Search results for: spectrum congestion

Authors: Tesfay Mekonnen Weldegerima

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Analysis of precipitation time series is a fundamental undertaking in meteorology and hydrology. The extreme precipitation scenario of the Kulfo River watershed is studied using wavelet analysis and atmospheric transport, a lagrangian trajectory model. Daily rainfall data for the 1991-2020 study periods are collected from the office of the Ethiopian Meteorology Institute. Meteorological fields on a three-dimensional grid at 0.5o x 0.5o spatial resolution and daily temporal resolution are also obtained from the Global Data Assimilation System (GDAS). Wavelet analysis of the daily precipitation processed with the lag-1 coefficient reveals some high power recurred once every 38 to 60 days with greater than 95% confidence for red noise. The analysis also identified inter-annual periodicity in the periods 2002 - 2005 and 2017 - 2019. Back trajectory analysis for 3-day periods up to May 19/2011, indicates the Indian Ocean source; trajectories crossed the eastern African escarpment to arrive at the Kulfo watershed. Atmospheric flows associated with the Western Indian monsoon redirected by the low-level Somali winds and Arabian ridge are responsible for the moisture supply. The time-localization of the wavelet power spectrum yields valuable hydrological information, and the back trajectory approaches provide useful characterization of air mass source.

Keywords: extreme precipitation events, power spectrum, back trajectory, kulfo watershed

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Authors: Shogo Nagano, Yusuke Tanigaki, Hirokazu Fukuda

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Vegetables harvested early in the morning or late in the afternoon are valued in plant production, and so the time of harvest is important. The biological functions known as circadian clocks have a significant effect on this harvest timing. The purpose of this study was to non-destructively estimate the circadian clock and so construct a method for determining a suitable harvest time. We took eight samples of green busil (Perilla frutescens var. crispa) every 4 hours, six times for 1 day and analyzed all samples at the same time. A hyperspectral camera was used to collect spectrum intensities at 141 different wavelengths (350–1050 nm). Calculation of correlations between spectrum intensity of each wavelength and harvest time suggested the suitability of the hyperspectral camera for non-destructive estimation. However, even the highest correlated wavelength had a weak correlation, so we used machine learning to raise the accuracy of estimation and constructed a machine learning model to estimate the internal time of the circadian clock. Artificial neural networks (ANN) were used for machine learning because this is an effective analysis method for large amounts of data. Using the estimation model resulted in an error between estimated and real times of 3 min. The estimations were made in less than 2 hours. Thus, we successfully demonstrated this method of non-destructively estimating internal time.

Keywords: artificial neural network (ANN), circadian clock, green busil, hyperspectral camera, non-destructive evaluation

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Authors: Snehal Mevada, Darshana Bhatt, Aryan Kalthiya, Neel Parmar, Vishal Baraiya, Dhruvit Bhanderi, Tisha Patel

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In multi-storeyed framed buildings, damage occurring from earthquake ground motion generally initiates at locations of structural weaknesses present in the lateral load-resisting frame. In some cases, these weaknesses may be created by discontinuities in stiffness, mass, plan, and torsion. Such discontinuity between storeys is often associated with sudden variations in the vertical geometric irregularities and plan irregularities. Vertical irregularities are structures with a soft storey that can further be broken down into the different types of irregularities as well as their severity for a more refined assessment tool pushover analysis which is one of the methods available for evaluating building against earthquake loads. So, it is very necessary to analyse and understand the seismic performance of the irregular structure in order to reduce the damage which occurs during an earthquake. In this project, a multi-storey (G+4) RCC building with four irregularities (stiffness, mass, plan, torsion) is studied for earthquake loads using the response spectrum method (dynamic analysis) and STADD PRO. All analyses have been done for seismic zone IV and for Medium Soil. In this study effects of different irregularities are analysed based on storey displacement, storey drift, and storey shear.

Keywords: comparison of regular and irregular structure, dynamic analysis, mass irregularity, plan irregularity, response spectrum method, stiffness irregularity, seismic performance, torsional irregularity, STAAD PRO

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Authors: Sophie Sakka, Rénald Gaboriau

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This paper describes a preliminary work aimed at setting a therapeutic support for autistic teenagers using three humanoid robots NAO shared by ASD (Autism Spectrum Disorder) subjects. The studied population had attended successfully a first year program, and were observed with a second year program using the robots. This paper focuses on the content and the effects of the second year program. The approach is based on a master puppet concept: the subjects program the robots, and use them as an extension for communication. Twenty sessions were organized, alternating ten preparatory sessions and ten robotics programming sessions. During the preparatory sessions, the subjects write a story to be played by the robots. During the robot programming sessions, the subjects program the motions to be realized to make the robot tell the story. The program was concluded by a public performance. The experiment involves five ASD teenagers aged 12-15, who had all attended the first year robotics training. As a result, a progress in voluntary and organized communication skills of the five subjects was observed, leading to improvements in social organization, focus, voluntary communication, programming, reading and writing abilities. The changes observed in the subjects general behavior took place in a short time, and could be observed from one robotics session to the next one. The approach allowed the subjects to draw the limits of their body with respect to the environment, and therefore helped them confronting the world with less anxiety.

