher learning, but one adapting additional business nomenclature. Therefore, huge financial resources are invested by educational institutions to polish their image and improve their global and national ranking. In Nigeria, which boasts of a vast population of over 180 million people, some of whose patronage can bolster its education sector; standard of education continues to decline. Today, some Nigerian tertiary education institutions are shadows of their pasts, in terms of academic excellence. Quality has been relinquished because of the unquenchable quest by government officials, some civil servants, school heads and educators to amass wealth. It is very difficult to gain student satisfaction and their loyalty. Some of the student’s loyalties factor towards public higher educational institutions might be confusing. It is difficult to understand the extent to which students are satisfy on many needs. Some students might feel satisfy with the academic lecturers only, whereas others may want everything, and others will never satisfy. Due to these problems, this research aims to uncover the crucial factors influencing student loyalty and to examine if students’ satisfaction might impact mediate the relationship between service quality, organisational image and students’ loyalty towards public higher education institutions in Kano State, Nigeria. The significance of the current study is underscored by the paucity of similar research in the subject area and public tertiary education in a developing country like Nigeria as shown in existing literature. Methodology: The current study was undertaken by quantitative research methodology. Sample of 600 valid responses were obtained within the study population comprising six selected public higher education institutions in Kano State, Nigeria. These include: North West University Kano, Bayero University Kano, School of Management Studies Kano, School of Technology Kano, Sa’adatu Rimi College Kano and Federal College of Education (FCE) Kano. Four main hypotheses were formulated and tested using structural equation modeling techniques with Analysis of Moment Structure (AMOS Version 22.0). Results: Analysis of the data provided support for the main issue of this study, and the following findings are established: “Student Satisfaction mediates the relationship between Service Quality and Student Loyalty”, “Student Satisfaction mediates the relationship between Organizational Image and Student Loyalty” respectively. The findings of this study contributed to the theoretical implication which proposed a structural model that examined the relationships among overall Organizational image, service quality, student satisfaction and student loyalty. Conclusion: In addition, the findings offered a better insight to the managerial (higher institution of learning service providers) by focusing on portraying the image of service quality with student satisfaction in improving the quality of student loyalty.

Keywords: student loyalty, service quality, student satisfaction, organizational image

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Authors: Saeed Vahedikamal, Ian Hepburn

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Microwave Kinetic Inductance Detectors (MKIDs) are considered as one of the most promising photon detectors of the future in many Astronomical applications such as exoplanet detections. The MKID advantages stem from their single photon sensitivity (ranging from UV to optical and near infrared), photon energy resolution and high temporal capability (~microseconds). There has been substantial progress in the development of these detectors and MKIDs with Megapixel arrays is now possible. The unique capability of recording an incident photon and its energy (or wavelength) while also registering its time of arrival to within a microsecond enables an array of MKIDs to produce a four-dimensional data block of x, y, z and t comprising x, y spatial, z axis per pixel spectral and t axis per pixel which is temporal. This offers the possibility that the spectrum and brightness variation for any detected piece of space debris as a function of time might offer a unique identifier or fingerprint. Such a fingerprint signal from any object identified in multiple detections by different observers has the potential to determine the orbital features of the object and be used for their tracking. Modelling performed so far shows that with a 20 cm telescope located at an Astronomical observatory (e.g. La Palma, Canary Islands) we could detect sub cm objects at GEO. By considering a Lambertian sphere with a 10 % reflectivity (albedo of the Moon) we anticipate the following for a GEO object: 10 cm object imaged in a 1 second image capture; 1.2 cm object for a 70 second image integration or 0.65 cm object for a 4 minute image integration. We present details of our modelling and the potential instrument for a dedicated GEO surveillance system.

