Search results for: map labeling

Authors: Amelia Tero-Vescan, Camil-Eugen Vari, Laura Ciulea, Cristina Filip, Silvia Imre

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A HPLC –UV method for the identification of ephedrine (EPH), sibutramine (SB), yohimbine (Y) and caffeine (CF) was developed. Separation was performed on a Kromasil 100-RP8, 150 mm x 4.6 mm, 5 mm column equipped with a precolumn Kromasil RP 8. Mobile phase was a gradient of 80-35 % sodium dihydrogen phosphate pH=5 with NH4OH and acetonitrile over 15 minutes time of analysis. Based on the responses of 113 athletes about dietary supplements (DS) consumed for "fat burning" and weight loss which have a legal status in Romania, 28 supplements have been selected and investigated for their content in CF, Y, legal substances, and SB, EPH (prohibited substances in DS). The method allows quantitative determination of the four substances in a short analysis time and with minimum cost. The presence of SB and EPH in the analyzed DS was not detected while the content in CF and Y considering the dosage recommended by the manufacturer does not affect the health of the consumers. DS labeling (plant extracts with CF and Y content) allows manufacturers to avoid declaring correct and exact amounts per pharmaceutical form (pure CF or equivalent and Y, respectively).

Keywords: dietary supplements, sibutramine, ephedrine, yohimbine, caffeine, HPLC

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Authors: Alessandro Falconieri, Sara De Vincentiis, Vittoria Raffa

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Mechanical force regulates axonal growth, elongation and maturation processes. This force is opening new frontiers in the field, contributing to a general understanding of the mechanisms of axon growth that, in the past, was thought to be governed exclusively by the growth cone and its ability to influence axonal growth in response to chemical signals. A method recently developed in our laboratory allows, through the labeling of neurons with magnetic nanoparticles (MNPs) and the use of permanent magnets, to apply extremely low mechanical forces, similar to those generated endogenously by the growth cone or by the increase of body mass during the organism growth. We found that these extremely low forces strongly enhance the spontaneous axonal elongation rate as well as neuronal sprouting. Data obtained don’t exclude that local phenomena, such as local transport and local translation, may be involved. These new advances could shed new light on what happens when the cell is subjected to external mechanical forces, opening new interesting scenarios in the field of mechanobiology.

Keywords: axon, external mechanical forces, magnetic nanoparticles, mechanotransduction

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Authors: Afsaneh Ghorbanzadeh, Afshin Farahbakhsh, Zakieh Bayat

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The drug capsulation was used for release and targeted delivery in determined time, place and temperature or pH. The DOX nanocapsules were used to reduce and to minimize the unwanted side effects of drug. In this paper, the encapsulation methods of doxorubicin (DOX) and the labeling it by the magnetic core of iron (Fe3O4) has been studied. The Fe3O4 was conjugated with DOX via hydrazine bond. The solution was capsuled by the sensitive polymer of heat or pH such as chitosan-g-poly (N-isopropylacrylamide-co-N,N-dimethylacrylamide), dextran-g-poly(N-isopropylacrylamide-co-N,N-dimethylacrylamide) and mPEG-G2.5 PAMAM by hydrazine bond. The drug release was very slow at temperatures lower than 380°C. There was a rapid and controlled drug release at temperatures higher than 380°C. According to experiments, the use mPEG-G2.5PAMAM is the best method of DOX nanocapsules synthesis, because in this method, the drug delivery time to certain place is lower than other methods and the percentage of released drug is higher. The synthesized magnetic carrier system has potential applications in magnetic drug-targeting delivery and magnetic resonance imaging.

Keywords: drug carrier, drug release, doxorubicin, iron oxide NPs

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Authors: D. Pranav

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Pesticides are a class of Biocide, whose use in agriculture has led to a momentous increase in the yield of crops, fruits and vegetables all over the word and its effective use has also been the pillars of success for the Green Revolution. However, the incessant use of pesticides has now reached alarming levels. In 2007 alone, the world used an estimated 2.4 million tons of pesticides. Despite its tremendous benefits for agriculture, pesticide has been one of the major reasons for degradation of the natural environment and undesirable effects on human beings. It has not only caused damage to human health, but has also threatened the survival of few birds and animal species. In India, the sale and usage of banned pesticide, increased usage of pesticides and its inadequate labeling has caused Bio magnification, which is causing deleterious effects on child development, resulting in stunted mental and physical growth. This paper aims to bring to shed light on major loopholes in the current pesticide regulations such as the Insecticide Act of 1968. It further discusses loopholes in the yet to be tabled Pesticides Management Bill of 2008. It discusses and arrives at potential amendments to the laws and regulations concerning pesticides; that cannot only be applied to the Indian subcontinent but other developing countries as well.

