Search results for: lossy image encryption
1873 Deep Learning-Based Liver 3D Slicer for Image-Guided Therapy: Segmentation and Needle Aspiration
Authors: Ahmedou Moulaye Idriss, Tfeil Yahya, Tamas Ungi, Gabor Fichtinger
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Image-guided therapy (IGT) plays a crucial role in minimally invasive procedures for liver interventions. Accurate segmentation of the liver and precise needle placement is essential for successful interventions such as needle aspiration. In this study, we propose a deep learning-based liver 3D slicer designed to enhance segmentation accuracy and facilitate needle aspiration procedures. The developed 3D slicer leverages state-of-the-art convolutional neural networks (CNNs) for automatic liver segmentation in medical images. The CNN model is trained on a diverse dataset of liver images obtained from various imaging modalities, including computed tomography (CT) and magnetic resonance imaging (MRI). The trained model demonstrates robust performance in accurately delineating liver boundaries, even in cases with anatomical variations and pathological conditions. Furthermore, the 3D slicer integrates advanced image registration techniques to ensure accurate alignment of preoperative images with real-time interventional imaging. This alignment enhances the precision of needle placement during aspiration procedures, minimizing the risk of complications and improving overall intervention outcomes. To validate the efficacy of the proposed deep learning-based 3D slicer, a comprehensive evaluation is conducted using a dataset of clinical cases. Quantitative metrics, including the Dice similarity coefficient and Hausdorff distance, are employed to assess the accuracy of liver segmentation. Additionally, the performance of the 3D slicer in guiding needle aspiration procedures is evaluated through simulated and clinical interventions. Preliminary results demonstrate the effectiveness of the developed 3D slicer in achieving accurate liver segmentation and guiding needle aspiration procedures with high precision. The integration of deep learning techniques into the IGT workflow shows great promise for enhancing the efficiency and safety of liver interventions, ultimately contributing to improved patient outcomes.Keywords: deep learning, liver segmentation, 3D slicer, image guided therapy, needle aspiration
Procedia PDF Downloads 361872 Photomicrograph-Based Neuropathology Consultation in Tanzania; The Utility of Static-Image Neurotelepathology in Low- And Middle-Income Countries
Authors: Francis Zerd, Brian E. Moore, Atuganile E. Malango, Patrick W. Hosokawa, Kevin O. Lillehei, Laurence Lemery Mchome, D. Ryan Ormond
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Introduction: Since neuropathologic diagnosis in the developing world is hampered by limitations in technical infrastructure, trained laboratory personnel, and subspecialty-trained pathologists, the use of telepathology for diagnostic support, second-opinion consultations, and ongoing training holds promise as a means of addressing these challenges. This research aims to assess the utility of static teleneuropathology in improving neuropathologic diagnoses in low- and middle-income countries. Methods: Consecutive neurosurgical biopsy and resection specimens obtained at Muhimbili National Hospital in Tanzania between July 1, 2018, and June 30, 2019, were selected for retrospective, blinded static-image neuropathologic review followed by on-site review by an expert neuropathologist. Results: A total of 75 neuropathologic cases were reviewed. The agreement of static images and on-site glass diagnosis was 71% with strict criteria and 88% with less stringent criteria. This represents an overall improvement in diagnostic accuracy from 36% by general pathologists to 71% by a neuropathologist using static telepathology (or 76% to 88% with less stringent criteria). Conclusions: Telepathology offers a suitable means of providing diagnostic support, second-opinion consultations, and ongoing training to pathologists practicing in resource-limited countries. Moreover, static digital teleneuropathology is an uncomplicated, cost-effective, and reliable way to achieve these goals.Keywords: neuropathology, resource-limited settings, static image, Tanzania, teleneuropathology
Procedia PDF Downloads 991871 Multimodality in Storefront Windows: The Impact of Verbo-Visual Design on Consumer Behavior
Authors: Angela Bargenda, Erhard Lick, Dhoha Trabelsi
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Research in retailing has identified the importance of atmospherics as an essential element in enhancing store image, store patronage intentions, and the overall shopping experience in a retail environment. However, in the area of atmospherics, store window design, which represents an essential component of external store atmospherics, remains a vastly underrepresented phenomenon in extant scholarship. This paper seeks to fill this gap by exploring the relevance of store window design as an atmospheric tool. In particular, empirical evidence of theme-based theatrical store front windows, which put emphasis on the use of verbo-visual design elements, was found in Paris and New York. The purpose of this study was to identify to what extent such multimodal window designs of high-end department stores in metropolitan cities have an impact on store entry decisions and attitudes towards the retailer’s image. As theoretical construct, the linguistic concept of multimodality and Mehrabian’s and Russell’s model in environmental psychology were applied. To answer the research question, two studies were conducted. For Study 1 a case study approach was selected to define three different types of store window designs based on