Search results for: visual image

Authors: Mohamed Salaheldien Mohamed Alayat, Ahmed Mohamed Elsoudany, Roaa Abdulghani Sroge, Bayan Muteb Aldhahwani

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Background: Neck pain is a common illness that could affect individual’s daily activities. Class IV laser with longer wavelength can stimulate tissues and penetrate more than the classic low-level laser therapy. Objectives: The aim of the study was to investigate the efficacy of class IV diode laser in the treatment of patients with chronic neck pain (CNP). Methods: Fifty-two patients participated and completed the study. Their mean age (SD) was 50.7 (6.2). Patients were randomized into two groups and treated with laser plus exercise (laser + EX) group and placebo laser plus exercise (PL+EX) group. Treatment was performed by Class IV laser in two phases; scanning and trigger point phases. Scanning to the posterior neck and shoulder girdle region with 4 J/cm2 with a total energy of 300 J applied to 75 cm2 in 4 minutes and 16 seconds. Eight trigger points on the posterior neck area were treated by 4 J/cm2 and the time of application was in 30 seconds. Both groups received exercise two times per week for 4 weeks. Exercises included range of motion, isometric, stretching, isotonic resisted exercises to the cervical extensors, lateral bending and rotators muscles with postural correction exercises. The measured variables were pain level using visual analogue scale (VAS), and neck functional activity using neck disability index (NDI) score. Measurements were taken at baseline and after 4 weeks of treatment. The level of statistical significance was set as p < 0.05. Results: There were significant decreases in post-treatment VAS and NDI in both groups as compared to baseline values. Laser + EX effectively decreased VAS (mean difference -6.5, p = 0.01) and NDI scores after (mean difference -41.3, p = 0.01) 4 weeks of treatment compared to PL + EX. Conclusion: Class IV laser combined with exercise is effective treatment for patients with CNP as compared to PL + EX therapy. The combination of laser + EX effectively increased functional activity and reduced pain after 4 weeks of treatment.

Keywords: chronic neck pain, class IV laser, exercises, neck disability index, visual analogue scale

Procedia PDF Downloads 307

Authors: Sophia Shi

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Acute kidney injury (AKI) is the sudden onset of kidney damage in which the kidneys cannot filter waste from the blood, requiring emergency hospitalization. AKI patient mortality rate is high in the ICU and is virtually impossible for doctors to predict because it is so unexpected. Currently, there is no hybrid model predicting AKI that takes advantage of two types of data. De-identified patient data from the MIMIC-III database and de-identified kidney images and corresponding patient records from the Beijing Hospital of the Ministry of Health were collected. Using data features including serum creatinine among others, two numeric models using MIMIC and Beijing Hospital data were built, and with the hospital ultrasounds, an image-only model was built. Convolutional neural networks (CNN) were used, VGG and Resnet for numeric data and Resnet for image data, and they were combined into a hybrid model by concatenating feature maps of both types of models to create a new input. This input enters another CNN block and then two fully connected layers, ending in a binary output after running through Softmax and additional code. The hybrid model successfully predicted AKI and the highest AUROC of the model was 0.953, achieving an accuracy of 90% and F1-score of 0.91. This model can be implemented into urgent clinical settings such as the ICU and aid doctors by assessing the risk of AKI shortly after the patient’s admission to the ICU, so that doctors can take preventative measures and diminish mortality risks and severe kidney damage.

Keywords: Acute kidney injury, Convolutional neural network, Hybrid deep learning, Patient record data, ResNet, Ultrasound kidney images, VGG

Procedia PDF Downloads 129

Authors: Afsha Shaikh, Mohammed Azizur Rahman, Ibrahim Hassan, Mayur Pal

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Student engagement in learning is instantly affected by the sources of learning methods available for them, such as videos showing the applications of the concept or showing a practical demonstration. Specific to the engineering discipline, there exist enormous challenging concepts that can be simplified when they are connected to real-world scenarios. For this study, the concept of heat exchangers was used as it is a part of multidisciplinary engineering fields. To make the learning experience enjoyable and impactful, 3-D printed heat exchanger models were created for students to use while working on in-class activities and assignments. Students were encouraged to use the 3-D printed heat exchanger models to enhance their understanding of theoretical concepts associated with its applications. To assess the effectiveness of the method, feedback was received by students pursuing undergraduate engineering via an anonymous electronic survey. To make the feedback more realistic, unbiased, and genuine, students spent nearly two to three weeks using the models in their in-class assignments. The impact of these tools on their learning was assessed through their performance in their ungraded assignments as well as their interactive discussions with peers. ‘Having to apply the theory learned in class whilst discussing with peers on a class assignment creates a relaxed and stress-free learning environment in classrooms’; this feedback was received by more than half the students who took the survey and found 3-D models of heat exchanger very easy to use. Amongst many ways to enhance learning and make students more engaged through interactive models, this study sheds light on the importance of physical tools that help create a lasting mental representation in the minds of students. Moreover, in this technologically enhanced era, the concept of augmented reality was considered in this research. E-drawings application was recommended to enhance the vision of engineering students so they can see multiple views of the detailed 3-D models and cut through its different sides and angles to visualize it properly. E-drawings could be the next tool to implement in classrooms to enhance students’ understanding of engineering concepts.