Keywords: pesticides, India, human health, environment, regulations, reform

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Authors: Elizabeth Godwin Mahenge

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This study seeks to investigate the portrayal of albinism in Swahili literature. People with albinism have faced many life-threatening challenges, from being hunted for their body parts of being assigned derogatory names that depict them as ghosts as or less than humans. Many studies have been conducted on the perception of people towards Persons with Albinism [PWA] worldwide. Findings showed there is negative perception or negative portrayal of PWA in different societies worldwide. These negative connotations raised hot debates around the world among different societies and associations of/for PWA. People with disability in different parts of the world started arguing the labeling and name calling same applied to persons with disability in Tanzania (albinism included). They went the same debate about name calling hence in 2010, the Tanzanian Parliament passed the bill on Persons with Disability Act which banned derogative names attached to disability in general and to albinism in particular. In Tanzanian societies, there have been a mixed feelings with regards to albinism. Some do have negative perceptions because of the killings with connection to superstitious believes, while in other societies are perceived positively as blessed children a family. From these two contradictory perceptions that exist in this society, the study seeks to find out how Swahili literature portrays albinism.

Keywords: albinism, portrayal, disability, Kiswahili literature

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Authors: Ksenia Meshkova

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With increasing amount of multimedia data, it is very important to automate and speed up the process of obtaining meta. This process means not just recognition of some object or its movement, but recognition of the entire scene versus separate frames and having timeline segmentation as a final result. Labeling datasets is time consuming, besides, attributing characteristics to particular scenes is clearly difficult due to their nature. In this article, we will consider autoencoders application to unsupervised scene recognition and clusterization based on interpretable features. Further, we will focus on particular types of auto encoders that relevant to our study. We will take a look at the specificity of deep learning related to information theory and rate-distortion theory and describe the solutions empowering poor interpretability of deep learning in media content processing. As a conclusion, we will present the results of the work of custom framework, based on autoencoders, capable of scene recognition as was deeply studied above, with highlights generation resulted out of this recognition. We will not describe in detail the mathematical description of neural networks work but will clarify the necessary concepts and pay attention to important nuances.

Keywords: neural networks, computer vision, representation learning, autoencoders

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Authors: Mahmudjon Kuchkarov, Marufjon Kuchkarov

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The origin of ‘Human Language’ is still a secret and the most interesting subject of historical linguistics. The core element is the nature of labeling or coding the things or processes with symbols and sounds. In this paper, we investigate human’s involuntary Paired Sounds and Shape Production (PSSP) and its contribution to the development of early human communication. Aimed at twenty-six volunteers who provided many physical movements with various difficulties, the research team investigated the natural, repeatable, and paired sounds and shape productions during human activities. The paper claims the involvement of Paired Sounds and Shape Production (PSSP) in the phonetic origin of some modern words and the existence of similarities between elements of PSSP with characters of the classic Latin alphabet. The results may be used not only as a supporting idea for existing theories but to create a closer look at some fundamental nature of the origin of the languages as well.

Keywords: body shape, body language, coding, Latin alphabet, merging method, movement language, movement sound, natural sound, origin of language, pairing, phonetics, sound and shape production, word origin, word semantic

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Authors: Malgorzata Wojcik

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Groups are a powerful and significant part of human development. They serve as major emergent microsocial structures in children’s and youth’s ecological system. During middle and secondary school, peer groups become a particularly salient influence. While they promote a range of prosocial and positive emotional and behavioral attributes, they can also elicit negative or antisocial attributes, effectively “bringing out the worst” in some individuals. The grounded theory approach was employed to guide data collection and analysis, as it allows for a deeper understanding of the group processes and students’ perspectives on complex intragroup relations. Students’ perspectives on bullying cases were investigated by observing daily interactions among those involved and interviewing 47 students. The results complement theories of labeling in bullying by showing that all students self-label themselves and find it difficult to break patterns of behaviors related to bullying, such as supporting the bully or not defending the victim. In terms of the practical implications, the findings indicate that it could be beneficial to use non-punitive, restorative anti-bullying interventions that implement peer influence to transform bullying relations by removing behavioral labels.

Keywords: bullying, peer group, victimization, class reputation

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Authors: Simiao Ren, En Wei

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Drowning is a significant safety issue worldwide, and a robust computer vision-based alert system can easily prevent such tragedies in swimming pools. However, due to domain shift caused by the visual gap (potentially due to lighting, indoor scene change, pool floor color etc.) between the training swimming pool and the test swimming pool, the robustness of such algorithms has been questionable. The annotation cost for labeling each new swimming pool is too expensive for mass adoption of such a technique. To address this issue, we propose a domain-aware data augmentation pipeline based on Gaussian Poisson Generative Adversarial Network (GP-GAN). Combined with YOLOv8, we demonstrate that such a domain adaptation technique can significantly improve the model performance (from 0.24 mAP to 0.82 mAP) on new test scenes. As the augmentation method only require background imagery from the new domain (no annotation needed), we believe this is a promising, practical route for preventing swimming pool drowning.

