Search results for: crowd detecting and tracking

Authors: Corey F. Fitzgerald

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This study provides a comprehensive examination of the biomechanical sequencing inherent in pitching motions, coupled with an advanced methodology for interpreting gathered data to inform programming strategies. The analysis is conducted utilizing state-of-the-art biomechanical laboratory equipment capable of detecting subtle changes and deviations, facilitating highly informed decision-making processes. Through this presentation, the intricate dynamics of pitching sequences are meticulously discussed to highlight the complex movement patterns accessible and actionable for performance enhancement purposes in the weight room.

Keywords: sport science, applied biomechanics, strength and conditioning, applied research

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Authors: A. Oukaci, R. Toufouti, D. Dib, l. Atarsia

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This article presents a multitude of alternative techniques to control the vector control, namely the nonlinear control and sliding mode control. Moreover, the implementation of their control law applied to the high-performance to the induction motor with the objective to improve the tracking control, ensure stability robustness to parameter variations and disturbance rejection. Tests are performed numerical simulations in the Matlab/Simulink interface, the results demonstrate the efficiency and dynamic performance of the proposed strategy.

Keywords: Induction Motor (IM), Non-linear Control (NLC), Sliding Mode Control (SMC), nonlinear sliding surface

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Authors: Warnakulasuriya Arachichige Malisha Ann Rosary Fernando, Udalamatta Gamage Omila Chalanka Jinadasa, Bihini Pabasara Amandi Amarasinghe, Manul Thisuraka Mandalawatta, Uthpala Samarakoon, Manori Gamage

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The surge in sexually transmitted diseases (STDs) has become a critical public health crisis demanding urgent attention and action. Like many other nations, Sri Lanka is grappling with a significant increase in STDs due to a lack of education and awareness regarding their dangers. Presently, the available applications for tracking and managing STDs cover only a limited number of easily detectable infections, resulting in a significant gap in effectively controlling their spread. To address this gap and combat the rising STD rates, it is essential to leverage technology and data. Employing technology to enhance the tracking and management of STDs is vital to prevent their further propagation and to enable early intervention and treatment. This requires adopting a comprehensive approach that involves raising public awareness about the perils of STDs, improving access to affordable healthcare services for early detection and treatment, and utilizing advanced technology and data analysis. The proposed mobile application aims to cater to a broad range of users, including STD patients, recovered individuals, and those unaware of their STD status. By harnessing cutting-edge technologies like image detection, symptom-based identification, prevention methods, doctor and clinic recommendations, and virtual counselor chat, the application offers a holistic approach to STD management. In conclusion, the escalating STD rates in Sri Lanka and across the globe require immediate action. The integration of technology-driven solutions, along with comprehensive education and healthcare accessibility, is the key to curbing the spread of STDs and promoting better overall public health.

Keywords: STD, machine learning, NLP, artificial intelligence

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Authors: Payton Small

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In response to increasing demographic diversity, many U.S. organizations have implemented diversity initiatives to increase the representation of women and ethnic minorities. While these initiatives aim to promote more fair and positive outcomes for underrepresented minorities (URMs) widespread backlash against these policies can negatively impact the groups of individuals that are supposed to be supported by them. A recent theory-based analysis of best practices for instituting diversity policies proposes an "inclusion for all" approach that negotiates the oft-divergent goals and motivations of both marginalized and dominant group members in these contexts. Empirical work finds that "inclusion for all" strategies decrease White's tendency to implicitly associate diversity with exclusion and increased their personal endorsement of diversity initiatives. Similarly, Whites report higher belongingness when considering an inclusion for all approach to diversity versus a colorblind approach. While inclusion-for-all approaches may effectively increase Whites' responsiveness to diversity efforts, the downstream consequences of implementing these policies on URM's have yet to be explored. The current research investigated how inclusion-for-all diversity framing influences Whites' sensitivity to detecting discrimination against URM's as well as perceptions of reverse discrimination against Whites. Lastly, the current research looked at how URM's respond to inclusion-for-all diversity approaches. Three studies investigated the impact of inclusion-for-all diversity framing on perceptions of discrimination against Whites and URM's in a company setting. Two separate mechanisms by which exposure to an inclusion-for-all diversity statement might differentially influence perceptions of discrimination for URMs and Whites were also tested. In Studies 1 and 2, exposure to an inclusion-for-all diversity approach reduced Whites' concerns about reverse discrimination and heightened sensitivity to detecting discrimination against URM's. These effects were mediated by decreased concerns about zero-sum outcomes at the company. Study 3 found that racial minorities are concerned about increased discrimination at a company with an inclusion-for-all diversity statement and that this effect is mediated by decreased feelings of belonging at the company. In sum, companies that adopt an inclusion-for-all approach to diversity implementation reduce Whites' backlash and the negative downstream consequences associated with such backlash; however, racial minorities feel excluded and expect heightened experiences of discrimination at these same companies.