Keywords: autism spectrum disorder, robot, therapeutic support, rob'autism

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Authors: Pavlina Capkova, Josef Srovnal, Vera Becvarova, Marie Trkova, Zuzana Capkova, Andrea Stefekova, Vaclava Curtisova, Alena Santava, Sarka Vejvalkova, Katerina Adamova, Radek Vodicka

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ASDs are heterogeneous and complex developmental diseases with a significant genetic background. Recurrent CNVs are known to be a frequent cause of ASD. These CNVs can have, however, a variable expressivity which results in a spectrum of phenotypes from asymptomatic to ID/DD/ASD. ASD is associated with ID in ~75% individuals. Various platforms are used to detect pathogenic mutations in the genome of these patients. The performed study is focused on a determination of the frequency of pathogenic mutations in a group of ASD patients and a group of ID/DD patients using various strategies along with a comparison of their detection rate. The possible role of the origin of these mutations in aetiology of ASD was assessed. The study included 35 individuals with ASD and 68 individuals with ID/DD (64 males and 39 females in total), who underwent rigorous genetic, neurological and psychological examinations. Screening for pathogenic mutations involved karyotyping, screening for FMR1 mutations and for metabolic disorders, a targeted MLPA test with probe mixes Telomeres 3 and 5, Microdeletion 1 and 2, Autism 1, MRX and a chromosomal microarray analysis (CMA) (Illumina or Affymetrix). Chromosomal aberrations were revealed in 7 (1 in the ASD group) individuals by karyotyping. FMR1 mutations were discovered in 3 (1 in the ASD group) individuals. The detection rate of pathogenic mutations in ASD patients with a normal karyotype was 15.15% by MLPA and CMA. The frequencies of the pathogenic mutations were 25.0% by MLPA and 35.0% by CMA in ID/DD patients with a normal karyotype. CNVs inherited from asymptomatic parents were more abundant than de novo changes in ASD patients (11.43% vs. 5.71%) in contrast to the ID/DD group where de novo mutations prevailed over inherited ones (26.47% vs. 16.18%). ASD patients shared more frequently their mutations with their fathers than patients from ID/DD group (8.57% vs. 1.47%). Maternally inherited mutations predominated in the ID/DD group in comparison with the ASD group (14.7% vs. 2.86 %). CNVs of an unknown significance were found in 10 patients by CMA and in 3 patients by MLPA. Although the detection rate is the highest when using CMA, recurrent CNVs can be easily detected by MLPA. CMA proved to be more efficient in the ID/DD group where a larger spectrum of rare pathogenic CNVs was revealed. This study determined that maternally inherited highly penetrant mutations and de novo mutations more often resulted in ID/DD without ASD in patients. The paternally inherited mutations could be, however, a source of the greater variability in the genome of the ASD patients and contribute to the polygenic character of the inheritance of ASD. As the number of the subjects in the group is limited, a larger cohort is needed to confirm this conclusion. Inherited CNVs have a role in aetiology of ASD possibly in combination with additional genetic factors - the mutations elsewhere in the genome. The identification of these interactions constitutes a challenge for the future. Supported by MH CZ – DRO (FNOl, 00098892), IGA UP LF_2016_010, TACR TE02000058 and NPU LO1304.

Keywords: autistic spectrum disorders, copy number variant, chromosomal microarray, intellectual disability, karyotyping, MLPA, multiplex ligation-dependent probe amplification

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Authors: Vishal D. Bharud, B. J. Patil, S. S. Dahiwale, V. N. Bhoraskar, S. D. Dhole

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Photon induced average reaction cross section of ¹¹¹Cd (γ, γ`) ¹¹¹ᵐCd reaction was experimentally determined for the bremsstrahlung energy spectrum of 6 MeV by utilizing the activation and offline γ-ray spectrometric techniques. The 6 MeV electron accelerator Racetrack Microtron of Savitribai Phule Pune University, Pune was used for the experimental work. The bremsstrahlung spectrum generated by bombarding 6 MeV electrons on lead target was theoretically estimated by FLUKA code. Bremsstrahlung radiation can have energies exceeding the threshold of the particle emission, which is normally above 6 MeV. Photons of energies below the particle emission threshold undergo absorption into discrete energy levels, with possibility of exciting nuclei to excited state including metastable state. The ¹¹¹Cd (γ, γ`) ¹¹¹ᵐCd reaction cross sections were calculated at different energies of bombarding Photon by using the TALYS 1.8 computer code with a default parameter. The focus of the present work was to study the (γ,γ’) reaction for exciting ¹¹¹Cd nuclei to metastable states which have threshold energy below 3 MeV. The flux weighted average cross section was obtained from the theoretical values of TALYS 1.8 and TENDL 2017 and is found to be in good agreement with the present experimental cross section.

Keywords: bremsstrahlung, cross section, FLUKA, TALYS-1.8

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Authors: Asma Alsaleh, Kara Makara

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Autistic spectrum disorder (ASD) is a neurodevelopmental condition characterized by difficulties with communication and interaction. Besides presenting challenges for the ASD individual, the condition can entail negative outcomes for those who care for them, most often mothers. While this issue has been studied substantially in Western society, less is known about how mothers in the Arab world are affected by raising an ASD child. This study sought to gain insights into this area by assessing quality of life and stress in mothers with (n = 25) and without (n = 25) ASD children in Riyadh (Saudi Arabia) by using, respectively, the World Health Organization Quality of Life Assessment-BREF (WHOQOL-BREF) and the Parenting Stress Index-Short Form (PSI-SF). Data pertaining to income and education were also attained to investigate how socioeconomic factors interact with the above-mentioned variables. The analysis revealed that total stress scores and scores on the individual subscales of the PSI-SF were significantly higher for the mothers with an ASD child compared to those without an ASD child, though the opposite was true of quality of life scores. Moreover, increased income was associated with increased quality of life and decreased stress. While there were not main effects of education, there were interactions between education, whether children were ASD or non-ASD, and the outcome variables. These results suggest that mothers of ASD children in an Arab culture are at increased risk of negative outcomes relative to mothers of typically developing children, and, therefore, this study may act as a foundation for the delivery of interventions to assist mothers in this position.

