Search results for: edge data centers

Authors: A. Benatiallah, D. Benatiallah, F. Abaidi, B. Nasri, A. Harrouz, S. Mansouri

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The region of Adrar is located in the south-western Algeria and covers a total area of 443.782 km², occupied by a population of 432,193 inhabitants. The main activity of population is agriculture, mainly based on the date palm cultivation occupies a total area of 23,532 ha. Adrar region climate is a continental desert characterized by a high variation in temperature between months (July, August) it exceeds 48°C and coldest months (December, January) with 16°C. Rainfall is very limited in frequency and volume with an aridity index of 4.6 to 5 which corresponds to a type of arid climate. Geologically Adrar region is located on the edge North West and is characterized by a Precambrian basement cover stolen sedimentary deposit of Phanerozoic age transgressive. The depression is filled by Touat site Paleozoic deposits (Cambrian to Namurian) of a vast sedimentary basin extending secondary age of the Saharan Atlas to the north hamada Tinhirt Tademaït and the plateau of south and Touat Gourara west to Gulf of Gabes in the Northeast. In this work we have study geothermal potential of Adrar region from the borehole data eatable in various sites across the area of 400,000 square kilometres; from these data we developed a GIS (Adrar_GIS) that plots data on the various points and boreholes in the region specifying information on available geothermal potential has variable depths.

Keywords: sig, geothermal, potenteil, temperature

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Authors: Yan Ding, Fei Yan, Ji Liang, Hong Jiang, Xiaoguang Yang, Xu Qian

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The health status of GonjiKolela District, Amhara Region, Ethiopia is below its national average, and a sub-project of China UK Global Health Support Programme (GHSP) is expected to increase the uptake of a suite of reproductive, maternal, newborn and child health (RMNCH) interventions there. To explore what is on the ground and what could be helpful for the uptake of RMNCH services in GonjiKolela, a qualitative study was performed as part of the baseline assessment before the implementation of the project. Nine key informants from GonjiKolela were interviewed with self-designed interview guides and they were from the district Health Office, health centers, health posts, women health development army (community volunteer groups), mothers of newborns, and also a gynecologist from the maternal and child health center which is the referral center for pregnant women for this project. The interview were transcribed into words and sorted with qualitative analysis software MAXqda. Content analysis was mainly used to analyze the data. The district health office, the health centers and the health posts all had focal persons taking care of the management and provision of RMNCH services, and RMNCH related indicators were recorded and reported at each level routinely. In addition, district government and administration at community/administrative village level kept a close eye on the reduction of maternal, neonatal and child mortality. Women Health Development Amy at household level supported health workers at community/administrative village level (called health extension workers) in tracing, recording and reporting pregnant women, newborn and under-five children,organizing events for health education, demonstrating and leading health promotion activities, and stimulating the utilization of RMNCH.

Keywords: Reproductive Maternal Newborn and Child Health, Health Care Utilization, Qualitative Study, Ethiopia

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Authors: Esra Güney, Tuba Uçar

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Aim: This study has been conducted for the purpose of determining the effects of fetal movement counting on antenatal maternal attachment. Material and Method: This research was conducted on the basis of the real test model with the pre-test /post-test control groups. The study population consists of pregnant women registered in the six different Family Health Centers located in the central Malatya districts of Yeşilyurt and Battalgazi. When power analysis is done, the sample size was calculated for each group of at least 55 pregnant women (55 tests, 55 controls). The data were collected by using Personal Information Form and MAAS (Maternal Antenatal Attachment Scale) between July 2015-June 2016. Fetal movement counting training was given to pregnant women by researchers in the experimental group after the pre-test data collection. No intervention was applied to the control group. Post-test data for both groups were collected after four weeks. Data were evaluated with percentage, chi-square arithmetic average, chi-square test and as for the dependent and independent group’s t test. Result: In the MAAS, the pre-test average of total scores in the experimental group is 70.78±6.78, control group is also 71.58±7.54 and so there was no significant difference in mean scores between the two groups (p>0.05). MAAS post-test average of total scores in the experimental group is 78.41±6.65, control group is also is 72.25±7.16 and so the mean scores between groups were found to have statistically significant difference (p<0.05). Conclusion: It was determined that fetal movement counting increases the maternal antenatal attachments.

Keywords: antenatal maternal attachment, fetal movement counting, pregnancy, midwifery

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Authors: Hoora Dehghani, Meisam Shahbazi, Reza Zare

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During the previous decade, a significant evolution has occurred in the number of private educational centers and, accordingly, the increase in the number of providers and students of these centers around the world. The number of language teaching institutes in Iran that are considered private educational sectors is also growing exponentially as the request for learning foreign languages has extremely increased in recent years. This fact caused competition among the institutions in improving better services tailored to the students’ demands to win the competition. Along with the growth in the industry of education, higher education institutes should apply the marketing-related concepts and view students as customers because students’ outlooks are similar to consumers with education. Studying the influential factors in the selection of an institute has multiple benefits. Firstly, it acknowledges the institutions of the students’ choice factors. Secondly, the institutions use the obtained information to improve their marketing methods. It also helps institutions know students’ outlooks that can be applied to expand the student know-how. Moreover, it provides practical evidence for educational centers to plan useful amenities and programs, and use efficient policies to cater to the market, and also helps them execute the methods that increase students’ feeling of contentment and assurance. Thus, this study explored the influencing factors in the selection of a language learning institute by language learners and examined and compared the importance among the varying age groups and genders. In the first phase of the study, the researchers selected 15 language learners as representative cases within the specified age ranges and genders purposefully and interviewed them to explore the comprising elements in their language institute selection process and analyzed the results qualitatively. In the second phase, the researchers identified elements as specified items of a questionnaire, and 1000 English learners across varying educational contexts rated them. The TOPSIS method was used to analyze the data quantitatively by representing the level of importance of the items for the participants generally and specifically in each subcategory; genders and age groups. The results indicated that the educational quality, teaching method, duration of training course, establishing need-oriented courses, and easy access were the most important elements. On the other hand, offering training in different languages, the specialized education of only one language, the uniform and appropriate appearance of office staff, having native professors to the language of instruction, applying Computer or online tests instead of the usual paper tests respectively as the least important choice factors in selecting a language institute. Besides, some comparisons among different groups’ ratings of choice factors were made, which revealed the differences among different groups' priorities in choosing a language institute.

