Search results for: image processing

Authors: Nada Farhani, Naim Terbeh, Mounir Zrigui

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The recognition of the objects contained in images has always presented a challenge in the field of research because of several difficulties that the researcher can envisage because of the variability of shape, position, contrast of objects, etc. In this paper, we will be interested in the recognition of objects. The classical Hough Transform (HT) presented a tool for detecting straight line segments in images. The technique of HT has been generalized (GHT) for the detection of arbitrary forms. With GHT, the forms sought are not necessarily defined analytically but rather by a particular silhouette. For more precision, we proposed to combine the results from the GHT with the results from a calculation of similarity between the histograms and the spatiograms of the images. The main purpose of our work is to use the concepts from recognition to generate sentences in Arabic that summarize the content of the image.

Keywords: recognition of shape, generalized hough transformation, histogram, spatiogram, learning

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Authors: Atin Mukherjee, Amitabha Sinha, Debesh Choudhury

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Fast Fourier transform (FFT) of large-number of samples requires larger hardware resources of field programmable gate arrays and it asks for more area as well as power. In this paper, an area efficient architecture of FFT processor is proposed, that reuses the butterfly units more than once. The FFT processor is emulated and the results are validated on Virtex-6 FPGA. The proposed architecture outperforms the conventional architecture of a N-point FFT processor in terms of area which is reduced by a factor of log_N(2) with the negligible increase of processing time.

Keywords: FFT, FPGA, resource optimization, butterfly units

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Authors: Chollawat Pookpienlert, Jintana Sanwong

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An element a of a semigroup S is called left (right) regular if there exists x in S such that a=xa² (a=a²x) and said to be intra-regular if there exist u,v in such that a=ua²v. Let T(X) be the semigroup of all full transformations on a set X under the composition of maps. For a fixed nonempty subset Y of X, let Fix(X,Y)={α ™ T(X) : yα=y for all y ™ Y}, where yα is the image of y under α. Then Fix(X,Y) is a semigroup of full transformations on X which fix all elements in Y. Here, we characterize left regular, right regular and intra-regular elements of Fix(X,Y) which characterizations are shown as follows: For α ™ Fix(X,Y), (i) α is left regular if and only if Xα\Y = Xα²\Y, (ii) α is right regular if and only if πα = πα², (iii) α is intra-regular if and only if | Xα\Y | = | Xα²\Y | such that Xα = {xα : x ™ X} and πα = {xα⁻¹ : x ™ Xα} in which xα⁻¹ = {a ™ X : aα=x}. Moreover, those regularities are equivalent if Xα\Y is a finite set. In addition, we count the number of those elements of Fix(X,Y) when X is a finite set. Finally, we determine the maximal congruence ρ on Fix(X,Y) when X is finite and Y is a nonempty proper subset of X. If we let | X \Y | = n, then we obtain that ρ = (Fixn x Fixn) ∪ (H ε x H ε) where Fixn = {α ™ Fix(X,Y) : | Xα\Y | < n} and H ε is the group of units of Fix(X,Y). Furthermore, we show that the maximal congruence is unique.

Keywords: intra-regular, left regular, maximal congruence, right regular, transformation semigroup

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Authors: Anteneh Getachew Gebrie, Rabian Wangkeeree

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The purpose of this paper is to introduce iterative algorithm solving split system of minimization problem given as a task of finding a common minimizer point of finite family of proper, lower semicontinuous convex functions and whose image under a bounded linear operator is also common minimizer point of another finite family of proper, lower semicontinuous convex functions. We obtain strong convergence of the sequence generated by our algorithm under some suitable conditions on the parameters. The iterative schemes are developed with a way of selecting the step sizes such that the information of operator norm is not necessary. Some applications and numerical experiment is given to analyse the efficiency of our algorithm.