Keywords: computer vision, deep learning, YOLOv8, detection, swimming pool, drowning, domain adaptation, generative adversarial network, GAN, GP-GAN

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Authors: Yuntao Liu, Lei Wang, Haoran Xia

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Machine learning has shown extensive applications in the development of classification models for autism spectrum disorder (ASD) using neural image data. This paper proposes a fusion multi-modal classification network based on a graph neural network. First, the brain is segmented into 116 regions of interest using a medical segmentation template (AAL, Anatomical Automatic Labeling). The image features of sMRI and the signal features of fMRI are extracted, which build the node and edge embedding representations of the brain map. Then, we construct a dynamically updated brain map neural network and propose a method based on a dynamic brain map adjacency matrix update mechanism and learnable graph to further improve the accuracy of autism diagnosis and recognition results. Based on the Autism Brain Imaging Data Exchange I dataset(ABIDE I), we reached a prediction accuracy of 74% between ASD and TD subjects. Besides, to study the biomarkers that can help doctors analyze diseases and interpretability, we used the features by extracting the top five maximum and minimum ROI weights. This work provides a meaningful way for brain disorder identification.

Keywords: autism spectrum disorder, brain map, supervised machine learning, graph network, multimodal data, model interpretability

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Authors: Dima Basma

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The unprecedented expansion in the use of Non-Fungible Tokens (NFTS) has prompted luxury brand owners to file their trademark applications for the use of their marks in the metaverse world. While NFTs provide a favorable tool for product traceability and anti-counterfeiting endeavors, the legal ramifications of such abrupt shift are complex, diverse, and yet to be understood. Practically, a sizable number of NFT creators are minting digital tokens associated with existing trademarks, selling them at strikingly high rates, thus disadvantaging trademark owners who joined and are yet to join the meta-verse world. As a result, multiple luxury brands are filing confusion and dilution lawsuits against alleged artists offering for sale NFTs depicting reputable marks labeling their use as “parody” and “social commentary.” Given the already muddled state of trademark law in relation to both traditional and modern infringement criteria, this paper aims to explore the feasibility of the current system in dealing with the emerging NFT trends. The paper firstly delves into the intersection between trademarks and NFTs. Furthermore, in light of the striking increase in NFT use, the paper sheds critical light on the shortcoming of the current system. Finally, the paper provides recommendations for overcoming current and prospective challenges in this area.

Keywords: trademarks, NFTs, dilution, social commentary

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Authors: Hiroyuki Aoki

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The physical properties of polymer materials are dependent on the conformation and molecular motion of a polymer chain. Therefore, the structure and dynamic behavior of the single polymer chain have been the most important concerns in the field of polymer physics. However, it has been impossible to directly observe the conformation of the single polymer chain in a bulk medium. In the current work, the novel techniques to study the conformation and dynamics of a single polymer chain are proposed. Since a fluorescence method is extremely sensitive, the fluorescence microscopy enables the direct detection of a single molecule. However, the structure of the polymer chain as large as 100 nm cannot be resolved by conventional fluorescence methods because of the diffraction limit of light. In order to observe the single chains, we developed the labeling method of polymer materials with a photo-switchable dye and the super-resolution microscopy. The real-space conformational analysis of single polymer chains with the spatial resolution of 15-20 nm was achieved. The super-resolution microscopy enables us to obtain the three-dimensional coordinates; therefore, we succeeded the conformational analysis in three dimensions. The direct observation by the nanometric optical microscopy would reveal the detailed information on the molecular processes in the various polymer systems.

Keywords: polymer materials, single molecule, super-resolution techniques, conformation

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Authors: Yeon Woo Seo, Haeyoung Choi, Jung Hyun Jeong

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Recently, the UC phosphors have attracted much attention owing to their wide applicability in areas such as biological fluorescence labeling, three-dimensional color displays, temperature sensor, solar cells, white light emitting diodes (WLEDs), fiber optic communication, anti-counterfeiting and other areas. The UC efficiency is mainly dependent on the host lattice and the interaction between the host lattice and doped ions. Up to date, various host matrices, such as oxides, fluorides, vanadates and phosphates, have been investigated as efficient UC luminescent hosts. Recently, oxide materials with low phonon energy have been investigated as the host matrices of UC materials due to their high chemical durability and physical stability. A series of Sr2CeO4: Tm3+/Yb3+ phosphors with different concentrations of Yb3+ ions have been successfully prepared using the high-energy ball milling method. In this study, we reported the UC luminescent properties of Tm3+/Yb3+ ions co-doped Sr2CeO4 phosphors under an excitation wavelength of 975 nm. Furthermore, the structural and morphological characteristics, as well as the UC luminescence mechanism were investigated in detail. The X-ray diffraction patterns confirmed their orthorhombic structure. Under 975 nm excitation, the emission peaks were observed at 478 nm (blue) and 652 nm (red), corresponding to the 1G4 → 3H6 and 1G4 → 3F4 transitions of Tm3+, respectively. The optimized doping concentration of Yb3+ ion was 10 mol%.