Keywords: student engagement, life-long-learning, visual demonstration, 3-D printed models, engineering education

Procedia PDF Downloads 111

Authors: Muhammad Ather Nadeem, Bilal Ahmad Khan, Tasawer Abbas

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Nanoherbicides utilize nanotechnology to enhance the delivery of biological or chemical herbicides using combinations of nanomaterials. The aim of this research was to examine the efficacy of chitosan nanoparticles containing MCPA herbicide as a potential eco-friendly alternative for weed control in wheat crops. Scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), and ultraviolet absorbance were used to analyze the developed nanoparticles. The SEM analysis indicated that the average size of the particles was 35 nm, forming clusters with a porous structure. Both nanoparticles of fluroxyper + MCPA exhibited maximal absorption peaks at a wavelength of 320 nm. The compound fluroxyper +MCPA has a strong peak at a 2θ value of 30.55°, which correlates to the 78 plane of the anatase phase. The weeds, including Chenopodium album, Lathyrus aphaca, Angalis arvensis, and Melilotus indica, were sprayed with the nanoparticles while they were in the third or fourth leaf stage. There were seven distinct dosages used: doses (D0 (Check weeds), D1 (Recommended dose of traditional herbicide, D2 (Recommended dose of Nano-herbicide (NPs-H)), D3 (NPs-H with 05-fold lower dose), D4 ((NPs-H) with 10-fold lower dose), D5 (NPs-H with 15-fold lower dose), and D6 (NPs-H with 20-fold lower dose)). The chitosan-based nanoparticles of MCPA at the prescribed dosage of conventional herbicide resulted in complete death and visual damage, with a 100% fatality rate. The dosage that was 5-fold lower exhibited the lowest levels of plant height (3.95 cm), chlorophyll content (5.63%), dry biomass (0.10 g), and fresh biomass (0.33 g) in the broad-leaved weed of wheat. The herbicide nanoparticles, when used at a dosage 10-fold lower than that of conventional herbicides, had a comparable impact on the prescribed dosage. Nano-herbicides have the potential to improve the efficiency of standard herbicides by increasing stability and lowering toxicity.

Keywords: mortality, visual injury, chlorophyl contents, chitosan-based nanoparticles

Procedia PDF Downloads 62

Authors: Marina Shurupova, Victor Anisimov, Alexander Latanov

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Background: The cerebellar lesions inevitably provoke oculomotor impairments in patients of different age. Symptoms of subtentorial tumors, particularly medulloblastomas, include static and dynamic coordination disorders (ataxia, asynergia, imbalance), hypo-muscle tonus, disruption of the cranial nerves, and within the oculomotor system - nystagmus (fine or gross). Subtentorial tumors can also affect the areas of cerebellum that control the oculomotor system. The noninvasive eye-tracking technology allows obtaining multiple oculomotor characteristics such as the number of fixations and their duration, amplitude, latency and velocity of saccades, trajectory and scan path of gaze during the process of the visual field navigation. Eye tracking could be very useful in clinical studies serving as convenient and effective tool for diagnostics. The aim: We studied the dynamics of oculomotor system functioning in patients undergoing remission from cerebellar tumors removal surgeries and following neurocognitive rehabilitation. Methods: 38 children (23 boys, 15 girls, 9-17 years old) that have recovered from the cerebellar tumor-removal surgeries, radiation therapy and chemotherapy and were undergoing course of neurocognitive rehabilitation participated in the study. Two tests were carried out to evaluate oculomotor performance - gaze stability test and counting test. The monocular eye movements were recorded with eye tracker ArringtonResearch (60 Hz). Two experimental sessions with both tests were conducted before and after rehabilitation courses. Results: Within the final session of both tests we observed remarkable improvement in oculomotor performance: 1) in the gaze stability test the spread of gaze positions significantly declined compared to the first session, and 2) the visual path in counting test significantly shortened both compared to the first session. Thus, neurocognitive rehabilitation improved the functioning of the oculomotor system in patients following the cerebellar tumor removal surgeries and subsequent therapy. Conclusions: The experimental data support the effectiveness of the utilization of the eye tracking technique as diagnostic tool in the field of neurooncology.

Keywords: eye tracking, rehabilitation, cerebellar tumors, oculomotor system

Procedia PDF Downloads 156

Authors: Mawloud Mosbah, Bachir Boucheham

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Color Histogram is considered as the oldest method used by CBIR systems for indexing images. In turn, the global histograms do not include the spatial information; this is why the other techniques coming later have attempted to encounter this limitation by involving the segmentation task as a preprocessing step. The weak segmentation is employed by the local histograms while other methods as CCV (Color Coherent Vector) are based on strong segmentation. The indexation based on local histograms consists of splitting the image into N overlapping blocks or sub-regions, and then the histogram of each block is computed. The dissimilarity between two images is reduced, as consequence, to compute the distance between the N local histograms of the both images resulting then in N*N values; generally, the lowest value is taken into account to rank images, that means that the lowest value is that which helps to designate which sub-region utilized to index images of the collection being asked. In this paper, we make under light the local histogram indexation method in the hope to compare the results obtained against those given by the global histogram. We address also another noteworthy issue when Relying on local histograms namely which value, among N*N values, to trust on when comparing images, in other words, which sub-region among the N*N sub-regions on which we base to index images. Based on the results achieved here, it seems that relying on the local histograms, which needs to pose an extra overhead on the system by involving another preprocessing step naming segmentation, does not necessary mean that it produces better results. In addition to that, we have proposed here some ideas to select the local histogram on which we rely on to encode the image rather than relying on the local histogram having lowest distance with the query histograms.

Keywords: CBIR, color global histogram, color local histogram, weak segmentation, Euclidean distance

Procedia PDF Downloads 356

Authors: S. Sadallah

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In this paper, dynamic programming is used to determine the optimal management of financial resources in company. Solution of the problem by consider into simpler substructures is constructed. The optimal management of internal capital of company are simulated. The tools applied in this development are based on graph theory. The software of given problems is built by using greedy algorithm. The obtained model and program maintenance enable us to define the optimal version of management of proper financial flows by using visual diagram on each level of investment.