Keywords: space debris, orbital debris, detection system, observation, microwave kinetic inductance detectors, MKID

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Authors: Xiaoya Yi, Yi He, Zhao Lu, Yang Zhang

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In the process of rapid urbanization, many historical cities have undergone excessive demolition and construction under the protection and renewal mechanism. The original pattern of the city has been changed, the urban context has been cut off, and historical features have gradually been lost. The historical city gradually changed into the form of decentralization and fragmentation. The understanding of the ancient city includes two levels. The first one refers to the ancient city on the physical space, which defined an ancient city by its historic walls. The second refers to the public perception of the image, which is derived from people's spatial identification of the ancient city. In ancient China, people draw maps to show their way of understanding the city. Starting from ancient maps and exploring the spatial characteristics of traditional Chinese cities from the perspective of urban imagery is a key clue to understanding the spatial characteristics of historical cities on an overall level. The spatial characteristics of the urban image presented by the ancient map are summarized into two levels by typology. The first is the spatial pattern composed of the center, axis and boundary. The second is the space element that contains the city, street, and sign system. Taking the ancient city of Shipu as a typical case, the "city image" in the ancient map is analyzed as a prototype, and it is projected into the current urban space. The research found that after a long period of evolution, the historical spatial pattern of the ancient city has changed from “dominant” to “recessive control”, and the historical spatial elements are non-centralized and fragmented. The wall that serves as the boundary of the ancient city is transformed into “fragmentary remains”, the streets and lanes that serve as the axis of the ancient city are transformed into “structural remains”, and the symbols of the ancient city center are transformed into “site remains”. Based on this, the paper proposed the methods of controlling the protection of land boundaries, the protecting of the streets and lanes, and the selective restoring of the city wall system and the sign system by accurate assessment. In addition, this paper emphasizes the continuity of the ancient city's traditional spatial pattern and attempts to explore a holistic conservation method of the ancient city in the modern context.

Keywords: ancient city protection, ancient maps, Shipu ancient city, urban intention

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Authors: Ananya Ananya, Karthik Rao

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Accurate segmentation of knee cartilage in 3-D magnetic resonance (MR) images for quantitative assessment of volume is crucial for studying and diagnosing osteoarthritis (OA) of the knee, one of the major causes of disability in elderly people. Radiologists generally perform this task in slice-by-slice manner taking 15-20 minutes per 3D image, and lead to high inter and intra observer variability. Hence automatic methods for knee cartilage segmentation are desirable and are an active field of research. This paper presents design and experimental evaluation of 2D convolutional neural networks based fully automated methods for knee cartilage segmentation in 3D MRI. The architectures are validated based on 40 test images and 60 training images from SKI10 dataset. The proposed methods segment 2D slices one by one, which are then combined to give segmentation for whole 3D images. Proposed methods are modified versions of U-net and dilated convolutions, consisting of a single step that segments the given image to 5 labels: background, femoral cartilage, tibia cartilage, femoral bone and tibia bone; cartilages being the primary components of interest. U-net consists of a contracting path and an expanding path, to capture context and localization respectively. Dilated convolutions lead to an exponential expansion of receptive field with only a linear increase in a number of parameters. A combination of modified U-net and dilated convolutions has also been explored. These architectures segment one 3D image in 8 – 10 seconds giving average volumetric Dice Score Coefficients (DSC) of 0.950 - 0.962 for femoral cartilage and 0.951 - 0.966 for tibia cartilage, reference being the manual segmentation.

Keywords: convolutional neural networks, dilated convolutions, 3 dimensional, fully automated, knee cartilage, MRI, segmentation, U-net

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Authors: Nidhal Azawi

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Colonoscopy procedure is widely used in the world to detect an abnormality. Early diagnosis can help to heal many patients. Because of the unavoidable artifacts that exist in colon images, doctors cannot detect a colon surface precisely. The purpose of this work is to improve the visual quality of colonoscopy videos to provide better information for physicians by removing some artifacts. This work complements a series of work consisting of three previously published papers. In this paper, Optic flow is used for motion compensation, and then consecutive images are aligned/registered to integrate some information to create a new image that has or reveals more information than the original one. Colon images have been classified into informative and noninformative images by using a deep neural network. Then, two different strategies were used to treat informative and noninformative images. Informative images were treated by using Lucas Kanade (LK) with an adaptive temporal mean/median filter, whereas noninformative images are treated by using Lucas Kanade with a derivative of Gaussian (LKDOG) with adaptive temporal median images. A comparison result showed that this work achieved better results than that results in the state- of- the- art strategies for the same degraded colon images data set, which consists of 1000 images. The new proposed algorithm reduced the error alignment by about a factor of 0.3 with a 100% successfully image alignment ratio. In conclusion, this algorithm achieved better results than the state-of-the-art approaches in case of enhancing the informative images as shown in the results section; also, it succeeded to convert the non-informative images that have very few details/no details because of the blurriness/out of focus or because of the specular highlight dominate significant amount of an image to informative images.