Keywords: choice factors, EFL institute selection, english learning, need analysis, TOPSIS

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Authors: Ankur Dixit, Hiroaki Wagatsuma

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The crack detection on a concrete bridge is an important and constant task in civil engineering. Chronically, humans are checking the bridge for inspection of cracks to maintain the quality and reliability of bridge. But this process is very long and costly. To overcome such limitations, we have used a drone with a digital camera, which took some images of bridge deck and these images are processed by morphological component analysis (MCA). MCA technique is a very strong application of sparse coding and it explores the possibility of separation of images. In this paper, MCA has been used to decompose the image into coarse and fine components with the effectiveness of two dictionaries namely anisotropic diffusion and wavelet transform. An anisotropic diffusion is an adaptive smoothing process used to adjust diffusion coefficient by finding gray level and gradient as features. These cracks in image are enhanced by subtracting the diffused coarse image into the original image and the results are treated by Sobel edge detector and binary filtering to exhibit the cracks in a fine way. Our results demonstrated that proposed MCA framework using anisotropic diffusion followed by Sobel operator and binary filtering may contribute to an automation of crack detection even in open field sever conditions such as bridge decks.

Keywords: anisotropic diffusion, coarse component, fine component, MCA, Sobel edge detector and wavelet transform

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Authors: Sameh Ibrahim Ghali Hanna

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Information system (IS) are fairly crucial in the operation of private and public establishments in growing and developed international locations. Growing countries are saddled with many project failures throughout the implementation of records systems. However, successful information systems are greatly wished for in developing nations in an effort to decorate their economies. This paper is extraordinarily critical in view of the high failure fee of data structures in growing nations, which desire to be decreased to minimal proper levels by means of advocated interventions. This paper centers on a review of IS development in developing international locations. The paper gives evidence of the IS successes and screw-ups in developing nations and posits a version to deal with the IS failures. The proposed model can then be utilized by means of growing nations to lessen their IS mission implementation failure fee. A contrast is drawn between IS improvement in growing international locations and evolved international locations. The paper affords valuable records to assist in decreasing IS failure, and growing IS models and theories on IS development for developing countries.

Keywords: research information systems (RIS), research information, heterogeneous sources, data quality, data cleansing, science system, standardization artificial intelligence, AI, enterprise information system, EIS, integration developing countries, information systems, IS development, information systems failure, information systems success, information systems success model

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Authors: Nupur A. D., Miah M. S., Moniruzzaman S. K.

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Autism is a neurobiological disorder that affects physical, social, and language skills of a person. A child with autism feels difficulty for processing, integrating, and responding to sensory stimuli. Current estimates have shown that 45% to 96 % of children with Autism Spectrum Disorder demonstrate sensory difficulties. As autism is a worldwide burning issue, it has become a highly prioritized and important service provision in Bangladesh. The sensory deficit does not only hamper the normal development of a child, it also hampers the learning process and functional independency. The purpose of this study was to find out the prevalence of sensory dysfunction among children with autism and recognize common patterns of sensory dysfunction. A cross-sectional study design was chosen to carry out this research work. This study enrolled eighty children with autism and their parents by using the systematic sampling method. In this study, data were collected through the Short Sensory Profile (SSP) assessment tool, which consists of 38 items in the questionnaire, and qualified graduate Occupational Therapists were directly involved in interviewing parents as well as observing child responses to sensory related activities of the children with autism from four selected autism centers in Dhaka, Bangladesh. All item analyses were conducted to identify items yielding or resulting in the highest reported sensory processing dysfunction among those children through using SSP and Statistical Package for Social Sciences (SPSS) version 21.0 for data analysis. This study revealed that almost 78.25% of children with autism had significant sensory processing dysfunction based on their sensory response to relevant activities. Under-responsive sensory seeking and auditory filtering were the least common problems among them. On the other hand, most of them (95%) represented that they had definite to probable differences in sensory processing, including under-response or sensory seeking, auditory filtering, and tactile sensitivity. Besides, the result also shows that the definite difference in sensory processing among 64 children was within 100%; it means those children with autism suffered from sensory difficulties, and thus it drew a great impact on the children’s Daily Living Activities (ADLs) as well as social interaction with others. Almost 95% of children with autism require intervention to overcome or normalize the problem. The result gives insight regarding types of sensory processing dysfunction to consider during diagnosis and ascertaining the treatment. So, early sensory problem identification is very important and thus will help to provide appropriate sensory input to minimize the maladaptive behavior and enhance to reach the normal range of adaptive behavior.

Keywords: autism, sensory processing difficulties, sensory profile, occupational therapy

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Authors: Viriyavudh Sim, WooYoung Jung

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Damage due to high wind is not limited to load resistance components such as beam and column. The majority of damage is due to breach in the building envelope such as broken roof, window, and door. In this paper, wind fragility of window glass in residential apartment was determined to compare the difference between two window configuration models. Monte Carlo Simulation method had been used to derive damage data and analytical fragilities were constructed. Fragility of window system showed that window located in leeward wall had higher probability of failure, especially those close to the edge of structure. Between the two window models, Model 2 had higher probability of failure, this was due to the number of panel in this configuration.