Keywords: management, software, optimal, greedy algorithm, graph-diagram

Procedia PDF Downloads 279

Authors: Shariful Islam, Sharun Akter Khushbu, S. M. Shaqib, Shahriar Sultan Ramit

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In the construction sector, ensuring worker safety is of the utmost significance. In this study, a deep learning-based technique is presented for identifying safety gear worn by construction workers, such as helmets, goggles, jackets, gloves, and footwear. The suggested method precisely locates these safety items by using the YOLO v7 (You Only Look Once) object detection algorithm. The dataset utilized in this work consists of labeled images split into training, testing and validation sets. Each image has bounding box labels that indicate where the safety equipment is located within the image. The model is trained to identify and categorize the safety equipment based on the labeled dataset through an iterative training approach. We used custom dataset to train this model. Our trained model performed admirably well, with good precision, recall, and F1-score for safety equipment recognition. Also, the model's evaluation produced encouraging results, with a [email protected] score of 87.7%. The model performs effectively, making it possible to quickly identify safety equipment violations on building sites. A thorough evaluation of the outcomes reveals the model's advantages and points up potential areas for development. By offering an automatic and trustworthy method for safety equipment detection, this research contributes to the fields of computer vision and workplace safety. The proposed deep learning-based approach will increase safety compliance and reduce the risk of accidents in the construction industry.

Keywords: deep learning, safety equipment detection, YOLOv7, computer vision, workplace safety

Procedia PDF Downloads 63

Authors: Roni Naor-Hofri

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This paper shows how self-inflicted pain enabled the expression of love for God among Christian monastic ascetics in medieval central Europe. As scholars have shown, being in a state of pain leads to a change in or destruction of language, an essential feature of the self. The author argues that this transformation allows the self to transcend its boundaries as an object, even if only temporarily and in part. The epistemic achievement of love for God, a non-object, would not otherwise have been possible. To substantiate her argument, the author shows that the self’s transformation into a non-object enables the imitation of God: not solely in the sense of imitatio Christi, of physical and visual representations of God incarnate in the flesh of His son Christ, but also in the sense of the self’s experience of being a non-object, just like God, the target of the self’s love.

Keywords: love for God , pain, philosophy, religion

Procedia PDF Downloads 242

Authors: T. Vijayashree, A. Gopal

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The aim of the work is to classify and authenticate medicinal plant materials and herbs widely used for Indian herbal medicinal preparation. The quality and authenticity of these raw materials are to be ensured for the preparation of herbal medicines. These raw materials are to be carefully screened, analyzed and documented due to mistaken of look-alike materials which do not have medicinal characteristics.

Keywords: authenticity, standardization, principal component analysis, imaging processing, signal processing

Procedia PDF Downloads 239

Authors: K. Doi, T. Nishimura, H. Fujimoto, T. Tanaka

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It has been known that visually impaired persons have some problems in getting visual information. Therefore, information accessibility for the visually impaired persons is very important in a current information society. Some application software with read-aloud function for using personal computer and smartphone are getting more and more popular among visually impaired persons in the world. On the other hand, it is also very important for being able to learn how to read and write characters such as Braille and Visual character. Braille typewriter has been widely used in learning Braille. And also raised-line drawing kits as writing material has been used for decades for especially acquired visually impaired persons. However, there are some drawbacks such as the drawn line cannot be erased. Moreover, visibility of drawing lines is not so good for visually impaired with low vision. We had significant number of requests for developing new writing material for especially acquired visually impaired persons instead of raised-line drawing kits. For conducting development research of novel writing material, we could receive a research grant from ministry of health, labor and welfare in Japanese government. In this research, we developed writing material typed pens and pencils with Beeswax-discharge instead of conventional raised-line drawing kits. This writing material was equipped with cartridge heater for melting beeswax and its heat controller. When this pen users held down the pen tip on the regular paper such as fine paper and so on, the melted beeswax could be discharged from pen tip with valve structure. The beeswax was discharged at 100 gf of holding down force based on results of our previous trial study. The shape of pen tip was semispherical for becoming low friction between pen tip and surface of paper. We conducted one basic experiment to evaluate influence of the curvature of pen tip on ease to write. Concretely, the conditions of curvature was 0.15, 0.35, 0.50, 1.00 mm. The following four interval scales were used as indexes of subjective assessment during writing such as feeling of smooth motion of pen, feeling of comfortable writing, sense of security and feeling of writing fatigue. Ten subjects were asked to participate in this experiment. The results reveal that subjects could draw easily when the radius of the pen tip was 1.00 mm, and lines drawn with beeswax-discharge writing material were easy to perceive.

Keywords: beeswax-discharge writing material, raised-line drawing kits, visually impaired persons, pen tip

Procedia PDF Downloads 306

Authors: Anna Bak-Klimek, Emily Spencer, Siew Lee, Karen Campbell, Wendy McInally

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Background & Significance: Over half of Teenagers and Young Adults (TYAs) say that they experience psychological distress after cancer diagnosis and TYAs with cancer are at higher risk of developing distress compared to other age groups. Despite this there are no age-appropriate interventions to help TYAs manage distress and there is a lack of conceptual understanding of what causes distress in this population group. This makes it difficult to design a targeted, developmentally appropriate intervention. This review aims to identify the key determinants of distress in TYAs affected by cancer and to propose an integrative model of cancer-related distress for TYAs. Method: A literature search was performed in Cochrane Database of Systematic Reviews, MEDLINE, PsycINFO, CINAHL, EMBASE and PsycArticles in May-June, 2022. Quantitative literature was systematically reviewed on the relationship between psychological distress experienced by TYAs affected by cancer and a wide range of factors i.e. individual (demographic, psychological, developmental, and clinical factors) and contextual (social/environmental) factors. Evidence was synthesized and correlates were categorized using the Biopsychosocial Model. The full protocol is available from PROSPERO (CRD42022322069) Results: Thirty eligible quantitative studies met criteria for the review. A total of twenty-six studies were cross-sectional, three were longitudinal and one study was a case control study. The evidence on the relationship between the socio-demographic, illness and treatment-related factors and psychological distress is inconsistent and unclear. There is however consistent evidence on the link between psychological factors and psychological distress. For instance, the use of cognitive and defence coping, negative meta-cognitive beliefs, less optimism, a lack of sense of meaning and lower resilience levels were significantly associated with higher psychological distress. Furthermore, developmental factors such as poor self-image, identity issues and perceived conflict were strongly associated with higher distress levels. Conclusions: The current review suggests that psychological and developmental factors such as ineffective coping strategies, poor self-image and identity issues may play a key role in the development of psychological distress in TYAs affected by cancer. The review proposes a Positive Developmental Psychology Model of Distress for Teenagers and Young Adults affected by cancer. The review highlights that implementation of psychological interventions that foster optimism, improve resilience and address self-image may result in reduced distress in TYA’s with cancer.