Keywords: optic flow, colonoscopy, artifacts, spatial temporal filter

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Authors: Deborah Zelinsky

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The retina filters millions of incoming signals into a smaller amount of exiting optic nerve fibers that travel to different portions of the brain. Most of the signals are for eyesight (called "image-forming" signals). However, there are other faster signals that travel "elsewhere" and are not directly involved with eyesight (called "non-image-forming" signals). This article centers on the neurons of the optic nerve connecting to parts of the limbic system. Eye care providers are currently looking at parvocellular and magnocellular processing pathways without realizing that those are part of an enormous "galaxy" of all the body systems. Lenses are modifying both non-image and image-forming pathways, taking A.M. Skeffington's seminal work one step further. Almost 100 years ago, he described the Where am I (orientation), Where is It (localization), and What is It (identification) pathways. Now, among others, there is a How am I (animation) and a Who am I (inclination, motivation, imagination) pathway. Classic eye testing considers pupils and often assesses posture and motion awareness, but classical prescriptions often overlook limbic involvement in visual processing. The limbic system is composed of the hippocampus, amygdala, hypothalamus, and anterior nuclei of the thalamus. The optic nerve's limbic connections arise from the intrinsically photosensitive retinal ganglion cells (ipRGC) through the "retinohypothalamic tract" (RHT). There are two main hypothalamic nuclei with direct photic inputs. These are the suprachiasmatic nucleus and the paraventricular nucleus. Other hypothalamic nuclei connected with retinal function, including mood regulation, appetite, and glucose regulation, are the supraoptic nucleus and the arcuate nucleus. The retino-hypothalamic tract is often overlooked when we prescribe eyeglasses. Each person is different, but the lenses we choose are influencing this fast processing, which affects each patient's aiming and focusing abilities. These signals arise from the ipRGC cells that were only discovered 20+ years ago and do not address the campana retinal interneurons that were only discovered 2 years ago. As eyecare providers, we are unknowingly altering such factors as lymph flow, glucose metabolism, appetite, and sleep cycles in our patients. It is important to know what we are prescribing as the visual processing evaluations expand past the 20/20 central eyesight.

Keywords: neuromodulation, retinal processing, retinohypothalamic tract, limbic system, visual processing

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Authors: P. S. Surya Meghana, K. Lingeshwaran, C. Kannan, V. Raghavendran, C. Priya

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One of the most basic and powerful tools in all of science and medicine is the light microscope, the fundamental device for laboratory as well as research purposes. With the improving technology, the need for portable, economic and user-friendly instruments is in high demand. The conventional microscope fails to live up to the emerging trend. Also, adequate access to healthcare is not widely available, especially in developing countries. The most basic step towards the curing of a malady is the diagnosis of the disease itself. The main aim of this paper is to diagnose Malaria with the most common device, cell phones, which prove to be the immediate solution for most of the modern day needs with the development of wireless infrastructure allowing to compute and communicate on the move. This opened up the opportunity to develop novel imaging, sensing, and diagnostics platforms using mobile phones as an underlying platform to address the global demand for accurate, sensitive, cost-effective, and field-portable measurement devices for use in remote and resource-limited settings around the world.

