Search results for: face presentation attack detection

Authors: Kritin K. Verma, Brian L. Ransdell

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White patches are a symptom of vitiligo, a chronic autoimmune dermatological condition that causes a loss of pigmentation in the skin. Vitiligo can cause issues of self-esteem and quality of life while also progressing the development of other autoimmune diseases. Current treatments in allopathy and homeopathy exist; some treatments have been found to be toxic, whereas others have been helpful. Allopathy has seemed to offer several treatment plans, such as phototherapy, skin lightening preparations, immunosuppressive drugs, combined modality therapy, and steroid medications to improve vitiligo. This presentation will review the FDA-approved topical cream, Opzelura, a JAK inhibitor, and its effects on limiting vitiligo progression. Meanwhile, other non-conventional methods, such as Arsenic Sulphuratum Flavum used in homeopathy, will be debunked based on current literature. Most treatments still serve to arrest progression and induce skin repigmentation. Treatment plans may differ between patients due to depigmentation location on the skin. Since there is no gold standard plan for treating patients with vitiligo, the oral presentation will review all topical and systemic pharmacological therapies that fight the depigmentation of the skin and categorize their validity from a systematic review of the literature. Since treatment plans are limited in nature, all treatment methods will be mentioned and an attempt will be made to make a golden standard treatment process for these patients.

Keywords: vitiligo, phototherapy, immunosuppressive drugs, skin lightening preparations, combined modality therapy, arsenic sulphuratum flavum, homeopathy, allopathy, golden standard, Opzelura

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Authors: Miroslav Hyza, Petr Rulik, Vojtech Bednar, Jan Sury

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An early and reliable detection of an increased radioactivity level in the atmosphere is one of the key aspects of atmospheric radiological monitoring. Although the standard laboratory procedures provide detection limits as low as few µBq/m³, their major drawback is the delayed result reporting: typically a few days. This issue is the main objective of the HAMRAD project, which gave rise to a prototype of an autonomous monitoring device. It is based on the idea of sequential aerosol sampling using a carrousel sample changer combined with a gamma-ray spectrometer. In our hardware configuration, the air is drawn through a filter positioned on the carrousel so that it could be rotated into the measuring position after a preset sampling interval. Filter analysis is performed via a 50% HPGe detector inside an 8.5cm lead shielding. The spectrometer output signal is then analyzed using DSP electronics and Gamwin software with preset nuclide libraries and other analysis parameters. After the counting, the filter is placed into a storage bin with a capacity of 250 filters so that the device can run autonomously for several months depending on the preset sampling frequency. The device is connected to a central server via GPRS/GSM where the user can view monitoring data including raw spectra and technological data describing the state of the device. All operating parameters can be remotely adjusted through a simple GUI. The flow rate is continuously adjustable up to 10 m³/h. The main challenge in spectrum analysis is the natural background subtraction. As detection limits are heavily influenced by the deposited activity of radon decay products and the measurement time is fixed, there must exist an optimal sample decay time (delayed spectrum acquisition). To solve this problem, we adopted a simple procedure based on sequential spectrum acquisition and optimal partial spectral sum with respect to the detection limits for a particular radionuclide. The prototyped device proved to be able to detect atmospheric contamination at the level of mBq/m³ per an 8h sampling.

Keywords: aerosols, atmosphere, atmospheric radioactivity monitoring, autonomous sampler

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Authors: Seyed Mohsen Jameii

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Wireless underwater sensor networks are a type of sensor networks that are located in underwater environments and linked together by acoustic waves. The application of these kinds of network includes monitoring of pollutants (chemical, biological, and nuclear), oil fields detection, prediction of the likelihood of a tsunami in coastal areas, the use of wireless sensor nodes to monitor the passing submarines, and determination of appropriate locations for anchoring ships. This paper proposes a boundary coverage algorithm for intrusion detection in underwater sensor networks. In the first phase of the proposed algorithm, optimal deployment of nodes is done in the water. In the second phase, after the employment of nodes at the proper depth, clustering is executed to reduce the exchanges of messages between the sensors. In the third phase, the algorithm of "divide and conquer" is used to save energy and increase network efficiency. The simulation results demonstrate the efficiency of the proposed algorithm.

Keywords: boundary coverage, clustering, divide and ‎conquer, underwater sensor nodes

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

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

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

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Authors: Sergey Svita, Valeriy Astapenko

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The presentation is devoted to the theoretical analysis of ultrashort electromagnetic pulses (USP) scattering on metallic nanospheres in a dielectric medium in the vicinity of surface plasmon resonance due to excitation of dipole and quadrupole surface plasmons.