Keywords: diversity, intergroup relations, organizational social psychology, zero-sum

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Authors: Robert Vanderburg, Michael Cowling, Nicholas Gibson

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Mathematics is one of the core subjects taught in the Australian K-12 education system and is considered an important component for future studies in areas such as engineering and technology. In addition to this, Australia has been a world leader in distance education due to the vastness of its geographic landscape. Despite this, research is still needed on distance math instruction. Even though delivery of curriculum has given way to online studies, and there is a resultant push for computer-based (PC, tablet, smartphone) math instruction, much instruction still involves practice problems similar to those original curriculum packs, without the ability for students to self-regulate their learning using the full interactive capabilities of these devices. Given this need, this paper addresses issues students have during online instruction. This study consists of 32 students struggling with mathematics enrolled in a math tutorial conducted in an online setting. The study used a case study design to understand some of the blockades hindering the students’ success. Data was collected by tracking students practice and quizzes, tracking engagement of the site, recording one-on-one tutorials, and collecting data from interviews with the students. Results revealed that when students have cognitively straining tasks in an online instructional setting, the first thing to dissipate was their ability to self-regulate. The results also revealed that instructors could ameliorate the situation and provided useful data on strategies that could be used for designing future online tasks. Specifically, instructors could utilize cognitive dissonance strategies to reduce the cognitive drain of the tasks online. They could segment the instruction process to reduce the cognitive demands of the tasks and provide in-depth self-regulatory training, freeing mental capacity for the mathematics content. Finally, instructors could provide specific scheduling and assignment structure changes to reduce the amount of student centered self-regulatory tasks in the class. These findings will be discussed in more detail and summarized in a framework that can be used for future work.

Keywords: digital education, distance education, mathematics education, self-regulation

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Authors: Tesfaye Mengistu

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Power cables play a crucial role in the transmission and distribution of electrical energy. As the electricity generation, transmission, distribution, and storage systems become smarter, there is a growing emphasis on incorporating intelligent approaches to ensure the reliability of power cables. Various types of electrical cables are employed for transmitting and distributing electrical energy, with cross-linked polyethylene (XLPE) cables being widely utilized due to their exceptional electrical and mechanical properties. However, insulation defects can occur in XLPE cables due to subpar manufacturing techniques during production and cable joint installation. To address this issue, experts have proposed different methods for monitoring XLPE cables. Some suggest the use of interdigital capacitive (IDC) technology for online monitoring, while others propose employing continuous wave (CW) terahertz (THz) imaging systems to detect internal defects in XLPE plates used for power cable insulation. In this study, we have developed models that employ a custom dataset collected locally to classify the physical safety status of individual power cables. Our models aim to replace physical inspections with computer vision and image processing techniques to classify defective power cables from non-defective ones. The implementation of our project utilized the Python programming language along with the TensorFlow package and a convolutional neural network (CNN). The CNN-based algorithm was specifically chosen for power cable defect classification. The results of our project demonstrate the effectiveness of CNNs in accurately classifying power cable defects. We recommend the utilization of similar or additional datasets to further enhance and refine our models. Additionally, we believe that our models could be used to develop methodologies for detecting power cable defects from live video feeds. We firmly believe that our work makes a significant contribution to the field of power cable inspection and maintenance. Our models offer a more efficient and cost-effective approach to detecting power cable defects, thereby improving the reliability and safety of power grids.

Keywords: artificial intelligence, computer vision, defect detection, convolutional neural net

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Authors: Ben Abdallah Aicha

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In this work we show a H∞ synthesis method which enables us to calculate a feedback controller according to considerations of stability robustness and disturbance rejection translated on to the open loop response. However, it may happen that we have an additional specification on the closed loop response relating to tracking of the reference trajectory. The H∞ synthesis has the advantage of offering increased specifications in robustness stability. Implemented for a DC motor, it offers invaluable performance in speed control in both directions of rotation.

Keywords: H∞ synthesis, DC motor, robustness stability, performance conditions

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Authors: Myung Hwan Na, Ho- Chun Song, EunHee Hong

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We widely use normal linear mixed-effects model to analysis data in repeated measurement. In case of detecting heteroscedasticity and the non-normality of the population distribution at the same time, normal linear mixed-effects model can give improper result of analysis. To achieve more robust estimation, we use heavy tailed linear mixed-effects model which gives more exact and reliable analysis conclusion than standard normal linear mixed-effects model.

Keywords: reliability, tires, field data, linear mixed-effects model

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Authors: Arsalan Hassan Pour, Mansoureh Jeihani, Samira Ahangari

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Distracted driving has been one of the most integral concerns surrounding our daily use of vehicles since the invention of the automobile. While much attention has been recently given to cell phones related distraction, commercial billboards along roads are also candidates for drivers' visual and cognitive distractions, as they may take drivers’ eyes from the road and their minds off the driving task to see, perceive and think about the billboard’s content. Using a driving simulator and a head-mounted eye-tracking system, speed change, acceleration, deceleration, throttle response, collision, lane changing, and offset from the center of the lane data along with gaze fixation duration and frequency data were collected in this study. Some 92 participants from a fairly diverse sociodemographic background drove on a simulated freeway in Baltimore, Maryland area and were exposed to three different billboards to investigate the effects of billboards on drivers’ behavior. Participants glanced at the billboards several times with different frequencies, the maximum of which occurred on the billboard with the highest cognitive load. About 74% of the participants didn’t look at billboards for more than two seconds at each glance except for the billboard with a short visible area. Analysis of variance (ANOVA) was performed to find the variations in driving behavior when they are invisible, readable, and post billboards area. The results show a slight difference in speed, throttle, brake, steering velocity, and lane changing, among different areas. Brake force and deviation from the center of the lane increased in the readable area in comparison with the visible area, and speed increased right after each billboard. The results indicated that billboards have a significant effect on driving performance and visual attention based on their content and visibility status. Generalized linear model (GLM) analysis showed no connection between participants’ age and driving experience with gaze duration. However, the visible distance of the billboard, gender, and billboard content had a significant effect on gaze duration.