Keywords: autism, education, income, mothers, quality of life, stress

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Authors: Vinay Agrawal, Suyash Garg, Ravindra Nagar, Vinay Chandwani

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Open ground storey with floating columns is a typical feature in the modern multistory constructions in urban India. Such features are very much undesirable in buildings built in seismically active areas. The present study proposes a feasible solution to mitigate the effects caused due to non-uniformity of stiffness and discontinuity in load path and to simultaneously hold the functional use of the open storey particularly under the floating column, through a combination of various lateral strengthening systems. An investigation is performed on an example building with nine different analytical models to bring out the importance of recognising the presence of open ground storey and floating columns. Two separate analyses on various models of the building namely, the equivalent static analysis and the response spectrum analysis as per IS: 1893-2002 were performed. Various measures such as incorporation of Chevron bracings and shear walls, strengthening the columns in the open ground storey, and their different combinations were examined. The analysis shows that, in comparison to two short ones separated by interconnecting beams, the structural walls are most effective when placed at the periphery of the buildings and used as one long structural wall. Further, it can be shown that the force transfer from floating columns becomes less horizontal when the Chevron Bracings are placed just below them, thereby reducing the shear forces in the beams on which the floating column rests.

Keywords: equivalent static analysis, floating column, open ground storey, response spectrum analysis, shear wall, stiffness irregularity

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Authors: Olivier Delage, Thierry Portafaix, Hassan Bencherif, Guillaume Guimbretiere

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Most observation data sequences in geophysics can be interpreted as resulting from the interaction of several physical processes at several time and space scales. As a consequence, measurements time series in geophysics have often characteristics of non-linearity and non-stationarity and thereby exhibit strong fluctuations at all time-scales and require a time-frequency representation to analyze their variability. Empirical Mode Decomposition (EMD) is a relatively new technic as part of a more general signal processing method called the Hilbert-Huang transform. This analysis method turns out to be particularly suitable for non-linear and non-stationary signals and consists in decomposing a signal in an auto adaptive way into a sum of oscillating components named IMFs (Intrinsic Mode Functions), and thereby acts as a bank of bandpass filters. The advantages of the EMD technic are to be entirely data driven and to provide the principal variability modes of the dynamics represented by the original time series. However, the main limiting factor is the frequency resolution that may give rise to the mode mixing phenomenon where the spectral contents of some IMFs overlap each other. To overcome this problem, J. Gilles proposed an alternative entitled “Empirical Wavelet Transform” (EWT) which consists in building from the segmentation of the original signal Fourier spectrum, a bank of filters. The method used is based on the idea utilized in the construction of both Littlewood-Paley and Meyer’s wavelets. The heart of the method lies in the segmentation of the Fourier spectrum based on the local maxima detection in order to obtain a set of non-overlapping segments. Because linked to the Fourier spectrum, the frequency resolution provided by EWT is higher than that provided by EMD and therefore allows to overcome the mode-mixing problem. On the other hand, if the EWT technique is able to detect the frequencies involved in the original time series fluctuations, EWT does not allow to associate the detected frequencies to a specific mode of variability as in the EMD technic. Because EMD is closer to the observation of physical phenomena than EWT, we propose here a new technic called EAWD (Empirical Adaptive Wavelet Decomposition) based on the coupling of the EMD and EWT technics by using the IMFs density spectral content to optimize the segmentation of the Fourier spectrum required by EWT. In this study, EMD and EWT technics are described, then EAWD technic is presented. Comparison of results obtained respectively by EMD, EWT and EAWD technics on time series of ozone total columns recorded at Reunion island over [1978-2019] period is discussed. This study was carried out as part of the SOLSTYCE project dedicated to the characterization and modeling of the underlying dynamics of time series issued from complex systems in atmospheric sciences

Keywords: adaptive filtering, empirical mode decomposition, empirical wavelet transform, filter banks, mode-mixing, non-linear and non-stationary time series, wavelet

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Authors: Hamida Qumber Ali, Waseem Muhammad Arain, Shama Siddiqui, Sayeed Ghani

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We present an implementing of RMAC in TinyOS 1.x. RMAC is a cross layer and Duty-cycle MAC protocols that was proposed to provide energy efficient transmission services for wireless sensor networks. The protocol has a unique and efficient packet transmission scheduling mechanism that enables it to overcome delivery latency and overcome traffic congestion. Design details and implementation challenges are divulged. Experiments are conducted to show the correctness of our implementation with numerous assumptions. Simulations are performed to compare the performance of RMAC and SMAC. Our results show that RMAC outperforms SMAC in energy efficiency and delay.

Keywords: MAC protocol, performance, RMAC, wireless sensor networks

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Authors: Seyed Sobhan Alvani, Mohammad Gohari

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By developing cities and increasing the population, traffic congestion has become a vital problem. Due to this crisis, urban designers try to present solutions to decrease this difficulty. On the other hand, predicting the model with perfect accuracy is essential for solution-providing. The current study presents a model based on artificial intelligence which can predict traffic index based on city population, growth rate, and area. The accuracy of the model was evaluated, which is acceptable and it is around 90%. Thus, urban designers and planners can employ it for predicting traffic index in the future to provide strategies.

