Search results for: vision spectrum

Authors: Sharifah Mousli, Sona Taheri, Jiayuan He

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Autism spectrum disorder (ASD) is a complex developmental condition involving persistent difficulties with social communication, restricted interests, and repetitive behavior. The challenges associated with ASD can interfere with an affected individual’s ability to function in social, academic, and employment settings. Although there is no effective medication known to treat ASD, to our best knowledge, early intervention can significantly improve an affected individual’s overall development. Hence, an accurate diagnosis of ASD at an early phase is essential. The use of machine learning approaches improves and speeds up the diagnosis of ASD. In this paper, we focus on the application of unsupervised clustering methods in ASD as a large volume of ASD data generated through hospitals, therapy centers, and mobile applications has no pre-existing labels. We conduct a comparative analysis using seven clustering approaches such as K-means, agglomerative hierarchical, model-based, fuzzy-C-means, affinity propagation, self organizing maps, linear vector quantisation – as well as the recently developed optimization-based clustering (COMSEP-Clust) approach. We evaluate the performances of the clustering methods extensively on real-world ASD datasets encompassing different age groups: toddlers, children, adolescents, and adults. Our experimental results suggest that the COMSEP-Clust approach outperforms the other seven methods in recognizing ASD with well-separated clusters.

Keywords: autism spectrum disorder, clustering, optimization, unsupervised machine learning

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Authors: Magdy Roman, Mostafa Shoeib, Mostafa Rostom

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Global vision, whether provided by overhead fixed cameras, on-board aerial vehicle cameras, or satellite images can always provide detailed information on the environment around mobile robots. In this paper, an intelligent vision-based method of path planning and obstacle avoidance for mobile robots is presented. The method integrates visual perception with a new proposed field-based path-planning method to overcome common path-planning problems such as local minima, unreachable destination and unnecessary lengthy paths around obstacles. The method proposes an exponential angle deviation field around each obstacle that affects the orientation of a close robot. As the robot directs toward, the goal point obstacles are classified into right and left groups, and a deviation angle is exponentially added or subtracted to the orientation of the robot. Exponential field parameters are chosen based on Lyapunov stability criterion to guarantee robot convergence to the destination. The proposed method uses obstacles' shape and location, extracted from global vision system, through a collision prediction mechanism to decide whether to activate or deactivate obstacles field. In addition, a search mechanism is developed in case of robot or goal point is trapped among obstacles to find suitable exit or entrance. The proposed algorithm is validated both in simulation and through experiments. The algorithm shows effectiveness in obstacles' avoidance and destination convergence, overcoming common path planning problems found in classical methods.

Keywords: path planning, collision avoidance, convergence, computer vision, mobile robots

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Authors: Kyoungwoon Kim, Cuong Huynh, Cam Nguyen

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Exploding demands for more data, faster data transmission speed, less interference, more users, more wireless devices, and better reliable service-far exceeding those provided in the current mobile communications networks in the RF spectrum below 6 GHz-has led the wireless communication industry to focus on higher, previously unallocated spectrums. High frequencies in RF spectrum near (around 28 GHz) or within the millimeter-wave regime is the logical solution to meet these demands. This high-frequency RF spectrum is of increasingly important for wireless communications due to its large available bandwidths that facilitate various applications requiring large-data high-speed transmissions, reaching up to multi-gigabit per second, of vast information. It also resolves the traffic congestion problems of signals from many wireless devices operating in the current RF spectrum (below 6 GHz), hence handling more traffic. Consequently, the wireless communication industries are moving towards 5G (fifth generation) for next-generation communications such as mobile phones, autonomous vehicles, virtual reality, and the Internet of Things (IoT). The U.S. Federal Communications Commission (FCC) proved on 14th July 2016 three frequency bands for 5G around 28, 37 and 39 GHz. We present some silicon-based RFIC power amplifiers (PA) for possible implementation for 5G wireless communications around 28, 37 and 39 GHz. The 16.5-28 GHz PA exhibits measured gain of more than 34.5 dB and very flat output power of 19.4±1.2 dBm across 16.5-28 GHz. The 25.5/37-GHz PA exhibits gain of 21.4 and 17 dB, and maximum output power of 16 and 13 dBm at 25.5 and 37 GHz, respectively, in the single-band mode. In the dual-band mode, the maximum output power is 13 and 9.5 dBm at 25.5 and 37 GHz, respectively. The 10-19/23-29/33-40 GHz PA has maximum output powers of 15, 13.3, and 13.8 dBm at 15, 25, and 35 GHz, respectively, in the single-band mode. When this PA is operated in dual-band mode, it has maximum output powers of 11.4/8.2 dBm at 15/25 GHz, 13.3/3 dBm at 15/35 GHz, and 8.7/6.7 dBm at 25/35 GHz. In the tri-band mode, it exhibits 8.8/5.4/3.8 dBm maximum output power at 15/25/35 GHz. Acknowledgement: This paper was made possible by NPRP grant # 6-241-2-102 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors

Keywords: Microwaves, Millimeter waves, Power Amplifier, Wireless communications

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Authors: Dongjoo Chin

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The purpose of this study was to investigate the effectiveness of an Early Intensive Behavioral Intervention (EIBI) program on infants with autism spectrum disorder (ASD) and to explore the factors predicting the effectiveness of the program, focusing on the infant's age, language ability, problem behaviors, and parental stress. 19 pairs of infants aged between 2 and 5 years who have had been diagnosed with ASD, and their parents participated in an EIBI program at a clinic providing evidence-based treatment based on applied behavior analysis. The measurement tools which were administered before and after the EIBI program and compared, included PEP-R, a curriculum evaluation, K-SIB-R, K-Vineland-II, K-CBCL, and PedsQL for the infants, and included PSI-SF and BDI-II for the parents. Statistical analysis was performed using a sample t-test and multiple regression analysis and the results were as follows. The EIBI program showed significant improvements in overall developmental age, curriculum assessment, and quality of life for infants. There was no difference in parenting stress or depression. Furthermore, measures for both children and parents at the start of the program predicted neither PEP-R nor the degree of improvement in curriculum evaluation measured six months later at the end of the program. Based on these results, the authors suggest future directions for developing an effective intensive early intervention (EIBI) program for infants with ASD in Korea, and discuss the implications and limitations of this study.

Keywords: applied behavior analysis, autism spectrum disorder, early intensive behavioral intervention, parental stress

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Authors: Yao-Hong Tsai

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Due to the sensor technology, video surveillance has become the main way for security control in every big city in the world. Surveillance is usually used by governments for intelligence gathering, the prevention of crime, the protection of a process, person, group or object, or the investigation of crime. Many surveillance systems based on computer vision technology have been developed in recent years. Moving target tracking is the most common task for Unmanned Aerial Vehicle (UAV) to find and track objects of interest in mobile aerial surveillance for civilian applications. The paper is focused on vision-based collision avoidance for UAVs by recurrent neural networks. First, images from cameras on UAV were fused based on deep convolutional neural network. Then, a recurrent neural network was constructed to obtain high-level image features for object tracking and extracting low-level image features for noise reducing. The system distributed the calculation of the whole system to local and cloud platform to efficiently perform object detection, tracking and collision avoidance based on multiple UAVs. The experiments on several challenging datasets showed that the proposed algorithm outperforms the state-of-the-art methods.

Keywords: unmanned aerial vehicle, object tracking, deep learning, collision avoidance

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Authors: Tushnik Sarkar, Mofazzal H. Khondekar, Subrata Banerjee

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This paper investigates the nature of the fluctuation of the daily average Solar wind speed time series collected over a period of 2492 days, from 1^st January, 1997 to 28^th October, 2003. The degree of self-similarity and scalability of the Solar Wind Speed signal has been explored to characterise the signal fluctuation. Multi-fractal Detrended Fluctuation Analysis (MFDFA) method has been implemented on the signal which is under investigation to perform this task. Furthermore, the singularity spectra of the signals have been also obtained to gauge the extent of the multifractality of the time series signal.

Keywords: detrended fluctuation analysis, generalized hurst exponent, holder exponents, multifractal exponent, multifractal spectrum, singularity spectrum, time series analysis

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Authors: Hoda Hashemi

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This study aimed to explore K-12 educators’ perceptions of using sensory-based strategies (SBS) with students on the autism spectrum in classroom settings. One hundred and ninety-three educators, including 107 special education teachers, 48 general education teachers, and 38 paraprofessionals, participated in this study. They answered 44 questions about using SBS in classroom settings, the degree to which they use the strategies on a 5-point Likert scale, the outcomes they targeted, and their perception of the strategies' effectiveness. The survey results indicated that most educators rated only one sensory-based strategy, which was alternated seating options, as highly effective in addressing the targeted behaviors of students on the autism spectrum. However, in some instances, educators' perceptions of the effectiveness of some strategies did not align with other research findings, highlighting the need for further evidence to confidently implement them.

Keywords: sensory-based strategies, K-12, educators, autism, survey

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Authors: Adinarayana S., Sudhakar I.