Keywords: ANOVA, billboards, distracted driving, drivers' behavior, driving simulator, eye-Tracking system, GLM

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Authors: Mohammad Zavid Parvez, Manoranjan Paul

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A seizure prediction method is proposed by extracting global features using phase correlation between adjacent epochs for detecting relative changes and local features using fluctuation/deviation within an epoch for determining fine changes of different EEG signals. A classifier and a regularization technique are applied for the reduction of false alarms and improvement of the overall prediction accuracy. The experiments show that the proposed method outperforms the state-of-the-art methods and provides high prediction accuracy (i.e., 97.70%) with low false alarm using EEG signals in different brain locations from a benchmark data set.

Keywords: Epilepsy, seizure, phase correlation, fluctuation, deviation.

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Authors: Seyed Hossein Hosseini, Seyed Majid Hashemzadeh

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Solar energy is one of the remarkable renewable energy sources that have particular characteristics such as unlimited, no environmental pollution, and free access. Generally, solar energy can be used in thermal and photovoltaic (PV) types. The cost of installation of the PV system is very high. Additionally, due to dependence on environmental situations such as solar radiation and ambient temperature, electrical power generation of this system is unpredictable and without power electronics devices, there is no guarantee to maximum power delivery at the output of this system. Maximum power point tracking (MPPT) should be used to achieve the maximum power of a PV string. MPPT is one of the essential parts of the PV system which without this section, it would be impossible to reach the maximum amount of the PV string power and high losses are caused in the PV system. One of the noticeable challenges in the problem of MPPT is the partial shading conditions (PSC). In PSC, the output photocurrent of the PV module under the shadow is less than the PV string current. The difference between the mentioned currents passes from the module's internal parallel resistance and creates a large negative voltage across shaded modules. This significant negative voltage damages the PV module under the shadow. This condition is called hot-spot phenomenon. An anti-paralleled diode is inserted across the PV module to prevent the happening of this phenomenon. This diode is known as the bypass diode. Due to the performance of the bypass diode under PSC, the P-V curve of the PV string has several peaks. One of the P-V curve peaks that makes the maximum available power is the global peak. Model-based Global MPPT (GMPPT) methods can estimate the optimal point with higher speed than other GMPPT approaches. Centralized, modular, and interleaved DC-DC converter topologies are the significant structures that can be used for GMPPT at a PV string. there are some problems in the centralized structure such as current mismatch losses at PV sting, loss of power of the shaded modules because of bypassing by bypass diodes under PSC, needing to series connection of many PV modules to reach the desired voltage level. In the modular structure, each PV module is connected to a DC-DC converter. In this structure, by increasing the amount of demanded power from the PV string, the number of DC-DC converters that are used at the PV system will increase. As a result, the cost of the modular structure is very high. We can implement the model-based GMPPT through the multi-input interleaved boost DC-DC converter to increase the power extraction from the PV string and reduce hot-spot and current mismatch error in a PV string under different environmental condition and variable load circumstances. The interleaved boost DC-DC converter has many privileges than other mentioned structures, such as high reliability and efficiency, better regulation of DC voltage at DC link, overcome the notable errors such as module's current mismatch and hot spot phenomenon, and power switches voltage stress reduction.

Keywords: solar energy, photovoltaic systems, interleaved boost converter, maximum power point tracking, model-based method, partial shading conditions

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Authors: Nora Geczy

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In today’s architectural practice, during the process of designing public, educational, healthcare and cultural space, human-centered architectural designs helping spatial orientation, safe space usage and the appropriate spatial sequence of actions are gaining increasing importance. Related to the methodology of designing public buildings, several scientific experiments in spatial recognition, spatial analysis and spatial psychology with regard to the components of space producing mental and physiological effects have been going on at the Department of Architectural Design and the Interdisciplinary Student Workshop (IDM) at the Széchenyi István University, Győr since 2013. Defining the creation of preventive, anticipated spatial design and the architectural tools of spatial comfort of public buildings and their practical usability are in the limelight of our research. In the experiments applying eye-tracking cameras, we studied the way public spaces are used, especially concentrating on the characteristics of spatial behaviour, orientation, recognition, the sequence of actions, and space usage. Along with the role of mental maps, human perception, and interaction problems in public spaces (at railway stations, galleries, and educational institutions), we analyzed the spatial situations influencing psychological and ergonomic factors. We also analyzed the eye movements of the experimental subjects in dynamic situations, in spatial procession, using stairs and corridors. We monitored both the consequences and the distorting effects of the ocular dominance of the right eye on spatial orientation; we analyzed the gender-based differences of women and men’s orientation, stress-inducing spaces, spaces affecting concentration and the spatial situation influencing territorial behaviour. Based on these observations, we collected the components of creating public interior spaces, which -according to our theory- contribute to the optimal usability of public spaces. We summed up our research in criteria for design, including 10 points. Our further goals are testing design principles needed for optimizing orientation and space usage, their discussion, refinement, and practical usage.