Keywords: Hilbert Space, minimization problems, Moreau-Yosida approximate, split feasibility problem

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Authors: A. B. Bazaralieva, A. A. Turgumbayeva

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The phytosubstance from garlic was obtained by extraction with liquid carbon dioxide under critical conditions. Methods of processing raw materials are proposed, and the chemical composition of garlic is studied by gas chromatography and mass spectrometry. The garlic extract's composition was determined using gas chromatography (GC) and gas chromatography-mass spectrophotometry (GC-MS). The phytosubstance had 54 constituents. The extract included the following main compounds: Manool (39.56%), Viridifrolol (7%), Podocarpa-1,8,11,13-tetraen-3-one, 14-isopropyl-1,13-dimethoxy- 5,15 percent, (+)-2-Bornanone (4.29%), Thujone (3.49%), Linolic acid ethyl ester (3.41%), and 12-O-Methylcarn.

Keywords: Allium sativum, bioactive compounds of garlic, carbon dioxide extraction of garlic, GS-MS method

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Authors: Salehi Zahabi Saleh, Rajabi Hosaien, Rasaneh Samira

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Yttrium-90 (90Y) radioembolisation(RE) is increasingly used for the treatment of patients with unresectable primary or metastatic liver tumours. Image-based approaches to assess microsphere distribution after RE have gained interest but are mostly hampered by the limited imaging possibilities of the Isotope 90Y. Quantitative 90Y-SPECT imaging has limited spatial resolution because it is based on 90Y Bremsstrahlung whereas 90Y-PET has better spatial resolution but low sensitivity. As a consequence, new alternative methods of visualizing the microspheres have been investigated, such as MR imaging of iron-labelled microspheres. It was also shown that MRI combines high sensitivity with high spatial and temporal resolution and with superior soft tissue contrast and thus can be used to cover a broad range of clinically interesting imaging parameters.The aim of the study in this article was to investigate the capability of MRI to measure the intrahepatic microsphere distribution in order to quantify the absorbed radiation dose in RE.

Keywords: radioembolisation, MRI, imaging, dosimetry

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Authors: Miguel Contreras, David Long, Will Bachman

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Background: Microscopy plays a central role in cell and developmental biology. In particular, fluorescence microscopy can be used to visualize specific cellular components and subsequently quantify their morphology through development of virtual-cell models for study of effects of mechanical forces on cells. However, there are challenges with these imaging experiments, which can make it difficult to quantify cell morphology: inconsistent results, time-consuming and potentially costly protocols, and limitation on number of labels due to spectral overlap. To address these challenges, the objective of this project is to develop an automatic computational machine learning pipeline to predict cellular components morphology for virtual-cell generation based on fluorescence cell membrane confocal z-stacks. Methods: Registered confocal z-stacks of nuclei and cell membrane of endothelial cells, consisting of 20 images each, were obtained from fluorescence confocal microscopy and normalized through software pipeline for each image to have a mean pixel intensity value of 0.5. An open source machine learning algorithm, originally developed to predict fluorescence labels on unlabeled transmitted light microscopy cell images, was trained using this set of normalized z-stacks on a single CPU machine. Through transfer learning, the algorithm used knowledge acquired from its previous training sessions to learn the new task. Once trained, the algorithm was used to predict morphology of nuclei using normalized cell membrane fluorescence images as input. Predictions were compared to the ground truth fluorescence nuclei images. Results: After one week of training, using one cell membrane z-stack (20 images) and corresponding nuclei label, results showed qualitatively good predictions on training set. The algorithm was able to accurately predict nuclei locations as well as shape when fed only fluorescence membrane images. Similar training sessions with improved membrane image quality, including clear lining and shape of the membrane, clearly showing the boundaries of each cell, proportionally improved nuclei predictions, reducing errors relative to ground truth. Discussion: These results show the potential of pre-trained machine learning algorithms to predict cell morphology using relatively small amounts of data and training time, eliminating the need of using multiple labels in immunofluorescence experiments. With further training, the algorithm is expected to predict different labels (e.g., focal-adhesion sites, cytoskeleton), which can be added to the automatic machine learning pipeline for direct input into Principal Component Analysis (PCA) for generation of virtual-cell mechanical models.