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Energy conversion is one of the inevitable parts of any industries. It involves either conversion of mechanical energy in to electrical or vice versa. The later conversion of energy i.e. electrical to mechanical emphasizes the need of motor. Statistics reveals, about 8 % of industries’ annual turnover met on maintenance. Thus substantial numbers of efforts are required to minimize in incurring expenditure met towards break down maintenance. Condition monitoring is one of such techniques based on vibration widely used to recognize premature failures and paves a way to minimize cumbersome involved during breakdown of machinery. The present investigation involves a case study of squirrel cage induction motor (frequently in the electro machines) has been chosen for the conditional monitoring to predict its soundness on the basis of results of FFT analyser. Accelerometer which measures the acceleration converts in to impulses by FFT analyser generates vibration spectrum and time spectrum has been located at various positions on motor under different conditions. Results obtained from the FFT analyser are compared to that of ISO standard vibration severity charts are taken to predict the preventative condition of considered machinery. Initial inspection of motor revealed that stator faults, broken end rings in rotor, eccentricity faults and misalignment between bearings are trouble shootings areas for present investigation. From the results of the shaft frequencies, it can be perceived that there is a misalignment between the bearings at both the ends. The higher order harmonics of FTF shows the presence of cracks on the race of the bearings at both the ends which are in the incipient stage. Replacement of the bearings at both the drive end (6306) and non drive end (6206) and the alignment check between the bearings in the shaft are suggested as the constructive measures towards preventive maintenance of considered squirrel cage induction motor.

Keywords: FFT analyser, condition monitoring, vibration spectrum, time wave form

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Authors: Sandip Suman

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Mechanical defects (cracks, voids, irregularities) in rocket motor propellant are not new and it is induced due to various reasons, which could be an improper manufacturing process, lot-to-lot variation in chemicals or just the natural aging of the products. These defects are normally identified during the examination of radiographic films by quality inspectors. However, a lot of times, these defects are under or over-classified by human inspectors, which leads to unpredictable performance during lot acceptance tests and significant economic loss. The human eye can only visualize larger cracks and defects in the radiographs, and it is almost impossible to visualize every small defect through the human eye. A different artificial intelligence-based machine vision methodology has been proposed in this work to identify and classify the structural defects in the radiographic films of rocket motors with solid propellant. The proposed methodology can extract the features of defects, characterize them, and make intelligent decisions for acceptance or rejection as per the customer requirements. This will automatize the defect detection process during manufacturing with human-like intelligence. It will also significantly reduce production downtime and help to restore processes in the least possible time. The proposed methodology is highly scalable and can easily be transferred to various products and processes.

Keywords: artificial intelligence, machine vision, defect detection, rocket motor propellant grains

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Authors: Changhwan Choi, Yongwan Park

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In this paper, we propose a method that allows faster and more accurate detection of traffic lights by a vision sensor during driving, DGPS is used to obtain physical location of a traffic light, extract from the image information of the vision sensor only the traffic light area at this location and ascertain if the sign is in operation and determine its form. This method can solve the problem in existing research where low visibility at night or reflection under bright light makes it difficult to recognize the form of traffic light, thus making driving unstable. We compared our success rate of traffic light recognition in day and night road environments. Compared to previous researches, it showed similar performance during the day but 50% improvement at night.

Keywords: traffic light, intelligent vehicle, night, detection, DGPS

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Authors: F. Stake

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This work is a parametric study combining simple and well known optical theories. These simple theories are arranged to form part of one answer to the question: “Can a semi-transparent Thermo-Photo-Voltaic (TPV) emitter have an optical extinction spectrum so much greater than its optical absorption spectrum that it becomes its own band-pass pre-filter, and if so, how well might it be expected to suppress light of undesired wavelengths?” In the report, hypothetical materials and operating temperatures will be used for comparative analyses only. Thermal emission properties of these hypothetical materials were created using two openly available FORTRAN programs. Results indicate that if using highly transparent materials it may be possible to create a thermal emitter that is its own band-pass pre-filter.