Keywords: surface plasmon, scattering, metallic nanosphere

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Authors: H. Aldewachi, M. Hines, M. McCulloch, N. Woodroofe, P. Gardiner

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DPP-IV is an enzyme whose expression is affected in a variety of diseases, therefore, has been identified as possible diagnostic or prognostic marker for various tumours, immunological, inflammatory, neuroendocrine, and viral diseases. Recently, DPP-IV enzyme has been identified as a novel target for type II diabetes treatment where the enzyme is involved. There is, therefore, a need to develop sensitive and specific methods that can be easily deployed for the screening of the enzyme either as a tool for drug screening or disease marker in biological samples. A variety of assays have been introduced for the determination of DPP-IV enzyme activity using chromogenic and fluorogenic substrates, nevertheless these assays either lack the required sensitivity especially in inhibited enzyme samples or displays low water solubility implying difficulty for use in vivo samples in addition to labour and time-consuming sample preparation. In this study, novel strategies based on exploiting the high extinction coefficient of gold nanoparticles (GNPs) are investigated in order to develop fast, specific and reliable enzymatic assay by investigating synthetic peptide sequences containing a DPP IV cleavage site and coupling them to GNPs. The DPP IV could be detected by colorimetric response of peptide capped GNPs (P-GNPS) that could be monitored by a UV-visible spectrophotometer or even naked eyes, and the detection limit could reach 0.01 unit/ml. The P-GNPs, when subjected to DPP IV, showed excellent selectivity compared to other proteins (thrombin and human serum albumin) , which led to prominent colour change. This provided a simple and effective colorimetric sensor for on-site and real-time detection of DPP IV.

Keywords: gold nanoparticles, synthetic peptides, colorimetric detection, DPP-IV enzyme

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Authors: Hyun-Woo Cho

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Automatic process monitoring schemes are designed to give early warnings for unusual process events or abnormalities as soon as possible. For this end, various techniques have been developed and utilized in various industrial processes. It includes multivariate statistical methods, representation skills in reduced spaces, kernel-based nonlinear techniques, etc. This work presents a nonlinear empirical monitoring scheme for batch type production processes with incomplete process measurement data. While normal operation data are easy to get, unusual fault data occurs infrequently and thus are difficult to collect. In this work, noise filtering steps are added in order to enhance monitoring performance by eliminating irrelevant information of the data. The performance of the monitoring scheme was demonstrated using batch process data. The results showed that the monitoring performance was improved significantly in terms of detection success rate of process fault.

Keywords: batch process, monitoring, measurement, kernel method

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Authors: Eliane Abdo

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Small and medium sized firms “SMEs” play essential role in the countries’ economic development mainly in terms of production, employment and equitable distribution of income. For innovative SMEs, the investment in the human capital and in research and development are crucial to survive in a competitive environment. In this paper we perform a literature review to underline the financing difficulties and constraints which innovative SMEs face while investing in intangible assets: not only when defining amount of the investments but also while choosing its financing methods. Literature review revealed that in order to finance their intangible assets, SMEs rely in first on their internal financing: the availability of internal cash flows can then determine their investment’s decision. Moreover SMEs face difficulties to finance their intangibles by financial debts due to the uncertainty of future cash flow and the absence of physical guarantees; they will therefore go for the issuance of new shares as a second choice, since innovative companies have high opportunity of growth that attract new shareholders.

Keywords: small and medium sized firms, capital structure, intangible investment, financial constraints

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Authors: Gauri Shankar Shah

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Objectives: The Type I diabetes mellitus in children is frequently a missed diagnosis and children presents in emergency with diabetic ketoacidosis having significant morbidity and mortality. The present study was done to find out the clinical presentation and outcome at a tertiary-care centre. Methods: This was retrospective analysis of data of Type I diabetes mellitus reporting to our centre during last one year (2012-2013). Results: There were 12 patients (8 males) and the age group was 4-14 years (mean ± 3.7). The presenting symptoms were fever, vomiting, altered sensorium and fast breathing in 8 (66.6%), 6 (50%), 4 (33.3%), and 4 (33.3%) cases, respectively. The classical triad of polyuria, polydypsia, and polyphagia were present only in two patients (33.2%). Seizures and epigastric pain were found in two cases each (33.2%). The four cases (33.3%) presented with diabetic ketoacidosis due to discontinuation of insulin doses, while 2 had hyperglycemia alone. The hemogram revealed mean hemoglobin of 12.1± 1.6 g/dL and total leukocyte count was 22,883.3 ± 10,345.9 per mm3, with polymorphs percentage of 73.1 ± 9.0%. The mean blood sugar at presentation was 740 ± 277 mg/ dl (544–1240). HbA1c ranged between 7.1-8.8 with mean of 8.1±0.6 %. The mean sodium, potassium, blood ph, pCO2, pO2 and bicarbonate were 140.8 ± 6.9 mEq/L, 4.4 ± 1.8mEq/L, 7.0 ± 0.2, 20.2 ± 10.8 mmHg, 112.6 ± 46.5 mmHg and 9.2 ± 8.8 mEq/L, respectively. All the patients were managed in pediatric intensive care unit as per our protocol, recovered and discharged on intermediate insulin given twice daily. Conclusions: Thus, it shows that these patients have uncontrolled hyperglycemia and often presents in emergency with ketoacidosis and deranged biochemical profile. The regular administration of insulin, frequent monitoring of blood sugar and health education are required to have better metabolic control and good quality of life.