Keywords: wind fragility, glass window, high rise building, wind disaster

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Authors: Sharon Hovav, Ilya Levner, Oren Nahum, Istvan Szabo

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In modern large-scale logistic centers (e.g., big automated warehouses), complex logistic operations performed by human staff (pickers) need to be coordinated with the operations of automated facilities (robots, conveyors, cranes, lifts, flow racks, etc.). The efficiency of advanced logistic centers strongly depends on optimizing picking technologies in synch with the facility/product layout, as well as on optimal distribution of material flows (products) in the system. The challenge is to develop a mathematical operations research (OR) tool that will optimize system cost-effectiveness. In this work, we propose a model that describes an automatic logistic center consisting of a set of workstations located at several galleries (floors), with each station containing a known number of flow racks. The requirements of each product and the working capacity of stations served by a given set of workers (pickers) are assumed as predetermined. The goal of the model is to maximize system efficiency. The proposed model includes two echelons. The first is the setting of the (optimal) number of workstations needed to create the total processing/logistic system, subject to picker capacities. The second echelon deals with the assignment of the products to the workstations and flow racks, aimed to achieve maximal throughputs of picked products over the entire system given picker capacities and budget constraints. The solutions to the problems at the two echelons interact to balance the overall load in the flow racks and maximize overall efficiency. We have developed an operations research model within each echelon. In the first echelon, the problem of calculating the optimal number of workstations is formulated as a non-standard bin-packing problem with capacity constraints for each bin. The problem arising in the second echelon is presented as a constrained product-workstation-flow rack assignment problem with non-standard mini-max criteria in which the workload maximum is calculated across all workstations in the center and the exterior minimum is calculated across all possible product-workstation-flow rack assignments. The OR problems arising in each echelon are proved to be NP-hard. Consequently, we find and develop heuristic and approximation solution algorithms based on exploiting and improving local optimums. The LC model considered in this work is highly dynamic and is recalculated periodically based on updated demand forecasts that reflect market trends, technological changes, seasonality, and the introduction of new items. The suggested two-echelon approach and the min-max balancing scheme are shown to work effectively on illustrative examples and real-life logistic data.

Keywords: logistics center, product-workstation, assignment, maximum performance, load balancing, fast algorithm

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Authors: Amarendar Reddy Addula

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Definition of Artificial Intelligence: Artificial intelligence is the simulation of mortal intelligence processes by machines, especially computer systems. Explicit operations of AI comprise expert systems, natural language processing, and speech recognition, and machine vision. Artificial Intelligence (AI) is an original medium for digital business, according to a new report by Gartner. The last 10 times represent an advance period in AI’s development, prodded by the confluence of factors, including the rise of big data, advancements in cipher structure, new machine literacy ways, the materialization of pall computing, and the vibrant open- source ecosystem. Influence of AI to a broader set of use cases and druggies and its gaining fashionability because it improves AI’s versatility, effectiveness, and rigidity. Edge AI will enable digital moments by employing AI for real- time analytics closer to data sources. Gartner predicts that by 2025, further than 50 of all data analysis by deep neural networks will do at the edge, over from lower than 10 in 2021. Responsible AI is a marquee term for making suitable business and ethical choices when espousing AI. It requires considering business and societal value, threat, trust, translucency, fairness, bias mitigation, explainability, responsibility, safety, sequestration, and nonsupervisory compliance. Responsible AI is ever more significant amidst growing nonsupervisory oversight, consumer prospects, and rising sustainability pretensions. Generative AI is the use of AI to induce new vestiges and produce innovative products. To date, generative AI sweats have concentrated on creating media content similar as photorealistic images of people and effects, but it can also be used for law generation, creating synthetic irregular data, and designing medicinals and accoutrements with specific parcels. AI is the subject of a wide- ranging debate in which there's a growing concern about its ethical and legal aspects. Constantly, the two are varied and nonplussed despite being different issues and areas of knowledge. The ethical debate raises two main problems the first, abstract, relates to the idea and content of ethics; the alternate, functional, and concerns its relationship with the law. Both set up models of social geste, but they're different in compass and nature. The juridical analysis is grounded on anon-formalistic scientific methodology. This means that it's essential to consider the nature and characteristics of the AI as a primary step to the description of its legal paradigm. In this regard, there are two main issues the relationship between artificial and mortal intelligence and the question of the unitary or different nature of the AI. From that theoretical and practical base, the study of the legal system is carried out by examining its foundations, the governance model, and the nonsupervisory bases. According to this analysis, throughout the work and in the conclusions, International Law is linked as the top legal frame for the regulation of AI.

Keywords: artificial intelligence, ethics & human rights issues, laws, international laws

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Authors: Anahita Shahrokhi, Hamed Kazemzadeh

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Various issues are included in cultural relations between societies. Art styles along with architectural similarities are by far one of the most noticeable cultural-historic relations. The Dagestan Republic located in the south of Russia Federation in the North Caucasus has had cultural relations with historical Iran since long ago and is considered as a part of the Islamic world. From Sassanid era and Islamic Empire prior to Tsars’ government, such relations had been maintained largely due to Iran and Islam’s political and social dominance over the region. The presence of the Iranians, mostly for business and commerce, is evident through not only written documents but also other cultural elements including architecture and art. Southern Dagestan and northern provinces of Iran, not distant from each other by sea, have a lot of artistic and cultural aspects in common. The architecture used in some structures such as religious centers, Tekie and Saqa Nafars strongly resembles religious centers in the south of Dagestan. The majority of these similarities lie in the wooden carvings, engravings, and paintings of the interior decorations on the pillars, capitals, walls, and ceilings, as well as the similarity of the plans. Such designs were formed in Safavid dynasty first in Mazandaran and later in Dagestan so that this style is currently named Persiski, meaning Persian, in the Dagestan Republic. These similarities indicate the relationship between the artists and educated people from Iran and Dagestan and the Iranians’ role on the religious and cultural development of Dagestan from the 17th and 18th centuries.