Keywords: cellular, hand-held, health care, image processing, malarial parasites, microscope

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Authors: Bello Yusuf Idi

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The Gongola arm of the Upper Banue Trough, Northeastern Nigeria is predominantly covered by the outcrops of Limestone-bearing rocks in form of Sandstone with intercalation of carbonate clay, shale, basaltic, felsphatic and migmatide rocks at subpixel dimension. In this work, subpixel classification algorithm was used to classify the data acquired from landsat 7 Enhance Thematic Mapper (ETM+) satellite system with the aim of producing fractional distribution image for three most economically important solid minerals of the area: Limestone, Basalt and Migmatide. Linear Spectral Unmixing (LSU) algorithm was used to produce fractional distribution image of abundance of the three mineral resources within a 100Km2 portion of the area. The results show that the minerals occur at different proportion all over the area. The fractional map could therefore serve as a guide to the ongoing reconnaissance for the economic potentiality of the formation.

Keywords: linear spectral un-mixing, upper benue trough, gongola arm, geological engineering

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Authors: Zaqiatul Mardiah, Afdol Tharik Wastono, Abdul Muta'ali

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In general, the Arabic preposition ‘ala encodes the sense of UP-DOWN schema. However, the use of the preposition ‘ala can has many extended schemas that still have relation to its primary sense. In this paper, we show how the framework of cognitive linguistics (CL) based on image schemas can be applied to analyze the spatial semantic of the use of preposition ‘ala in the horizontal and vertical axes. The preposition ‘ala is usually used in the locative sense in which one physical entity is UP-DOWN relation to another physical entity. In spite of that, the cognitive analysis of ‘ala justifies the use of this preposition in many situations to seemingly encode non-up down-related spatial relations, and non-physical relation. This uncovers some of the unsolved issues concerning prepositions in general and the Arabic prepositions in particular the use of ‘ala as a sample. Using the Arabic corpus data, we reveal that in many cases and situations, the use of ‘ala is extended to depict relations other than the ones where the Trajector (TR) is actually in up-down relation to the Landmark (LM). The instances analyzed in this paper show that ‘ala encodes not only the spatial relations in which the TR and the LM are horizontally or vertically related to each other, but also non-spatial relations.

Keywords: image schema, preposition, spatial semantic, up-down relation

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Authors: Jentel Van Havermaet, Geert Van Hove, Elisabeth De Schauwer

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This study re-conceptualizes visual impairment in the interdependent context of James, his family, and allies. Living with a visual impairment is understood as an entanglement of assemblages, dynamics, disablism, systems… We narrated this diffractively into two meaningful events: decisions and processes on (inclusive) education and hinderances in connecting with others. We entangled and (un)raveled lived experiences in assemblages in which the contextualized meaning of visual impairment became more clearly. The contextualized narrative of James interwove complex intra-actions; showed the complexity and contextualization of entangled relationalities.

Keywords: disability studies, contextualization, visual impairment, assemblage, entanglement, lived experiences

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Authors: Sarah Holdren, Laura Crook, Anne Drapkin Lyerly

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Objective: The COVID-19 Pandemic has drawn new attention to long-existing bioethical questions around pregnancy, childbirth, and parenthood. Due to the increased risk of severe COVID-19, pregnant individuals may experience anxiety regarding medical decision-making. Especially in the case of hospital births, questions around the ethics of bringing healthy pregnant individuals into a high-risk environment for viral transmission illuminate gaps in the American maternal and child healthcare system. Limited research has sought to understand the experiences of those who gave birth outside hospitals during this time. This study aims to understand pregnant individuals’ conceptualization of risk during the COVID-19 pandemic. Methods: Individuals who gave birth after March 2020 were recruited through advertisements on social media. Participants completed a 1-hour semi-structured interview and a demographic questionnaire. Interviews were transcribed and coded by members of the research team using thematic narrative analysis. Results: A total of 18 participants were interviewed and completed the demographic questionnaire. The language of risk was utilized in birth narratives in three different ways, which highlighted the multileveled and nuanced ways in which risk is understood and mitigated by pregnant and birthing individuals. These included: 1. The risk of contracting COVID-19 before, during, and after birth, 2. The risk of birth complications requiring medical interventions dependent on selected birthing space (home, birthing center, hospital), and 3. The overall risk of creating life in the middle of a pandemic. The risk of contracting COVID-19 and risk of birth complications were often weighed in paradoxical ways throughout each individual’s pregnancy, while phrases such as “pandemic baby” and “apocalypse” appeared throughout narratives and highlighted the broader implications of pregnancy and childbirth during this momentous time. Conclusions: Healthcare professionals should consider the variety of ways that pregnant and birthing individuals understand the risk when counseling patients on healthcare decisions, especially during times of healthcare crisis such as COVID-19. Future work should look to understand how the language of risk fits into a broader understanding of the human experience of growing life in times of crisis.