Keywords: type I diabetes mellitus, hyperglycemia, outcome, glycemic control

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Authors: Walaa M.Abd-Elhafiez, Wajeb Gharibi

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In this paper a novel color image compression technique for efficient storage and delivery of data is proposed. The proposed compression technique started by RGB to YCbCr color transformation process. Secondly, the canny edge detection method is used to classify the blocks into edge and non-edge blocks. Each color component Y, Cb, and Cr compressed by discrete cosine transform (DCT) process, quantizing and coding step by step using adaptive arithmetic coding. Our technique is concerned with the compression ratio, bits per pixel and peak signal to noise ratio, and produce better results than JPEG and more recent published schemes (like, CBDCT-CABS and MHC). The provided experimental results illustrate the proposed technique which is efficient and feasible in terms of compression ratio, bits per pixel and peak signal to noise ratio.

Keywords: image compression, color image, q-coder, quantization, edge-detection

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Authors: Balarabe Bilyaminu Ismail, Osman Cavus, Fügen Durlu Özkaya

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This study is aimed at determining the level of awareness of chefs and students of food science and technology on food safety in general and allergens in particular. To get appropriate data, a questionnaire comprising of 19 questions covering many food safety issues and allergens in foods were used to collect information for the study through face to face interviews. Interviews were conducted for 284 people in Nigeria and Turkey. Sixty-eight percent of respondents from Turkey; 31.3% were students and 68.7% were chefs. Thirty-one percent of respondents from Nigeria include 33.7% students and 66.3% chefs. The result of the study indicated that most of the findings of scientific studies on food safety issues have not been directly applied by the people working in the food sector. Additionally, the knowledge level of the gastronomy and culinary arts students on food safety and allergens are significantly higher than the restaurant chefs that prepare the food and serve it to the public. The study, therefore, concluded that proper training of food business operators is critical to ensuring the safety of foods and control of allergens.

Keywords: allergens, food safety, questionnaire survey, training

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Authors: Hu Ding, Kai Liu, Guoan Tang

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The Chinese Loess Plateau suffers from serious gully erosion induced by natural and human causes. Gully features detection including gully-affected area and its two dimension parameters (length, width, area et al.), is a significant task not only for researchers but also for policy-makers. This study aims at gully-affected area detection in three catchments of Chinese Loess Plateau, which were selected in Changwu, Ansai, and Suide by using unmanned aerial vehicle (UAV). The methodology includes a sequence of UAV data generation, image segmentation, feature calculation and selection, and random forest classification. Two experiments were conducted to investigate the influences of segmentation strategy and feature selection. Results showed that vertical and horizontal root-mean-square errors were below 0.5 and 0.2 m, respectively, which were ideal for the Loess Plateau region. The segmentation strategy adopted in this paper, which considers the topographic information, and optimal parameter combination can improve the segmentation results. Besides, the overall extraction accuracy in Changwu, Ansai, and Suide achieved was 84.62%, 86.46%, and 93.06%, respectively, which indicated that the proposed method for detecting gully-affected area is more objective and effective than traditional methods. This study demonstrated that UAV can bridge the gap between field measurement and satellite-based remote sensing, obtaining a balance in resolution and efficiency for catchment-scale gully erosion research.