Keywords: Strontium Cerate, up-conversion, luminescence, Tm3+, Yb3+

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Authors: Samir Dekali, David Crouzier

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Due to their new physico-chemical properties engineered nanoparticles (ENPs) are increasingly employed in numerous industrial sectors (such as electronics, textile, aerospace, cosmetics, pharmaceuticals, food industry, etc). These new physico-chemical properties can also represent a threat for the human health. Consumers can notably be exposed involuntarily by different routes such as inhalation, ingestion or through the skin. Several studies recently reported a possible biodistribution of these ENPs on the blood-brain barrier (BBB). Consequently, there is a great need for developing BBB in vitro models representative of the in vivo situation and capable of rapidly and accurately assessing ENPs toxic effects and their potential translocation through this barrier. In this study, several in vitro models established with micro-endothelial brain cell lines of different origins (bEnd.3 mouse cell line or a new human cell line) co-cultivated or not with astrocytic cells (C6 rat or C8-B4 mouse cell lines) on Transwells® were compared using different endpoints: trans-endothelial resistance, permeability of the Lucifer yellow and protein junction labeling. Impact of NIST diesel exhaust particles on BBB cell viability is also discussed.

Keywords: nanoparticles, blood-brain barrier, diesel exhaust particles, toxicology

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Authors: Mohammed Idaan Hassan Al-Majidi

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An analysis of twenty one assorted brands of vegetable oils in Babylon Iraq, reveals varying levels of cholesterol content. Cholesterol was found to be present in most of the oil brands sampled using three standard methods. Cholesterol was detected in seventeen of the vegetable oil brands with concentration of less than 1 mg/ml while seven of the oil brands had cholesterol concentrations ranging between 1-4 mg/ml. Low iodine values were obtained in four of the vegetable oil brands and three of them had high acid values. High performance liquid chromatography (HPLC) confirmed the presence of cholesterol at varying concentrations in all the oil brands and gave the lowest detectable cholesterol values in all the oil brands. The Laser brand made from rapeseed had the highest cholesterol concentration of 3.2 mg/ml while Grand brand made from groundnuts had the least concentration (0.12 mg/ml) of cholesterol using HPLC analysis. Leibermann-Burchard method showed that Gino brand from palm kernel had the least concentration of cholesterol (3.86 mg/ml ±0.032) and the highest concentration of 3.996 mg/ml ±0.0404 was obtained in Sesame seed oil brand. This report is important in view of health implications of cholesterol in our diets. Consequently, we have been able to show that there is no cholesterol free oil in the market as shown on the vegetable oil brand labels. Therefore, companies producing and marketing vegetable oils are enjoined to desist from misleading the public by labeling their products as “cholesterol free”. They should indicate the amount of cholesterol present in the vegetable oil, no matter how small the quantity may be.

Keywords: vegetable oils, heart diseases, leibermann-burchard, cholesterol

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Authors: Nonlapun Meenil, Pisitpong Intarapong, Thitima Wongsheree, Pranchalee Samanpiboon

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In Thailand, once pineapples are harvested, they must be classified into two classes based on their sweetness: sweet and unsweet. This paper has studied and developed the assessment of internal quality of pineapples using a low-cost compact spectroscopy sensor according to the Spectroscopy approach and Neural Network (NN). During the experiments, Batavia pineapples were utilized, generating 100 samples. The extracted pineapple juice of each sample was used to determine the Soluble Solid Content (SSC) labeling into sweet and unsweet classes. In terms of experimental equipment, the sensor cover was specifically designed to install the sensor and light source to read the reflectance at a five mm depth from pineapple flesh. By using a spectroscopy sensor, data on visible and near-infrared reflectance (Vis-NIR) were collected. The NN was used to classify the pineapple classes. Before the classification step, the preprocessing methods, which are Class balancing, Data shuffling, and Standardization were applied. The 510 nm and 900 nm reflectance values of the middle parts of pineapples were used as features of the NN. With the Sequential model and Relu activation function, 100% accuracy of the training set and 76.67% accuracy of the test set were achieved. According to the abovementioned information, using a low-cost compact spectroscopy sensor has achieved favorable results in classifying the sweetness of the two classes of pineapples.