Keywords: maternal and child health, thematic narrative analysis, COVID-19, risk mitigation

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Authors: C. Zimmermann, E. Lackner, M. Ebner

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Massive Open Online Courses (MOOCs) are increasingly popular learning hubs that are boasting considerable participant numbers, innovative technical features, and a multitude of instructional resources. Still, there is a high level of evidence showing that almost all MOOCs suffer from a declining frequency of participant activity and fairly low completion rates. In this paper, we would like to share the lessons learned in implementing several design patterns that have been suggested in order to foster participant activity. Our conclusions are based on experiences with the ‘Dr. Internet’ MOOC, which was created as an xMOOC to raise awareness for a more critical approach to online health information: participants had to diagnose medical case studies. There is a growing body of recommendations (based on Learning Analytics results from earlier xMOOCs) as to how the decline in participant activity can be alleviated. One promising focus in this regard is instructional design patterns, since they have a tremendous influence on the learner’s motivation, which in turn is a crucial trigger of learning processes. Since Medieval Age storytelling, micro-learning units and specific comprehensible, narrative structures were chosen to animate the audience to follow narration. Hence, MOOC participants are not likely to abandon a course or information channel when their curiosity is kept at a continuously high level. Critical aspects that warrant consideration in this regard include shorter course duration, a narrative structure with suspense peaks (according to the ‘storytelling’ approach), and a course schedule that is diversified and stimulating, yet easy to follow. All of these criteria have been observed within the design of the Dr. Internet MOOC: 1) the standard eight week course duration was shortened down to six weeks, 2) all six case studies had a special quiz format and a corresponding resolution video which was made available in the subsequent week, 3) two out of six case studies were split up in serial video sequences to be presented over the span of two weeks, and 4) the videos were generally scheduled in a less predictable sequence. However, the statistical results from the first run of the MOOC do not indicate any strong influences on the retention rate, so we conclude with some suggestions as to why this might be and what aspects need further consideration.

Keywords: case study, Dr. internet, experience, MOOCs, design patterns

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Authors: Khalak Bin Khair, Saqib Jahir, Mohammed Ibrahim, Fahad Bin, Debajyoti Karmaker

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Object detection is a computer technology that deals with searching through digital images and videos for occurrences of semantic elements of a particular class. It is associated with image processing and computer vision. On top of object detection, we detect camouflage objects within an image using Deep Learning techniques. Deep learning may be a subset of machine learning that's essentially a three-layer neural network Over 6500 images that possess camouflage properties are gathered from various internet sources and divided into 4 categories to compare the result. Those images are labeled and then trained and tested using vgg16 architecture on the jupyter notebook using the TensorFlow platform. The architecture is further customized using Transfer Learning. Methods for transferring information from one or more of these source tasks to increase learning in a related target task are created through transfer learning. The purpose of this transfer of learning methodologies is to aid in the evolution of machine learning to the point where it is as efficient as human learning.

Keywords: deep learning, transfer learning, TensorFlow, camouflage, object detection, architecture, accuracy, model, VGG16

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Authors: Yasuyuki Takahashi, Genta Hoshi, Kyoko Saito

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Objectives: The objective of this study was to evaluate the reproducibility of I-123-N-ω-fluoropropyl-2β-carbomethoxy-3β-(4- iodophenyl) nortropane (I-123 FP-CIT) SPECT by using specific binding ratio (SBR) in phantom studies and Parkinson’s Disease (PD) patients. Methods: We made striatum phantom originally and confirmed reproducibility. The phantom studies changed head position and accumulation of FP-CIT, each. And image processing confirms influence on SBR by 30 cases. 30 PD received a SPECT for 3 hours post injection of I-123 FP-CIT 167MBq. Results: SBR decreased in rotatory direction by the patient position by the phantom studies. And, SBR improved the influence after the attenuation and the scatter correction in the cases (y=0.99x+0.57 r2=0.83). However, Stage II recognized dispersion in SBR by low accumulation. Conclusion: Than the phantom studies that assumed the normal cases, the SPECT image after the attenuation and scatter correction had better reproducibility.