Keywords: wooden works, Mazandaran, Dagestan, Saqa Nafar, ritual and Islamic architecture

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Authors: David P. Tantua, Abdulkader Helwan

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Biometrics has been recently used for the human identification systems using the biological traits such as the fingerprints and iris scanning. Identification systems based biometrics show great efficiency and accuracy in such human identification applications. However, these types of systems are so far based on some image processing techniques only, which may decrease the efficiency of such applications. Thus, this paper aims to develop a human palmprint identification system using multi-layer perceptron neural network which has the capability to learn using a backpropagation learning algorithms. The developed system uses images obtained from a public database available on the internet (CASIA). The processing system is as follows: image filtering using median filter, image adjustment, image skeletonizing, edge detection using canny operator to extract features, clear unwanted components of the image. The second phase is to feed those processed images into a neural network classifier which will adaptively learn and create a class for each different image. 100 different images are used for training the system. Since this is an identification system, it should be tested with the same images. Therefore, the same 100 images are used for testing it, and any image out of the training set should be unrecognized. The experimental results shows that this developed system has a great accuracy 100% and it can be implemented in real life applications.

Keywords: biometrics, biological traits, multi-layer perceptron neural network, image skeletonizing, edge detection using canny operator

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Authors: Danjuma Bawa

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This paper aimed at exploring the capabilities of Location-Allocation model in complementing the strides of the existing physical planning models in the location and distribution of facilities for regional consumption. The paper was designed to provide a blueprint to the Nigerian government and other donor agencies especially the Fertilizer Distribution Initiative (FDI) by the federal government for the revitalization of the terrorism ravaged regions. Theoretical underpinnings of central place theory related to spatial distribution, interrelationships, and threshold prerequisites were reviewed. The study showcased how Location-Allocation Model (L-AM) alongside Central Place Theory (CPT) was applied in Geographic Information System (GIS) environment to; map and analyze the spatial distribution of settlements; exploit their physical and economic interrelationships, and to explore their hierarchical and opportunistic influences. The study was purely spatial qualitative research which largely used secondary data such as; spatial location and distribution of settlements, population figures of settlements, network of roads linking them and other landform features. These were sourced from government ministries and open source consortium. GIS was used as a tool for processing and analyzing such spatial features within the dictum of CPT and L-AM to produce a comprehensive spatial digital plan for equitable and judicious location and distribution of fertilizer deports in the study area in an optimal way. Population threshold was used as yardstick for selecting suitable settlements that could stand as service centers to other hinterlands; this was accomplished using the query syntax in ArcMapTM. ArcGISTM’ network analyst was used in conducting location-allocation analysis for apportioning of groups of settlements around such service centers within a given threshold distance. Most of the techniques and models ever used by utility planners have been centered on straight distance to settlements using Euclidean distances. Such models neglect impedance cutoffs and the routing capabilities of networks. CPT and L-AM take into consideration both the influential characteristics of settlements and their routing connectivity. The study was undertaken in two terrorism ravaged Local Government Areas of Adamawa state. Four (4) existing depots in the study area were identified. 20 more depots in 20 villages were proposed using suitability analysis. Out of the 300 settlements mapped in the study area about 280 of such settlements where optimally grouped and allocated to the selected service centers respectfully within 2km impedance cutoff. This study complements the giant strides by the federal government of Nigeria by providing a blueprint for ensuring proper distribution of these public goods in the spirit of bringing succor to these terrorism ravaged populace. This will ardently at the same time help in boosting agricultural activities thereby lowering food shortage and raising per capita income as espoused by the government.

Keywords: central place theory, GIS, location-allocation, network analysis, urban and regional planning, welfare economics

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Authors: Pedram Khazaie, Sajjad Moein

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In the conventional hot forging of Tongue, which is a fitting for polymer insulator, the material wasted to flash accounts for 20-30% of workpiece. In order to reduce the cost of forged products, this waste material must be minimized. In this study, a flashless forging die is designed and simulated using the finite element method (FEM). A solution to avoid overloading the die with a simple preform is also presented. Moreover, since in flashless forging, burr is formed on the edge of workpiece, a controlled flash forging method is proposed to solve this problem. The simulation results have been validated by experiments; achieving close agreement between simulated and experimental data. It was shown that numerical modeling is helpful in reducing cost and time in the manufacturing process.

Keywords: burr formation, die design, finite element method, flashless forging

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Authors: Jie Zhao, Meng Su

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Image recognition, as one of the most critical technologies in computer vision, works to help machine-like robotics understand a scene, that is, if deployed appropriately, will trigger the revolution in remote sensing and industry automation. With the developments of AI technologies, there are many prevailing and sophisticated neural networks as technologies developed for image recognition. However, computer vision platforms as hardware, supporting neural networks for image recognition, as crucial as the neural network technologies, need to be more congruently addressed as the research subjects. In contrast, different computer vision platforms are deterministic to leverage the performance of different neural networks for recognition. In this paper, three different computer vision platforms – Jetson Nano(with 4GB), a standalone laptop(with RTX 3000s, using CUDA), and Google Colab (web-based, using GPU) are explored and four prominent neural network architectures (including AlexNet, VGG(16/19), GoogleNet, and ResNet(18/34/50)), are investigated. In the context of pairwise usage between different computer vision platforms and distinctive neural networks, with the merits of recognition accuracy and time efficiency, the performances are evaluated. In the case study using public imageNets, our findings provide a nuanced perspective on optimizing image recognition tasks across Edge-AI platforms, offering guidance on selecting appropriate neural network structures to maximize performance under hardware constraints.