Keywords: cancer, determinant, psychological distress, teenager and young adult, theoretical model

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Authors: A. Raj Kumar, S. Bilaloglu

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Stroke is a leading cause of adult disability worldwide. We depend on our hands for our activities of daily living(ADL). Although many patients regain the ability to walk, they continue to experience long-term hand motor impairments. As the number of individuals with young stroke is increasing, there is a critical need for effective approaches for rehabilitation of hand function post-stroke. Motor relearning for dexterity requires task-specific kinesthetic, tactile and visual feedback. However, when a stroke results in both sensory and motor impairment, it becomes difficult to ascertain when and what type of sensory substitutions can facilitate motor relearning. In an ideal situation, real-time task-specific data on the ability to learn and data-driven feedback to assist such learning will greatly assist rehabilitation for dexterity. We have found that kinesthetic and tactile information from the unaffected hand can assist patients re-learn the use of optimal fingertip forces during a grasp and lift task. Measurement of fingertip grip force (GF), load forces (LF), their corresponding rates (GFR and LFR), and other metrics can be used to gauge the impairment level and progress during learning. Currently ATI mini force-torque sensors are used in research settings to measure and compute the LF, GF, and their rates while grasping objects of different weights and textures. Use of the ATI sensor is cost prohibitive for deployment in clinical or at-home rehabilitation. A cost effective mechatronic device is developed to quantify GF, LF, and their rates for stroke rehabilitation purposes using off-the-shelf components such as load cells, flexi-force sensors, and an Arduino UNO microcontroller. A salient feature of the device is its integration with an interactive gaming environment to render a highly engaging user experience. This paper elaborates the integration of kinesthetic and tactile sensing through computation of LF, GF and their corresponding rates in real time, information processing, and interactive interfacing through augmented reality for visual feedback.

Keywords: feedback, gaming, kinesthetic, rehabilitation, tactile

Procedia PDF Downloads 238

Authors: Prodipta Bhowmik, Poulami Saha, Preety Mehra, Yogesh Soni, Triloki Nath Jha

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In India, the smart city concept is growing day by day. So, for smart city development, a better traffic management and monitoring system is a very important requirement. Nowadays, road accidents increase due to more vehicles on the road. Reckless driving is mainly responsible for a huge number of accidents. So, an efficient traffic management system is required for all kinds of roads to control the traffic speed. The speed limit varies from road to road basis. Previously, there was a radar system but due to high cost and less precision, the radar system is unable to become favorable in a traffic management system. Traffic management system faces different types of problems every day and it has become a researchable topic on how to solve this problem. This paper proposed a computer vision and machine learning-based automated system for multiple vehicle detection, tracking, and speed estimation of vehicles using image processing. Detection of vehicles and estimating their speed from a real-time video is tough work to do. The objective of this paper is to detect vehicles and estimate their speed as accurately as possible. So for this, a real-time video is first captured, then the frames are extracted from that video, then from that frames, the vehicles are detected, and thereafter, the tracking of vehicles starts, and finally, the speed of the moving vehicles is estimated. The goal of this method is to develop a cost-friendly system that can able to detect multiple types of vehicles at the same time.

Keywords: OpenCV, Haar Cascade classifier, DLIB, YOLOV3, centroid tracker, vehicle detection, vehicle tracking, vehicle speed estimation, computer vision

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Authors: Montserrat Crespi Vallbona, Marta Domínguez Pérez

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Globalization impacts on cities and especially on their centers, especially on those spaces more visible and coveted. Changes are involved in processes such as touristification, gentrification or studentification, in addition of shop trendiness. The city becomes a good of interchange rather than a communal good for its inhabitants and consequently, its value is monetized. So, these different tendencies are analyzed: on one hand, the presence of tourists, the home rental increase, the explosion of businesses related to tourism; on the other hand; the return of middle classes or gentries to the center in a socio-spatial model that has changed highlighting the centers by their culture and their opportunities as well as by the value of public space and centrality; then, the interest of students (national and international) to be part of these city centers as dynamic groups and emerging classes with a higher purchasing power and better cultural capital than in the past; and finally, the conversion of old stores into modern ones, where vintage trend and the renewal of antiquity is the essence. All these transforming processes impact the European cities and redefine their image. All these trends reinforce the impression and brand of the urban center as an attractive space for investment, keeping such nonsense meaningful. These four tendencies have been spreading correlatively impacting the centers and transforming them involving the displacement of former residents of these spaces and revitalizing the center that is financed and commercialized in parallel. The cases of Madrid and Barcelona as spaces of greater evidence in Spain of these tendencies serve to illustrate these processes and represent the spearhead. Useful recommendations are presented to urban planners to find the conciliation of communal and commercialized spaces.