Keywords: cell morphology prediction, computational machine learning, fluorescence microscopy, virtual-cell models

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Authors: Li Xiaoge, Wang Chaodong

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We introduce the first Chinese Coreference Resolution Model based on BERT (CCRM-BERT) and show that it significantly outperforms all previous work. The key idea is to consider the features of the mention, such as part of speech, width of spans, distance between spans, etc. And the influence of each features on the model is analyzed. The model computes mention embeddings that combine BERT with features. Compared to the existing state-of-the-art span-ranking approach, our model significantly improves accuracy on the Chinese OntoNotes benchmark.

Keywords: BERT, coreference resolution, deep learning, nature language processing

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Authors: Ali Arshad

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The study examines the depiction of women characters in Urdu and Punjabi films. It is a critical evaluation of forty-eight Pakistani films. It explores the characters of women portrays in Urdu and Punjabi film of Pakistan. Using content analysis as methodology with feminist research that helps to investigate the phenomena and supports the study. Finding of the study shows that women characters in Urdu and Punjabi films are not the reflection of true Pakistani women rather this picture represents a negative image of Pakistani women in viewers mind. These characters don’t address the women’s issues nor do they present the solutions to these problems faced by Pakistani women. The characters of Pakistani women are not free from male prejudice, and these films do not portray the social and political role perform by actual Pakistani women. The analysis shows that the characters of women in Urdu and Punjabi films are based on the assumptions.

Keywords: women, Pakistani, film, characters

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Authors: Carolina Brandão Piva

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In our visual culture, images play a newly significant role in the basis of a complex dialogue between imagination, creativity, and social practice. Insofar as imagination has broken out of the 'special expressive space of art' to become a part of the quotidian mental work of ordinary people, it is pertinent to recognize that visual representation can no longer be assumed as if in a domain detached from everyday life or exclusively 'centered' within the limited frame of 'art history.' The approach of Visual Culture as a field of study is, in this sense, indispensable to comprehend that not only 'the image,' but also 'the imagined' and 'the imaginary' are produced in the plurality of social interactions; crucial enough, this assertion directs us to something new in contemporary cultural processes, namely both imagination and image production constitute a social practice. This paper starts off with this approach and seeks to examine the artistic practice of two women from the State of Goiás, Brazil, who are ordinary citizens with their daily activities and narratives but also dedicated to visuality production. With no formal training from art schools, branded or otherwise, Maria Aparecida de Souza Pires deploys 'waste disposal' of daily life—from car tires to old work clothes—as a trampoline for art; also adept at sourcing raw materials collected from her surroundings, she manipulates raw hewn wood, tree trunks, plant life, and various other pieces she collects from nature giving them new meaning and possibility. Hilda Freire works with sculptures in clay using different scales and styles; her art focuses on representations of women and pays homage to unprivileged groups such as the practitioners of African-Brazilian religions, blue-collar workers, poor live-in housekeepers, and so forth. Although they have never been acknowledged by any mainstream art institution in Brazil, whose 'criterion of value' still favors formally trained artists, Maria Aparecida de Souza Pires, and Hilda Freire have produced visualities that instigate 'new ways of seeing,' meriting cultural significance in many ways. Their artworks neither descend from a 'traditional' medium nor depend on 'canonical viewing settings' of visual representation; rather, they consist in producing relationships with the world which do not result in 'seeing more,' but 'at least differently.' From this perspective, the paper finally demonstrates that grouping this kind of artistic production under the label of 'mere craft' has much more to do with who is privileged within the fields of power in art system, who we see and who we do not see, and whose imagination of what is fed by which visual images in Brazilian contemporary society.