Keywords: traffic index, population growth rate, cities wideness, artificial neural network

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Authors: Leticia Souza Guirra, Márcia Eduarda Vieira Ramos, Edlaine Souza Pereira, Leticia Correa Celeste

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Introduction: Studies indicate that equine-assisted therapy enables improvements in several areas of functioning that are impaired in children with autism spectrum disorder (ASD), such as social interaction and communication. Objective: The study proposes to analyze the development of dialogic skills of a verbal child with ASD after participating in the equine-assisted therapy Step By Step in Communication. Method: This is quantitative and qualitative research through a case study. It refers to a 6 years old child diagnosed with ASD belonging to a group of practitioners of the Brazilian National Equine-Assited-Therapy Association. The Behavioral Observation Protocol (PROC) was used to evaluate communicative skills before and after the intervention, which consisted of 24 sessions once a week. Results: All conversational skills increased their frequency, with participation in dialogue and initiation of interaction. The child also increases the habit of waiting for his turn and answering the interlocutor. The emission of topics not related to conversation and echolalia showed a significant decrease after the intervention. Conclusion: The studied child showed improvement in communicative skills after participating in the equine-assisted therapy Step By Step in Communication. Contributions: This study contributes to a greater understanding of the impact of equine-assisted therapy on the communicative abilities of children with ASD.

Keywords: equine-assisted-therapy, autism spectrum disorder, language, communication, language and hearing sciences

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Authors: Arab M., Ait Abdallah M., Zeraoulia N., Boumaza H., Aoutia M., Griene L., Ait Abdelkader B.,

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breast and ovarian cancer are respectively the first and fourth leading causes of cancer among women in Algeria. A family story of cancer in the most important risk factor, and in most cases of families with breast and /or ovarian cancer, the pattern of cancer family can be attributed to mutation in BRCA1/2genes. objectibes: the aim of our study in to investigate the spectrum of BRCA1/2 germiline mutation in familial breast and /or ovarian cancer and to determine the prevalence and the nature of BRCA1/2mutation in Algeria methods: we deremined the prevalence of BRCA1/2 mutation within a cohort of 161 probands selected according the eisinger score double stranded sanger sequencing of all coding exons of BRCA1/2including flanking intronic region were performed results: we identified a total of 23 distinct deleterious mutations (class5) 12 differents mutations in BRCA1(52%) and 11 in BRCA2(48%). 78% (18/23) were protein truncating and 22%(5/23) missens mutations.3 novel deleterious mutations have been identified, which have not been described in public mutation database. one new mutation were found in two unrelated patients. the overall mutation detection rate in our study is 28,5%(46/161).more over, an UVS c7783 located in BRCA2 is found in two unrelated probands and segregate in the 02 families/ conclusion: our results sugget of large spectrum of BRCA1/2 mutation in Algerian breast/ovarian cancer family. The nature and prevalence of BRCA1/2mutation in algerian families are ongoing in a larger study, 80 probands are to day under investigation. This study which may therefore identify the genetic particularity of Algerian breast /ovarian cancer.

Keywords: BRCA1/2 mutations, hereditary breast cancer, algerian women, prvalence

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Authors: Ferah Tesfaye Admasu

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Autism Spectrum Disorder (ASD) often presents significant communication challenges, particularly for non-verbal individuals who struggle to express their needs and emotions effectively. Assistive technologies (AT) have emerged as vital tools in enhancing communication abilities for this population. Recent advancements in artificial intelligence (AI) hold the potential to revolutionize the design and functionality of these technologies. This study explores the application of AI in developing intelligent, adaptive, and user-centered assistive technologies for non-verbal individuals with autism. Through a review of current AI-driven tools, including speech-generating devices, predictive text systems, and emotion-recognition software, this research investigates how AI can bridge communication gaps, improve engagement, and support independence. Machine learning algorithms, natural language processing (NLP), and facial recognition technologies are examined as core components in creating more personalized and responsive communication aids. The study also discusses the challenges and ethical considerations involved in deploying AI-based AT, such as data privacy and the risk of over-reliance on technology. Findings suggest that integrating AI into assistive technologies can significantly enhance the quality of life for non-verbal individuals with autism, providing them with greater opportunities for social interaction and participation in daily activities. However, continued research and development are needed to ensure these technologies are accessible, affordable, and culturally sensitive.

Keywords: artificial intelligence, autism spectrum disorder, non-verbal communication, assistive technology, machine learning

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Authors: Guneet Saini, Shahrukh, Sunil Sharma