Keywords: neural network, pineapple, soluble solid content, spectroscopy

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Authors: Shan-Ying Wu, Sheng-Hui Lan, Xi-Zhang Lin, Ih-Jen Su, Ting-Fen Tsai, Chia-Jui Yen, Tsung-Hsueh Lu, Fu-Wen Liang, Huey-Jen Su, Chun-Li Su, Hsiao-Sheng Liu

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In hepatocelluar carcinoma (HCC), dysregulated expression of cyclin D1 and impaired autophagy has been reported separately. However, the relationship between them has not been explored. In this study, we demonstrated that autophagy was inversely correlated with cyclin D1 expression in 147 paired HCC patient specimens. HCC specimen with highly expression of cyclin D1 shows correlation with poor overall survival rate. Furthermore, induction of autophagy by amiodarone (antiarrhythmic drug) in Hep 3B cells, cyclin D1 was recruited into autophagosomes demonstrated by immune-gold labeling of cyclin D1 after extraction of autophagosomes. We further demonstrated that autophagy suppresses Hep 3B cell proliferation, and further analysis revealed that cell cycle was arrested at G1 phase. The interaction between LC3 (maker of autophagy) and cyclin D1 was increased after autophagy induction. In addition, ubiquitinated-cyclin D1 was also increased after autophagy induction, which is selectively degraded by autophagosome through binding with SQSTM1/p62 (an adaptor protein). In vivo study showed that amiodarone induced autophagy suppresses liver tumor formation in xenograft mouse and orthotopic rat model through decreasing cyclin D1 expression and inhibition of cell proliferation. Altogether, we reveal a novel mechanism that ubiquitinated cyclin D1 degraded by autophagic pathway by p62 and amiodarone is a promising drug for targeting cyclin D1 in liver cancer therapy.

Keywords: autophagy, cyclin D1, hepatocellular carcinoma, amiodarone

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Authors: Shalini Attri

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Silence has been 'scriptured' in women within dominating social structures, as the modes of speaking and behaving which deny women free investiture to language. A woman becomes the product of ideological constructions as language substantiates andro-centric bias. Constrained from writing/speaking in the public sphere, women have traditionally been confined to expressing themselves in writing private poetry, letters or diaries. The helplessness of a woman is revealed in the ways in which she is expected to speak a language, which, in fact, is man-made. There are visible binaries of coloniser- colonised; Western-Eastern; White-Black, Nature-Culture, even Male-Female that contribute significantly to our understanding of the concept of representation and its resultant politics. Normally, an author is labeled as feminist, humanist, or propagandist and this process of labeling correspond to a sense of politics besides his inclination to a particular field. One cannot even think of contemporary literature without this representational politics. Thus, each and every bit of analysis of a work of literature demands a political angle to be dealt with. Besides literature, the historical facts and manuscripts are also subject to this politics. The image of woman as someone either dependent on man or is exploited by him only provides half the picture of this representational politics. The present paper is an attempt to study Panchali’s (Draupadi of Mahabharata) voiceless articulation and her representation as a strong woman in Chitra Divakurani’s The Palace of Illusions.

Keywords: politics, representation, silence, social structures

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Authors: C. A. Anser Pasha

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In this paper, a new Vehicular Speed Detection Camera System that is applicable as an alternative to traditional radars with the same accuracy or even better is presented. The real-time measurement and analysis of various traffic parameters such as speed and number of vehicles are increasingly required in traffic control and management. Image processing techniques are now considered as an attractive and flexible method for automatic analysis and data collections in traffic engineering. Various algorithms based on image processing techniques have been applied to detect multiple vehicles and track them. The SDCS processes can be divided into three successive phases; the first phase is Objects detection phase, which uses a hybrid algorithm based on combining an adaptive background subtraction technique with a three-frame differencing algorithm which ratifies the major drawback of using only adaptive background subtraction. The second phase is Objects tracking, which consists of three successive operations - object segmentation, object labeling, and object center extraction. Objects tracking operation takes into consideration the different possible scenarios of the moving object like simple tracking, the object has left the scene, the object has entered the scene, object crossed by another object, and object leaves and another one enters the scene. The third phase is speed calculation phase, which is calculated from the number of frames consumed by the object to pass by the scene.

Keywords: radar, image processing, detection, tracking, segmentation

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Authors: Plessen Mogens Graf

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Within the context of multivariate time series segmentation, this paper proposes a method inspired by a posteriori optimal trading. After a normalization step, time series are treated channelwise as surrogate stock prices that can be traded optimally a posteriori in a virtual portfolio holding either stock or cash. Linear transaction costs are interpreted as hyperparameters for noise filtering. Trading signals, as well as trading signals obtained on the reversed time series, are used for unsupervised channelwise labeling before a consensus over all channels is reached that determines the final segmentation time instants. The method is model-free such that no model prescriptions for segments are made. Benefits of proposed approach include simplicity, computational efficiency, and adaptability to a wide range of different shapes of time series. Performance is demonstrated on synthetic and real-world data, including a large-scale dataset comprising a multivariate time series of dimension 1000 and length 2709. Proposed method is compared to a popular model-based bottom-up approach fitting piecewise affine models and to a recent model-based top-down approach fitting Gaussian models and found to be consistently faster while producing more intuitive results in the sense of segmenting time series at peaks and valleys.