Keywords: alexNet, VGG, googleNet, resNet, Jetson nano, CUDA, COCO-NET, cifar10, imageNet large scale visual recognition challenge (ILSVRC), google colab

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Authors: M. Dhana Lakshmi, S. Sakthivel Murugan

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As light passes from source to observer in the water medium, it is scattered by the suspended particulate matter. This scattering effect will plague the captured images with non-uniform illumination, blurring details, halo artefacts, weak edges, etc. To overcome this, pixel normalization with an Amended Unsharp Mask (AUM) filter is proposed to enhance the degraded image. To validate the robustness of the proposed technique irrespective of atmospheric light, the considered datasets are collected on dual locations. For those images, the maxima and minima pixel intensity value is computed and normalized; then the AUM filter is applied to strengthen the blurred edges. Finally, the enhanced image is obtained with good illumination and contrast. Thus, the proposed technique removes the effect of scattering called de-hazing and restores the perceptual information with enhanced edge detail. Both qualitative and quantitative analyses are done on considering the standard non-reference metric called underwater image sharpness measure (UISM), and underwater image quality measure (UIQM) is used to measure color, sharpness, and contrast for both of the location images. It is observed that the proposed technique has shown overwhelming performance compared to other deep-based enhancement networks and traditional techniques in an adaptive manner.

Keywords: underwater drone imagery, pixel normalization, thresholding, masking, unsharp mask filter

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Authors: Fatemeh Abdollahi, Munn-Sann Lye, Jamshid Yazdani Charati, Mehran Zarghami

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Fathers are at risk of depression during the postpartum period. Some studies have been reported maternal depression is the key predictor of paternal postpartum depression (PPD). This study aimed to estimate the prevalence and predictors of parental PPD and its association with maternal PPD. In a cross-sectional study, via a stratified random and convenience sampling method, participants referring to health centers during 2-8 weeks postpartum were recruited from March to October 2017. Paternal PPD and its relation to maternal PPD and other related factors were assessed using multiple logistic regression. Participants were 591 literate couples who referred to Mazandaran province primary health centers during to study period. Couples were screened for depression using Edinburgh Postnatal Depression Scale (EPDS). Fathers provided information on socio-demographic characteristics, life events, neonatal stressor, perceived stress (Perceived Stress Scale), social support (Multidimensional Scale of Perceived Social Support), and general health status using General Health Questionnaire (GHQ) as well. Data on mothers ‘demographic characteristics and obstetrics factors was also gathered. Overall, 93 fathers (15.7%) and 188 mothers (31.8%) reported depressive symptoms above the cut-off EPDS score of 12. In the multiple logistic regression model, older age [OR=1.20, (95%CI: 1.05- 1.36)], maternal depressive symptoms [OR=1.15, (95%CI: 1.04-1.27)], higher GHQ scores [OR=1.21, (95%CI: 1.11-1.33)] and increased recent life events [OR=1.42, (95%CI: 1.01-1.2.00)] were related to paternal PPD. A significant inverse association was found between number of children and paternal PPD [OR=0.20, (95%CI: 0.07-0.53)]. Depressive symptoms, especially in first-time fathers following the birth of a child, are not uncommon. Maternal depressive symptoms and paternal well-being were strong predictors of parental PPD. Creating opportunities for men to access special health care services, parental education to help adapting to parenthood, screening programs, and psychiatric/psychosocial interventions to decrease the suffering of depression for both depressed parents are recommended.

Keywords: depression, men, postpartum, risk factors, women

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Authors: Pallavi Bhogaram, Xiaolong Wu, Min He, Onyedikachi Okenwa

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A transportation network is a realization of a spatial network, describing a structure which permits either vehicular movement or flow of some commodity. Examples include road networks, railways, air routes, pipelines, and many more. The transportation network plays a vital role in maintaining the vigor of the nation’s economy. Hence, ensuring the network stays resilient all the time, especially in the face of challenges such as heavy traffic loads and large scale natural disasters, is of utmost importance. In this paper, we used the Neo4j application to develop the graph. Neo4j is the world's leading open-source, NoSQL, a native graph database that implements an ACID-compliant transactional backend to applications. The Southern California network model is developed using the Neo4j application and obtained the most critical and optimal nodes and paths in the network using centrality algorithms. The edge betweenness centrality algorithm calculates the critical or optimal paths using Yen's k-shortest paths algorithm, and the node betweenness centrality algorithm calculates the amount of influence a node has over the network. The preliminary study results confirm that the Neo4j application can be a suitable tool to study the important nodes and the critical paths for the major congested metropolitan area.

Keywords: critical path, transportation network, connectivity reliability, network model, Neo4j application, edge betweenness centrality index

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Authors: Marco F. Benaglia, Mei H. Chen, Kune M. Tsai, Chia H. Hung

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As societal and family structures, consumer dietary habits, and awareness about food safety and quality continue to evolve in most developed countries, the demand for refrigerated and frozen foods has been growing, and the issues related to their preservation have gained increasing attention. A well-established cold chain logistics system is essential to avoid any temperature abuse; therefore, assessing potential disruptions in the operational processes of cold chain logistics centers becomes pivotal. This study preliminarily employs HACCP to find disruption factors in cold chain logistics centers that may cause temperature abuse. Then, concept mapping is applied: selected experts engage in brainstorming sessions to identify any further factors. The panel consists of ten experts, including four from logistics and home delivery, two from retail distribution, one from the food industry, two from low-temperature logistics centers, and one from the freight industry. Disruptions include equipment-related aspects, human factors, management aspects, and process-related considerations. The areas of observation encompass freezer rooms, refrigerated storage areas, loading docks, sorting areas, and vehicle parking zones. The experts also categorize the disruption factors based on perceived similarities and build a similarity matrix. Each factor is evaluated for its impact, frequency, and investment importance. Next, multiple scale analysis, cluster analysis, and other methods are used to analyze these factors. Simultaneously, key disruption factors are identified based on their impact and frequency, and, subsequently, the factors that companies prioritize and are willing to invest in are determined by assessing investors’ risk aversion behavior. Finally, Cumulative Prospect Theory (CPT) is applied to verify the risk patterns. 66 disruption factors are found and categorized into six clusters: (1) "Inappropriate Use and Maintenance of Hardware and Software Facilities", (2) "Inadequate Management and Operational Negligence", (3) "Product Characteristics Affecting Quality and Inappropriate Packaging", (4) "Poor Control of Operation Timing and Missing Distribution Processing", (5) "Inadequate Planning for Peak Periods and Poor Process Planning", and (6) "Insufficient Cold Chain Awareness and Inadequate Training of Personnel". This study also identifies five critical factors in the operational processes of cold chain logistics centers: "Lack of Personnel’s Awareness Regarding Cold Chain Quality", "Personnel Not Following Standard Operating Procedures", "Personnel’s Operational Negligence", "Management’s Inadequacy", and "Lack of Personnel’s Knowledge About Cold Chain". The findings show that cold chain operators prioritize prevention and improvement efforts in the "Inappropriate Use and Maintenance of Hardware and Software Facilities" cluster, particularly focusing on the factors of "Temperature Setting Errors" and "Management’s Inadequacy". However, through the application of CPT theory, this study reveals that companies are not usually willing to invest in the improvement of factors related to the "Inappropriate Use and Maintenance of Hardware and Software Facilities" cluster due to its low occurrence likelihood, but they acknowledge the severity of the consequences if it does occur. Hence, the main implication is that the key disruption factors in cold chain logistics centers’ processes are associated with personnel issues; therefore, comprehensive training, periodic audits, and the establishment of reasonable incentives and penalties for both new employees and managers may significantly reduce disruption issues.