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Traffic congestion is the most critical issue faced by those in the transportation profession today. Over the past few years, roundabouts have been recognized as a measure to promote efficiency at intersections globally. In developing countries like India, this type of intersection still faces a lot of issues, such as bottleneck situations, long queues and increased waiting times, due to increasing traffic which in turn affect the performance of the entire urban network. This research is a case study of a non-conventional roundabout, in terms of geometric design, in a small town in India. These types of roundabouts should be analyzed for their functionality in mixed traffic conditions, prevalent in many developing countries. Microscopic traffic simulation is an effective tool to analyze traffic conditions and estimate various measures of operational performance of intersections such as capacity, vehicle delay, queue length and Level of Service (LOS) of urban roadway network. This study involves analyzation of an unsymmetrical non-circular 6-legged roundabout known as “Kala Aam Chauraha” in a small town Bulandshahr in Uttar Pradesh, India using VISSIM simulation package which is the most widely used software for microscopic traffic simulation. For coding in VISSIM, data are collected from the site during morning and evening peak hours of a weekday and then analyzed for base model building. The model is calibrated on driving behavior and vehicle parameters and an optimal set of calibrated parameters is obtained followed by validation of the model to obtain the base model which can replicate the real field conditions. This calibrated and validated model is then used to analyze the prevailing operational traffic performance of the roundabout which is then compared with a proposed alternative to improve efficiency of roundabout network and to accommodate pedestrians in the geometry. The study results show that the alternative proposed is an advantage over the present roundabout as it considerably reduces congestion, vehicle delay and queue length and hence, successfully improves roundabout performance without compromising on pedestrian safety. The study proposes similar designs for modification of existing non-conventional roundabouts experiencing excessive delays and queues in order to improve their efficiency especially in the case of developing countries. From this study, it can be concluded that there is a need to improve the current geometry of such roundabouts to ensure better traffic performance and safety of drivers and pedestrians negotiating the intersection and hence this proposal may be considered as a best fit.

Keywords: operational performance, roundabout, simulation, VISSIM

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Authors: Evangelia-Chrysanthi Kouklari, Stella Tsermentseli, Claire P. Monks

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Executive function (EF) refers to a set of future-oriented and goal-directed cognitive skills that are crucial for problem solving and social behaviour, as well as the ability to organise oneself. It has been suggested that EF could be conceptualised as two distinct but interrelated constructs, one emotional (hot) and one cognitive (cool), as it facilitates both affective and cognitive regulation. Cool EF has been found to be strongly related to Theory of Mind (ToM) that is the ability to infer mental states, but research has not taken into account the association between hot EF and ToM in Autism Spectrum Disorder (ASD) to date. The present study investigates the associations between both hot and cool EF and ToM in school-aged children with ASD. This cross-sectional study assesses 79 school-aged children with ASD (7-15 years) and 91 controls matched for age and IQ, on tasks tapping cool EF (working memory, inhibition, planning), hot EF (effective decision making, delay discounting), and ToM (emotional understanding and false/no false belief). Significant group differences in each EF measure support a global executive dysfunction in ASD. Strong associations between hot EF and ToM in ASD are reported for the first time (i.e. ToM emotional understanding and delay discounting). These findings highlight that hot EF also makes a unique contribution to the developmental profile of ASD. Considering the role of both hot and cool EF in association with ToM in individuals with ASD may aid in gaining a greater understanding not just of how these complex multifaceted cognitive abilities relate to one another, but their joint role in the distinct developmental pathway followed in ASD.

Keywords: ASD, executive function, school age, theory of mind

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Authors: K. H. Teng, A. Shaw, M. Ateeq, A. Al-Shamma'a, S. Wylie, S. N. Kazi, B. T. Chew

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Numerical and experimental of using novel electromagnetic wave technique to detect water hardness concentration has been presented in this paper. Simulation is powerful and efficient engineering methods which allow for a quick and accurate prediction of various engineering problems. The RF module is used in this research to predict and design electromagnetic wave propagation and resonance effect of a guided wave to detect water hardness concentration in term of frequency domain, eigenfrequency, and mode analysis. A cylindrical cavity resonator is simulated and designed in the electric field of fundamental mode (TM010). With the finite volume method, the three-dimensional governing equations were discretized. Boundary conditions for the simulation were the cavity materials like aluminum, two ports which include transmitting and receiving port, and assumption of vacuum inside the cavity. The design model was success to simulate a fundamental mode and extract S21 transmission signal within 2.1 – 2.8 GHz regions. The signal spectrum under effect of port selection technique and dielectric properties of different water concentration were studied. It is observed that the linear increment of magnitude in frequency domain when concentration increase. The numerical results were validated closely by the experimentally available data. Hence, conclusion for the available COMSOL simulation package is capable of providing acceptable data for microwave research.

Keywords: electromagnetic wave technique, frequency domain, signal spectrum, water hardness concentration

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Authors: Ali Ganoun, Wesam Algablawi, Wasim BenAnaif

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Video based traffic surveillance based on License Plate Recognition (LPR) system is an essential part for any intelligent traffic management system. The LPR system utilizes computer vision and pattern recognition technologies to obtain traffic and road information by detecting and recognizing vehicles based on their license plates. Generally, the video based LPR system is a challenging area of research due to the variety of environmental conditions. The LPR systems used in a wide range of commercial applications such as collision warning systems, finding stolen cars, controlling access to car parks and automatic congestion charge systems. This paper presents an automatic LPR system of Libyan license plate. The performance of the proposed system is evaluated with three video sequences.