Keywords: architecture, eye-tracking, human-centered spatial design, public interior spaces, visual perception

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Authors: Petra Hypšová, Martin Seitl

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One of the challenges of forensic psychology is to detect deception during a face-to-face interview. In addition to the classical approaches of monitoring the utterance and its components, detection is also sought by observing behavioral and physiological changes that occur as a result of the increased emotional and cognitive load caused by the production of distorted information. Typical are changes in facial temperature, eye movements and their fixation, pupil dilation, emotional micro-expression, heart rate and its variability. Expanding technological capabilities have opened the space to detect these psychophysiological changes and behavioral manifestations through non-contact technologies that do not interfere with face-to-face interaction. Non-contact deception detection methodology is still in development, and there is a lack of studies that combine multiple non-contact technologies to investigate their accuracy, as well as studies that show how different types of lies produced by different interviewers affect physiological and behavioral changes. The main objective of this study is to apply a specific non-contact technology for deception detection. The next objective is to investigate scenarios in which non-contact deception detection is possible. A series of psychophysiological experiments using infrared thermal imaging, eye tracking and behavioral analysis with FaceReader 9.0 software was used to achieve our goals. In the laboratory experiment, 16 adults (12 women, 4 men) between 18 and 35 years of age (SD = 4.42) were instructed to produce alternating prepared and spontaneous truths and lies. The baseline of each proband was also measured, and its results were compared to the experimental conditions. Because the personality of the examiner (particularly gender and facial appearance) to whom the subject is lying can influence physiological and behavioral changes, the experiment included four different interviewers. The interviewer was represented by a photograph of a face that met the required parameters in terms of gender and facial appearance (i.e., interviewer likability/antipathy) to follow standardized procedures. The subject provided all information to the simulated interviewer. During follow-up analyzes, facial temperature (main ROIs: forehead, cheeks, the tip of the nose, chin, and corners of the eyes), heart rate, emotional expression, intensity and fixation of eye movements and pupil dilation were observed. The results showed that the variables studied varied with respect to the production of prepared truths and lies versus the production of spontaneous truths and lies, as well as the variability of the simulated interviewer. The results also supported the assumption of variability in physiological and behavioural values during the subject's resting state, the so-called baseline, and the production of prepared and spontaneous truths and lies. A series of psychophysiological experiments provided evidence of variability in the areas of interest in the production of truths and lies to different interviewers. The combination of technologies used also led to a comprehensive assessment of the physiological and behavioral changes associated with false and true statements. The study presented here opens the space for further research in the field of lie detection with non-contact technologies.

Keywords: emotional expression decoding, eye-tracking, functional infrared thermal imaging, non-contact deception detection, psychophysiological experiment

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Authors: Y. Kavanagh, N. O'Hara, R. Palmer, P. Lowe, D. Rafferty

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Physical Physics is a physics education methodology for games programfmes that integrates physical activity with movement tracking and modelling. It significantly enhances the learning experience and it is effective in illustrating how physics is core in games design and programming, while allowing students to be active participants and take ownership of the learning process. It has been successfully piloted with undergraduate students studying Games Development.

Keywords: activity, enhanced learning, game development, physics

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Authors: Abdullah Alnutayfat, Alexander Sutin, Dong Liu

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Wind turbine has become one of the most popular energy productions. However, failure of blades and maintenance costs evolve into significant issues in the wind power industry, so it is essential to detect the initial blade defects to avoid the collapse of the blades and structure. This paper aims to apply modulation of high-frequency blade vibrations by low-frequency blade rotation, which is close to the known Vibro-Acoustic Modulation (VAM) method. The high-frequency wideband blade vibration is produced by the interaction of the surface blades with the environment air turbulence, and the low-frequency modulation is produced by alternating bending stress due to gravity. The low-frequency load of rotational wind turbine blades ranges between 0.2-0.4 Hz and can reach up to 2 Hz for strong wind. The main difference between this study and previous ones on VAM methods is the use of a wideband vibration signal from the blade's natural vibrations. Different features of the vibroacoustic modulation are considered using a simple model of breathing crack. This model considers the simple mechanical oscillator, where the parameters of the oscillator are varied due to low-frequency blade rotation. During the blade's operation, the internal stress caused by the weight of the blade modifies the crack's elasticity and damping. The laboratory experiment using steel samples demonstrates the possibility of VAM using a probe wideband noise signal. A cycle load with a small amplitude was used as a pump wave to damage the tested sample, and a small transducer generated a wideband probe wave. The received signal demodulation was conducted using the Detecting of Envelope Modulation on Noise (DEMON) approach. In addition, the experimental results were compared with the modulation index (MI) technique regarding the harmonic pump wave. The wideband and traditional VAM methods demonstrated similar sensitivity for earlier detection of invisible cracks. Importantly, employing a wideband probe signal with the DEMON approach speeds up and simplifies testing since it eliminates the need to conduct tests repeatedly for various harmonic probe frequencies and to adjust the probe frequency.