Keywords: concept mapping, cold chain, HACCP, cumulative prospect theory

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Authors: L. R. Shobin, S. Manivannan

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One dimensional silver nanowires and nanoparticles gained more interest in developing transparent conducting films, catalysis, biological and chemical sensors. Silver nanostructures can be synthesized by varying reaction conditions such as the precursor concentration, molar ratio of the surfactant, injection speed of silver ions, etc. in the polyol process. However, the reaction proceeds for greater than 2 hours for the formation of silver nanowires. The introduction of etchant in the medium promotes the growth of silver nanowires from silver nanoparticles along the [100] direction. Rapid growth of silver nanowires is accomplished using the Cl- ions from NaCl and polyvinyl pyrrolidone (PVP) as surfactant. The role of Cl- ion was investigated in the growth of the nanostructured silver. Silver nanoparticles (<100 nm) were harvested from glycerol medium in the absence of Cl- ions. Trace amount of Cl- ions (2.5 mM -NaCl) produced the edge joined nanowires of length upto 2 μm and width ranging from 40 to 65 nm. Formation and rapid growth (within 25 minutes) of long, uniform silver nanowires (upto 5 μm) with good yield were realized in the presence of 5 mM NaCl at 200ºC. The growth of nanostructures was monitored by UV-vis-NIR spectroscopy. Scanning and transmission electron microscopes reveal the morphology of the silver nano harvests. The role of temperature in the reduction of silver ions, growth mechanism for nanoparticles, edge joined and straight nanowires will be discussed.

Keywords: silver nanowires, glycerol mediated polyol process, scanning electron microscopy, UV-Vis- NIR spectroscopy, transmission electron microscopy

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Authors: Yosra M. Badiei, Evelyn Ortiz, Marisa Portenti, David Szalda

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Water-oxidation half-reaction is a critical reaction that can be driven by a sustainable energy source (e.g., solar or wind) and be coupled with a chemical fuel making reaction which stores the released electrons and protons from water (e.g., H₂ or methanol). The use of molecular water-oxidation catalysts (WOC) allow the rationale design of redox active metal centers and provides a better understanding of their structure-activity-relationship. Herein, the structure of a Ru(III) complex bearing a doubly deprotonated N,N'-bis(aryl)pyridine-2,6-dicarboxamide ligand which contains a water molecule in its primary coordination sphere was elucidated by single-crystal X-ray diffraction. Further spectroscopic experimental data and pH-dependent electrochemical studies reveal its water-oxidation reactivity. Emphasis on mechanistic details for O₂ formation of this complex will be addressed.

Keywords: water-oxidation, catalysis, ruthenium, artificial photosynthesis

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Authors: Moleseng Claude Moshobane

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Alien species cause considerable negative impacts on biodiversity, economy and public health. Impacts of alien species on public health have received a degree of attention worldwide, largely in developed countries, but scarce in developing countries. Here, we provide a review of human exposures and poisonings cases from native and alien plant species reported to poison information centers. A retrospective review of the Tygerberg Poison Information Centre (TPIC) and Poisons Information Centre (PIC) at Red Cross War Memorial Children's Hospital (RCWMCH) was conducted over approximately 2-year period (1 June 2015 through to 06 March 2017). Combined, TPIC and PIC handled 626 cases during the 2-year period. Toxicity cases were more abundant in Gauteng (47.1%), followed by Western Cape (29.4%). The primary mechanism of injury was ingestion (96.7%), and all cases were predominantly accidental. Most reported cases involved infants (20.6%), with few fully-grown adults related cases (5.8%). Adults presented minor to moderate toxicity, while infants none to minor toxicity. We conclude that reported toxicity cases on human health are biased towards few alien species and that several cases relate to unknown species of mushrooms. Public awareness is essential to reducing the poisoning incidences.

Keywords: alien species, poisoning, invasive species, public health

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Authors: Jehnming Lin

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The effects of the contact ball-lens on the soda lime glass in laser thermal cleavage with a cw Nd-YAG laser were investigated in this study. A contact ball-lens was adopted to generate a bending force on the crack formation of the soda-lime glass in the laser cutting process. The Nd-YAG laser beam (wavelength of 1064 nm) was focused through the ball-lens and transmitted to the soda-lime glass, which was coated with a carbon film on the surface with a bending force from a ball-lens to generate a tensile stress state on the surface cracking. The fracture was controlled by the contact ball-lens and a straight cutting was tested to demonstrate the feasibility. Experimental observations on the crack propagation from the leading edge, main section and trailing edge of the glass sheet were compared with various mechanical and thermal loadings. Further analyses on the stress under various laser powers and contact ball loadings were made to characterize the innovative technology. The results show that the distributions of the side crack at the leading and trailing edges are mainly dependent on the boundary condition, contact force, cutting speed and laser power. With the increase of the mechanical and thermal loadings, the region of the side cracks might be dramatically reduced with proper selection of the geometrical constraints. Therefore, the application of the contact ball-lens is a possible way to control the fracture in laser cleavage with improved cutting qualities.