Keywords: visual culture, artistic practice, women's art in the Brazilian State of Goiás, Maria Aparecida de Souza Pires, Hilda Freire

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Authors: Sujui Yang, Peeraya Somsak, Markus Blut

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This research examines the international tourists in Chiang Mai, Thailand. It aims to study non-Thai tourists’ of this region to better understand their behavior and motives influencing the choice of cultural heritage tourists in Chiang Mai, Thailand. The data includes questionnaires of 250 tourists in the study area. The most important motives influencing decisions choices are several concerning customers’ perspectives on tourist destinations in cultural heritage in Chiang Mai province. Thai tourists in Chiang Mai are single, 72.5 percent are in the age of 21-40 years old and 50% of sample group are from central and northern of Thailand. Tourists’ motives capture the factor loading as well as the corresponding show 5 components: relaxation motives, place/ physical motives, learning motives, image motives, and achievement motives.

Keywords: tourists motives, cultural heritage, Chiang Mai, customers’ perspectives

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Authors: Dalibor Štys, Kryštof M. Stys, Maryia Chkalova, Petr Kouba, Aliaxandr Pautsina, Dalibor Štys Jr., Jana Pečenková, Denis Durniev, Tomáš Náhlík, Petr Císař

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In this article, a construction and some properties of the 5iD viewer, the system recording simultaneously five views of a given experimental object is reported. Properties of the system are demonstrated on the analysis of fish schooling behavior. It is demonstrated the method of instrument calibration which allows inclusion of image distortion and it is proposed and partly tested also the method of distance assessment in the case that only two opposite cameras are available. Finally, we demonstrate how the state trajectory of the behavior of the fish school may be constructed from the entropy of the system.

Keywords: 3D positioning, school behavior, distance calibration, space vision, space distortion

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Authors: Thuvanan Borvornvitchotikarn, Werasak Kurutach

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Mutual information (MI) is widely used in medical image registration. In the different medical images analysis, it is difficult to choose an optimal bins size number for calculating the probability distributions in MI. As the result, this paper presents a new adaptive bins number selection approach that named a hybrid EMPCA-Scott approach. This work combines an expectation maximization principal component analysis (EMPCA) and the modified Scott’s rule. The proposed approach solves the binning problem from the various intensity values in medical images. Experimental results of this work show the lower registration errors compared to other adaptive binning approaches.

Keywords: mutual information, EMPCA, Scott, probability distributions

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Authors: N. Zoghi, Laleh Maleknia , M. E. Olya

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The nano-Cu particles were produced on cotton fabric substrate by ink-jet printing technology with water-soluble ink, which was based on copper. The surface tension and viscosity of the prepared inks were evaluated. The ink-jet printing process was repeated 1, 3, and 5 times in order to evaluate variations in the optical properties by changing thickness of printed film. Following initial drying of the printed film, the samples were annealed at different temperatures (150 °C, 200 °C and 250 °C) to determine the optimum temperature for the parameters set out in this experiment. The prepared nano-Cu particles were characterized by XRD and UV spectroscopy. The appearance of printed image and the nano-Cu particles morphology were observed by SEM. The results demonstrated that the ink-jet printing technology can be used to produce nano-particles on the cotton fabrics surface.

Keywords: ink-jet printing, nano-cu, fabric ink, in situ production, cotton fabric, water-soluble ink, morphology

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Authors: Jiahe Liu, Hongyang Yu, Feng Qian, Miao Luo, Linhang Zhu

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This study proposed a 3D human body reconstruction method, which integrates multi-view joint information into a set of joints and processes it with a parametric human body template. Firstly, we obtained human body image information captured from multiple perspectives. The multi-view information can avoid self-occlusion and occlusion problems during the reconstruction process. Then, we used the MvP algorithm to integrate multi-view joint information into a set of joints. Next, we used the parametric human body template SMPL-X to obtain more accurate three-dimensional human body reconstruction results. Compared with the traditional single-view parametric human body template reconstruction, this method significantly improved the accuracy and stability of the reconstruction.