Keywords: gentrification, shop trendiness, studentification, touristification

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Authors: Natalia Pacheco Rego

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The Liezation functor is a map from the category of Leibniz algebras to the category of Lie algebras, which assigns a Leibniz algebra to the Lie algebra given by the quotient of the Leibniz algebra by the ideal spanned by the square elements of the Leibniz algebra. This functor is left adjoint to the inclusion functor that considers a Lie algebra as a Leibniz algebra. This environment fits in the framework of central extensions and commutators in semi-abelian categories with respect to a Birkhoff subcategory, where classical or absolute notions are relative to the abelianization functor. Classical properties of Leibniz algebras (properties relative to the abelianization functor) were adapted to the relative setting (with respect to the Liezation functor); in general, absolute properties have the corresponding relative ones, but not all absolute properties immediately hold in the relative case, so new requirements are needed. Following this line of research, it was conducted an analysis of central derivations of Leibniz algebras relative to the Liezation functor, called as Lie-derivations, and a characterization of Lie-stem Leibniz algebras by their Lie-central derivations was obtained. In this paper, we present an overview of these results, and we analyze some new properties concerning Lie-central derivations and almost inner Lie-derivations. Namely, a Leibniz algebra is a vector space equipped with a bilinear bracket operation satisfying the Leibniz identity. We define the Lie-bracket by [x, y]lie = [x, y] + [y, x] , for all x, y . The Lie-center of a Leibniz algebra is the two-sided ideal of elements that annihilate all the elements in the Leibniz algebra through the Lie-bracket. A Lie-derivation is a linear map which acts as a derivative with respect to the Lie-bracket. Obviously, usual derivations are Lie-derivations, but the converse is not true in general. A Lie-derivation is called a Lie-central derivation if its image is contained in the Lie-center. A Lie-derivation is called an almost inner Lie-derivation if the image of an element x is contained in the Lie-commutator of x and the Leibniz algebra. The main results we present in this talk refer to the conditions under which Lie-central derivation and almost inner Lie-derivations coincide.

Keywords: almost inner Lie-derivation, Lie-center, Lie-central derivation, Lie-derivation

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Authors: Francisco Pedroza-Montero, Jesús Naín Pedroza-Montero, Diego Soto-Puebla, Osiris Alvarez-Bajo, Beatriz Castaneda, Sofía Navarro-Espinoza, Martín Pedroza-Montero

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Nanodiamonds have been widely studied for their physical properties, including chemical inertness, biocompatibility, optical transparency from the ultraviolet to the infrared region, high thermal conductivity, and mechanical strength. In this work, we studied how the fluorescence spectrum of nanodiamonds quenches concerning the concentration in aqueous solutions systematically ranging from 0.1 to 10 mg/mL. Our results demonstrated a non-linear fluorescence quenching as the concentration increases for both of the NV zero-phonon lines; the 5 mg/mL concentration shows the maximum fluorescence emission. Furthermore, this behaviour is theoretically explained as an electronic recombination process that modulates the intensity in the NV centres. Finally, to gain more insight, the FRET methodology is used to determine the fluorescence efficiency in terms of the fluorophores' separation distance. Thus, the concentration level is simulated as follows, a small distance between nanodiamonds would be considered a highly concentrated system, whereas a large distance would mean a low concentrated one. Although the 5 mg/mL concentration shows the maximum intensity, our main interest is focused on the concentration of 0.5 mg/mL, which our studies demonstrate the optimal human cell viability (99%). In this respect, this concentration has the feature of being as biocompatible as water giving the possibility to internalize it in cells without harming the living media. To this end, not only can we track nanodiamonds on the surface or inside the cell with excellent precision due to their fluorescent intensity, but also, we can perform thermometry tests transforming a fluorescence contrast image into a temperature contrast image.

Keywords: nanodiamonds, fluorescence spectroscopy, concentration, bioimaging, thermometry

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Authors: Yingwei Hou, Tao Liu, Yong Pang

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The paper explored the three-dimensional deformation of mussel plaques anchor to wet polydimethylsiloxane (PDMS) substrates under tension stress with different angles. Mussel plaques exhibiting natural adhesive structures, have attracted significant attention for their remarkable adhesion properties. Understanding their behavior under mechanical stress, particularly in a three-dimensional context, holds immense relevance for biomimetic material design and bio-inspired adhesive development. This study employed a novel approach to investigate the 3D deformation of the PDMS substrates anchored by mussel plaques subjected to controlled tension. Utilizing our customized stereo digital image correlation technique and mechanical mechanics analyses, we found the distributions of the displacement and resultant force on the substrate became concentrated under the plaque. Adhesion and sucking mechanisms were analyzed for the mussel plaque-substrate system under tension until detachment. The experimental findings were compared with a developed model using finite element analysis and the results provide new insights into mussels’ attachment mechanism. This research not only contributes to the fundamental understanding of biological adhesion but also holds promising implications for the design of innovative adhesive materials with applications in fields such as medical adhesives, underwater technologies, and industrial bonding. The comprehensive exploration of mussel plaque behavior in three dimensions is important for advancements in biomimicry and materials science, fostering the development of adhesives that emulate nature's efficiency.

Keywords: adhesion mechanism, mytilus edulis, mussel plaque, stereo digital image correlation

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Authors: Tsega Asresa, Getahun Tigistu, Melaku Bayih