Keywords: time series segmentation, model-free, trading-inspired, multivariate data

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Authors: Hyojin Lim, Cuong Nguyen Khac, Yeongyu Choi, Ho-Youl Jung

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In this paper, we propose a simple moving object detection, which is based on motion vectors obtained from pyramidal Lucas-Kanade optical flow. The proposed method detects moving objects such as pedestrians, the other vehicles and some obstacles at the front-side of the host vehicle, and it can provide the warning to the driver. Motion vectors are obtained by using pyramidal Lucas-Kanade optical flow, and some outliers are eliminated by comparing the amplitude of each vector with the pre-defined threshold value. The background model is obtained by calculating the mean and the variance of the amplitude of recent motion vectors in the rectangular shaped local region called the cell. The model is applied as the reference to classify motion vectors of moving objects and those of background. Motion vectors are clustered to rectangular regions by using the unsupervised clustering K-means algorithm. Labeling method is applied to label groups which is close to each other, using by distance between each center points of rectangular. Through the simulations tested on four kinds of scenarios such as approaching motorbike, vehicle, and pedestrians to host vehicle, we prove that the proposed is simple but efficient for moving object detection in parking lots.

Keywords: moving object detection, dynamic scene, optical flow, pyramidal optical flow

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Authors: Arth Bohra, Marwa Mahmoud

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In this paper, we utilize computer vision to develop a tool for youth coaches to formulate set-piece tactics for their players. We used the Soccernet database to extract the ResNet features and camera calibration data for over 3000 corner kick across 500 professional matches in the top 6 European leagues (English Premier League, UEFA Champions League, Ligue 1, La Liga, Serie A, Bundesliga). Leveraging the provided homography matrix, we construct a feature vector representing the formation of players on these corner kicks. Additionally, labeling the videos manually, we obtained the pass-trajectory of each of the 3000+ corner kicks by segmenting the field into four zones. Next, after determining the localization of the players and ball, we used event data to give the corner kicks a rating on a 1-4 scale. By employing a Convolutional Neural Network, our model managed to predict the success of a corner kick given the formations of players. This suggests that with the right formations, teams can optimize the way they approach corner kicks. By understanding this, we can help coaches formulate set-piece tactics for their own teams in order to maximize the success of their play. The proposed model can be easily extended; our method could be applied to even more game situations, from free kicks to counterattacks. This research project also gives insight into the myriad of possibilities that artificial intelligence possesses in transforming the domain of sports.

Keywords: soccer, corner kicks, AI, computer vision

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Authors: Temitope Ogungbemi

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Jama'atu Ahlis Sunna Lidda'awati wal-Jihad (also called Boko Haram) in the North-East of Nigeria has facilitated ideological binarity in discourses on the crisis. Since its proliferation, media representation of the crisis has facilitated identity contamination and ideological struggle through which other critical issues, such as religious intolerance, ethnic diversity and other forms of class conflict in the Nigerian state, are brought to public notice. Though Boko Haram insurgency is ideological laden, the manifestation of the inherent ideologies requires extensive scholarly attention in order deconstruct the veiled ideologies. Therefore, the thrust of this study is to critically investigate identity (mis)representation as a basis for ideological mapping in discourses on Boko Haram in Nigeria, adopting critical discourse analytical tools supported with insights from systemic functional linguistics and critical discourse analysis. The data for this study consist of articles on Boko Haram in Nigerian newspapers published in English. The data selection is purposive and aimed at responding to challenges that are inherent in Nigeria's multifaithism and multiculturalism, and their effects on the construction of narratives on Boko Haram. The study reveals that identity manipulation is a constructive device for ideological mapping, realised through labeling, agency activation, and transitivity. Identity representation in discourses on Boko Haram depicted four dichotomous binarities using exclusion, generalisation, contrasting and attribution.

Keywords: identity representation, ideology, Boko Haram, newspapers

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Authors: Jie Huo, Jonathan Wu

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Segmentation of anatomical structures in medical images is essential for scientific inquiry into the complex relationships between biological structure and clinical diagnosis, treatment and assessment. As a method of incorporating the prior knowledge and the anatomical structure similarity between a target image and atlases, multi-atlas segmentation has been successfully applied in segmenting a variety of medical images, including the brain, cardiac, and abdominal images. The basic idea of multi-atlas segmentation is to transfer the labels in atlases to the coordinate of the target image by matching the target patch to the atlas patch in the neighborhood. However, this technique is limited by the pairwise registration between target image and atlases. In this paper, a novel multi-atlas segmentation approach is proposed by introducing a dynamic energy model. First, the target is mapped to each atlas image by minimizing the dynamic energy function, then the segmentation of target image is generated by weighted fusion based on the energy. The method is tested on MICCAI 2012 Multi-Atlas Labeling Challenge dataset which includes 20 target images and 15 atlases images. The paper also analyzes the influence of different parameters of the dynamic energy model on the segmentation accuracy and measures the dice coefficient by using different feature terms with the energy model. The highest mean dice coefficient obtained with the proposed method is 0.861, which is competitive compared with the recently published method.