different types of visual-verbal relations. Each of these types of store window design represented a different level of cognitive elaboration required for the decoding process. Study 2 consisted of an on-line survey carried out among more than 300 respondents to examine the influence of these three types of store window design on the consumer behavioral variables mentioned above. The results of this study show that the higher the cognitive elaboration needed to decode the message of the store window, the lower the store entry propensity. In contrast, the higher the cognitive elaboration, the higher the perceived image of the retailer’s image. One important conclusion is that in order to increase consumers’ propensity to enter stores with theme-based theatrical store front windows, retailers need to limit the cognitive elaboration required to decode their verbo-visual window design.Keywords: consumer behavior, multimodality, store atmospherics, store window design
Procedia PDF Downloads 1941870 A Neural Network Classifier for Identifying Duplicate Image Entries in Real-Estate Databases
Authors: Sergey Ermolin, Olga Ermolin
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A Deep Convolution Neural Network with Triplet Loss is used to identify duplicate images in real-estate advertisements in the presence of image artifacts such as watermarking, cropping, hue/brightness adjustment, and others. The effects of batch normalization, spatial dropout, and various convergence methodologies on the resulting detection accuracy are discussed. For comparative Return-on-Investment study (per industry request), end-2-end performance is benchmarked on both Nvidia Titan GPUs and Intel’s Xeon CPUs. A new real-estate dataset from San Francisco Bay Area is used for this work. Sufficient duplicate detection accuracy is achieved to supplement other database-grounded methods of duplicate removal. The implemented method is used in a Proof-of-Concept project in the real-estate industry.Keywords: visual recognition, convolutional neural networks, triplet loss, spatial batch normalization with dropout, duplicate removal, advertisement technologies, performance benchmarking
Procedia PDF Downloads 3271869 A Hybrid Watermarking Model Based on Frequency of Occurrence
Authors: Hamza A. A. Al-Sewadi, Adnan H. M. Al-Helali, Samaa A. K. Khamis
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Ownership proofs of multimedia such as text, image, audio or video files can be achieved by the burial of watermark is them. It is achieved by introducing modifications into these files that are imperceptible to the human senses but easily recoverable by a computer program. These modifications would be in the time domain or frequency domain or both. This paper presents a procedure for watermarking by mixing amplitude modulation with frequency transformation histogram; namely a specific value is used to modulate the intensity component Y of the YIQ components of the carrier image. This scheme is referred to as histogram embedding technique (HET). Results comparison with those of other techniques such as discrete wavelet transform (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD) have shown an enhance efficiency in terms of ease and performance. It has manifested a good degree of robustness against various environment effects such as resizing, rotation and different kinds of noise. This method would prove very useful technique for copyright protection and ownership judgment.Keywords: authentication, copyright protection, information hiding, ownership, watermarking
Procedia PDF Downloads 5601868 Object Tracking in Motion Blurred Images with Adaptive Mean Shift and Wavelet Feature
Authors: Iman Iraei, Mina Sharifi
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A method for object tracking in motion blurred images is proposed in this article. This paper shows that object tracking could be improved with this approach. We use mean shift algorithm to track different objects as a main tracker. But, the problem is that mean shift could not track the selected object accurately in blurred scenes. So, for better tracking result, and increasing the accuracy of tracking, wavelet transform is used. We use a feature named as blur extent, which could help us to get better results in tracking. For calculating of this feature, we should use Harr wavelet. We can look at this matter from two different angles which lead to determine whether an image is blurred or not and to what extent an image is blur. In fact, this feature left an impact on the covariance matrix of mean shift algorithm and cause to better performance of tracking. This method has been concentrated mostly on motion blur parameter. transform. The results reveal the ability of our method in order to reach more accurately tracking.Keywords: mean shift, object tracking, blur extent, wavelet transform, motion blur
Procedia PDF Downloads 2041867 Utilizing the Principal Component Analysis on Multispectral Aerial Imagery for Identification of Underlying Structures
Authors: Marcos Bosques-Perez, Walter Izquierdo, Harold Martin, Liangdon Deng, Josue Rodriguez, Thony Yan, Mercedes Cabrerizo, Armando Barreto, Naphtali Rishe, Malek Adjouadi
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Aerial imagery is a powerful tool when it comes to analyzing temporal changes in ecosystems and extracting valuable information from the observed scene. It allows us to identify and assess various elements such as objects, structures, textures, waterways, and shadows. To extract meaningful information, multispectral cameras capture data across different wavelength bands of the electromagnetic spectrum. In this study, the collected multispectral aerial images were subjected to principal component analysis (PCA) to identify independent and uncorrelated components or features that extend beyond the visible spectrum captured in standard RGB images. The results demonstrate that these principal components contain unique characteristics specific to certain wavebands, enabling effective object identification and image segmentation.Keywords: big data, image processing, multispectral, principal component analysis