Keywords: parametric human body templates, reconstruction of the human body, multi-view, joint

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Authors: Robert Poenaru, Mihail Pleşa

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In this work, a solution that addresses the protection of pre-trained neural networks is developed: Singularization. This method involves applying permutations to the weight matrices of a pre-trained model, introducing a form of structured noise that obscures the original model’s architecture. These permutations make it difficult for an attacker to reconstruct the original model, even if the permuted weights are obtained. Experimental benchmarks indicate that the application of singularization has a profound impact on model performance, often degrading it to the point where retraining from scratch becomes necessary to recover functionality, which is particularly effective for securing intellectual property in neural networks. Moreover, unlike other approaches, singularization is lightweight and computationally efficient, which makes it well suited for resource-constrained environments. Our experiments also demonstrate that this technique performs efficiently in various image classification tasks, highlighting its broad applicability and practicality in real-world scenarios.

Keywords: machine learning, ANE, CNN, security

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Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan

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In this paper, the comparison between k-Nearest Neighbor (kNN) algorithms for classifying the 3D EEG model in brain balancing is presented. The EEG signal recording was conducted on 51 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, maximum PSD values were extracted as features from the model. There are three indexes for the balanced brain; index 3, index 4 and index 5. There are significant different of the EEG signals due to the brain balancing index (BBI). Alpha-α (8–13 Hz) and beta-β (13–30 Hz) were used as input signals for the classification model. The k-NN classification result is 88.46% accuracy. These results proved that k-NN can be used in order to predict the brain balancing application.

Keywords: power spectral density, 3D EEG model, brain balancing, kNN

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Authors: Bandar Alahmadi

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The fact that people tend to remember pictures better than texts, motivates researchers to develop graphical passwords as an alternative to textual passwords. Graphical passwords as such were introduced as a possible alternative to traditional text passwords, in which users prove their identity by clicking on pictures rather than typing alphanumerical text. In this paper, we present a scheme for graphical passwords that are resistant to shoulder surfing attacks and spyware attacks. The proposed scheme introduces a clicking technique to chosen images. First, the users choose a set of images, the images are then included in a grid where users can click in the cells around each image, the location of the click and the number of clicks are saved. As a result, the proposed scheme can be safe from shoulder surface and spyware attacks.

Keywords: security, password, authentication, attack, applications

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Authors: Won Jung

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In automotive, propeller shaft is the device for transferring power from engine to axle via transmission, and the slip yoke is one of the main parts in the component. Since the propeller shafts are subject to torsion and shear stress, they need to be strong enough to bear the stress. The purpose of this research is to improve the productivity of slip yoke for automotive propeller shaft. We present how to redesign the component that currently manufactured as a forged single body type. The research was focused on not only reducing processing time but insuring durability of the component simultaneously.

Keywords: automotive, propeller shaft, productivity, durability, slip yoke

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Authors: Veronika Sharok

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Research relevance on psychological determinants of risky behaviors is caused by high prevalence of such behaviors, particularly among youth. Risky sexual behavior, including unprotected and casual sex, frequent change of sexual partners, drug and alcohol use lead to negative social consequences and contribute to the spread of HIV infection and other sexually transmitted diseases. Data were obtained from 302 respondents aged 15-35 which were divided into 3 empirical groups: persons prone to risky sexual behavior, drug users and alcohol users; and 3 control groups: the individuals who are not prone to risky sexual behavior, persons who do not use drugs and the respondents who do not use alcohol. For processing, we used the following methods: Qualitative method for nominative data (Chi-squared test) and quantitative methods for metric data (student's t-test, Fisher's F-test, Pearson's r correlation test). Statistical processing was performed using Statistica 6.0 software. The study identifies two groups of factors that prevent risky behaviors. Internal factors, which include the moral and value attitudes; significance of existential values: love, life, self-actualization and search for the meaning of life; understanding independence as a responsibility for the freedom and ability to get attached to someone or something up to a point when this relationship starts restricting the freedom and becomes vital; awareness of risky behaviors as dangerous for the person and for others; self-acknowledgement. External factors (prevent risky behaviors in case of absence of the internal ones): absence of risky behaviors among friends and relatives; socio-demographic characteristics (middle class, marital status); awareness about the negative consequences of risky behaviors; inaccessibility to psychoactive substances. These factors are common for proneness to each type of risky behavior, because it usually caused by the same reasons. It should be noted that if prevention of risky behavior is based only on elimination of external factors, it is not as effective as it may be if we pay more attention to internal factors. The results obtained in the study can be used to develop training programs and activities for prevention of risky behaviors, for using values preventing such behaviors and promoting healthy lifestyle.