Keywords: brain MRI segmentation, dynamic energy model, multi-atlas segmentation, energy minimization

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Authors: Swapnila V. Shinde, Hemant P. Joshi, Sumit R. Dhas, Dhananjaysingh B. Rajput

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The objective of the present study is to develop hydro-dynamically balanced system for atenolol, β-blocker as a single unit floating tablet. Atenolol shows pH dependent solubility resulting into a bioavailability of 36%. Thus, site specific oral controlled release floating drug delivery system was developed. Formulation includes novice use of rate controlling polymer such as locust bean gum (LBG) in combination of HPMC K4M and gas generating agent sodium bicarbonate. Tablet was prepared by direct compression method and evaluated for physico-mechanical properties. The statistical method was utilized to optimize the effect of independent variables, namely amount of HPMC K4M, LBG and three dependent responses such as cumulative drug release, floating lag time, floating time. Graphical and mathematical analysis of the results allowed the identification and quantification of the formulation variables influencing the selected responses. To study the gastrointestinal transit of the optimized gastro-retentive formulation, in vivo gamma scintigraphy was carried out in six healthy rabbits, after radio labeling the formulation with 99mTc. The transit profiles demonstrated that the dosage form was retained in the stomach for more than 5 hrs. The study signifies the potential of the developed system for stomach targeted delivery of atenolol with improved bioavailability.

Keywords: floating tablet, factorial design, gamma scintigraphy, antihypertensive model drug, HPMC, locust bean gum

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Authors: Akrem Sellami, Imed Riadh Farah

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Hyperspectral imagery (HSI) typically provides a wealth of information captured in a wide range of the electromagnetic spectrum for each pixel in the image. Hence, a pixel in HSI is a high-dimensional vector of intensities with a large spectral range and a high spectral resolution. Therefore, the semantic interpretation is a challenging task of HSI analysis. We focused in this paper on object classification as HSI semantic interpretation. However, HSI classification still faces some issues, among which are the following: The spatial variability of spectral signatures, the high number of spectral bands, and the high cost of true sample labeling. Therefore, the high number of spectral bands and the low number of training samples pose the problem of the curse of dimensionality. In order to resolve this problem, we propose to introduce the process of dimensionality reduction trying to improve the classification of HSI. The presented approach is a semi-supervised band selection method based on spatial hypergraph embedding model to represent higher order relationships with different weights of the spatial neighbors corresponding to the centroid of pixel. This semi-supervised band selection has been developed to select useful bands for object classification. The presented approach is evaluated on AVIRIS and ROSIS HSIs and compared to other dimensionality reduction methods. The experimental results demonstrate the efficacy of our approach compared to many existing dimensionality reduction methods for HSI classification.

Keywords: dimensionality reduction, hyperspectral image, semantic interpretation, spatial hypergraph

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Authors: Nurul Ain Haron, Saiful Hazmi Bachek, Hafez Zainudin

Abstract:

This study is aimed to establish the importance and contribution of Original Design Manufacturing (ODM) in Malaysian Furniture Industry and to close the gap between the players in the industry. The study confirms that today’s furniture industry favor Original Equipment Manufacturing (OEM) basis. Thus, resulting in the local industry lacking the expertise of designing furniture to a state of no contest. This study method used consists of literature reviews, observation, questionnaire and sessions of interviews. The result shows that the public has from minimum to almost no knowledge of the term Original Design Manufacturing (ODM) concept and the impact towards our current future industry. The manufacturers however, prefers Original Equipment Manufacturing (OEM) concept due to its easy and fast investment returns with the need of product designing process, while the interviews carried out with the authorized council had some convincing urges of doing their part promoting the awareness through trainings and seminars. Findings show that, in the rush of archiving ODM status needs extensive cooperation from many parties that are authorized council, furniture manufacturers, designers and also the public perceptions of labeling local made goods as the black goat. The current mind set of OEM manufacturers need to be change for industry’s future. As Malaysia’s living status constantly increases, so will the demands of a better salary. If these current issues are not resolved, OEM international buyers will definitely have to shift to some other lower cost manufacturer like China or Taiwan. When vendors stopped to order, today’s OEM manufacturers will no longer exist in the future.