Keywords: license plate recognition, localization, segmentation, recognition

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Authors: Michaela Dušková, Kateřina Šimůnková, Martin Hill, Hana Hruškovičová, Hana Pospíšilová, Eva Králíková, Luboslav Stárka

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Smoking represents the most widespread substance dependence in the world. Several studies show the nicotine's ability to alter women hormonal homeostasis. Women smokers have higher testosterone and lower estradiol levels throughout life compared to non-smoker women. We monitored the effect of smoking discontinuation on steroid spectrum with 40 premenopausal and 60 postmenopausal women smokers. These women had been examined before they discontinued smoking and also after 6, 12, 24, and 48 weeks of abstinence. At each examination, blood was collected to determine steroid spectrum (measured by GC-MS), LH, FSH, and SHBG (measured by IRMA). Repeated measures ANOVA model was used for evaluation of the data. The study has been approved by the local Ethics Committee. Given the small number of premenopausal women who endured not to smoke, only the first 6 week period data could be analyzed. A slight increase in androgens after the smoking discontinuation occurred. In postmenopausal women, an increase in testosterone, dihydrotestosterone, dehydroepiandrosterone, and other androgens occurred, too. Nicotine replacement therapy, weight changes, and age does not play any role in the androgen level increase. The higher androgens levels correlated with failure in smoking cessation. Women smokers have higher androgen levels, which might play a role in smoking dependence development. Women successful in smoking cessation, compared to the non-successful ones, have lower androgen levels initially and also after smoking discontinuation. The question is what androgen levels women have before they start smoking.

Keywords: addiction, smoking, cessation, androgens

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Authors: Richard Sogah

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The significance of transport infrastructure investments for economic growth and development has been central to the World Bank’s strategy for poverty reduction. Among the conventional surface transport infrastructures, road infrastructure is significant in facilitating the movement of human capital goods and services. When transport projects (i.e., roads, super-highways) are implemented, they come along with some negative social values (costs), such as increased noise and air pollution for local residents living near these facilities, displaced individuals, etc. However, these projects also facilitate better utilization of existing capital stock and generate other observable benefits that can be easily quantified. For example, the improvement or construction of roads creates employment, stimulates revenue generation (toll), reduces vehicle operating costs and accidents, increases accessibility, trade expansion, safety improvement, etc. Aside from these benefits, travel time savings (TTSs) which are the major economic benefits of urban and inter-urban transport projects and therefore integral in the economic assessment of transport projects, are often overlooked and omitted when estimating the benefits of transport projects, especially in developing countries. The absence of current and reliable domestic travel data and the inability of replicated models from the developed world to capture the actual value of travel time savings due to the large unemployment, underemployment, and other labor-induced distortions has contributed to the failure to assign value to travel time savings when estimating the benefits of transport schemes in developing countries. This omission of the value of travel time savings from the benefits of transport projects in developing countries poses problems for investors and stakeholders to either accept or dismiss projects based on schemes that favor reduced vehicular operating costs and other parameters rather than those that ease congestion, increase average speed, facilitate walking and handloading, and thus save travel time. Given the complex reality in the estimation of the value of travel time savings and the presence of widespread informal labour activities in Sub-Saharan Africa, we construct a “nationally ranked distribution of time values” and estimate the value of travel time savings based on the area beneath the distribution. Compared with other approaches, our method captures both formal sector workers and individuals/people who work outside the formal sector and hence changes in their time allocation occur in the informal economy and household production activities. The dataset for the estimations is sourced from the World Bank, the International Labour Organization, etc.

Keywords: road infrastructure, transport projects, travel time savings, congestion, Sub-Sahara Africa

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Authors: Anshul Gupta, T. Shankar

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In this paper, we had analyzed the call drop to provide a good quality of service to user. By optimizing it we can increase the coverage area and also the reduction of interference and congestion created in a network. Basically handover is the transfer of call from one cell site to another site during a call. Here we have analyzed the whole network by two method-statistic model and analytic model. In statistic model we have collected all the data of a network during busy hour and normal 24 hours and in analytic model we have the equation through which we have to find the call drop probability. By avoiding unnecessary handovers we can increase the number of calls per hour. The most important parameter is co-efficient of variation on which the whole paper discussed.

Keywords: coefficient of variation, mean, standard deviation, call drop probability, handover

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Authors: SKhan Park, Seok Jin Lee, Jong Sun Kim, Jun Ho Lee, Bong Chan Kim

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Because of the large economic losses caused by traffic congestion in metropolitan areas, various studies on the underground network design and construction techniques has been performed various studies in the developed countries. In Korea, it has performed a study to develop a versatile double-deck of deep tunnel model. This paper is an introduction to develop a ground reinforcement method to enable the safe tunnel construction in the weakened pillar section like as junction of tunnel. Applicable ground reinforcement method in the weakened section is proposed and it is expected to verify the method by the field application tests.

Keywords: double-deck tunnel, ground reinforcement, tunnel construction, weakened pillar section

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Authors: Yibeltal Chanie Manie, Zebider Asire Munyelet

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5G and 6G technology offers enhanced quality of service with high data transmission rates, which necessitates the implementation of the Internet of Things (IoT) in 5G/6G architecture. In this paper, we proposed the integration of free space optical communication (FSO) with fiber sensor networks for IoT applications. Recently, free-space optical communications (FSO) are gaining popularity as an effective alternative technology to the limited availability of radio frequency (RF) spectrum. FSO is gaining popularity due to flexibility, high achievable optical bandwidth, and low power consumption in several applications of communications, such as disaster recovery, last-mile connectivity, drones, surveillance, backhaul, and satellite communications. Hence, high-speed FSO is an optimal choice for wireless networks to satisfy the full potential of 5G/6G technology, offering 100 Gbit/s or more speed in IoT applications. Moreover, machine learning must be integrated into the design, planning, and optimization of future optical wireless communication networks in order to actualize this vision of intelligent processing and operation. In addition, fiber sensors are important to achieve real-time, accurate, and smart monitoring in IoT applications. Moreover, we proposed deep learning techniques to estimate the strain changes and peak wavelength of multiple Fiber Bragg grating (FBG) sensors using only the spectrum of FBGs obtained from the real experiment.