Keywords: laser cleavage, stress analysis, crack visualization, laser

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Authors: Salim Çalışkan, Hakan Akyüz

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Digital image correlation has been accustomed as a versatile and efficient method for measuring displacements on the article surfaces by comparing reference subsets in undeformed images with the define target subset in the distorted image. The theoretical model points out that the accuracy of the digital image correlation displacement data can be exactly anticipated based on the divergence of the image noise and the sum of the squares of the subset intensity gradients. The digital image correlation procedure locates each subset of the original image in the distorted image. The software then determines the displacement values of the centers of the subassemblies, providing the complete displacement measures. In this paper, the effect of the speckle distribution and its effect on displacements measured out plane displacement data as a function of the size of the subset was investigated. Nine groups of speckle patterns were used in this study: samples are sprayed randomly by pre-manufactured patterns of three different hole diameters, each with three coverage ratios, on a computer numerical control punch press. The resulting displacement values, referenced at the center of the subset, are evaluated based on the average of the displacements of the pixel’s interior the subset.

Keywords: digital image correlation, speckle pattern, experimental mechanics, tensile test, aluminum alloy

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Authors: Kathleen Cravero, Amanda Nace, Samantha Ski

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The Violence Against Children Surveys (VACS) is nationally representative surveys of male and female youth ages 13-24, designed to measure the burden of sexual, physical, and emotional violence experienced in childhood and adolescence. As of 2019, 24 countries implemented or are in the process of implementing a VACS, covering over ten percent of the world’s child population. Since the first article using VACS data from Swaziland was published in 2009, several peer-reviewed articles have been published on the VACS. However, no publications to date have analyzed the breadth of the work and analyzed how the data are represented in the peer-reviewed literature. In this study, we conducted a literature review of all peer-reviewed research that used VACS data or discussed the implementation and methodology of the VACS. The literature review revealed several important findings. Between 2009 and July 2019, thirty-five peer-reviewed articles using VACS data from 12 countries have been published. Twenty of the studies focus on one country, while 15 of the studies focus on two or more countries. Some countries are featured in the literature more than others, for example Kenya (N=14), Malawi (N=12), and Tanzania (N=12). A review of the research by gender demonstrates that research on violence against boys is under-represented. Only two studies specifically focused on boys/young men, while 11 studies focused only on violence against girls. This is despite research which suggests boys and girls experience similar rates of violence. A review of the publications by type of violence revealed significant differences in the types of violence being featured in the literature. Thirteen publications specifically focused on sexual violence, while three studies focused on physical violence, and only one study focused on emotional violence. Almost 70% of the peer-reviewed articles (24 of the 35) were first-authored by someone at the U.S. Centers for Disease Control and Prevention. There were very few first authors from VACS countries, which raises questions about who is leveraging the data and the extent to which capacities for data liberation are being developed within VACS countries. The VACS provide an unprecedented amount of information on the prevalence and past-year incidence of violence against children. Through a review of the peer-reviewed literature on the VACS we can begin to identify trends and gaps in how the data is being used as well as identify areas for further research.

Keywords: data to action, global health, implementation science, violence against children surveys

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Authors: Faisal Kalota

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Big Data and analytics have gained a huge momentum in recent years. Big Data feeds into the field of Learning Analytics (LA) that may allow academic institutions to better understand the learners’ needs and proactively address them. Hence, it is important to have an understanding of Big Data and its applications. The purpose of this descriptive paper is to provide an overview of Big Data, the technologies used in Big Data, and some of the applications of Big Data in education. Additionally, it discusses some of the concerns related to Big Data and current research trends. While Big Data can provide big benefits, it is important that institutions understand their own needs, infrastructure, resources, and limitation before jumping on the Big Data bandwagon.

Keywords: big data, learning analytics, analytics, big data in education, Hadoop

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Authors: Gaurav Kumar Sinha

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In an era defined by the proliferation of data and the utilization of cloud computing environments, the efficient transfer and processing of big data workloads across multi-cloud platforms have emerged as critical challenges. This research paper embarks on a comprehensive exploration of the complexities associated with managing and optimizing big data in a multi-cloud ecosystem.The foundation of this study is rooted in the recognition that modern enterprises increasingly rely on multiple cloud providers to meet diverse business needs, enhance redundancy, and reduce vendor lock-in. As a consequence, managing data across these heterogeneous cloud environments has become intricate, necessitating innovative approaches to ensure data integrity, security, and performance.The primary objective of this research is to investigate strategies and techniques for enhancing the efficiency of data transfer and processing in multi-cloud scenarios. It recognizes that big data workloads are characterized by their sheer volume, variety, velocity, and complexity, making traditional data management solutions insufficient for harnessing the full potential of multi-cloud architectures.The study commences by elucidating the challenges posed by multi-cloud environments in the context of big data. These challenges encompass data fragmentation, latency, security concerns, and cost optimization. To address these challenges, the research explores a range of methodologies and solutions. One of the key areas of focus is data transfer optimization. The paper delves into techniques for minimizing data movement latency, optimizing bandwidth utilization, and ensuring secure data transmission between different cloud providers. It evaluates the applicability of dedicated data transfer protocols, intelligent data routing algorithms, and edge computing approaches in reducing transfer times.Furthermore, the study examines strategies for efficient data processing across multi-cloud environments. It acknowledges that big data processing requires distributed and parallel computing capabilities that span across cloud boundaries. The research investigates containerization and orchestration technologies, serverless computing models, and interoperability standards that facilitate seamless data processing workflows.Security and data governance are paramount concerns in multi-cloud environments. The paper explores methods for ensuring data security, access control, and compliance with regulatory frameworks. It considers encryption techniques, identity and access management, and auditing mechanisms as essential components of a robust multi-cloud data security strategy.The research also evaluates cost optimization strategies, recognizing that the dynamic nature of multi-cloud pricing models can impact the overall cost of data transfer and processing. It examines approaches for workload placement, resource allocation, and predictive cost modeling to minimize operational expenses while maximizing performance.Moreover, this study provides insights into real-world case studies and best practices adopted by organizations that have successfully navigated the challenges of multi-cloud big data management. It presents a comparative analysis of various multi-cloud management platforms and tools available in the market.