Keywords: design manufacturing, furniture design, original design manufacturing, original equipment manufacturing

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Authors: Somaye Sabetnia

Abstract:

This paper is accomplished to probe Susanna Kaysen’s memoir Girl, Interrupted in the light of Michel Foucault’s theory of madness comprehensively set forth in his History of Madness (1961). It is an endeavor to analysis this novel based on Foucault’s idea of madness. In his archeological study of madness, Foucault introduces a way to perceive madness and its association with dominant discourses. He argues that the concept of madness is constructed within the social context, and different institutions affect its definition. Furthermore, he takes into consideration how each era treats madness, and affirms that in modern times, people considered mad are exiled out of cities, confined in madhouses, and later in clinics where they are treated with drugs. Set after World War II, the novel under observation highlights women’s conditions in which they were becoming a housewife or following their own desires; in fact, choosing the second one results in labeling mad. The protagonist of novel is labeled 'mad,' and is hence impelled to go to asylums where so-called patients are under the vigilant surveillance of the authorities to go through the process of 'normalization.' To discern how she is considered 'mad,' this article probes the dominant discourse of the time when the stories take place to provide a better understanding of madness under the impact of social, cultural, and political conditions. It examines how a so-called mad considered 'Other' and treated after being confined by the disciplinary system of the asylum in a panoptic world. In addition to, it describes the aim of treatment is to punish and control a patient not to cure. This article aims to indicate that Susanna Kaysen tries to picture what is defined as women’s madness is the result of the patriarchal society of the post-war America as well as the mental illness has nothing to do with blood; it is rather the result of the social inequality of the age.

Keywords: clinical treatment, disciplining and punishment, dominant discourse, normalization, other, panoptic world, reason vs. unreason

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Authors: Kathleen Seers, Rachel Hogg

Abstract:

Diagnosis of Autism Spectrum Disorder (ASD) in women is increasing, prompting research into the presentation of female ASD and exploring why females are failing to meet the diagnostic threshold. One explanation is the use of masking behaviors, where traits of ASD are suppressed and gender-appropriate behaviors are mimicked to reduce the visibility and victimization of ASD girls. Current research explores ASD presentation and the lived experiences of ASD girls and adolescents; however, there is a paucity of literature in relation to the intra- and inter- psychic experiences of ASD women. Through a social constructionist framework, this qualitative study sought to understand how the construction of gender and the medicalisation of ASD influences women’s experiences of ASD. This study also explored the use and consequence of masking strategies and the impact this has on well-being. Eight women were interviewed, and three major themes were identified. The themes outline the influence of gender expectations and social norms on the women’s experiences, the significance of diagnosis to their identity, and the influence of the medicalization of ASD. Participants shared experiences of feeling different and internalizing blame for this difference. The feeling of difference was a major contributor to the women’s positive or negative mental well-being. The process of diagnosis allowed participants to create and confirm their identity. Diagnosis also led to improvements in well-being, however, the findings also explore the complexity of labeling individuals with a disorder and the difficulties that arise from the construct of ‘functionality’ for those with Autism. The study also explores the temporal nature of ASD and the changing experiences of women as they mature. It is hoped this study promotes discussion and provides clinicians and those connected to ASD women with insights into the support ASD women require to live authentic lives.

Keywords: female autism, gender, masking, social constructionism

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Authors: Sangwoo Oh, Jaewoo Kim, Dongmin Seo, Jaewon Park, Yongha Hwang, Sungkyu Seo

Abstract:

Plasmonics has been regarded one of the most powerful bio-sensing modalities to evaluate bio-molecular interactions in real-time. However, most of the plasmonic sensing methods are based on labeling metallic nanoparticles, e.g. gold or silver, as optical modulation markers, which are non-recyclable and expensive. This plasmonic modulation can be usually achieved through various nano structures, e.g., nano-hole arrays. Among those structures, plasmonic lens has been regarded as a unique plasmonic structure due to its light focusing characteristics. In this study, we introduce a custom designed plasmonic lens array for bio-sensing, which was simulated by finite-difference-time-domain (FDTD) approach and fabricated by top-down approach. In our work, we performed the FDTD simulations of various plasmonic lens designs for bacteria sensor, i.e., Samonella and Hominis. We optimized the design parameters, i.e., radius, shape, and material, of the plasmonic lens. The simulation results showed the change in the peak intensity value with the introduction of each bacteria and antigen i.e., peak intensity 1.8711 a.u. with the introduction of antibody layer of thickness of 15nm. For Salmonella, the peak intensity changed from 1.8711 a.u. to 2.3654 a.u. and for Hominis, the peak intensity changed from 1.8711 a.u. to 3.2355 a.u. This significant shift in the intensity due to the interaction between bacteria and antigen showed a promising sensing capability of the plasmonic lens. With the batch processing and bulk production of this nano scale design, the cost of biological sensing can be significantly reduced, holding great promise in the fields of clinical diagnostics and bio-defense.

Keywords: plasmonic lens, FDTD, fabrication, bacteria sensor, salmonella, hominis

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