Keywords: Christensen effect, DISORT, index of refraction, scattering

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Authors: Ayat Bani Rashaid, Zain Khasawneh, Mazin Alqhazo, Shreen Nusair, Mohammad El-Khateeb, Mahmoud Bashtawi

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Autism Spectrum disorder (ASD) is a psychiatric disorder with unknown etiology that mainly affects children in the first three years of life. Alterations of amino acid levels are believed to contribute to ASD. The levels of six essential amino acids (methionine, histidine, valine, leucine, threonine, and phenylalanine), five conditional amino acids (proline, tyrosine, glutamine, cysteine, and cystine), and five non-essential amino acids (asparagine, aspartic acid, alanine, serine, and glutamic acid) in hair samples of children with ASD (n = 25) were analyzed and compared to corresponding levels in healthy age-matched controls (n = 25). The results showed that the levels of methionine, alanine, and asparagine were significantly lower in the hair samples of ASD group compared to those of the control group (p ≤ 0.05). However, the levels of glutamic acid were significantly higher in the ASD group than the control group (p ≤ 0.05). The current findings could contribute towards further understanding of ASD etiology and provide specialists with a hair amino acid profile utilized as a biomarker for early diagnosis of ASD. Such biomarkers could participate in future developments of therapies that reduce ASD-related symptoms.

Keywords: autism spectrum disorder, amino acids, liquid chromatography-tandem mass spectrometry, human hair

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Authors: kamran Bhatti

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Objective: To evaluate spectrum and resistance rates to antibacterial agents in causative pathogens of bacterial prostatitis in patients from Southern Europe, the Middle East, and Africa. Materials: 1027 isolates from cultures of urine or expressed prostatic secretion, post-massage urine or seminal fluid, or urethral samples were considered. Results: Escherichia coli (32%) and Enterococcus spp. (21%) were the most common isolates. Other Gram-negative, Gram-positive, and atypical pathogens accounted for 22%, 20%, and 5%, respectively. Resistance was <15% for piperacillin/tazobactam and carbapenems (both Gram-negative and -positive pathogens); <5% for glycopeptides against Gram-positive; 7%, 14%, and 20% for aminoglycosides, fosfomycin, and macrolides against Gram-negative pathogens, respectively; 10% for amoxicillin/clavulanate against Gram-positive pathogens; <20% for cephalosporins and fluoroquinolones against to Gram-negative pathogens (higher against Gram-positive pathogens); none for macrolides against atypical pathogens, but 20% and 27% for fluoroquinolones and tetracyclines. In West Africa, the resistance rates were generally higher, although the highest rates for ampicillin, cephalosporins, and fluoroquinolones were observed in the Gulf area. Lower rates were observed in Southeastern Europe. Conclusions: Resistance to antibiotics is a health problem requiring local health authorities to combat this phenomenon. Knowledge of the spectrum of pathogens and antibiotic resistance rates is crucial to assess local guidelines for the treatment of prostatitis.

Keywords: enterobacteriacae; escherichia coli, gram-positive pathogens, antibiotic, bacterial prostatitis, resistance

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Authors: D. Liu, D. M. Donskoy

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The vibroacoustic modulation method is based on the modulation effect of high-frequency ultrasonic wave (carrier) by low-frequency vibration in the presence of various defects, primarily contact-type such as cracks, delamination, etc. The presence and severity of the defect are measured by the ratio of the spectral sidebands and the carrier in the spectrum of the modulated signal. This approach, however, does not differentiate between amplitude and frequency modulations, AM and FM, respectfully. It was experimentally shown that both modulations could be present in the spectrum, yet each modulation may be associated with different physical mechanisms. AM mechanisms are quite well understood and widely covered in the literature. This paper is a first attempt to explain the generation mechanisms of FM and its correlation with the flaw properties. Here we proposed two possible mechanisms leading to FM modulation based on nonlinear local defect resonance and dynamic acousto-elastic models.

Keywords: non-destructive testing, nonlinear acoustics, structural health monitoring, acousto-elasticity, local defect resonance

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Authors: Yasunori Kobori, Nobukazu Tsukiji, Nobukazu Takai, Haruo Kobayashi

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In this paper, we study a Pulse-WidthModulation (PWM) controlled Zero-Voltage-Switching (ZVS) for single-inductor dual-output (SIDO) converters. This method can meet the industry demands for high efficiency due to ZVS and small size and low cost, thanks to single-inductor per multiple voltages. We show the single inductor single-output (SISO) ZVS buck converter with its operation and simulation and then the experimental results. Next proposed ZVS-PWM controlled SIDO converters are explained in the simulation. Finally we have proposed EMI reduction method with spread spectrum.