Keywords: vibro-acoustic modulation, detecting of envelope modulation on noise, damage, turbine blades

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Authors: Dor Oppenheim, Yael Edan, Guy Shani

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This paper presents an image analysis algorithm to detect and count yellow tomato flowers in a greenhouse with uneven illumination conditions, complex growth conditions and different flower sizes. The algorithm is designed to be employed on a drone that flies in greenhouses to accomplish several tasks such as pollination and yield estimation. Detecting the flowers can provide useful information for the farmer, such as the number of flowers in a row, and the number of flowers that were pollinated since the last visit to the row. The developed algorithm is designed to handle the real world difficulties in a greenhouse which include varying lighting conditions, shadowing, and occlusion, while considering the computational limitations of the simple processor in the drone. The algorithm identifies flowers using an adaptive global threshold, segmentation over the HSV color space, and morphological cues. The adaptive threshold divides the images into darker and lighter images. Then, segmentation on the hue, saturation and volume is performed accordingly, and classification is done according to size and location of the flowers. 1069 images of greenhouse tomato flowers were acquired in a commercial greenhouse in Israel, using two different RGB Cameras – an LG G4 smartphone and a Canon PowerShot A590. The images were acquired from multiple angles and distances and were sampled manually at various periods along the day to obtain varying lighting conditions. Ground truth was created by manually tagging approximately 25,000 individual flowers in the images. Sensitivity analyses on the acquisition angle of the images, periods throughout the day, different cameras and thresholding types were performed. Precision, recall and their derived F1 score were calculated. Results indicate better performance for the view angle facing the flowers than any other angle. Acquiring images in the afternoon resulted with the best precision and recall results. Applying a global adaptive threshold improved the median F1 score by 3%. Results showed no difference between the two cameras used. Using hue values of 0.12-0.18 in the segmentation process provided the best results in precision and recall, and the best F1 score. The precision and recall average for all the images when using these values was 74% and 75% respectively with an F1 score of 0.73. Further analysis showed a 5% increase in precision and recall when analyzing images acquired in the afternoon and from the front viewpoint.

Keywords: agricultural engineering, image processing, computer vision, flower detection

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Authors: Ashwaq Alsulami, Jianhua Shao

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Various organisations often need to understand discussions on social media, such as what trending topics are and characteristics of the people engaged in the discussion. A number of approaches have been proposed to extract attributes that would characterise a discussion group. However, these approaches are largely based on supervised learning, and as such they require a large amount of labelled data. We propose an approach in this paper that does not require labelled data, but rely on lexical sources to detect meaningful attributes for online discussion groups. Our findings show an acceptable level of accuracy in detecting attributes for Twitter discussion groups.

Keywords: attributed community, attribute detection, community, social network

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Authors: A. J. Babajanyan, T. A. Abrahamyan, H. A. Minasyan, K. V. Nerkararyan

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Optical radiation emitted from a metal-coated fiber tip apex at liquid-air interface was measured. The intensity of the output radiation was strongly depending on the relative position of the tip to a liquid-air interface and varied with surface fluctuations. This phenomenon permits in-situ real-time investigation of nano-metric vibrations of the liquid surface and provides a basis for development of various origin ultrasensitive vibration detecting sensors. The described method can be used for detection of week seismic vibrations.

Keywords: fiber-tip, liquid-air interface, nano vibration, opto-mechanical sensor

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Authors: Y. Zheng, M. Busi, A. F. Pedersen, M. A. Beltran, C. Gundlach

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X-ray phase contrast imaging has shown to yield a better contrast compared to conventional attenuation X-ray imaging, especially for soft tissues in the medical imaging energy range. This can potentially lead to better diagnosis for patients. However, phase contrast imaging has mainly been performed using highly brilliant Synchrotron radiation, as it requires high coherence X-rays. Many research teams have demonstrated that it is also feasible using a laboratory source, bringing it one step closer to clinical use. Nevertheless, the requirement of fine gratings and high precision stepping motors when using a laboratory source prevents it from being widely used. Recently, a random phase object has been proposed as an analyzer. This method requires a much less robust experimental setup. However, previous studies were done using a particular X-ray source (liquid-metal jet micro-focus source) or high precision motors for stepping. We have been working on a much simpler setup with just small modification of a commercial bench-top micro-CT (computed tomography) scanner, by introducing a piece of sandpaper as the phase analyzer in front of the X-ray source. However, it needs a suitable algorithm for speckle tracking and 3D reconstructions. The precision and sensitivity of speckle tracking algorithm determine the resolution of the system, while the 3D reconstruction algorithm will affect the minimum number of projections required, thus limiting the temporal resolution. As phase contrast imaging methods usually require much longer exposure time than traditional absorption based X-ray imaging technologies, a dynamic phase contrast micro-CT with a high temporal resolution is particularly challenging. Different reconstruction methods, including neural network based techniques, will be evaluated in this project to increase the temporal resolution of the phase contrast micro-CT. A Monte Carlo ray tracing simulation (McXtrace) was used to generate a large dataset to train the neural network, in order to address the issue that neural networks require large amount of training data to get high-quality reconstructions.

Keywords: micro-ct, neural networks, reconstruction, speckle-based x-ray phase contrast

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Authors: Jiri Kysucan, Dusan Klos, Katherine Vomackova, Pavel Koranda, Martin Lovecek, Cestmir Neoral, Roman Havlik