Keywords: optical sensor, artificial Intelligence, Internet of Things, free-space optics

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Authors: Jessica Scher Lisa, Eric Shyman

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Autism spectrum disorder (ASD) is a neuro-developmental disorder that is characterized by persistent deficits in social communication and social interaction (i.e. deficits in social-emotional reciprocity, nonverbal communicative behaviors, and establishing/maintaining social relationships), as well as by the presence of repetitive behaviors and perseverative areas of interest (i.e. stereotyped or receptive motor movements, use of objects, or speech, rigidity, restricted interests, and hypo or hyperactivity to sensory input or unusual interest in sensory aspects of the environment). Additionally, diagnoses of ASD require the presentation of symptoms in the early developmental period, marked impairments in adaptive functioning, and a lack of explanation by general intellectual impairment or global developmental delay (although these conditions may be co-occurring). Over the past several decades, many theories have been developed in an effort to explain the root cause of ASD in terms of atypical central cognitive processes. The field of neuroscience is increasingly finding structural and functional differences between autistic and neurotypical individuals using neuro-imaging technology. One main area this research has focused upon is in visuospatial processing, with specific attention to the notion of ‘weak central coherence’ (WCC). This paper offers an analysis of findings from selected studies in order to explore research that challenges the ‘deficit’ characterization of a weak central coherence theory as opposed to a ‘superiority’ characterization of strong local coherence. The weak central coherence theory has long been both supported and refuted in the ASD literature and has most recently been increasingly challenged by advances in neuroscience. The selected studies lend evidence to the notion of amplified localized perception rather than deficient global perception. In other words, WCC may represent superiority in ‘local processing’ rather than a deficit in global processing. Additionally, the right hemisphere and the specific area of the extrastriate appear to be key in both the visual and lexicosemantic process. Overactivity in the striate region seems to suggest inaccuracy in semantic language, which lends itself to support for the link between the striate region and the atypical organization of the lexicosemantic system in ASD.

Keywords: autism spectrum disorder, neurology, visual processing, weak coherence

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Authors: Zikra Faiz, Nisar Abid, Muhammad Waqas

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This study aim to examine the challenges faced by teachers during teaching to those students who are intellectually disable, suffering from autism spectrum disorder, learning disability, and ADHD at the primary level. The descriptive research design of quantitative approach was adopted to conduct this study; a cross-sectional survey method was used to collect data. The sample was comprised of 258 (43 male and 215 female) teachers who teach at special education institutes of Lahore district selected through proportionate stratified random sampling technique. Self-developed questionnaire was used which was comprised of 22 closed-ended items. Collected data were analyzed through descriptive and inferential statistical techniques by using Statistical Package for Social Sciences (SPSS) version 21. Results show that teachers faced problems during group activities, to handle bad behavior and different disabilities of students. It is concluded that there was a significant difference between male and female teachers perceptions about challenges faced during teaching with developmental disable students. Furthermore, there was a significant difference exist in the perceptions of teachers regarding challenges faced during teaching to students with developmental disabilities in term of teachers’ age and area of specialization. It is recommended that developmentally disable student require extra attention so that, teacher should trained through pre-service and in-service training to teach developmentally disabled students.

Keywords: intellectual disability, autism spectrum disorder, ADHD, learning disability

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Authors: Mustafa Alhamdi

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Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

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Authors: Gursimran Jandu, Melissa Nelson, Mia Ingram, Hana Jalal

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There is a significant overlap between autism spectrum disorder (ASD) and obsessive-compulsive disorder (OCD), with up to 90% of young people diagnosed with ASD having this co-morbidity. Distinguishing between the symptoms of the two leads to issues with accurate treatment, yet this is paramount in benefiting the young person. There are two distinct methods of treatment, psychological or pharmacological, with clinicians tending to choose one or the other, potentially due to the lack of research available. This report reviews the efficacy of psychological and pharmacological treatments for young people diagnosed with ASD and co-morbid OCD. A literature review was performed on papers from the last fifteen years including ‘ASD’, ‘OCD’ and individuals under the age of 18. Eleven papers were selected as relevant. The report looks at the comparison between more traditional methods, such as selective-serotonin-reuptake-inhibitors (SSRI) and Cognitive behaviour therapy (CBT), and newer therapies, such as modified or intensive ASD focused psychotherapies, and the use of other medication classes. On reviewing the data, it was identified that there was a distinct lack of information on this important topic. The most widely used treatment was medication such as Fluoxetine, an SSRI, which rarely showed improvement in symptoms or outcomes. This is in contrast to modified forms of CBT which often reduces symptoms or even results in OCD remission. With increased research into non-traditional management of these co-morbid conditions, it is clear there is scope that modified CBT may become the future treatment of choice for OCD in young people with ASD.