Keywords: unmanned aerial vehicle (UAV), object-analysis image analysis, gully erosion, gully-affected area, Loess Plateau, random forest

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Authors: Roman Kusaiko

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For decades, remaking was one of the film industry’s main practices but has become vivid in recent years. The latest geopolitical developments, though, are becoming a new challenge for filmmakers regarding cultural landscapes and contextual differences. Deglobalization may also affect transnational remaking practices. Thus, these upcoming challenges can be addressed through the analysis of contemporary academic thought, primarily from adaptation and film studies and their understanding of the issues of transmediality and how it affects film remaking. However, the analysis would be insufficient without conducting case studies. This paper is part of broader research about transnational remaking practices and their cultural and contextual specifics. This paper aims to understand whether shifting medium affects remaking as a critical category and present case studies of the popular Hong Kong motion picture Infernal Affairs and its transition into the Japanese remake Double Face. Consequently, the analysis of their contextual distinctions will lead to the correct categorization of the transnational remakes allowing scholars and filmmakers to better understand the existing remaking practices and whether they affect the final result.

Keywords: cinema, context, culture, films, remaking, transmediality

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Authors: Animut Meseret Simachew

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Parallel Code Phase Search Acquisition (PCSA) Algorithm has been considered as a promising method in GPS software receivers for detection and estimation of the accurate correlation peak between the received Global Positioning System (GPS) signal and locally generated replicas. GPS signal acquisition in highly dense multipath environments is the main research challenge. In this work, we proposed a robust variable step-size (RVSS) PCSA algorithm based on fast frequency transform (FFT) filtering technique to mitigate short time delay multipath signals. Simulation results reveal the effectiveness of the proposed algorithm over the conventional PCSA algorithm. The proposed RVSS-PCSA algorithm equalizes the received carrier wiped-off signal with locally generated C/A code.

Keywords: adaptive PCSA, detection and estimation, GPS signal acquisition, GPS software receiver

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Authors: Patrick Cormier, Cesar Meylan, Matt Jensen, Dana Agar-Newman, Chloe Werle, Ming-Chang Tsai, Marc Klimstra

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Sprint-derived horizontal force-velocity-power (FVP) profiles can be developed with adequate validity and reliability with satellite (GPS/GNSS) systems. However, FVP metrics are sensitive to small nuances in data processing procedures such that minor differences in defining the onset and end of the sprint could result in different FVP metric outcomes. Furthermore, in team-sports, there is a requirement for rapid analysis and feedback of results from multiple athletes, therefore developing standardized and automated methods to improve the speed, efficiency and reliability of this process are warranted. Thus, the purpose of this study was to compare different methods of sprint end detection on the development of FVP profiles from 10Hz GPS/GNSS data through goodness-of-fit and intertrial reliability statistics. Seventeen national team female soccer players participated in the FVP protocol which consisted of 2x40m maximal sprints performed towards the end of a soccer specific warm-up in a training session (1020 hPa, wind = 0, temperature = 30°C) on an open grass field. Each player wore a 10Hz Catapult system unit (Vector S7, Catapult Innovations) inserted in a vest in a pouch between the scapulae. All data were analyzed following common procedures. Variables computed and assessed were the model parameters, estimated maximal sprint speed (MSS) and the acceleration constant τ, in addition to horizontal relative force (F₀), velocity at zero (V₀), and relative mechanical power (Pmax). The onset of the sprints was standardized with an acceleration threshold of 0.1 m/s². The sprint end detection methods were: 1. Time when peak velocity (MSS) was achieved (zero acceleration), 2. Time after peak velocity drops by -0.4 m/s, 3. Time after peak velocity drops by -0.6 m/s, and 4. When the integrated distance from the GPS/GNSS signal achieves 40-m. Goodness-of-fit of each sprint end detection method was determined using the residual sum of squares (RSS) to demonstrate the error of the FVP modeling with the sprint data from the GPS/GNSS system. Inter-trial reliability (from 2 trials) was assessed utilizing intraclass correlation coefficients (ICC). For goodness-of-fit results, the end detection technique that used the time when peak velocity was achieved (zero acceleration) had the lowest RSS values, followed by -0.4 and -0.6 velocity decay, and 40-m end had the highest RSS values. For intertrial reliability, the end of sprint detection techniques that were defined as the time at (method 1) or shortly after (method 2 and 3) when MSS was achieved had very large to near perfect ICC and the time at the 40 m integrated distance (method 4) had large to very large ICCs. Peak velocity was reached at 29.52 ± 4.02-m. Therefore, sport scientists should implement end of sprint detection either when peak velocity is determined or shortly after to improve goodness of fit to achieve reliable between trial FVP profile metrics. Although, more robust processing and modeling procedures should be developed in future research to improve sprint model fitting. This protocol was seamlessly integrated into the usual training which shows promise for sprint monitoring in the field with this technology.