Procedia PDF Downloads 1631866 An Accurate Computer-Aided Diagnosis: CAD System for Diagnosis of Aortic Enlargement by Using Convolutional Neural Networks
Authors: Mahdi Bazarganigilani
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Aortic enlargement, also known as an aortic aneurysm, can occur when the walls of the aorta become weak. This disease can become deadly if overlooked and undiagnosed. In this paper, a computer-aided diagnosis (CAD) system was introduced to accurately diagnose aortic enlargement from chest x-ray images. An enhanced convolutional neural network (CNN) was employed and then trained by transfer learning by using three different main areas from the original images. The areas included the left lung, heart, and right lung. The accuracy of the system was then evaluated on 1001 samples by using 4-fold cross-validation. A promising accuracy of 90% was achieved in terms of the F-measure indicator. The results showed using different areas from the original image in the training phase of CNN could increase the accuracy of predictions. This encouraged the author to evaluate this method on a larger dataset and even on different CAD systems for further enhancement of this methodology.Keywords: computer-aided diagnosis systems, aortic enlargement, chest X-ray, image processing, convolutional neural networks
Procedia PDF Downloads 1501865 An Analysis of the Relations between Aggregates’ Shape and Mechanical Properties throughout the Railway Ballast Service Life
Authors: Daianne Fernandes Diogenes
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Railway ballast aggregates’ shape properties and size distribution can be directly affected by several factors, such as traffic, fouling, and maintenance processes, which cause breakage and wearing, leading to the fine particles’ accumulation through the ballast layer. This research aims to analyze the influence of traffic, tamping process, and sleepers’ stiffness on aggregates' shape and mechanical properties, by using traditional and digital image processing (DIP) techniques and cyclic tests, like resilient modulus (RM) and permanent deformation (PD). Aggregates were collected in different phases of the railway service life: (i) right after the crushing process; (ii) after construction, for the aggregates positioned below the sleepers and (iii) after 5 years of operation. An increase in the percentage of cubic particles was observed for the materials (ii) and (iii), providing a better interlocking, increasing stiffness and reducing axial deformation after 5 years of service, when compared to the initial conditions.Keywords: digital image processing, mechanical behavior, railway ballast, shape properties
Procedia PDF Downloads 1151864 Continual Learning Using Data Generation for Hyperspectral Remote Sensing Scene Classification
Authors: Samiah Alammari, Nassim Ammour
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When providing a massive number of tasks successively to a deep learning process, a good performance of the model requires preserving the previous tasks data to retrain the model for each upcoming classification. Otherwise, the model performs poorly due to the catastrophic forgetting phenomenon. To overcome this shortcoming, we developed a successful continual learning deep model for remote sensing hyperspectral image regions classification. The proposed neural network architecture encapsulates two trainable subnetworks. The first module adapts its weights by minimizing the discrimination error between the land-cover classes during the new task learning, and the second module tries to learn how to replicate the data of the previous tasks by discovering the latent data structure of the new task dataset. We conduct experiments on HSI dataset Indian Pines. The results confirm the capability of the proposed method.Keywords: continual learning, data reconstruction, remote sensing, hyperspectral image segmentation
Procedia PDF Downloads 2471863 Brand Building in Higher Education: A Grounded Theory Investigation of the Impact of the ‘Positive-Visualization-Course in Brand Identity’ upon Freshmen Student's Perception
Authors: Maria Kountouridou, Dino Domic
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Within an increasingly competitive and dynamic environment, the higher education sector is becoming more commodified, with the concept of branding to become exceedingly imperative and an inextricable ingredient for the university’s success. Branding in higher education has proven to be an effective strategy that managed to receive considerable attention in the recent few years, and a growing number of articles have begun to appear in the literature. However, a clear void in the literature confirms that the concept of students’ perceptions towards the university’s brand image has not been researched extensively. An investigation on this central concept is of paramount importance since it will facilitate the development of an inductively generated theoretical model concerning branding in higher education. This research focuses on examining the impact of the ‘positive-visualization-course in brand identity’ upon the perception of freshmen students towards a university’s brand image. A grounded theory methodology has been selected, consisting of semi-structured interviews. Forty-two students have participated in the research, among which twenty-five women and seventeen