Keywords: DC-DC switching converter, zero-oltage switching control, single-inductor dual-output converter, EMI reduction, spread spectrum

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Authors: Janice Keener, Christine Houlihan

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Over the last several years, there has been an increase in children identified as having Autism Spectrum Disorder (ASD). Specialists across several disciplines: mental health and medical professionals have been tasked with ensuring accurate and timely evaluations for children with suspected ASD. Due to the nature of the ASD symptom presentation, an interdisciplinary assessment and treatment approach best addresses the needs of the whole child. During the unprecedented COVID-19 Pandemic, clinicians were faced with how to continue with interdisciplinary assessments in a telehealth arena. Instruments that were previously used to assess ASD in-person were no longer appropriate measures to use due to the safety restrictions. For example, The Autism Diagnostic Observation Schedule requires examiners and children to be in very close proximity of each other and if masks or face shields are worn, they render the evaluation invalid. Similar issues arose with the various cognitive measures that are used to assess children such as the Weschler Tests of Intelligence and the Differential Ability Scale. Thus the need arose to identify measures that are able to be safely and accurately administered using safety guidelines. The incidence of ASD continues to rise over time. Currently, the Center for Disease Control estimates that 1 in 59 children meet the criteria for a diagnosis of ASD. The reasons for this increase are likely multifold, including changes in diagnostic criteria, public awareness of the condition, and other environmental and genetic factors. The rise in the incidence of ASD has led to a greater need for diagnostic and treatment services across the United States. The uncertainty of the diagnostic process can lead to an increased level of stress for families of children with suspected ASD. Along with this increase, there is a need for diagnostic clarity to avoid both under and over-identification of this condition. Interdisciplinary assessment is ideal for children with suspected ASD, as it allows for an assessment of the whole child over the course of time and across multiple settings. Clinicians such as Psychologists and Developmental Pediatricians play important roles in the initial evaluation of autism spectrum disorder. An ASD assessment may consist of several types of measures such as standardized checklists, structured interviews, and direct assessments such as the ADOS-2 are just a few examples. With the advent of telehealth clinicians were asked to continue to provide meaningful interdisciplinary assessments via an electronic platform and, in a sense, going to the family home and evaluating the clinical symptom presentation remotely and confidently making an accurate diagnosis. This poster presentation will review the benefits, limitations, and interpretation of these various instruments. The role of other medical professionals will also be addressed, including medical providers, speech pathology, and occupational therapy.

Keywords: Autism Spectrum Disorder Assessments, Interdisciplinary Evaluations , Tele-Assessment with Autism Spectrum Disorder, Diagnosis of Autism Spectrum Disorder

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Authors: Norah Salem Al Mosa

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This paper critically examines the ethical position of academic scholarship concerning "women in leadership" in Saudi Arabia, focusing on the context of the Saudi Vision 2030 initiative. While this vision places a strong emphasis on empowering women and increasing their presence in the workforce, women still face significant cultural, organisational, and personal barriers to leadership roles. The existing literature highlights the challenges Saudi women encounter, including the male guardianship system, and international perspectives add complexity to the issue. The debate among scholars about considering cultural context versus highlighting ongoing challenges is explored. The paper underscores that despite efforts to enhance women's representation in leadership positions, progress has been slow due to cultural norms, the absence of legal quotas, and limited access to education and professional development. It raises questions about the seriousness of research efforts and the government's commitment to gender equality in leadership roles, emphasising the need for increased academic scrutiny in this area. Ultimately, the paper aims to enhance understanding of the challenges and opportunities for women in leadership roles, their contributions to corporate governance in Saudi Arabia, and potential implications beyond its borders.

Keywords: female directors, gender diversity, women on executive positions, Saudi vision 2030

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Authors: Keigo Matsuura, Isao Tomita

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We have studied a method to widen the spectrum of optical pulses that pass through an InGaAsP waveguide for application to broadband optical communication. In particular, we have investigated the competitive effect between spectral broadening arising from nonlinear refraction (optical Kerr effect) and shrinking due to two photon absorption in the InGaAsP waveguide with chi^(3) nonlinearity. The shrunk spectrum recovers broadening by the enhancement effect of the nonlinear refractive index near the bandgap of InGaAsP with a bandgap wavelength of 1490 nm. The broadened spectral width at around 1525 nm (196.7 THz) becomes 10.7 times wider than that at around 1560 nm (192.3 THz) without the enhancement effect, where amplified optical pulses with a pulse width of 2 ps and a peak power of 10 W propagate through a 1-cm-long InGaAsP waveguide with a cross-section of 4 um^2.