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Computer vision is a subfield of artificial intelligence that allows computers and systems to extract meaning from digital images and video. It is used in a wide range of fields of study, including self-driving cars, video surveillance, medical diagnosis, manufacturing, law, agriculture, quality control, health care, facial recognition, and military applications. Aromatic medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, essential oils, decoration, cleaning, and other natural health products for therapeutic and Aromatic culinary purposes. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs but also going to export for valuable foreign currency exchange. In Ethiopia, there is a lack of technologies for the classification and identification of Aromatic medicinal plant parts and disease type cured by aromatic medicinal plants. Farmers, industry personnel, academicians, and pharmacists find it difficult to identify plant parts and disease types cured by plants before ingredient extraction in the laboratory. Manual plant identification is a time-consuming, labor-intensive, and lengthy process. To alleviate these challenges, few studies have been conducted in the area to address these issues. One way to overcome these problems is to develop a deep learning model for efficient identification of Aromatic medicinal plant parts with their corresponding disease type. The objective of the proposed study is to identify the aromatic medicinal plant parts and their disease type classification using computer vision technology. Therefore, this research initiated a model for the classification of aromatic medicinal plant parts and their disease type by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides roots, flowers, fruits, and latex. For this study, the researcher used RGB leaf images with a size of 128x128 x3. In this study, the researchers trained five cutting-edge models: convolutional neural network, Inception V3, Residual Neural Network, Mobile Network, and Visual Geometry Group. Those models were chosen after a comprehensive review of the best-performing models. The 80/20 percentage split is used to evaluate the model, and classification metrics are used to compare models. The pre-trained Inception V3 model outperforms well, with training and validation accuracy of 99.8% and 98.7%, respectively.

Keywords: aromatic medicinal plant, computer vision, convolutional neural network, deep learning, plant classification, residual neural network

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Authors: Sung Uk Ryu, Byoung Gook Jeon, Sung-Jae Yi, Dong-Jin Euh

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In such passive safety injection systems in the nuclear power plant as Core Makeup Tank (CMT) and Hybrid Safety Injection Tank, various thermal-hydraulic phenomena including the direct contact condensation of steam and the thermal stratification of coolant occur. These phenomena are also closely related to the performance of the system. Depending on the condensation rate of the steam injected to the tank, the injection of the coolant and pressure equalizing timings of the tank are decided. The steam injected to the tank from the upper nozzle penetrates the coolant and induces a direct contact condensation. In the present study, the direct contact condensation of steam and the thermal mixing between the steam and coolant were examined by using the Particle Image Velocimetry (PIV) technique. Especially, by altering the size of the nozzle from which the steam is injected, the influence of steam injection velocity on the thermal mixing with coolant and condensation shall be comprehended, while also investigating the influence of condensation on the pressure variation inside the tank. Even though the amounts of steam inserted were the same in three different nozzle size conditions, it was found that the velocity of pressure rise becomes lower as the steam injection area decreases. Also, as the steam injection area increases, the thickness of the zone within which the coolant’s temperature decreases. Thereby, the amount of steam condensed by the direct contact condensation also decreases. The results derived from the present study can be utilized for the detailed design of a passive safety injection system, as well as for modeling the direct contact condensation triggered by the steam jet’s penetration into the coolant.

Keywords: passive safety injection systems, steam penetration, direct contact condensation, particle image velocimetry

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Authors: Monapat Sasingha, Suttisak Soralump

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This research presents the behavior of slope of the road along the canal stabilized by short piles. In this investigation, the centrifuge machine was used, modelling the condition of the water levels in the canal. The centrifuge tests were performed at 35 g. To observe the movement of the soil, visual analysis was performed to evaluate the failure behavior. Conclusively, the use of short piles to stabilize the canal slope proved to be an effective solution. However, the certain amount of settlement was found behind the short pile rows.

Keywords: centrifuge test, slope failure, embankment, stability of slope

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Authors: Hsiao-Chuan Huang, King-Lung Kuo, Mei-Hsin Lo, Hsiao-Yun Chou, Yusen Lin

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The most robust and economical method for laboratory diagnosis of TB is to identify mycobacterial bacilli (AFB) under acid-fast staining despite its disadvantages of low sensitivity and labor-intensive. Though digital pathology becomes popular in medicine, an automated microscopic system for microbiology is still not available. A new AI-assisted automated microscopic system, consisting of a microscopic scanner and recognition program powered by big data and deep learning, may significantly increase the sensitivity of TB smear microscopy. Thus, the objective is to evaluate such an automatic system for the identification of AFB. A total of 5,930 smears was enrolled for this study. An intelligent microscope system (TB-Scan, Wellgen Medical, Taiwan) was used for microscopic image scanning and AFB detection. 272 AFB smears were used for transfer learning to increase the accuracy. Referee medical technicians were used as Gold Standard for result discrepancy. Results showed that, under a total of 1726 AFB smears, the automated system's accuracy, sensitivity and specificity were 95.6% (1,650/1,726), 87.7% (57/65), and 95.9% (1,593/1,661), respectively. Compared to culture, the sensitivity for human technicians was only 33.8% (38/142); however, the automated system can achieve 74.6% (106/142), which is significantly higher than human technicians, and this is the first of such an automated microscope system for TB smear testing in a controlled trial. This automated system could achieve higher TB smear sensitivity and laboratory efficiency and may complement molecular methods (eg. GeneXpert) to reduce the total cost for TB control. Furthermore, such an automated system is capable of remote access by the internet and can be deployed in the area with limited medical resources.

Keywords: TB smears, automated microscope, artificial intelligence, medical imaging

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Authors: Sergio Tovar-Pérez, Sebastian Töpfer, Markus Gräfe

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The work proposes a technique that decreases the detection acquisition time of quantum holography schemes down to one-third; this allows the possibility to image moving objects. Since its invention, quantum holography with undetected photon schemes has gained interest in the scientific community. This is mainly due to its ability to tailor the detected wavelengths according to the needs of the scheme implementation. Yet this wavelength flexibility grants the scheme a wide range of possible applications; an important matter was yet to be addressed. Since the scheme uses digital phase-shifting techniques to retrieve the information of the object out of the interference pattern, it is necessary to acquire a set of at least four images of the interference pattern along with well-defined phase steps to recover the full object information. Hence, the imaging method requires larger acquisition times to produce well-resolved images. As a consequence, the measurement of moving objects remains out of the reach of the imaging scheme. This work presents the use and implementation of a spatial light modulator along with a digital holographic technique called quasi-parallel phase-shifting. This technique uses the spatial light modulator to build a structured phase image consisting of a chessboard pattern containing the different phase steps for digitally calculating the object information. Depending on the reduction in the number of needed frames, the acquisition time reduces by a significant factor. This technique opens the door to the implementation of the scheme for moving objects. In particular, the application of this scheme in imaging alive specimens comes one step closer.