Keywords: autism spectrum disorder, intensive or adapted cognitive behavioural therapy, obsessive compulsive disorder, pharmacological management

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Authors: Hugo Sampaio Libero, Max de Castro Magalhaes

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The perception of sound radiated from a building floor is greatly influenced by the rooms in which it is immersed and by the position of both listener and source. The main question that remains unanswered is related to the influence of the source position on the sound power radiated by a complex wall-floor system in buildings. This research is concerned with the investigation of vibration transmission across walls and floors in buildings. It is primarily based on the determination of vibration reduction index via experimental tests. Knowledge of this parameter may help in predicting noise and vibration propagation in building components. First, the physical mechanisms involving vibration transmission across structural junctions are described. An experimental setup is performed to aid this investigation. The experimental tests have shown that the vibration generation in the walls and floors is directed related to their size and boundary conditions. It is also shown that the vibration source position can affect the overall vibration spectrum significantly. Second, the characteristics of the noise spectra inside the rooms due to an impact source (tapping machine) are also presented. Conclusions are drawn for the general trend of vibration and noise spectrum of the structural components and rooms, respectively. In summary, the aim of this paper is to investigate the vibro-acoustical behavior of building floors and walls under floor impact excitation. The impact excitation was at distinct positions on the slab. The analysis has highlighted the main physical characteristics of the vibration transmission mechanism.

Keywords: vibration transmission, vibration reduction index, impact excitation, experimental tests

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Authors: Sawitree Wongkittirungrueang

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The objectives of this research were: 1) to study the effect of social stories on social interaction of students with autism. The sample was Pratomsuksa level 5 student with autism, Khon Kaen University Demonstration School, who was diagnosed by the Physician as High Functioning Autism since he was able to read, write, calculate and was studying in inclusive classroom. However, he still had disability in social interaction to participate in social activity group and communication. He could not learn how to develop friendship or create relationship. He had inappropriate behavior in social context. He did not understand complex social situations. In addition, he did seemed not know time and place. He was not able to understand feeling of oneself as well as the others. Consequently, he could not express his emotion appropriately. He did not understand or express his non-verbal language for communicating with friends. He lacked of common interest or emotion with nearby persons. He greeted inappropriately or was not interested in greeting. In addition, he did not have eye contact. He used inadequate language etc. He was elected by Purposive Sampling. His parents were willing to allow them to participate in this study. The research instruments were the lesson plan of social stories, and the picture book of social stories. The instruments used for data collection, were the social interaction evaluation of autistic students. This research was Quasi Experimental Research as One Group Pre-test, Post-test Design. For the Pre-test, the experiment was conducted by social stories. Then, the Post-test was implemented. The statistic used for data analysis, included the Mean, and Standard Deviation. The research findings were shown by Graph. The findings revealed hat the autistic students taught by social stories indicated better social interaction after being taught by social stories.

Keywords: social story, autism spectrum disorder (ASD), autism, social interaction

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Authors: Manish Saha, Manish Kumar Niranjan, Saket Asthana

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The K₀.₅Na₀.₅NbO₃ (KNN) system has emerged as one of the most promising lead-free piezoelectric over the years. In this work, we perform a comprehensive investigation of electronic structure, lattice dynamics and dielectric/ferroelectric properties of the room temperature phase of KNN by combining ab-initio DFT-based theoretical analysis and experimental characterization. We assign the symmetry labels to KNN vibrational modes and obtain ab-initio polarized Raman spectra, Infrared (IR) reflectivity, Born-effective charge tensors, oscillator strengths etc. The computed Raman spectrum is found to agree well with the experimental spectrum. In particular, the results suggest that the mode in the range ~840-870 cm-¹ reported in the experimental studies is longitudinal optical (LO) with A_1 symmetry. The Raman mode intensities are calculated for different light polarization set-ups, which suggests the observation of different symmetry modes in different polarization set-ups. The electronic structure of KNN is investigated, and an optical absorption spectrum is obtained. Further, the performances of DFT semi-local, metal-GGA and hybrid exchange-correlations (XC) functionals, in the estimation of KNN band gaps are investigated. The KNN bandgap computed using GGA-1/2 and HSE06 hybrid functional schemes are found to be in excellant agreement with the experimental value. The COHP, electron localization function and Bader charge analysis is also performed to deduce the nature of chemical bonding in the KNN. The solid-state reaction and hydrothermal methods are used to prepare the KNN ceramics, and the effects of grain size on the physical characteristics these ceramics are examined. A comprehensive study on the impact of different synthesis techniques on the structural, electrical, and photocatalytic properties of ferroelectric ceramics KNN. The KNN-S prepared by solid-state method have significantly larger grain size as compared to that for KNN-H prepared by hydrothermal method. Furthermore, the KNN-S is found to exhibit higher dielectric, piezoelectric and ferroelectric properties as compared to KNN-H. On the other hand, the increased photocatalytic activity is observed in KNN-H as compared to KNN-S. As compared to the hydrothermal synthesis, the solid-state synthesis causes an increase in the relative dielectric permittivity (ε^') from 2394 to 3286, remnant polarization (P_r) from 15.38 to 20.41 μC/cm^², planer electromechanical coupling factor (k_p) from 0.19 to 0.28 and piezoelectric coefficient (d_33) from 88 to 125 pC/N. The KNN-S ceramics are also found to have a lower leakage current density, and higher grain resistance than KNN-H ceramic. The enhanced photocatalytic activity of KNN-H is attributed to relatively smaller particle sizes. The KNN-S and KNN-H samples are found to have degradation efficiencies of RhB solution of 20% and 65%, respectively. The experimental study highlights the importance of synthesis methods and how these can be exploited to tailor the dielectric, piezoelectric and photocatalytic properties of KNN. Overall, our study provides several bench-mark important results on KNN that have not been reported so far.

Keywords: lead-free piezoelectric, Raman intensity spectrum, electronic structure, first-principles calculations, solid state synthesis, photocatalysis, hydrothermal synthesis

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