Keywords: existential values, prevention, psychological features, risky behavior

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Authors: Abdelkadir Elhaouari

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The priciest thing in human life since his birth is his freedom, basing on this idea, the conflict exists till now, the fight against oppression, injustice, tyranny and slavery, searching for freedom and political resistances, and this makes the freedom is deeply related to the defense for its existence all over years. This project attempts using any way to preserve this freedom, and building and maintaining bases and rules to organize this life. Appeal is a one of the most important method that human uses to protect his freedom, and we will mention in this thesis our attempt to clarify this aspect to the individual. We can say that the law does not know just one color or one logic, and is not based on one rule to be taken by heart, but the law is neutrality, the diversity, abstraction and diligence diversity. The penal law is a valued law and it deserves to be studied and searched more… so that to attempt to master it. Our thesis is just a brief explanation of an important point in this law, where we attempt to clarify and simplify the image to the normal person, so that he can preserve his rights, and we hope that we had succeeded to choose the right topic for that.

Keywords: appeal, penalization, judgement, criminal

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Authors: R. Burahee, B. Chassinat, T. de Laclos, A. Dépée, A. Sastim

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The purpose of this paper is to propose a solution to detect, predict and reconstitute rain drops in real time – during the night – using an embedded material with an infrared camera. To prevent the system from needing too high hardware resources, simple models are considered in a powerful image treatment algorithm reducing considerably calculation time in OpenCV software. Using a smart model – drops will be matched thanks to a process running through two consecutive pictures for implementing a sophisticated tracking system. With this system drops computed trajectory gives information for predicting their future location. Thanks to this technique, treatment part can be reduced. The hardware system composed by a Raspberry Pi is optimized to host efficiently this code for real time execution.

Keywords: reconstitution, prediction, detection, rain drop, real time, raspberry, infrared

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Authors: Devatha Kalyan Kumar, Aravindraj D., Sadathulla A.

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Big data are now rapidly expanding in all engineering and science and many other domains. The potential of large or massive data is undoubtedly significant, make sense to require new ways of thinking and learning techniques to address the various big data challenges. Machine learning is continuously unleashing its power in a wide range of applications. In this paper, the latest advances and advancements in the researches on machine learning for big data processing. First, the machine learning techniques methods in recent studies, such as deep learning, representation learning, transfer learning, active learning and distributed and parallel learning. Then focus on the challenges and possible solutions of machine learning for big data.

Keywords: active learning, big data, deep learning, machine learning

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Authors: Robert Lenzie

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Transcranial electrical stimulation (tES) is significant in the research literature. However, the effects of tES on brain activity are still poorly understood at the surface level, the Brodmann Area level, and the impact on neural networks. Using a method like electroencephalography (EEG) in conjunction with tES might make it possible to comprehend the brain response and mechanisms behind published observed alterations in more depth. Using a method to directly see the effect of tES on EEG may offer high temporal resolution data on the brain activity changes/modulations brought on by tES that correlate to various processing stages within the brain. This paper provides unpublished information on a cutting-edge methodology that may reveal details about the dynamics of how the human brain works beyond what is now achievable with existing methods.