Keywords: quasi-parallel phase shifting, quantum imaging, quantum holography, quantum metrology

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Authors: Giorgi Methodishvili, Iuliia Methodishvili

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In this paper product development algorithm is used to determine the optimal management of financial resources in company. Aspects of financial management considered include put initial investment, examine all possible ways to solve the problem and the optimal rotation length of profit. The software of given problems is based using greedy algorithm. The obtained model and program maintenance enable us to define the optimal version of management of proper financial flows by using visual diagram on each level of investment.

Keywords: management, software, optimal, greedy algorithm, graph-diagram

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Authors: Mehrdad Shafiei Dizaji, Hoda Azari

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The research explores the pioneering integration of Physics-Informed Neural Networks (PINNs) into the domain of Ground-Penetrating Radar (GPR) data prediction, akin to advancements in medical imaging for tracking tumor progression in the human body. This research presents a detailed development framework for a specialized PINN model proficient at interpreting and forecasting GPR data, much like how medical imaging models predict tumor behavior. By harnessing the synergy between deep learning algorithms and the physical laws governing subsurface structures—or, in medical terms, human tissues—the model effectively embeds the physics of electromagnetic wave propagation into its architecture. This ensures that predictions not only align with fundamental physical principles but also mirror the precision needed in medical diagnostics for detecting and monitoring tumors. The suggested deep learning structure comprises three components: a CNN, a spatial feature channel attention (SFCA) mechanism, and ConvLSTM, along with temporal feature frame attention (TFFA) modules. The attention mechanism computes channel attention and temporal attention weights using self-adaptation, thereby fine-tuning the visual and temporal feature responses to extract the most pertinent and significant visual and temporal features. By integrating physics directly into the neural network, our model has shown enhanced accuracy in forecasting GPR data. This improvement is vital for conducting effective assessments of bridge deck conditions and other evaluations related to civil infrastructure. The use of Physics-Informed Neural Networks (PINNs) has demonstrated the potential to transform the field of Non-Destructive Evaluation (NDE) by enhancing the precision of infrastructure deterioration predictions. Moreover, it offers a deeper insight into the fundamental mechanisms of deterioration, viewed through the prism of physics-based models.

Keywords: physics-informed neural networks, deep learning, ground-penetrating radar (GPR), NDE, ConvLSTM, physics, data driven

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Authors: M. Saba, A. Iaaly, E. Carlier, N. Georges

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This research focuses on assessing the ground water quality of Northern Lebanon affected by saline water intrusion. The chemical, physical and microbiological parameters were collected in various seasons spanning over the period of two years. Results were assessed using Geographic Information System (GIS) due to its visual capabilities in presenting the pollution extent in the studied region. Future projections of the excessive pumping were also simulated using GIS in order to assess the extent of the problem of saline intrusion in the near future.

Keywords: GIS, saline water, quality control, drinkable water quality standards, pumping

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Authors: Chitralekha Ngangbam, Aniruddha Mondal, Naorem Khelchand Singh

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Aluminium (Al) doped In2O3 (Indium Oxide) nanocolumn array was synthesized by glancing angle deposition (GLAD) technique on Si (n-type) substrate for photodetector application. The sample was characterized by scanning electron microscopy (SEM). The average diameter of the nanocolumn was calculated from the top view of the SEM image and found to be ∼80 nm. The length of the nanocolumn (~500 nm) was calculated from cross sectional SEM image and it shows that the nanocolumns are perpendicular to the substrate. The EDX analysis confirmed the presence of Al (Aluminium), In (Indium), O (Oxygen) elements in the samples. The XRD patterns of the Al-doped In2O3 nanocolumn show the presence of different phases of the Al doped In2O3 nanocolumn i.e. (222) and (622). Three different peaks were observed from the PL analysis of Al doped In2O3 nanocolumn at 365 nm, 415 nm and 435 nm respectively. The peak at PL emission at 365 nm can be attributed to the near band gap transition of In2O3 whereas the peaks at 415 nm and 435 nm can be attributed to the trap state emissions due to oxygen vacancies and oxygen–indium vacancy centre in Al doped In2O3 nanocolumn. The current-voltage (I–V) characteristics of the Al doped In2O3 nanocolumn based detector was measured through the Au Schottky contact. The devices were then examined under the halogen light (20 W) illumination for photocurrent measurement. The Al-doped In2O3 nanocolumn based optical detector showed high conductivity and low turn on voltage at 0.69 V under white light illumination. A maximum photoresponsivity of 82 A/W at 380 nm was observed for the device. The device shows a high internal gain of ~267 at UV region (380 nm) and ∼127 at visible region (760 nm). Also the rise time and fall time for the device at 650 nm is 0.15 and 0.16 sec respectively which makes it suitable for fast response detector.