Keywords: 123I-FP-CIT, specific binding ratio, Parkinson’s disease

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Authors: Zahra Barzegar, Reza Deedari, Behzad Pourgharib

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This study examines how metamorphosis in nature is depicted in Charles Tomlinson's poetry through Lawrence Buell's mimesis and referential strategy of adéquation. This study aims to answer the questions that what is the relationship between Tomlinson's selected poems and nature, and how does Tomlinson's poetry bring the reader close to the natural environment. Adéquation is a way that brings the reader close to nature, not by imitating nature but by referring to it imaginatively and creating a stylized image. Using figurative language, namely imagery, metaphor, and analogy, adéquation creates a stylized image of metamorphosis in a nature scene that acts as a middle way between the reader and nature. This paper proves that adéquation reinvents the metamorphosis in natural occurrences in Charles Tomlinson's selected poems. Thus, a reader whose imagination is addressed achieves closeness with nature and a caring outlook toward natural happenings. This article confirms that Tomlinson's poems are potential enough to represent metamorphosis in nature through adéquation. Therefore, the reader understands nature beyond the poem as the poem presents a gist of nature through adéquation.

Keywords: adéquation, metamorphosis, nature, referentiality

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Authors: Brayden Mi

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Reverse time migration has been widely used in the Petroleum exploration industry to reveal subsurface images and to detect rock and fluid properties since the early 1980s. The seismic technology involves the construction of a velocity model through interpretive model construction, seismic tomography, or full waveform inversion, and the application of the reverse-time propagation of acquired seismic data and the original wavelet used in the acquisition. The methodology has matured from 2D, simple media to present-day to handle full 3D imaging challenges in extremely complex geological conditions. Conventional Ultrasound computed tomography (USCT) utilize travel-time-inversion to reconstruct the velocity structure of an organ. With the velocity structure, USCT data can be migrated with the “bend-ray” method, also known as migration. Its seismic application counterpart is called Kirchhoff depth migration, in which the source of reflective energy is traced by ray-tracing and summed to produce a subsurface image. It is well known that ray-tracing-based migration has severe limitations in strongly heterogeneous media and irregular acquisition geometries. Reverse time migration (RTM), on the other hand, fully accounts for the wave phenomena, including multiple arrives and turning rays due to complex velocity structure. It has the capability to fully reconstruct the image detectable in its acquisition aperture. The RTM algorithms typically require a rather accurate velocity model and demand high computing powers, and may not be applicable to real-time imaging as normally required in day-to-day medical operations. However, with the improvement of computing technology, such a computational bottleneck may not present a challenge in the near future. The present-day (RTM) algorithms are typically implemented from a flat datum for the seismic industry. It can be modified to accommodate any acquisition geometry and aperture, as long as sufficient illumination is provided. Such flexibility of RTM can be conveniently implemented for the application in USCT imaging if the spatial coordinates of the transmitters and receivers are known and enough data is collected to provide full illumination. This paper proposes an implementation of a full 3D RTM algorithm for USCT imaging to produce an accurate 3D acoustic image based on the Phase-shift-plus-interpolation (PSPI) method for wavefield extrapolation. In this method, each acquired data set (shot) is propagated back in time, and a known ultrasound wavelet is propagated forward in time, with PSPI wavefield extrapolation and a piece-wise constant velocity model of the organ (breast). The imaging condition is then applied to produce a partial image. Although each image is subject to the limitation of its own illumination aperture, the stack of multiple partial images will produce a full image of the organ, with a much-reduced noise level if compared with individual partial images.

Keywords: illumination, reverse time migration (RTM), ultrasound computed tomography (USCT), wavefield extrapolation

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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: 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

Abstract:

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

Procedia PDF Downloads 499