Keywords: automated, biomechanics, team-sports, sprint

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Authors: Birmohan Singh, V.K.Jain

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Computer aided diagnosis systems provide vital opinion to radiologists in the detection of early signs of breast cancer from mammogram images. Masses and microcalcifications, architectural distortions are the major abnormalities. In this paper, a computer aided diagnosis system has been proposed for distinguishing abnormal mammograms with architectural distortion from normal mammogram. Four types of texture features GLCM texture, GLRLM texture, fractal texture and spectral texture features for the regions of suspicion are extracted. Support Vector Machine has been used as classifier in this study. The proposed system yielded an overall sensitivity of 96.47% and accuracy of 96% for the detection of abnormalities with mammogram images collected from Digital Database for Screening Mammography (DDSM) database.

Keywords: architecture distortion, mammograms, GLCM texture features, GLRLM texture features, support vector machine classifier

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Authors: Assma Azeroual, Karim Afdel, Mohamed El Hajji, Hassan Douzi

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Key frame extraction methods select the most representative frames of a video, which can be used in different areas of video processing such as video retrieval, video summary, and video indexing. In this paper we present a novel approach for extracting key frames from video sequences. The frame is characterized uniquely by his contours which are represented by the dominant blocks. These dominant blocks are located on the contours and its near textures. When the video frames have a noticeable changement, its dominant blocks changed, then we can extracte a key frame. The dominant blocks of every frame is computed, and then feature vectors are extracted from the dominant blocks image of each frame and arranged in a feature matrix. Singular Value Decomposition is used to calculate sliding windows ranks of those matrices. Finally the computed ranks are traced and then we are able to extract key frames of a video. Experimental results show that the proposed approach is robust against a large range of digital effects used during shot transition.

Keywords: FSDWT, key frame extraction, shot detection, singular value decomposition

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

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

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

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Authors: Jessica Wood, Serge Desmarais

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There has been recent resurgence in the popular and academic interest of consensual non-monogamous (CNM) relationships- an umbrella term that defines relationships in which each partner has openly agreed to engage in additional romantic and/or sexual relationships outside of their primary partnership. Despite an increase in the academic study of CNM, little psychological attention has been paid to the study of CNM, with the consideration of these relationships commonly occurring within related social science disciplines such as sociology or anthropology. As a discipline, psychology has a history of conducting research in the area of intimate relationships, and psychologists have amassed a wealth of theoretical knowledge in this field. However, historically individuals who engage in "alternative" sexual and romantic behaviours, such as non-heterosexual sex or sex with multiple partners have been pathologized within psychological research. Individuals in CNM relationships or individuals identifying as lesbian, gay, bisexual, trans or queer have often been excluded from research or “othered” in psychological interpretations of what healthy relationships entail. Thus, our current theoretical understandings of romantic relationships are limited to heterosexual, monogamous relationships. The goal of this presentation is to examine commonly cited components of relationship satisfaction (e.g., commitment, communication) and to critically assess how CNM experiences are presented in, or missing from, the psychological literature on romantic relationships. Additionally, the presentation will also consider how CNM relationships may add to our understanding or enhancement of traditional psychological theories and address issues related to heteronormativity and mononormativity within the discipline. Finally, we will close with a consideration of additional theoretical perspectives that may aid in our understanding of CNM relationships and suggest directions for future research.

Keywords: heteronormativity, mononormativity, psychological research, diverse relationships, gender, sexuality, feminism, queer theory

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Authors: Masrur Alam Khan

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The purpose of this study was to examine the dyadic interaction techniques that social media users utilize to reduce uncertainty in their day to day business engagements in the absence of their physical interaction. The study empirically tested assumptions of uncertainty reduction theory while addressing self-disclosure, seeking questions to develop consensus, and subsequently to achieve intimacy in very conducive environment. Moreover, this study examined the effect of dyadic interaction through social media among business community while identifying the strength of their reciprocity in relationships and compares it with those having no dyadic relations due to absence of social media. Using socio-metric survey, the study revealed a better understanding of their partners for upholding their professional relations more credible. A sample of unacquainted, both male and female, was randomly asked questions regarding their nature of dyadic interaction within their office while using social media (face-to-face, visual CMC (webcam) or text-only). Primary results explored that the social media users develop their better know-how about their professional obligations to reduce ambiguity and align with one to one interact.