Keywords: tACS, frequency, EEG, optimal

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Authors: Samineh Barmaki, Ville Jokinen, Esko Kankuri

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We report a microfluidic chip that can be used to modify the gaseous microenvironment of a cell-culture in ambient atmospheric conditions. The aim of the study is to show the cellular response to nitric oxide (NO) under hypoxic (oxygen < 5%) condition. Simultaneously targeting to hypoxic and nitric oxide will provide an opportunity for NO‑based therapeutics. Studies on cellular responses to lowered oxygen concentration or to gaseous mediators are usually carried out under a specific macro environment, such as hypoxia chambers, or with specific NO donor molecules that may have additional toxic effects. In our study, the chip consists of a microfluidic layer and a cell culture well, separated by a thin gas permeable polydimethylsiloxane (PDMS) membrane. The main design goal is to separate the gas oxygen scavenger and NO donor solutions, which are often toxic, from the cell media. Two different types of gas exchangers, titled 'pool' and 'meander' were tested. We find that the pool design allows us to reach a higher level of oxygen depletion than meander (24.32 ± 19.82 %vs -3.21 ± 8.81). Our microchip design can make the cells culture more simple and makes it easy to adapt existing cell culture protocols. Our first application is utilizing the chip to create hypoxic conditions on targeted areas of cell culture. In this study, oxygen scavenger sodium sulfite generates hypoxia and its effect on human embryonic kidney cells (HEK-293). The PDMS membrane was coated with fibronectin before initiating cell cultures, and the cells were grown for 48h on the chips before initiating the gas control experiments. The hypoxia experiments were performed by pumping of O₂-depleted H₂O into the microfluidic channel with a flow-rate of 0.5 ml/h. Image-iT® reagent as an oxygen level responser was mixed with HEK-293 cells. The fluorescent signal appears on cells stained with Image-iT® hypoxia reagent (after 6h of pumping oxygen-depleted H₂O through the microfluidic channel in pool area). The exposure to different levels of O₂ can be controlled by varying the thickness of the PDMS membrane. Recently, we improved the design of the microfluidic chip, which can control the microenvironment of two different gases at the same time. The hypoxic response was also improved from the new design of microchip. The cells were grown on the thin PDMS membrane for 30 hours, and with a flowrate of 0.1 ml/h; the oxygen scavenger was pumped into the microfluidic channel. We also show that by pumping sodium nitroprusside (SNP) as a nitric oxide donor activated under light and can generate nitric oxide on top of PDMS membrane. We are aiming to show cellular microenvironment response of HEK-293 cells to both nitric oxide (by pumping SNP) and hypoxia (by pumping oxygen scavenger solution) in separated channels in one microfluidic chip.

Keywords: hypoxia, nitric oxide, microenvironment, microfluidic chip, sodium nitroprusside, SNP

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Authors: Anocha Rojanapanich

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This research aimed to identify important factors that effect customer satisfaction in boutique hotels and the important factors effecting customer loyalty in returning to boutique hotels. Furthermore, this study also aimed to study demographics, which effect variable factors. Four hundred questionnaires were completed by customers of the boutique hotels. The descriptive statistics used in this paper were percentages, means, and standard deviation (S.D.), while hypothesis testing was done using T-test, Anova, Correlation and Regression to analyze the relationship among those factors. In terms of the purpose in staying, it was found that the largest respondent was for ‘leisure purposes’. While the frequency indicated that most of the customers who stayed ‘once’in the last two years in the hotels had less concern in the hotel’s image than other groups. For customer’s perceived value and income levels had an influence on customer perceived values in both functional value price and emotional value.

Keywords: boutique hotels, customer attitude, customer satisfaction, customer loyalty

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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: L. Chevez, A. Apaza, J. Rodriguez, R. Puga, H. Loro, Juan Z. Davalos

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Virtual Dimension (VD) procedure is used to analyze Hyperspectral Image (HIS) treatment-data in order to estimate the abundance of mineral components of a mining sample. Hyperspectral images coming from reflectance spectra (NIR region) are pre-treated using Standard Normal Variance (SNV) and Minimum Noise Fraction (MNF) methodologies. The endmember components are identified by the Simplex Growing Algorithm (SVG) and after adjusted to the reflectance spectra of reference-databases using Simulated Annealing (SA) methodology. The obtained abundance of minerals of the sample studied is very near to the ones obtained using XRD with a total relative error of 2%.