Keywords: InGaAsP waveguide, Chi^(3) nonlinearity, spectral broadening, photon absorption

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Authors: Marco Furinghetti, Alberto Pavese, Michele Rinaldi

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Concave Surface Slider devices have been more and more used in real applications for seismic protection of both bridge and building structures. Several research activities have been carried out, in order to investigate the lateral response of such a typology of devices, and a reasonably high level of knowledge has been reached. If radial analysis is performed, the frictional force is always aligned with respect to the restoring force, whereas under bidirectional seismic events, a bi-axial interaction of the directions of motion occurs, due to the step-wise projection of the main frictional force, which is assumed to be aligned to the trajectory of the isolator. Nonetheless, if non-linear time history analyses have to be performed, standard codes provide precise rules for the definition of an averagely spectrum-compatible set of accelerograms in radial conditions, whereas for bidirectional motions different combinations of the single components spectra can be found. Moreover, nowadays software for the adjustment of natural accelerograms are available, which lead to a higher quality of spectrum-compatibility and to a smaller dispersion of results for radial motions. In this endeavor a simplified design procedure is defined, for building structures, base-isolated by means of Concave Surface Slider devices. Different case study structures have been analyzed. In a first stage, the capacity curve has been computed, by means of non-linear static analyses on the fixed-base structures: inelastic fiber elements have been adopted and different direction angles of lateral forces have been studied. Thanks to these results, a linear elastic Finite Element Model has been defined, characterized by the same global stiffness of the linear elastic branch of the non-linear capacity curve. Then, non-linear time history analyses have been performed on the base-isolated structures, by applying seven bidirectional seismic events. The spectrum-compatibility of bidirectional earthquakes has been studied, by considering different combinations of single components and adjusting single records: thanks to the proposed procedure, results have shown a small dispersion and a good agreement in comparison to the assumed design values.

Keywords: concave surface slider, spectrum-compatibility, bidirectional earthquake, base isolation

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Authors: Romel Cordova Shedan

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The traditional seismic design is the methodology of Forced Based Design (FBD). The Displacement Based Design (DBD) is a seismic design that considers structural damage to achieve a failure mechanism of the structure before the collapse. It is easier to quantify damage of a structure with displacements rather than forces. Therefore, a structure to achieve an inelastic displacement design with good ductility, it is necessary to be damaged. The first part of this investigation is about differences between the methodologies of DBD and FBD with some DBD advantages. In the second part, there is a study case about a dual building 5-story, which is regular in plan and elevation. The building is located in a seismic zone, which acceleration in firm soil is 45% of the acceleration of gravity. Then it is applied both methodologies into the study case to compare its displacements, shear forces and overturning moments. In the third part, the Dynamic Time History Analysis (DTHA) is done, to compare displacements with DBD and FBD methodologies. Three accelerograms were used and the magnitude of the acceleration scaled to be spectrum compatible with design spectrum. Then, using ASCE 41-13 guidelines, the hinge plastics were assigned to structure. Finally, both methodologies results about study case are compared. It is important to take into account that the seismic performance level of the building for DBD is greater than FBD method. This is due to drifts of DBD are in the order of 2.0% and 2.5% comparing with FBD drifts of 0.7%. Therefore, displacements of DBD is greater than the FBD method. Shear forces of DBD result greater than FBD methodology. These strengths of DBD method ensures that structure achieves design inelastic displacements, because those strengths were obtained due to a displacement spectrum reduction factor which depends on damping and ductility of the dual system. Also, the displacements for the study case for DBD results to be greater than FBD and DTHA. In that way, it proves that the seismic performance level of the building for DBD is greater than FBD method. Due to drifts of DBD which are in the order of 2.0% and 2.5% compared with little FBD drifts of 0.7%.

Keywords: displacement-based design, displacement spectrum reduction factor, dynamic time history analysis, forced based design

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Authors: John Paul Q. Tomas, Mark Wilson L. de los Reyes, Kirsten Joyce P. Vasquez

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The most frequent type of fracture is a wrist fracture, which often makes it difficult for medical professionals to find and locate. In this study, fractures in wrist x-ray pictures were located and identified using deep learning and computer vision. The researchers used image filtering, masking, morphological operations, and data augmentation for the image preprocessing and trained the RetinaNet and Faster R-CNN models with ResNet50 backbones and Adam optimizers separately for each image filtering technique and projection. The RetinaNet model with Anisotropic Diffusion Smoothing filter trained with 50 epochs has obtained the greatest accuracy of 99.14%, precision of 100%, sensitivity/recall of 98.41%, specificity of 100%, and an IoU score of 56.44% for the Posteroanterior projection utilizing augmented data. For the Lateral projection using augmented data, the RetinaNet model with an Anisotropic Diffusion filter trained with 50 epochs has produced the highest accuracy of 98.40%, precision of 98.36%, sensitivity/recall of 98.36%, specificity of 98.43%, and an IoU score of 58.69%. When comparing the test results of the different individual projections, models, and image filtering techniques, the Anisotropic Diffusion filter trained with 50 epochs has produced the best classification and regression scores for both projections.