Keywords: multi-cloud environments, big data workloads, data transfer optimization, data processing strategies

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Authors: Sangita Pokhrel, Nalinda Somasiri, Rebecca Jeyavadhanam, Swathi Ganesan

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Tourism is a booming industry with huge future potential for global wealth and employment. There are countless data generated over social media sites every day, creating numerous opportunities to bring more insights to decision-makers. The integration of Big Data Technology into the tourism industry will allow companies to conclude where their customers have been and what they like. This information can then be used by businesses, such as those in charge of managing visitor centers or hotels, etc., and the tourist can get a clear idea of places before visiting. The technical perspective of natural language is processed by analysing the sentiment features of online reviews from tourists, and we then supply an enhanced long short-term memory (LSTM) framework for sentiment feature extraction of travel reviews. We have constructed a web review database using a crawler and web scraping technique for experimental validation to evaluate the effectiveness of our methodology. The text form of sentences was first classified through Vader and Roberta model to get the polarity of the reviews. In this paper, we have conducted study methods for feature extraction, such as Count Vectorization and TFIDF Vectorization, and implemented Convolutional Neural Network (CNN) classifier algorithm for the sentiment analysis to decide the tourist’s attitude towards the destinations is positive, negative, or simply neutral based on the review text that they posted online. The results demonstrated that from the CNN algorithm, after pre-processing and cleaning the dataset, we received an accuracy of 96.12% for the positive and negative sentiment analysis.

Keywords: counter vectorization, convolutional neural network, crawler, data technology, long short-term memory, web scraping, sentiment analysis

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Authors: Ayşe Duygu Kaçar

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Industrial regions and buildings that have stopped their primary functions are in the interest of the discipline of architecture in the last decades. The renewal of these spaces of production for different functions is a common aspect for contemporary world countries. Totally different functions can be added to the existing as well, which can help improving the social, cultural and aesthetic character of these beings and sustaining their uniqueness. Therefore, these sites linking the past and future can be used as museums, exhibition centers, art ateliers, city parks, recreational centers, botanic gardens, sculpture parks, theatres, etc. in order to continue their place in the collective memory of the cities. The present paper depicts a way of shedding light on the Cotton Textile Industry (İplik ve Dokuma Fabrikası A.Ş), a local industrial site in Antalya, the most popular tourism center of Turkey, as a part of International Architecture Biennale, 2011 and on Lohberg coal mine, a local industrial site in the Ruhr region of Germany. As a transparent, fragile, temporary and economical material, the string was used as a design element in both experiential architecture works with architecture students and the outcomes will be discussed and presented through the theme 'rejecting / reversing architecture'.

Keywords: industrial sites, the Cotton Textile Industry Antalya, Lohberg coal mine, architectural design, identity

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Authors: Samuele Viaro, Pierre Ricco

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Görtler instabilities generate in boundary layers from an unbalance between pressure and centrifugal forces caused by concave surfaces. Their spatial streamwise evolution influences transition to turbulence. It is therefore important to understand even the early stages where perturbations, still small, grow linearly and could be controlled more easily. This work presents a rigorous theoretical framework for compressible flows using the linearized unsteady boundary region equations, where only the streamwise pressure gradient and streamwise diffusion terms are neglected from the full governing equations of fluid motion. Boundary and initial conditions are imposed through an asymptotic analysis in order to account for the interaction of the boundary layer with free-stream turbulence. The resulting parabolic system is discretize with a second-order finite difference scheme. Realistic flow parameters are chosen from wind tunnel studies performed at supersonic and subsonic conditions. The Mach number ranges from 0.5 to 8, with two different radii of curvature, 5 m and 10 m, frequencies up to 2000 Hz, and vortex spanwise wavelengths from 5 mm to 20 mm. The evolution of the perturbation flow is shown through velocity, temperature, pressure profiles relatively close to the leading edge, where non-linear effects can still be neglected, and growth rate. Results show that a global stabilizing effect exists with the increase of Mach number, frequency, spanwise wavenumber and radius of curvature. In particular, at high Mach numbers curvature effects are less pronounced and thermal streaks become stronger than velocity streaks. This increase of temperature perturbations saturates at approximately Mach 4 flows, and is limited in the early stage of growth, near the leading edge. In general, Görtler vortices evolve closer to the surface with respect to a flat plate scenario but their location shifts toward the edge of the boundary layer as the Mach number increases. In fact, a jet-like behavior appears for steady vortices having small spanwise wavelengths (less than 10 mm) at Mach 8, creating a region of unperturbed flow close to the wall. A similar response is also found at the highest frequency considered for a Mach 3 flow. Larger vortices are found to have a higher growth rate but are less influenced by the Mach number. An eigenvalue approach is also employed to study the amplification of the perturbations sufficiently downstream from the leading edge. These eigenvalue results are compared with the ones obtained through the initial value approach with inhomogeneous free-stream boundary conditions. All of the parameters here studied have a significant influence on the evolution of the instabilities for the Görtler problem which is indeed highly dependent on initial conditions.

Keywords: compressible boundary layers, Görtler instabilities, receptivity, turbulence transition

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