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Aim: The prognosis of patients with pancreatic cancer is poor. The median of survival after establishing diagnosis is 3-11 months without surgical treatment, 13-20 months with surgical treatment depending on the disease stage, 5-year survival is less than 5%. Radical surgical resection remains the only hope of curing the disease. Early diagnosis with valid establishment of tumor resectability is, therefore, the most important aim for patients with pancreatic cancer. The aim of the work is to evaluate the contribution and define the role of 18F-FDG PET/CT in preoperative staging. Material and Methods: In 195 patients (103 males, 92 females, median age 66,7 years, 32-88 years) with a suspect pancreatic lesion, as part of the standard preoperative staging, in addition to standard examination methods (ultrasonography, contrast spiral CT, endoscopic ultrasonography, endoscopic ultrasonographic biopsy), a hybrid 18F-FDG PET/CT was performed. All PET/CT findings were subsequently compared with standard staging (CT, EUS, EUS FNA), with peroperative findings and definitive histology in the operated patients as reference standards. Interpretation defined the extent of the tumor according to TNM classification. Limitations of resectability were local advancement (T4) and presence of distant metastases (M1). Results: PET/CT was performed in a total of 195 patients with a suspect pancreatic lesion. In 153 patients, pancreatic carcinoma was confirmed and of these patients, 72 were not indicated for radical surgical procedure due to local inoperability or generalization of the disease. The sensitivity of PET/CT in detecting the primary lesion was 92.2%, specificity was 90.5%. A false negative finding in 12 patients, a false positive finding was seen in 4 cases, positive predictive value (PPV) 97.2%, negative predictive value (NPV) 76,0%. In evaluating regional lymph nodes, sensitivity was 51.9%, specificity 58.3%, PPV 58,3%, NPV 51.9%. In detecting distant metastases, PET/CT reached a sensitivity of 82.8%, specificity was 97.8%, PPV 96.9%, NPV 87.0%. PET/CT found distant metastases in 12 patients, which were not detected by standard methods. In 15 patients (15.6%) with potentially radically resectable findings, the procedure was contraindicated based on PET/CT findings and the treatment strategy was changed. Conclusion: PET/CT is a highly sensitive and specific method useful in preoperative staging of pancreatic cancer. It improves the selection of patients for radical surgical procedures, who can benefit from it and decreases the number of incorrectly indicated operations.

Keywords: cancer, PET/CT, staging, surgery

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Authors: Youtao Gao, Bingyu Jin, Tanran Zhao, Bo Xu

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The history of satellite navigation can be dated back to the 1960s. From the U.S. Transit system and the Russian Tsikada system to the modern Global Positioning System (GPS) and the Globalnaya Navigatsionnaya Sputnikovaya Sistema (GLONASS), performance of satellite navigation has been greatly improved. Nowadays, the navigation accuracy and coverage of these existing systems have already fully fulfilled the requirement of near-Earth users, but these systems are still beyond the reach of deep space targets. Due to the renewed interest in space exploration, a novel high-precision satellite navigation system is becoming even more important. The increasing demand for such a deep space navigation system has contributed to the emergence of a variety of new constellation architectures, such as the Lunar Global Positioning System. Apart from a Walker constellation which is similar to the one adopted by GPS on Earth, a novel constellation architecture which consists of libration point satellites in the Earth-Moon system is also available to construct the lunar navigation system, which can be called accordingly, the libration point satellite navigation system. The concept of using Earth-Moon libration point satellites for lunar navigation was first proposed by Farquhar and then followed by many other researchers. Moreover, due to the special characteristics of Libration point orbits, an autonomous orbit determination technique, which is called ‘Liaison navigation’, can be adopted by the libration point satellites. Using only scalar satellite-to-satellite tracking data, both the orbits of the user and libration point satellites can be determined autonomously. In this way, the extensive Earth-based tracking measurement can be eliminated, and an autonomous satellite navigation system can be developed for future space exploration missions. The method of state estimate is an unnegligible factor which impacts on the orbit determination accuracy besides type of orbit, initial state accuracy and measurement accuracy. We apply the extended Kalman filter(EKF) and the unscented Kalman filter(UKF) to determinate the orbits of Lagrangian navigation satellites. The autonomous orbit determination errors are compared. The simulation results illustrate that UKF can improve the accuracy and z-axis convergence to some extent.

Keywords: extended Kalman filter, autonomous orbit determination, unscented Kalman filter, navigation constellation

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Authors: Sukhvinder Kaur, Jayanta Bora, Ashok Agarwal, Sangeeta Kaul

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Background: HIV and STI transmission can be prevented if condoms are used properly, but condom tear may lead to infections even if are used consistently. Studies reveal high rates of condom breakage among Female Sex Workers (FSWs). USAID PHFI-PIPPSE is piloting a prevention model among high risk groups at Thane district of Maharashtra, India by implementing prevention and advocacy efforts for such risk behaviors. The current analysis highlights the correlates of condom breakage among FSWs from Thane. Method: A Behavioral Tracking Survey was conducted in 2014-15 among 503 FSWs through probability-based two stage random sampling from 3,660 FSWs at 100 hotspots, to understand levels of high risk behaviors, awareness and exposure to prevention programs. Bi-variate and multivariate-logistic regression methods used to assess the association of condom breakage while having sex with age, STI occurrence, anal sex with clients and alcohol consumption. Only self-reported STIs (Genital sore/ulcer, yellowish/ greenish discharge from vagina with/without foul smell, lower abdominal pain without diarrhea/dysentery or menses) were considered. Major Findings: Results depicted FSWs who reported condom breakage while having sex with any type of partner (paying clients, non-paying partners and other than main partner husband/boyfriend) had significantly high number of STIs (42.3% vs 16.9 %, P, 0.000) and had started sexual relationship in <16 years of age (31.0% vs 16.4 %, P, 0.000). Multivariate analysis after controlling the age at sex, knowledge about HIV and literacy, highlighted significantly higher odds of condom breakage among FSWs who have reported currently suffering with STI [AOR 2.91, 95% CI 1.75 - 4.83; P, 0.000]; who had anal sex with their paying client [AOR 2.59, 95% CI 1.59 - 4.19; P, 0.000]; and who consumed alcohol in the last 12 months [AOR 1.89, 95% CI 1.01 - 3.53; P, 0.047]. Conclusion: Risky behavior like anal sex with paying clients and impact of alcohol while having sex are main factors for condom breakage among young sex workers; and condom breakage leads to STIs. Hence, program interventions should address measures for prevention of condom breakage for HIV/STI prevention.