Keywords: dyadic-interaction, social media, uncertainty reduction, socio-metric survey, self-disclosure, intimacy, reciprocity in relationship

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Authors: Kakali Roy, Sahana P. Raju, Subhra Dhar, Sandipan Dhar

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Introduction: Xeroderma pigmentosa (XP) is a rare inherited (autosomal recessive) disease resulting from impairment in DNA repair that involves recognition and repair of ultraviolet radiation (UVR) induced DNA damage in the nucleotide excision repair pathway. Which results in increased photosensitivity, UVR induced damage to skin and eye, increased susceptibility of skin and ocular cancer, and progressive neurodegeneration in some patients. XP is present worldwide, with higher incidence in areas having frequent consanguinity. Being extremely rare, there is limited literature on XP and associated complications. Here, the clinico-pathological experience (spectrum of clinical presentation, histopathological findings of malignant skin lesions, and progression) of managing 8 cases of XP is presented. Methodology: A retrospective study was conducted in a pediatric tertiary care hospital in eastern India during a ten-year period from 2013 to 2022. A clinical diagnosis was made based on severe sun burn or premature photo-aging and/or onset of cutaneous malignancies at early age (1st decade) in background of consanguinity and autosomal recessive inheritance pattern in family. Results: The mean age of presentation was 1.2 years (range of 7month-3years), while three children presented during their infancy. Male to female ratio was 5:3, and all were born of consanguineous marriage. They presented with dermatological manifestations (100%) followed by ophthalmic (75%) and/or neurological symptoms (25%). Patients had normal skin at birth but soon developed extreme sensitivity to UVR in the form of exaggerated sun tanning, burning, and blistering on minimal sun exposure, followed by abnormal skin pigmentation like freckles and lentiginosis. Subsequently, over time there was progressive xerosis, atrophy, wrinkling, and poikiloderma. Six patients had varied degree of ocular involvement, while three of them had severe manifestation, including madarosis, tylosis, ectropion, Lagopthalmos, Pthysis bulbi, clouding and scarring of the cornea with complete or partial loss of vision, and ophthalmic malignancies. 50% (n=4) cases had skin and ocular pre-malignant (actinic keratosis) and malignant lesions, including melanoma and non melanoma skin cancer (NMSC) like squamous cell carcinoma (SCC) and basal cell carcinoma (BCC) in their early childhood. One patient had simultaneous occurrence of multiple malignancies together (SCC, BCC, and melanoma). Subnormal intelligence was noticed as neurological feature, and none had sensory neural hearing loss, microcephaly, neuroregression, or neurdeficit. All the patients had been being managed by a multidisciplinary team of pediatricians, dermatologists, ophthalmologists, neurologists and psychiatrists. Conclusion: Although till date there is no complete cure for XP and the disease is ultimately fatal. But increased awareness, early diagnosis followed by persistent vigorous protection from UVR, and regular screening for early detection of malignancies along with psychological support can drastically improve patients’ quality of life and life expectancy. Further research is required on formulating optimal management of XP, specifically the role and possibilities of gene therapy in XP.

Keywords: childhood malignancies, dermato-pathological findings, eastern India, Xeroderma pigmentosa

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Authors: Hamid Falaki, Roya Kelkanlo, Mojtaba Tabatabaei

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The present study aimed at distinguishing the effects of work type on hand dimensions and investigating the relationship between anthropometric dimensions and occupation. The anthropometric data used in study were collected on 12 hand anthropometric dimensions. The participants included 91 males in two groups, namely manual labor job and office workers. All the data were analyzed using SPSS version 16. All measurements were significantly greater than those of office jobs except for the grip diameter obtained from the manual workers. The hand perimeter was the greatest value among the 12 measured dimensions, while the thickness of the side little finger was the smallest one. In four dimensions, namely width of four fingers together from the central hinge; diameter of thumb to face; diameter of index finger to face; hand thickness from index finger revealed the availability of a significant difference between manual labor jobs and office workers. Moreover, no significant relation was observed between weight and stature with hand dimension, which represents the correlation between occupation and the four dimensions. The results of this study showed that the difference between the two occupational groups was significant in terms of the four dimensions. Therefore, it is suggested that tool designers should consider this finding in their designing process.

Keywords: hand dimensions, occupation, tool design, anthropometry

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Authors: Artur Krukowski, Emmanouela Vogiatzaki

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The article presents results from the AF3 project “Advanced Forest Fire Fighting” focused on Unmanned Aircraft Systems (UAS)-based 3D surveillance and 3D area mapping using high-resolution photogrammetric methods from multispectral imaging, also taking advantage of the 3D scanning techniques from the SCAN4RECO project. We also present a proprietary embedded sensor system used for the detection of fire ignitions in the forest using near-infrared based scanner with weight and form factors allowing it to be easily deployed on standard commercial micro-UAVs, such as DJI Inspire or Mavic. Results from real-life pilot trials in Greece, Spain, and Israel demonstrated added-value in the use of UAS for precise and reliable detection of forest fires, as well as high-resolution 3D aerial modeling for accurate quantification of human resources and equipment required for firefighting.