men. The identification of the sample emerged through the use of the snowball sampling technique. The participants were divided into two groups (experimental and control group) after the researcher had taken into consideration the factor ‘program of study’, to eliminate any possible interaction between the participants of each group. An experiment was carried out where a ‘positive-visualization-course in brand identity’ was conducted among the participants of the experimental group, while the participants of the control group have not been exposed to the course. For the purpose of this research, the term ‘positive-visualization-course in brand identity’ refers to a course where brand history, past achievements/recognitions/awards, its values, and its mission are presented. Prior to the course implementation, face-to-face semi-structured interviews were carried out among the participants of both groups, with the aim of examining the freshmen students’ perceptions towards the university’s brand image. One week after the course implementation, the researcher carried out semi-structured interviews with the participants of the experimental group only in order to identify whether students’ perceptions had been affected after the course completion. Four months after the course completion, semi-structured interviews were carried out among the participants of both groups. Eight months after the course completion, semi-structured interviews were conducted with the aim of identifying the freshmen students’ updated perceptions. Data has been analyzed using substantive coding (open and selective coding), theoretical coding, field memos, and constant comparative analysis. The findings strongly suggest that the ‘positive-visualization-course in brand identity’ can positively affect freshmen students’ perceptions towards a university’s brand image. Additionally, other factors conduce to the formation of perception throughout the months. This study contributes and expands upon the existing literature by presenting an inductively generated theoretical model to guide future research in the links between ‘positive-visualization-course in brand identity’ and the perception of freshmen students towards a university’s brand image.Keywords: brand image, brand name, branding, higher education marketing, perception
Procedia PDF Downloads 1731862 Frequency of Occurrence Hybrid Watermarking Scheme
Authors: Hamza A. Ali, Adnan H. M. Al-Helali
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Generally, a watermark is information that identifies the ownership of multimedia (text, image, audio or video files). It is achieved by introducing modifications into these files that are imperceptible to the human senses but easily recoverable by a computer program. These modifications are done according to a secret key in a descriptive model that would be either in the time domain or frequency domain or both. This paper presents a procedure for watermarking by mixing amplitude modulation with frequency transformation histogram; namely a specific value is used to modulate the intensity component Y of the YIQ components of the carrier image. This scheme is referred to as histogram embedding technique (HET). Results comparison with those of other techniques such as discrete wavelet transform (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD) have shown an enhance efficiency in terms of ease and performance. It has manifested a good degree of robustness against various environment effects such as resizing, rotation and different kinds of noise. This method would prove very useful technique for copyright protection and ownership judgment.Keywords: watermarking, ownership, copyright protection, steganography, information hiding, authentication
Procedia PDF Downloads 3631861 Spaces of Interpretation: Personal Space
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
Procedia PDF Downloads 971860 Utilization of Secure Wireless Networks as Environment for Learning and Teaching in Higher Education
Authors: Mohammed A. M. Ibrahim
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This paper investigate the utilization of wire and wireless networks to be platform for distributed educational monitoring system. Universities in developing countries suffer from a lot of shortages(staff, equipment, and finical budget) and optimal utilization of the wire and wireless network, so universities can mitigate some of the mentioned problems and avoid the problems that maybe humble the education processes in many universities by using our implementation of the examinations system as a test-bed to utilize the network as a solution to the shortages for academic staff in Taiz University. This paper selects a two areas first one quizzes activities is only a test bed application for wireless network learning environment system to be distributed among students. Second area is the features and the security of wireless, our tested application implemented in a promising area which is the use of WLAN in higher education for leering environment.Keywords: networking wire and wireless technology, wireless network security, distributed computing, algorithm, encryption and decryption
Procedia PDF Downloads 3291859 High Aspect Ratio Sio2 Capillary Based On Silicon Etching and Thermal Oxidation Process for Optical Modulator
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
Procedia PDF Downloads 4801858 Factor to Elicit Spatial Presence: Calmness
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
Procedia PDF Downloads 2811857 Performance Evaluation of Various Segmentation Techniques on MRI of Brain Tissue
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
Procedia PDF Downloads 3191856 Generalized π-Armendariz Authentication Cryptosystem
Authors: Areej M. Abduldaim, Nadia M. G. Al-Saidi