Keywords: glancing angle deposition, nanocolumn, semiconductor, photodetector, indium oxide

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Authors: Chiara Cosentino, Carlo Pruneti, Carla Merisio, Domenico Sgromo

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Introduction – Psychoneuroimmunology as approach clearly showed how psychological features can influence health through specific physiological pathways linked to the stress reaction. This can be true also in cancer, in its latter conceptualization seen as a chronic disease. Therefore, it is still not clear how the psychological features can combine with a physiological specific path, for a better adjustment to cancer. The aim of this study is identifying how in Italian survivors, perceived social support, body image, coping and quality of life correlate with or influence Heart Rate Variability (HRV), the physiological parameter that can mirror a condition of chronic stress or a good relaxing capability. Method - The study had an exploratory transversal design. The final sample was made of 38 ovarian cancer survivors aged from 29 to 80 (M= 56,08; SD=12,76) following a program for Ovarian Cancer at the Oncological Clinic, University Hospital of Parma, Italy. Participants were asked to fill: Multidimensional Scale of Perceived Social Support (MSPSS); Derridford Appearance Scale-59 (DAS-59); Mental Adjustment to Cancer (MAC); Quality of Life Questionnaire (EORTC). For each participant was recorded Short-Term HRV (5 minutes) using emWavePro. Results– Data showed many interesting correlations within the psychological features. EORTC scores have a significant correlation with DAS-59 (r =-.327 p <.05), MSPSS (r =.411 p<.05), and MAC scores, in particular with the strategy Fatalism (r =.364 p<.05). A good social support improves HRV (F(1,33)= 4.27 p<.05). Perceiving themselves as effective in their environment, preserving a good role functioning (EORTC), positively affects HRV (F(1,33)=9.810 p<.001). Women admitting concerns towards body image seem prone to emotive disclosure, reducing emotional distress and improving HRV (β=.453); emotional avoidance worsens HRV (β=-.391). Discussion and conclusion - Results showed a strong relationship between body image and Quality of Life. These data suggest that higher concerns on body image, in particular, the negative self-concept linked to appearance, was linked to the worst functioning in everyday life. The relation between the negative self-concept and a reduction in emotional functioning is understandable in terms of possible distress deriving from the perception of body appearance. The relationship between a high perceived social support and a better functioning in everyday life was also confirmed. In this sample fatalism, was associated with a better physical, role and emotional functioning. In these women, the presence of a good support may activate the physiological Social Engagement System improving their HRV. Perceiving themselves effective in their environment, preserving a good role functioning, also positively affects HRV, probably following the same physiological pathway. A higher presence of concerns about appearance contributes to a higher HRV. Probably women admitting more body concerns are prone to a better emotive disclosure. This could reduce emotional distress improving HRV and global health. This study reached preliminary demonstration of an ‘Integrated Model of Defense’ in these cancer survivors. In these model, psychological features interact building a better quality of life and a condition of psychological well-being that is associated and influence HRV, then the physiological condition.

Keywords: cancer survivors, heart rate variability, ovarian cancer, psychophysiological adjustment

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Authors: Thomas Vlasak, Tanja Dujlociv, Alfred Barth

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Shift work is an essential element of modern labor, ensuring ideal conditions of service for today’s economy and society. Despite the beneficial properties, its impact on the neurobehavioral performance of exposed subjects remains controversial. This meta-analysis aims to provide first summarizing the effects regarding the association between shift work exposure and different cognitive functions. A literature search was performed via the databases PubMed, PsyINFO, PsyARTICLES, MedLine, PsycNET and Scopus including eligible studies until December 2020 that compared shift workers with non-shift workers regarding neurobehavioral performance tests. A random-effects model was carried out using Hedge’s g as a meta-analytical effect size with a restricted likelihood estimator to summarize the mean differences between the exposure group and controls. The heterogeneity of effect sizes was addressed by a sensitivity analysis using funnel plots, egger’s tests, p-curve analysis, meta-regressions, and subgroup analysis. The meta-analysis included 18 studies resulting in a total sample of 18,802 participants and 37 effect sizes concerning six different neurobehavioral outcomes. The results showed significantly worse performance in shift workers compared to non-shift workers in the following cognitive functions with g (95% CI): processing speed 0.16 (0.02 - 0.30), working memory 0.28 (0.51 - 0.50), psychomotor vigilance 0.21 (0.05 - 0.37), cognitive control 0.86 (0.45 - 1.27) and visual attention 0.19 (0.11 - 0.26). Neither significant moderating effects of publication year or study quality nor significant subgroup differences regarding type of shift or type of profession were indicated for the cognitive outcomes. These are the first meta-analytical findings that associate shift work with decreased cognitive performance in processing speed, working memory, psychomotor vigilance, cognitive control, and visual attention. Further studies should focus on a more homogenous measurement of cognitive functions, a precise assessment of experience of shift work and occupation types which are underrepresented in the current literature (e.g., law enforcement). In occupations where shift work is fundamental (e.g., healthcare, industries, law enforcement), protective countermeasures should be promoted for workers.

Keywords: meta-analysis, neurobehavioral performance, occupational psychology, shift work

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Authors: S. M. Ishtiaque, V. K. Yadav, S. D. Joshi, J. K. Chatterjee

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The DIAMETRIC FAULTS system has been developed that captures a bi-directional image of yarn continuously in sequentially manner and provides the detailed classification of faults. A novel mathematical framework developed on the acquired bi-directional images forms the basis of fault classification in four broad categories, namely, Thick1, Thick2, Thin and Normal Yarn. A discretised version of Radon transformation has been used to convert the bi-directional images into one-dimensional signals. Images were divided into training and test sample sets. Karhunen–Loève Transformation (KLT) basis is computed for the signals from the images in training set for each fault class taking top six highest energy eigen vectors. The fault class of the test image is identified by taking the Euclidean distance of its signal from its projection on the KLT basis for each sample realization and fault class in the training set. Euclidean distance applied using various techniques is used for classifying an unknown fault class. An accuracy of about 90% is achieved in detecting the correct fault class using the various techniques. The four broad fault classes were further sub classified in four sub groups based on the user set boundary limits for fault length and fault volume. The fault cross-sectional area and the fault length defines the total volume of fault. A distinct distribution of faults is found in terms of their volume and physical dimensions which can be used for monitoring the yarn faults. It has been shown from the configurational based characterization and classification that the spun yarn faults arising out of mass variation, exhibit distinct characteristics in terms of their contours, sizes and shapes apart from their frequency of occurrences.

Keywords: Euclidean distance, fault classification, KLT, Radon Transform

Procedia PDF Downloads 259