Keywords: hyperspectral imaging, minimum noise fraction, MNF, simplex growing algorithm, SGA, standard normal variance, SNV, virtual dimension, XRD

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Authors: Lakshmidevi Sreeramareddy, Komalpreet Kaur, Nane Pothier

Abstract:

Graphical-based passwords have existed for decades. Their major advantage is that they are easier to remember than an alphanumeric password. However, their disadvantage (especially recognition-based passwords) is the smaller password space, making them more vulnerable to brute force attacks. Graphical passwords are also highly susceptible to the shoulder-surfing effect. The gesture-based password method that we developed is a grid-free, template-free method. In this study, we evaluated the gesture-based passwords for usability and vulnerability. The results of the study are significant. We developed a gesture-based password application for data collection. Two modes of data collection were used: Creation mode and Replication mode. In creation mode (Session 1), users were asked to create six different passwords and reenter each password five times. In replication mode, users saw a password image created by some other user for a fixed duration of time. Three different duration timers, such as 5 seconds (Session 2), 10 seconds (Session 3), and 15 seconds (Session 4), were used to mimic the shoulder-surfing attack. After the timer expired, the password image was removed, and users were asked to replicate the password. There were 74, 57, 50, and 44 users participated in Session 1, Session 2, Session 3, and Session 4 respectfully. In this study, the machine learning algorithms have been applied to determine whether the person is a genuine user or an imposter based on the password entered. Five different machine learning algorithms were deployed to compare the performance in user authentication: namely, Decision Trees, Linear Discriminant Analysis, Naive Bayes Classifier, Support Vector Machines (SVMs) with Gaussian Radial Basis Kernel function, and K-Nearest Neighbor. Gesture-based password features vary from one entry to the next. It is difficult to distinguish between a creator and an intruder for authentication. For each password entered by the user, four features were extracted: password score, password length, password speed, and password size. All four features were normalized before being fed to a classifier. Three different classifiers were trained using data from all four sessions. Classifiers A, B, and C were trained and tested using data from the password creation session and the password replication with a timer of 5 seconds, 10 seconds, and 15 seconds, respectively. The classification accuracies for Classifier A using five ML algorithms are 72.5%, 71.3%, 71.9%, 74.4%, and 72.9%, respectively. The classification accuracies for Classifier B using five ML algorithms are 69.7%, 67.9%, 70.2%, 73.8%, and 71.2%, respectively. The classification accuracies for Classifier C using five ML algorithms are 68.1%, 64.9%, 68.4%, 71.5%, and 69.8%, respectively. SVMs with Gaussian Radial Basis Kernel outperform other ML algorithms for gesture-based password authentication. Results confirm that the shorter the duration of the shoulder-surfing attack, the higher the authentication accuracy. In conclusion, behavioral features extracted from the gesture-based passwords lead to less vulnerable user authentication.

Keywords: authentication, gesture-based passwords, machine learning algorithms, shoulder-surfing attacks, usability

Procedia PDF Downloads 107

Authors: Hae-Yeoun Lee

Abstract:

Reversible watermarking that not only protects the copyright but also preserve the original quality of the digital content have been intensively studied. In particular, the demand for reversible watermarking has increased. In this paper, we propose a reversible watermarking scheme based on interpolation-error shifting and error precompensation. The intensity of a pixel is interpolated from the intensities of neighbouring pixels, and the difference histogram between the interpolated and the original intensities is obtained and modified to embed the watermark message. By restoring the difference histogram, the embedded watermark is extracted and the original image is recovered by compensating for the interpolation error. The overflow and underflow are prevented by error precompensation. To show the performance of the method, the proposed algorithm is compared with other methods using various test images.

Keywords: reversible watermarking, high capacity, high quality, interpolated error shifting, error precompensation

Procedia PDF Downloads 322