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Algebra is one of the important fields of mathematics. It concerns with the study and manipulation of mathematical symbols. It also concerns with the study of abstractions such as groups, rings, and fields. Due to the development of these abstractions, it is extended to consider other structures, such as vectors, matrices, and polynomials, which are non-numerical objects. Computer algebra is the implementation of algebraic methods as algorithms and computer programs. Recently, many algebraic cryptosystem protocols are based on non-commutative algebraic structures, such as authentication, key exchange, and encryption-decryption processes are adopted. Cryptography is the science that aimed at sending the information through public channels in such a way that only an authorized recipient can read it. Ring theory is the most attractive category of algebra in the area of cryptography. In this paper, we employ the algebraic structure called skew -Armendariz rings to design a neoteric algorithm for zero knowledge proof. The proposed protocol is established and illustrated through numerical example, and its soundness and completeness are proved.Keywords: cryptosystem, identification, skew π-Armendariz rings, skew polynomial rings, zero knowledge protocol
Procedia PDF Downloads 2051855 The Mediating Effects of Student Satisfaction on the Relationship Between Organisational Image, Service Quality and Students’ Loyalty in Higher Education Institutions in Kano State, Nigeria
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
Procedia PDF Downloads 601854 Investigation of Detectability of Orbital Objects/Debris in Geostationary Earth Orbit by Microwave Kinetic Inductance Detectors
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
Procedia PDF Downloads 861853 Analysis of Lightweight Register Hardware Threat
Authors: Yang Luo, Beibei Wang
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In this paper, we present a design methodology of lightweight register transfer level (RTL) hardware threat implemented based on a MAX II FPGA platform. The dynamic power consumed by the toggling of the various bit of registers as well as the dynamic power consumed per unit of logic circuits were analyzed. The hardware threat was designed taking advantage of the differences in dynamic power consumed per unit of logic circuits to hide the transfer information. The experiment result shows that the register hardware threat was successfully implemented by using different dynamic power consumed per unit of logic circuits to hide the key information of DES encryption module. It needs more than 100000 sample curves to reduce the background noise by comparing the sample space when it completely meets the time alignment requirement. In additional, an external trigger signal is playing a very important role to detect the hardware threat in this experiment.Keywords: side-channel analysis, hardware Trojan, register transfer level, dynamic power
Procedia PDF Downloads 2721852 Research on the Overall Protection of Historical Cities Based on the 'City Image' in Ancient Maps: Take the Ancient City of Shipu, Zhejiang, China as an Example
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
Procedia PDF Downloads 1181851 2D Convolutional Networks for Automatic Segmentation of Knee Cartilage in 3D MRI
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
Procedia PDF Downloads 2501850 Adaptive Motion Compensated Spatial Temporal Filter of Colonoscopy Video
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
Procedia PDF Downloads 1071849 Limbic Involvement in Visual Processing
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
Procedia PDF Downloads 741848 Mobile Microscope for the Detection of Pathogenic Cells Using Image Processing
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
Procedia PDF Downloads 2571847 Targeting Mineral Resources of the Upper Benue trough, Northeastern Nigeria Using Linear Spectral Unmixing
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
Procedia PDF Downloads 3621846 The Cognitive Perspective on Arabic Spatial Preposition ‘Ala
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
Procedia PDF Downloads 1411845 PUF-Based Lightweight Iot Secure Authentication Chip Design
Authors: Wenxuan Li, Lei Li, Jin Li, Yuanhang He
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This paper designed a secure chip for IoT communication security integrated with the PUF-based firmware protection scheme. Then, the Xilinx Kintex-7 and STM-32 were used for the prototype verification. Firmware protection worked well on FPGA and embedded platforms. For the ASIC implementation of the PUF module, contact PUF is chosen. The post-processing method and its improvement are analyzed with emphasis. This paper proposed a more efficient post-processing method for contact PUF named SXOR, which has practical value for realizing lightweight security modules in IoT devices. The analysis was carried out under the hypothesis that the contact holes are independent and combine the existing data in the open literature. The post-processing effects of SXOR and XOR are basically the same under the condition that the proposed post-processing circuit occupies only 50.6% of the area of XOR. The average Hamming weight of the PUF output bit sequence obtained by the proposed post-processing method is 0.499735, and the average Hamming weight obtained by the XOR-based post-processing method is 0.499999.Keywords: PUF, IoT, authentication, secure communication, encryption, XOR
Procedia PDF Downloads 1311844 A Comprehensive Study of Camouflaged Object Detection Using Deep Learning
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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