Keywords: female sex workers, condom breakage, anal sex, young sex workers

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Authors: Mrinal Kanti Bhowmik, Shawli Bardhan Jr., Debotosh Bhattacharjee

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Human skin containing temperature value more than absolute zero, discharges infrared radiation related to the frequency of the body temperature. The difference in infrared radiation from the skin surface reflects the abnormality present in human body. Considering the difference, detection and forecasting the temperature variation of the skin surface is the main objective of using Medical Infrared Thermography(MIT) as a diagnostic tool for pain detection. Medical Infrared Thermography(MIT) is a non-invasive imaging technique that records and monitors the temperature flow in the body by receiving the infrared radiated from the skin and represent it through thermogram. The intensity of the thermogram measures the inflammation from the skin surface related to pain in human body. Analysis of thermograms provides automated anomaly detection associated with suspicious pain regions by following several image processing steps. The paper represents a rigorous study based survey related to the processing and analysis of thermograms based on the previous works published in the area of infrared thermal imaging for detecting inflammatory pain diseases like arthritis, spondylosis, shoulder impingement, etc. The study also explores the performance analysis of thermogram processing accompanied by thermogram acquisition protocols, thermography camera specification and the types of pain detected by thermography in summarized tabular format. The tabular format provides a clear structural vision of the past works. The major contribution of the paper introduces a new thermogram acquisition standard associated with inflammatory pain detection in human body to enhance the performance rate. The FLIR T650sc infrared camera with high sensitivity and resolution is adopted to increase the accuracy of thermogram acquisition and analysis. The survey of previous research work highlights that intensity distribution based comparison of comparable and symmetric region of interest and their statistical analysis assigns adequate result in case of identifying and detecting physiological disorder related to inflammatory diseases.

Keywords: acquisition protocol, inflammatory pain detection, medical infrared thermography (MIT), statistical analysis

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Authors: Mohammad Tarek Al Muallim, Ozhan Duzenli, Ceyhun Ilguy

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Harbor protection systems are so important. The need for automatic protection systems has increased over the last years. Diver detection active sonar has great significance. It used to detect underwater threats such as divers and autonomous underwater vehicle. To automatically detect such threats the sonar image is processed by algorithms. These algorithms used to detect, track and classify of underwater objects. In this work, divers tracking and classification algorithm is improved be proposing a robust wake detection method. To detect objects the sonar images is normalized then segmented based on fixed threshold. Next, the centroids of the segments are found and clustered based on distance metric. Then to track the objects linear Kalman filter is applied. To reduce effect of noise and creation of false tracks, the Kalman tracker is fine tuned. The tuning is done based on our active sonar specifications. After the tracks are initialed and updated they are subjected to a filtering stage to eliminate the noisy and unstable tracks. Also to eliminate object with a speed out of the diver speed range such as buoys and fast boats. Afterwards the result tracks are subjected to a classification stage to deiced the type of the object been tracked. Here the classification stage is to deice wither if the tracked object is an open circuit diver or a close circuit diver. At the classification stage, a small area around the object is extracted and a novel wake detection method is applied. The morphological features of the object with his wake is extracted. We used support vector machine to find the best classifier. The sonar training images and the test images are collected by ARMELSAN Defense Technologies Company using the portable diver detection sonar ARAS-2023. After applying the algorithm to the test sonar data, we get fine and stable tracks of the divers. The total classification accuracy achieved with the diver type is 97%.

Keywords: harbor protection, diver detection, active sonar, wake detection, diver classification

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Authors: Kiwon Yeom

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Change points are abrupt variations in a data sequence. Detection of change points is useful in modeling, analyzing, and predicting time series in application areas such as robotics and teleoperation. In this paper, a change point is defined to be a discontinuity in one of its derivatives. This paper presents a reliable method for detecting discontinuities within a three-dimensional trajectory data. The problem of determining one or more discontinuities is considered in regular and irregular trajectory data from teleoperation. We examine the geometric detection algorithm and illustrate the use of the method on real data examples.

Keywords: change point, discontinuity, teleoperation, abrupt variation

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Authors: Amenawo I. Offiong, Hodo B. Riman

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Public debt profile of Nigeria has continuously been on the increase over the years. The drop in international crude oil prices has further worsened revenue position of the country, thus, necessitating further acquisition of public debt to bridge the gap in revenue deficit. Yet, when we look back at the increasing public sector spending, there are concerns that the government spending do not amount to increase in public goods provided for the country. Using data from 1980 to 2014 the study therefore seeks to investigate the factors responsible for the poor provision of public goods in the face of increasing public debt profile. Using the unrestricted VAR model Governance and Tax revenue were introduced into the model as structural variables. The result suggested that governance and tax revenue were structural determinants of the effectiveness of public goods provisioning in Nigeria. The study therefore identified weak governance as the major reason for the non-provision of public goods in Nigeria. While tax revenue exerted positive influence on the provisions of public goods, weak/poor governance was observed to crowd the benefits from increase tax revenue. The study therefore recommends reappraisal of the governance system in Nigeria. Elected officers in governance should be more transparent and accountable to the electorates they represent. Furthermore, the study advocates for an annual auditing of all government MDAs accounts by external auditors to ensure (a) accountability of public debts utilization, (b) transparent in implementation of program support funds, (c) integrity of agencies responsible for program management, and (d) measuring program effectiveness with amount of funds expended.