Keywords: Artificial Intelligence, Computer Vision, Wrist Fracture, Deep Learning

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Authors: A. Attaf A., I. Bouhaf Kharkhachi

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Spray ultrasonic deposition technique of tin disulfide (SnS2) thin films know wide application due to their adequate physicochemical properties for microelectronic applications and especially for solar cells. SnS2 film was deposited by spray ultrasonic technique, on pretreated glass substrates at well-determined conditions.The effect of SnS2 concentration on different optical properties of SnS2 Thin films, such us MEB, XRD, and UV spectroscopy visible spectrum was investigated. MEB characterization technique shows that the morphology of this films is uniform, compact and granular. x-ray diffraction study detects the best growth crystallinity in hexagonal structure with preferential plan (001). The results of UV spectroscopy visible spectrum show that films deposited at 0.1 mol/l is large transmittance greater than 25% in the visible region.The band gap energy is 2.54 Ev for molarity 0.1 mol/l.

Keywords: MEB, thin disulfide, thin films, ultrasonic spray, X-Ray diffraction, UV spectroscopy visible

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Authors: Muazzam A. Khan

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In order to avoid dangerous environmental disasters, robots are being recognized as good entrants to step in as human rescuers. Robots has been gaining interest of many researchers in rescue matters especially which are furnished with advanced sensors. In distributed wireless robot system main objective for a rescue system is to track the location of the object continuously. This paper provides a novel idea to track and locate human in disaster area using stereo vision system and ZigBee technology. This system recursively predict and updates 3D coordinates in a robot coordinate camera system of a human which makes the system cost effective. This system is comprised of ZigBee network which has many advantages such as low power consumption, self-healing low data rates and low cost.

Keywords: stereo vision, segmentation, classification, human tracking, ZigBee module

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Authors: Michael Nicolosi, Karola Dillenburger

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The University of California at Los Angeles-Young Autism Project (UCLA-YAP) provides one of the best-known and most researched comprehensive applied behavior analysis-based intervention models for young children on the autism spectrum. This paper reports a systematic literature review of replication studies over more than 30 years. The data show that the relatively high-intensity UCLA-YAP model can be greatly beneficial for children on the autism spectrum, particularly with regard to their cognitive functioning and adaptive behavior. This review concludes that, while more research is always welcome, the impact of the UCLA-YAP model on autism interventions is justified by more than 30 years of outcome evidence.

Keywords: ABA, applied behavior analysis, autism, California at Los Angeles Young Autism project, intervention, Lovaas, UCLA-YAP

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Authors: K. Khelil, H. Ammar, K. Saouchi

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Fiber Bragg Grating (FBG) structure is an periodically modulated optical fiber. It acts as a selective filter of wavelength whose reflected peak is called Bragg wavelength and it depends on the period of the fiber and the refractive index. The simulation of FBG is based on solving the Coupled Mode Theory equation by using the Transfer Matrix Method which is carried out using MATLAB. It is found that spectral reflectivity is shifted when the change of temperature and strain is uniform. Under non-uniform temperature or strain perturbation, the spectrum is both shifted and destroyed. In case of transverse loading, reflectivity spectrum is split into two peaks, the first is specific to X axis, and the second belongs to Y axis. FBGs are used in civil engineering to detect perturbations applied to buildings.

Keywords: Bragg wavelength, coupled mode theory, optical fiber, temperature measurement

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Authors: Shreya Thusoo, Karan Modi, Ankit Kumar Jha, Rajesh Kumar

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Since the evolution of computational tools and simulation software, there has been considerable increase in research on Soil Structure Interaction (SSI) to decrease the computational time and increase accuracy in the results. To aid the designer with a proper understanding of the response of structure in different soil types, the presented paper compares the deformation, shear stress, acceleration and other parameters of multi-storey building for a specific input ground motion using Response-spectrum Analysis (RSA) method. The response of all the models of different heights have been compared in different soil types. Finite Element Simulation software, ANSYS, has been used for all the computational purposes. Overall, higher response is observed with SSI, while it increases with decreasing stiffness of soil.

Keywords: soil-structure interaction, response spectrum, analysis, finite element method, multi-storey buildings

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Authors: Francisco Bulnes

Abstract:

Through the Fukaya conjecture and the wrapped Floer cohomology, the correspondences between paths in a loop space and states of a wrapping space of states in a Hamiltonian space (the ramification of field in this case is the connection to the operator that goes from TM to T*M) are demonstrated where these last states are corresponding to bosonic extensions of a spectrum of the space-time or direct image of the functor Spec, on space-time. This establishes a distinguished diffeomorphism defined by the mapping from the corresponding loops space to wrapping category of the Floer cohomology complex which furthermore relates in certain proportion D-branes (certain D-modules) with strings. This also gives to place to certain conjecture that establishes equivalences between moduli spaces that can be consigned in a moduli identity taking as space-time the Hitchin moduli space on G, whose dual can be expressed by a factor of a bosonic moduli spaces.