Keywords: forest wildfires, surveillance, fuel volume estimation, firefighting, ignition detectors, 3D modelling, UAV

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Authors: Morsy Ahmed Morsy Ismail

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In this paper, the structure of a coherent homodyne receiver for the Binary Phase Shift Keying (BPSK) Optical Code Division Multiple Access (OCDMA) network is introduced based on the Multi-Length Weighted Modified Prime Code (ML-WMPC) for multimedia applications. The Bit Error Rate (BER) of this homodyne detection is evaluated as a function of the number of active users and the signal to noise ratio for different code lengths according to the multimedia application such as audio, voice, and video. Besides, the Mach-Zehnder interferometer is used as an external phase modulator in homodyne detection. Furthermore, the Multiple Access Interference (MAI) and the receiver noise in a shot-noise limited regime are taken into consideration in the BER calculations.

Keywords: OCDMA networks, bit error rate, multiple access interference, binary phase-shift keying, multimedia

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Authors: May Ling González-Ruiz, Ana Cristina Solís-Solís

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Everyday more people can thrive towards the dream of pursuing a university diploma. This can be more attainable for some than for others who may face different types of limitations. Even though not all limitations come from within the individual but most of the times they come from without it may include the environment, the support of the person’s family, the school – its infrastructure, administrative procedures, and attitudes. This is a qualitative type of research that is developed through a case study. It is based on the experiences of two students who are visually impaired and who have attended a public university in Costa Rica. We enquire about the experiences of these two students in the English as a Foreign Language courses at the university scenario. An in-depth analysis of their lived experiences is presented. Their values, attitudes, and expectations serve as the guiding elements for this research. Findings are presented in light of the Social Justice Approach to inclusive education. Some of the most salient aspects found have to do with the attitudes the students used to face challenges; others point at those elements that may have hindered the learning experience of the persons observed and to those that encouraged them to continue their journey and successfully achieve a diploma.

Keywords: inclusion, case study, visually impaired student, learning experience, social justice approach

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Authors: Tanmay Bisen, Aastha Shayla, Susham Biswas

Abstract:

Oil spills from tankers can cause significant harm to the environment and local communities, as well as have economic consequences. Early predictions of oil spills can help to minimize these impacts. Our proposed system uses machine learning and neural networks to predict potential oil spills by monitoring data from ship Automatic Identification Systems (AIS). The model analyzes ship movements, speeds, and changes in direction to identify patterns that deviate from the norm and could indicate a potential spill. Our approach not only identifies anomalies but also predicts spills before they occur, providing early detection and mitigation measures. This can prevent or minimize damage to the reputation of the company responsible and the country where the spill takes place. The model's performance on the MV Wakashio oil spill provides insight into its ability to detect and respond to real-world oil spills, highlighting areas for improvement and further research.

Keywords: Anomaly Detection, Oil Spill Prediction, Machine Learning, Image Processing, Graph Neural Network (GNN)

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Authors: Mikko Salminen, Niklas Ravaja

Abstract:

Emotional intelligence (EI) consists of skills for monitoring own emotions and emotions of others, skills for discriminating different emotions, and skills for using this information in thinking and actions. EI enhances, for example, work outcomes and organizational climate. We suggest that the role and manifestations of EI should also be studied in real leadership situations, especially during the emotional, social interaction. Leadership is essentially a process to influence others for reaching a certain goal. This influencing happens by managerial processes and computer-mediated communication (e.g. e-mail) but also by face-to-face, where facial expressions have a significant role in conveying emotional information. Persons with high EI are typically perceived more positively, and they have better social skills. We hypothesize, that during social interaction high EI enhances the ability to detect other’s emotional state and controlling own emotional expressions. We suggest, that emotionally intelligent leader’s experience less stress during social leadership situations, since they have better skills in dealing with the related emotional work. Thus the high-EI leaders would be more able to enjoy these situations, but also be more efficient in choosing appropriate expressions for building constructive dialogue. We suggest, that emotionally intelligent leaders show more positive emotional expressions than low-EI leaders. To study these hypotheses we observed performance review discussions of 40 leaders (24 female) with 78 (45 female) of their followers. Each leader held a discussion with two followers. Psychophysiological methods were chosen because they provide objective and continuous data from the whole duration of the discussions. We recorded sweating of the hands (electrodermal activation) by electrodes placed to the fingers of the non-dominant hand to assess the stress-related physiological arousal of the leaders. In addition, facial electromyography was recorded from cheek (zygomaticus major, activated during e.g. smiling) and periocular (orbicularis oculi, activated during smiling) muscles using electrode pairs placed on the left side of the face. Leader’s trait EI was measured with a 360 questionnaire, filled by each leader’s followers, peers, managers and by themselves. High-EI leaders had less sweating of the hands (p = .007) than the low-EI leaders. It is thus suggested that the high-EI leaders experienced less physiological stress during the discussions. Also, high scores in the factor “Using of emotions” were related to more facial muscle activation indicating positive emotional expressions (cheek muscle: p = .048; periocular muscle: p = .076, almost statistically significant). The results imply that emotionally intelligent managers are positively relaxed during s social leadership situations such as a performance review discussion. The current study also highlights the importance of EI in face-to-face social interaction, given the central role facial expressions have in interaction situations. The study also offers new insight to the biological basis of trait EI. It is suggested that the identification, forming, and intelligently using of facial expressions are skills that could be trained during leadership development courses.