Keywords: impulse response function, public debt shocks, governance, public goods, tax revenue, vector auto-regression

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Authors: Afef Badri

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The role of metaphor in creating the coherence and the cohesion of discourse in online interactive talk has almost received no attention. This paper intends to provide some theoretical reflections on metaphorical coherence as a jointly constructed process that evolves in online, face-to-face interactions. It suggests that the presence of a global conceptual structure in a conversation makes it conceptually cohesive. Yet, coherence remains a process largely determined by other variables (shared goals, communicative intentions, and framework of understanding). Metaphorical coherence created by these variables can be useful in detecting bias in media reporting.

Keywords: coherence, cohesion, face-to-face interactions, metaphor

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Authors: Larissa Pliska, Isabel Neitzel, Michael Buschermöhle, Olga Kunina-Habenicht, Ute Ritterfeld

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Visual preferences, which can be assessed using eye tracking technologies, are considered one of the defining hallmarks of Autism Spectrum Disorder (ASD). Specifically, children with ASD show a decreased preference for social images rather than geometric images compared to typically developed (TD) children. Such differences are already prevalent at a very early age and indicate the severity of the disorder: toddlers with ASD who preferred geometric images when confronted with social and geometric images showed higher ASD symptom severity than toddlers with ASD who showed higher social attention. Furthermore, the complexity of social pictures (one child playing vs. two children playing together) as well as the mode of stimulus presentation (video or image), are not decisive for the marker. The average age of diagnosis for ASD in Germany is 6.5 years, and visual preference data on this age group is missing. In the present study, we therefore investigated whether visual preferences persist into school age. We examined the visual preferences of 16 boys aged 6 to 11 with ASD and unimpaired cognition as well as TD children (1:1 matching based on children's age and the parent's level of education) within an experimental setting. Different stimulus presentation formats (images vs. videos) and different levels of stimulus complexity were included. Children with and without ASD received pairs of social and non-social images and video stimuli on a screen while eye movements (i.e., eye position and gaze direction) were recorded. For this specific use case, KIZMO GmbH developed a customized, native iOS app (KIZMO Face-Analyzer) for use on iPads. Neither the format of stimulus presentation nor the complexity of the social images had a significant effect on the visual preference of children with and without ASD in this study. Despite the tendency for a difference between the groups for the video stimuli, there were no significant differences. Overall, no statistical differences in visual preference occurred between boys with and without ASD, suggesting that gaze preference in these groups is similar at primary school age. One limitation is that the children with ASD were already receiving Autism-specific intervention. The potential of a visual preference task as an indicator of ASD can be emphasized. The article discusses the clinical relevance of this marker in elementary school children.

Keywords: autism spectrum disorder, eye tracking, hallmark, visual preference

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Authors: Sherehan Hamdalla

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Egypt has experienced a series of terrifying love crimes in the last few months. This ‘trend’ of love crimes started with a young man caught on video slaughtering his ex-girlfriend in the street in the city of El Mansoura. The crime shocked all Egyptian citizens at all levels; unfortunately, not less than three similar crimes took place in other different Egyptian cities with the same killing trigger. The characteristics and easy access and reach of social media consider the reason why it is one of the most crucial online communication channels; users utilize social media platforms for sharing and exchanging ideas, news, and many other activities; they can freely share posts that reflect their mindset or personal views regarding any issues, these posts are going viral in all social media account by reposting or numbers of shares for these posts to support the content included, or even to attack. The repetition of sharing certain posts could mobilize other supporters with the same point of view, especially when that crowd’s online participation is confronting a public opinion case’s consequences. The death of that young woman was followed by similar crimes in other cities, such as El Sharkia and Port Said. These love crimes provoked a massive wave of contention among all social classes in Egypt. Strangely, some were supporting the criminal and defending his side for several reasons, which the study will uncover. Facebook, the most popular social media platform for Egyptians, reflects the debate between supporters of the victim and supporters of the criminal. Facebook pages were created specifically to disseminate certain viewpoints online, for example, asking for the maximum penalty to be given to criminals. These pages aimed to mobilize the maximum number of supporters and to affect the outcome of the trials.

Keywords: love crimes, victim, criminal, social media

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Authors: Shukri Dughman, Anthony Rossiter

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This paper builds on earlier work which demonstrated that Model Predictive Control (MPC) may give a poor choice of default feed forward compensator. By first demonstrating the impact of future information of target changes on the performance, this paper proposes a pragmatic method for identifying the amount of future information on the target that can be utilised effectively in both finite and infinite horizon algorithms. Numerical illustrations in MATLAB give evidence of the efficacy of the proposal.

Keywords: model predictive control, tracking control, advance knowledge, feed forward

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