Keywords: Floer cohomology, Fukaya conjecture, Lagrangian submanifolds, quantum topological diffeomorphism

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Authors: Danilo López, Edwin Rivas, Fernando Pedraza

Abstract:

Currently, one of the major challenges in wireless networks is the optimal use of radio spectrum, which is managed inefficiently. One of the solutions to existing problem converges in the use of Cognitive Radio (CR), as an essential parameter so that the use of the available licensed spectrum is possible (by secondary users), well above the usage values that are currently detected; thus allowing the opportunistic use of the channel in the absence of primary users (PU). This article presents the results found when estimating or predicting the future use of a spectral transmission band (from the perspective of the PU) for a chaotic type channel arrival behavior. The time series prediction method (which the PU represents) used is ANFIS (Adaptive Neuro Fuzzy Inference System). The results obtained were compared to those delivered by the RNA (Artificial Neural Network) algorithm. The results show better performance in the characterization (modeling and prediction) with the ANFIS methodology.

Keywords: ANFIS, cognitive radio, prediction primary user, RNA

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Authors: Chonlakorn Wiboonsiriruk, Ekachai Phaisangittisagul, Chadchai Srisurangkul, Itsuo Kumazawa

Abstract:

Public transportation is a crucial aspect of passenger transportation, with buses playing a vital role in the transportation service. Passenger counting is an essential tool for organizing and managing transportation services. However, manual counting is a tedious and time-consuming task, which is why computer vision algorithms are being utilized to make the process more efficient. In this study, different object detection algorithms combined with passenger tracking are investigated to compare passenger counting performance. The system employs the EfficientDet algorithm, which has demonstrated superior performance in terms of speed and accuracy. Our results show that the proposed system can accurately count passengers in varying conditions with an accuracy of 94%.

Keywords: computer vision, object detection, passenger counting, public transportation

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Authors: Juan Sebastian Huertas Piedrahita, Jaime Arturo Lopez Duque, Eduardo Luis Perez Londoño, Julián S. Rodríguez

Abstract:

The process of generating computer vision is called artificial vision. The artificial vision is a branch of artificial intelligence that allows the obtaining, processing, and analysis of any type of information especially the ones obtained through digital images. Actually the artificial vision is used in manufacturing areas for quality control and production, as these processes can be realized through counting algorithms, positioning, and recognition of objects that can be measured by a single camera (or more). On the other hand, the companies use assembly lines formed by conveyor systems with actuators on them for moving pieces from one location to another in their production. These devices must be previously programmed for their good performance and must have a programmed logic routine. Nowadays the production is the main target of every industry, quality, and the fast elaboration of the different stages and processes in the chain of production of any product or service being offered. The principal base of this project is to program a computer that recognizes geometric figures (circle, square, and triangle) through a camera, each one with a different color and link it with a group of conveyor systems to organize the mentioned figures in cubicles, which differ from one another also by having different colors. This project bases on artificial vision, therefore the methodology needed to develop this project must be strict, this one is detailed below: 1. Methodology: 1.1 The software used in this project is QT Creator which is linked with Open CV libraries. Together, these tools perform to realize the respective program to identify colors and forms directly from the camera to the computer. 1.2 Imagery acquisition: To start using the libraries of Open CV is necessary to acquire images, which can be captured by a computer’s web camera or a different specialized camera. 1.3 The recognition of RGB colors is realized by code, crossing the matrices of the captured images and comparing pixels, identifying the primary colors which are red, green, and blue. 1.4 To detect forms it is necessary to realize the segmentation of the images, so the first step is converting the image from RGB to grayscale, to work with the dark tones of the image, then the image is binarized which means having the figure of the image in a white tone with a black background. Finally, we find the contours of the figure in the image to detect the quantity of edges to identify which figure it is. 1.5 After the color and figure have been identified, the program links with the conveyor systems, which through the actuators will classify the figures in their respective cubicles. Conclusions: The Open CV library is a useful tool for projects in which an interface between a computer and the environment is required since the camera obtains external characteristics and realizes any process. With the program for this project any type of assembly line can be optimized because images from the environment can be obtained and the process would be more accurate.

Keywords: artificial intelligence, artificial vision, binarized, grayscale, images, RGB

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