Keywords: emotional intelligence, leadership, performance review discussion, psychophysiology, social interaction

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Authors: Anastassis Kozanitis, Diane Leduc, Alain Stockless

Abstract:

This paper presents preliminary results from a two-year funded research program looking to analyze and understand the relationship between high cognitive engagement, higher order cognitive processes employed in situations of complex learning tasks, and the use of active learning pedagogies in engineering undergraduate programs. A mixed method approach was used to gauge student engagement and their cognitive processes when accomplishing complex tasks. Quantitative data collected from the self-report cognitive engagement scale shows that deep learning approach is positively correlated with high levels of complex learning tasks and the level of student engagement, in the context of classroom active learning pedagogies. Qualitative analyses of in depth face-to-face interviews reveal insights into the mechanisms influencing students’ cognitive processes when confronted with open-ended problem resolution. Findings also support evidence that students will adjust their level of cognitive engagement according to the specific didactic environment.

Keywords: cognitive engagement, deep and shallow strategies, engineering programs, higher order cognitive processes

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Authors: Zhongzhen Luo, Saeid Habibi, Martin v. Mohrenschildt

Abstract:

Self-driving vehicle require a high level of situational awareness in order to maneuver safely when driving in real world condition. This paper presents a LiDAR based real time perception system that is able to process sensor raw data for multiple target detection and tracking in dynamic environment. The proposed algorithm is nonparametric and deterministic that is no assumptions and priori knowledge are needed from the input data and no initializations are required. Additionally, the proposed method is working on the three-dimensional data directly generated by LiDAR while not scarifying the rich information contained in the domain of 3D. Moreover, a fast and efficient for real time clustering algorithm is applied based on a radially bounded nearest neighbor (RBNN). Hungarian algorithm procedure and adaptive Kalman filtering are used for data association and tracking algorithm. The proposed algorithm is able to run in real time with average run time of 70ms per frame.

Keywords: lidar, segmentation, clustering, tracking

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Authors: Subrat Partha Sarathi Pattnaik, Rajan N.K.S.

Abstract:

Integrated rocket ramjet engines are highly suitable for long range missile applications. Designing the fixed geometry intakes for such missiles that can operate efficiently over a range of operating conditions is a highly challenging task. Hence, the present study aims to evaluate the effect of throat design on the performance of a rectangular mixed compression intake for operation in the Mach number range of 1.8 – 2.5. The analysis has been carried out at four different Mach numbers of 1.8, 2, 2.2, 2.5 and two angle-of-attacks of +5 and +10 degrees. For the throat design, three different throat heights have been considered, one corresponding to a 3- external shock design and two heights corresponding to a 2-external shock design leading to different internal contraction ratios. The on-design Mach number for the study is M 2.2. To obtain the viscous flow field in the intake, the theoretical designs have been considered for computational fluid dynamic analysis. For which Favre averaged Navier- Stokes (FANS) equations with two equation SST k-w model have been solved. The analysis shows that for zero angle of attack at on-design and high off-design Mach number operations the three-ramp design leads to a higher total pressure recovery (TPR) compared to the two-ramp design at both contraction ratios maintaining same mass flow ratio (MFR). But at low off-design Mach numbers the total pressure shows an opposite trend that is maximum for the two-ramp low contraction ratio design due to lower shock loss across the external shocks similarly the MFR is higher for low contraction ratio design as the external ramp shocks move closer to the cowl. At both the angle of attack conditions and complete range of Mach numbers the total pressure recovery and mass flow ratios are highest for two ramp low contraction design due to lower stagnation pressure loss across the detached bow shock formed at the ramp and lower mass spillage. Hence, low contraction design is found to be suitable for higher off-design performance.

Keywords: internal contraction ratio, mass flow ratio, mixed compression intake, performance, supersonic flows

Procedia PDF Downloads 90